Gerardo Salazar
8c6aa6a3b3
* Adds CapacityEstimate and SymbolCapacity
The capacity estimation has been moved from
the report generator and wired directly into
Lean via the ResultHandler. In addition,
the capacity estimation strategy has changed
to account for errors in the previous iteration
of the capacity estimation.
Many many thanks to Jared for being much of the
mastermind behind this project. It would have
been harder to complete without him to bounce ideas
off of.
* Moves old tests to regression algorithms
* Adds Estimated Capacity statistic
* Removes old capacity estimation tests
Final report capacity estimation. Pushing to save state
* Fixes bugs, cleans up code and adds comments
* Adds forced sampling to Capacity Estimation
* Misc. bug fixes for daily data
* Updates capacity test cases' Estimated Strategy Capacity statistic
* Adds Capacity Estimate to all regression algorithms
* Removes Report's StrategyCapacity class and fixes bug in tests
* Adds null check in BacktestingResultHandler to fix
BacktestingTransactionHandler failing tests
* Deletes old capacity estimation classes
* Retrieve capacity estimates from backtest statistics results
instead of calculating at runtime
* Make $0.00 capacity return as "-" and Result = 0 in report
* Adds capacity to runtime statistics
* Converts capacity to number denoted by financial figures in RuntimeStats
* Addresses review: code cleanup for Capacity and adds comments to regression tests
250 lines
11 KiB
C#
250 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.Linq;
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using QuantConnect.Data;
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using QuantConnect.Brokerages;
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using QuantConnect.Indicators;
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using QuantConnect.Orders;
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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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/// The demonstration algorithm shows some of the most common order methods when working with Crypto assets.
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="using quantconnect" />
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/// <meta name="tag" content="trading and orders" />
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public class BasicTemplateCryptoAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private ExponentialMovingAverage _fast;
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private ExponentialMovingAverage _slow;
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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(2018, 4, 4); // Set Start Date
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SetEndDate(2018, 4, 4); // Set End Date
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// Although typically real brokerages as GDAX only support a single account currency,
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// here we add both USD and EUR to demonstrate how to handle non-USD account currencies.
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// Set Strategy Cash (USD)
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SetCash(10000);
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// Set Strategy Cash (EUR)
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// EUR/USD conversion rate will be updated dynamically
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SetCash("EUR", 10000);
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// Add some coins as initial holdings
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// When connected to a real brokerage, the amount specified in SetCash
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// will be replaced with the amount in your actual account.
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SetCash("BTC", 1m);
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SetCash("ETH", 5m);
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SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash);
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// You can uncomment the following line when live trading with GDAX,
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// to ensure limit orders will only be posted to the order book and never executed as a taker (incurring fees).
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// Please note this statement has no effect in backtesting or paper trading.
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// DefaultOrderProperties = new GDAXOrderProperties { PostOnly = true };
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// Find more symbols here: http://quantconnect.com/data
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AddCrypto("BTCUSD");
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AddCrypto("ETHUSD");
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AddCrypto("BTCEUR");
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var symbol = AddCrypto("LTCUSD").Symbol;
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// create two moving averages
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_fast = EMA(symbol, 30, Resolution.Minute);
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_slow = EMA(symbol, 60, Resolution.Minute);
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="data">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice data)
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{
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if (Portfolio.CashBook["EUR"].ConversionRate == 0
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|| Portfolio.CashBook["BTC"].ConversionRate == 0
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|| Portfolio.CashBook["ETH"].ConversionRate == 0
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|| Portfolio.CashBook["LTC"].ConversionRate == 0)
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{
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Log($"EUR conversion rate: {Portfolio.CashBook["EUR"].ConversionRate}");
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Log($"BTC conversion rate: {Portfolio.CashBook["BTC"].ConversionRate}");
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Log($"LTC conversion rate: {Portfolio.CashBook["LTC"].ConversionRate}");
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Log($"ETH conversion rate: {Portfolio.CashBook["ETH"].ConversionRate}");
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throw new Exception("Conversion rate is 0");
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}
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if (Time.Hour == 1 && Time.Minute == 0)
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{
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// Sell all ETH holdings with a limit order at 1% above the current price
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var limitPrice = Math.Round(Securities["ETHUSD"].Price * 1.01m, 2);
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var quantity = Portfolio.CashBook["ETH"].Amount;
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LimitOrder("ETHUSD", -quantity, limitPrice);
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}
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else if (Time.Hour == 2 && Time.Minute == 0)
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{
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// Submit a buy limit order for BTC at 5% below the current price
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var usdTotal = Portfolio.CashBook["USD"].Amount;
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var limitPrice = Math.Round(Securities["BTCUSD"].Price * 0.95m, 2);
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// use only half of our total USD
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var quantity = usdTotal * 0.5m / limitPrice;
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LimitOrder("BTCUSD", quantity, limitPrice);
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}
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else if (Time.Hour == 2 && Time.Minute == 1)
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{
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// Get current USD available, subtracting amount reserved for buy open orders
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var usdTotal = Portfolio.CashBook["USD"].Amount;
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var usdReserved = Transactions.GetOpenOrders(x => x.Direction == OrderDirection.Buy && x.Type == OrderType.Limit)
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.Where(x => x.Symbol == "BTCUSD" || x.Symbol == "ETHUSD")
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.Sum(x => x.Quantity * ((LimitOrder) x).LimitPrice);
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var usdAvailable = usdTotal - usdReserved;
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// Submit a marketable buy limit order for ETH at 1% above the current price
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var limitPrice = Math.Round(Securities["ETHUSD"].Price * 1.01m, 2);
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// use all of our available USD
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var quantity = usdAvailable / limitPrice;
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// this order will be rejected for insufficient funds
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LimitOrder("ETHUSD", quantity, limitPrice);
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// use only half of our available USD
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quantity = usdAvailable * 0.5m / limitPrice;
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LimitOrder("ETHUSD", quantity, limitPrice);
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}
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else if (Time.Hour == 11 && Time.Minute == 0)
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{
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// Liquidate our BTC holdings (including the initial holding)
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SetHoldings("BTCUSD", 0m);
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}
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else if (Time.Hour == 12 && Time.Minute == 0)
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{
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// Submit a market buy order for 1 BTC using EUR
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Buy("BTCEUR", 1m);
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// Submit a sell limit order at 10% above market price
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var limitPrice = Math.Round(Securities["BTCEUR"].Price * 1.1m, 2);
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LimitOrder("BTCEUR", -1, limitPrice);
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}
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else if (Time.Hour == 13 && Time.Minute == 0)
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{
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// Cancel the limit order if not filled
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Transactions.CancelOpenOrders("BTCEUR");
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}
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else if (Time.Hour > 13)
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{
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// To include any initial holdings, we read the LTC amount from the cashbook
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// instead of using Portfolio["LTCUSD"].Quantity
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if (_fast > _slow)
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{
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if (Portfolio.CashBook["LTC"].Amount == 0)
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{
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Buy("LTCUSD", 10);
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}
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}
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else
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{
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if (Portfolio.CashBook["LTC"].Amount > 0)
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{
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// The following two statements currently behave differently if we have initial holdings:
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// https://github.com/QuantConnect/Lean/issues/1860
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Liquidate("LTCUSD");
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// SetHoldings("LTCUSD", 0);
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}
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}
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}
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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Debug(Time + " " + orderEvent);
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}
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public override void OnEndOfAlgorithm()
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{
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Log($"{Time} - TotalPortfolioValue: {Portfolio.TotalPortfolioValue}");
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Log($"{Time} - CashBook: {Portfolio.CashBook}");
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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", "10"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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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", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "0"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$85.34"},
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{"Estimated Strategy Capacity", "$0"},
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{"Fitness Score", "0.5"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "79228162514264337593543950335"},
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{"Return Over Maximum Drawdown", "-43.943"},
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{"Portfolio Turnover", "1.028"},
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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", "1bf1a6d9dd921982b72a6178f9e50e68"}
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};
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}
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}
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