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Bayarri, M.J., Castellanos, M.E. and Morales, J. (2006) MCMC Methods to Approximate Conditional Predictive Distributions. Computational Statistics & Data Analysis, 51, 621-640.
https://doi.org/10.1016/j.csda.2006.01.018

has been cited by the following article:

• TITLE: Bayesian Diagnostic Checking of the Capital Asset Pricing Model

  AUTHORS: Jun Li, Shaun S. Wulff

  KEYWORDS: Finance Model, Model Expansion, Linear Regression, Normality, Outlier, Residual

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.6 No.2, February 8, 2018

  ABSTRACT: The capital asset pricing model (CAPM) is a commonly used regression model in finance to model stock returns. Bayesian methods have been developed for the CAPM to account for market fluctuations within the industry. However, a Bayesian model checking procedure is needed to assess the CAPM in terms of the usual regression model assumptions of independence, homogeneity of variance, and normality. This paper develops Bayesian residuals and Bayesian p-values to check these model assumptions as well as to suggest model extensions to the CAPM.