Errors in variables; Hedge fund performance; Asset pricing models
Abstract :
[en] This paper revisits the performance of hedge funds in the presence of errors in variables. To reduce the bias induced by measurement error, we introduce an estimator based on cross sample moments of orders three and four. This Higher Moment Estimation (HME) technique has significant consequences on the measure of factor loadings and the estimation of abnormal performance. Large changes in alphas can be attributed to measurement errors at the level of explanatory variables, while we emphasize some shifts in the economic contents of the equity risk premiums by switching from OLS to HME.
Disciplines :
Finance
Author, co-author :
Coën, Alain
Hübner, Georges ; Université de Liège - ULiège > HEC-Ecole de gestion : UER > Gestion financière
Language :
English
Title :
Risk and performance estimation in hedge funds revisited: Evidence from errors in variables
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Bibliography
Agarwal V., and Naik N.Y. Risks and portfolio decisions involving hedge funds. Review of Financial Studies 17 (2004) 63-98
Bailey W., Li H., and Zhang X. Hedge fund performance evaluation: a stochastic discount factor approach. Working Paper (2004), Cornell University
Capocci D., and Hübner G. Analysis of hedge fund performance. Journal of Empirical Finance 11 (2004) 55-89
Carhart M. On persistence in mutual funds performance. Journal of Finance 52 (1997) 57-82
Carmichael B., and Coën A. Asset pricing models with errors-in-variables. Journal of Empirical Finance 15 (2008) 778-788
Chen Y., and Liang B. Do market timing hedge funds time the market?. Journal of Financial and Quantitative Analysis 42 (2007) 827-856
Cragg J.G. Making good inferences from bad data. Canadian Journal of Economics 27 (1994) 776-800
Cragg J.G. Using higher moments to estimate simple error-in-variable model. Rand Journal of Economics 28 (1997) S71-S91
Dagenais M.G. Parameter estimation in regression models with errors in the variables and autocorrelated disturbances. Journal of Econometrics 64 (1994) 145-163
Dagenais M.G., and Dagenais D.L. Higher moment estimators for linear regression models with errors in the variables. Journal of Econometrics 76 (1997) 193-221
Davidson R., and MacKinnon J. Estimation and Inference in Econometrics (1993), Oxford University Press, New York
Davidson R., and MacKinnon J.G. Econometric Theory and Methods (2004), Oxford University Press, New York
Diez de los Rios A., and Garcia R. Assessing and valuing the nonlinear structure of hedge funds' returns. Working Paper (2005), CIRANO
Durbin J. Errors in variables. International Statistical Review 22 (1954) 23-32
Erickson T., and Whited T.M. Measurement error and the relationship between investment and "q". Journal of Political Economy 108 5 (2000) 1027-1057
Erickson T., and Whited T.M. GMM estimation of the errors-in-variables model using high-order moments. Econometric Theory 18 (2002) 776-799
Fama E.F., and French K.R. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33 (1993) 3-56
Fama E.F., and French K.R. Industry costs of equity. Journal of Financial Economics 43 (1997) 153-193
Fama G., and MacBeth J. Risk, return and equilibrium: empirical test. Journal of Political Economy (1973) 607-636
Frisch R.A. Statistical Confluence Analysis by Means of Complete Regression System (1934), University Institute of Economics, Oslo
Fuller W.A. Measurement Error Models (1987), Wiley, New York, NY
Fung W., and Hsieh D.A. The risk in hedge fund strategies: theory and evidence from trend followers. Review of Financial Studies 14 (2001) 313-341
Fung W., and Hsieh D.A. Hedge fund benchmarks: a risk-based approach. Financial Analysts Journal 60 (2004) 65-81
Fung W., Hsieh D.A., Naik N., and Ramadorai T. Hedge funds: performance, risk, and capital formation. Working Paper (2006), London Business School
Glosten L., and Jagannathan R. A contingent claims approach to performance evaluation. Journal of Empirical Finance 1 (1994) 133-160
Hausman J.A. Specification tests in econometrics. Econometrica 46 (1978) 1251-1271
Huang C.F., and Litzenberger R.H. Foundations for Financial Economics (1988), Prentice Hall, Englewood Cliffs
Kandel S., and Stambaugh R. Portfolio inefficiency and the cross-section of expected returns. Journal of Finance 50 (1995) 157-184
Klepper S., and Leamer E.E. Consistent sets of estimates for regressions with errors in all variables. Econometrica 52 (1984) 163-184
Leamer E.E. Errors in variables in linear systems. Econometrica 55 (1987) 893-909
Lewbel A. Using heteroskedasticity to identify and estimate mismeasurement and endogenous regressor models. Working Paper (2006), Boston College January 2006
Pal M. Consistent moment estimators of regression coefficients in the presence of errors in variables. Journal of Econometrics 14 (1980) 349-364
Roll R. A critique of the asset pricing theory's tests: part I: on the past and the potential testability of the theory. Journal of Financial Economics (1977) 129-176
Ross S.A. The arbitrage theory and capital asset pricing. Journal of Economic Theory (1976) 343-362
Samuelson P.A. The fundamental approximation theorem of portfolio analysis in terms of means, variances and higher moments. Review of Economic Studies 37 (1970) 537-542
Shanken W.F. On the estimation of beta-pricing models. Review of Financial Studies 5 (1992) 1-34
Similar publications
Sorry the service is unavailable at the moment. Please try again later.
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.