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92 – 92 - Time Series and Finance
Option Pricing with Higher-Order Stochastic Volatility Models
Md. Nazmul Ahsan
Concordia University
We study the performance of higher-order stochastic volatility [SV(p)] models in the valuation of options. This class of models provides more flexibility to represent volatility persistence and heavy tails and are natural extensions of the leading Hull and White (1987) model used in option pricing. A simulation-based option pricing algorithm is developed, which uses the winsorized ARMA-based estimator of Ahsan and Dufour (2021). The proposed algorithm is applied to S&P 500 European call options (2015-2019). We find that the SV(3) model provides the smallest pricing error among the competing models in all levels of moneyness. Our findings highlight the usefulness of higher-order SV models for option pricing.