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Predicting FTSE 100 returns and volatility using sentiment analysis
Author(s) -
Johnman Mark,
Vanstone Bruce James,
Gepp Adrian
Publication year - 2018
Publication title -
accounting and finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.645
H-Index - 49
eISSN - 1467-629X
pISSN - 0810-5391
DOI - 10.1111/acfi.12373
Subject(s) - volatility (finance) , economics , econometrics , financial economics , index (typography) , sentiment analysis , monetary economics , computer science , machine learning , world wide web
We investigate the statistical and economic effect of positive and negative sentiment on daily excess returns and volatility in the FTSE 100 index, using business news articles published by the Guardian Media Group between 01/01/2000 and 01/06/2016. The analysis indicates that while business news sentiment derived from articles aimed at retail traders does not influence excess returns in the FTSE 100 index, it does affect volatility, with negative sentiment increasing volatility and positive sentiment reducing it. Further, an ETF ‐based trading strategy based on these findings is found to outperform the naïve buy‐and‐hold approach.