Overall Statistics
Total Orders
561
Average Win
1.46%
Average Loss
-1.50%
Compounding Annual Return
9.381%
Drawdown
36.000%
Expectancy
0.129
Start Equity
100000
End Equity
171300.04
Net Profit
71.300%
Sharpe Ratio
0.314
Sortino Ratio
0.324
Probabilistic Sharpe Ratio
3.980%
Loss Rate
43%
Win Rate
57%
Profit-Loss Ratio
0.97
Alpha
0
Beta
0
Annual Standard Deviation
0.207
Annual Variance
0.043
Information Ratio
0.42
Tracking Error
0.207
Treynor Ratio
0
Total Fees
$1412.10
Estimated Strategy Capacity
$20000000.00
Lowest Capacity Asset
CE T5JLBNU20TPH
Portfolio Turnover
5.48%
 
#region imports
    using System;
    using System.Collections;
    using System.Collections.Generic;
    using System.Linq;
    using System.Globalization;
    using System.Drawing;
    using QuantConnect;
    using QuantConnect.Algorithm.Selection;
    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.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.Positions;
    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

namespace QuantConnect.Algorithm.CSharp
{
    public class ConservativeRebalancingAlphaModel : AlphaModel
    {
        private int _vLookback;
        private int _mLookback;
        private List<Symbol> _symbols;
        private int _month;

        public ConservativeRebalancingAlphaModel(int vLookback, int mLookback)
        {
            _vLookback = vLookback;
            _mLookback = mLookback;
            _symbols = new List<Symbol>();
            _month = -1;
        }

        public override void OnSecuritiesChanged(QCAlgorithmFramework algorithm, SecurityChanges changes)
        {
            foreach (var added in changes.AddedSecurities)
            {
                _symbols.Add(added.Symbol);
            }

            foreach (var removed in changes.RemovedSecurities)
            {
                _symbols.Remove(removed.Symbol);
                algorithm.Liquidate(removed.Symbol);
            }
        }

        public override IEnumerable<Insight> Update(QCAlgorithmFramework algorithm, Slice data)
        {
            if (algorithm.Time.Day != 1 || algorithm.Time.Month == _month)
            {
                algorithm.Log($"List of constituents: {string.Join(", ", _symbols.Select(s => s.Value))}");
                return Enumerable.Empty<Insight>();
            }

            _month = algorithm.Time.Month;

            var alphas = new Dictionary<Symbol, decimal>();

            foreach (var symbol in _symbols)
            {
                if (!data.ContainsKey(symbol))
                {
                    continue;
                }

                var roc = algorithm.ROC(symbol, 1, Resolution.Daily);
                var std = algorithm.STD(symbol, _vLookback, Resolution.Daily);
                var momp = algorithm.MOMP(symbol, _mLookback, Resolution.Daily);

                var history = algorithm.History(symbol, Math.Max(_vLookback, _mLookback)+1, Resolution.Daily);

                foreach (var row in history)
                {
                    roc.Update(row.EndTime, row.Close);
                    std.Update(row.EndTime, roc.Current.Value);
                    momp.Update(row.EndTime, row.Close);
                }
                // Log the readiness of the indicators
                algorithm.Log($"Indicators for {symbol} at {algorithm.Time}: ROC ready = {roc.IsReady}, STD ready = {std.IsReady}, MOMP ready = {momp.IsReady}");
                alphas[symbol] = momp.Current.Value / std.Current.Value;
                algorithm.Log($"Alpha value for {symbol}: {alphas[symbol]}");
            }

            var selected = alphas.OrderByDescending(x => x.Value).Take(5).Select(x => x.Key);
            // Log the selected symbols
            algorithm.Debug($"Selected symbols at {algorithm.Time}: {string.Join(", ", selected)}");

            // int daysInMonth = DateTime.DaysInMonth(algorithm.Time.Year, algorithm.Time.Month);
            // TimeSpan lifespan = TimeSpan.FromDays(daysInMonth - 1);

            return selected.Select(symbol => new Insight(symbol, TimeSpan.FromDays(2), InsightType.Price, InsightDirection.Up));
        }
    }
}
#region imports
    using System;
    using System.Collections;
    using System.Collections.Generic;
    using System.Linq;
    using System.Globalization;
    using System.Drawing;
    using QuantConnect;
    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

namespace QuantConnect.Algorithm.CSharp
{
    public class ConservativeAlgorithm : QCAlgorithm
    {
        public override void Initialize()
        {                       
            SetStartDate(2018, 1, 1);
            SetEndDate(2024, 1, 1);
            SetCash(100000);

            // Set number days to trace back
            int vLookback = 36; 
            int mLookback = 12; 
            // SetWarmUp(40);

            SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin);

            // SPY 500 companies
            string spy = "SPY";
            UniverseSettings.Resolution = Resolution.Daily;
            UniverseSettings.Schedule.On(DateRules.MonthStart());
            AddUniverseSelection(new ETFConstituentsUniverseSelectionModel(spy));
            SetAlpha(new ConservativeRebalancingAlphaModel(vLookback, mLookback));
            // Set the portfolio construction to rebalance on the first trading day of each month
            Settings.RebalancePortfolioOnInsightChanges = false;
            Settings.RebalancePortfolioOnSecurityChanges = false;
            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel(
                time =>
                {
                    // Rebalance on the first trading day of each month
                    if (time.Day == 1)
                    {
                        return time;
                    }
                    return null;
                }));
            SetRiskManagement(new NullRiskManagementModel());
            SetExecution(new ImmediateExecutionModel());
        }
    }
}