| Overall Statistics |
|
Total Trades 4 Average Win 0.16% Average Loss -11.83% Compounding Annual Return -11.660% Drawdown 19.900% Expectancy -0.493 Net Profit -11.690% Sharpe Ratio -0.748 Probabilistic Sharpe Ratio 1.441% Loss Rate 50% Win Rate 50% Profit-Loss Ratio 0.01 Alpha -0.055 Beta -0.136 Annual Standard Deviation 0.103 Annual Variance 0.011 Information Ratio -0.742 Tracking Error 0.33 Treynor Ratio 0.568 Total Fees $140.00 Estimated Strategy Capacity $260000000.00 Lowest Capacity Asset GOOCV VP83T1ZUHROL Portfolio Turnover 0.73% |
# region imports
from AlgorithmImports import *
# endregion
class Algo_B(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 1, 1)
self.SetEndDate(2021,1,1)
self.SetCash(1000000)
self.AddEquity("GOOG", Resolution.Daily)
self.AddEquity("AMZN", Resolution.Daily)
self.loss_cap = 100000
self.init_cap = 1000000
self.stop = 0
self.goog_price = None
self.amzn_price = None
def OnData(self, data: Slice):
if self.goog_price is None:
self.goog_price = self.Securities["GOOG"].Price
self.LimitOrder("GOOG", 6000, 0.95*self.goog_price)
if self.amzn_price is None:
self.amzn_price = self.Securities["AMZN"].Price
self.LimitOrder("AMZN", -8000, 1.05*self.amzn_price)
if self.Portfolio.TotalPortfolioValue < self.init_cap - self.loss_cap: # Be careful to choose the typle of profit you use, please refer to the documentation
self.Liquidate()