Original title: Bayesian vector auto-regression model with Laplace errors applied to financial market data
Authors: Šindelář, Jan
Document type: Papers
Conference/Event: Mathematical Methods in Economics 2010, České Budějovice (CZ), 2010-09-08 / 2010-09-10
Year: 2010
Language: eng
Abstract: The article presents alternative version of Bayesian vector auto-regression model with Laplace distributed innovations. Bayesian estimation in such model is more computationally demanding than estimation in a model with normally distributed innovations, but because of the heavier tails of Laplace distribution, it is more robust. In the article I try to present the way of proceeding with the estimation, obtaining a full posterior distribution of the parameters as a result. At the end an efficient algorithm is sketched, but this part of the research is still unfinished.
Keywords: auto-regression; parameter estimation; robust
Project no.: CEZ:AV0Z10750506 (CEP), 1M0572 (CEP), GA102/08/0567 (CEP)
Funding provider: GA MŠk, GA ČR
Host item entry: Proceedings of Mathematical Methods in Economics 2010, ISBN 978-80-7394-218-2

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2010/AS/sindelar-bayesian vector auto-regression model with laplace errors applied to financial market data.pdf
Original record: http://hdl.handle.net/11104/0187854

Permalink: http://www.nusl.cz/ntk/nusl-41645


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Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers