| Overall Statistics |
|
Total Trades 1 Average Win 0% Average Loss 0% Compounding Annual Return 1.980% Drawdown 3.500% Expectancy 0 Net Profit 0.167% Sharpe Ratio 0.213 Probabilistic Sharpe Ratio 40.264% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0.02 Beta 0.826 Annual Standard Deviation 0.099 Annual Variance 0.01 Information Ratio 0.415 Tracking Error 0.047 Treynor Ratio 0.026 Total Fees $15.41 Estimated Strategy Capacity $120000000.00 Lowest Capacity Asset SPY R735QTJ8XC9X |
from QuantConnect.Data.Custom.CBOE import CBOE
from QuantConnect.Data.Custom.Fred import *
class RSIAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 1, 1)
self.SetEndDate(2020, 2, 1)
self.SetCash(1000000)
self.SetBrokerageModel(BrokerageName.AlphaStreams)
self.buffer = 0.02
self.Settings.FreePortfolioValuePercentage = self.buffer
self.vix = self.AddData(CBOE, 'VIX', Resolution.Daily).Symbol
self.symbolData = {}
for ticker in ['SPY']:
symbol = self.AddEquity("SPY").Symbol
self.symbolData[symbol] = SymbolData(self, symbol)
self.SetWarmUp(100)
def OnData(self, data):
if self.IsWarmingUp or self.vix not in data:
return
self.Log(f'Time: {self.Time}')
count = len(self.symbolData)
for symbol, symbolDatum in self.symbolData.items():
symbolDatum.consolidator.Scan(self.Time)
if not self.Portfolio[symbol].Invested:
if symbolDatum.Close > symbolDatum.SMA.Current.Value:
self.SetHoldings(symbol, 1/count)
self.Log(f'Value Close: {symbolDatum.Close}')
self.Log(f'Value SMA: {symbolDatum.SMA.Current.Value}')
self.Log("-------------------")
class SymbolData:
def __init__(self, algorithm, symbol):
self.algorithm = algorithm
self.SMA = SimpleMovingAverage(30)
self.Close = 0
self.consolidator = TradeBarConsolidator(timedelta(1))
self.consolidator.DataConsolidated += self.ValueDailyBarHandler
algorithm.RegisterIndicator(symbol, self.SMA, self.consolidator)
def ValueDailyBarHandler(self, sender, bar):
self.algorithm.Debug(f'New Bar: {bar.Close} @ {self.algorithm.Time}')
# Saving new bar to variable:
self.Close = bar.Close