I tried to implement the famous paper https://www.math.nyu.edu/faculty/avellane/AvellanedaLeeStatArb071108.pdf
Can a generous soul cross check the notebook implementation because when I backtest this strategy it is not profitable? The paper is easy to understand.
Best regards,
Beginner
I didn't check the whole algo but it seems you are destroyed by transaction costs. It is slightly winning before taking them into account
Hi Beginner!
considering the above strategies, I was wondering if you have checked out the below paper.
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1404905.
Attilio has published Matlab code with the paper.
The paper does seem more clear to me.
Thoughts....
Regards,
Andrew
Beginner, the paper 404'd do you have the name of it or a mirror? Thanks.
edit: https://www.math.nyu.edu/faculty/avellane/AvellanedaLeeStatArb071108.pdf
Hey, thanks for your work. But I am wondering why
"eigport = eigport / np.sum(np.abs(eigport)) * 250000"
rather than
"eigport = eigport / np.sum(eigport) * 250000"
Hi, thanks for your algo. I am currently studying this paper and can anyone kindly tell me what is score and hf really? why 2 and why 5? Plus, what is counter? why 5? Thx!!
Have you identified the issue yet? I can't seem to find the "close position" signal, i.e abs(s) < 0.5, in your code.
Hi John,
I gave up on this approach. There are many other ways to do statistical arbitrage.
Best regards,
Pravin
Just had a second look at your code. You implemented the "close" signals incorrectly, if I'm not mistaken.
Your algo closes ALL open positions if NONE of the stocks in the list yields abs(score) > 2 and hf < 5 and ...
Instead, each stock should be treated individually and if abs(score) < 0.5 only the position related to that stock should be closed.
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