Predicting Stock Price Volatility by Analyzing Semantic Content in Media.

Forskningsoutput: Working paper

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.

Detaljer

Författare
Enheter & grupper
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Psykologi
  • Nationalekonomi

Nyckelord

Originalspråkengelska
FörlagDepartment of Economics, Lund University
Antal sidor43
StatusPublished - 2014
PublikationskategoriForskning

Publikationsserier

NamnWorking Paper / Department of Economics, School of Economics and Management, Lund University
Nr.38