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Media-expressed tone, option characteristics, and stock return predictability

Publication at Faculty of Mathematics and Physics |
2022

Abstract

We investigate the informational content of a huge assortment of NASDAQ articles about a joint cross-section of S&P 500 stock return data and related single-stock option data. Splitting the articles into a trading-time and an overnight archive, we distill tone from each of them.

We show that media-expressed tone is informative about option markets and that both option data and tone predict stock returns. The predictive power of option variables is robust to partialling out tone, but varies depending on whether tone is from the overnight or the trading-time archive.

A potential reason is that the archives differ in terms of their thematic content. Overall, we conclude that the informational content of option data for predicting single-stock returns extends beyond the information summarized in tone and traditional market factors. (c) 2021 Elsevier B.V.

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