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Inferring Financial Bubbles from Option Data

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  • Jarrow, Robert A.
  • Kwok, Simon S.

Abstract

Financial bubbles arise when the underlying asset's market price deviates from its fundamen- tal 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.

Suggested Citation

  • Jarrow, Robert A. & Kwok, Simon S., 2020. "Inferring Financial Bubbles from Option Data," Working Papers 2020-04, University of Sydney, School of Economics, revised Jun 2021.
    • Handle: RePEc:syd:wpaper:2020-04
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    References listed on IDEAS

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    Cited by:

    1. Xiaoting Dai & Linhai Wu, 2023. "The impact of capitalist profit-seeking behavior by online food delivery platforms on food safety risks and government regulation strategies," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    2. H. Peter Boswijk & Jun Yu & Yang Zu, 2024. "Testing for an Explosive Bubble using High-Frequency Volatility," Working Papers 202402, University of Macau, Faculty of Business Administration.
    3. Philip Stahl & Jérôme Blauth, 2024. "Martingale defects in the volatility surface and bubble conditions in the underlying," Review of Derivatives Research, Springer, vol. 27(1), pages 85-111, April.
    4. Robert A. Jarrow & Simon S. Kwok, 2023. "An explosion time characterization of asset price bubbles," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 469-479, June.
    5. Mahalakshmi Manian & Parthajit Kayal, 2024. "Detecting and Forecasting Financial Bubbles in The Indian Stock Market Using Machine Learning Models," Working Papers 2024-270, Madras School of Economics,Chennai,India.
    6. Francesca Biagini & Lukas Gonon & Andrea Mazzon & Thilo Meyer-Brandis, 2022. "Detecting asset price bubbles using deep learning," Papers 2210.01726, arXiv.org, revised Jun 2024.
    7. Osband, Kent & Filoso, Valerio & Capasso, Salvatore, 2024. "The limits of limitless debt," Journal of Macroeconomics, Elsevier, vol. 79(C).

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