Stanford machine learning lectures and POMDP

Came across this gem accidentally today. Here are the complete 20 lectures for CS 229 Machine Learning from Stanford University for my own record. I have learned most of the material before, but have forgotten most of it already.

In particular, the last lecture talks about POMDP. I have always thought it would be a great tool to be applied on a financial trading system. Long story short, POMDP is a distinctive machine learning algorithm because it inherently assumes the ‘world’ is partially-observable (MDP on its own takes care of the uncertainty part). A drawback with using artificial intelligence in trading is that A.I. are good for closed ended system but bad for open ended ones (i.e. trading). I believe POMDP can be worked on to become a valuable trading system.

I haven’t tried implementing it myself yet because of lack of a good platform and data. But since POMDP has been around for years now, I would assume somebody somewhere has tried this already. Unfortunately, I haven’t been able to find any information on this problem.

In any case, this post is merely a reminder for myself.

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5 Comments

  1. zin says:

    hello, paul :) nice to read your good post
    i have reached to your blog while finding pomdp articles
    i’m trading currency (fx) and i’m trying pomdp way to that
    as you know, there is various a.i. (many types of neural network , rl ,etc etc)
    i have studied about that for long time
    and now i’m trying pomdp , it will works well?
    i hope so :)
    good luck for your trading and see you on the market ~

  2. Benjamin says:

    Hi Paul,
    just discovered your blog. Have been reading your articles with great interest. I haven’t heard of POMDP before, but they look interesting. In fact a fast search turns up several studies with stocks and POMDP.

    Just one thing… You write:

    A drawback with using artificial intelligence in trading is that A.I. are good for closed ended system but bad for open ended ones (i.e. trading).

    Machine learning (ML) techniques, such as POMDP, (if you say “artificial intelligence”, more traditional rule-based systems could be understood) are based on statistical patterns in data, which implies that you don’t have to know everything about the system, you just need enough data.

  3. Yuan Zhang says:

    Hi Paul,

    It was a great read about your post on applying POMDP on financial trading. I have been working on improving POMDP algorithms and applying POMDP on medical decision area in my Ph.D research. Seems like there are very few studies about applying POMDP on trading, but I bet there must be some chance to combine those together. Good luck with your trading!

  4. Yuan Zhang says:

    Paul,

    See if you are interested in this paper , which described a POMDP model to analyze stock investing policies.

  5. Paul says:

    @Yuan, thanks for the link! I’ll check it out once I’m back to work. I haven’t applied any complex ML technique for a couple of years because I’m now leaning toward using transparent methods.

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