Predicting Stock Prices with LSTMs: One Mistake Everyone Makes (Episode 16)

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You pinpointed exactly what I was wondering about. As a person who worked in the financial market for more than a decade and just learned ML. Min-Max scaling was a big question mark for me. First you never know what is the max of a certain price especially in a market (like gold) is always doing higher highs. Also, minimum price is not actually known throughout the data set, so unless you are a bank who has 80-150 years of recorded data for minimum, your data set size will never reflect the true lows or true highs. this leads that most ML models in YT tutorials just plainly panic and fails when the price is doing new historical highs or lows (according to the data set it was trained on, not actual historical highs or lows). scaling and standardization is crucial no doubts, but MinMax technique is fundamentally wrong and reflects absolutely an ignorance about the market dynamics and the core principles of training a ML model.

MZak-jsoy

This video is a gem. I saw a lot of blogs and tutorials repeating the mistakes you had mentioned.

adwaitdathanr

This video is so underrated. I happen to see the same errors. I would also advise that instead of using a min-max scaler, to use a power transform and standardize.

vohemiq

I believe it's important to keep things in the same scale because the algorithms apply the same learning rate to all feature dimensions.

anoriginalnick

Thank you very much. I recommend not saying that when scaling the ideas is to have values be "small". People who might take you literally will think you mean very small values (ex. 1.2x10^-20). I would also introduce stationarity at your timestamp for "Stock returns instead of ..." since this is a step towards that.

emmang

In this video you comment that using prices is wrong but using returns is correct. Does using logs of prices have the same problem? (I ask because logs of prices are commonly used in finance because they have the property that adding logs gives the return over a period of time.) Logs of prices have no min or max, so I imagine they are similarly wrong.

hughdbrown

sequence length of 1 is fine if the lstm is stateful (hidden state from prev period is used as input aswell). if the lstm is statless, you need to pass the whole sequence (and zero hidden state as input). so it basically depends what kind of lstm you are training. (stateful or stateless) but lstms are still useless for price prediction, because they tend to output the last price of the input sequence. thats what i learned when playing around with lstms for stock price prediction.

cenobit

This is just a promotion video, if you think carefully.

alaincheong

Thanks for this video. I finally took action and bought the course on Udemy. I am broke so I usually find a way to get stuff for free so this was a big step for me. I have been trading for more than 2 years now and wanted to apply ML in ways different than what I have seen online. So, thank you for making this course!

onceappuonatime

It took me a while to grasp, but thank you a lot. Mistake number 5 should be all over the internet! Everybody, if you are using a training window does not mean you are using a sequence, it is about the sequence of training

xVantwoutMaarten

You’re right but we can use price and minmaxscaling locally to find patterns I usually apply it locally when sampling data and not on the whole data

gamingsaloon

Thank you so much for explaining these concepts properly, it can be seen that you have a lot of experience in this subject. I started learning machine learning techniques for analyzing economical data but I could not figure out the best method in order to forecast stock prices.

plasmaflare

Holy shit I just standardized the data on one of my LSTM models and I instantly got over 10x less loss

MOriginal

I cannot find you other videos about other mistakes.
I agree about using the return value instead of price as input. However this will result in input range between -1, 1. What activation function would you use then ?

MansourAlAkeel

Are these courses applied machine learning or advanced machine learning in depth of its working mechanism to object layer?

SimonIslit

Very insightful, very true the bit about using 1 sequence not multiple.

BoHorror

awesome...i saw so many examples, with this mistake, but always, i felt what they are doing has some flaw. But, was unable to reason it myself. Thanks for the clarification.

kartikpodugu

LOVE this video! Cannot help laughing when watching the virus part, but it is so true! I am really glad that I didn’t use min max scaler in my time series tutorials. Thank you for your contribution to the machine learning community, sir!

grabngoinfo

Hey, thanks for the great content,
i am using R, do you think it's as good as python for this kind of analysis ?

kyloren

Thank you very much for this video, I was starting to think I was worng until I saw this video. There are tons of mistakes out there, specifically on this topic.

gastonvilches

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