Testing for Asset Price Bubbles using Options Data

Abstract

We present a new approach to identifying asset price bubbles based on options data. We estimate asset bubbles by exploiting the differential pricing between put and call options. We apply our methodology to two stock market indexes, the S&P 500 and the Nasdaq-100, and two technology stocks, Amazon and Facebook, over the 2014-2018 sample period. We find that, while indexes do not exhibit significant bubbles, Amazon and Facebook show frequent and significant bubbles. The estimated bubbles tend to be associated with high trading volume and earning announcement days. Since our approach can be implemented in real time, it is useful to both policy-makers and investors. As an illustration we consider two case studies: the Nasdaq dot-com bubble (between 1999 to 2002) and GameStop (between December 2020 and January 2021). In both cases we identify significant and persistent bubbles.

Keywords: Asset Price Bubbles, Option Pricing, Stochastic Volatility, Martingales, Local Martingales

JEL Classification: C51, C52, G12, G13