Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit
34 Pages Posted: 15 Jul 2020 Last revised: 5 Jan 2021
Date Written: July 1, 2020
Using data on international, on-line media coverage and tone of the Brexit referendum, we test whether it is media coverage or tone to provide the largest forecasting performance improvements in the prediction of the conditional variance of weekly FTSE 100 stock returns. We find that versions of standard symmetric and asymmetric Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models augmented to include media coverage and especially media tone scores outperforme traditional GARCH models both in-and-out-of-sample.
Keywords: Tention, Sentiment, Text Mining, Forecasting, Conditional Variance, GARCH Model, Brexit
JEL Classification: C53, C58, G17
Suggested Citation: Suggested Citation