Overall Statistics
Total Trades
3701
Average Win
0.75%
Average Loss
-1.77%
Compounding Annual Return
-46.110%
Drawdown
91.600%
Expectancy
-0.083
Net Profit
-90.120%
Sharpe Ratio
-0.826
Probabilistic Sharpe Ratio
0.000%
Loss Rate
35%
Win Rate
65%
Profit-Loss Ratio
0.42
Alpha
-0.391
Beta
1.023
Annual Standard Deviation
0.365
Annual Variance
0.133
Information Ratio
-1.113
Tracking Error
0.349
Treynor Ratio
-0.295
Total Fees
$4408.00
Estimated Strategy Capacity
$3800000.00
Lowest Capacity Asset
TSLA UNU3P8Y3WFAD
 
# region imports
from AlgorithmImports import *
# endregion



class MyAlgorithm(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2015, 1, 1)
        self.SetEndDate(2022, 1, 1)
        # Set the cash we'd like to use for our strategy
        self.SetCash(10000)
        self.trade_quantity=100

        # Set the equity we'd like to trade
        self.symbol = self.AddEquity("TSLA").Symbol

        # Set the period for the RSI indicator
        self.rsi_period = 14

        # Create the RSI indicator
        self.rsi = self.RSI(self.symbol, self.rsi_period)

    def OnData(self, data):
        # Check if we have enough data to calculate the RSI indicator
        if not self.rsi.IsReady:
            return

        # Check if the RSI is above 70 (overbought)
        if self.rsi.Current.Value > 72:
            # If the RSI is overbought, place a sell order
            self.Liquidate()
        # Check if the RSI is below 30 (oversold)
        elif self.rsi.Current.Value < 28:
            # If the RSI is oversold, place a buy order
            self.MarketOrder(self.symbol, self.trade_quantity)