Robust Estimation and Forecasting of the Capital Asset Pricing Model
Guorui Bian,
Michael McAleer and
Wing-Keung Wong
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Guorui Bian: East China Normal University
No 13-036/III, Tinbergen Institute Discussion Papers from Tinbergen Institute
Abstract:
See the article in the Annals of Financial Economics (2013). Volume 8, issue 2, pages 1-18.
In this paper, we develop a modified maximum likelihood (MML) estimator for the multiple linear regression model with underlying student t distribution. We obtain the closed form of the estimators, derive the asymptotic properties, and demonstrate that the MML estimator is more appropriate for estimating the parameters of the Capital Asset Pricing Model by comparing its performance with least squares estimators (LSE) on the monthly returns of US portfolios. The empirical results reveal that the MML estimators are more efficient than LSE in terms of the relative efficiency of one-step-ahead forecast mean square error in small samples
Keywords: Maximum likelihood estimators; Modified maximum likelihood estimators; Student t family; Capital asset pricing model; Robustness (search for similar items in EconPapers)
JEL-codes: C1 C2 G1 (search for similar items in EconPapers)
Date: 2013-03-04
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)
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https://papers.tinbergen.nl/13036.pdf (application/pdf)
Related works:
Journal Article: ROBUST ESTIMATION AND FORECASTING OF THE CAPITAL ASSET PRICING MODEL (2013) 
Working Paper: Robust Estimation and Forecasting of the Capital Asset Pricing Model (2012) 
Working Paper: Robust Estimation and Forecasting of the Capital Asset Pricing Model (2010) 
Working Paper: Robust Estimation and Forecasting of the Capital Asset Pricing Model (2010) 
Working Paper: Robust Estimation and Forecasting of the Capital Asset Pricing Model (2010) 
Working Paper: Robust Estimation and Forecasting of the Capital Asset Pricing Model (2010) 
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20130036
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