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RSS FeedsEntropy, Vol. 25, Pages 219: Investigating Deep Stock Market Forecasting with Sentiment Analysis (Entropy)

 
 

23 january 2023 08:44:13

 
Entropy, Vol. 25, Pages 219: Investigating Deep Stock Market Forecasting with Sentiment Analysis (Entropy)
 


When forecasting financial time series, incorporating relevant sentiment analysis data into the feature space is a common assumption to increase the capacities of the model. In addition, deep learning architectures and state-of-the-art schemes are increasingly used due to their efficiency. This work compares state-of-the-art methods in financial time series forecasting incorporating sentiment analysis. Through an extensive experimental process, 67 different feature setups consisting of stock closing prices and sentiment scores were tested on a variety of different datasets and metrics. In total, 30 state-of-the-art algorithmic schemes were used over two case studies: one comparing methods and one comparing input feature setups. The aggregated results indicate, on the one hand, the prevalence of a proposed method and, on the other, a conditional improvement in model efficiency after the incorporation of sentiment setups in certain forecast time frames.


 
103 viewsCategory: Informatics, Physics
 
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