Informational Content of Options Trading on Acquirer Announcement Return

64 Pages Posted: 15 Jul 2013 Last revised: 2 Sep 2013

See all articles by Konan Chan

Konan Chan

National Chengchi Unversity (NCCU) - Finance

Li Ge

Monash University - Monash Business School

Tse-Chun Lin

The University of Hong Kong - Faculty of Business and Economics

Date Written: September 2, 2013

Abstract

This study examines the informational content of options trading on acquirer announcement returns. We show that implied volatility spread predicts positively on the cumulative abnormal return (CAR), and implied volatility skew predicts negatively on the CAR. The predictability is much stronger around actual merger and acquisition (M&A) announcement days, compared with pseudo-event days. The prediction is weaker if pre-M&A stock price has incorporated part of the information, but stronger if acquirer’s options trading is more liquid. Finally, we find that higher relative trading volume of options to stock predicts higher absolute CARs. The relation also exists among the target firms.

Keywords: Merger and Acquisition, Acquirer, Informed Trading, Implied Volatility Spread, Implied Volatility Skew

JEL Classification: G12, G14, G34

Suggested Citation

Chan, Konan and Ge, Li and Lin, Tse-Chun, Informational Content of Options Trading on Acquirer Announcement Return (September 2, 2013). Journal of Financial and Quantitative Analysis (JFQA), Forthcoming. Available at SSRN: https://ssrn.com/abstract=2293748 or http://dx.doi.org/10.2139/ssrn.2293748

Konan Chan

National Chengchi Unversity (NCCU) - Finance ( email )

No. 64, Chih-Nan Road
Section 2
Taipei, 11623
Taiwan
+886-2-29393091 ext 81239 (Phone)

Li Ge (Contact Author)

Monash University - Monash Business School ( email )

Building H Level 3, 900 Dandenong Road
Caulfield East
Melbourne, Victoria 3145
Australia
+61 399032123 (Phone)

Tse-Chun Lin

The University of Hong Kong - Faculty of Business and Economics ( email )

Pokfulam Road
Hong Kong
China

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
535
Abstract Views
2,204
rank
53,077
PlumX Metrics