How Informationally Efficient Are Options Markets?

48 Pages Posted: 28 Dec 2018 Last revised: 6 Apr 2022

See all articles by Luis Goncalves-Pinto

Luis Goncalves-Pinto

University of New South Wales (UNSW)

Carlo Sala

ESADE Business School

Date Written: April 2, 2022

Abstract

The ability of option-based measures to predict future stock returns is not a sufficient condition for the existence of incremental information in options. If options markets are informationally more efficient than the stock market, then option measures may be used to predict future actual stock returns, but there should be weaker or no predictability for future synthetic (option-implied) stock returns. We propose to extract the incremental information in option-based measures from their ability to predict the spread between actual and synthetic stock returns. We document that existing proxies for informed option trading, such as the option-to-stock volume ratio, are unable to predict this spread around the release of scheduled and unscheduled firm-specific news. This is evidence inconsistent with the greater informational efficiency of the options markets, and casts doubt on the existence of incremental information in options. The empirical analysis is motivated using a noisy rational expectations model with informed investors who can trade simultaneously in stock and options.

Keywords: Information Markets, Put-Call Parity, Synthetic Returns, Predictability

JEL Classification: G11, G12, C13

Suggested Citation

Goncalves-Pinto, Luis and Sala, Carlo, How Informationally Efficient Are Options Markets? (April 2, 2022). Available at SSRN: https://ssrn.com/abstract=3297953 or http://dx.doi.org/10.2139/ssrn.3297953

Luis Goncalves-Pinto (Contact Author)

University of New South Wales (UNSW) ( email )

Kensington
High St
Sydney, NSW 2052
Australia

HOME PAGE: http://luis.goncalvespinto.com/

Carlo Sala

ESADE Business School ( email )

Avenida de Torreblanca 59
Barcelona, Barcelona 08172
Spain

HOME PAGE: http://www.people.usi.ch/salaca

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
139
Abstract Views
1,068
rank
283,674
PlumX Metrics