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Title: Pricing and hedging of non-affine ARSV options using volatility dependent kernels Authors:  Alex Badescu - University of Calgary (Canada)
Lyudmila Grigoryeva - University of Konstanz (Germany) [presenting]
Juan-Pablo Ortega - University St. Gallen (Switzerland)
Abstract: New pricing and hedging strategies are proposed for a non-affine auto-regressive stochastic volatility (ARSV) models with non-predictable drift which allows to account for leverage effects. We consider a volatility dependent exponential linear pricing kernel with stochastic risk aversion parameters and implement both pricing and hedging for ARSV models estimated via the hierarchical-likelihood method. This technique proves to outperform standard GARCH and Heston-Nandi based strategies in terms of a variety of considered criteria in an empirical exercise using historical returns and options data.