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The EWMA Heston model

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  • Léo Parent

Abstract

This paper introduces the exponentially weighted moving average (EWMA) Heston model, a Markovian stochastic volatility model able to capture a wide range of empirical features related to volatility dynamics while being more tractable for simulations than rough volatility models based on fractional processes. After presenting the model and its principal characteristics, our analysis focuses on the use of its associated Euler-discretization scheme as a time-series generator for Monte-Carlo simulations. Using this discretization scheme, and on the basis of S&P500 empirical time series, we show that the EWMA Heston model is overall consistent with market data, making it a credible alternative to other existing stochastic volatility models.

Suggested Citation

  • Léo Parent, 2023. "The EWMA Heston model," Quantitative Finance, Taylor & Francis Journals, vol. 23(1), pages 71-93, January.
    • Handle: RePEc:taf:quantf:v:23:y:2023:i:1:p:71-93
    DOI: 10.1080/14697688.2022.2140699
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    Cited by:

    1. Julien Guyon & Jordan Lekeufack, 2023. "Volatility is (mostly) path-dependent," Quantitative Finance, Taylor & Francis Journals, vol. 23(9), pages 1221-1258, September.
    2. Guido Gazzani & Julien Guyon, 2024. "Pricing and calibration in the 4-factor path-dependent volatility model," Papers 2406.02319, arXiv.org.
    3. Fabio Baschetti & Giacomo Bormetti & Pietro Rossi, 2023. "Deep calibration with random grids," Papers 2306.11061, arXiv.org, revised Jan 2024.

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