This is complete rubbish. Zero evaluation compared to any sane baseline, zero thinking about representation (predicting raw price?!). I'll just say it, ML was frankly better when fewer people knew it and there was less money in claiming to be an expert.
Using a Keras Long Short-Term Memory Model to Predict Stock Prices
101–110 of 178 posts
Re: Using a Keras Long Short-Term Memory Model to Predict Stock Prices
#102This is pure nonsense. This isn’t even the right way to begin thinking about this as a forecasting task — the target series should be log-normal returns, not raw asset price. The performance of this model is laughably bad, which is probably why he spends zero time evaluating its effectiveness. You could trivially get better forecasts than this by naively repeating the last-observed price . This isn’t ML. It’s cargo-c…
Can you clarify why "the target series should be log-normal returns" is important or provide a pointer for more information?
Re: Using a Keras Long Short-Term Memory Model to Predict Stock Prices
#103lol Derrick Mwiti getting rekt in the comments
Re: Using a Keras Long Short-Term Memory Model to Predict Stock Prices
#104Re: Using a Keras Long Short-Term Memory Model to Predict Stock Prices
#105Earlier quoted context omitted.
These predictions can also be self-reenforcing. If enough money believes the model is accurate, it will create it's own market conditions. In a distopian AI stock prediction world the best model will be the one with the widest publicity and adoption, not the best data points.
The problem I see with that hypothesis is that the asset pricing must eventually be tied to actual performance--while it may be self-reinforcing to some extend, if it _is_ fundamentally wrong, there will be a reckoning and an adjustment after a high value stock goes bankrupt, for example.
But the stock market isn’t just a bunch of people placing speculative bets about company performance; it’s a bunch of people placing speculative bets about company performance by buying shares of the companies. If the market is irrational, it can actually prop up companies that would otherwise go bankrupt.
Re: Using a Keras Long Short-Term Memory Model to Predict Stock Prices
#106From my experience, LSTM or other recurrent neural network models only work "well" at forecasting bounded and periodic or oscillating time series. Might work for something like seasonal sale data, but would fail spectacularly with unbounded and chaotic time series like stock prices.
Re: Using a Keras Long Short-Term Memory Model to Predict Stock Prices
#107I believe a simple moving average would achieve the same result and that mixing training and test data for validation invalidates your model results...
On a positive note, nice showcase of how simple implementation with Keras is.
Re: Using a Keras Long Short-Term Memory Model to Predict Stock Prices
#108This is pure nonsense. This isn’t even the right way to begin thinking about this as a forecasting task — the target series should be log-normal returns, not raw asset price. The performance of this model is laughably bad, which is probably why he spends zero time evaluating its effectiveness. You could trivially get better forecasts than this by naively repeating the last-observed price . This isn’t ML. It’s cargo-c…
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Re: Using a Keras Long Short-Term Memory Model to Predict Stock Prices
#109I don’t know what’s more embarrassing. This article, or the fact that it’s #1 on HN right now.
Re: Using a Keras Long Short-Term Memory Model to Predict Stock Prices
#110Again, as always, and every time -- if a stock market price-predicting scheme worked, it would not be published on the internet for free. It would not be for sale. It would be in constant use to make money for the authors.