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Fractional Barndorff-Nielsen and Shephard model: applications in variance and volatility swaps, and hedging

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Abstract

In this paper, we introduce and analyze the fractional Barndorff-Nielsen and Shephard (BN-S) stochastic volatility model. The proposed model is based upon two desirable properties of the long-term variance process suggested by the empirical data: long-term memory and jumps. The proposed model incorporates the long-term memory and positive autocorrelation properties of fractional Brownian motion with \(H>1/2\), and the jump properties of the BN-S model. We find arbitrage-free prices for variance and volatility swaps for this new model. Because fractional Brownian motion is still a Gaussian process, we derive some new expressions for the distributions of integrals of continuous Gaussian processes as we work towards an analytic expression for the prices of these swaps. The model is analyzed in connection to the quadratic hedging problem and some related analytical results are developed. The amount of derivatives required to minimize a quadratic hedging error is obtained. Finally, we provide some numerical analysis based on the VIX data. Numerical results show the efficiency of the proposed model compared to the Heston model and the classical BN-S model.

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References

  • Alós, E., Leòn, J.A., Vives, J.: On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility. Finance Stochast. 11(4), 571–589 (2007)

    Article  Google Scholar 

  • Alós, E., Yang, Y.: A fractional Heston model with \(H>\frac{1}{2}\). Stochastics 89(1), 384–399 (2017)

    Article  Google Scholar 

  • Baillie, R.T.: Long memory processes and fractional integration in econometrics. J. Econ. 73(1), 5–59 (1996)

    Article  Google Scholar 

  • Baillie, R.T., Calonaci, F., Cho, D., Rho, S.: Long memory, realized volatility and heterogeneous autoregressive models. J. Time Ser. Anal. 40(4), 609–628 (2019)

    Article  Google Scholar 

  • Barndorff-Nielsen, O.E., Shephard, N.: Non-Gaussian Ornstein-Uhlenbeck-based models and some of their uses in financial economics. J. R. Stat. Soc. Ser. B (Stat. Methodol.) 63, 167–241 (2001)

    Article  Google Scholar 

  • Barndorff-Nielsen, O. E., Shephard, N.: Modelling by Lévy processes for financial econometrics, In: Barndorff-Nielsen, O.E., Mikosch, T., Resnick, S. (eds.) Lévy Processes: Theory and Applications, 283-318, Birkhäuser (2001)

  • Bayer, C., Friz, P., Gassiat, P., Martin, J., Stemper, B.: A regularity structure for rough volatility. Math. Finance 30(3), 782–832 (2020)

    Article  Google Scholar 

  • Bayer, C., Friz, P., Gatheral, J.: Pricing under rough volatility. Quant. Finance 16(6), 887–904 (2016)

    Article  Google Scholar 

  • Bennedsen, M., Lunde, A., Pakkanen, M.S.: Decoupling the short- and long-term behavior of stochastic volatility. J. Financ. Econ. 1–46 (2021). https://doi.org/10.1093/jjfinec/nbaa049

  • Benth, F.E., Groth, M., Kufakunesu, R.: Valuing volatility and variance swaps for a non-Gaussian Ornstein–Uhlenbeck stochastic volatility model. Appl. Math. Finance 14(4), 347–363 (2007)

    Article  Google Scholar 

  • Comte, F., Coutin, L., Renault, E.: Affine fractional stochastic volatility models. Ann. Finance 8(2–3), 337–378 (2012)

    Article  Google Scholar 

  • Comte, F., Renault, E.: Long memory in continuous-time stochastic volatility models. Math. Finance 8(4), 291–323 (1998)

    Article  Google Scholar 

  • Cont, R.: Empirical properties of asset returns: stylized facts and statistical issues. Quant. Finance 1, 223–236 (2001)

    Article  Google Scholar 

  • Cont, R., Tankov, P.: Financial Modelling With Jump Processes, Chapman and Hall/CRC Financial Mathematics Series (2004)

  • Ding, Z., Granger, C.W.J., Engle, R.F.: A long memory property of stock market returns and a new model. J. Empirical Finance 1(1), 83–106 (1993)

    Article  Google Scholar 

  • Fink, H., Klüppelberg, C., Zähle, M.: Conditional distributions of processes related to fractional Brownian motion. J. Appl. Probab. 50(1), 166–183 (2013)

    Article  Google Scholar 

  • Gatheral, J., Jaisson, T., Rosenbaum, M.: Volatility is rough. Quant. Finance 18(6), 933–949 (2018)

    Article  Google Scholar 

  • Habtemicael, S., SenGupta, I.: Pricing variance and volatility swaps for Barndorff–Nielsen and Shephard process driven financial markets. Int. J. Financ. Eng., 3(4) 1650027 (2016)

  • Habtemicael, S., SenGupta, I.: Pricing covariance swaps for Barndorff–Nielsen and Shephard process driven financial markets. Ann. Financ. Econ. 11, 1650012 (2016)

  • Issaka, A., SenGupta, I.: Analysis of variance based instruments for Ornstein–Uhlenbeck type models: swap and price index. Ann. Finance 13(4), 401–434 (2017)

    Article  Google Scholar 

  • Kallenberg, O.: Foundations of Modern Probability. Springer, Berlin (2002)

    Book  Google Scholar 

  • Kim, S.-W., Kim, J.-H.: Volatility and variance swaps and options in the fractional SABR model. Eur. J. Finance 26(17), 1725–1745 (2020)

    Article  Google Scholar 

  • Miljkovic, T., SenGupta, I.: A new analysis of VIX using mixture of regressions: examination and short-term forecasting for the S & P 500 market. High frequency 1(1), 53–65 (2018)

    Article  Google Scholar 

  • Nicolato, E., Venardos, E.: Option pricing in stochastic volatility models of the Ornstein-Uhlenbeck type. Math. Finance 13, 445–466 (2003)

    Article  Google Scholar 

  • Nourdin, I.: Selected Aspects of Fractional Brownian Motion. Springer, Berlin (2021)

    Google Scholar 

  • Roberts, M., SenGupta, I.: Infinitesimal generators for two-dimensional Lévy process-driven hypothesis testing. Ann. Finance 16(1), 121–139 (2020)

    Article  Google Scholar 

  • Salvi, G., Swishchuk, A.: Covariance and correlation swaps for financial markets with Markov-modulated volatilities. Int. J. Theoret. Appl. Finance, 17(1), 1450006-1-1450006-23 (2014)

  • SenGupta, I.: Generalized BN-S stochastic volatility model for option pricing. Int. J. Theoret. Appl. Finance, 19(02), 1650014 (2016)

  • SenGupta, I., Wilson, W., Nganje, W.: Barndorff–Nielsen and Shephard model: oil hedging with variance swap and option. Math. Financ. Econ. 13(2), 209–226 (2019)

    Article  Google Scholar 

  • Shoshi, H., SenGupta, I.: Hedging and machine learning driven crude oil data analysis using a refined Barndorff-Nielsen and Shephard model. Int. J. Financ. Eng. https://doi.org/10.1142/S2424786321500158 (2021)

  • Swishchuk, A.: Modeling and pricing of variance swaps for multi-factor stochastic volatilities with delay. Can. Appl. Math. Q. 14(4), 439–67 (2006)

    Google Scholar 

  • Swishchuk, A.: Modeling and Pricing of Swaps for Financial and Energy Markets with Stochastic Volatilities. World Scientific Publishing Company, Singapore (2013)

    Book  Google Scholar 

  • Swishchuk, A., Vadori, N.: Smiling for the delayed volatility swaps. Wilmott 2014(74), 62–73 (2014)

    Article  Google Scholar 

  • Wilson, W., Nganje, W., Gebresilasie, S., SenGupta, I.: Barndorff-Nielsen and Shephard model for hedging energy with quantity risk. High Frequency 2(3–4), 202–214 (2019)

    Article  Google Scholar 

  • Young, L.C.: An inequality of the Hölder type, connected with Stieltjes integration. Acta Math. 67, 251–282 (1936)

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the anonymous reviewers for their careful reading of the manuscript and for suggesting points to improve the quality of the paper.

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Correspondence to Indranil SenGupta.

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Salmon, N., SenGupta, I. Fractional Barndorff-Nielsen and Shephard model: applications in variance and volatility swaps, and hedging. Ann Finance 17, 529–558 (2021). https://doi.org/10.1007/s10436-021-00394-4

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