Hacker News Reader

Comment by ge96 | Hacker News Reader

So... can you or can you not, predict the stocks with ANN's... haha, guess I won't be quitting my job any time soon.

>A stock time series is unfortunately not a function that can be mapped.

> So... can you or can you not, predict the stocks with ANN's... haha, guess I won't be quitting my job any time soon.

Not sure about "predicting" the stocks with ANNs, but how do you explain the Medallion Fund averaging about 30%/y (ballpark) without a single loss year since 1990 ?

https://www.bloomberg.com/news/articles/2016-11-21/how-renai...

Except these firms don't use LSTMs at their core. They do tons of feature engineering combined with statistical models and very simple machine learning models (think linear/logistic regression). Some firms will use more complicated black box models (which would include LSTMs), but only as one additional signal to combine with all their hand engineered features and financial models.

Or Virtu having a single losing day in a six year period?

https://www.bloomberg.com/news/articles/2015-02-20/high-freq...

I wonder what the Sharpe Ratios of the trading systems these funds run are.

Virtu does high frequency trading so it makes sense that they don't have many down days. Also HFT strategies can have ridiculous sharpe ratios of like 100

True, although conventional metrics like Sharpe ratio or ROI are not very meaningful for HFT models, because they can't scale with any additional capital (you can safely assume they are scaled to the max). Their returns are extremely consistent, but also ultimately limited in magnitude. Rather than magical money-making machines who have cracked the "secret code" of financial markets, HFTs are essentially a fixed-cost utility service for reducing market inefficiency through improved price discovery.

>HFT strategies can have ridiculous sharpe ratios of like 100

Yeah, I've heard similar and it explains their basically linear equity curves...

You most certainly can, just not with such naïve approach. Jane Street is a company that does it, and they are quite open about their tech approach (just not about their specific models):

https://www.youtube.com/watch?v=hKcOkWzj0_s

Jane Street went from zero to trading $1 trillion in volume in just 15 years.

I would say that you certainly can not predict it. But given enough information (all stocks, news, etc) sufficiently complicated LSTM-like network might be able to beat you. But feasibility of building and computing it today - I have my serious doubts :)

To be fair, all you really need to do in most stock market use cases is to predict measurably better than the competition to be able to get something of business value, not necessarily really close to "perfect" or within so much accuracy.

Yeah I don't know anything about this stuff at this point. fantasy

Anyway thanks

Reply on news.ycombinator.com