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Hello , When i add the risk management function to my algorithm ,it seems that it s not working as the report doesn't recognize the risk control.
Can someone help me on this please ?
from Risk.TrailingStopRiskManagementModel import TrailingStopRiskManagementModel
import numpy as np
import pandas as pd
import datetime
class NadionResistanceAutosequencers(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2017, 1, 1)
self.SetEndDate(2020,1,1)# Set Start Date
self.SetCash(100000)
self.Security=["LMT","MSFT","GM","MS","FB","NKE","AAL","TSLA","MS","GS","AMZN","T","BA","BLK","EA","C","KO","AMD","MMM","AXP","F","HON","SPY"]
for s in self.Security:
self.AddEquity(s,Resolution.Daily)
self.SetRiskManagement(TrailingStopRiskManagementModel(0.03))
self.SetExecution(ImmediateExecutionModel())
# Set Strategy Cash
# self.AddEquity("SPY", Resolution.Minute)
def OnData(self,data):
S=["LMT","MSFT","GM","MS","FB","NKE","AAL","TSLA","MS","GS","AMZN","T","BA","BLK","EA","C","KO","AMD","MMM","AXP","F","HON","SPY"]
M=self.History(S,360,Resolution.Daily)
M=M.close
V=M.unstack(level=0)
Daily_returns=np.log(V/V.shift(1))
Daily_returns_mean = Daily_returns.mean()
SPY_index_return = Daily_returns_mean[-1]
SPY_index_Var = Daily_returns.var()[-1]
covariance_index_stock = Daily_returns.cov()
Beta = covariance_index_stock.iloc[:,-4]/SPY_index_Var
Rcapm = 0.02 + Beta * (SPY_index_return-0.02)
SR = (Rcapm-0.02)/SPY_index_Var
for i in range(len(S)-1):
if SR[i]<0:
self.SetHoldings(S[i],0.10)
else :
return
for i in range(len(S)-1):
if SR[i]>0:
self.SetHoldings(S[i],-0.10)
else:
return
Rahul Chowdhury
Hey Wawes,
This risk management model seems to be working normally here. One way to notice this is by checking the difference between a backtest with the risk management model enabled and a backtest without it enabled.
If that hasn't answered your question, please let me know.
Wawes23
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