Bayesian outlier detection in Capital Asset Pricing Model

Details Bayesian outlier detection in Capital Asset Pricing Model Bayesian outlier detection in Capital Asset Pricing Model

2008-06-10

arxiv.org/abs/0806.1631v2

statistical Modelling ,2010, 10, 379--390

Statistics

Applications

Scientific paper

We propose a novel Bayesian optimisation procedure for outlier detection in the Capital Asset Pricing Model. We use a parametric product partition model to robustly estimate the systematic risk of an asset. We assume that the returns follow independent normal distributions and we impose a partition structure on the parameters of interest. The partition structure imposed on the parameters induces a corresponding clustering of the returns. We identify via an optimisation procedure the partition that best separates standard observations from the atypical ones. The methodology is illustrated with reference to a real data set, for which we also provide a microeconomic interpretation of the detected outliers.

Affiliated with

Also associated with

No associations

Rating

Bayesian outlier detection in Capital Asset Pricing Model does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Bayesian outlier detection in Capital Asset Pricing Model, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Bayesian outlier detection in Capital Asset Pricing Model will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-174863