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Predicting Stock Market Movements Using Network Science: An Information Theoretic Approach by shubhamkks2 is a document available to read on EtoBox.

This research paper presents a novel method for predicting stock market movements, specifically the S&P 500 Index, using network science and information theory. By constructing time-series complex networks based on mutual information from stock price movements, the authors demonstrate that network measurements can enhance the accuracy of ARIMA models for forecasting. The findings suggest that this approach could serve as a valuable tool for financial policymakers and quantitative investors to anticipate mar

Author

shubhamkks2

Language

EN