| Overall Statistics |
|
Total Trades 46 Average Win 0.21% Average Loss -0.18% Compounding Annual Return 3.426% Drawdown 6.900% Expectancy 0.148 Net Profit 0.524% Sharpe Ratio 0.249 Probabilistic Sharpe Ratio 36.369% Loss Rate 48% Win Rate 52% Profit-Loss Ratio 1.19 Alpha 0.021 Beta -0.627 Annual Standard Deviation 0.131 Annual Variance 0.017 Information Ratio 0.202 Tracking Error 0.248 Treynor Ratio -0.052 Total Fees $72.98 Estimated Strategy Capacity $2900000.00 Lowest Capacity Asset BA R735QTJ8XC9X |
from Execution.ImmediateExecutionModel import ImmediateExecutionModel
from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel
from Risk.MaximumDrawdownPercentPerSecurity import MaximumDrawdownPercentPerSecurity
from Selection.QC500UniverseSelectionModel import QC500UniverseSelectionModel
class SimpleRSITestQC500Universe(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2010, 1, 1) # Set Start Date
self.SetEndDate(2010, 2, 28) # Set End Date
self.SetCash(100000) # Set Strategy Cash
self.SetExecution(ImmediateExecutionModel())
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
self.SetRiskManagement(MaximumDrawdownPercentPerSecurity(0.05))
symbols = [ Symbol.Create("SPY", SecurityType.Equity, Market.USA), Symbol.Create("GE", SecurityType.Equity, Market.USA), Symbol.Create("BA", SecurityType.Equity, Market.USA) ]
self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
self.AddAlpha(RsiAlphaModelTest())
class RsiAlphaModelTest(AlphaModel):
def __init__(self, period = 14, resolution = Resolution.Daily):
self.period = period
self.resolution = resolution
self.insightPeriod = Time.Multiply(Extensions.ToTimeSpan(resolution), period)
self.symbolDataBySymbol = {}
self.closeWindows = {}
resolutionString = Extensions.GetEnumString(resolution, Resolution)
self.Name = '{}({},{})'.format(self.__class__.__name__, period, resolutionString)
def Update(self, algorithm, data):
insights = []
for symbol, symbolData in self.symbolDataBySymbol.items():
if data.ContainsKey(symbol) and data[symbol] is not None:
self.closeWindows[symbol].Add(data[symbol].Close)
if self.closeWindows[symbol].Count>2:
pass
#algorithm.Debug(self.closeWindows[symbol][2])
rsi = symbolData.RSI
previous_state = symbolData.State
state = self.GetState(rsi, previous_state)
if state != previous_state and rsi.IsReady:
if state == State.TrippedLow:
insights.append(Insight.Price(symbol, self.insightPeriod, InsightDirection.Up))
if state == State.TrippedHigh:
insights.append(Insight.Price(symbol, self.insightPeriod, InsightDirection.Down))
symbolData.State = state
return insights
def OnSecuritiesChanged(self, algorithm, changes):
# clean up data for removed securities
symbols = [ x.Symbol for x in changes.RemovedSecurities ]
if len(symbols) > 0:
for subscription in algorithm.SubscriptionManager.Subscriptions:
if subscription.Symbol in symbols:
self.symbolDataBySymbol.pop(subscription.Symbol, None)
subscription.Consolidators.Clear()
# initialize data for added securities
addedSymbols = [ x.Symbol for x in changes.AddedSecurities if x.Symbol not in self.symbolDataBySymbol]
if len(addedSymbols) == 0: return
history = algorithm.History(addedSymbols, self.period, self.resolution)
for symbol in addedSymbols:
rsi = algorithm.RSI(symbol, self.period, MovingAverageType.Wilders, self.resolution)
self.closeWindows[symbol] = RollingWindow[float](4)
# need to figure out how to load historical data into rolling window
if not history.empty:
ticker = SymbolCache.GetTicker(symbol)
if ticker not in history.index.levels[0]:
Log.Trace(f'RsiAlphaModel.OnSecuritiesChanged: {ticker} not found in history data frame.')
continue
for tuple in history.loc[ticker].itertuples():
rsi.Update(tuple.Index, tuple.close)
self.symbolDataBySymbol[symbol] = SymbolData(symbol, rsi)
def GetState(self, rsi, previous):
if rsi.Current.Value > 70:
return State.TrippedHigh
if rsi.Current.Value < 30:
return State.TrippedLow
if previous == State.TrippedLow:
if rsi.Current.Value > 35:
return State.Middle
if previous == State.TrippedHigh:
if rsi.Current.Value < 65:
return State.Middle
return previous
def OnEndOfAlgorithm(self):
for symbol, SymbolData in self.symbolDataBySymbol.items():
algorithm.Debug( str(symbol) + " " )
class SymbolData:
def __init__(self, symbol, rsi):
self.Symbol = symbol
self.RSI = rsi
self.State = State.Middle
class State(Enum):
'''Defines the state. This is used to prevent signal spamming and aid in bounce detection.'''
TrippedLow = 0
Middle = 1
TrippedHigh = 2