Minimizing the tracking error of cardinality constrained portfolios. (February 2018)
- Record Type:
- Journal Article
- Title:
- Minimizing the tracking error of cardinality constrained portfolios. (February 2018)
- Main Title:
- Minimizing the tracking error of cardinality constrained portfolios
- Authors:
- Mutunge, Purity
Haugland, Dag - Abstract:
- Highlights: Proves NP-hardness of an index tracking problem without bounds on asset weights. Convex hull formulation with quadratic objective function. Running time analysis of greedy construction and local improvement methods. Computational experiments proving superiority over a general purpose B&B-solver. Abstract: We study the problem of selecting a restricted number of shares included in a stock market index, such that the portfolio resembles the index as closely as possible. To measure the difference between the portfolio and the index, referred to as the tracking error, we use a quadratic function with the covariance matrix of the index returns as coefficient matrix. The problem is proved to be strongly NP-hard, and we give theoretical evidence that continuous relaxations of mixed integer quadratic programming (MIQP) formulations are likely to produce poor lower bounds on the tracking error. For fast computation of near-optimal portfolios, we demonstrate how the best-extension-by-one construction heuristic can be designed to run in time bounded by a fourth order polynomial. We also show that the running time of one iteration of the best-exchange-by one improvement heuristic is of the same order. Computational experiments applied to real-life stock market indices show that in instances where an index of less than 500 assets is to be tracked by a portfolio of 10 assets, a commercially available MIQP solver fails to reduce the integrality gap below 94% in 30 CPU-minutes.Highlights: Proves NP-hardness of an index tracking problem without bounds on asset weights. Convex hull formulation with quadratic objective function. Running time analysis of greedy construction and local improvement methods. Computational experiments proving superiority over a general purpose B&B-solver. Abstract: We study the problem of selecting a restricted number of shares included in a stock market index, such that the portfolio resembles the index as closely as possible. To measure the difference between the portfolio and the index, referred to as the tracking error, we use a quadratic function with the covariance matrix of the index returns as coefficient matrix. The problem is proved to be strongly NP-hard, and we give theoretical evidence that continuous relaxations of mixed integer quadratic programming (MIQP) formulations are likely to produce poor lower bounds on the tracking error. For fast computation of near-optimal portfolios, we demonstrate how the best-extension-by-one construction heuristic can be designed to run in time bounded by a fourth order polynomial. We also show that the running time of one iteration of the best-exchange-by one improvement heuristic is of the same order. Computational experiments applied to real-life stock market indices show that in instances where an index of less than 500 assets is to be tracked by a portfolio of 10 assets, a commercially available MIQP solver fails to reduce the integrality gap below 94% in 30 CPU-minutes. In contrast, the construction heuristic under study needs less than 30 CPU-seconds to produce a portfolio of 100 assets tracking an index of nearly 2000 assets. … (more)
- Is Part Of:
- Computers & operations research. Volume 90(2018)
- Journal:
- Computers & operations research
- Issue:
- Volume 90(2018)
- Issue Display:
- Volume 90, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 90
- Issue:
- 2018
- Issue Sort Value:
- 2018-0090-2018-0000
- Page Start:
- 33
- Page End:
- 41
- Publication Date:
- 2018-02
- Subjects:
- Portfolio management -- Index tracking -- Integer quadratic programming -- Heuristics
Operations research -- Periodicals
Electronic digital computers -- Periodicals
004.05 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03050548 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cor.2017.09.002 ↗
- Languages:
- English
- ISSNs:
- 0305-0548
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.770000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5060.xml