Compare commits
180 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
8f3ced7639 | ||
|
|
e0b9a2735f | ||
|
|
895dfedf81 | ||
|
|
69dd4fc638 | ||
|
|
fd20b5377d | ||
|
|
e78c3e1eb7 | ||
|
|
0fbbc0e612 | ||
|
|
fb90f118c9 | ||
|
|
d7558406c8 | ||
|
|
00dd3dbd2c | ||
|
|
cb2062debd | ||
|
|
4b86c78df0 | ||
|
|
17d57cb578 | ||
|
|
284b26a9bd | ||
|
|
0bc087954e | ||
|
|
f5dd997ca0 | ||
|
|
33616a44b0 | ||
|
|
9bd6b46160 | ||
|
|
eb995b86ea | ||
|
|
59a3912f68 | ||
|
|
1be6cccbd4 | ||
|
|
a658beb31e | ||
|
|
8cf6e073af | ||
|
|
2f39ac7d83 | ||
|
|
ea25e76faa | ||
|
|
b7a21ce4be | ||
|
|
b9d3d99917 | ||
|
|
64125668db | ||
|
|
06228a8de8 | ||
|
|
813412afb2 | ||
|
|
e0d29e1da7 | ||
|
|
41b7ff58cf | ||
|
|
6d181cc452 | ||
|
|
b8c8460c7a | ||
|
|
9fe018390e | ||
|
|
427f2a70fe | ||
|
|
32f49f1f92 | ||
|
|
b3c2303111 | ||
|
|
fc008fe906 | ||
|
|
bbcf5d71a2 | ||
|
|
482d86a44a | ||
|
|
6eab53f619 | ||
|
|
f617d25af9 | ||
|
|
a8e104f696 | ||
|
|
d1ff914e5a | ||
|
|
574d685647 | ||
|
|
fbd12c7eb1 | ||
|
|
49562c712f | ||
|
|
73fa0461ed | ||
|
|
6cf537b26f | ||
|
|
a374ce9b6e | ||
|
|
ad34429014 | ||
|
|
cc1c305432 | ||
|
|
caaa506c56 | ||
|
|
29e426c2b6 | ||
|
|
368cfe0f5d | ||
|
|
06c05c4274 | ||
|
|
cde4743ca7 | ||
|
|
58e89872c1 | ||
|
|
85eb1fca9a | ||
|
|
cc18e47cd6 | ||
|
|
15066ae5e1 | ||
|
|
1dc118304f | ||
|
|
de57cedc5a | ||
|
|
6273671eb7 | ||
|
|
cece811cce | ||
|
|
0c9c8c45e5 | ||
|
|
7e64bd0265 | ||
|
|
48a7ba77ef | ||
|
|
b6de0e7222 | ||
|
|
7732a27c1b | ||
|
|
adb6afc4f1 | ||
|
|
29588095ed | ||
|
|
e7043bfc7e | ||
|
|
a44d7b2f92 | ||
|
|
18b99338fc | ||
|
|
f129ab1a09 | ||
|
|
f86926bf7a | ||
|
|
68c046fc7b | ||
|
|
3e52816f6e | ||
|
|
c598a8d260 | ||
|
|
e63bfc9127 | ||
|
|
e316f12394 | ||
|
|
306298a16f | ||
|
|
e8160f33d5 | ||
|
|
ce3cb8e1a3 | ||
|
|
2d644d7879 | ||
|
|
b80e274d4f | ||
|
|
9a355c9be5 | ||
|
|
303b95ab50 | ||
|
|
d826d267f4 | ||
|
|
eb55311052 | ||
|
|
27d18fa2e8 | ||
|
|
bb0c671e7c | ||
|
|
c8dc343c13 | ||
|
|
b6815d22de | ||
|
|
459f60603b | ||
|
|
1aaaa20c61 | ||
|
|
07b6572bf9 | ||
|
|
a675aca7e5 | ||
|
|
87db3fe379 | ||
|
|
74321d1727 | ||
|
|
9fd50a302e | ||
|
|
fc0b2f3fa4 | ||
|
|
c4a2d6eef4 | ||
|
|
c2b60e4e48 | ||
|
|
ca9e55fda6 | ||
|
|
b698641c90 | ||
|
|
e5c709ee29 | ||
|
|
ca787d0a25 | ||
|
|
b1a1277eca | ||
|
|
30d7fb042b | ||
|
|
d1bb70fbb7 | ||
|
|
0946bfc2fb | ||
|
|
f34be8e3ff | ||
|
|
e1d1e28bb8 | ||
|
|
5ea9f04b10 | ||
|
|
2529ba124d | ||
|
|
472f78cc53 | ||
|
|
0c26d42561 | ||
|
|
4b94f50754 | ||
|
|
5bdc60b137 | ||
|
|
3837c32b36 | ||
|
|
0e298edcb2 | ||
|
|
7a753bfa3f | ||
|
|
8e2554b110 | ||
|
|
bfa58b4692 | ||
|
|
e3375bc45e | ||
|
|
ac8b500ba2 | ||
|
|
2557a36feb | ||
|
|
55cb3bdaff | ||
|
|
10bb627fc2 | ||
|
|
3d3733c0fb | ||
|
|
1303ccf843 | ||
|
|
3b5f3fcf42 | ||
|
|
e2de241c2b | ||
|
|
68e2a9170a | ||
|
|
d395f704b3 | ||
|
|
4d1fc7e05a | ||
|
|
e3a562d3c9 | ||
|
|
4fdd60d146 | ||
|
|
abbb50e209 | ||
|
|
0e1cc288a6 | ||
|
|
3b826535c7 | ||
|
|
59da486e30 | ||
|
|
f42d7bb3a2 | ||
|
|
87bd0d7792 | ||
|
|
8ca9258e70 | ||
|
|
72105539fc | ||
|
|
589e8a9293 | ||
|
|
dd27a382f7 | ||
|
|
62a8aee38c | ||
|
|
7e7c27416b | ||
|
|
26f2f88c67 | ||
|
|
c08c129860 | ||
|
|
bae10389ae | ||
|
|
4301d7cead | ||
|
|
d49f1d0d6c | ||
|
|
264c3c8374 | ||
|
|
8a1f67edfc | ||
|
|
5f434f2fa5 | ||
|
|
e37f8ae878 | ||
|
|
b4e95209f6 | ||
|
|
ea65c61dc8 | ||
|
|
6bf6ff1a6a | ||
|
|
d1a35e6281 | ||
|
|
fed1fa929b | ||
|
|
9e7962f5a2 | ||
|
|
3e66733413 | ||
|
|
c11a09e08a | ||
|
|
f06bab944d | ||
|
|
df63b6f5d6 | ||
|
|
1358bd8115 | ||
|
|
40cc7a808a | ||
|
|
e3a4fa1838 | ||
|
|
1d8243ecac | ||
|
|
a8c81cad2a | ||
|
|
5f95a9ba77 | ||
|
|
a9b914c9ef | ||
|
|
5436275901 |
4
.github/workflows/gh-actions.yml
vendored
4
.github/workflows/gh-actions.yml
vendored
@@ -19,7 +19,7 @@ jobs:
|
||||
run: dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
|
||||
|
||||
- name: Run Tests
|
||||
run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter TestCategory!=TravisExclude -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\)
|
||||
run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "TestCategory!=TravisExclude&TestCategory!=ResearchRegressionTests" -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\)
|
||||
|
||||
- name: Generate & Publish python stubs
|
||||
if: startsWith(github.ref, 'refs/tags/')
|
||||
@@ -28,3 +28,5 @@ jobs:
|
||||
./ci_build_stubs.sh -t -g -p
|
||||
env:
|
||||
PYPI_API_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
|
||||
ADDITIONAL_STUBS_REPOS: ${{ secrets.ADDITIONAL_STUBS_REPOS }}
|
||||
QC_GIT_TOKEN: ${{ secrets.QC_GIT_TOKEN }}
|
||||
|
||||
35
.github/workflows/research-regression-tests.yml
vendored
Normal file
35
.github/workflows/research-regression-tests.yml
vendored
Normal file
@@ -0,0 +1,35 @@
|
||||
name: Research Regression Tests
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: ['*']
|
||||
tags: ['*']
|
||||
pull_request:
|
||||
branches: [master]
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-20.04
|
||||
container:
|
||||
image: quantconnect/lean:foundation
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
|
||||
- name: install dependencies
|
||||
run: |
|
||||
pip3 install papermill clr-loader
|
||||
|
||||
- name: install kernel
|
||||
run: dotnet tool install --global Microsoft.dotnet-interactive --version 1.0.317502
|
||||
|
||||
- name: Add dotnet tools to Path
|
||||
run: echo "$HOME/.dotnet/tools" >> $GITHUB_PATH
|
||||
|
||||
- name: activate kernel for jupyter
|
||||
run: dotnet interactive jupyter install
|
||||
|
||||
- name: Build
|
||||
run: dotnet build /p:Configuration=Release /v:quiet /p:WarningLevel=1 QuantConnect.Lean.sln
|
||||
|
||||
- name: Run Tests
|
||||
run: dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter TestCategory=ResearchRegressionTests -- TestRunParameters.Parameter\(name=\"log-handler\", value=\"ConsoleErrorLogHandler\"\) TestRunParameters.Parameter\(name=\"reduced-disk-size\", value=\"true\"\)
|
||||
4
.vscode/launch.json
vendored
4
.vscode/launch.json
vendored
@@ -8,8 +8,8 @@
|
||||
marketplace.
|
||||
|
||||
Attach to Python:
|
||||
Will attempt to attach to LEAN running locally using PTVSD. Requires that the process is
|
||||
actively running and config is set: "debugging": true, "debugging-method": "PTVSD",
|
||||
Will attempt to attach to LEAN running locally using DebugPy. Requires that the process is
|
||||
actively running and config is set: "debugging": true, "debugging-method": "DebugPy",
|
||||
Requires Python extension from the marketplace. Currently only works with algorithms in
|
||||
Algorithm.Python directory. This is because we map that directory to our build directory
|
||||
that contains the py file at runtime. If using another location change "localRoot" value
|
||||
|
||||
2
.vscode/readme.md
vendored
2
.vscode/readme.md
vendored
@@ -95,7 +95,7 @@ Python algorithms require a little extra work in order to be able to debug them.
|
||||
First in order to debug a Python algorithm in VS Code we must make the following change to our configuration (Launcher\config.json) under the comment debugging configuration:
|
||||
|
||||
"debugging": true,
|
||||
"debugging-method": "PTVSD",
|
||||
"debugging-method": "DebugPy",
|
||||
|
||||
In setting this we are telling Lean to expect a debugger connection using ‘Python Tools for Visual Studio Debugger’. Once this is set Lean will stop upon initialization and await a connection to the debugger via port 5678.
|
||||
|
||||
|
||||
@@ -69,6 +69,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 3943;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -105,6 +105,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 58;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -82,6 +82,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 24;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -0,0 +1,141 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using System;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Interfaces;
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Regression algorithm reproducing GH issue #5971 where we add and remove an option in the same loop
|
||||
/// </summary>
|
||||
public class AddAndRemoveSecuritySameLoopRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private Symbol _contract;
|
||||
private bool _hasRemoved;
|
||||
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2014, 06, 06);
|
||||
SetEndDate(2014, 06, 09);
|
||||
|
||||
UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
|
||||
UniverseSettings.MinimumTimeInUniverse = TimeSpan.Zero;
|
||||
|
||||
var aapl = AddEquity("AAPL").Symbol;
|
||||
|
||||
_contract = OptionChainProvider.GetOptionContractList(aapl, Time)
|
||||
.OrderBy(symbol => symbol.ID.Symbol)
|
||||
.FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
|
||||
&& optionContract.ID.OptionStyle == OptionStyle.American);
|
||||
}
|
||||
|
||||
public override void OnData(Slice slice)
|
||||
{
|
||||
if (_hasRemoved)
|
||||
{
|
||||
throw new Exception("Expect a single call to OnData where we removed the option and underlying");
|
||||
}
|
||||
|
||||
_hasRemoved = true;
|
||||
AddOptionContract(_contract);
|
||||
|
||||
// changed my mind!
|
||||
RemoveOptionContract(_contract);
|
||||
RemoveSecurity(_contract.Underlying);
|
||||
|
||||
RemoveSecurity(AddEquity("SPY", Resolution.Daily).Symbol);
|
||||
}
|
||||
public override void OnEndOfAlgorithm()
|
||||
{
|
||||
if (!_hasRemoved)
|
||||
{
|
||||
throw new Exception("We did not remove the option contract!");
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 24;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "0"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "0%"},
|
||||
{"Drawdown", "0%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "0%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-9.486"},
|
||||
{"Tracking Error", "0.008"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$0.00"},
|
||||
{"Estimated Strategy Capacity", "$0"},
|
||||
{"Lowest Capacity Asset", ""},
|
||||
{"Fitness Score", "0"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "79228162514264337593543950335"},
|
||||
{"Portfolio Turnover", "0"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -27,7 +27,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public class AddBetaIndicatorRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private BetaIndicator _beta;
|
||||
private Beta _beta;
|
||||
private SimpleMovingAverage _sma;
|
||||
private decimal _lastSMAValue;
|
||||
|
||||
@@ -99,6 +99,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public virtual Language[] Languages { get; } = { Language.CSharp};
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 10977;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 11;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -0,0 +1,175 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using System;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Orders;
|
||||
using QuantConnect.Interfaces;
|
||||
using QuantConnect.Securities;
|
||||
using System.Collections.Generic;
|
||||
using QuantConnect.Securities.Future;
|
||||
using QuantConnect.Data.UniverseSelection;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Continuous Futures Regression algorithm. Asserting and showcasing the behavior of adding a continuous future
|
||||
/// and a future contract at the same time
|
||||
/// </summary>
|
||||
public class AddFutureContractWithContinuousRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private Symbol _currentMappedSymbol;
|
||||
private Future _continuousContract;
|
||||
private Future _futureContract;
|
||||
private bool _ended;
|
||||
|
||||
/// <summary>
|
||||
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2013, 10, 6);
|
||||
SetEndDate(2013, 10, 10);
|
||||
|
||||
_continuousContract = AddFuture(Futures.Indices.SP500EMini,
|
||||
dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
|
||||
dataMappingMode: DataMappingMode.LastTradingDay,
|
||||
contractDepthOffset: 0
|
||||
);
|
||||
|
||||
_futureContract = AddFutureContract(FutureChainProvider.GetFutureContractList(_continuousContract.Symbol, Time).First());
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
|
||||
/// </summary>
|
||||
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
|
||||
public override void OnData(Slice data)
|
||||
{
|
||||
if (_ended)
|
||||
{
|
||||
throw new Exception($"Algorithm should of ended!");
|
||||
}
|
||||
if (data.Keys.Count > 2)
|
||||
{
|
||||
throw new Exception($"Getting data for more than 2 symbols! {string.Join(",", data.Keys.Select(symbol => symbol))}");
|
||||
}
|
||||
if (UniverseManager.Count != 3)
|
||||
{
|
||||
throw new Exception($"Expecting 3 universes (chain, continuous and user defined) but have {UniverseManager.Count}");
|
||||
}
|
||||
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
Buy(_futureContract.Symbol, 1);
|
||||
Buy(_continuousContract.Mapped, 1);
|
||||
|
||||
RemoveSecurity(_futureContract.Symbol);
|
||||
RemoveSecurity(_continuousContract.Symbol);
|
||||
|
||||
_ended = true;
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnOrderEvent(OrderEvent orderEvent)
|
||||
{
|
||||
if (orderEvent.Status == OrderStatus.Filled)
|
||||
{
|
||||
Log($"{orderEvent}");
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnSecuritiesChanged(SecurityChanges changes)
|
||||
{
|
||||
Debug($"{Time}-{changes}");
|
||||
|
||||
if (changes.AddedSecurities.Any(security => security.Symbol != _continuousContract.Symbol && security.Symbol != _futureContract.Symbol)
|
||||
|| changes.RemovedSecurities.Any(security => security.Symbol != _continuousContract.Symbol && security.Symbol != _futureContract.Symbol))
|
||||
{
|
||||
throw new Exception($"We got an unexpected security changes {changes}");
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 59;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "3"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "-0.03%"},
|
||||
{"Compounding Annual Return", "-2.503%"},
|
||||
{"Drawdown", "0.000%"},
|
||||
{"Expectancy", "-1"},
|
||||
{"Net Profit", "-0.032%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "100%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-0.678"},
|
||||
{"Tracking Error", "0.243"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$7.40"},
|
||||
{"Estimated Strategy Capacity", "$2100000.00"},
|
||||
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
|
||||
{"Fitness Score", "0.419"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "-81.557"},
|
||||
{"Portfolio Turnover", "0.837"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "68775c18eb40c1bde212653faec4016e"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -160,6 +160,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 210329;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -219,6 +219,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 779544;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -114,6 +114,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 37597;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -166,6 +166,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 5797;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
175
Algorithm.CSharp/AddOptionContractTwiceRegressionAlgorithm.cs
Normal file
175
Algorithm.CSharp/AddOptionContractTwiceRegressionAlgorithm.cs
Normal file
@@ -0,0 +1,175 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using System;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Interfaces;
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Regression algorithm reproducing GH issue #6073 where we remove and re add an option and expect it to work
|
||||
/// </summary>
|
||||
public class AddOptionContractTwiceRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private Symbol _contract;
|
||||
private bool _hasRemoved;
|
||||
private bool _reAdded;
|
||||
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2014, 06, 06);
|
||||
SetEndDate(2014, 06, 09);
|
||||
|
||||
UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
|
||||
UniverseSettings.MinimumTimeInUniverse = TimeSpan.Zero;
|
||||
UniverseSettings.FillForward = false;
|
||||
|
||||
AddEquity("SPY", Resolution.Daily);
|
||||
|
||||
var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
|
||||
|
||||
_contract = OptionChainProvider.GetOptionContractList(aapl, Time)
|
||||
.OrderBy(symbol => symbol.ID.Symbol)
|
||||
.FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
|
||||
&& optionContract.ID.OptionStyle == OptionStyle.American);
|
||||
AddOptionContract(_contract);
|
||||
}
|
||||
|
||||
public override void OnData(Slice slice)
|
||||
{
|
||||
if (_hasRemoved)
|
||||
{
|
||||
if (!_reAdded && slice.ContainsKey(_contract) && slice.ContainsKey(_contract.Underlying))
|
||||
{
|
||||
throw new Exception("Getting data for removed option and underlying!");
|
||||
}
|
||||
|
||||
if (!Portfolio.Invested && _reAdded)
|
||||
{
|
||||
var option = Securities[_contract];
|
||||
var optionUnderlying = Securities[_contract.Underlying];
|
||||
if (option.IsTradable && optionUnderlying.IsTradable
|
||||
&& slice.ContainsKey(_contract) && slice.ContainsKey(_contract.Underlying))
|
||||
{
|
||||
Buy(_contract, 1);
|
||||
}
|
||||
}
|
||||
|
||||
if (!Securities[_contract].IsTradable
|
||||
&& !Securities[_contract.Underlying].IsTradable
|
||||
&& !_reAdded)
|
||||
{
|
||||
// ha changed my mind!
|
||||
AddOptionContract(_contract);
|
||||
_reAdded = true;
|
||||
}
|
||||
}
|
||||
|
||||
if (slice.ContainsKey(_contract) && slice.ContainsKey(_contract.Underlying))
|
||||
{
|
||||
if (!_hasRemoved)
|
||||
{
|
||||
RemoveOptionContract(_contract);
|
||||
RemoveSecurity(_contract.Underlying);
|
||||
_hasRemoved = true;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnEndOfAlgorithm()
|
||||
{
|
||||
if (!_hasRemoved)
|
||||
{
|
||||
throw new Exception("We did not remove the option contract!");
|
||||
}
|
||||
if (!_reAdded)
|
||||
{
|
||||
throw new Exception("We did not re add the option contract!");
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 4677;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "2"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "-0.05%"},
|
||||
{"Compounding Annual Return", "-4.548%"},
|
||||
{"Drawdown", "0.100%"},
|
||||
{"Expectancy", "-1"},
|
||||
{"Net Profit", "-0.051%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "100%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-9.486"},
|
||||
{"Tracking Error", "0.008"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$2.00"},
|
||||
{"Estimated Strategy Capacity", "$30000.00"},
|
||||
{"Lowest Capacity Asset", "AAPL VXBK4Q9ZIFD2|AAPL R735QTJ8XC9X"},
|
||||
{"Fitness Score", "0"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "-89.181"},
|
||||
{"Portfolio Turnover", "0"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "546b6182e1df2d222178454d8f311566"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -40,8 +40,8 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
private int _expectedContractIndex;
|
||||
private readonly List<Symbol> _expectedContracts = new List<Symbol>
|
||||
{
|
||||
SymbolRepresentation.ParseOptionTickerOSI("GOOG 151224P00750000"),
|
||||
SymbolRepresentation.ParseOptionTickerOSI("GOOG 151224P00747500"),
|
||||
SymbolRepresentation.ParseOptionTickerOSI("GOOG 151224P00750000"),
|
||||
SymbolRepresentation.ParseOptionTickerOSI("GOOG 151224P00752500")
|
||||
};
|
||||
|
||||
@@ -109,6 +109,11 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
var googOptionChain = AddOption(UnderlyingTicker);
|
||||
googOptionChain.SetFilter(u =>
|
||||
{
|
||||
// we added the universe at 10, the universe selection data should not be from before
|
||||
if (u.Underlying.EndTime.Hour < 10)
|
||||
{
|
||||
throw new Exception($"Unexpected underlying data point {u.Underlying.EndTime} {u.Underlying}");
|
||||
}
|
||||
// find first put above market price
|
||||
return u.IncludeWeeklys()
|
||||
.Strikes(+1, +1)
|
||||
@@ -205,6 +210,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 200618;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
@@ -231,7 +246,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$6.00"},
|
||||
{"Estimated Strategy Capacity", "$2000.00"},
|
||||
{"Lowest Capacity Asset", "GOOCV 305RBQ2BZBZT2|GOOCV VP83T1ZUHROL"},
|
||||
{"Lowest Capacity Asset", "GOOCV 305RBR0BSWIX2|GOOCV VP83T1ZUHROL"},
|
||||
{"Fitness Score", "0"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
@@ -251,7 +266,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "1e7b3e90918777b9dbf46353a96f3329"}
|
||||
{"OrderListHash", "550a99c482106defd8ba15f48183768e"}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
142
Algorithm.CSharp/AddRemoveSecurityCacheRegressionAlgorithm.cs
Normal file
142
Algorithm.CSharp/AddRemoveSecurityCacheRegressionAlgorithm.cs
Normal file
@@ -0,0 +1,142 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using System;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Interfaces;
|
||||
using System.Collections.Generic;
|
||||
using QuantConnect.Orders;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Regression algorithm making sure the securities cache is reset correctly once it's removed from the algorithm
|
||||
/// </summary>
|
||||
public class AddRemoveSecurityCacheRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
/// <summary>
|
||||
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2013, 10, 07); //Set Start Date
|
||||
SetEndDate(2013, 10, 11); //Set End Date
|
||||
SetCash(100000); //Set Strategy Cash
|
||||
|
||||
AddEquity("SPY", Resolution.Minute, extendedMarketHours: true);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
|
||||
/// </summary>
|
||||
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
|
||||
public override void OnData(Slice data)
|
||||
{
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
SetHoldings("SPY", 1);
|
||||
}
|
||||
|
||||
if (Time.Day == 11)
|
||||
{
|
||||
return;
|
||||
}
|
||||
if (!ActiveSecurities.ContainsKey("AIG"))
|
||||
{
|
||||
var aig = AddEquity("AIG", Resolution.Minute);
|
||||
|
||||
var ticket = MarketOrder("AIG", 1);
|
||||
|
||||
if (ticket.Status != OrderStatus.Invalid)
|
||||
{
|
||||
throw new Exception("Expected order to always be invalid because there is no data yet!");
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
RemoveSecurity("AIG");
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 11202;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "19"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0.00%"},
|
||||
{"Compounding Annual Return", "271.720%"},
|
||||
{"Drawdown", "2.500%"},
|
||||
{"Expectancy", "-1"},
|
||||
{"Net Profit", "1.754%"},
|
||||
{"Sharpe Ratio", "11.994"},
|
||||
{"Probabilistic Sharpe Ratio", "74.160%"},
|
||||
{"Loss Rate", "100%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0.618"},
|
||||
{"Beta", "0.81"},
|
||||
{"Annual Standard Deviation", "0.185"},
|
||||
{"Annual Variance", "0.034"},
|
||||
{"Information Ratio", "3.961"},
|
||||
{"Tracking Error", "0.061"},
|
||||
{"Treynor Ratio", "2.746"},
|
||||
{"Total Fees", "$21.45"},
|
||||
{"Estimated Strategy Capacity", "$830000.00"},
|
||||
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
|
||||
{"Fitness Score", "0.204"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "43.135"},
|
||||
{"Return Over Maximum Drawdown", "261.238"},
|
||||
{"Portfolio Turnover", "0.204"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "6ee62edf1ac883882b0fcef8cb3e9bae"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -106,6 +106,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 7063;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -59,6 +59,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 3943;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -0,0 +1,160 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using System;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Interfaces;
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Regression algorithm reproducing issue where underlying option contract would be removed with the first call
|
||||
/// too RemoveOptionContract
|
||||
/// </summary>
|
||||
public class AddTwoAndRemoveOneOptionContractRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private Symbol _contract1;
|
||||
private Symbol _contract2;
|
||||
private bool _hasRemoved;
|
||||
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2014, 06, 06);
|
||||
SetEndDate(2014, 06, 06);
|
||||
|
||||
UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
|
||||
UniverseSettings.MinimumTimeInUniverse = TimeSpan.Zero;
|
||||
|
||||
var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
|
||||
|
||||
var contracts = OptionChainProvider.GetOptionContractList(aapl, Time)
|
||||
.OrderBy(symbol => symbol.ID.Symbol)
|
||||
.Where(optionContract => optionContract.ID.OptionRight == OptionRight.Call
|
||||
&& optionContract.ID.OptionStyle == OptionStyle.American)
|
||||
.Take(2)
|
||||
.ToList();
|
||||
|
||||
_contract1 = contracts[0];
|
||||
_contract2 = contracts[1];
|
||||
AddOptionContract(_contract1);
|
||||
AddOptionContract(_contract2);
|
||||
}
|
||||
|
||||
public override void OnData(Slice slice)
|
||||
{
|
||||
if (slice.HasData)
|
||||
{
|
||||
if (!_hasRemoved)
|
||||
{
|
||||
RemoveOptionContract(_contract1);
|
||||
_hasRemoved = true;
|
||||
}
|
||||
else
|
||||
{
|
||||
var subscriptions =
|
||||
SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs("AAPL");
|
||||
if (subscriptions.Count == 0)
|
||||
{
|
||||
throw new Exception("No configuration for underlying was found!");
|
||||
}
|
||||
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
Buy(_contract2, 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnEndOfAlgorithm()
|
||||
{
|
||||
if (!_hasRemoved)
|
||||
{
|
||||
throw new Exception("Expect a single call to OnData where we removed the option and underlying");
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 1578;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "2"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "0%"},
|
||||
{"Drawdown", "0%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "0%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "0"},
|
||||
{"Tracking Error", "0"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$2.00"},
|
||||
{"Estimated Strategy Capacity", "$230000.00"},
|
||||
{"Lowest Capacity Asset", "AAPL VXBK4QQIRLZA|AAPL R735QTJ8XC9X"},
|
||||
{"Fitness Score", "0"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "0"},
|
||||
{"Return Over Maximum Drawdown", "0"},
|
||||
{"Portfolio Turnover", "0"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "228194dcc6fd8689a67f383577ee2d85"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -78,6 +78,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 53;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -89,6 +89,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 234018;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -153,6 +153,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 795;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -186,6 +186,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 35410;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -65,6 +65,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public virtual long DataPoints => 890;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public virtual int AlgorithmHistoryDataPoints => 12;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -41,6 +41,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 6214;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 61;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
@@ -65,8 +75,8 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Information Ratio", "-0.859"},
|
||||
{"Tracking Error", "0.004"},
|
||||
{"Treynor Ratio", "-0.832"},
|
||||
{"Total Fees", "$2.89"},
|
||||
{"Estimated Strategy Capacity", "$8900000000.00"},
|
||||
{"Total Fees", "€2.89"},
|
||||
{"Estimated Strategy Capacity", "€8900000000.00"},
|
||||
{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
|
||||
{"Fitness Score", "0.506"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
|
||||
@@ -78,6 +78,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 893;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 2;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -92,6 +92,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 2313;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 1;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -1,162 +0,0 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
using System;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Indicators;
|
||||
using QuantConnect.Orders.Fees;
|
||||
using QuantConnect.Data.Custom;
|
||||
using System.Collections.Generic;
|
||||
using QuantConnect.Algorithm.Framework.Alphas;
|
||||
using QuantConnect.Algorithm.Framework.Execution;
|
||||
using QuantConnect.Algorithm.Framework.Portfolio;
|
||||
using QuantConnect.Algorithm.Framework.Risk;
|
||||
using QuantConnect.Algorithm.Framework.Selection;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp.Alphas
|
||||
{
|
||||
///<summary>
|
||||
/// This Alpha Model uses Wells Fargo 30-year Fixed Rate Mortgage data from Quandl to
|
||||
/// generate Insights about the movement of Real Estate ETFs. Mortgage rates can provide information
|
||||
/// regarding the general price trend of real estate, and ETFs provide good continuous-time instruments
|
||||
/// to measure the impact against. Volatility in mortgage rates tends to put downward pressure on real
|
||||
/// estate prices, whereas stable mortgage rates, regardless of true rate, lead to stable or higher real
|
||||
/// estate prices. This Alpha model seeks to take advantage of this correlation by emitting insights
|
||||
/// based on volatility and rate deviation from its historic mean.
|
||||
///
|
||||
/// This alpha is part of the Benchmark Alpha Series created by QuantConnect which are open
|
||||
/// sourced so the community and client funds can see an example of an alpha.
|
||||
///</summary>
|
||||
public class MortgageRateVolatilityAlgorithm : QCAlgorithm
|
||||
{
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2017, 1, 1); //Set Start Date
|
||||
SetCash(100000); //Set Strategy Cash
|
||||
|
||||
UniverseSettings.Resolution = Resolution.Daily;
|
||||
SetSecurityInitializer(security => security.FeeModel = new ConstantFeeModel(0));
|
||||
|
||||
// Basket of 6 liquid real estate ETFs
|
||||
Func<string, Symbol> toSymbol = x => QuantConnect.Symbol.Create(x, SecurityType.Equity, Market.USA);
|
||||
var realEstateETFs = new[] { "VNQ", "REET", "TAO", "FREL", "SRET", "HIPS" }.Select(toSymbol).ToArray();
|
||||
SetUniverseSelection(new ManualUniverseSelectionModel(realEstateETFs));
|
||||
|
||||
SetAlpha(new MortgageRateVolatilityAlphaModel(this));
|
||||
|
||||
SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
|
||||
|
||||
SetExecution(new ImmediateExecutionModel());
|
||||
|
||||
SetRiskManagement(new NullRiskManagementModel());
|
||||
|
||||
}
|
||||
|
||||
private class MortgageRateVolatilityAlphaModel : AlphaModel
|
||||
{
|
||||
private readonly int _indicatorPeriod;
|
||||
private readonly Resolution _resolution;
|
||||
private readonly TimeSpan _insightDuration;
|
||||
private readonly int _deviations;
|
||||
private readonly double _insightMagnitude;
|
||||
private readonly Symbol _mortgageRate;
|
||||
private readonly SimpleMovingAverage _mortgageRateSma;
|
||||
private readonly StandardDeviation _mortgageRateStd;
|
||||
|
||||
public MortgageRateVolatilityAlphaModel(
|
||||
QCAlgorithm algorithm,
|
||||
int indicatorPeriod = 15,
|
||||
double insightMagnitude = 0.0005,
|
||||
int deviations = 2,
|
||||
Resolution resolution = Resolution.Daily
|
||||
)
|
||||
{
|
||||
// Add Quandl data for a Well's Fargo 30-year Fixed Rate mortgage
|
||||
_mortgageRate = algorithm.AddData<QuandlMortgagePriceColumns>("WFC/PR_GOV_30YFIXEDVA_APR").Symbol;
|
||||
_indicatorPeriod = indicatorPeriod;
|
||||
_resolution = resolution;
|
||||
_insightDuration = resolution.ToTimeSpan().Multiply(indicatorPeriod);
|
||||
_insightMagnitude = insightMagnitude;
|
||||
_deviations = deviations;
|
||||
|
||||
// Add indicators for the mortgage rate -- Standard Deviation and Simple Moving Average
|
||||
_mortgageRateStd = algorithm.STD(_mortgageRate, _indicatorPeriod, resolution);
|
||||
_mortgageRateSma = algorithm.SMA(_mortgageRate, _indicatorPeriod, resolution);
|
||||
|
||||
// Use a history call to warm-up the indicators
|
||||
WarmUpIndicators(algorithm);
|
||||
}
|
||||
|
||||
public override IEnumerable<Insight> Update(QCAlgorithm algorithm, Slice data)
|
||||
{
|
||||
var insights = new List<Insight>();
|
||||
|
||||
// Return empty list if data slice doesn't contain monrtgage rate data
|
||||
if (!data.Keys.Contains(_mortgageRate))
|
||||
{
|
||||
return insights;
|
||||
}
|
||||
// Extract current mortgage rate, the current STD indicator value, and current SMA value
|
||||
var rate = data[_mortgageRate].Value;
|
||||
var deviation = _deviations * _mortgageRateStd;
|
||||
var sma = _mortgageRateSma;
|
||||
|
||||
// Loop through all Active Securities to emit insights
|
||||
foreach (var security in algorithm.ActiveSecurities.Keys)
|
||||
{
|
||||
// Mortgage rate Symbol will be in the collection, so skip it
|
||||
if (security == _mortgageRate)
|
||||
{
|
||||
return insights;
|
||||
}
|
||||
|
||||
// If volatility in mortgage rates is high, then we emit an Insight to sell
|
||||
if ((rate < sma - deviation) || (rate > sma + deviation))
|
||||
{
|
||||
insights.Add(Insight.Price(security, _insightDuration, InsightDirection.Down, _insightMagnitude));
|
||||
}
|
||||
|
||||
// If volatility in mortgage rates is low, then we emit an Insight to buy
|
||||
if ((rate < sma - (decimal)deviation/2) || (rate > sma + (decimal)deviation/2))
|
||||
{
|
||||
insights.Add(Insight.Price(security, _insightDuration, InsightDirection.Up, _insightMagnitude));
|
||||
}
|
||||
}
|
||||
|
||||
return insights;
|
||||
}
|
||||
|
||||
private void WarmUpIndicators(QCAlgorithm algorithm)
|
||||
{
|
||||
// Make a history call and update the indicators
|
||||
algorithm.History(new[] { _mortgageRate }, _indicatorPeriod, _resolution).PushThrough(bar =>
|
||||
{
|
||||
_mortgageRateSma.Update(bar.EndTime, bar.Value);
|
||||
_mortgageRateStd.Update(bar.EndTime, bar.Value);
|
||||
});
|
||||
}
|
||||
}
|
||||
public class QuandlMortgagePriceColumns : Quandl
|
||||
{
|
||||
public QuandlMortgagePriceColumns()
|
||||
|
||||
// Rename the Quandl object column to the data we want, which is the 'Value' column
|
||||
// of the CSV that our API call returns
|
||||
: base(valueColumnName: "Value")
|
||||
{
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -82,6 +82,16 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
@@ -195,4 +205,4 @@ namespace QuantConnect.Algorithm.CSharp.Alphas
|
||||
UltraShort = ultraShort;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -73,6 +73,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 1893;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 100;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -143,6 +143,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 14531;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 84;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -105,6 +105,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 3943;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 40;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -293,6 +293,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 1753491;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -14,6 +14,7 @@
|
||||
*/
|
||||
|
||||
using System.Collections.Generic;
|
||||
using QuantConnect.Brokerages;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Interfaces;
|
||||
|
||||
@@ -33,6 +34,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
SetStartDate(2018, 04, 04); //Set Start Date
|
||||
SetEndDate(2018, 04, 04); //Set End Date
|
||||
SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash);
|
||||
//Before setting any cash or adding a Security call SetAccountCurrency
|
||||
SetAccountCurrency("EUR");
|
||||
SetCash(100000); //Set Strategy Cash
|
||||
@@ -63,6 +65,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 4324;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 120;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
@@ -87,14 +99,14 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Information Ratio", "0"},
|
||||
{"Tracking Error", "0"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$0.00"},
|
||||
{"Estimated Strategy Capacity", "$85000.00"},
|
||||
{"Total Fees", "€298.35"},
|
||||
{"Estimated Strategy Capacity", "€85000.00"},
|
||||
{"Lowest Capacity Asset", "BTCEUR XJ"},
|
||||
{"Fitness Score", "0.506"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "-14.148"},
|
||||
{"Return Over Maximum Drawdown", "-13.614"},
|
||||
{"Portfolio Turnover", "1.073"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
@@ -109,7 +121,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "18dc611407abec4ea47092e71f33f983"}
|
||||
{"OrderListHash", "2ba443899dcccc79dc0f04441f797bf9"}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
@@ -72,6 +72,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 3943;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -43,9 +43,6 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
|
||||
DefaultOrderProperties = new AtreyuOrderProperties
|
||||
{
|
||||
// Can specify the default exchange to execute an order on.
|
||||
// If not specified will default to the primary exchange
|
||||
Exchange = Exchange.BATS,
|
||||
// Currently only support order for the day
|
||||
TimeInForce = TimeInForce.Day
|
||||
};
|
||||
@@ -59,10 +56,8 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
// will set 25% of our buying power with a market order that will be routed to exchange set in the default order properties (BATS)
|
||||
// will set 25% of our buying power with a market order
|
||||
SetHoldings("SPY", 0.25m);
|
||||
// will increase our SPY holdings to 50% of our buying power with a market order that will be routed to ARCA
|
||||
SetHoldings("SPY", 0.50m, orderProperties: new AtreyuOrderProperties { Exchange = Exchange.ARCA });
|
||||
|
||||
Debug("Purchased SPY!");
|
||||
}
|
||||
@@ -78,39 +73,49 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 3901;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "2"},
|
||||
{"Total Trades", "1"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "93.443%"},
|
||||
{"Drawdown", "1.100%"},
|
||||
{"Compounding Annual Return", "39.143%"},
|
||||
{"Drawdown", "0.500%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "0.847%"},
|
||||
{"Sharpe Ratio", "6.515"},
|
||||
{"Probabilistic Sharpe Ratio", "67.535%"},
|
||||
{"Net Profit", "0.423%"},
|
||||
{"Sharpe Ratio", "5.634"},
|
||||
{"Probabilistic Sharpe Ratio", "67.498%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0.11"},
|
||||
{"Annual Variance", "0.012"},
|
||||
{"Information Ratio", "6.515"},
|
||||
{"Tracking Error", "0.11"},
|
||||
{"Annual Standard Deviation", "0.055"},
|
||||
{"Annual Variance", "0.003"},
|
||||
{"Information Ratio", "5.634"},
|
||||
{"Tracking Error", "0.055"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$0.52"},
|
||||
{"Estimated Strategy Capacity", "$8600000.00"},
|
||||
{"Total Fees", "$0.60"},
|
||||
{"Estimated Strategy Capacity", "$150000000.00"},
|
||||
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
|
||||
{"Fitness Score", "0.124"},
|
||||
{"Fitness Score", "0.062"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "78.376"},
|
||||
{"Portfolio Turnover", "0.124"},
|
||||
{"Return Over Maximum Drawdown", "71.634"},
|
||||
{"Portfolio Turnover", "0.062"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
@@ -124,7 +129,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "01a751a837beafd90015b2fd82edf994"}
|
||||
{"OrderListHash", "d549c64ee7f5e3866712b3c7dbd64caa"}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
176
Algorithm.CSharp/BasicTemplateContinuousFutureAlgorithm.cs
Normal file
176
Algorithm.CSharp/BasicTemplateContinuousFutureAlgorithm.cs
Normal file
@@ -0,0 +1,176 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using System;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Orders;
|
||||
using QuantConnect.Interfaces;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data.UniverseSelection;
|
||||
using QuantConnect.Indicators;
|
||||
using QuantConnect.Securities;
|
||||
using QuantConnect.Securities.Future;
|
||||
using Futures = QuantConnect.Securities.Futures;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Basic Continuous Futures Template Algorithm
|
||||
/// </summary>
|
||||
public class BasicTemplateContinuousFutureAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private Future _continuousContract;
|
||||
private Security _currentContract;
|
||||
private SimpleMovingAverage _fast;
|
||||
private SimpleMovingAverage _slow;
|
||||
|
||||
/// <summary>
|
||||
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2013, 7, 1);
|
||||
SetEndDate(2014, 1, 1);
|
||||
|
||||
_continuousContract = AddFuture(Futures.Indices.SP500EMini,
|
||||
dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
|
||||
dataMappingMode: DataMappingMode.LastTradingDay,
|
||||
contractDepthOffset: 0
|
||||
);
|
||||
|
||||
_fast = SMA(_continuousContract.Symbol, 3, Resolution.Daily);
|
||||
_slow = SMA(_continuousContract.Symbol, 10, Resolution.Daily);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
|
||||
/// </summary>
|
||||
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
|
||||
public override void OnData(Slice data)
|
||||
{
|
||||
foreach (var changedEvent in data.SymbolChangedEvents.Values)
|
||||
{
|
||||
Debug($"{Time} - SymbolChanged event: {changedEvent}");
|
||||
if (Time.TimeOfDay != TimeSpan.Zero)
|
||||
{
|
||||
throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
|
||||
}
|
||||
}
|
||||
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
if(_fast > _slow)
|
||||
{
|
||||
_currentContract = Securities[_continuousContract.Mapped];
|
||||
Buy(_currentContract.Symbol, 1);
|
||||
}
|
||||
}
|
||||
else if(_fast < _slow)
|
||||
{
|
||||
Liquidate();
|
||||
}
|
||||
|
||||
if (_currentContract != null && _currentContract.Symbol != _continuousContract.Mapped)
|
||||
{
|
||||
Log($"{Time} - rolling position from {_currentContract.Symbol} to {_continuousContract.Mapped}");
|
||||
|
||||
var currentPositionSize = _currentContract.Holdings.Quantity;
|
||||
Liquidate(_currentContract.Symbol);
|
||||
Buy(_continuousContract.Mapped, currentPositionSize);
|
||||
_currentContract = Securities[_continuousContract.Mapped];
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnOrderEvent(OrderEvent orderEvent)
|
||||
{
|
||||
Debug($"{orderEvent}");
|
||||
}
|
||||
|
||||
public override void OnSecuritiesChanged(SecurityChanges changes)
|
||||
{
|
||||
Debug($"{Time}-{changes}");
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 875590;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "2"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0.00%"},
|
||||
{"Compounding Annual Return", "-0.007%"},
|
||||
{"Drawdown", "0.000%"},
|
||||
{"Expectancy", "-1"},
|
||||
{"Net Profit", "-0.004%"},
|
||||
{"Sharpe Ratio", "-0.369"},
|
||||
{"Probabilistic Sharpe Ratio", "10.640%"},
|
||||
{"Loss Rate", "100%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "-0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-2.751"},
|
||||
{"Tracking Error", "0.082"},
|
||||
{"Treynor Ratio", "-0.616"},
|
||||
{"Total Fees", "$3.70"},
|
||||
{"Estimated Strategy Capacity", "$0"},
|
||||
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
|
||||
{"Fitness Score", "0.007"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "-0.738"},
|
||||
{"Portfolio Turnover", "0.01"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "bd7fbe57802dfedb36c85609b7234016"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -198,6 +198,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 12970;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 240;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -63,6 +63,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 73;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -84,6 +84,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 3943;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -18,6 +18,7 @@ using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Data.UniverseSelection;
|
||||
using QuantConnect.Interfaces;
|
||||
using QuantConnect.Securities;
|
||||
using QuantConnect.Securities.Future;
|
||||
@@ -64,6 +65,9 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
|
||||
var benchmark = AddEquity("SPY");
|
||||
SetBenchmark(benchmark.Symbol);
|
||||
|
||||
var seeder = new FuncSecuritySeeder(GetLastKnownPrices);
|
||||
SetSecurityInitializer(security => seeder.SeedSecurity(security));
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
@@ -72,6 +76,15 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// <param name="slice">The current slice of data keyed by symbol string</param>
|
||||
public override void OnData(Slice slice)
|
||||
{
|
||||
foreach (var changedEvent in slice.SymbolChangedEvents.Values)
|
||||
{
|
||||
Debug($"{Time} - SymbolChanged event: {changedEvent}");
|
||||
if (Time.TimeOfDay != TimeSpan.Zero)
|
||||
{
|
||||
throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
|
||||
}
|
||||
}
|
||||
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
foreach(var chain in slice.FutureChains)
|
||||
@@ -112,6 +125,19 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
var maintenanceIntraday = futureMarginModel.MaintenanceIntradayMarginRequirement;
|
||||
}
|
||||
|
||||
public override void OnSecuritiesChanged(SecurityChanges changes)
|
||||
{
|
||||
foreach (var addedSecurity in changes.AddedSecurities)
|
||||
{
|
||||
if (addedSecurity.Symbol.SecurityType == SecurityType.Future
|
||||
&& !addedSecurity.Symbol.IsCanonical()
|
||||
&& !addedSecurity.HasData)
|
||||
{
|
||||
throw new Exception($"Future contracts did not work up as expected: {addedSecurity.Symbol}");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
@@ -122,6 +148,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 203367;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 518;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
@@ -131,30 +167,30 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Average Win", "0.00%"},
|
||||
{"Average Loss", "0.00%"},
|
||||
{"Compounding Annual Return", "-100.000%"},
|
||||
{"Drawdown", "13.400%"},
|
||||
{"Drawdown", "13.500%"},
|
||||
{"Expectancy", "-0.818"},
|
||||
{"Net Profit", "-13.418%"},
|
||||
{"Sharpe Ratio", "-321.172"},
|
||||
{"Net Profit", "-13.517%"},
|
||||
{"Sharpe Ratio", "-98.781"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "89%"},
|
||||
{"Win Rate", "11%"},
|
||||
{"Profit-Loss Ratio", "0.69"},
|
||||
{"Alpha", "-1.208"},
|
||||
{"Beta", "0.013"},
|
||||
{"Annual Standard Deviation", "0.003"},
|
||||
{"Alpha", "-1.676"},
|
||||
{"Beta", "0.042"},
|
||||
{"Annual Standard Deviation", "0.01"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-71.816"},
|
||||
{"Tracking Error", "0.24"},
|
||||
{"Treynor Ratio", "-77.951"},
|
||||
{"Information Ratio", "-73.981"},
|
||||
{"Tracking Error", "0.233"},
|
||||
{"Treynor Ratio", "-23.975"},
|
||||
{"Total Fees", "$15207.00"},
|
||||
{"Estimated Strategy Capacity", "$8000.00"},
|
||||
{"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
|
||||
{"Fitness Score", "0.031"},
|
||||
{"Fitness Score", "0.033"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "-9.206"},
|
||||
{"Return Over Maximum Drawdown", "-7.871"},
|
||||
{"Portfolio Turnover", "302.123"},
|
||||
{"Sortino Ratio", "-8.62"},
|
||||
{"Return Over Maximum Drawdown", "-7.81"},
|
||||
{"Portfolio Turnover", "302.321"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
@@ -168,7 +204,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "9e50b7d8e41033110f927658e731f4c6"}
|
||||
{"OrderListHash", "35b3f4b7a225468d42ca085386a2383e"}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
170
Algorithm.CSharp/BasicTemplateFuturesDailyAlgorithm.cs
Normal file
170
Algorithm.CSharp/BasicTemplateFuturesDailyAlgorithm.cs
Normal file
@@ -0,0 +1,170 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*
|
||||
*/
|
||||
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Interfaces;
|
||||
using QuantConnect.Securities;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// This example demonstrates how to add futures with daily resolution.
|
||||
/// </summary>
|
||||
/// <meta name="tag" content="using data" />
|
||||
/// <meta name="tag" content="benchmarks" />
|
||||
/// <meta name="tag" content="futures" />
|
||||
public class BasicTemplateFuturesDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private Symbol _contractSymbol;
|
||||
protected virtual Resolution Resolution => Resolution.Daily;
|
||||
|
||||
// S&P 500 EMini futures
|
||||
private const string RootSP500 = Futures.Indices.SP500EMini;
|
||||
|
||||
// Gold futures
|
||||
private const string RootGold = Futures.Metals.Gold;
|
||||
|
||||
/// <summary>
|
||||
/// Initialize your algorithm and add desired assets.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2013, 10, 08);
|
||||
SetEndDate(2014, 10, 10);
|
||||
SetCash(1000000);
|
||||
|
||||
var futureSP500 = AddFuture(RootSP500, Resolution);
|
||||
var futureGold = AddFuture(RootGold, Resolution);
|
||||
|
||||
// set our expiry filter for this futures chain
|
||||
// SetFilter method accepts TimeSpan objects or integer for days.
|
||||
// The following statements yield the same filtering criteria
|
||||
futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
|
||||
futureGold.SetFilter(0, 182);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
|
||||
/// </summary>
|
||||
/// <param name="slice">The current slice of data keyed by symbol string</param>
|
||||
public override void OnData(Slice slice)
|
||||
{
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
foreach(var chain in slice.FutureChains)
|
||||
{
|
||||
// find the front contract expiring no earlier than in 90 days
|
||||
var contract = (
|
||||
from futuresContract in chain.Value.OrderBy(x => x.Expiry)
|
||||
where futuresContract.Expiry > Time.Date.AddDays(90)
|
||||
select futuresContract
|
||||
).FirstOrDefault();
|
||||
|
||||
// if found, trade it
|
||||
if (contract != null && IsMarketOpen(contract.Symbol))
|
||||
{
|
||||
_contractSymbol = contract.Symbol;
|
||||
MarketOrder(_contractSymbol, 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
Liquidate();
|
||||
}
|
||||
|
||||
foreach (var changedEvent in slice.SymbolChangedEvents.Values)
|
||||
{
|
||||
if (Time.TimeOfDay != TimeSpan.Zero)
|
||||
{
|
||||
throw new Exception($"{Time} unexpected symbol changed event {changedEvent}!");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public virtual bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public virtual long DataPoints => 17041;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public virtual int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "92"},
|
||||
{"Average Win", "0.08%"},
|
||||
{"Average Loss", "-0.01%"},
|
||||
{"Compounding Annual Return", "-0.450%"},
|
||||
{"Drawdown", "0.500%"},
|
||||
{"Expectancy", "-0.824"},
|
||||
{"Net Profit", "-0.453%"},
|
||||
{"Sharpe Ratio", "-1.803"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "98%"},
|
||||
{"Win Rate", "2%"},
|
||||
{"Profit-Loss Ratio", "7.09"},
|
||||
{"Alpha", "-0.003"},
|
||||
{"Beta", "-0.001"},
|
||||
{"Annual Standard Deviation", "0.002"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-1.394"},
|
||||
{"Tracking Error", "0.089"},
|
||||
{"Treynor Ratio", "4.298"},
|
||||
{"Total Fees", "$170.20"},
|
||||
{"Estimated Strategy Capacity", "$36000.00"},
|
||||
{"Lowest Capacity Asset", "ES VP274HSU1AF5"},
|
||||
{"Fitness Score", "0.009"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "-0.8"},
|
||||
{"Return Over Maximum Drawdown", "-0.992"},
|
||||
{"Portfolio Turnover", "0.025"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "09b2f274fa2385597a803e58b784f675"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -130,6 +130,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 123378;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -135,6 +135,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 133616;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 5539;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
106
Algorithm.CSharp/BasicTemplateFuturesHourlyAlgorithm.cs
Normal file
106
Algorithm.CSharp/BasicTemplateFuturesHourlyAlgorithm.cs
Normal file
@@ -0,0 +1,106 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*
|
||||
*/
|
||||
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Interfaces;
|
||||
using QuantConnect.Securities;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// This regressions tests the BasicTemplateFuturesDailyAlgorithm with hour data
|
||||
/// </summary>
|
||||
/// <meta name="tag" content="using data" />
|
||||
/// <meta name="tag" content="benchmarks" />
|
||||
/// <meta name="tag" content="futures" />
|
||||
public class BasicTemplateFuturesHourlyAlgorithm : BasicTemplateFuturesDailyAlgorithm
|
||||
{
|
||||
private Symbol _contractSymbol;
|
||||
protected override Resolution Resolution => Resolution.Hour;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public override bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public override Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 249038;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "1988"},
|
||||
{"Average Win", "0.01%"},
|
||||
{"Average Loss", "0.00%"},
|
||||
{"Compounding Annual Return", "-4.120%"},
|
||||
{"Drawdown", "4.200%"},
|
||||
{"Expectancy", "-0.870"},
|
||||
{"Net Profit", "-4.150%"},
|
||||
{"Sharpe Ratio", "-6.061"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "97%"},
|
||||
{"Win Rate", "3%"},
|
||||
{"Profit-Loss Ratio", "2.92"},
|
||||
{"Alpha", "-0.027"},
|
||||
{"Beta", "-0.006"},
|
||||
{"Annual Standard Deviation", "0.005"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-1.66"},
|
||||
{"Tracking Error", "0.089"},
|
||||
{"Treynor Ratio", "4.919"},
|
||||
{"Total Fees", "$3677.80"},
|
||||
{"Estimated Strategy Capacity", "$2000.00"},
|
||||
{"Lowest Capacity Asset", "ES VP274HSU1AF5"},
|
||||
{"Fitness Score", "0.128"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "-6.856"},
|
||||
{"Return Over Maximum Drawdown", "-0.995"},
|
||||
{"Portfolio Turnover", "0.648"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "87d2b127c9859cad9d2c65ac9d76deb5"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -72,6 +72,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 78;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -30,36 +30,39 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// <meta name="tag" content="indexes" />
|
||||
public class BasicTemplateIndexAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private Symbol _spx;
|
||||
private Symbol _spxOption;
|
||||
protected Symbol Spx;
|
||||
protected Symbol SpxOption;
|
||||
private ExponentialMovingAverage _emaSlow;
|
||||
private ExponentialMovingAverage _emaFast;
|
||||
|
||||
protected virtual Resolution Resolution => Resolution.Minute;
|
||||
protected virtual int StartDay => 4;
|
||||
|
||||
/// <summary>
|
||||
/// Initialize your algorithm and add desired assets.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2021, 1, 4);
|
||||
SetStartDate(2021, 1, StartDay);
|
||||
SetEndDate(2021, 1, 18);
|
||||
SetCash(1000000);
|
||||
|
||||
// Use indicator for signal; but it cannot be traded
|
||||
_spx = AddIndex("SPX", Resolution.Minute).Symbol;
|
||||
Spx = AddIndex("SPX", Resolution).Symbol;
|
||||
|
||||
// Trade on SPX ITM calls
|
||||
_spxOption = QuantConnect.Symbol.CreateOption(
|
||||
_spx,
|
||||
SpxOption = QuantConnect.Symbol.CreateOption(
|
||||
Spx,
|
||||
Market.USA,
|
||||
OptionStyle.European,
|
||||
OptionRight.Call,
|
||||
3200m,
|
||||
new DateTime(2021, 1, 15));
|
||||
|
||||
AddIndexOptionContract(_spxOption, Resolution.Minute);
|
||||
AddIndexOptionContract(SpxOption, Resolution);
|
||||
|
||||
_emaSlow = EMA(_spx, 80);
|
||||
_emaFast = EMA(_spx, 200);
|
||||
_emaSlow = EMA(Spx, 80);
|
||||
_emaFast = EMA(Spx, 200);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
@@ -67,7 +70,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public override void OnData(Slice slice)
|
||||
{
|
||||
if (!slice.Bars.ContainsKey(_spx) || !slice.Bars.ContainsKey(_spxOption))
|
||||
if (!slice.Bars.ContainsKey(Spx) || !slice.Bars.ContainsKey(SpxOption))
|
||||
{
|
||||
return;
|
||||
}
|
||||
@@ -80,7 +83,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
|
||||
if (_emaFast > _emaSlow)
|
||||
{
|
||||
SetHoldings(_spxOption, 1);
|
||||
SetHoldings(SpxOption, 1);
|
||||
}
|
||||
else
|
||||
{
|
||||
@@ -90,7 +93,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
|
||||
public override void OnEndOfAlgorithm()
|
||||
{
|
||||
if (Portfolio[_spx].TotalSaleVolume > 0)
|
||||
if (Portfolio[Spx].TotalSaleVolume > 0)
|
||||
{
|
||||
throw new Exception("Index is not tradable.");
|
||||
}
|
||||
@@ -99,17 +102,27 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = true;
|
||||
public virtual bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public virtual long DataPoints => 16690;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public virtual int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "4"},
|
||||
{"Average Win", "0%"},
|
||||
|
||||
118
Algorithm.CSharp/BasicTemplateIndexDailyAlgorithm.cs
Normal file
118
Algorithm.CSharp/BasicTemplateIndexDailyAlgorithm.cs
Normal file
@@ -0,0 +1,118 @@
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using QuantConnect.Data;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Regression for running an Index algorithm with Daily data
|
||||
/// </summary>
|
||||
public class BasicTemplateIndexDailyAlgorithm : BasicTemplateIndexAlgorithm
|
||||
{
|
||||
protected override Resolution Resolution => Resolution.Daily;
|
||||
protected override int StartDay => 1;
|
||||
|
||||
// two complete weeks starting from the 5th plus the 18th bar
|
||||
protected virtual int ExpectedBarCount => 2 * 5 + 1;
|
||||
protected int BarCounter = 0;
|
||||
|
||||
/// <summary>
|
||||
/// Purchase a contract when we are not invested, liquidate otherwise
|
||||
/// </summary>
|
||||
public override void OnData(Slice slice)
|
||||
{
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
// SPX Index is not tradable, but we can trade an option
|
||||
MarketOrder(SpxOption, 1);
|
||||
}
|
||||
else
|
||||
{
|
||||
Liquidate();
|
||||
}
|
||||
|
||||
// Count how many slices we receive with SPX data in it to assert later
|
||||
if (slice.ContainsKey(Spx))
|
||||
{
|
||||
BarCounter++;
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnEndOfAlgorithm()
|
||||
{
|
||||
if (BarCounter != ExpectedBarCount)
|
||||
{
|
||||
throw new ArgumentException($"Bar Count {BarCounter} is not expected count of {ExpectedBarCount}");
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public override bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public override Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 122;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "9"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "-39.42%"},
|
||||
{"Compounding Annual Return", "394.321%"},
|
||||
{"Drawdown", "0.200%"},
|
||||
{"Expectancy", "-1"},
|
||||
{"Net Profit", "8.219%"},
|
||||
{"Sharpe Ratio", "6.812"},
|
||||
{"Probabilistic Sharpe Ratio", "91.380%"},
|
||||
{"Loss Rate", "100%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "2.236"},
|
||||
{"Beta", "-1.003"},
|
||||
{"Annual Standard Deviation", "0.317"},
|
||||
{"Annual Variance", "0.101"},
|
||||
{"Information Ratio", "5.805"},
|
||||
{"Tracking Error", "0.359"},
|
||||
{"Treynor Ratio", "-2.153"},
|
||||
{"Total Fees", "$0.00"},
|
||||
{"Estimated Strategy Capacity", "$0"},
|
||||
{"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
|
||||
{"Fitness Score", "0.027"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "1776.081"},
|
||||
{"Portfolio Turnover", "0.027"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "474e8e0e28ee84c869f8c69ec3efe371"}
|
||||
};
|
||||
}
|
||||
}
|
||||
82
Algorithm.CSharp/BasicTemplateIndexHourlyAlgorithm.cs
Normal file
82
Algorithm.CSharp/BasicTemplateIndexHourlyAlgorithm.cs
Normal file
@@ -0,0 +1,82 @@
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Regression for running an Index algorithm with Hourly data
|
||||
/// </summary>
|
||||
public class BasicTemplateIndexHourlyAlgorithm : BasicTemplateIndexDailyAlgorithm
|
||||
{
|
||||
protected override Resolution Resolution => Resolution.Hour;
|
||||
protected override int ExpectedBarCount => base.ExpectedBarCount * 8;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public override bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public override Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 408;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "70"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "-0.23%"},
|
||||
{"Compounding Annual Return", "-34.441%"},
|
||||
{"Drawdown", "2.000%"},
|
||||
{"Expectancy", "-1"},
|
||||
{"Net Profit", "-2.028%"},
|
||||
{"Sharpe Ratio", "-11.139"},
|
||||
{"Probabilistic Sharpe Ratio", "0.000%"},
|
||||
{"Loss Rate", "100%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "-0.269"},
|
||||
{"Beta", "0.086"},
|
||||
{"Annual Standard Deviation", "0.023"},
|
||||
{"Annual Variance", "0.001"},
|
||||
{"Information Ratio", "-3.624"},
|
||||
{"Tracking Error", "0.094"},
|
||||
{"Treynor Ratio", "-3.042"},
|
||||
{"Total Fees", "$0.00"},
|
||||
{"Estimated Strategy Capacity", "$310000.00"},
|
||||
{"Lowest Capacity Asset", "SPX XL80P3GHDZXQ|SPX 31"},
|
||||
{"Fitness Score", "0.002"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "-14.51"},
|
||||
{"Return Over Maximum Drawdown", "-17.213"},
|
||||
{"Portfolio Turnover", "0.299"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "3eb56c551f20e2ffa1c56c47c5ee6667"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -30,20 +30,22 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
private Symbol _spx;
|
||||
private ExponentialMovingAverage _emaSlow;
|
||||
private ExponentialMovingAverage _emaFast;
|
||||
protected virtual Resolution Resolution => Resolution.Minute;
|
||||
protected virtual int StartDay => 4;
|
||||
|
||||
/// <summary>
|
||||
/// Initialize your algorithm and add desired assets.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2021, 1, 4);
|
||||
SetStartDate(2021, 1, StartDay);
|
||||
SetEndDate(2021, 2, 1);
|
||||
SetCash(1000000);
|
||||
|
||||
// Use indicator for signal; but it cannot be traded.
|
||||
// We will instead trade on SPX options
|
||||
_spx = AddIndex("SPX", Resolution.Minute).Symbol;
|
||||
var spxOptions = AddIndexOption(_spx, Resolution.Minute);
|
||||
_spx = AddIndex("SPX", Resolution).Symbol;
|
||||
var spxOptions = AddIndexOption(_spx, Resolution);
|
||||
spxOptions.SetFilter(filterFunc => filterFunc.CallsOnly());
|
||||
|
||||
_emaSlow = EMA(_spx, 80);
|
||||
@@ -122,17 +124,27 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = false;
|
||||
public virtual bool CanRunLocally { get; } = false;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public virtual long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public virtual int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "8220"},
|
||||
{"Average Win", "0.00%"},
|
||||
|
||||
127
Algorithm.CSharp/BasicTemplateIndexOptionsDailyAlgorithm.cs
Normal file
127
Algorithm.CSharp/BasicTemplateIndexOptionsDailyAlgorithm.cs
Normal file
@@ -0,0 +1,127 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*
|
||||
*/
|
||||
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Regression for running an IndexOptions algorithm with Daily data
|
||||
/// </summary>
|
||||
public class BasicTemplateIndexOptionsDailyAlgorithm : BasicTemplateIndexOptionsAlgorithm
|
||||
{
|
||||
protected override Resolution Resolution => Resolution.Daily;
|
||||
protected override int StartDay => 1;
|
||||
|
||||
/// <summary>
|
||||
/// Index EMA Cross trading index options of the index.
|
||||
/// </summary>
|
||||
public override void OnData(Slice slice)
|
||||
{
|
||||
foreach (var chain in slice.OptionChains.Values)
|
||||
{
|
||||
// Select the contract with the lowest AskPrice
|
||||
var contract = chain.Contracts.OrderBy(x => x.Value.AskPrice).FirstOrDefault().Value;
|
||||
|
||||
if (contract == null)
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
if (Portfolio.Invested)
|
||||
{
|
||||
Liquidate();
|
||||
}
|
||||
else
|
||||
{
|
||||
MarketOrder(contract.Symbol, 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public override bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public override Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 381;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "9"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "-0.01%"},
|
||||
{"Compounding Annual Return", "-0.091%"},
|
||||
{"Drawdown", "0.000%"},
|
||||
{"Expectancy", "-1"},
|
||||
{"Net Profit", "-0.008%"},
|
||||
{"Sharpe Ratio", "-4.033"},
|
||||
{"Probabilistic Sharpe Ratio", "0.013%"},
|
||||
{"Loss Rate", "100%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "-0.001"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-0.447"},
|
||||
{"Tracking Error", "0.136"},
|
||||
{"Treynor Ratio", "-4.612"},
|
||||
{"Total Fees", "$0.00"},
|
||||
{"Estimated Strategy Capacity", "$0"},
|
||||
{"Lowest Capacity Asset", "SPX XL80P59H5E6M|SPX 31"},
|
||||
{"Fitness Score", "0"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "-50718.291"},
|
||||
{"Return Over Maximum Drawdown", "-11.386"},
|
||||
{"Portfolio Turnover", "0"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "5f5df233d68d9115a0d81785de54e71d"}
|
||||
};
|
||||
}
|
||||
}
|
||||
97
Algorithm.CSharp/BasicTemplateIndexOptionsHourlyAlgorithm.cs
Normal file
97
Algorithm.CSharp/BasicTemplateIndexOptionsHourlyAlgorithm.cs
Normal file
@@ -0,0 +1,97 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*
|
||||
*/
|
||||
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Regression for running an IndexOptions algorithm with Hourly data
|
||||
/// </summary>
|
||||
public class BasicTemplateIndexOptionsHourlyAlgorithm : BasicTemplateIndexOptionsDailyAlgorithm
|
||||
{
|
||||
protected override Resolution Resolution => Resolution.Hour;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public override bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public override Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 2212;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "70"},
|
||||
{"Average Win", "0.00%"},
|
||||
{"Average Loss", "0.00%"},
|
||||
{"Compounding Annual Return", "0%"},
|
||||
{"Drawdown", "0.000%"},
|
||||
{"Expectancy", "0.000"},
|
||||
{"Net Profit", "0%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "36.504%"},
|
||||
{"Loss Rate", "97%"},
|
||||
{"Win Rate", "3%"},
|
||||
{"Profit-Loss Ratio", "34.00"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "-0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-0.449"},
|
||||
{"Tracking Error", "0.138"},
|
||||
{"Treynor Ratio", "-0"},
|
||||
{"Total Fees", "$0.00"},
|
||||
{"Estimated Strategy Capacity", "$0"},
|
||||
{"Lowest Capacity Asset", "SPX XL80P59H5E6M|SPX 31"},
|
||||
{"Fitness Score", "0"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "0"},
|
||||
{"Portfolio Turnover", "0"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "f21910eb98ceaa39e02020de95354d86"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -14,8 +14,9 @@
|
||||
*/
|
||||
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Orders;
|
||||
using System.Collections.Generic;
|
||||
using QuantConnect.Interfaces;
|
||||
using QuantConnect.Orders;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
@@ -26,20 +27,21 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// <meta name="tag" content="using data" />
|
||||
/// <meta name="tag" content="using quantconnect" />
|
||||
/// <meta name="tag" content="trading and orders" />
|
||||
public class BasicTemplateIndiaAlgorithm : QCAlgorithm
|
||||
public class BasicTemplateIndiaAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
/// <summary>
|
||||
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2003, 10, 07); //Set Start Date
|
||||
SetEndDate(2003, 10, 11); //Set End Date
|
||||
SetCash(100000); //Set Strategy Cash
|
||||
SetAccountCurrency("INR"); //Set Account Currency
|
||||
SetStartDate(2019, 1, 23); //Set Start Date
|
||||
SetEndDate(2019, 10, 31); //Set End Date
|
||||
SetCash(100000); //Set Strategy Cash
|
||||
|
||||
// Find more symbols here: http://quantconnect.com/data
|
||||
// Equities Resolutions: Tick, Second, Minute, Hour, Daily.
|
||||
AddEquity("UNIONBANK", Resolution.Second, Market.India);
|
||||
AddEquity("YESBANK", Resolution.Minute, Market.India);
|
||||
|
||||
//Set Order Prperties as per the requirements for order placement
|
||||
DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE);
|
||||
@@ -58,7 +60,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
var marketTicket = MarketOrder("UNIONBANK", 1);
|
||||
var marketTicket = MarketOrder("YESBANK", 1);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -73,60 +75,70 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = false;
|
||||
public bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 29524;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "3"},
|
||||
{"Total Trades", "1"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "-1.01%"},
|
||||
{"Compounding Annual Return", "261.134%"},
|
||||
{"Drawdown", "2.200%"},
|
||||
{"Expectancy", "-1"},
|
||||
{"Net Profit", "1.655%"},
|
||||
{"Sharpe Ratio", "8.505"},
|
||||
{"Probabilistic Sharpe Ratio", "66.840%"},
|
||||
{"Loss Rate", "100%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "-0.010%"},
|
||||
{"Drawdown", "0.000%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "-0.008%"},
|
||||
{"Sharpe Ratio", "-1.183"},
|
||||
{"Probabilistic Sharpe Ratio", "0.001%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "-0.091"},
|
||||
{"Beta", "1.006"},
|
||||
{"Annual Standard Deviation", "0.224"},
|
||||
{"Annual Variance", "0.05"},
|
||||
{"Information Ratio", "-33.445"},
|
||||
{"Tracking Error", "0.002"},
|
||||
{"Treynor Ratio", "1.893"},
|
||||
{"Total Fees", "$10.32"},
|
||||
{"Estimated Strategy Capacity", "$27000000.00"},
|
||||
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
|
||||
{"Fitness Score", "0.747"},
|
||||
{"Kelly Criterion Estimate", "38.796"},
|
||||
{"Kelly Criterion Probability Value", "0.228"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "85.095"},
|
||||
{"Portfolio Turnover", "0.747"},
|
||||
{"Total Insights Generated", "100"},
|
||||
{"Total Insights Closed", "99"},
|
||||
{"Total Insights Analysis Completed", "99"},
|
||||
{"Long Insight Count", "100"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-1.183"},
|
||||
{"Tracking Error", "0"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "₹6.00"},
|
||||
{"Estimated Strategy Capacity", "₹61000000000.00"},
|
||||
{"Lowest Capacity Asset", "YESBANK UL"},
|
||||
{"Fitness Score", "0"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "-0.247"},
|
||||
{"Return Over Maximum Drawdown", "-1.104"},
|
||||
{"Portfolio Turnover", "0"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$135639.1761"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$21852.9784"},
|
||||
{"Mean Population Estimated Insight Value", "$220.7372"},
|
||||
{"Mean Population Direction", "53.5354%"},
|
||||
{"Mean Population Magnitude", "53.5354%"},
|
||||
{"Rolling Averaged Population Direction", "58.2788%"},
|
||||
{"Rolling Averaged Population Magnitude", "58.2788%"},
|
||||
{"OrderListHash", "ad2216297c759d8e5aef48ff065f8919"}
|
||||
{"Estimated Monthly Alpha Value", "₹0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "₹0"},
|
||||
{"Mean Population Estimated Insight Value", "₹0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "6cc69218edd7bd461678b9ee0c575db5"}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
168
Algorithm.CSharp/BasicTemplateIndiaIndexAlgorithm.cs
Normal file
168
Algorithm.CSharp/BasicTemplateIndiaIndexAlgorithm.cs
Normal file
@@ -0,0 +1,168 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*
|
||||
*/
|
||||
|
||||
using System;
|
||||
using QuantConnect.Data;
|
||||
using System.Collections.Generic;
|
||||
using QuantConnect.Indicators;
|
||||
using QuantConnect.Interfaces;
|
||||
using QuantConnect.Orders;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// This example demonstrates how to add index asset types.
|
||||
/// </summary>
|
||||
/// <meta name="tag" content="using data" />
|
||||
/// <meta name="tag" content="benchmarks" />
|
||||
/// <meta name="tag" content="indexes" />
|
||||
public class BasicTemplateIndiaIndexAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
protected Symbol Nifty;
|
||||
protected Symbol NiftyETF;
|
||||
private ExponentialMovingAverage _emaSlow;
|
||||
private ExponentialMovingAverage _emaFast;
|
||||
|
||||
/// <summary>
|
||||
/// Initialize your algorithm and add desired assets.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetAccountCurrency("INR"); //Set Account Currency
|
||||
SetStartDate(2019, 1, 1); //Set End Date
|
||||
SetEndDate(2019, 1, 5); //Set End Date
|
||||
SetCash(1000000); //Set Strategy Cash
|
||||
|
||||
// Use indicator for signal; but it cannot be traded
|
||||
Nifty = AddIndex("NIFTY50", Resolution.Minute, Market.India).Symbol;
|
||||
|
||||
//Trade Index based ETF
|
||||
NiftyETF = AddEquity("JUNIORBEES", Resolution.Minute, Market.India).Symbol;
|
||||
|
||||
//Set Order Prperties as per the requirements for order placement
|
||||
DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE);
|
||||
|
||||
_emaSlow = EMA(Nifty, 80);
|
||||
_emaFast = EMA(Nifty, 200);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Index EMA Cross trading underlying.
|
||||
/// </summary>
|
||||
public override void OnData(Slice slice)
|
||||
{
|
||||
if (!slice.Bars.ContainsKey(Nifty) || !slice.Bars.ContainsKey(NiftyETF))
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
// Warm up indicators
|
||||
if (!_emaSlow.IsReady)
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
if (_emaFast > _emaSlow)
|
||||
{
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
var marketTicket = MarketOrder(NiftyETF, 1);
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
Liquidate();
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnEndOfAlgorithm()
|
||||
{
|
||||
if (Portfolio[Nifty].TotalSaleVolume > 0)
|
||||
{
|
||||
throw new Exception("Index is not tradable.");
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public virtual bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public virtual Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 2882;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "6"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0.00%"},
|
||||
{"Compounding Annual Return", "-0.395%"},
|
||||
{"Drawdown", "0.000%"},
|
||||
{"Expectancy", "-1"},
|
||||
{"Net Profit", "-0.004%"},
|
||||
{"Sharpe Ratio", "-23.595"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "100%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-23.595"},
|
||||
{"Tracking Error", "0"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "₹36.00"},
|
||||
{"Estimated Strategy Capacity", "₹74000.00"},
|
||||
{"Lowest Capacity Asset", "JUNIORBEES UL"},
|
||||
{"Fitness Score", "0"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "-29.6"},
|
||||
{"Return Over Maximum Drawdown", "-123.624"},
|
||||
{"Portfolio Turnover", "0"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "₹0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "₹0"},
|
||||
{"Mean Population Estimated Insight Value", "₹0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "4637f26543287548b28a3c296db055d3"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -99,6 +99,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 884208;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -109,6 +109,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 884616;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -106,6 +106,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 884197;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -69,7 +69,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
var contractsByExpiration = chain.Where(x => x.Expiry != Time.Date).OrderBy(x => x.Expiry);
|
||||
var contract = contractsByExpiration.FirstOrDefault();
|
||||
|
||||
if (contract != null)
|
||||
if (contract != null && IsMarketOpen(contract.Symbol))
|
||||
{
|
||||
// if found, trade it
|
||||
MarketOrder(contract.Symbol, 1);
|
||||
@@ -119,6 +119,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 41730;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -97,6 +97,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 1722373;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -136,6 +136,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 990979;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -76,7 +76,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
.ThenByDescending(x => x.Right)
|
||||
.FirstOrDefault();
|
||||
|
||||
if (atmContract != null)
|
||||
if (atmContract != null && IsMarketOpen(atmContract.Symbol))
|
||||
{
|
||||
// if found, trade it
|
||||
MarketOrder(atmContract.Symbol, 1);
|
||||
@@ -106,6 +106,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 64216;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
100
Algorithm.CSharp/BinanceCashAccountFeeRegressionAlgorithm.cs
Normal file
100
Algorithm.CSharp/BinanceCashAccountFeeRegressionAlgorithm.cs
Normal file
@@ -0,0 +1,100 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using QuantConnect.Brokerages;
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Binance cash account regression algorithm, reproduces issue https://github.com/QuantConnect/Lean/issues/6123
|
||||
/// </summary>
|
||||
public class BinanceCashAccountFeeRegressionAlgorithm : CryptoBaseCurrencyFeeRegressionAlgorithm
|
||||
{
|
||||
/// <summary>
|
||||
/// The target account type
|
||||
/// </summary>
|
||||
protected override AccountType AccountType { get; } = AccountType.Cash;
|
||||
|
||||
public override void Initialize()
|
||||
{
|
||||
SetAccountCurrency("USDT");
|
||||
SetStartDate(2018, 05, 02);
|
||||
SetEndDate(2018, 05, 03);
|
||||
BrokerageName = BrokerageName.Binance;
|
||||
Pair = "BTCUSDT";
|
||||
base.Initialize();
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 50;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 28;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public override Dictionary<string, string> ExpectedStatistics => new()
|
||||
{
|
||||
{"Total Trades", "49"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "0%"},
|
||||
{"Drawdown", "0%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "0%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "0"},
|
||||
{"Tracking Error", "0"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "USDT45.62"},
|
||||
{"Estimated Strategy Capacity", "USDT220000.00"},
|
||||
{"Lowest Capacity Asset", "BTCUSDT 18N"},
|
||||
{"Fitness Score", "0.208"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "26.189"},
|
||||
{"Portfolio Turnover", "0.208"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "USDT0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "USDT0"},
|
||||
{"Mean Population Estimated Insight Value", "USDT0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "7417649395922ff3791471b4f3b5c021"}
|
||||
};
|
||||
}
|
||||
}
|
||||
100
Algorithm.CSharp/BinanceMarginAccountFeeRegressionAlgorithm.cs
Normal file
100
Algorithm.CSharp/BinanceMarginAccountFeeRegressionAlgorithm.cs
Normal file
@@ -0,0 +1,100 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using QuantConnect.Brokerages;
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Binance margin account regression algorithm, reproduces issue https://github.com/QuantConnect/Lean/issues/6123
|
||||
/// </summary>
|
||||
public class BinanceMarginAccountFeeRegressionAlgorithm : CryptoBaseCurrencyFeeRegressionAlgorithm
|
||||
{
|
||||
/// <summary>
|
||||
/// The target account type
|
||||
/// </summary>
|
||||
protected override AccountType AccountType { get; } = AccountType.Margin;
|
||||
|
||||
public override void Initialize()
|
||||
{
|
||||
SetAccountCurrency("USDT");
|
||||
SetStartDate(2018, 05, 02);
|
||||
SetEndDate(2018, 05, 03);
|
||||
BrokerageName = BrokerageName.Binance;
|
||||
Pair = "BTCUSDT";
|
||||
base.Initialize();
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 50;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 28;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public override Dictionary<string, string> ExpectedStatistics => new()
|
||||
{
|
||||
{"Total Trades", "49"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "0%"},
|
||||
{"Drawdown", "0%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "0%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "0"},
|
||||
{"Tracking Error", "0"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "USDT45.62"},
|
||||
{"Estimated Strategy Capacity", "USDT12000000.00"},
|
||||
{"Lowest Capacity Asset", "BTCUSDT 18N"},
|
||||
{"Fitness Score", "0.208"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "26.189"},
|
||||
{"Portfolio Turnover", "0.208"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "USDT0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "USDT0"},
|
||||
{"Mean Population Estimated Insight Value", "USDT0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "7417649395922ff3791471b4f3b5c021"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,99 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using QuantConnect.Brokerages;
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Bitfinex cash account regression algorithm, reproduces issue https://github.com/QuantConnect/Lean/issues/6123
|
||||
/// </summary>
|
||||
public class BitfinexCashAccountFeeRegressionAlgorithm : CryptoBaseCurrencyFeeRegressionAlgorithm
|
||||
{
|
||||
/// <summary>
|
||||
/// The target account type
|
||||
/// </summary>
|
||||
protected override AccountType AccountType { get; } = AccountType.Cash;
|
||||
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2013, 10, 02);
|
||||
SetEndDate(2013, 10, 03);
|
||||
BrokerageName = BrokerageName.Bitfinex;
|
||||
Pair = "BTCUSD";
|
||||
base.Initialize();
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 126;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 28;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public override Dictionary<string, string> ExpectedStatistics => new()
|
||||
{
|
||||
{"Total Trades", "49"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "0%"},
|
||||
{"Drawdown", "0%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "0%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "0"},
|
||||
{"Tracking Error", "0"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$1.13"},
|
||||
{"Estimated Strategy Capacity", "$2000.00"},
|
||||
{"Lowest Capacity Asset", "BTCUSD E3"},
|
||||
{"Fitness Score", "0.002"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "79228162514264337593543950335"},
|
||||
{"Portfolio Turnover", "0.002"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "7f892f0c42d8826ff770ee602fe207a2"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,99 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using QuantConnect.Brokerages;
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Bitfinex margin account regression algorithm, reproduces issue https://github.com/QuantConnect/Lean/issues/6123
|
||||
/// </summary>
|
||||
public class BitfinexMarginAccountFeeRegressionAlgorithm : CryptoBaseCurrencyFeeRegressionAlgorithm
|
||||
{
|
||||
/// <summary>
|
||||
/// The target account type
|
||||
/// </summary>
|
||||
protected override AccountType AccountType { get; } = AccountType.Margin;
|
||||
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2013, 10, 02);
|
||||
SetEndDate(2013, 10, 03);
|
||||
BrokerageName = BrokerageName.Bitfinex;
|
||||
Pair = "BTCUSD";
|
||||
base.Initialize();
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public override long DataPoints => 126;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public override int AlgorithmHistoryDataPoints => 28;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public override Dictionary<string, string> ExpectedStatistics => new()
|
||||
{
|
||||
{"Total Trades", "49"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "0%"},
|
||||
{"Drawdown", "0%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "0%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "0"},
|
||||
{"Tracking Error", "0"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$1.13"},
|
||||
{"Estimated Strategy Capacity", "$640000.00"},
|
||||
{"Lowest Capacity Asset", "BTCUSD E3"},
|
||||
{"Fitness Score", "0.002"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "79228162514264337593543950335"},
|
||||
{"Portfolio Turnover", "0.002"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "7f892f0c42d8826ff770ee602fe207a2"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -73,6 +73,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 14082;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 256;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -122,6 +122,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 5765;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 120;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -51,6 +51,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -96,6 +96,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -180,6 +180,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -66,6 +66,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -72,6 +72,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -66,6 +66,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -92,6 +92,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -67,6 +67,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -67,6 +67,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -60,6 +60,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -60,6 +60,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -61,6 +61,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -52,6 +52,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -37,7 +37,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
SetEndDate(2019, 2, 21);
|
||||
SetCash("EUR", 100000);
|
||||
|
||||
_symbol = AddCfd("DE30EUR", Resolution.Minute, Market.Oanda).Symbol;
|
||||
_symbol = AddCfd("DE30EUR").Symbol;
|
||||
|
||||
SetBenchmark(_symbol);
|
||||
}
|
||||
@@ -70,6 +70,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 2776;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
@@ -94,8 +104,8 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Information Ratio", "-19.772"},
|
||||
{"Tracking Error", "0.014"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$0.00"},
|
||||
{"Estimated Strategy Capacity", "$670000.00"},
|
||||
{"Total Fees", "€0.00"},
|
||||
{"Estimated Strategy Capacity", "€670000.00"},
|
||||
{"Lowest Capacity Asset", "DE30EUR 8I"},
|
||||
{"Fitness Score", "0"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
|
||||
@@ -111,6 +111,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 2003;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -156,6 +156,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 7239;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -139,6 +139,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 998462;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -111,6 +111,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 78091;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -89,6 +89,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 70952;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -95,6 +95,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 49662;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 6;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -66,45 +66,55 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = {Language.CSharp, Language.Python};
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 15643;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 208;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "7"},
|
||||
{"Average Win", "0.01%"},
|
||||
{"Average Loss", "-0.40%"},
|
||||
{"Compounding Annual Return", "1143.086%"},
|
||||
{"Total Trades", "18"},
|
||||
{"Average Win", "0.00%"},
|
||||
{"Average Loss", "-0.02%"},
|
||||
{"Compounding Annual Return", "88.032%"},
|
||||
{"Drawdown", "1.800%"},
|
||||
{"Expectancy", "-0.319"},
|
||||
{"Net Profit", "3.275%"},
|
||||
{"Sharpe Ratio", "23.495"},
|
||||
{"Probabilistic Sharpe Ratio", "80.494%"},
|
||||
{"Loss Rate", "33%"},
|
||||
{"Win Rate", "67%"},
|
||||
{"Profit-Loss Ratio", "0.02"},
|
||||
{"Alpha", "4.366"},
|
||||
{"Beta", "1.255"},
|
||||
{"Annual Standard Deviation", "0.292"},
|
||||
{"Annual Variance", "0.085"},
|
||||
{"Information Ratio", "47.955"},
|
||||
{"Tracking Error", "0.102"},
|
||||
{"Treynor Ratio", "5.461"},
|
||||
{"Total Fees", "$71.37"},
|
||||
{"Estimated Strategy Capacity", "$3500000.00"},
|
||||
{"Expectancy", "-0.679"},
|
||||
{"Net Profit", "0.811%"},
|
||||
{"Sharpe Ratio", "5.833"},
|
||||
{"Probabilistic Sharpe Ratio", "65.782%"},
|
||||
{"Loss Rate", "73%"},
|
||||
{"Win Rate", "27%"},
|
||||
{"Profit-Loss Ratio", "0.18"},
|
||||
{"Alpha", "-0.473"},
|
||||
{"Beta", "0.725"},
|
||||
{"Annual Standard Deviation", "0.165"},
|
||||
{"Annual Variance", "0.027"},
|
||||
{"Information Ratio", "-14.297"},
|
||||
{"Tracking Error", "0.071"},
|
||||
{"Treynor Ratio", "1.331"},
|
||||
{"Total Fees", "$31.70"},
|
||||
{"Estimated Strategy Capacity", "$5900000.00"},
|
||||
{"Lowest Capacity Asset", "AIG R735QTJ8XC9X"},
|
||||
{"Fitness Score", "0.501"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "148.07"},
|
||||
{"Return Over Maximum Drawdown", "1487.238"},
|
||||
{"Portfolio Turnover", "0.501"},
|
||||
{"Total Insights Generated", "2"},
|
||||
{"Sortino Ratio", "13.543"},
|
||||
{"Return Over Maximum Drawdown", "75.664"},
|
||||
{"Portfolio Turnover", "0.505"},
|
||||
{"Total Insights Generated", "6"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "2"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Long Insight Count", "5"},
|
||||
{"Short Insight Count", "1"},
|
||||
{"Long/Short Ratio", "500%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
@@ -112,7 +122,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "5a171f804d47cd27f84aaef791da8594"}
|
||||
{"OrderListHash", "f25344c69f9b9476ae5a834616a65c82"}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
@@ -60,6 +60,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 3943;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -73,6 +73,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 3943;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -139,6 +139,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 8091;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -165,6 +165,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 59;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
@@ -79,7 +79,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
}
|
||||
}
|
||||
|
||||
if (_lastDateLog.Month != Time.Month)
|
||||
if (_lastDateLog.Month != Time.Month && _continuousContract.HasData)
|
||||
{
|
||||
_lastDateLog = Time;
|
||||
|
||||
@@ -88,10 +88,9 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
Liquidate();
|
||||
}
|
||||
else if(_continuousContract.HasData)
|
||||
else
|
||||
{
|
||||
// This works because we set this contract as tradable, even if it's a canonical security
|
||||
Buy(_continuousContract.Symbol, 1);
|
||||
Buy(_continuousContract.Mapped, 1);
|
||||
}
|
||||
|
||||
if(Time.Month == 1 && Time.Year == 2013)
|
||||
@@ -132,39 +131,49 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 815242;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "2"},
|
||||
{"Average Win", "1.11%"},
|
||||
{"Average Win", "1.21%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "2.199%"},
|
||||
{"Drawdown", "1.700%"},
|
||||
{"Compounding Annual Return", "2.412%"},
|
||||
{"Drawdown", "1.600%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "1.109%"},
|
||||
{"Sharpe Ratio", "0.717"},
|
||||
{"Probabilistic Sharpe Ratio", "38.157%"},
|
||||
{"Net Profit", "1.209%"},
|
||||
{"Sharpe Ratio", "0.782"},
|
||||
{"Probabilistic Sharpe Ratio", "40.528%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "100%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "-0.007"},
|
||||
{"Alpha", "-0.005"},
|
||||
{"Beta", "0.099"},
|
||||
{"Annual Standard Deviation", "0.022"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-2.732"},
|
||||
{"Information Ratio", "-2.724"},
|
||||
{"Tracking Error", "0.076"},
|
||||
{"Treynor Ratio", "0.156"},
|
||||
{"Treynor Ratio", "0.171"},
|
||||
{"Total Fees", "$3.70"},
|
||||
{"Estimated Strategy Capacity", "$3900000.00"},
|
||||
{"Lowest Capacity Asset", "ES 1S1"},
|
||||
{"Estimated Strategy Capacity", "$810000000.00"},
|
||||
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
|
||||
{"Fitness Score", "0.007"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "0.484"},
|
||||
{"Return Over Maximum Drawdown", "1.736"},
|
||||
{"Portfolio Turnover", "0.011"},
|
||||
{"Sortino Ratio", "0.587"},
|
||||
{"Return Over Maximum Drawdown", "1.952"},
|
||||
{"Portfolio Turnover", "0.01"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
@@ -178,7 +187,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "7d6fb409115f2f8d403c7eb261b9b3b6"}
|
||||
{"OrderListHash", "95c62255290b4ad375579b398290230c"}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
}
|
||||
}
|
||||
|
||||
if (_lastDateLog.Month != Time.Month)
|
||||
if (_lastDateLog.Month != Time.Month && _continuousContract.HasData)
|
||||
{
|
||||
_lastDateLog = Time;
|
||||
|
||||
@@ -101,10 +101,9 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
Liquidate();
|
||||
}
|
||||
else if(_continuousContract.HasData)
|
||||
else
|
||||
{
|
||||
// This works because we set this contract as tradable, even if it's a canonical security
|
||||
Buy(_continuousContract.Symbol, 1);
|
||||
Buy(_continuousContract.Mapped, 1);
|
||||
}
|
||||
|
||||
if(Time.Month == 1 && Time.Year == 2013)
|
||||
@@ -145,39 +144,49 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 875590;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "3"},
|
||||
{"Average Win", "1.11%"},
|
||||
{"Average Win", "1.21%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "2.092%"},
|
||||
{"Drawdown", "1.700%"},
|
||||
{"Compounding Annual Return", "2.392%"},
|
||||
{"Drawdown", "1.600%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "1.055%"},
|
||||
{"Sharpe Ratio", "0.682"},
|
||||
{"Probabilistic Sharpe Ratio", "36.937%"},
|
||||
{"Net Profit", "1.199%"},
|
||||
{"Sharpe Ratio", "0.775"},
|
||||
{"Probabilistic Sharpe Ratio", "40.287%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "100%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "-0.007"},
|
||||
{"Alpha", "-0.006"},
|
||||
{"Beta", "0.099"},
|
||||
{"Annual Standard Deviation", "0.022"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-2.742"},
|
||||
{"Information Ratio", "-2.726"},
|
||||
{"Tracking Error", "0.076"},
|
||||
{"Treynor Ratio", "0.149"},
|
||||
{"Treynor Ratio", "0.169"},
|
||||
{"Total Fees", "$5.55"},
|
||||
{"Estimated Strategy Capacity", "$190000.00"},
|
||||
{"Lowest Capacity Asset", "ES 1S1"},
|
||||
{"Estimated Strategy Capacity", "$67000000.00"},
|
||||
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
|
||||
{"Fitness Score", "0.01"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "0.479"},
|
||||
{"Return Over Maximum Drawdown", "1.652"},
|
||||
{"Portfolio Turnover", "0.015"},
|
||||
{"Sortino Ratio", "0.516"},
|
||||
{"Return Over Maximum Drawdown", "1.935"},
|
||||
{"Portfolio Turnover", "0.016"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
@@ -191,7 +200,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "9f7574803b8ebfac8f912019c943d27e"}
|
||||
{"OrderListHash", "5fc26c7f1f2d9fff97d36a5b58853840"}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
173
Algorithm.CSharp/ContinuousFutureHistoryRegressionAlgorithm.cs
Normal file
173
Algorithm.CSharp/ContinuousFutureHistoryRegressionAlgorithm.cs
Normal file
@@ -0,0 +1,173 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using System;
|
||||
using System.Linq;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Interfaces;
|
||||
using QuantConnect.Securities;
|
||||
using System.Collections.Generic;
|
||||
using QuantConnect.Securities.Future;
|
||||
using QuantConnect.Data.UniverseSelection;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Continuous Futures History Regression algorithm. Asserting and showcasing the behavior of adding a continuous future
|
||||
/// </summary>
|
||||
public class ContinuousFutureHistoryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private Future _continuousContract;
|
||||
private bool _warmedUp;
|
||||
|
||||
/// <summary>
|
||||
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetStartDate(2013, 10, 10);
|
||||
SetEndDate(2013, 10, 11);
|
||||
|
||||
_continuousContract = AddFuture(Futures.Indices.SP500EMini,
|
||||
dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
|
||||
dataMappingMode: DataMappingMode.OpenInterest,
|
||||
contractDepthOffset: 1
|
||||
);
|
||||
SetWarmup(1, Resolution.Daily);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
|
||||
/// </summary>
|
||||
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
|
||||
public override void OnData(Slice data)
|
||||
{
|
||||
if (IsWarmingUp)
|
||||
{
|
||||
// warm up data
|
||||
_warmedUp = true;
|
||||
|
||||
if (!_continuousContract.HasData)
|
||||
{
|
||||
throw new Exception($"ContinuousContract did not get any data during warmup!");
|
||||
}
|
||||
|
||||
var backMonthExpiration = data.Keys.Single().Underlying.ID.Date;
|
||||
var frontMonthExpiration = FuturesExpiryFunctions.FuturesExpiryFunction(_continuousContract.Symbol)(Time.AddMonths(1));
|
||||
if (backMonthExpiration <= frontMonthExpiration.Date)
|
||||
{
|
||||
throw new Exception($"Unexpected current mapped contract expiration {backMonthExpiration}" +
|
||||
$" @ {Time} it should be AFTER front month expiration {frontMonthExpiration}");
|
||||
}
|
||||
}
|
||||
if (data.Keys.Count != 1)
|
||||
{
|
||||
throw new Exception($"We are getting data for more than one symbols! {string.Join(",", data.Keys.Select(symbol => symbol))}");
|
||||
}
|
||||
|
||||
if (!Portfolio.Invested && !IsWarmingUp)
|
||||
{
|
||||
Buy(_continuousContract.Mapped, 1);
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnEndOfAlgorithm()
|
||||
{
|
||||
if (!_warmedUp)
|
||||
{
|
||||
throw new Exception("Algorithm didn't warm up!");
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnSecuritiesChanged(SecurityChanges changes)
|
||||
{
|
||||
Debug($"{Time}-{changes}");
|
||||
if (changes.AddedSecurities.Any(security => security.Symbol != _continuousContract.Symbol)
|
||||
|| changes.RemovedSecurities.Any(security => security.Symbol != _continuousContract.Symbol))
|
||||
{
|
||||
throw new Exception($"We got an unexpected security changes {changes}");
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 40881;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "1"},
|
||||
{"Average Win", "0%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "0%"},
|
||||
{"Drawdown", "0%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "0%"},
|
||||
{"Sharpe Ratio", "0"},
|
||||
{"Probabilistic Sharpe Ratio", "0%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "0%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "0"},
|
||||
{"Beta", "0"},
|
||||
{"Annual Standard Deviation", "0"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "0"},
|
||||
{"Tracking Error", "0"},
|
||||
{"Treynor Ratio", "0"},
|
||||
{"Total Fees", "$1.85"},
|
||||
{"Estimated Strategy Capacity", "$290000000.00"},
|
||||
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
|
||||
{"Fitness Score", "0.408"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "79228162514264337593543950335"},
|
||||
{"Return Over Maximum Drawdown", "79228162514264337593543950335"},
|
||||
{"Portfolio Turnover", "0.408"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
{"Total Insights Analysis Completed", "0"},
|
||||
{"Long Insight Count", "0"},
|
||||
{"Short Insight Count", "0"},
|
||||
{"Long/Short Ratio", "100%"},
|
||||
{"Estimated Monthly Alpha Value", "$0"},
|
||||
{"Total Accumulated Estimated Alpha Value", "$0"},
|
||||
{"Mean Population Estimated Insight Value", "$0"},
|
||||
{"Mean Population Direction", "0%"},
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "9408389924d9b7333a9f0a4f64b08d27"}
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -22,6 +22,7 @@ using QuantConnect.Securities;
|
||||
using QuantConnect.Data.Market;
|
||||
using System.Collections.Generic;
|
||||
using QuantConnect.Securities.Future;
|
||||
using QuantConnect.Data.UniverseSelection;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
@@ -31,8 +32,9 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
public class ContinuousFutureRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private List<SymbolChangedEvent> _mappings = new();
|
||||
private Symbol _currentMappedSymbol;
|
||||
private Future _continuousContract;
|
||||
private DateTime _lastDateLog;
|
||||
private DateTime _lastMonth;
|
||||
|
||||
/// <summary>
|
||||
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
|
||||
@@ -55,6 +57,17 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
|
||||
public override void OnData(Slice data)
|
||||
{
|
||||
// we subtract a minute cause we can get data on the market close, from the previous minute
|
||||
if (!_continuousContract.Exchange.DateTimeIsOpen(Time.AddMinutes(-1)))
|
||||
{
|
||||
if (data.Bars.Count > 0 || data.QuoteBars.Count > 0)
|
||||
{
|
||||
throw new Exception($"We are getting data during closed market!");
|
||||
}
|
||||
}
|
||||
|
||||
var currentlyMappedSecurity = Securities[_continuousContract.Mapped];
|
||||
|
||||
if (data.Keys.Count != 1)
|
||||
{
|
||||
throw new Exception($"We are getting data for more than one symbols! {string.Join(",", data.Keys.Select(symbol => symbol))}");
|
||||
@@ -65,7 +78,12 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
if (changedEvent.Symbol == _continuousContract.Symbol)
|
||||
{
|
||||
_mappings.Add(changedEvent);
|
||||
Log($"SymbolChanged event: {changedEvent}");
|
||||
Log($"{Time} - SymbolChanged event: {changedEvent}");
|
||||
|
||||
if (_currentMappedSymbol == _continuousContract.Mapped)
|
||||
{
|
||||
throw new Exception($"Continuous contract current symbol did not change! {_continuousContract.Mapped}");
|
||||
}
|
||||
|
||||
var currentExpiration = changedEvent.Symbol.Underlying.ID.Date;
|
||||
var frontMonthExpiration = FuturesExpiryFunctions.FuturesExpiryFunction(_continuousContract.Symbol)(Time.AddMonths(1));
|
||||
@@ -77,20 +95,19 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (_lastDateLog.Month != Time.Month)
|
||||
if (_lastMonth.Month != Time.Month && currentlyMappedSecurity.HasData)
|
||||
{
|
||||
_lastDateLog = Time;
|
||||
_lastMonth = Time;
|
||||
|
||||
Log($"{Time}- {Securities[_continuousContract.Symbol].GetLastData()}");
|
||||
Log($"{Time}- {currentlyMappedSecurity.GetLastData()}");
|
||||
if (Portfolio.Invested)
|
||||
{
|
||||
Liquidate();
|
||||
}
|
||||
else if(_continuousContract.HasData)
|
||||
else
|
||||
{
|
||||
// This works because we set this contract as tradable, even if it's a canonical security
|
||||
Buy(_continuousContract.Symbol, 1);
|
||||
Buy(currentlyMappedSecurity.Symbol, 1);
|
||||
}
|
||||
|
||||
if(Time.Month == 1 && Time.Year == 2013)
|
||||
@@ -102,6 +119,8 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
_currentMappedSymbol = _continuousContract.Mapped;
|
||||
}
|
||||
|
||||
public override void OnOrderEvent(OrderEvent orderEvent)
|
||||
@@ -112,6 +131,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnSecuritiesChanged(SecurityChanges changes)
|
||||
{
|
||||
Debug($"{Time}-{changes}");
|
||||
if (changes.AddedSecurities.Any(security => security.Symbol != _continuousContract.Symbol)
|
||||
|| changes.RemovedSecurities.Any(security => security.Symbol != _continuousContract.Symbol))
|
||||
{
|
||||
throw new Exception($"We got an unexpected security changes {changes}");
|
||||
}
|
||||
}
|
||||
|
||||
public override void OnEndOfAlgorithm()
|
||||
{
|
||||
var expectedMappingCounts = 2;
|
||||
@@ -131,38 +160,48 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 875590;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
||||
{
|
||||
{"Total Trades", "3"},
|
||||
{"Average Win", "1.03%"},
|
||||
{"Average Win", "1.21%"},
|
||||
{"Average Loss", "0%"},
|
||||
{"Compounding Annual Return", "1.970%"},
|
||||
{"Drawdown", "1.400%"},
|
||||
{"Compounding Annual Return", "2.392%"},
|
||||
{"Drawdown", "1.600%"},
|
||||
{"Expectancy", "0"},
|
||||
{"Net Profit", "0.994%"},
|
||||
{"Sharpe Ratio", "0.7"},
|
||||
{"Probabilistic Sharpe Ratio", "37.553%"},
|
||||
{"Net Profit", "1.199%"},
|
||||
{"Sharpe Ratio", "0.775"},
|
||||
{"Probabilistic Sharpe Ratio", "40.287%"},
|
||||
{"Loss Rate", "0%"},
|
||||
{"Win Rate", "100%"},
|
||||
{"Profit-Loss Ratio", "0"},
|
||||
{"Alpha", "-0.006"},
|
||||
{"Beta", "0.091"},
|
||||
{"Annual Standard Deviation", "0.02"},
|
||||
{"Beta", "0.099"},
|
||||
{"Annual Standard Deviation", "0.022"},
|
||||
{"Annual Variance", "0"},
|
||||
{"Information Ratio", "-2.745"},
|
||||
{"Information Ratio", "-2.726"},
|
||||
{"Tracking Error", "0.076"},
|
||||
{"Treynor Ratio", "0.153"},
|
||||
{"Treynor Ratio", "0.169"},
|
||||
{"Total Fees", "$5.55"},
|
||||
{"Estimated Strategy Capacity", "$48000000.00"},
|
||||
{"Lowest Capacity Asset", "ES 1S1"},
|
||||
{"Estimated Strategy Capacity", "$67000000.00"},
|
||||
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
|
||||
{"Fitness Score", "0.01"},
|
||||
{"Kelly Criterion Estimate", "0"},
|
||||
{"Kelly Criterion Probability Value", "0"},
|
||||
{"Sortino Ratio", "0.492"},
|
||||
{"Return Over Maximum Drawdown", "1.708"},
|
||||
{"Sortino Ratio", "0.516"},
|
||||
{"Return Over Maximum Drawdown", "1.935"},
|
||||
{"Portfolio Turnover", "0.016"},
|
||||
{"Total Insights Generated", "0"},
|
||||
{"Total Insights Closed", "0"},
|
||||
@@ -177,7 +216,7 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
{"Mean Population Magnitude", "0%"},
|
||||
{"Rolling Averaged Population Direction", "0%"},
|
||||
{"Rolling Averaged Population Magnitude", "0%"},
|
||||
{"OrderListHash", "fb3bb82d84fc6c390a40f36d0d1faf59"}
|
||||
{"OrderListHash", "8ad040c62ad255e4f9cd423364147e85"}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
@@ -121,6 +121,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 22137;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
120
Algorithm.CSharp/CryptoBaseCurrencyFeeRegressionAlgorithm.cs
Normal file
120
Algorithm.CSharp/CryptoBaseCurrencyFeeRegressionAlgorithm.cs
Normal file
@@ -0,0 +1,120 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using System;
|
||||
using System.Linq;
|
||||
using QuantConnect.Util;
|
||||
using QuantConnect.Data;
|
||||
using QuantConnect.Orders;
|
||||
using QuantConnect.Interfaces;
|
||||
using QuantConnect.Brokerages;
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Base crypto account regression algorithm trading in and out
|
||||
/// </summary>
|
||||
public abstract class CryptoBaseCurrencyFeeRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private Symbol _symbol;
|
||||
|
||||
/// <summary>
|
||||
/// The target account type
|
||||
/// </summary>
|
||||
protected abstract AccountType AccountType { get; }
|
||||
|
||||
/// <summary>
|
||||
/// The target brokerage model name
|
||||
/// </summary>
|
||||
protected BrokerageName BrokerageName { get; set; }
|
||||
|
||||
/// <summary>
|
||||
/// The pair to add and trade
|
||||
/// </summary>
|
||||
protected string Pair { get; set; }
|
||||
|
||||
/// <summary>
|
||||
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
SetBrokerageModel(BrokerageName, AccountType);
|
||||
_symbol = AddCrypto(Pair, Resolution.Hour).Symbol;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
|
||||
/// </summary>
|
||||
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
|
||||
public override void OnData(Slice data)
|
||||
{
|
||||
if (!Portfolio.Invested)
|
||||
{
|
||||
CurrencyPairUtil.DecomposeCurrencyPair(_symbol, out var baseCurrency, out var quoteCurrency);
|
||||
|
||||
var initialQuoteCurrency = Portfolio.CashBook[quoteCurrency].Amount;
|
||||
var ticket = Buy(_symbol, 0.1m);
|
||||
var filledEvent = ticket.OrderEvents.Single(orderEvent => orderEvent.Status == OrderStatus.Filled);
|
||||
|
||||
if (Portfolio.CashBook[baseCurrency].Amount != ticket.QuantityFilled
|
||||
|| filledEvent.FillQuantity != ticket.QuantityFilled
|
||||
|| (0.1m - filledEvent.OrderFee.Value.Amount) != ticket.QuantityFilled)
|
||||
{
|
||||
throw new Exception($"Unexpected BaseCurrency porfoltio status. Event {filledEvent}. CashBook: {Portfolio.CashBook}. ");
|
||||
}
|
||||
|
||||
if (Portfolio.CashBook[quoteCurrency].Amount != (initialQuoteCurrency - 0.1m * filledEvent.FillPrice))
|
||||
{
|
||||
throw new Exception($"Unexpected QuoteCurrency porfoltio status. Event {filledEvent}. CashBook: {Portfolio.CashBook}. ");
|
||||
}
|
||||
|
||||
if (Securities[_symbol].Holdings.Quantity != (0.1m - filledEvent.OrderFee.Value.Amount))
|
||||
{
|
||||
throw new Exception($"Unexpected Holdings: {Securities[_symbol].Holdings}. Event {filledEvent}");
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
Liquidate();
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
||||
/// </summary>
|
||||
public bool CanRunLocally { get; } = true;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public virtual long DataPoints => 0;
|
||||
|
||||
/// </summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public virtual int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
public abstract Dictionary<string, string> ExpectedStatistics { get; }
|
||||
}
|
||||
}
|
||||
@@ -74,6 +74,16 @@ namespace QuantConnect.Algorithm.CSharp
|
||||
/// </summary>
|
||||
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 234043;
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of the algorithm history
|
||||
/// </summary>
|
||||
public int AlgorithmHistoryDataPoints => 0;
|
||||
|
||||
/// <summary>
|
||||
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
||||
/// </summary>
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user