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Detecting asset price bubbles using deep learning

Author

Listed:
  • Francesca Biagini
  • Lukas Gonon
  • Andrea Mazzon
  • Thilo Meyer-Brandis

Abstract

In this paper we employ deep learning techniques to detect financial asset bubbles by using observed call option prices. The proposed algorithm is widely applicable and model-independent. We test the accuracy of our methodology in numerical experiments within a wide range of models and apply it to market data of tech stocks in order to assess if asset price bubbles are present. Under a given condition on the pricing of call options under asset price bubbles, we are able to provide a theoretical foundation of our approach for positive and continuous stochastic asset price processes. When such a condition is not satisfied, we focus on local volatility models. To this purpose, we give a new necessary and sufficient condition for a process with time-dependent local volatility function to be a strict local martingale.

Suggested Citation

  • Francesca Biagini & Lukas Gonon & Andrea Mazzon & Thilo Meyer-Brandis, 2022. "Detecting asset price bubbles using deep learning," Papers 2210.01726, arXiv.org, revised Dec 2022.
    • Handle: RePEc:arx:papers:2210.01726
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    References listed on IDEAS

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    1. Erik Ekström & Johan Tysk, 2012. "Dupire'S Equation For Bubbles," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-12.
    2. Robert Jarrow & Younes Kchia & Philip Protter, 2011. "Is there a bubble in LinkedIn's stock price?," Papers 1105.5717, arXiv.org.
    3. Jan Libich & Liam Lenten, 2021. "Bitcoin, Tesla and GameStop Bubbles as a Flight to Focal Points," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 22(1), pages 83-108, January.
    4. Alexander Cox & David Hobson, 2005. "Local martingales, bubbles and option prices," Finance and Stochastics, Springer, vol. 9(4), pages 477-492, October.
    5. Robert A. Jarrow & Simon S. Kwok, 2021. "Inferring financial bubbles from option data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 1013-1046, November.
    6. Loewenstein, Mark & Willard, Gregory A., 2000. "Rational Equilibrium Asset-Pricing Bubbles in Continuous Trading Models," Journal of Economic Theory, Elsevier, vol. 91(1), pages 17-58, March.
    7. Lindsay, A.E. & Brecher, D.R., 2012. "Simulation of the CEV process and the local martingale property," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 868-878.
    8. Petteri Piiroinen & Lassi Roininen & Tobias Schoden & Martin Simon, 2018. "Asset Price Bubbles: An Option-based Indicator," Papers 1805.07403, arXiv.org, revised Jul 2018.
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    Cited by:

    1. Ariel Neufeld & Julian Sester, 2023. "Neural networks can detect model-free static arbitrage strategies," Papers 2306.16422, arXiv.org.

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