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PAUL-BERNARD avatar PAUL-BERNARD commented on June 22, 2024

Hello,
If the predictions of your model is not good, you can try to tune the hyper-parameters ( see https://reservoirpy.readthedocs.io/en/latest/user_guide/hyper.html ).

Otherwise, I would say that predicting stock market is a very difficult task, so I'm not surprised that you have worse results than on Mackey-Glass or Lorenz.

Is ReservoirPy designed to only predict on chaotic structured data?

Reservoir computing in general is a good framework for chaotic data, but it can be used for other tasks that are not really chaotic.

Any examples of Stock Market data forecasting?

As far as I know, not with ReservoirPy, but there are a few articles here and there about using Echo State Network for this task (but I haven't read them, so I can't point specific ones).

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wilbertmatthew avatar wilbertmatthew commented on June 22, 2024

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neuronalX avatar neuronalX commented on June 22, 2024

There are papers doing stock market prediction. One was done by Herbert Jaeger himself with students for a competition:
Iles et al (2007) Stepping forward through echoes of the past: forecasting with echo state networks
https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=368e4c95c69d3499ff1a1e46cf80b855c3b97fb5

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wilbertmatthew avatar wilbertmatthew commented on June 22, 2024

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