Overall Statistics
Total Trades
10
Average Win
6.22%
Average Loss
-1.16%
Compounding Annual Return
28.603%
Drawdown
3.100%
Expectancy
1.538
Net Profit
8.850%
Sharpe Ratio
1.552
Loss Rate
60%
Win Rate
40%
Profit-Loss Ratio
5.35
Alpha
0
Beta
13.075
Annual Standard Deviation
0.115
Annual Variance
0.013
Information Ratio
1.433
Tracking Error
0.115
Treynor Ratio
0.014
Total Fees
$4.00
 
class ForexIndicator(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2017, 6, 1)
        self.SetEndDate(2017, 10, 1)
        self.SetCash(5000)
        self.forex = self.AddForex("EURUSD", Resolution.Daily, Market.FXCM)
        self.SetBrokerageModel(BrokerageName.FxcmBrokerage)
        self.psar = self.PSAR(self.forex.Symbol, 0.02, 0.02, 0.2, Resolution.Daily)
        
        
        IndicatorPlot = Chart("Trade Plot")
        IndicatorPlot.AddSeries(Series("PSAR", SeriesType.Scatter, 0))
        IndicatorPlot.AddSeries(Series("Price", SeriesType.Line, 0))
        IndicatorPlot.AddSeries(Series("Buy", SeriesType.Scatter, 0))
        IndicatorPlot.AddSeries(Series("Sell", SeriesType.Scatter, 0))
        self.AddChart(IndicatorPlot)
        
    def OnData(self,data):
        if not self.psar.IsReady: return
        price = self.Securities['EURUSD'].Price
        self.Plot("Trade Plot", "PSAR", self.psar.Current.Value)
        self.Plot("Trade Plot", "Price", price)
        if not self.Portfolio.Invested and self.psar.Current.Value < price:
            
                self.MarketOrder(self.forex.Symbol,10000)
                self.Plot("Trade Plot", "Buy", price)
                
        elif self.Portfolio.Invested and self.psar.Current.Value > price:
                
                self.Liquidate()
                self.Plot("Trade Plot", "Sell", price)