{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T02:20:34Z","timestamp":1790734834371,"version":"4.1.0"},"reference-count":78,"publisher":"Emerald","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,6,7]]},"abstract":"<jats:p>Index tracking is a very popular passive investment strategy. Since an index cannot be traded directly, index tracking refers to the process of creating a portfolio that approximates its performance. A straightforward way to do that is to purchase all the assets that compose an index in appropriate quantities. However, to simplify the execution, avoid small and illiquid positions, and large transaction costs, it is desired that the tracking portfolio consists of a small number of assets, i.e., we wish to create a sparse portfolio.<\/jats:p>\n                  <jats:p>Although index tracking is driven from the financial industry, it is in fact a pure signal processing problem: a regression of the financial historical data subject to some portfolio constraints with some caveats and particularities. Furthermore, the sparse index tracking problem is similar to many sparsity formulations in the signal processing area in the sense that it is a regression problem with some sparsity requirements. In its original form, sparse index tracking can be formulated as a combinatorial optimization problem. A commonly used approach is to use mixed-integer programming (MIP) to solve small sized problems. Nevertheless, MIP solvers are not applicable for high-dimensional problems since the running time can be prohibiting for practical use.<\/jats:p>\n                  <jats:p>The goal of this monograph is to provide an in-depth overview of the index tracking problem and analyze all the caveats and practical issues an investor might have, such as the frequent rebalancing of weights, the changes in the index composition, the transaction costs, etc. Furthermore, a unified framework for a large variety of sparse index tracking formulations is provided. The derived algorithms are very attractive for practical use since they provide efficient tracking portfolios orders of magnitude faster than MIP solvers.<\/jats:p>","DOI":"10.1561\/2400000021","type":"journal-article","created":{"date-parts":[[2018,6,7]],"date-time":"2018-06-07T08:14:06Z","timestamp":1528359246000},"page":"171-279","source":"Crossref","is-referenced-by-count":44,"title":["Optimization Methods for Financial Index Tracking: From Theory to Practice"],"prefix":"10.1108","volume":"3","author":[{"given":"Konstantinos","family":"Benidis","sequence":"first","affiliation":[{"name":"The Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiyong","family":"Feng","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel P.","family":"Palomar","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2018,6,7]]},"reference":[{"issue":"1758","key":"2026033014421783900_ref001","doi-asserted-by":"crossref","first-page":"2039","DOI":"10.1098\/rsta.1999.0416","article-title":"Optimal hedging using cointegration","volume":"357","author":"Alexander","year":"1999","journal-title":"Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences"},{"issue":"2","key":"2026033014421783900_ref002","first-page":"46","article-title":"Effectiveness of minimum-variance hedging","volume":"33","author":"Alexander","year":"2007","journal-title":"Journal of Portfolio Management"},{"issue":"2","key":"2026033014421783900_ref003","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.jbankfin.2007.03.012","article-title":"Hedging index exchange traded funds","volume":"32","author":"Alexander","year":"2008","journal-title":"Journal of Banking & Finance"},{"issue":"4","key":"2026033014421783900_ref004","first-page":"16","article-title":"Return predictability and dynamic asset allocation: How often should investors rebalance?","volume":"40","author":"Almadi","year":"2014","journal-title":"Journal of Portfolio Management"},{"key":"2026033014421783900_ref005","article-title":"Understanding the profitability of pairs trading","volume-title":"Unpublished working paper, UC Berkeley, Northwestern University","author":"Andrade","year":"2005"},{"issue":"June","key":"2026033014421783900_ref006","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.tre.2012.11.006","article-title":"Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms","volume":"52","author":"Andriosopoulos","year":"2013","journal-title":"Transportation Research Part E: Logistics and Transportation Review"},{"issue":"2","key":"2026033014421783900_ref007","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.jempfin.2003.11.003","article-title":"Index futures and positive feedback trading: Evidence from major stock exchanges","volume":"12","author":"Antoniou","year":"2005","journal-title":"Journal of Empirical Finance"},{"issue":"3","key":"2026033014421783900_ref008","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1111\/1467-9965.00068","article-title":"Coherent measures of risk","volume":"9","author":"Artzner","year":"1999","journal-title":"Mathematical Finance"},{"issue":"2","key":"2026033014421783900_ref009","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1111\/0022-1082.00226","article-title":"Trading is hazardous to your wealth: The common stock investment performance of individual investors","volume":"55","author":"Barber","year":"2000","journal-title":"The Journal of Finance"},{"issue":"3","key":"2026033014421783900_ref010","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/S0377-2217(02)00425-3","article-title":"An evolutionary heuristic for the index tracking problem","volume":"148","author":"Beasley","year":"2003","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"2026033014421783900_ref011","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1109\/TSP.2017.2762286","article-title":"Sparse portfolios for high-dimensional financial index tracking","volume":"66","author":"Benidis","year":"2018","journal-title":"IEEE Transactions on Signal Processing"},{"key":"2026033014421783900_ref012","unstructured":"K.\n              Benidis\n             and D. 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