| Overall Statistics |
|
Total Trades 10 Average Win 0% Average Loss -0.33% Compounding Annual Return -27.316% Drawdown 1.600% Expectancy -1 Net Profit -1.647% Sharpe Ratio -3.568 Probabilistic Sharpe Ratio 0.202% Loss Rate 100% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.329 Beta 0.222 Annual Standard Deviation 0.058 Annual Variance 0.003 Information Ratio -10.854 Tracking Error 0.07 Treynor Ratio -0.93 Total Fees $10.00 Estimated Strategy Capacity $14000000.00 Lowest Capacity Asset FB V6OIPNZEM8V9 |
# VXX version - best length 22
# VIX hour version - best length 11
# VIX daily version - best length 22
import numpy as np
from datetime import datetime
class BasicTemplateAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2021, 10, 15)
#self.SetEndDate(2020, 3, 1)
self.SetEndDate(datetime.now())
self.SetCash(23400)
self.Settings.FreePortfolioValuePercentage = 0.00
self.data = {}
self.SetBenchmark("SPY")
self.CoarseSize = 8
self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin)
self.trailing_stop = self.GetParameter("trailing-stop")
self.trailing_stop = float(self.trailing_stop) if self.trailing_stop else 0.04
self.moving_average = self.GetParameter("moving-average")
self.moving_average = float(self.moving_average) if self.moving_average else 13
self.rsi_value = self.GetParameter("rsi-value")
self.rsi_value = float(self.rsi_value) if self.rsi_value else 55
self.vixrsi_value = self.GetParameter("vix-rsi-value")
self.vixrsi_value = float(self.vixrsi_value) if self.vixrsi_value else 50
self.sma_tolerance = self.GetParameter("sma-tolerance")
self.sma_tolerance = float(self.sma_tolerance) if self.sma_tolerance else 0.0063
self.vix_length = self.GetParameter("vix-length")
self.vix_length = float(self.vix_length) if self.vix_length else 8
self.rsi_upper = self.GetParameter("rsi-upper")
self.rsi_upper = float(self.rsi_upper) if self.rsi_upper else 65
self.qqq_length = self.GetParameter("qqq-length")
self.qqq_length = float(self.qqq_length) if self.qqq_length else 20
self.screener_price = self.GetParameter("screener-price")
self.screener_price = float(self.screener_price) if self.screener_price else 60
self.AddRiskManagement(TrailingStopRiskManagementModel(self.trailing_stop))
self.SPY = self.AddEquity("SPY", Resolution.Hour).Symbol
self.Schedule.On(self.DateRules.EveryDay("SPY"),
self.TimeRules.AfterMarketOpen(self.SPY, 0),
self.StartTrading)
self.Schedule.On(self.DateRules.EveryDay("SPY"),
self.TimeRules.BeforeMarketClose(self.SPY, 1),
self.EndOfDay)
self.vix = self.AddEquity("VXX", Resolution.Minute).Symbol
self.qqq = self.AddEquity("QQQ", Resolution.Minute).Symbol
self.staticAssets = [self.SPY, self.vix, self.qqq]
self.vixSma = self.SMA(self.vix, self.vix_length, Resolution.Hour)
self.vixRsi = self.RSI(self.vix, 14, Resolution.Hour)
self.qqqSma = self.SMA(self.qqq, self.qqq_length, Resolution.Hour)
vixHistory = self.History(self.vix, 14, Resolution.Hour)
for tuple in vixHistory.loc[self.vix].itertuples():
self.vixSma.Update(tuple.Index, tuple.close)
self.vixRsi.Update(tuple.Index, tuple.close)
qqqHistory = self.History(self.qqq, 20, Resolution.Hour)
for tuple in qqqHistory.loc[self.qqq].itertuples():
self.qqqSma.Update(tuple.Index, tuple.close)
self.Log(". VIX SMA INITIALIZED: " + str(self.vixSma.Current.Value))
self.AddUniverse(self.CoarseFilter)
'''
If VVIX > 50 day SMA,
Sell all current assets
Switch to vxx and IEF (50/50)
'''
self.UniverseSettings.Resolution = Resolution.Hour
self.lastMonth = -1
self.lastHour = -1
self.allowTrades = True
self.switchSafety = False
self.Log("Initialized")
def EndOfDay(self):
if self.IsWarmingUp: return
self.allowTrades = False
self.Log('End Of Day Stop Trade')
def StartTrading(self):
self.switchSafety = False
self.allowTrades = True
def CoarseFilter(self, coarse):
self.Log(f'CoarseFilter called on {self.Time}')
self.lastMonth = self.Time.month
topStocksByVolume = sorted([x for x in coarse
if x.Price > self.screener_price and x.Volume > 0 and x.HasFundamentalData and
x.Symbol.Value not in ["GME", "AMC", "GOOG", "SPY"]], # Manually exclude companies
key = lambda x: x.DollarVolume, reverse=True)[:self.CoarseSize]
return [x.Symbol for x in topStocksByVolume]
self.Log("Picked number of symbols in universe: " + str(len(finalSymbols)))
return [x.Symbol for x in finalSymbols]
def PlaceTrades(self, data):
isUptrend = []
for symbol, symbolData in self.data.items():
self.Debug(str(symbol.Value) + " at " + str(self.Time) + ". RSI: " + str(symbolData.Rsi.Current.Value) + ". SMA*T: " + str(symbolData.Sma.Current.Value * (1 + self.sma_tolerance)) + ". PRICE: " + str(self.Securities[symbol].Price))
if not data.ContainsKey(symbol):
self.Log("Does not contain data for " + str(symbol))
continue
if self.Securities[symbol].Price > (symbolData.Sma.Current.Value * (1 + self.sma_tolerance)) and not symbolData.Rsi.Current.Value < self.rsi_value and not symbolData.Rsi.Current.Value > self.rsi_upper and not self.Securities[self.qqq].Price < self.qqqSma.Current.Value:
isUptrend.append(symbol)
for symbol in isUptrend:
self.Debug("Buying: " + str(symbol))
self.SetHoldings(symbol, 1/len(isUptrend), False, "SMA: " + str(self.data[symbol].Sma.Current.Value) + ". RSI: " + str(self.data[symbol].Rsi.Current.Value))
def OnData(self, data):
if self.IsWarmingUp: return
self.Log(". VIX: " + str(self.Securities[self.vix].Price) + ". VIX SMA: " + str(self.vixSma.Current.Value) + ". VIX RSI: " + str(self.vixRsi.Current.Value))
self.Log(". Symbols: " + str(self.data.keys))
if self.allowTrades == False: return
#i moved place trades liquidate logic back to ondata
if self.Securities[self.vix].Price > self.vixSma.Current.Value and self.vixRsi.Current.Value > self.vixrsi_value:
self.Liquidate()
self.Log("ONDATA VIX OR QQQ CHECK FAILED LIQUIDATING")
return
if self.lastHour == self.Time.hour or self.Time.hour < 10:
return
self.lastHour = self.Time.hour
self.PlaceTrades(data)
def OnSecuritiesChanged(self, changes):
for added in changes.AddedSecurities:
symbol = added.Symbol
if symbol in self.staticAssets: continue
added.MarginModel = PatternDayTradingMarginModel()
sma = self.SMA(symbol, self.moving_average, Resolution.Hour)
rsi = self.RSI(symbol, 14, MovingAverageType.Simple, Resolution.Hour)
history = self.History(symbol, 15, Resolution.Hour)
for tuple in history.loc[symbol].itertuples():
sma.Update(tuple.Index, tuple.close)
rsi.Update(tuple.Index, tuple.close)
self.Log(f'New Securities Added: {[security.Symbol.Value for security in changes.AddedSecurities]}')
symbolData = SymbolData(sma, rsi)
self.data[symbol] = symbolData
for removed in changes.RemovedSecurities:
symbol = removed.Symbol
self.Liquidate(symbol, tag="Symbol Removed From Universe")
self.data.pop(symbol, None)
self.Log(f'Securities Removed{[security.Symbol.Value for security in changes.RemovedSecurities]}')
class SymbolData:
def __init__(self, sma, rsi):
self.Sma = sma
self.Rsi = rsi