Inferring Financial Bubbles from Option Data
61 Pages Posted: 26 May 2020 Last revised: 29 Jun 2021
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
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