/// <summary>
/// Calculates the total gain / total loss ratio.
/// Depends on 4 cases, and the result will be presented depending on those.
/// 1. If we have no trades, profit factor is 0.
/// 2. If we only have winning trades profit factor gets capped to 100.
/// 3. If we only have losingtrades profit factor is 0.
/// 4. If we have both winning and losing trades, profit factor is calculated.
/// </summary>
public double ProfitFactor(TradeManager tradeList)
{
double lossLosingTrades = 0;
double gainWinningTrades = 0;
SummerizeProfit(ref lossLosingTrades, ref gainWinningTrades, tradeList);
return(ReturnProfitfactorFromRules(lossLosingTrades, gainWinningTrades));
}
public int NumberOfFinishedTrades(TradeManager tradeList)
{
int nbrFinishedTrades = 0;
foreach (var item in tradeList.GetTradeList)
{
if (item.Finished)
{
nbrFinishedTrades++;
}
}
return(nbrFinishedTrades);
}
public int NbrOfWinners(TradeManager tradeList)
{
int nbrWinners = 0;
foreach (var item in tradeList.GetTradeList)
{
if (item.ProfitTrade() > 0 && item.Finished)
{
nbrWinners++;
}
}
return(nbrWinners);
}
public double TotalLoss(TradeManager tradelist)
{
double totalLoss = 0;
foreach (var item in tradelist.GetTradeList)
{
if (item.ProfitTrade() < 0 && item.Finished)
{
totalLoss += item.ProfitTrade() / item.Sell * _valuePerPoint;
}
}
return(Math.Abs(totalLoss));
}
public double TotalGain(TradeManager tradelist)
{
double totalGain = 0;
foreach (var item in tradelist.GetTradeList)
{
if (item.ProfitTrade() > 0 && item.Finished)
{
totalGain += item.ProfitTrade() / item.Sell * _valuePerPoint;
}
}
return(totalGain);
}
public double AverageProfit(TradeManager tradeList)
{
double sumProfitInSek = 0;
foreach (var item in tradeList.GetTradeList)
{
sumProfitInSek += item.ProfitTrade() / item.Sell * _valuePerPoint;
}
if (tradeList.NbrFinishedTrades() == 0)
{
return(0);
}
else
{
return(sumProfitInSek / tradeList.NbrFinishedTrades());
}
}
public double StandardDeviation(TradeManager tradeList)
{
double sumSquaredDevFromMean = 0;
foreach (var item in tradeList.GetTradeList)
{
sumSquaredDevFromMean += Math.Pow(item.ProfitTrade() / item.Sell * _valuePerPoint - AverageProfit(tradeList), 2);
}
if (tradeList.NbrFinishedTrades() == 0)
{
return(0);
}
else
{
return(Math.Sqrt(sumSquaredDevFromMean / tradeList.NbrFinishedTrades()));
}
}
public double AverageLoss(TradeManager tradeList)
{
double nbrLosers = 0;
double totalLoss = 0;
foreach (var item in tradeList.GetTradeList)
{
if (item.ProfitTrade() < 0 && item.Finished)
{
totalLoss += item.ProfitTrade() / item.Sell * _valuePerPoint;
nbrLosers++;
}
}
if (nbrLosers == 0)
{
return(0);
}
else
{
return(Math.Abs(totalLoss / nbrLosers));
}
}
public double AverageGain(TradeManager tradeList)
{
double nbrWinners = 0;
double totalGain = 0;
foreach (var item in tradeList.GetTradeList)
{
if (item.ProfitTrade() > 0 && item.Finished)
{
totalGain += item.ProfitTrade() / item.Sell * _valuePerPoint;
nbrWinners++;
}
}
if (nbrWinners == 0)
{
return(0);
}
else
{
return(totalGain / nbrWinners);
}
}
public OneStockBackTestData GetOneStockBacktest(TradeManager _tradeManager, List <DailyDataPoint> _dataList, string algoName, string stockName, DateTime startDate, DateTime endDate)
{
var backTestData = new OneStockBackTestData();
backTestData.AlgoName = algoName;
backTestData.Ticker = stockName;
backTestData.TimeSpanStart = startDate.ToShortDateString();
backTestData.TimeSpanFinish = endDate.ToShortDateString();
backTestData.PortfolioValueStart = PortfolioValueStart;
backTestData.PortfolioValueFinish = PortfolioValue;
backTestData.ReturnSek = ReturnSek();
backTestData.ReturnProcent = ReturnProcent();
backTestData.NumberOfFinishedTrades = NumberOfFinishedTrades(_tradeManager);
backTestData.Winners = WinnersPercent(_tradeManager);
backTestData.TotalGain = TotalGain(_tradeManager);
backTestData.TotalLoss = TotalLoss(_tradeManager);
backTestData.AverageGain = AverageGain(_tradeManager);
backTestData.AverageLoss = AverageLoss(_tradeManager);
backTestData.ProfitFactor = ProfitFactor(_tradeManager);
backTestData.Cagr = Cagr(_dataList, startDate, endDate);
backTestData.SharpRatio = SharpRatio(_tradeManager, _dataList, startDate, endDate);
backTestData.MaxDrawDownPercent = MaxDrawDownProp;
return(backTestData);
}
private double SharpRatioFromRules(double top, double bottom, TradeManager tradeList)
{
// If only one trade there is no variance and sharp ratio is useless, ie bottom is 0.
if (top > 0 && bottom == 0)
{
return(100);
}
else if (top < 0 && bottom == 0)
{
return(-100);
}
else if (NumberOfFinishedTrades(tradeList) == 0)
{
return(0);
}
else if (top <= -100)
{
return(-100);
}
else
{
return(top / bottom);
}
}
public NegMaImpuls(List <DailyDataPoint> dataList, int index, TradeManager tradeManager)
{
_dataList = dataList;
_index = index;
_tradeManager = tradeManager;
}
/// <summary>
/// Portfolio value after a trade
/// </summary>
public double ChangePortFolValue(TradeManager tradeList, int index)
{
_portfolioValue += (tradeList.GetTradeList[index].ProfitTrade() / tradeList.GetTradeList[index].Sell) * _valuePerPoint;
return(_portfolioValue);
}
private void SummerizeProfit(ref double lossLosingTrades, ref double gainWinningTrades, TradeManager tradeList)
{
foreach (var item in tradeList.GetTradeList)
{
if (item.ProfitTrade() > 0 && item.Finished)
{
gainWinningTrades += item.ProfitTrade() / item.Sell * _valuePerPoint;
}
else if (item.ProfitTrade() < 0 && item.Finished)
{
lossLosingTrades += item.ProfitTrade() / item.Sell * _valuePerPoint;
}
}
}
public AlgoPicker(List <DailyDataPoint> dataList, string nameOFAlgo, TradeManager tradeManager)
{
_dataList = dataList;
_nameOfAlgo = nameOFAlgo;
_tradeManager = tradeManager;
}
private void InitializeBacktest()
{
_tradeManager = new TradeManager();
_backtest = new Backtest(100000, 30000);
}