| Overall Statistics |
|
Total Trades 331 Average Win 0.66% Average Loss -0.76% Compounding Annual Return -4.186% Drawdown 20.400% Expectancy -0.047 Net Profit -6.415% Sharpe Ratio -0.336 Probabilistic Sharpe Ratio 2.167% Loss Rate 49% Win Rate 51% Profit-Loss Ratio 0.87 Alpha -0.028 Beta 0.197 Annual Standard Deviation 0.078 Annual Variance 0.006 Information Ratio -0.211 Tracking Error 0.157 Treynor Ratio -0.132 Total Fees $345.09 Estimated Strategy Capacity $24000000.00 Lowest Capacity Asset SPY R735QTJ8XC9X Portfolio Turnover 58.14% |
#region imports
from AlgorithmImports import *
from QuantConnect.Data.UniverseSelection import *
#endregion
class ShortAlgorithm(QCAlgorithm):
def __init__(self):
self.reb = 1
self.num_fine = 10
self.symbols = None
def Initialize(self):
self.SetCash(100000)
self.SetStartDate(2022, 1, 1)
self.AddIndex("VIX", Resolution.Daily)
self.spy = self.AddEquity("SPY", Resolution.Daily).Symbol
self.s200 = self.SMA("SPY", 200, Resolution.Daily)
self.SetBenchmark("SPY")
self.UniverseSettings.Resolution = Resolution.Daily
self.AddUniverse(self.CoarseSelectionFunction,self.FineSelectionFunction)
self.Schedule.On(self.DateRules.EveryDay(self.spy),
self.TimeRules.AfterMarketOpen(self.spy, 0), Action(self.rebalance))
def OnData(self, data):
if not data["SPY"]:
return
if not self.s200.IsReady:
return
def CoarseSelectionFunction(self, coarse):
if self.reb != 1:
return self.symbols
filtered_coarse = [x.Symbol for x in coarse if (x.HasFundamentalData)
and x.Price > 5
and x.Price < SimpleMovingAverage(200).Current.Value
and x.Volume > 1e5
]
return filtered_coarse
def FineSelectionFunction(self, fine):
if self.reb != 1:
return self.symbols
self.reb = 0
filtered_fine = [x for x in fine if
x.MarketCap > 2e9
]
top = sorted(filtered_fine, key = lambda x: x.MarketCap, reverse=True)[:self.num_fine]
self.symbols = [x.Symbol for x in top]
return self.symbols
def OnData(self, data):
pass
def rebalance(self):
# if this month the stock are not going to be long/short, liquidate it.
long_short_list = self.symbols
for i in self.Portfolio.Values:
if (i.Invested) and (i not in long_short_list):
self.Liquidate(i.Symbol)
if self.Securities["SPY"].Price < self.s200.Current.Value:
if self.Securities["VIX"].Price > 20:
for i in self.symbols:
self.SetHoldings(i, -1/self.num_fine)
else:
self.SetHoldings("SPY", 1)
else:
self.SetHoldings("SPY", 1)
self.reb = 1