Overall Statistics
Total Trades
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Net Profit
0%
Sharpe Ratio
0
Probabilistic Sharpe Ratio
0%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
-0.76
Tracking Error
0.062
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
#region imports
from AlgorithmImports import *
#endregion

class CarryTrading(QCAlgorithm):

    def Initialize(self):

        self.Pair_1 = "USDDKK"
        self.Pair_2 = "USDPLN"
        self.SetStartDate (2000, 3, 3) 
        self.SetEndDate(2022,5,24)
        self.SetCash(1000000)  
        self.SetBrokerageModel(BrokerageName.OandaBrokerage)
        self.EURSEK = self.AddForex(self.Pair_1, Resolution.Daily, Market.Oanda)
        self.GBPSGD = self.AddForex(self.Pair_2, Resolution.Daily, Market.Oanda)
        self.symbols = [self.Pair_1, self.Pair_2]
        self.prevMinPriceVariation = { symbol : RollingWindow[QuoteBar](20) for symbol in self.symbols }
        #added bool statement:
        self.added_rw = False
        symbol_properties = self.Securities[self.Pair_1].SymbolProperties
        MinimumPriceVariation = symbol_properties.MinimumPriceVariation
        
    def OnData(self,data):

        for symbol in self.symbols:
            if data.ContainsKey(symbol):
                self.prevMinPriceVariation[symbol].Add( data[symbol] )
        
        if not all([ window.IsReady for window in self.prevMinPriceVariation.values() ]):
            return   

        Pair1_Variation = self.prevMinPriceVariation[self.Pair_1]
        quote_bar = Pair1_Variation[6]
        self.Quit(f"QuoteBar low: {quote_bar.Bid.Low}; QuoteBar high: {quote_bar.Ask.High}")
        return

        Pair1_6D = Pair1_Variation[6].MinimumPriceVariation
        Pair1_5D = Pair1_variation[5].MinimumPriceVariation
        Pair1_4D = Pair1_Variation[4].MinimumPriceVariation
        Pair1_3D = Pair1_Variation[3].MinimumPriceVariation        
        Pair1_2D = Pair1_Variation[2].MinimumPriceVariation
        Pair1_1D = Pair1_Variation[1].MinimumPriceVariation
        Pair1_0D = Pair1_Variation[0].MinimumPriceVariation

        Pair2_Variation = self.prevMinPriceVariation[self.Pair_2]
        Pair2_6D = Pair1_Variation[6].MinimumPriceVariation
        Pair2_5D = Pair1_Variation[5].MinimumPriceVariation
        Pair2_4D = Pair1_Variation[4].MinimumPriceVariation
        Pair2_3D = Pair1_Variation[3].MinimumPriceVariation        
        Pair2_2D = Pair1_Variation[2].MinimumPriceVariation
        Pair2_1D = Pair1_Variation[1].MinimumPriceVariation
        Pair2_0D = Pair1_Variation[0].MinimumPriceVariation

        self.added_rw = True

        AvgPair1_Variation = (Pair1_0D + Pair1_1D + Pair1_2D + Pair1_3D + Pair1_4D +Pair1_5D + Pair1_6D) / 7
        AvgPair2_Variation = (Pair2_0D + Pair2_1D + Pair2_2D + Pair2_3D + Pair2_4D +Pair2_5D + Pair2_6D) / 7

        if self.added_rw is True: 
            self.Log( str+(AvgPair1_Variation))