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VaR and CVaR Implied in Option Prices

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  • Giovanni Barone Adesi

    (The Swiss Finance Institute at the Università della Svizzera italiana, 6904 Lugano, Switzerland)

Abstract

VaR (Value at Risk) and CVaR (Conditional Value at Risk) are implied by option prices. Their relationships to option prices are derived initially under the pricing measure. It does not require assumptions about the distribution of portfolio returns. The effects of changes of measure are modest at the short horizons typically used in applications. The computation of CVaR from option price is very convenient, because this measure is not elicitable, making direct comparisons of statistical inferences from market data problematic.

Suggested Citation

  • Giovanni Barone Adesi, 2016. "VaR and CVaR Implied in Option Prices," JRFM, MDPI, vol. 9(1), pages 1-6, February.
    • Handle: RePEc:gam:jjrfmx:v:9:y:2016:i:1:p:2-:d:64713
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    References listed on IDEAS

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    Cited by:

    1. Annalisa Molino & Carlo Sala, 2021. "Forecasting value at risk and conditional value at risk using option market data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1190-1213, November.
    2. Sangwon Suh & Eungyu Yoo & Sun‐Joong Yoon, 2021. "Stock market tail risk, tail risk premia, and return predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1569-1596, October.
    3. Fabio Bellini & Edit Rroji & Carlo Sala, 2022. "Implicit quantiles and expectiles," Annals of Operations Research, Springer, vol. 313(2), pages 733-753, June.
    4. Manuel Ammann & Alexander Feser, 2019. "Option-implied Value-at-Risk and the cross-section of stock returns," Review of Derivatives Research, Springer, vol. 22(3), pages 449-474, October.
    5. Ngoc Phu Tran & Thang Cong Nguyen & Duc Hong Vo & Michael McAleer, 2019. "Market Risk Analysis of Energy in Vietnam," Risks, MDPI, vol. 7(4), pages 1-13, November.
    6. Kai Schindelhauer & Chen Zhou, 2018. "Value-at-Risk prediction using option-implied risk measures," DNB Working Papers 613, Netherlands Central Bank, Research Department.
    7. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2019. "Quantifying Risk in Traditional Energy and Sustainable Investments," Sustainability, MDPI, vol. 11(3), pages 1-22, January.
    8. Ziegel, Johanna F. & Krueger, Fabian & Jordan, Alexander & Fasciati, Fernando, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Working Papers 0632, University of Heidelberg, Department of Economics.
    9. Johanna F. Ziegel & Fabian Kruger & Alexander Jordan & Fernando Fasciati, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Papers 1705.04537, arXiv.org.
    10. Giovanni Barone‐Adesi & Chiara Legnazzi & Carlo Sala, 2019. "Option‐implied risk measures: An empirical examination on the S&P 500 index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1409-1428, October.

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