Inference for Levy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo
We investigate simulation methodology for Bayesian inference in Lévy-driven stochastic volatility (SV) models. Typically, Bayesian inference from such models is performed using Markov chain Monte Carlo (MCMC); this is often a challenging task. Sequential Monte Carlo (SMC) samplers are methods that c...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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2011
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| _version_ | 1797096352566476800 |
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| author | Jasra, A Stephens, D Doucet, A Tsagaris, T |
| author_facet | Jasra, A Stephens, D Doucet, A Tsagaris, T |
| author_sort | Jasra, A |
| collection | OXFORD |
| description | We investigate simulation methodology for Bayesian inference in Lévy-driven stochastic volatility (SV) models. Typically, Bayesian inference from such models is performed using Markov chain Monte Carlo (MCMC); this is often a challenging task. Sequential Monte Carlo (SMC) samplers are methods that can improve over MCMC; however, there are many user-set parameters to specify. We develop a fully automated SMC algorithm, which substantially improves over the standard MCMC methods in the literature. To illustrate our methodology, we look at a model comprised of a Heston model with an independent, additive, variance gamma process in the returns equation. The driving gamma process can capture the stylized behaviour of many financial time series and a discretized version, fit in a Bayesian manner, has been found to be very useful for modelling equity data. We demonstrate that it is possible to draw exact inference, in the sense of no time-discretization error, from the Bayesian SV model. © 2010 Board of the Foundation of the Scandinavian Journal of Statistics. |
| first_indexed | 2024-03-07T04:40:36Z |
| format | Journal article |
| id | oxford-uuid:d1806c52-9eb7-4f80-bcf9-d8c6d569203c |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:40:36Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | oxford-uuid:d1806c52-9eb7-4f80-bcf9-d8c6d569203c2022-03-27T07:57:21ZInference for Levy-Driven Stochastic Volatility Models via Adaptive Sequential Monte CarloJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:d1806c52-9eb7-4f80-bcf9-d8c6d569203cEnglishSymplectic Elements at Oxford2011Jasra, AStephens, DDoucet, ATsagaris, TWe investigate simulation methodology for Bayesian inference in Lévy-driven stochastic volatility (SV) models. Typically, Bayesian inference from such models is performed using Markov chain Monte Carlo (MCMC); this is often a challenging task. Sequential Monte Carlo (SMC) samplers are methods that can improve over MCMC; however, there are many user-set parameters to specify. We develop a fully automated SMC algorithm, which substantially improves over the standard MCMC methods in the literature. To illustrate our methodology, we look at a model comprised of a Heston model with an independent, additive, variance gamma process in the returns equation. The driving gamma process can capture the stylized behaviour of many financial time series and a discretized version, fit in a Bayesian manner, has been found to be very useful for modelling equity data. We demonstrate that it is possible to draw exact inference, in the sense of no time-discretization error, from the Bayesian SV model. © 2010 Board of the Foundation of the Scandinavian Journal of Statistics. |
| spellingShingle | Jasra, A Stephens, D Doucet, A Tsagaris, T Inference for Levy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo |
| title | Inference for Levy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo |
| title_full | Inference for Levy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo |
| title_fullStr | Inference for Levy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo |
| title_full_unstemmed | Inference for Levy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo |
| title_short | Inference for Levy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo |
| title_sort | inference for levy driven stochastic volatility models via adaptive sequential monte carlo |
| work_keys_str_mv | AT jasraa inferenceforlevydrivenstochasticvolatilitymodelsviaadaptivesequentialmontecarlo AT stephensd inferenceforlevydrivenstochasticvolatilitymodelsviaadaptivesequentialmontecarlo AT douceta inferenceforlevydrivenstochasticvolatilitymodelsviaadaptivesequentialmontecarlo AT tsagarist inferenceforlevydrivenstochasticvolatilitymodelsviaadaptivesequentialmontecarlo |