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Stochastic volatility models for the implied correlation index

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  • Escobar, Marcos
  • Fang, Lin

Abstract

This paper studies the implied correlation index (CIX), revealing a new stylized fact: heteroscedasticity in correlation. A correlation stochastic volatility (C-SV) model is proposed and a consistent estimation methodology is implemented on CBOE S&P 500 CIX historical data. The impact of the SV parameters is studied for two types of crisis-motivated CIX derivatives, and the empirical study demonstrates that new parameters can have a significant influence of up to 60% on digital option prices.

Suggested Citation

  • Escobar, Marcos & Fang, Lin, 2020. "Stochastic volatility models for the implied correlation index," Finance Research Letters, Elsevier, vol. 35(C).
    • Handle: RePEc:eee:finlet:v:35:y:2020:i:c:s154461231930056x
    DOI: 10.1016/j.frl.2019.101309
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    1. Black, Fischer & Cox, John C, 1976. "Valuing Corporate Securities: Some Effects of Bond Indenture Provisions," Journal of Finance, American Finance Association, vol. 31(2), pages 351-367, May.
    2. G. Rubbaniy & Robel Asmerom & Syed Kumail Abbas Rizvi & Bushra Naqvi, 2014. "Do fear indices help predict stock returns?," Quantitative Finance, Taylor & Francis Journals, vol. 14(5), pages 831-847, May.
    3. Roger Lord & Remmert Koekkoek & Dick Van Dijk, 2010. "A comparison of biased simulation schemes for stochastic volatility models," Quantitative Finance, Taylor & Francis Journals, vol. 10(2), pages 177-194.
    4. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    5. Markopoulou, Chryssa & Skintzi, Vasiliki & Refenes, Apostolos, 2016. "On the predictability of model-free implied correlation," International Journal of Forecasting, Elsevier, vol. 32(2), pages 527-547.
    6. Florence Guillaume & Daniël Linders, 2015. "Stochastic modelling of herd behaviour indices," Quantitative Finance, Taylor & Francis Journals, vol. 15(12), pages 1963-1977, December.
    7. Dhaene, Jan & Linders, Daniël & Schoutens, Wim & Vyncke, David, 2012. "The Herd Behavior Index: A new measure for the implied degree of co-movement in stock markets," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 357-370.
    8. Vasiliki D. Skintzi & Apostolos‐Paul N. Refenes, 2005. "Implied correlation index: A new measure of diversification," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 25(2), pages 171-197, February.
    9. Giovanni Salvi & Anatoliy V. Swishchuk, 2014. "Covariance And Correlation Swaps For Financial Markets With Markov-Modulated Volatilities," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-23.
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