Overall Statistics
Total Trades
209
Average Win
0%
Average Loss
-0.07%
Compounding Annual Return
-45.459%
Drawdown
5.000%
Expectancy
-1
Net Profit
-4.966%
Sharpe Ratio
-3.082
Probabilistic Sharpe Ratio
0.015%
Loss Rate
100%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
-0.317
Beta
0.091
Annual Standard Deviation
0.084
Annual Variance
0.007
Information Ratio
-5.793
Tracking Error
0.152
Treynor Ratio
-2.849
Total Fees
$212.55
Estimated Strategy Capacity
$2000.00
Lowest Capacity Asset
BTC TLQHZ0DZBGPX
 
import numpy as np

### <summary>
### Basic template algorithm simply initializes the date range and cash. This is a skeleton
### framework you can use for designing an algorithm.
### </summary>
class BasicTemplateAlgorithm(QCAlgorithm):
    '''Basic template algorithm simply initializes the date range and cash'''

    def Initialize(self):
        self.SetStartDate(2021,12,1)  #Set Start Date
        self.SetEndDate(2021,12,31)    #Set End Date
        self.SetCash(6000)           #Set Strategy Cash
        self.AddEquity("BTC", Resolution.Minute)
        #self.SetBrokerageModel(BrokerageName.Bitfinex) 
        self.rsi = self.RSI("BTC", 7)
        self.BuyIn = 0.0
        CurrentPrice = self.Securities["BTC"].Price
        self.BuyIn = CurrentPrice
        take_profit = 0.2

    def OnData(self, data):
        
        if not self.rsi.IsReady: 
            return
    
        if self.rsi.Current.Value < 30 and self.Portfolio["BTC"].Invested <= 0:
            self.MarketOrder("BTC", 10)
            self.Debug("BO order was placed")
            
        if self.rsi.Current.Value < 20:
            self.MarketOrder("BTC", 20)
            self.Debug("SO order was placed")
            
        if self.rsi.Current.Value > 40:
            self.Liquidate()
            
            
            
        #if CurrentPrice > self.BuyIn*(1 + take_profit):
            #self.SetHoldings("AAPL", 0) # A market sell
            #return
            
    def OnEndOfDay(self):
        self.Plot("Indicators","RSI", self.rsi.Current.Value)