I used the tensorflow time series forecasting from this page: Time series forecasting | TensorFlow Core with a few other datasets. It is working fine, except for the multi-step and auto recursive models. With the tensorflow example dataset (jena_climate_2009_2016), I get T(deg) predictions that are more or less accurate.
With any stock OHLC times series I tried, I get Close predictions that looks like lines, and not at all in line with real values.
The (val) loss are similar in each case.
I can not figure out why the predictions are so “linear” with OHLC datasets.
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Hey @Site_de_Niche.
Can you please tell a bit more on your model/setup? (features engineering, data frequency, number of samples, specific model, hyperparameters, …)
Maybe you can share a colab?
Anyways, predicting financial markets is notoriously difficult.