Overall Statistics
Total Trades
36
Average Win
5.51%
Average Loss
-2.24%
Compounding Annual Return
145.262%
Drawdown
22.200%
Expectancy
1.118
Net Profit
77.288%
Sharpe Ratio
2.827
Probabilistic Sharpe Ratio
83.161%
Loss Rate
39%
Win Rate
61%
Profit-Loss Ratio
2.47
Alpha
0.526
Beta
2.182
Annual Standard Deviation
0.345
Annual Variance
0.119
Information Ratio
2.803
Tracking Error
0.274
Treynor Ratio
0.447
Total Fees
$234.47
Estimated Strategy Capacity
$46000000.00
Lowest Capacity Asset
MSFT R735QTJ8XC9X
 
from AlgorithmImports import *

class SECReport8KAlgorithm(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2019, 1, 1)
        self.SetEndDate(2019, 8, 21)
        self.SetCash(100000)

        self.mappings = {}
        self.UniverseSettings.Resolution = Resolution.Minute
        self.AddUniverse(self.CoarseSelector)

        # Request underlying equity data.
        ibm = self.AddEquity("IBM", Resolution.Minute).Symbol
        # Add news data for the underlying IBM asset
        earningsFiling = self.AddData(SECReport10Q, ibm, Resolution.Daily).Symbol
        # Request 120 days of history with the SECReport10Q IBM custom data Symbol
        history = self.History(SECReport10Q, earningsFiling, 120, Resolution.Daily)
        # Count the number of items we get from our history request
        self.Debug(f"We got {len(history)} items from our history request")

    def CoarseSelector(self, coarse):
        coarse = sorted([cf for cf in coarse if cf.HasFundamentalData],
            key=lambda cf: cf.DollarVolume, reverse=True)[:10]
        return [cf.Symbol for cf in coarse]

    def OnData(self, data):
        # Store the symbols we want to long in a list
        # so that we can have an equal-weighted portfolio
        longEquitySymbols = []

        # Get all SEC data and loop over it
        for report in data.Get(SECReport8K).Values:
            # Get the length of all contents contained within the report
            reportTextLength = sum([len(i.Text) for i in report.Report.Documents])

            if reportTextLength > 20000:
                longEquitySymbols.append(report.Symbol.Underlying)

        for equitySymbol in longEquitySymbols:
            self.SetHoldings(equitySymbol, 1.0 / len(longEquitySymbols))

    def OnSecuritiesChanged(self, changes):
        for symbol in [s.Symbol for s in changes.AddedSecurities]:
            self.mappings[symbol] = self.AddData(SECReport8K, symbol).Symbol

        for symbol in [s.Symbol for s in changes.RemovedSecurities]:
            # If removed from the universe, liquidate and remove the custom data from the algorithm
            self.Liquidate(symbol)
            reportSymbol = self.mappings.pop(symbol, None)
            if reportSymbol:
                self.RemoveSecurity(reportSymbol)