A survey of sampling-based Bayesian analysis of financial data

James Sfiridis and Alan Gelfand

Applied Mathematical Finance, 2002, vol. 9, issue 4, 273-291

Abstract: The capability of implementing a complete Bayesian analysis of experimental data has emerged over recent years due to computational advances developed within the statistical community. The objective of this paper is to provide a practical exposition of these methods in the illustrative context of a financial event study. The customary assumption of Gaussian errors underlying development of the model is later supplemented by considering Student-t errors, thus permitting a Bayesian sensitivity analysis. The supplied data analysis illustrates the advantages of the sampling-based Bayesian approach in allowing investigation of quantities beyond the scope of classical methods.

Keywords: Event Studies; Inference; Bayesian; Markov Chain Monte Carlo; Gibbs Sampler (search for similar items in EconPapers)
Date: 2002
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DOI: 10.1080/1350486022000026885

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