Performance evaluation of mutual fund investments: The impact of non-normality and time-varying volatility
- 13 Downloads
Extending previous work on mutual fund pricing, this article introduces the idea of modeling the conditional distribution of mutual fund returns using a fat tailed density and a time-varying conditional variance. This approach takes into account the stylized facts of mutual fund return series, that is heteroscedasticity and deviations from normality. We evaluate mutual fund performance using multifactor asset pricing models, with the relevant risk factors being identified through standard model selection techniques. We explore potential impacts of our approach by analyzing individual mutual funds and show that it can be economically important.
Keywordsfat tails GARCH model selection techniques mutual funds risk factors portfolio construction
We thank Mark Carhart for giving us access to the data of the ‘momentum’ factor. The Fama and French (1993) ‘size’ and ‘book-to-market’ factors’ data were obtained from Kenneth French's homepage.
- Akaike, H. (1973) Information theory and an extension of the maximum likelihood principle. In: B.N. Petrox and F. Caski (eds.) Second International Symposium on Information Theory. Budapest, Hungary: Akademiai Kiado, pp. 267–281.Google Scholar
- Allen, D.E. and Soucik, V. (2000) In Search of True Performance: Testing Benchmark-Model Validity in Managed Funds Context. Working Paper, Edith Cowan University.Google Scholar
- Breeden, D.T., Gibbons, M.R. and Litzenberger, R.H. (1989) Empirical tests of the consumption-oriented CAPM. Journal of Finance 44: 231–296.Google Scholar