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Bordignon, Silvano and Raggi, Davide (2007) Volatility, Jumps and Predictability of Returns: a Sequential Analysis. [Working Paper] WORKING PAPER SERIES, 15/2007 . , PADOVA (Inedito)

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Abstract (english)

In this paper we propose a sequential Monte Carlo algorithm to estimate a stochastic volatility model with leverage effects and non constant conditional mean and jumps. We are interested in estimating the time invariant parameters and the non-observable dynamics involved in the model. Our idea relies on the auxiliary particle filter algorithm mixed together with Markov Chain Monte Carlo (MCMC) methodology. Adding an MCMC step to the auxiliary particle filter prevents numerical degeneracies in the sequential algorithm and allows sequential evaluation of the fixed parameters and the latent processes. Empirical evaluation on simulated and real data is presented to assess the performance of the algorithm.


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EPrint type:Working Paper
Anno di Pubblicazione:November 2007
Key Words:Stochastic volatility with jumps, leverage, return's predictability, Bayesian estimation, auxiliary particle filters, MCMC.
Settori scientifico-disciplinari MIUR:Area 13 - Scienze economiche e statistiche > SECS-S/01 Statistica
Struttura di riferimento:Dipartimenti > Dipartimento di Scienze Statistiche
Codice ID:7107
Depositato il:11 Sep 2014 14:38
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