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What is Hybrid Neural Network for Stock Volatility about?
This document presents a hybrid time-series predictive neural network (HTPNN) for stock volatility forecasting that integrates news headlines with historical stock data. The model utilizes distributed word vectors and sparse auto-encoders to optimize efficiency, achieving an average accuracy improvement of nearly 5% over existing methods. The paper discusses the significance of incorporating social factors, particularly news, in predicting stock price fluctuations and details the methodology and experimenta
- Author
- ldceconfessions2024
- Language
- EN