ME> Vol.8 No.8, August 2017

Author(s)

Bruno Rémillard¹, Alexandre Hocquard², Hugo Lamarre¹, Nicolas Papageorgiou^2,3

¹Department of Decision Sciences, HEC Montréal, Montréal, Canada.
²Fiera Capital Corporation, Montréal, Canada.
³Department of Finance, HEC Montréal, Montréal, Canada.

We propose optimal mean-variance dynamic hedging strategies in discrete time under a multivariate Gaussian regime-switching model. The methodology, which also performs pricing, is robust to time-varying and clustering risk observed in financial time series. As such, it overcomes the main theoretical drawbacks of the Black-Scholes model. To support our approach, we provide goodness-of-fit tests to validate the model and for choosing the appropriate number of regimes, and we illustrate the methodology using monthly S & P 500 vanilla options prices. Then, we present the associated out-of-sample hedging results in the context of harvesting the implied versus realized volatility premium. Using the proposed methodology, the Sharpe ratio derived from the strategy doubles over the Black-Scholes delta-hedging methodology.

Option Pricing, Dynamic Hedging, Regime-Switching, Goodness-of-Fit, Hidden Markov Models

Rémillard, B. , Hocquard, A. , Lamarre, H. and Papageorgiou, N. (2017) Option Pricing and Hedging for Discrete Time Regime-Switching Models. Modern Economy, 8, 1005-1032. doi: 10.4236/me.2017.88070.