Checkley, Matthew, Anóñ Higón, D and Alles, C (2017) The Hasty Wisdom of the Mob: How Market Sentiment Predicts Stock Market Behavior. Expert Systems with Applications, 77. pp. 256-263. doi:10.1016/j.eswa.2017.01.029
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Abstract
We explore the ability of sentiment metrics, extracted from micro-blogging sites, to predict stock markets. We also address sentiments’ predictive time-horizons. The data concern bloggers’ feelings about five major stocks. Taking independent bullish and bearish sentiment metrics, granular to two minute intervals, we model their ability to forecast stock price direction, volatility, and traded volume. We find evidence of a causal link from sentiments to stock price returns, volatility and volume. The predictive time-horizon is minutes, rather than hours or days. We argue that diverse and high volume sentiment is more predictive of price volatility and traded volume than near-consensus is predictive of price direction. Causality is ephemeral. In this sense, the crowd is more a hasty mob than a source of wisdom.
Item Type: | Article |
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Article Type: | Article |
Uncontrolled Keywords: | Sentiment; Stock market; Social media; Forecasting; Micro-blogging; Analytics |
Subjects: | H Social Sciences > HG Finance > HG4001 Finance management. Business finance H Social Sciences > HG Finance > HG4501 Investment, capital formation, speculation |
Divisions: | Schools and Research Institutes > School of Business, Computing and Social Sciences |
Research Priority Areas: | Applied Business & Technology |
Depositing User: | Susan Turner |
Date Deposited: | 03 Feb 2017 16:42 |
Last Modified: | 04 Aug 2023 20:46 |
URI: | https://eprints.glos.ac.uk/id/eprint/4294 |
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