Mining Financial News for Major Events and Their Impacts on the Market

Abstract

In this paper we have proposed a stock market analysis system that analyzes financial news items to identify and characterize major events that impact the market. The events have been identified using latent Dirichlet allocation (LDA) based topic extraction mechanism. These topics have been thereafter analyzed in conjunction with actual market data to understand their impact on the market. A prediction system has been proposed which can predict whether the stock market will fall or rise, based on news items.

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