public MixtureEval(Mixture mixture, double fitness)
: base(mixture.Database)
{
MixtureId = mixture.Id;
Fitness = fitness;
Database.Store(this);
}
public static List <Day> Backtest(Database db, Mixture mixture, string symbol, DateTime startDate, DateTime endDate,
double initialEquity, double marginFactor, double tradeCost)
{
var preloadStart = startDate.AddYears(-1);
var allBars = new DataSeries <Bar>(symbol, db.QueryAll <DbBar>(x => x.Symbol == symbol, "Timestamp")
.Select(DataPreprocessing.DbBarToBar));
var bars = DataPreprocessing.TrimToWindow(allBars, DataPreprocessing.GetWindow(preloadStart, endDate, allBars));
var data = DataPreprocessing.LoadTrainingSet(db, symbol, preloadStart, endDate, Signals.Null);
var predictor = new MixturePredictor(mixture, data);
Debug.Assert(bars.Length == data.Input.ColumnCount);
var backtestStartIndex = bars.ToList().FindIndex(x => x.Timestamp >= startDate);
// preload
for (int t = 0; t < backtestStartIndex; t++)
{
predictor.Predict(t);
}
int totalPredictions = 0;
int correctPredictions = 0;
// backtest
var account = new VAccount(initialEquity, marginFactor, tradeCost);
for (int t = backtestStartIndex + 1; t < bars.Length; t++)
{
var prediction = predictor.Predict(t - 1);
Debug.Assert(prediction != 0);
var wasCorrect = ActOnSignal(bars[t - 1], bars[t], prediction, account, symbol);
totalPredictions++;
if (wasCorrect)
{
correctPredictions++;
}
}
double correctPct = (double)correctPredictions / totalPredictions;
return(null);
}
static MixtureEval EvaluateMixture(Mixture m, DataSet data)
{
using (var mixturePredictor = new MixturePredictor(m, data))
return(new MixtureEval(m, ComputeFitness(mixturePredictor, data)));
}
