Machine learning for financial prediction
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Machine learning for financial prediction
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Re: Machine learning for financial prediction
#2If anyone else is getting errors when loading the page, here's the google cached version http://webcache.googleusercontent.com/search?q=cache:-ciyXfS...
Re: Machine learning for financial prediction
#3If anyone else is getting errors when loading the page, here's the google cached version http://webcache.googleusercontent.com/search?q=cache:-ciyXfS...
Thank you.
Re: Machine learning for financial prediction
#4If anyone else is getting errors when loading the page, here's the google cached version http://webcache.googleusercontent.com/search?q=cache:-ciyXfS...
+1 thanks for the cached version.
Re: Machine learning for financial prediction
#5Never understood why anyone would spend time creating any trading method given even if it did work (possible, but unlikely) the SEC would audit you and then leak how you were making the outperforming returns.
Welcome any thoughts, in part because legally beating the market is possible, just don't get the SEC & OPSEC aspect.
Re: Machine learning for financial prediction
#6Interesting article. I do something related, and here's my take:
Data mining is useful because it gives you things that are predictive that you might not have considered at first, but make sense after. This is mainly due to combinatorial explosion in the potential number of formulas.
You generally have a vague idea of what might be predictive, eg cheapness vs earnings and cash flow, but there's a huge number of ways that might show up in the data, and there's a huge number of ways it might hide in the data.
So for instance an old school analyst might do a ranking of price/earnings as well as cash flow, or whatever bespoke formula desired.
A data mining approach could take all the fundamentals and generate formulas mixing the variables, yielding a number that seem to be effective. Out of those, you'd look at them and decide that they capture some thesis (low P/E, upward trend in earnings). Then you'd look at whether the formula is sensitive to small tweaks. For instance, if you regressed the last 6 earnings and it had phenomenal performance, but with 5 or 7 it wasn't, you probably conclude it's some sort of random result.
There's funds that take the mass approach to an extreme. They have huge databases, with a genetic algorithm that generates expression trees, and a battery of stats (incl backtests) to decide what works. They end up with many thousands of strategies that are a great deal more effective than your standard one-trick pony fund.
Re: Machine learning for financial prediction
#7Never understood why anyone would spend time creating any trading method given even if it did work (possible, but unlikely) the SEC would audit you and then leak how you were making the outperforming returns. Welcome any thoughts, in part because legally beating the market is possible, just don't get the SEC & OPSEC aspect.
Why would the SEC audit you? Just by random chance there are many people outperforming the market. They can't audit you just for outperforming.
If they do audit you, how will they discover how you are generating your trading decisions? Their remit is to make sure you aren't doing something illegal. There's no reason they would understand what you were doing in anything other than a superficial way.
Also, something can be profitable, and obviously so, without being easily reproducible. For instance there are firms that do simple footrace arbitrage on the same security between different exchanges. Not hard to understand, but you still can't do it. There's a whole spectrum of strategies that are on a frontier on the map of easy-to-understand vs easy-to-implement.
Besides all that, I think even if you were to learn about a way to beat the market, the way you found out might lead you to be very skeptical of whatever was proposed. If a guy is selling it on a website, you will probably not believe him, right? And if he showed you backtests that worked, you would suspect they were generated from a random generator of some sort. And if he then shows you the math, you would almost certainly find fault with it. Why did he do this or that transformation on the data? Must be random...
Re: Machine learning for financial prediction
#8Really successful traders spend their obtaining insider information, not massaging public data. It stands to reason that an ensemble of technical trading methods would regress towards the mean.
Re: Machine learning for financial prediction
#9...spend their time and resources...
Re: Machine learning for financial prediction
#10Never understood why anyone would spend time creating any trading method given even if it did work (possible, but unlikely) the SEC would audit you and then leak how you were making the outperforming returns. Welcome any thoughts, in part because legally beating the market is possible, just don't get the SEC & OPSEC aspect.
The problem isn't coming up with an algorithm that works (i.e. more wins than losses).
The difficulty is gaining confidence in your algo and determining when to move from paper trading to actual trading.
You run into counter-intuitive things while training a neural net, for example. You'd think more training data would be good, but when training neural nets, you actually want to use as little data as possible while still creating an ideal ROC curve.