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 tracki...

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Bibliographic Details
Published in:The Journal of the Operational Research Society 2013-11, Vol.64 (11), p.1676-1692
Main Authors: Mezali, H, Beasley, J E
Format: Article
Language:English
Subjects:
Benchmarks
Business and Management
Costs
enhanced indexation
Evolution
Fall lines
Financial portfolios
General Paper
General Papers
Genetic algorithms
index tracking
Investment policy
Linear equations
Linear programming
Literature reviews
Management
Operations research
Operations Research/Decision Theory
Optimal solutions
Periodical indexing
portfolio optimisation
Quantile regression
Regression analysis
Stock exchanges
Stock market indices
Studies
Transaction costs
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Summary: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.
ISSN:0160-5682
1476-9360
DOI:10.1057/jors.2012.186