In this paper we propose a sequential Monte Carlo algorithm to estimate a stochastic volatility model with leverage effect, non constant conditional mean and jumps. Our idea relies on the auxiliary particle filter algorithm together with the Markov Chain Monte Carlo (MCMC) methodology. Our method allows to sequentially evaluate the parameters and the latent processes involved in the dynamics of interest. An empirical application on simulated data and on the Standard & Poor's 500 index is presented to study the performance of the algorithm implemented.

D. Raggi, S. Bordignon (2007). Sequential Monte Carlo Methods for stochastic volatility models with jumps. PADOVA : CLEUP EDITORE.

Sequential Monte Carlo Methods for stochastic volatility models with jumps

RAGGI, DAVIDE;BORDIGNON, SILVANO
2007

Abstract

In this paper we propose a sequential Monte Carlo algorithm to estimate a stochastic volatility model with leverage effect, non constant conditional mean and jumps. Our idea relies on the auxiliary particle filter algorithm together with the Markov Chain Monte Carlo (MCMC) methodology. Our method allows to sequentially evaluate the parameters and the latent processes involved in the dynamics of interest. An empirical application on simulated data and on the Standard & Poor's 500 index is presented to study the performance of the algorithm implemented.
2007
S.Co. 2007 Fifth Conference - Complex Models and Computational Intensive Methods for Estimation and Prediction
409
414
D. Raggi, S. Bordignon (2007). Sequential Monte Carlo Methods for stochastic volatility models with jumps. PADOVA : CLEUP EDITORE.
D. Raggi; S. Bordignon
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/122607
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact