| Overall Statistics |
|
Total Orders 420 Average Win 1.61% Average Loss -1.71% Compounding Annual Return 1.395% Drawdown 24.600% Expectancy 0.082 Start Equity 100000 End Equity 127452.00 Net Profit 27.452% Sharpe Ratio -0.127 Sortino Ratio -0.064 Probabilistic Sharpe Ratio 0.002% Loss Rate 44% Win Rate 56% Profit-Loss Ratio 0.94 Alpha -0.016 Beta 0.198 Annual Standard Deviation 0.068 Annual Variance 0.005 Information Ratio -0.317 Tracking Error 0.138 Treynor Ratio -0.044 Total Fees $2438.28 Estimated Strategy Capacity $390000000.00 Lowest Capacity Asset SPY R735QTJ8XC9X Portfolio Turnover 6.55% |
#region imports
from AlgorithmImports import *
#endregion
# https://quantpedia.com/Screener/Details/41
class TurnOfMonthSPY(QCAlgorithm):
def initialize(self):
self.set_start_date(2001, 1, 11) # Set Start Date
self.set_end_date(2018, 7, 11) # Set End Date
self.set_cash(100000) # Set Strategy Cash
self._days = 0
self._spy = self.add_equity("SPY", Resolution.DAILY).symbol
# This event triggers the algorithm to purchase during the last trading day of the month
self.schedule.on(
self.date_rules.month_end(self._spy),
self.time_rules.after_market_open(self._spy, 1),
self._purchase)
def _purchase(self):
''' Immediately purchases the ETF at market opening '''
self.set_holdings(self._spy, 1)
self._days = 0
def on_data(self, data):
if self.portfolio.invested:
self._days += 1
# Liquidates after 3 days
if self._days > 3:
self.liquidate(self._spy, 'Liquidate after 3 days')