Three fuzzy goal programming models for index portfolios

Studies show that most actively managed mutual funds struggle to beat the market, driving an increase in the popularity of index investing. Index investing instruments, including index funds and Exchange-traded Funds, aim to track market performance. This study pursues both tracking error minimizati...

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Veröffentlicht in:The Journal of the Operational Research Society Jg. 65; H. 8; S. 1155 - 1169
Hauptverfasser: Wu, Liang-chuan, Tsai, I-chan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Taylor & Francis 01.08.2014
Palgrave Macmillan
Palgrave Macmillan UK
Taylor & Francis Ltd
Schlagworte:
Benchmarks
Business and Management
Costs
ETF
Exchange traded funds
Financial portfolios
fuzzy goal programming
Fuzzy sets
General Paper
General Papers
Genetic algorithms
Goal programming
Heuristic
index fund
Index funds
Integer programming
Investments
Investors
Management
Mathematical programming
Membership functions
Mutual funds
Operations research
Operations Research/Decision Theory
Optimization
Portfolio management
Programming models
Securities markets
Set theory
Stock exchanges
Stock market indices
Studies
tracking error
Volatility
fuzzy goal programming
tracking error
index fund
ETF
ISSN:0160-5682, 1476-9360
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Beschreibung
Zusammenfassung:Studies show that most actively managed mutual funds struggle to beat the market, driving an increase in the popularity of index investing. Index investing instruments, including index funds and Exchange-traded Funds, aim to track market performance. This study pursues both tracking error minimization and excess return maximization, two conflicting objectives, to construct an index portfolio. In the real-world financial environment, the desires and expectations of decision makers are generally imprecise. This study applies fuzzy theory to deal with imprecise objectives. This study represents minimizing tracking error and maximizing excess return as 'fuzzy goals' to improve traditional goal programming, which is suitable for handling multiple conflicting objectives, but subject to establishing crisp goals. Three fuzzy goal programming (FGP) models that track indexes are compared and discussed, and the results show that through certain membership functions and tracking models, an index tracking portfolio with a tracking error lower than the 0050 index fund, and a similar excess return to 0050 index fund can be constructed using additive type FGP. max-min type FGP underperforms the additive type FGP in index fund construction.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0160-5682
1476-9360
DOI:10.1057/jors.2013.47