Hello friends! Curious about how to properly predict stock prices?
I’ve now released the third video in this YouTube mini-series.
For those unfamiliar: this is a video series that debunks common mistakes found in nearly all blog articles / Github repos claiming to do “stock price predictions with LSTMs”.
These are typically written by non-experts in the field just looking for clicks, and I have a lot of fun breaking down precisely what they’re doing wrong.
Why is this important?
Beginners are often fooled by such content, wasting money on courses to learn things that don’t work. Even worse, they may end up putting such examples on their own Github accounts or in their portfolios / resumes, worsening their chances of getting a job in the field.
To be clear: the bad part isn’t that they learned something that doesn’t work (although that is pretty bad by itself). The bad part is, they don’t even understand why it doesn’t work. They are confident that it does and will fight me over it! (That is, until I ask them to verify or rebut any of the claims I’ve made).
Thus, not only does this stuff not work (due to all the mistakes I outline in my video series), but it could actually be detrimental to getting a job and working in this area. These are not just harmless mistakes!
The first video discussed why min-max scaling over the train set doesn’t work.
The second video discussed why using prices as inputs (i.e. lagged prices to build an autoregressive model) doesn’t work.
This third video (this video) will discuss why using prices as targets does not work.