| Overall Statistics |
|
Total Orders 8 Average Win 26.56% Average Loss -20.52% Compounding Annual Return -0.184% Drawdown 58.600% Expectancy 0.147 Start Equity 100000 End Equity 96948.01 Net Profit -3.052% Sharpe Ratio -0.148 Sortino Ratio -0.09 Probabilistic Sharpe Ratio 0.000% Loss Rate 50% Win Rate 50% Profit-Loss Ratio 1.29 Alpha -0.047 Beta 0.552 Annual Standard Deviation 0.109 Annual Variance 0.012 Information Ratio -0.735 Tracking Error 0.099 Treynor Ratio -0.029 Total Fees $35.47 Estimated Strategy Capacity $580000000.00 Lowest Capacity Asset SPY R735QTJ8XC9X Portfolio Turnover 0.13% |
from AlgorithmImports import *
from QuantConnect.DataSource import *
class FredAlternativeDataAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self.set_start_date(2003, 1, 1)
self.set_end_date(2019, 10, 11)
self.set_cash(100000)
self.spy = self.add_equity("SPY", Resolution.DAILY).symbol
# Requesting data
self.fred_peak_to_trough = self.add_data(Fred, Fred.OECDRecessionIndicators.united_states_from_peak_through_the_trough, Resolution.DAILY).symbol
# Historical data
history = self.history(self.fred_peak_to_trough, 60, Resolution.DAILY)
self.debug(f"We got {len(history)} items from our history request")
def on_data(self, slice: Slice) -> None:
if slice.contains_key(self.fred_peak_to_trough) and slice.contains_key(self.spy):
peak_to_trough = slice.Get(Fred, self.fred_peak_to_trough).value
# Buy SPY if peak to trough value is 1
if peak_to_trough == 1 and not self.portfolio.invested:
self.set_holdings(self.spy, 1)
# Liquidate holdings if peak to trough value is 0
elif peak_to_trough == 0 and self.portfolio.invested:
self.liquidate(self.spy)