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Determining Optimal Trading Rules without Backtesting
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Determining Optimal Trading Rules without Backtesting

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Determining Optimal Trading Rules without Backtesting

Source: [1408.1159] Determining Optimal Trading Rules without Backtesting

Peter P. Carr, Marcos Lopez de Prado

(Submitted on 6 Aug 2014)

Calibrating a trading rule using a historical simulation (also called backtest) contributes to backtest overfitting, which in turn leads to underperformance. In this paper we propose a procedure for determining the optimal trading rule (OTR) without running alternative model configurations through a backtest engine. We present empirical evidence of the existence of such optimal solutions for the case of prices following a discrete Ornstein-Uhlenbeck process, and show how they can be computed numerically. Although we do not derive a closed-form solution for the calculation of OTRs, we conjecture its existence on the basis of the empirical evidence presented.

PDF attached.

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  #3 (permalink)
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Code
#!/usr/bin/env python
# Profit-taking and stop-loss simulations
# On 20131003 by MLdP <lopezdeprado@lbl.gov> 
import numpy as np
from random import gauss
from itertools import product
#----------------------------------------------------------------------------------------
def main():
 rPT=rSLm=np.linspace(0,10,21)
 count=0
 for prod_ in product([10,5,0,-5,-10],[5,10,25,50,100]):
 count+=1
 coeffs={'forecast':prod_[0],'hl':prod_[1],'sigma':1}
 output=batch(coeffs,nIter=1e5,maxHP=100,rPT=rPT,rSLm=rSLm)
 return output
#----------------------------------------------------------------------------------------
def batch(coeffs,nIter=1e5,maxHP=100,rPT=np.linspace(0,10,21), \
 rSLm=np.linspace(0,10,21),seed=0):
 phi,output1=2**(-1./coeffs['hl']),[]
 for comb_ in product(rPT,rSLm):
 output2=[]
 for iter_ in range(int(nIter)):
 p,hp,count=seed,0,0
 while True:
 p=(1-phi)*coeffs['forecast']+phi*p+coeffs['sigma']*gauss(0,1)
 cP=p-seed;hp+=1
 if cP>comb_[0] or cP<-comb_[1] or hp>maxHP:
 output2.append(cP)
 break
 mean,std=np.mean(output2),np.std(output2)
 print comb_[0],comb_[1],mean,std,mean/std
 output1.append((comb_[0],comb_[1],mean,std,mean/std))
 return output1
Mike

Due to time constraints, please do not PM me if your question can be resolved or answered on the forum.

Need help?
1) Stop changing things. No new indicators, charts, or methods. Be consistent with what is in front of you first.
2) Start a journal and post to it daily with the trades you made to show your strengths and weaknesses.
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4) Accept responsibility for your actions. Stop looking elsewhere to explain away poor performance.
5) Where to start as a trader? Watch this webinar and read this thread for hundreds of questions and answers.
6)
Help using the forum? Watch this video to learn general tips on using the site.

If you want
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Nice find...i'm a fan of Marcos López de Prado's work. I've added this to my reading list.

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