Alexandre Catarino
2b0fd2e607
* Fixes Double to Decimal Cast in GetAnnualPerformance `GetAnnualPerformance` raises an exception if the `AnnualPerformance` calculation returns a double that cannot be cast to decimal (smaller than `decimal.MinValue` or bigger than `decimal.MaxValue`). See `ProbabilisticSharpeRatio` where the same solution was applied. * Updates SPY Market Data SPY is a key asset since it is the default benchmark, and any change can lead to different `Alpha` and `Beta` * Updates Unit Tests to Reflect Data Update * Updates Regression Tests to Reflect Data Update I Most of the regression tests change because of updated data (market and factors) of SPY (default benchmark) while the total trade remain the same. * Updates Regression Tests to Reflect Data Update II The following regression tests were changed to adapt to adjusted prices and keep the total trades: - `BacktestingBrokerageRegressionAlgorithm` - `LimitIfTouchedRegressionAlgorithm` - `PortfolioRebalanceOnCustomFuncRegressionAlgorithm` - `SetAccountCurrencySecurityMarginModelRegressionAlgorithm` - `StopLossOnOrderEventRegressionAlgorithm` - `TimeInForceAlgorithm` The following regression tests have more trades since adjusted prices allowed more 1-2 shares trades that were rounded down to zero before: - `FreePortfolioValueRegressionAlgorithm` 2 -> 3 - `PortfolioRebalanceOnDateRulesRegressionAlgorithm` 291 -> 298 - `TrailingStopRiskFrameworkAlgorithm` 5 -> 7 Especial cases: - `AutoRegressiveIntegratedMovingAverageRegressionAlgorithm` 65 -> 52 - ARIMA model sensibility - `BlackLittermanPortfolioOptimizationFrameworkAlgorithm` 18 -> 19 - BLM model sensibility - `ExtendedMarketHoursHistoryRegressionAlgorithm` 20 -> 18 - Less minute bars before market opens * Addresses Peer-Review Fix `BacktestingBrokerageRegressionAlgorithm` to use `CalculateOrderQuantity` and round down `quantity` to an even number to pass a value assertion and update the expected value from 50 to 52. The quantity calculated by `CalculateOrderQuantity` has changed from 50 to 53 because of factor file update.
232 lines
11 KiB
C#
232 lines
11 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using System;
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using System.Collections.Generic;
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using System.Globalization;
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using Newtonsoft.Json;
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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression test to demonstrate importing and trading on custom data.
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="custom data" />
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/// <meta name="tag" content="crypto" />
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/// <meta name="tag" content="regression test" />
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public class CustomDataRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2011, 9, 13);
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SetEndDate(2015, 12, 01);
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//Set the cash for the strategy:
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SetCash(100000);
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//Define the symbol and "type" of our generic data:
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var resolution = LiveMode ? Resolution.Second : Resolution.Daily;
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AddData<Bitcoin>("BTC", resolution);
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}
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/// <summary>
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/// Event Handler for Bitcoin Data Events: These Bitcoin objects are created from our
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/// "Bitcoin" type below and fired into this event handler.
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/// </summary>
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/// <param name="data">One(1) Bitcoin Object, streamed into our algorithm synchronised in time with our other data streams</param>
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public void OnData(Bitcoin data)
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{
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//If we don't have any bitcoin "SHARES" -- invest"
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if (!Portfolio.Invested)
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{
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//Bitcoin used as a tradable asset, like stocks, futures etc.
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if (data.Close != 0)
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{
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//Access custom data symbols using <ticker>.<custom-type>
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Order("BTC.Bitcoin", Portfolio.MarginRemaining / Math.Abs(data.Close + 1));
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}
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}
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public Language[] Languages { get; } = { Language.CSharp, Language.Python };
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Trades", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "157.497%"},
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{"Drawdown", "84.800%"},
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{"Expectancy", "0"},
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{"Net Profit", "5319.007%"},
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{"Sharpe Ratio", "2.086"},
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{"Probabilistic Sharpe Ratio", "69.456%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "1.736"},
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{"Beta", "0.142"},
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{"Annual Standard Deviation", "0.84"},
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{"Annual Variance", "0.706"},
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{"Information Ratio", "1.925"},
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{"Tracking Error", "0.846"},
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{"Treynor Ratio", "12.333"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Fitness Score", "0"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "2.269"},
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{"Return Over Maximum Drawdown", "1.858"},
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{"Portfolio Turnover", "0"},
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{"Total Insights Generated", "0"},
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{"Total Insights Closed", "0"},
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{"Total Insights Analysis Completed", "0"},
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{"Long Insight Count", "0"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$0"},
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{"Total Accumulated Estimated Alpha Value", "$0"},
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{"Mean Population Estimated Insight Value", "$0"},
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{"Mean Population Direction", "0%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "0%"},
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{"Rolling Averaged Population Magnitude", "0%"},
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{"OrderListHash", "50faa37f15732bf5c24ad1eeaa335bc7"}
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};
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/// <summary>
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/// Custom Data Type: Bitcoin data from Quandl - http://www.quandl.com/help/api-for-bitcoin-data
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/// </summary>
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public class Bitcoin : BaseData
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{
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[JsonProperty("timestamp")]
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public int Timestamp = 0;
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[JsonProperty("open")]
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public decimal Open = 0;
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[JsonProperty("high")]
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public decimal High = 0;
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[JsonProperty("low")]
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public decimal Low = 0;
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[JsonProperty("last")]
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public decimal Close = 0;
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[JsonProperty("bid")]
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public decimal Bid = 0;
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[JsonProperty("ask")]
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public decimal Ask = 0;
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[JsonProperty("vwap")]
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public decimal WeightedPrice = 0;
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[JsonProperty("volume")]
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public decimal VolumeBTC = 0;
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public decimal VolumeUSD = 0;
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/// <summary>
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/// 1. DEFAULT CONSTRUCTOR: Custom data types need a default constructor.
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/// We search for a default constructor so please provide one here. It won't be used for data, just to generate the "Factory".
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/// </summary>
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public Bitcoin()
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{
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Symbol = "BTC";
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}
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/// <summary>
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/// 2. RETURN THE STRING URL SOURCE LOCATION FOR YOUR DATA:
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/// This is a powerful and dynamic select source file method. If you have a large dataset, 10+mb we recommend you break it into smaller files. E.g. One zip per year.
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/// We can accept raw text or ZIP files. We read the file extension to determine if it is a zip file.
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/// </summary>
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/// <param name="config">Configuration object</param>
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/// <param name="date">Date of this source file</param>
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/// <param name="isLiveMode">true if we're in live mode, false for backtesting mode</param>
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/// <returns>String URL of source file.</returns>
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public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)
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{
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if (isLiveMode)
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{
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return new SubscriptionDataSource("https://www.bitstamp.net/api/ticker/", SubscriptionTransportMedium.Rest);
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}
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//return "http://my-ftp-server.com/futures-data-" + date.ToString("Ymd") + ".zip";
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// OR simply return a fixed small data file. Large files will slow down your backtest
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return new SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc&api_key=WyAazVXnq7ATy_fefTqm", SubscriptionTransportMedium.RemoteFile);
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}
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/// <summary>
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/// 3. READER METHOD: Read 1 line from data source and convert it into Object.
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/// Each line of the CSV File is presented in here. The backend downloads your file, loads it into memory and then line by line
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/// feeds it into your algorithm
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/// </summary>
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/// <param name="line">string line from the data source file submitted above</param>
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/// <param name="config">Subscription data, symbol name, data type</param>
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/// <param name="date">Current date we're requesting. This allows you to break up the data source into daily files.</param>
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/// <param name="isLiveMode">true if we're in live mode, false for backtesting mode</param>
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/// <returns>New Bitcoin Object which extends BaseData.</returns>
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public override BaseData Reader(SubscriptionDataConfig config, string line, DateTime date, bool isLiveMode)
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{
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var coin = new Bitcoin();
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if (isLiveMode)
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{
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//Example Line Format:
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//{"high": "441.00", "last": "421.86", "timestamp": "1411606877", "bid": "421.96", "vwap": "428.58", "volume": "14120.40683975", "low": "418.83", "ask": "421.99"}
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try
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{
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coin = JsonConvert.DeserializeObject<Bitcoin>(line);
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coin.EndTime = DateTime.UtcNow.ConvertFromUtc(config.ExchangeTimeZone);
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coin.Value = coin.Close;
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}
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catch { /* Do nothing, possible error in json decoding */ }
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return coin;
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}
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//Example Line Format:
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//Date Open High Low Close Volume (BTC) Volume (Currency) Weighted Price
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//2011-09-13 5.8 6.0 5.65 5.97 58.37138238, 346.0973893944 5.929230648356
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try
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{
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string[] data = line.Split(',');
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coin.Time = DateTime.Parse(data[0], CultureInfo.InvariantCulture);
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coin.EndTime = coin.Time.AddDays(1);
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coin.Open = Convert.ToDecimal(data[1], CultureInfo.InvariantCulture);
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coin.High = Convert.ToDecimal(data[2], CultureInfo.InvariantCulture);
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coin.Low = Convert.ToDecimal(data[3], CultureInfo.InvariantCulture);
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coin.Close = Convert.ToDecimal(data[4], CultureInfo.InvariantCulture);
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coin.VolumeBTC = Convert.ToDecimal(data[5], CultureInfo.InvariantCulture);
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coin.VolumeUSD = Convert.ToDecimal(data[6], CultureInfo.InvariantCulture);
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coin.WeightedPrice = Convert.ToDecimal(data[7], CultureInfo.InvariantCulture);
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coin.Value = coin.Close;
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}
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catch { /* Do nothing, skip first title row */ }
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return coin;
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}
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}
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}
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} |