Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors

Mark Fisher and Mark Jensen

No 2018-2, FRB Atlanta Working Paper from Federal Reserve Bank of Atlanta

Abstract: Change point models using hierarchical priors share in the information of each regime when estimating the parameter values of a regime. Because of this sharing, hierarchical priors have been very successful when estimating the parameter values of short-lived regimes and predicting the out-of-sample behavior of the regime parameters. However, the hierarchical priors have been parametric. Their parametric nature leads to global shrinkage that biases the estimates of the parameter coefficient of extraordinary regimes toward the value of the average regime. To overcome this shrinkage, we model the hierarchical prior nonparametrically by letting the hyperparameter's prior?in other words, the hyperprior?be unknown and modeling it with a Dirichlet processes prior. To apply a nonparametric hierarchical prior to the probability of a break occurring, we extend the change point model to a multiple-change-point panel model. The hierarchical prior then shares in the cross-sectional information of the break processes to estimate the transition probabilities. We apply our multiple-change-point panel model to a longitudinal data set of actively managed, U.S. equity, mutual fund returns to measure fund performance and investigate the chances of a skilled fund being skilled in the future.

Keywords: Bayesian nonparametric analysis; change points; Dirichlet process; hierarchical priors; mutual fund performance (search for similar items in EconPapers)
JEL-codes: C11 C14 C41 G11 G17 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2018-02-01
New Economics Papers: this item is included in nep-ets and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.frbatlanta.org/-/media/documents/resea ... riors-2018-02-22.pdf Full text (application/pdf)

Related works:
Journal Article: Bayesian inference and prediction of a multiple-change-point panel model with nonparametric priors (2019)
Working Paper: Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fip:fedawp:2018-02

Ordering information: This working paper can be ordered from

DOI: 10.29338/wp2018-02

Access Statistics for this paper

More papers in FRB Atlanta Working Paper from Federal Reserve Bank of Atlanta Contact information at EDIRC.
Bibliographic data for series maintained by Rob Sarwark ().