This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Clustering Mutual Funds by Return and Risk Levels

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
F. Lisi
Edoardo Otranto ()

Additional information is available for the following registered author(s):

Abstract

Mutual funds classifications, often made by rating agencies, are very common and sometimes criticized. In this work, a three-step statistical procedure for mutual funds classification is proposed. In the first step time series funds are characterized in terms of returns. In the second step, a clustering analysis is performed in order to obtain classes of homogeneous funds with respect to the risk levels. In particular, the risk is defined starting from an Asymmetric Threshold-GARCH model aimed to describe minimum, normal and turmoil risk. The third step merges the previous two. An application to 75 European funds belonging to 5 different categories is given.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://crenos.unica.it/crenos/files/wp/08-13.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia in its series Working Paper CRENoS with number 200813.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 2008
Date of revision:
Handle: RePEc:cns:cnscwp:200813

Contact details of provider:
Postal: Viale Sant'Ignazio da Laconi 78, I-09123 Cagliari
Phone: +70/6753759
Fax: +70/6753760
Email:
Web page: http://www.crenos.unica.it/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Ernesto Batteta).

Related research
Keywords: Cluster; distance; GARCH models; risk;

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
G23 - Financial Economics - - Financial Institutions and Services - - - Pension Funds; Other Private Financial Institutions

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. T. Kalantzis & D. Papanastassiou, 2008. "Classification of GARCH time series: an empirical investigation," Applied Financial Economics, Taylor and Francis Journals, vol. 18(9), pages 759-764. [Downloadable!] (restricted)
  2. Pattarin, Francesco & Paterlini, Sandra & Minerva, Tommaso, 2004. "Clustering financial time series: an application to mutual funds style analysis," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 353-372, September. [Downloadable!] (restricted)
  3. Newton Da Costa Jr & Jefferson Cunha & Sergio Da Silva, 2005. "Stock Selection Based on Cluster Analysis," Finance 0509022, EconWPA. [Downloadable!]
    Other versions:
  4. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
  5. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer, vol. 32(3), pages 241-254, September. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? The most prolific authors have over 700 items listed on IDEAS.

This page was last updated on 2009-11-27.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.