Live data from Hacker News

Building AI Trading Systems

dennybritz.com

1–10 of 109 posts

Re: Building AI Trading Systems

#6

What's the real performance of the system so far?

Probably not very good. Voleon does all ML-based trading and what I've seen of their returns does not give me any confidence in ML-based trading having alpha. I would estimate that at best in a good year returns would be like 5% y/y in the long term, much less than the sustained ~7% that index funds offer especially when adjusting for risk. Just speculation but there's a lot of firms with much more capital, better tools, and teams of extremely intelligent people who have pretty poor returns because of how good the competition already is.

Re: Building AI Trading Systems

#7
post #6

What's the real performance of the system so far?

Probably not very good. Voleon does all ML-based trading and what I've seen of their returns does not give me any confidence in ML-based trading having alpha. I would estimate that at best in a good year returns would be like 5% y/y in the long term, much less than the sustained ~7% that index funds offer especially when adjusting for risk. Just speculation but there's a lot of firms with much more capital, better to…

I think you're comparing apples to oranges here. These funds manage billions of dollars of client money, which forces them into highly liquid markets with scalable strategies. That's quite different from how individuals or smaller prop funds can operate, trading off capacity for higher returns by trading in less liquid markets or with strategies that are "not worth it" for large hedge funds. If you must manage billions of client money then you are right in terms of competition, but as someone who only trades his own capital, you can see a lot higher returns.

Re: Building AI Trading Systems

#8
I've never tried the AI trading path but I imagine that you can't get huge gains with public data, unless you find a way to extract "hidden" information by processing real time news.

I wonder nevertheless if there's a sweet spot where you can build a simple AI trading algorithm and get modest earnings from it.

Re: Building AI Trading Systems

#9
I tried doing some forecasting with various neural network models after assembling what I thought was a good amount of forex data. The neural net (I tried various architectures) couldn't do any better than chance. After playing around with it and trying to double-check everything, that was as far as I could get. This puts me ahead of most traders, since most of them lose money, then quit.

This makes me wonder what kind of trading systems can actually have any kind of edge, since some kind of autoregressive time series forecasting system seems pretty unreliable.

On a more general note, how do you move beyond it being gambling? Just because a system backtests well doesn't mean a phenomenon will continue to happen, especially if your system will significantly impact the market you're in. If you make a trend-following system, every time you trade, you're gambling that the trend is more likely to continue than not. If you're right, you'll come out ahead over many trades. If you don't have enough capital to withstand drawdown the way most beginners don't, you won't be able to last long enough for whatever phenomenon you've found to average out.

It takes a lot of time, effort and risk to do all this, so, this is a long-winded way of saying I don't think it's for me. If you build a SaaS product and it fails, at least you can talk about what you learned from building it and use that in future endeavors. If you lose money trading because your algorithm doesn't work, what do you learn from that besides that your algorithm doesn't work?

Re: Building AI Trading Systems

#10
readers may also be interested in Benter's paper "Computer Based Horse Race Handicapping and Wagering Systems: A Report" -- https://www.gwern.net/docs/statistics/decision/1994-benter.p...

> This paper examines the elements necessary for a practical and successful computerized horse race handicapping and wagering system. Data requirements, handicapping model development, wagering strategy, and feasibility are addressed. A logit-based technique and a corresponding heuristic measure of improvement are described for combining a fundamental handicapping model with the public's implied probability estimates. The author reports significant positive results in five years of actual implementation of such a system. This result can be interpreted as evidence of inefficiency in pari-mutuel racetrack wagering. This paper aims to emphasize those aspects of computer handicapping which the author has found most important in practical application of such a system

Arguably the paper describes the state of the art from three decades ago, applied to betting on Hong Kong horse races, not market price movements.

Post reply on HN