| Overall Statistics |
|
Total Trades 71 Average Win 1.74% Average Loss -0.25% Compounding Annual Return 14057.506% Drawdown 2.100% Expectancy 0.819 Net Profit 7.993% Sharpe Ratio 155.692 Probabilistic Sharpe Ratio 99.979% Loss Rate 77% Win Rate 23% Profit-Loss Ratio 6.96 Alpha 69.851 Beta -2.08 Annual Standard Deviation 0.461 Annual Variance 0.212 Information Ratio 106.805 Tracking Error 0.68 Treynor Ratio -34.492 Total Fees $211.82 Estimated Strategy Capacity $15000000.00 Lowest Capacity Asset MSFT R735QTJ8XC9X |
from AlgorithmImports import *
class BasicAlgo(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 2, 19) # Set Start Date
self.SetEndDate(2020, 2, 24) # Set End Date
self.SetCash(100000) # Set Strategy Cash
self.symbol = self.AddEquity("MSFT", Resolution.Second).Symbol
self.td = float(self.GetParameter("tick_amount"))
self.window_size_p = int(float(self.GetParameter("window_size_p")))
self.window_size_n = int(float(self.GetParameter("window_size_n")))
self.prob_threshold = float(self.GetParameter("pt"))
renkoClose = ClassicRenkoConsolidator(self.td)
renkoClose.DataConsolidated += self.HandleRenkoClose
self.SubscriptionManager.AddConsolidator(self.symbol, renkoClose)
self.next_positive_prob = 0
self.next_negative_prob = 0
self.next_positive_prob_1 = 0
self.next_negative_prob_1 = 0
self.next_positive_prob_2 = 0
self.next_negative_prob_2 = 0
self.tick_seq = []
self.index_list = []
self.cash_rate = 0.005
self.leverage_rate = .0075
self.short_rate = 0.0025
self.leverage_costs = 0
self.cash_interests = 0
self.short_costs = 0
self.max_leverage = 2
self.window_total_p = 0
self.window_total_n = 0
self.positive_ticks = 0
self.next_positive = 0
self.negative_ticks = 0
self.next_negative = 0
self.window_total_2_p = 0
self.window_total_2_n = 0
self.positive_ticks_2 = 0
self.next_positive_2 = 0
self.negative_ticks_2 = 0
self.next_negative_2 = 0
def OnData(self, data):
self.next_positive_prob = self.next_positive_prob_1
self.next_negative_prob = self.next_negative_prob_1
if not self.Portfolio.Invested:
if self.next_negative_prob > self.prob_threshold:
if sum(self.tick_seq[-(self.window_size_n)+1:]) == -self.window_size_n+1:
self.SetHoldings(self.symbol,-1)
self.Debug('Shorted at ' + str(data[self.symbol].Close))
if self.next_positive_prob > self.prob_threshold:
if sum(self.tick_seq[-(self.window_size_p)+1:]) == self.window_size_p-1:
self.SetHoldings(self.symbol,1)
self.Debug('Bought at ' + str(data[self.symbol].Close))
if self.Portfolio[self.symbol].IsShort:
if sum(self.tick_seq[-(self.window_size_n)+1:]) == self.window_size_n-1:
self.SetHoldings(self.symbol, 0)
self.Debug('Stoped short at '+ str(data[self.symbol].Close))
if self.Portfolio[self.symbol].IsLong:
if sum(self.tick_seq[-(self.window_size_p)+1:]) == -self.window_size_p+1:
self.Liquidate()
self.Debug('Liqudated at '+ str(data[self.symbol].Close))
def HandleRenkoClose(self, sender, data):
self.Debug(f"CLOSE - {data.Time} - {data.Open} {data.Close} {self.Securities[self.symbol].Price}")
if data.Open < data.Close:
self.tick_seq.append(1)
else:
self.tick_seq.append(-1)
self.Get_Probabilities()
def Get_Probabilities(self):
if len(self.tick_seq) == 0: return
self.tick_idx = [i for i in range(len(self.tick_seq))]
for i in range(self.window_size_p ,len(self.tick_seq)+1):
self.window_total_p = np.sum( self.tick_seq[i-self.window_size_p:i-1] )
if self.window_total_p == self.window_size_p-1:
self.positive_ticks += 1
if self.tick_seq[i-1] == 1:
self.next_positive += 1
for i in range(self.window_size_n ,len(self.tick_seq)+1):
self.window_total_n = np.sum( self.tick_seq[i-self.window_size_n:i-1] )
if -self.window_total_n == self.window_size_n-1:
self.negative_ticks += 1
if self.tick_seq[i-1] == -1:
self.next_negative += 1
if self.positive_ticks == 0: self.next_positive_prob_1 = 0
else: self.next_positive_prob_1 = self.next_positive/self.positive_ticks
if self.negative_ticks == 0: self.next_negative_prob_1=0
else: self.next_negative_prob_1 = self.next_negative /self.negative_ticks
self.Debug('Renko N. Positive probability: ' + str(self.next_positive_prob_1) +' negative probability ' + str(self.next_negative_prob_1))