Overall Statistics
Total Trades
561
Average Win
1.37%
Average Loss
-1.85%
Compounding Annual Return
4.912%
Drawdown
26.300%
Expectancy
0.124
Net Profit
77.134%
Sharpe Ratio
0.367
Probabilistic Sharpe Ratio
0.461%
Loss Rate
35%
Win Rate
65%
Profit-Loss Ratio
0.74
Alpha
0
Beta
0
Annual Standard Deviation
0.108
Annual Variance
0.012
Information Ratio
0.367
Tracking Error
0.108
Treynor Ratio
0
Total Fees
$2047.24
Estimated Strategy Capacity
$1200000000.00
Lowest Capacity Asset
SPY R735QTJ8XC9X
 
import numpy as np
import pandas as pd



class CalculatingFluorescentOrangeBee(QCAlgorithm):
    
    #1Today is Monday. 2The close must be at least 1% lower than Friday’s close. 3If one and two are true, then enter at the close. 4Exit at the close on Tuesday.

    def Initialize(self):
        self.SetStartDate(2010, 1, 1)  # Set Start Date
        self.SetEndDate(2021, 12, 1)  # Set Start Date
        self.SetCash(100000)  # Set Strategy Cash
        self.spy = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.SetWarmup(100)
        self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin)
                               
        # schedule: rebalance
        self.Schedule.On(self.DateRules.Every(DayOfWeek.Monday), self.TimeRules.BeforeMarketClose(self.spy, 0), self.entry_signal)
        self.Schedule.On(self.DateRules.Every(DayOfWeek.Tuesday), self.TimeRules.BeforeMarketClose(self.spy, 0), self.close_position)
                         


    def entry_signal(self):
        histh = self.History(self.spy,180, Resolution.Minute).loc["SPY"]["close"]
        histd = self.History(self.spy,21, Resolution.Daily).loc["SPY"]["close"]
        
        histd_df = pd.DataFrame(histd)
        histh_df = pd.DataFrame([histh.iloc[-1]])
        
        histd_df = histd_df.append(histh_df, ignore_index = True)
        
        ret = histd_df[::-1].pct_change()
        
        self.Log(str(ret.iloc[-1] * 100))
        change = ret.iloc[-1] * 100
        
        if change.close < 1.0:
            self.SetHoldings(self.spy, 1)
        
    def close_position(self):
        
        if self.Portfolio[self.spy].Invested:
            self.Liquidate()

    def OnData(self, data):
        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
            Arguments:
                data: Slice object keyed by symbol containing the stock data
        '''

        # if not self.Portfolio.Invested:
        #    self.SetHoldings("SPY", 1)