A methodology for index tracking based on time-series clustering

DOI10.1080/14697680400008668zbMath1405.91552OpenAlexW1967389254MaRDI QIDQ4610248

Frank J. Fabozzi, Sergio M. Focardi

Publication date: 15 January 2019

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697680400008668

zbMATH Keywords

index trackingtime-series clusteringoptimal tracking portfolio

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Portfolio theory (91G10)

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Cites Work

• Unnamed Item
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• An evolutionary heuristic for the index tracking problem.
• RANDOM MATRIX THEORY AND FINANCIAL CORRELATIONS
• Optimal tracking for asset allocation with fixed and proportional transaction costs
• Optimal hedging using cointegration