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Predicting Stock Price Volatility by Analyzing Semantic Content in Media.

Asgharian, Hossein LU and Sikström, Sverker LU (2014) In Working Paper / Department of Economics, School of Economics and Management, Lund University
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.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Working Paper
publication status
published
subject
keywords
latent semantic analysis, information flow, volatility, GARCH
in
Working Paper / Department of Economics, School of Economics and Management, Lund University
issue
38
pages
43 pages
publisher
Department of Economics, Lund Universtiy
language
English
LU publication?
yes
id
33dc9e07-bb62-446e-8101-bf912c1c8b29 (old id 4814733)
alternative location
http://swopec.hhs.se/lunewp/abs/lunewp2014_038.htm
date added to LUP
2014-11-27 16:39:09
date last changed
2016-04-16 07:32:02
@misc{33dc9e07-bb62-446e-8101-bf912c1c8b29,
  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.},
  author       = {Asgharian, Hossein and Sikström, Sverker},
  keyword      = {latent semantic analysis,information flow,volatility,GARCH},
  language     = {eng},
  number       = {38},
  pages        = {43},
  publisher    = {ARRAY(0x7d0df18)},
  series       = {Working Paper / Department of Economics, School of Economics and Management, Lund University},
  title        = {Predicting Stock Price Volatility by Analyzing Semantic Content in Media.},
  year         = {2014},
}