Bayesian Value-at-Risk with product partition models

DOI10.1080/14697680903512786zbMath1278.91185arXiv0809.0241OpenAlexW2065859069MaRDI QIDQ2869966

Claudia Tarantola, Maria Elena De Giuli, Giacomo Bormetti, Danilo Delpini

Publication date: 17 January 2014

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0809.0241

zbMATH Keywords

Monte Carlo methodsstatistical physicsvalue at risknon-Gaussian distributions

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Bayesian inference (62F15) Statistical methods; economic indices and measures (91B82)

Related Items (3)

Remaining useful life prediction: A multiple product partition approach ⋮ Nonparametric product partition models for multiple change-points analysis ⋮ Product partition latent variable model for multiple change-point detection in multivariate data

Cites Work

• Full predictivistic modeling of stock market data: application to change point problems
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• Detecting log-periodicity in a regime-switching model of stock returns
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• A semiparametric Bayesian model for randomised block designs
• Bayesian Clustering and Product Partition Models
• Monte Carlo sampling methods using Markov chains and their applications

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