public override double GetSchemeProfit(StockHistorySet testData, AbstractPredictor Predictor, int today, int daysToPredict)
{
double profit = 0D;
foreach (StockHistory stockHistory in testData.AllStockHistories)
{
double startV = stockHistory.Closes[today];
double actualEndV = stockHistory.Closes[today + daysToPredict];
profit += (actualEndV - startV);
}
return profit / testData.AllStockHistories.Count;
}
public override double GetSchemeProfit(StockHistorySet testData, AbstractPredictor Predictor, int today, int daysToPredict)
{
var stocksInOrder = testData.AllStockHistories.OrderByDescending(x => Predictor.PredictValue(x, today, daysToPredict) / x.Closes[today]).ToArray();
var tenBest = stocksInOrder.Take(10).ToArray();
double profit = 0D;
foreach (StockHistory stockHistory in tenBest)
{
double startV = stockHistory.Closes[today];
double actualEndV = stockHistory.Closes[today + daysToPredict];
profit += (actualEndV - startV);
}
return profit / 10;
}
public override double GetSchemeProfit(StockHistorySet testData, AbstractPredictor Predictor, int today, int daysToPredict)
{
double profit = 0D;
// If prediction is higher, buy 1 unit. Otherwise, short 1 unit
foreach (StockHistory stockHistory in testData.AllStockHistories)
{
double startV = stockHistory.Closes[today];
double predictedEndV = Predictor.PredictValue(stockHistory, today, daysToPredict);
double actualEndV = stockHistory.Closes[today + daysToPredict];
if (Predictor is RandomPredictor)
{
; ;
}
if (predictedEndV > startV)
profit += (actualEndV - startV);
else
profit += (startV - actualEndV);
}
return profit / testData.AllStockHistories.Count;
}
/// <summary> /// How good the Predictor is with this purchasing scheme. Specifically, if you invested $1 in it, how much would you get back. /// </summary> /// <returns>The profit of this scheme</returns> public abstract double GetSchemeProfit(StockHistorySet testData, AbstractPredictor Predictor, int today, int daysToPredict);
