EconPapers    
Economics at your fingertips  
 

A New Direction of Fund Rating Based on the Finite Normal Mixture Model

Zhangpeng Gao and Shahidur Rahman
Additional contact information
Zhangpeng Gao: Nanyang Technological University, Singapore
Shahidur Rahman: Division of Economics,School of Humanities and Social Sciences, Nanyang Technological University, Singapore

No 603, Economic Growth Centre Working Paper Series from Nanyang Technological University, School of Social Sciences, Economic Growth Centre

Abstract: In this paper we try to develop a theoretical framework for fund rating under the assumption that superior funds could have a higher expected return than that of inferior funds, which could arise from the segmented market information or the differentiated ability of mangers to acquire and analyze the information. Under this setting, the funds are rated based on the cross-sectional distribution of all the funds instead of the presetpercentiles as Morningstar. We use the finite normal mixture for rating fund performance with the number of performance groups determined by likelihood ratio test using parametric bootstrap procedures, and we estimate the model with EM algorithm by treating the group information of funds as missing information.

Keywords: Fund Rating; Fund Performance; Finite Normal Mixture; Bootstrap; EM Algorithm (search for similar items in EconPapers)
JEL-codes: C1 D4 G0 G1 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2006-03
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www3.ntu.edu.sg/hss2/egc/wp/2006/2006-03.pdf (application/pdf)

Related works:
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:nan:wpaper:0603

Access Statistics for this paper

More papers in Economic Growth Centre Working Paper Series from Nanyang Technological University, School of Social Sciences, Economic Growth Centre Contact information at EDIRC.
Bibliographic data for series maintained by Magdalene Lim ().

 
Page updated 2025-07-18
Handle: RePEc:nan:wpaper:0603