Inferring Financial Bubbles from Option Data

61 Pages Posted: 26 May 2020 Last revised: 29 Jun 2021

See all articles by Robert Jarrow

Robert Jarrow

Cornell SC Johnson College of Business

Simon Kwok

The University of Sydney

Date Written: June 29, 2021

Abstract

Financial bubbles arise when the underlying assets market price departs from its fundamental value. Unlike other bubble tests that use time series data and assume a reduced-form price process, we infer the existence of bubbles nonparametrically using option price data. Under no-arbitrage and acknowledging data constraints, we can partially identify asset price bubbles using a cross section of European option prices. In the empirical analysis, we obtain interval estimates of price bubbles embedded in the S&P 500 Index. The estimated index bubbles are then used to construct profitable momentum trading strategies that consistently outperform a buy-and-hold trading strategy.

Keywords: asset price bubble, fundamental value, risk-neutral probability measure, state price distribution, tail truncation, partial identification, nonparametric estimation, local polynomial

JEL Classification: C14, C58, G12

Suggested Citation

Jarrow, Robert and Kwok, Simon, Inferring Financial Bubbles from Option Data (June 29, 2021). Available at SSRN: https://ssrn.com/abstract=3586437 or http://dx.doi.org/10.2139/ssrn.3586437

Robert Jarrow (Contact Author)

Cornell SC Johnson College of Business

Ithaca, NY 14850
United States

Simon Kwok

The University of Sydney ( email )

University of Sydney
Sydney, NSW 2006
Australia

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