Arbeitspapier

On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers

Sequential Monte Carlo (SMC) methods are widely used for filtering purposes of non-linear economic or financial models. Nevertheless the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov- Chain Monte-Carlo (MCMC) methods. Not only SMC algorithms draw posterior distributions of static or dynamic parameters but additionally provide an estimate of the normalizing constant. The tempered and time (TNT) algorithm, developed in the paper, combines (off-line) tempered SMC inference with on-line SMC inference for estimating many slightly different distributions. The method encompasses the Iterated Batch Importance Sampling (IBIS) algorithm and more generally the Resample Move (RM) algorithm. Besides the number of particles, the TNT algorithm self-adjusts its calibrated parameters and relies on a new MCMC kernel that allows for particle interactions. The algorithm is well suited for efficiently back-testing models. We conclude by comparing in-sample and out-of-sample performances of complex volatility models.

Sprache
Englisch

Erschienen in
Series: NBB Working Paper ; No. 263

Klassifikation
Wirtschaft
Bayesian Analysis: General
Statistical Simulation Methods: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Financial Econometrics
Thema
Bayesian inference
Sequential Monte Carlo
Annealed Importance sampling
Differential Evolution
Volatility models
Multifractal model
Markov-switching model
Monte-Carlo-Simulation
Bayes-Statistik
Sequentialtest
Markov-Kette
Theorie

Ereignis
Geistige Schöpfung
(wer)
Dufays, Arnaud
Ereignis
Veröffentlichung
(wer)
National Bank of Belgium
(wo)
Brussels
(wann)
2014

Handle
Letzte Aktualisierung
10.03.2025, 11:45 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Dufays, Arnaud
  • National Bank of Belgium

Entstanden

  • 2014

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