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

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: longterm 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.

Automated summary

This paper introduces and analyzes a new fractional Barndorff-Nielsen and Shephard (BN-S) stochastic volatility model, which combines long-term memory and jump properties. By deriving new expressions based on fractional Brownian motion, arbitrage-free prices for the model are found, and the model is analyzed in connection to quadratic hedging. Numerical analysis based on VIX data shows the efficiency of the proposed model compared to the Heston model and classical BN-S model.