Home About Latest Browse RSS Advanced Search

Federal Reserve Bank of Atlanta
FRB Atlanta Working Paper
Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors
Mark Fisher
Mark J. Jensen
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.


Download Full text
Cite this item
Mark Fisher & Mark J. Jensen, Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors, Federal Reserve Bank of Atlanta, FRB Atlanta Working Paper 2018-2, 01 Feb 2018.
More from this series
JEL Classification:
Subject headings:
Keywords: Bayesian nonparametric analysis; change points; Dirichlet process; hierarchical priors; mutual fund performance
DOI: 10.29338/wp2018-02
For corrections, contact Elaine Clokey ()
Fed-in-Print is the central catalog of publications within the Federal Reserve System. It is managed and hosted by the Economic Research Division, Federal Reserve Bank of St. Louis.

Privacy Legal