chore: import upstream snapshot with attribution
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wehub-resource-sync
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/*
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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 Deedle;
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using QuantConnect.Orders;
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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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namespace QuantConnect.Report
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{
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/// <summary>
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/// Strategy metrics collection such as usage of funds and asset allocations
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/// </summary>
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public static class Metrics
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{
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/// <summary>
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/// Calculates the leverage used from trades. The series used to call this extension function should
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/// be the equity curve with the associated <see cref="Order"/> objects that go along with it.
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/// </summary>
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/// <param name="equityCurve">Equity curve series</param>
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/// <param name="orders">Orders associated with the equity curve</param>
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/// <returns>Leverage utilization over time</returns>
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public static Series<DateTime, double> LeverageUtilization(Series<DateTime, double> equityCurve, List<Order> orders)
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{
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if (equityCurve.IsEmpty || orders.Count == 0)
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{
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return new Series<DateTime, double>(new DateTime[] { }, new double[] { });
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}
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var pointInTimePortfolios = PortfolioLooper.FromOrders(equityCurve, orders)
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.ToList(); // Required because for some reason our AbsoluteHoldingsValue is multiplied by two whenever we GroupBy on the raw IEnumerable
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return LeverageUtilization(pointInTimePortfolios);
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}
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/// <summary>
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/// Gets the leverage utilization from a list of <see cref="PointInTimePortfolio"/>
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/// </summary>
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/// <param name="portfolios">Point in time portfolios</param>
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/// <returns>Series of leverage utilization</returns>
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public static Series<DateTime, double> LeverageUtilization(List<PointInTimePortfolio> portfolios)
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{
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var leverage = portfolios.GroupBy(portfolio => portfolio.Time)
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.Select(group => new KeyValuePair<DateTime, double>(group.Key, (double)group.Last().Leverage))
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.ToList();
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// Drop missing because we don't care about the missing values
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return new Series<DateTime, double>(leverage).DropMissing();
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}
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/// <summary>
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/// Calculates the portfolio's asset allocation percentage over time. The series used to call this extension function should
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/// be the equity curve with the associated <see cref="Order"/> objects that go along with it.
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/// </summary>
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/// <param name="equityCurve">Equity curve series</param>
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/// <param name="orders">Orders associated with the equity curve</param>
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/// <returns></returns>
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public static Series<Symbol, double> AssetAllocations(Series<DateTime, double> equityCurve, List<Order> orders)
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{
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if (equityCurve.IsEmpty || orders.Count == 0)
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{
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return new Series<Symbol, double>(new Symbol[] { }, new double[] { });
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}
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// Convert PointInTimePortfolios to List because for some reason our AbsoluteHoldingsValue is multiplied by two whenever we GroupBy on the raw IEnumerable
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return AssetAllocations(PortfolioLooper.FromOrders(equityCurve, orders).ToList());
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}
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/// <summary>
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/// Calculates the asset allocation percentage over time.
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/// </summary>
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/// <param name="portfolios">Point in time portfolios</param>
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/// <returns>Series keyed by Symbol containing the percentage allocated to that asset over time</returns>
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public static Series<Symbol, double> AssetAllocations(List<PointInTimePortfolio> portfolios)
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{
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var portfolioHoldings = portfolios.GroupBy(x => x.Time)
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.Select(kvp => kvp.Last())
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.ToList();
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var totalPortfolioValueOverTime = (double)portfolioHoldings.Sum(x => x.Holdings.Sum(y => y.AbsoluteHoldingsValue));
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var holdingsBySymbolOverTime = new Dictionary<Symbol, double>();
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foreach (var portfolio in portfolioHoldings)
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{
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foreach (var holding in portfolio.Holdings)
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{
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if (!holdingsBySymbolOverTime.ContainsKey(holding.Symbol))
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{
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holdingsBySymbolOverTime[holding.Symbol] = (double)holding.AbsoluteHoldingsValue;
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continue;
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}
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holdingsBySymbolOverTime[holding.Symbol] = holdingsBySymbolOverTime[holding.Symbol] + (double)holding.AbsoluteHoldingsValue;
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}
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}
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return new Series<Symbol, double>(
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holdingsBySymbolOverTime.Keys,
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holdingsBySymbolOverTime.Values.Select(x => x / totalPortfolioValueOverTime).ToList()
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).DropMissing();
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}
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/// <summary>
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/// Strategy long/short exposure by asset class
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/// </summary>
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/// <param name="equityCurve">Equity curve</param>
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/// <param name="orders">Orders of the strategy</param>
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/// <param name="direction">Long or short</param>
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/// <returns>
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/// Frame keyed by <see cref="SecurityType"/> and <see cref="OrderDirection"/>.
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/// Returns a Frame of exposure per asset per direction over time
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/// </returns>
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public static Frame<DateTime, Tuple<SecurityType, OrderDirection>> Exposure(Series<DateTime, double> equityCurve, List<Order> orders, OrderDirection direction)
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{
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if (equityCurve.IsEmpty || orders.Count == 0)
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{
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return Frame.CreateEmpty<DateTime, Tuple<SecurityType, OrderDirection>>();
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}
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return Exposure(PortfolioLooper.FromOrders(equityCurve, orders).ToList(), direction);
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}
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/// <summary>
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/// Strategy long/short exposure by asset class
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/// </summary>
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/// <param name="portfolios">Point in time portfolios</param>
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/// <param name="direction">Long or short</param>
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/// <returns>
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/// Frame keyed by <see cref="SecurityType"/> and <see cref="OrderDirection"/>.
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/// Returns a Frame of exposure per asset per direction over time
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/// </returns>
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public static Frame<DateTime, Tuple<SecurityType, OrderDirection>> Exposure(List<PointInTimePortfolio> portfolios, OrderDirection direction)
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{
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// We want to add all of the holdings by asset class to a mock dataframe that is column keyed by SecurityType with
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// rows being DateTime and values being the exposure at that given time (as double)
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var holdingsByAssetClass = new Dictionary<SecurityType, List<KeyValuePair<DateTime, double>>>();
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var multiplier = direction == OrderDirection.Sell ? -1 : 1;
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foreach (var portfolio in portfolios)
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{
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List<KeyValuePair<DateTime, double>> holdings;
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if (!holdingsByAssetClass.TryGetValue(portfolio.Order.SecurityType, out holdings))
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{
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holdings = new List<KeyValuePair<DateTime, double>>();
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holdingsByAssetClass[portfolio.Order.SecurityType] = holdings;
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}
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var assets = portfolio.Holdings
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.Where(pointInTimeHoldings => pointInTimeHoldings.Symbol.SecurityType == portfolio.Order.SecurityType)
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.ToList();
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if (assets.Count > 0)
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{
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// Use the multiplier to flip the holdings value around
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var sum = (double)assets.Where(pointInTimeHoldings => multiplier * pointInTimeHoldings.HoldingsValue > 0)
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.Select(pointInTimeHoldings => pointInTimeHoldings.AbsoluteHoldingsValue)
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.Sum();
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holdings.Add(new KeyValuePair<DateTime, double>(portfolio.Time, sum / (double)portfolio.TotalPortfolioValue));
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}
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}
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var frame = Frame.CreateEmpty<DateTime, Tuple<SecurityType, OrderDirection>>();
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foreach (var kvp in holdingsByAssetClass)
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{
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// Skip Base asset class since we need it as a special value
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// (and it can't be traded on either way)
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if (kvp.Key == SecurityType.Base)
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{
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continue;
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}
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// Select the last entry of a given time to get accurate results of the portfolio's actual value.
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// Then, select only the long or short holdings.
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frame = frame.Join(
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new Tuple<SecurityType, OrderDirection>(kvp.Key, direction),
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new Series<DateTime, double>(kvp.Value.GroupBy(x => x.Key).Select(x => x.Last())) * multiplier
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);
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}
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// Equivalent to `pd.fillna(method='ffill').dropna(axis=1, how='all').dropna(how='all')`
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// First drops any missing SecurityTypes, then drops the rows with missing values
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// to get rid of any empty data prior to the first value.
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return frame.FillMissing(Direction.Forward)
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.DropSparseColumnsAll()
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.DropSparseRowsAll();
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}
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}
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}
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