| Overall Statistics |
|
Total Trades 9688 Average Win 0.09% Average Loss -0.04% Compounding Annual Return -0.884% Drawdown 45.300% Expectancy 0.004 Net Profit -8.308% Sharpe Ratio -0.008 Loss Rate 66% Win Rate 34% Profit-Loss Ratio 2.00 Alpha -0.009 Beta 0.148 Annual Standard Deviation 0.113 Annual Variance 0.013 Information Ratio -0.299 Tracking Error 0.192 Treynor Ratio -0.006 Total Fees $18653.36 |
from clr import AddReference
AddReference("System.Core")
AddReference("System.Collections")
AddReference("QuantConnect.Common")
AddReference("QuantConnect.Algorithm")
import statistics
from datetime import datetime
from System.Collections.Generic import List
class ShortTimeReversal(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2006, 1, 1)
self.SetEndDate(2016, 12, 31)
self.SetCash(1000000)
self.UniverseSettings.Resolution = Resolution.Daily
self.AddUniverse(self.CoarseSelectionFunction)
self._numberOfSymbols = 100
self._numberOfTradings = 10
self._LastMonth = -1
self._LastDay = -1
self._stocks = []
self._values = {}
def CoarseSelectionFunction(self, coarse):
sortedByDollarVolume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True)
top100 = sortedByDollarVolume[:self._numberOfSymbols]
list = List[Symbol]()
for x in top100:
list.Add(x.Symbol)
#self.Log("This is symbol: {0}".format(x.Symbol))
return list
def OnData(self, data):
if not self._values:
self._stocks = []
self.uni_symbol = None
symbols = self.UniverseManager.Keys
for i in symbols:
if str(i.Value) == "QC-UNIVERSE-COARSE-USA":
self.uni_symbol = i
for i in self.UniverseManager[self.uni_symbol].Members:
self._stocks.append(i.Value.Symbol)
#self.Log("This is sym: {0}".format(i.Value.Symbol))
self._values[i.Value.Symbol] = self.Securities[i.Value.Symbol].Price
self._LastDay = self.Time.date()
self._LastMonth = self.Time.month
else:
if self.Time.month != self._LastMonth:
self._LastMonth = self.Time.month
returns = {}
for stock in self._stocks:
newPrice = self.Securities[stock].Price
returns[stock] = newPrice/self._values[stock]
newArr = [(v,k) for k,v in returns.items()]
newArr.sort()
for ret, stock in newArr[self._numberOfTradings:-self._numberOfTradings]:
self.SetHoldings(stock, 0)
for ret, stock in newArr[0:self._numberOfTradings]:
self.SetHoldings(stock, 0.5/self._numberOfTradings)
for ret, stock in newArr[-self._numberOfTradings:]:
self.SetHoldings(stock, -0.5/self._numberOfTradings)
self._LastDay = self.Time.date()
return
delta = self.Time.date() - self._LastDay
if delta.days >= 7:
for stock in self._stocks:
if self.Portfolio[stock].IsLong:
self.SetHoldings(stock, 0.5/self._numberOfTradings)
if self.Portfolio[stock].IsShort:
self.SetHoldings(stock, -0.5/self._numberOfTradings)
self._LastDay = self.Time.date()