Narrow search
Showing 1 - 10 of 10,076
Cover Image
An Efficient Parallel Simulation Method for Posterior Inference on Paths of Markov Processes
Held, Matthias; Omachel, Marcel - Fakultät für Wirtschaftswissenschaft, … - 2014
In this note, we propose a method for efficient simulation of paths of latent Markovian state processes in a Markov Chain Monte Carlo setting. Our method harnesses available parallel computing power by breaking the sequential nature of commonly encountered state simulation routines. We offer a...
Persistent link: https://www.econbiz.de/10010960419
Cover Image
Estimating and forecasting structural breaks in financial time series
BAUWENS, Luc; DUFAYS, Arnaud; DE BACKER, Bruno - Center for Operations Research and Econometrics (CORE), … - 2011
We present an algorithm, based on a differential evolution MCMC method, for Bayesian inference in AR-GARCH models subject to an unknown number of structural breaks at unknown dates. Break dates are directly treated as parameters and the number of breaks is determined by the marginal likelihood...
Persistent link: https://www.econbiz.de/10010927663
Cover Image
Infinite-state Markov-switching for dynamic volatility and correlation models
DUFAYS, Arnaud - Center for Operations Research and Econometrics (CORE), … - 2012
Dynamic volatility and correlation models with fixed parameters are restrictive for time series subject to breaks …
Persistent link: https://www.econbiz.de/10010927665
Cover Image
On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers
Dufays, Arnaud - Nationale Bank van België/Banque national de Belqique (BNB) - 2014
back-testing models. We conclude by comparing in-sample and out-of-sample performances of complex volatility models. …
Persistent link: https://www.econbiz.de/10011272750
Cover Image
Autoregressive moving average infinite hidden markov-switching models
Bauwens, Luc; Carpantier, Jean-François; Dufays, Arnaud - Center for Operations Research and Econometrics (CORE), … - 2015
Markov-switching models are usually specified under the assumption that all the parameters change when a regime switch occurs. Relaxing this hypothesis and being able to detect which parameters evolve over time is relevant for interpreting the changes in the dynamics of the series, for...
Persistent link: https://www.econbiz.de/10011246294
Cover Image
The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation
Basturk, Nalan; Hoogerheide, Lennart; Opschoor, Anne; … - Tinbergen Instituut - 2012
This paper presents the R package MitISEM, which provides an automatic and flexible method to approximate a non-elliptical target density using adaptive mixtures of Student-t densities, where only a kernel of the target density is required. The approximation can be used as a candidate density in...
Persistent link: https://www.econbiz.de/10011255807
Cover Image
Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo
Zellner, Arnold; Ando, Tomohiro; Basturk, Nalan; … - Tinbergen Instituut - 2012
This discussion paper resulted in a publication in <I>Econometric Reviews</I>. Vol. 33(1-4), 3-35.<P> We discuss Bayesian inferential procedures within the family of instrumental variables regression models and focus on two issues: existence conditions for posterior moments of the parameters of interest...</p></i>
Persistent link: https://www.econbiz.de/10011256253
Cover Image
MCMC Bayesian Estimation of a Skew-GED Stochastic Volatily Model
Cappuccio, Nunzio; Lubian, Diego; Raggi, Davide - Dipartimento di Scienze Economiche, Facoltà di Economia - 2003
In this paper we present a stochastic volatility model assuming that the return shock has a Skew-GED distribution. This …
Persistent link: https://www.econbiz.de/10011264964
Cover Image
AdMit: Adaptive Mixtures of Student-t Distributions
Ardia, David; van Dijk, Herman K.; Hoogerheide, … - Departement für Quantitative Wirtschaftsforschung, … - 2008
This short note presents the R package AdMit which provides flexible functions to approximate a certain target distribution and to efficiently generate a sample of random draws from it, given only a kernel of the target density function. The estimation procedure is fully automatic and thus...
Persistent link: https://www.econbiz.de/10005244931
Cover Image
Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications
Nakajima, Jouchi - In: Monetary and Economic Studies 29 (2011) November, pp. 107-142
structural vector autoregression (TVP-VAR) with stochastic volatility, in both methodology and empirical applications. The TVP …-VAR model, combined with stochastic volatility, enables us to capture possible changes in underlying structure of the economy in … stochastic volatility into the TVP estimation significantly improves estimation performance. The Markov chain Monte Carlo method …
Persistent link: https://www.econbiz.de/10009364154