Predicting Stock Price Volatility by Analyzing Semantic Content in Media

Hossein Asgharian and Sverker Sikström ()
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Sverker Sikström: Department of Psychology, Lund University, Postal: Department of Psychology, Lund University, Box 7082, S-22007 Lund, Sweden

No 2014:38, Working Papers from Lund University, Department of Economics

Abstract: Current models for predicting volatility do not incorporate information flow and are solely based on historical volatilities. We suggest a method to quantify the semantic content of words in news articles about a company and use this as a predictor of its stock volatility. The results show that future stock volatility is better predicted by our method than the conventional models. We also analyze the functional role of text in media either as a passive documentation of past information flow or as an active source for new information influencing future volatility. Our data suggest that semantic content may take both roles.

Keywords: volatility; information flow; latent semantic analysis; GARCH (search for similar items in EconPapers)
JEL-codes: G19 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2014-11-20
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Related works:
Working Paper: Predicting Stock Price Volatility by Analyzing Semantic Content in Media (2013)
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