| Overall Statistics |
|
Total Orders 84 Average Win 0.86% Average Loss -0.76% Compounding Annual Return 37.615% Drawdown 29.100% Expectancy 0.545 Start Equity 100000 End Equity 137735.79 Net Profit 37.736% Sharpe Ratio 1.037 Sortino Ratio 0.977 Probabilistic Sharpe Ratio 46.614% Loss Rate 27% Win Rate 73% Profit-Loss Ratio 1.12 Alpha 0.148 Beta 0.888 Annual Standard Deviation 0.282 Annual Variance 0.079 Information Ratio 0.941 Tracking Error 0.139 Treynor Ratio 0.328 Total Fees $114.14 Estimated Strategy Capacity $1500000000.00 Lowest Capacity Asset MSFT R735QTJ8XC9X Portfolio Turnover 1.00% Drawdown Recovery 110 |
# region imports
from AlgorithmImports import *
# endregion
class VirtualMagentaBeaver(QCAlgorithm):
def initialize(self):
self.set_start_date(2020, 1, 1)
self.set_end_date(2021, 1, 1)
self.set_cash(100000)
# Universe: Top 10 most liquid US equities
self.universe_settings.resolution = Resolution.DAILY
self._universe = self.add_universe(self.universe.top(10))
# Rebalance monthly on the first trading day
self.schedule.on(
self.date_rules.month_start('SPY'),
self.time_rules.midnight,
self._rebalance
)
def _rebalance(self):
symbols = list(self._universe.selected)
if not symbols:
return
targets = [PortfolioTarget(symbol, 1.0 / len(symbols)) for symbol in symbols]
self.set_holdings(targets, True)