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Investor learning and mutual fund family.

Zhang, Z. and Ding, L. and Zhou, S. (2014) 'Investor learning and mutual fund family.', Journal of empirical finance., 26 . pp. 171-188.


In this paper we revisit the cross-fund learning method suggested by Jones and Shanken (2005) and construct a linear hierarchical model to consider the learning across funds within the fund family during the performance evaluation. We provide a full Bayesian treatment on all the factors of the pricing model and allow both the fund family and the individual manager to have dependent prior information regarding funds' alphas. The simulation results suggest that returns from peer funds within the family significantly affect investors' updating on fund alphas since the posterior distribution on fund alphas experiences a faster shrinkage than those reported in the previous literature. The model can also be simulated with specific prior belief on different factors of the pricing model, i.e. fund alphas, betas and factor loadings of each pricing benchmark, to better address the learning issue.

Item Type:Article
Keywords:Mutual fund, Performance, Bayesian analysis, Hierarchical model.
Full text:(AM) Accepted Manuscript
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Publisher statement:NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Empirical Finance. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Empirical Finance, 26, 2014, 10.1016/j.jempfin.2013.12.001.
Date accepted:04 December 2013
Date deposited:24 April 2014
Date of first online publication:13 December 2013
Date first made open access:No date available

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