The Information Content of Option-Implied Tail Risk on Post-Earnings Abnormal Stock Returns

45 Pages Posted: 27 Jul 2018 Last revised: 18 Oct 2018

See all articles by Mengxi (Maggie) Liu

Mengxi (Maggie) Liu

University of Queensland, Business School

Kam Fong Chan

University of Queensland - Faculty of Business, Economics and Law; Financial Research Network (FIRN)

Robert W. Faff

University of Queensland

Date Written: July 25, 2018

Abstract

We show that option-implied jump tail risk estimated prior to earnings announcements strongly predicts post-earnings risk-adjusted abnormal stock returns. The predictive power of implied jump tail risk is particularly strong on extreme abnormal stock returns whose absolute values exceed 10%. The finding is robust to various event windows and after controlling for model-free implied moments of variance, skewness and kurtosis. We argue that the tail risk implied from options preceding earnings news releases reflects a sudden flood of information of informed traders and investors, and this results in the tail risk usefully predicting abnormal stock returns. Finally, we show that upside and downside tail risk contain distinctive predictive information, with upside (downside) tail risk strongly predicting positive (negative) abnormal stock returns.

Keywords: Implied tail risk; Abnormal stock returns; Earnings announcements

JEL Classification: G11; G12; G14

Suggested Citation

Liu, Mengxi (Maggie) and Chan, Kam Fong and Faff, Robert W., The Information Content of Option-Implied Tail Risk on Post-Earnings Abnormal Stock Returns (July 25, 2018). 31st Australasian Finance and Banking Conference 2018. Available at SSRN: https://ssrn.com/abstract=3221043 or http://dx.doi.org/10.2139/ssrn.3221043

Mengxi (Maggie) Liu (Contact Author)

University of Queensland, Business School ( email )

St Lucia
Australia

Kam Fong Chan

University of Queensland - Faculty of Business, Economics and Law ( email )

4072 Brisbane, Queensland
Australia

Financial Research Network (FIRN) ( email )

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

Robert W. Faff

University of Queensland ( email )

St Lucia
Brisbane, Queensland 4072
Australia

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