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Temporal Volatility Surface Projection: Parametric Surface Projection Method for Derivatives Portfolio Risk Management

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  • Shiva Zamani
  • Alireza Moslemi Haghighi
  • Hamid Arian

Abstract

This study delves into the intricate realm of risk evaluation within the domain of specific financial derivatives, notably options. Unlike other financial instruments, like bonds, options are susceptible to broader risks. A distinctive trait characterizing this category of instruments is their non-linear price behavior relative to their pricing parameters. Consequently, evaluating the risk of these securities is notably more intricate when juxtaposed with analogous scenarios involving fixed-income instruments, such as debt securities. A paramount facet in options risk assessment is the inherent uncertainty stemming from first-order fluctuations in the underlying asset's volatility. The dynamic patterns of volatility fluctuations manifest striking resemblances to the interest rate risk associated with zero-coupon bonds. However, it is imperative to bestow heightened attention on this risk category due to its dependence on a more extensive array of variables and the temporal variability inherent in these variables. This study scrutinizes the methodological approach to risk assessment by leveraging the implied volatility surface as a foundational component, thereby diverging from the reliance on a singular estimate of the underlying asset's volatility.

Suggested Citation

  • Shiva Zamani & Alireza Moslemi Haghighi & Hamid Arian, 2023. "Temporal Volatility Surface Projection: Parametric Surface Projection Method for Derivatives Portfolio Risk Management," Papers 2311.14985, arXiv.org.
  • Handle: RePEc:arx:papers:2311.14985
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    References listed on IDEAS

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    1. Toby Daglish & John Hull & Wulin Suo, 2007. "Volatility surfaces: theory, rules of thumb, and empirical evidence," Quantitative Finance, Taylor & Francis Journals, vol. 7(5), pages 507-524.
    2. Benoit Mandelbrot & Howard M. Taylor, 1967. "On the Distribution of Stock Price Differences," Operations Research, INFORMS, vol. 15(6), pages 1057-1062, December.
    3. Peter Carr & Liuren Wu, 2020. "Option Profit and Loss Attribution and Pricing: A New Framework," Journal of Finance, American Finance Association, vol. 75(4), pages 2271-2316, August.
    4. Şener, Emrah & Baronyan, Sayad & Ali Mengütürk, Levent, 2012. "Ranking the predictive performances of value-at-risk estimation methods," International Journal of Forecasting, Elsevier, vol. 28(4), pages 849-873.
    5. Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Applied Energy, Elsevier, vol. 293(C).
    6. Pritsker, Matthew, 2006. "The hidden dangers of historical simulation," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 561-582, February.
    7. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    8. repec:bla:jfinan:v:53:y:1998:i:6:p:2059-2106 is not listed on IDEAS
    9. Hull, John C & White, Alan D, 1987. "The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
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