Journal article

Publication year: 2011

Pages: 103-123

Journal: Computational Management Science

Volume number: 8

Issue number: 1-2

ISSN: 1619-697X

eISSN: 1619-6988

DOI Link: https://doi.org/10.1007/s10287-009-0103-x

Publisher: Springer

Abstract: 
For estimating the parameters of models for financial market data, the use of robust techniques is of particular interest. Conditional forecasts, based on the capital asset pricing model, and a factor model are considered. It is proposed to consider least median of squares estimators as one possible alternative to ordinary least squares. Given the complexity of the objective function for the leastmedian of squares estimator, the estimates are obtained by means of optimization heuristics. The performance of two heuristics is compared, namely differential evolution and threshold accepting. It is shown that these methods are well suited to obtain least median of squares estimators for real world problems. Furthermore, it is analyzed to what extent parameter estimates and conditional forecasts differ between the two estimators. The empirical analysis considers daily and monthly data on some stocks from the Dow Jones Industrial Average Index.

Harvard Citation style: Winker, P., Lyra, M. and Sharpe, C. (2011) Least median of squares estimation by optimization heuristics with an application to the CAPM and a multi-factor model, Computational Management Science, 8(1-2), pp. 103-123. https://doi.org/10.1007/s10287-009-0103-x

APA Citation style: Winker, P., Lyra, M., & Sharpe, C. (2011). Least median of squares estimation by optimization heuristics with an application to the CAPM and a multi-factor model. Computational Management Science. 8(1-2), 103-123. https://doi.org/10.1007/s10287-009-0103-x