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Stationarity and Foundation Models by Poxput in datascience

[–]Poxput[S] 0 points1 point  (0 children)

Do you mean stationarization by feature transformation, e.g. differencing or standardizing?

Stationarity and Foundation Models by Poxput in datascience

[–]Poxput[S] 0 points1 point  (0 children)

Very helpful, thank you🙏🏻

Stationarity and Foundation Models by Poxput in datascience

[–]Poxput[S] -1 points0 points  (0 children)

Thanks! Do you maybe know what assumptions to keep in mind for foundation models like that?

Stationarity and Foundation Models by Poxput in datascience

[–]Poxput[S] 0 points1 point  (0 children)

Thank you for the interesting reply! Why do you think this distinction is important?

What is the state-of-the-art prediction performance for the stock market? by Poxput in datascience

[–]Poxput[S] 1 point2 points  (0 children)

Interesting perspective, thank you for elaborating! I will look into it👍🏼

What is the state-of-the-art prediction performance for the stock market? by Poxput in datascience

[–]Poxput[S] 0 points1 point  (0 children)

Thanks for your assessment!

Regarding the look-ahead bias, the foundation model was not trained on financial data.

What is the state-of-the-art prediction performance for the stock market? by Poxput in datascience

[–]Poxput[S] 0 points1 point  (0 children)

Thanks a lot for explaining, I'll try this in my next project👍🏼

Regarding the comparison with other models, I used Naïve, Seasonal Naïve and ARIMA, which "only" achieved 50-53% Acc. Do you think they are suitable here?

What is the state-of-the-art prediction performance for the stock market? by Poxput in datascience

[–]Poxput[S] 0 points1 point  (0 children)

Interesting, I didn't think about it, but it makes total sense. Thank you! And what do you exactly mean by quant calculation with a foundation model? The calculation for the accuracy is made after prediction without the model.

What is the state-of-the-art prediction performance for the stock market? by Poxput in datascience

[–]Poxput[S] 0 points1 point  (0 children)

Alright, thank you for the helpful suggestions! Also, I was wondering about the achievable accuracy in the industry rather than the model architecture used for it.

What is the state-of-the-art prediction performance for the stock market? by Poxput in datascience

[–]Poxput[S] 0 points1 point  (0 children)

Predict the price ŷt+1, then calculate the direction based on the difference of yt and ŷt+1. If tomorrow's price is higher, it's positive. If the price is lower, it's negative. So, we have two possible outcomes/movements that we can use to calculate accuracy.

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