Discussion of article "Data Science and Machine Learning (Part 04): Predicting Current Stock Market Crash"

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New article Data Science and Machine Learning (Part 04): Predicting Current Stock Market Crash has been published:

In this article I am going to attempt to use our logistic model to predict the stock market crash based upon the fundamentals of the US economy, the NETFLIX and APPLE are the stocks we are going to focus on, Using the previous market crashes of 2019 and 2020 let's see how our model will perform in the current dooms and glooms.

That's it see the full code linked below, now its time to test the model in the strategy tester

APPLE Testing results

Graph

Author: Omega J Msigwa

[Marcel Fitzner]

Very interesting indeed. Did you also consider testing at different/random start dates or simply split the history in equally large intervals? 

Also, it would be very interesting to see how the classification works throughout all the different sectors (basic mats, energy, finance, healthcare, consumer cyclical/defensive, tech, utilities,..)

Anyways, great share, thanks again!

[Omega J Msigwa]

Marcel Fitzner #:
Very interesting indeed. Did you also consider testing at different/random start dates or simply split the history in equally large intervals? 

Also, it would be very interesting to see how the classification works throughout all the different sectors (basic mats, energy, finance, healthcare, consumer cyclical/defensive, tech, utilities,..)

Anyways, great share, thanks again!

great question,

A: about choosing the random testing and training datasets, it is possible to do so and it is my goal that after further updates on the library one should be able to do so(python libraries on ML can help you achieve this) still there is a lot to cover on this subject

B: you can read about the classification in all the sectors you've mentioned outside this platform because, I think that's irrelevant in the trading community available in this platform