| Overall Statistics |
|
Total Orders 29 Average Win 0.08% Average Loss -0.03% Compounding Annual Return -25.300% Drawdown 0.700% Expectancy 1.712 Net Profit -0.478% Sharpe Ratio -14.45 Sortino Ratio -19.176 Probabilistic Sharpe Ratio 0.000% Loss Rate 25% Win Rate 75% Profit-Loss Ratio 2.62 Alpha -0.251 Beta -0.036 Annual Standard Deviation 0.016 Annual Variance 0 Information Ratio 1.238 Tracking Error 0.123 Treynor Ratio 6.612 Total Fees $51.62 Estimated Strategy Capacity $12000000.00 Lowest Capacity Asset UNPH R735QTJ8XC9X Portfolio Turnover 20.01% |
#region imports
using System;
using System.Collections;
using System.Collections.Generic;
using System.Linq;
using System.Globalization;
using System.Drawing;
using QuantConnect;
using System.Text.RegularExpressions;
using QuantConnect.Algorithm.Framework;
using QuantConnect.Algorithm.Framework.Selection;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Algorithm.Framework.Execution;
using QuantConnect.Algorithm.Framework.Risk;
using QuantConnect.Algorithm.Selection;
using QuantConnect.Parameters;
using QuantConnect.Benchmarks;
using QuantConnect.Brokerages;
using QuantConnect.Util;
using QuantConnect.Interfaces;
using QuantConnect.Algorithm;
using QuantConnect.Indicators;
using QuantConnect.Data;
using QuantConnect.Data.Consolidators;
using QuantConnect.Data.Custom;
using QuantConnect.DataSource;
using QuantConnect.Data.Fundamental;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Notifications;
using QuantConnect.Orders;
using QuantConnect.Orders.Fees;
using QuantConnect.Orders.Fills;
using QuantConnect.Orders.Slippage;
using QuantConnect.Scheduling;
using QuantConnect.Securities;
using QuantConnect.Securities.Equity;
using QuantConnect.Securities.Future;
using QuantConnect.Securities.Option;
using QuantConnect.Securities.Forex;
using QuantConnect.Securities.Crypto;
using QuantConnect.Securities.Interfaces;
using QuantConnect.Storage;
using QCAlgorithmFramework = QuantConnect.Algorithm.QCAlgorithm;
using QCAlgorithmFrameworkBridge = QuantConnect.Algorithm.QCAlgorithm;
#endregion
using QuantConnect.DataSource;
namespace QuantConnect
{
public class KavoutCompositeFactorBundleAlgorithm : QCAlgorithm
{
private DateTime _time = DateTime.MinValue;
public override void Initialize()
{
SetStartDate(2003, 1, 10);
SetEndDate(2003, 1, 15);
SetCash(100000);
AddUniverse(MyCoarseFilterFunction);
UniverseSettings.Resolution = Resolution.Minute;
}
private IEnumerable<Symbol> MyCoarseFilterFunction(IEnumerable<CoarseFundamental> coarse)
{
return (from c in coarse
where c.HasFundamentalData
orderby c.DollarVolume descending
select c.Symbol).Take(100);
}
public override void OnData(Slice slice)
{
if (_time > Time) return;
// Accessing Data
var points = slice.Get<KavoutCompositeFactorBundle>();
var sortedByScore = from s in points.Values
orderby TotalScore(s) descending
select s.Symbol.Underlying;
var longSymbols = sortedByScore.Take(10).ToList();
var shortSymbols = sortedByScore.TakeLast(10).ToList();
foreach (var kvp in Portfolio)
{
var symbol = kvp.Key;
if (kvp.Value.Invested &&
!longSymbols.Contains(symbol) &&
!shortSymbols.Contains(symbol))
{
Liquidate(symbol);
}
}
var targets = new List<PortfolioTarget>();
targets.AddRange(longSymbols.Select(symbol => new PortfolioTarget(symbol, 0.05m)));
targets.AddRange(shortSymbols.Select(symbol => new PortfolioTarget(symbol, -0.05m)));
SetHoldings(targets);
_time = Expiry.EndOfDay(Time);
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
foreach(var security in changes.AddedSecurities)
{
// Requesting Data
var kavoutCompositeFactorBundleSymbol = AddData<KavoutCompositeFactorBundle>(security.Symbol).Symbol;
// Historical Data
var history = History(new[]{kavoutCompositeFactorBundleSymbol}, 60, Resolution.Daily);
Debug($"We got {history.Count()} items from our history request");
}
}
private decimal TotalScore(KavoutCompositeFactorBundle value)
{
/// Return the total score to integrate overall likelihood to outcompete, take equal weighting for each factor
return value.Growth + value.ValueFactor + value.Quality + value.Momentum + value.LowVolatility;
}
}
}