Quantile regression for index tracking and enhanced indexation
Quantile regression differs from traditional least-squares regression in that one constructs regression lines for the quantiles of the dependent variable in terms of the independent variable. In this paper we apply quantile regression to two problems in financial portfolio construction, index tracking and enhanced indexation. Index tracking is the problem of reproducing the performance of a stock market index, but without purchasing all of the stocks that make up the index. Enhanced indexation deals with the problem of out-performing the index. We present a mixed-integer linear programming formulation of these problems based on quantile regression. Our formulation includes transaction costs, a constraint limiting the number of stocks that can be in the portfolio and a limit on the total transaction cost that can be incurred. Numeric results are presented for eight test problems drawn from major world markets, where the largest of these test problems involves over 2000 stocks.
If you experience problems downloading a file, check if you have the proper application to view it first. 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 64 (2013)
Issue (Month): 11 (November)
|Contact details of provider:|| Web page: http://www.palgrave-journals.com/|
Web page: http://www.theorsociety.com/
|Order Information:||Web: http://www.springer.com/business+%26+management/operations+research/journal/41274|
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.:
- Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, 03.
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Thiemo Krink & Stefan Mittnik & Sandra Paterlini, 2009.
"Differential evolution and combinatorial search for constrained index-tracking,"
Annals of Operations Research,
Springer, vol. 172(1), pages 153-176, November.
- Thiemo Krink & Stefan Mittnik & Sandra Paterlini, 2009. "Differential Evolution and Combinatorial Search for Constrained Index Tracking," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 09032, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
- Beasley, J. E. & Meade, N. & Chang, T. -J., 2003. "An evolutionary heuristic for the index tracking problem," European Journal of Operational Research, Elsevier, vol. 148(3), pages 621-643, August.
- N. Meade & J. E. Beasley, 2011. "Detection of momentum effects using an index out-performance strategy," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 313-326.
- Enrico Angelelli & Renata Mansini & M. Speranza, 2012. "Kernel Search: a new heuristic framework for portfolio selection," Computational Optimization and Applications, Springer, vol. 51(1), pages 345-361, January.
- Canakgoz, N.A. & Beasley, J.E., 2009. "Mixed-integer programming approaches for index tracking and enhanced indexation," European Journal of Operational Research, Elsevier, vol. 196(1), pages 384-399, July.
- Guastaroba, G. & Speranza, M.G., 2012. "Kernel Search: An application to the index tracking problem," European Journal of Operational Research, Elsevier, vol. 217(1), pages 54-68. Full references (including those not matched with items on IDEAS)