| Overall Statistics |
|
Total Orders 2 Average Win 0% Average Loss 0% Compounding Annual Return 257.866% Drawdown 3.000% Expectancy 0 Start Equity 10000000 End Equity 10648949 Net Profit 6.489% Sharpe Ratio 11.695 Sortino Ratio 32.393 Probabilistic Sharpe Ratio 98.670% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0.994 Beta 0.956 Annual Standard Deviation 0.13 Annual Variance 0.017 Information Ratio 18.618 Tracking Error 0.052 Treynor Ratio 1.584 Total Fees $150.50 Estimated Strategy Capacity $4600000000.00 Lowest Capacity Asset NQ Y6URRFPZ86BL Portfolio Turnover 8.43% |
# region imports
from AlgorithmImports import *
# endregion
class FocusedFluorescentYellowGoshawk(QCAlgorithm):
def initialize(self):
self.set_start_date(2023, 1, 7)
self.set_end_date(2023, 1, 24)
self.set_cash(10000000)
tickers = [
Futures.Indices.NASDAQ_100_E_MINI,
Futures.Indices.SP_500_E_MINI
]
self._futures = []
for ticker in tickers:
future = self.add_future(ticker)
self.log(f"{future.symbol}: {future.symbol_properties.contract_multiplier}")
self._futures.append(future)
def on_data(self, data):
#q0 = self.calculate_order_quantity(self._futures[0].mapped, 0.1)
#q1 = self.calculate_order_quantity(self._futures[1].mapped, 0.1)
if not self.portfolio.invested:
self.market_order(self._futures[0].mapped, self._futures[1].symbol_properties.contract_multiplier)
self.market_order(self._futures[1].mapped, -self._futures[0].symbol_properties.contract_multiplier)