Overall Statistics
Total Trades
23
Average Win
20.24%
Average Loss
-4.63%
Compounding Annual Return
6.993%
Drawdown
31.800%
Expectancy
2.418
Net Profit
188.176%
Sharpe Ratio
0.55
Probabilistic Sharpe Ratio
2.431%
Loss Rate
36%
Win Rate
64%
Profit-Loss Ratio
4.37
Alpha
0.07
Beta
-0.058
Annual Standard Deviation
0.117
Annual Variance
0.014
Information Ratio
-0.117
Tracking Error
0.221
Treynor Ratio
-1.115
Total Fees
$23.00
from System.Drawing import Color

class Crossover_Algo(QCAlgorithm):
    
    def Initialize(self):
        self.SetStartDate(2005, 1, 1)                       # the starting date for our backtest
        #self.SetEndDate(2020, 2, 1)                        # the ending date for our backtest (if no date, then it will test up until today)
        self.start_value = 5000                             # define the amount of starting cash
        self.SetCash(self.start_value)                      # initialize our wallet
        self.EQY = "SPY"                                    # define the stock ticker
        self.AddEquity(self.EQY, Resolution.Daily)          # add a stock to the list of those we want to trade, and how often to pull data
        self.starting_price = None
        self.spy_portfolio = None
        self.period1 = 20
        self.period2 = 200
        
        # set up our sma indicators
        self.sma_short = self.SMA(self.EQY, self.period1, Resolution.Daily) 
        self.sma_long = self.SMA(self.EQY, self.period2, Resolution.Daily) 
        

        # need to give the indicators data before running the algorithm
        self.SetWarmUp(self.period2)
    
        # set up a chart to display our buy and sell dates
        self.stockPlot = Chart('Equity')
        # self.SPY_candles  = Series(self.EQY, SeriesType.Candle)
        # self.stockPlot.AddSeries(self.SPY_candles)
        self.stockPlot.AddSeries(Series('Buy', SeriesType.Scatter, '$', Color.Green, ScatterMarkerSymbol.Triangle))
        self.stockPlot.AddSeries(Series('Sell', SeriesType.Scatter, '$', Color.Red, ScatterMarkerSymbol.TriangleDown))
        self.AddChart(self.stockPlot)
   
    # this is for plotting the relative change of each stock and our portfolio value   
    def OnEndOfDay(self):
        current_portfolio = self.Portfolio.TotalPortfolioValue
        change_portfolio = (current_portfolio - self.start_value )/ self.start_value
        self.Plot("Percent Change","Portfolio Change", change_portfolio)
        
        # # if we haven't gotten the starting price, then get it
        if self.starting_price == None:
            self.starting_price = self.Securities[self.EQY].Price
        
        start_price = self.starting_price
        price = self.Securities[self.EQY].Price
        self.change_in_price = (price - start_price)/ start_price
        self.Plot("Percent Change", self.EQY + " Change", self.change_in_price)
        
        
    def OnData(self, data):
        
        # # if the indicators aren't ready, don't do anything
        if self.IsWarmingUp: return
        
        daily_low_price  = self.Securities[self.EQY].Low
        daily_high_price = self.Securities[self.EQY].High
        
        # # extract the current value of each indicator
        sma_short = self.sma_short.Current.Value
        sma_long = self.sma_long.Current.Value
        
        sma_pct_delta = (sma_short-sma_long)/sma_long
        
        # determine the time to open and close the position
        open_signal = sma_short > sma_long
        #buy_signal = sma_signal < -0.01 
        close_signal = sma_short < sma_long
        #close_signal = sma_signal > 0.02
        
        
        if (open_signal):
            if not self.Portfolio[self.EQY].Invested:
                self.SetHoldings(self.EQY, 1)       # if the price is above the 20-day moving average, buy the stock
                self.Plot("Equity", 'Buy', self.Securities[self.EQY].Price)
        elif (close_signal):
            if self.Portfolio[self.EQY].Invested:
                self.SetHoldings(self.EQY, 0)        # otherwise exit the position
                self.Plot("Equity", 'Sell', self.Securities[self.EQY].Price)
        
        
        # plotting stuff
        # self.SPY_candles.AddPoint(self.Time + timedelta(minutes=1), self.Securities[self.EQY].Open)
        # self.SPY_candles.AddPoint(self.Time + timedelta(minutes=2), self.Securities[self.EQY].High)
        # self.SPY_candles.AddPoint(self.Time + timedelta(minutes=3), self.Securities[self.EQY].Low)
        # self.SPY_candles.AddPoint(self.Time + timedelta(minutes=4), self.Securities[self.EQY].Close)
        self.Plot("Equity",self.EQY,self.Securities[self.EQY].Price)
        self.Plot("Equity","SMA_short", sma_short)
        self.Plot("Equity","SMA_long", sma_long)
        
        self.Plot("sma pct delta","sma_pct_delta", sma_pct_delta)
        
        
    def OnOrderEvent(self, orderEvent):
        
        if orderEvent.Status != OrderStatus.Filled:
            return
        
        self.Log(f"Order Executed! Time: {self.Time}, Price: {self.Securities[self.EQY].Price}, SMA: {self.sma_short.Current.Value}")