We propose a class of discrete-time stochastic volatility models that, in a parsimonious way, capture the time-varying higher moments observed in financial series. Three desirable results are obtained. First, we have a recursive procedure for the log-price characteristic function which allows a semi-analytical formula for option prices as in Heston and Nandi. Second, we reproduce some features of the VIX Index. Finally, we derive a simple formula for the VIX index and use it for option pricing

Hitaj, A., Mercuri, L., Rroji, E. (2018). VIX computation based on affine stochastic volatility models in discrete time. In International Series in Operations Research and Management Science (pp. 141-164). Springer New York LLC [10.1007/978-3-319-61320-8_7].

VIX computation based on affine stochastic volatility models in discrete time

Hitaj, A.
Primo
;
Mercuri, L.
Secondo
;
Rroji, E.
Ultimo
2018

Abstract

We propose a class of discrete-time stochastic volatility models that, in a parsimonious way, capture the time-varying higher moments observed in financial series. Three desirable results are obtained. First, we have a recursive procedure for the log-price characteristic function which allows a semi-analytical formula for option prices as in Heston and Nandi. Second, we reproduce some features of the VIX Index. Finally, we derive a simple formula for the VIX index and use it for option pricing
Capitolo o saggio
Affine stochastic volatility; Implied volatility surface; VIX; Software; Computer Science Applications1707 Computer Vision and Pattern Recognition; Strategy and Management1409 Tourism, Leisure and Hospitality Management; Management Science and Operations Research; Applied Mathematics
English
International Series in Operations Research and Management Science
2018
978-3-319-61318-5
257
Springer New York LLC
141
164
Hitaj, A., Mercuri, L., Rroji, E. (2018). VIX computation based on affine stochastic volatility models in discrete time. In International Series in Operations Research and Management Science (pp. 141-164). Springer New York LLC [10.1007/978-3-319-61320-8_7].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/180597
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