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arXiv Machine Learning By Yuanzhe Jia, Ali Anaissi, Basem Suleiman

ResNLS: An Improved Model for Stock Price Forecasting

Read the original on arXiv Machine Learning →

ResNLS is a hybrid neural model combining ResNet and LSTM to forecast stock prices by emphasizing dependencies between adjacent prices. The model uses the closing prices of the previous five trading days as input, achieving optimal performance and outperforming state‑of‑the‑art baselines by at least 20%. In back‑testing, a trading strategy based on ResNLS‑5 predictions mitigated losses during market declines and generated profits during upturns.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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