Accounting for Earnings Announcements in the Pricing of Equity Options

TL;DR

This paper develops an option pricing model that incorporates earnings announcement impacts, providing analytical formulas and bounds for implied volatility, and demonstrates good calibration and practical implications for pre-EA American options.

Contribution

It introduces analytical option pricing formulas with jump models for earnings announcements, including bounds and asymptotics for implied volatility, and compares risk-neutral and historical distributions.

Findings

Analytical formulas for options with EA jumps under Kou model.

Good fit of implied volatility surface prior to earnings.

Insights into pre-EA American option valuation and strategies.

Abstract

We study an option pricing framework that accounts for the price impact of an earnings announcement (EA), and analyze the behavior of the implied volatility surface prior to the event. On the announcement date, we incorporate a random jump to the stock price to represent the shock due to earnings. We consider different distributions of the scheduled earnings jump as well as different underlying stock price dynamics before and after the EA date. Our main contributions include analytical option pricing formulas when the underlying stock price follows the Kou model along with a double-exponential or Gaussian EA jump on the announcement date. Furthermore, we derive analytic bounds and asymptotics for the pre-EA implied volatility under various models. The calibration results demonstrate adequate fit of the entire implied volatility surface prior to an announcement. We also compare the risk-neutral distribution of the EA jump to its historical distribution. Finally, we discuss the valuation and exercise strategy of pre-EA American options, and illustrate an analytical approximation and numerical results.