INTEGRATED METAHEURISTIC OPTIMIZATION OF 130-30 INVESTMENT-STRATEGY-BASED LONG-SHORT PORTFOLIOS
SUMMARY A 130–30 strategy is an attractive and viable equity investment strategy for building long–short portfolios and notionally expected to enhance investment exposure and market protection. However, the amalgamation of the strategy in the portfolio optimization problem model poses complex constr...
Gespeichert in:
Veröffentlicht in: | Intelligent systems in accounting, finance & management finance & management, 2012-01, Vol.19 (1), p.43-74 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 74 |
---|---|
container_issue | 1 |
container_start_page | 43 |
container_title | Intelligent systems in accounting, finance & management |
container_volume | 19 |
creator | Vijayalakshmi Pai, G.A. Michel, Thierry |
description | SUMMARY
A 130–30 strategy is an attractive and viable equity investment strategy for building long–short portfolios and notionally expected to enhance investment exposure and market protection. However, the amalgamation of the strategy in the portfolio optimization problem model poses complex constraints which render the problem model difficult for solving using traditional methods, thus justifying the application of metaheuristic solutions.
We discuss a metaheuristic and integrated optimization of long–short portfolios, when the 130–30‐strategy‐based constraint, besides other investor preferential constraints, is incorporated in the problem's formulation. In the absence of reported work and for reasons of performance comparison and analysis, two metaheuristic strategies have been proposed in order to solve the problem: (i) evolution strategy with hall of fame and (ii) differential evolution (rand/1/bin) with hall of fame. The experimental studies were undertaken on the Bombay Stock Exchange (BSE200) and Tokyo Stock Exchange (Nikkei 225) data sets and specifically for the period March 1999–March 2009, which included both upturns and downturns in the global markets. The efficiencies of the portfolios obtained by the two metaheuristic methods were analysed using an efficiency improvement possibility function, a portfolio productivity indicator which is a variation of Luenberger's shortage functions. Copyright © 2012 John Wiley & Sons, Ltd. |
doi_str_mv | 10.1002/isaf.335 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_929379154</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2614850501</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3615-e3a825646f3701ff73ef3c71ac8bdcb70239375485d7870baa3723e34e0e7523</originalsourceid><addsrcrecordid>eNp10F1LwzAUBuAgCs4p-BOKV95kniRN017W2naBfow1OvUmdF0KnR-b7Ybu39sxEbzwJufmec8JL0KXBEYEgN40XVmPGONHaECJAxhA2MdoQDgHTDzbO0VnXbcEAM-jMEBaZiqMp74K76w0VP44vJ_KQsnAyidKpvLZVzLPrDyyCAPMwJLZQ1ioNMwULtQ-Fz_hW7_o40mexbgY51NlTfonyhOZF-fopC5fO3PxM4dIRaEKxjjJYxn4Ca6YQzg2rHQpd2ynZgJIXQtmalYJUlbufFHNBVDmMcFtly-EK2BelkxQZphtwAhO2RBdHdau29XH1nQbvVxt2_f-ovZon_QIt3t0fUBVu-q61tR63TZvZbvTBPS-PL0vT_fl9RQf6Gfzanb_Oi0LP_rjm25jvn592b5oR_Qf17Ms1jQO0hnQQj-ybzZLdn0</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>929379154</pqid></control><display><type>article</type><title>INTEGRATED METAHEURISTIC OPTIMIZATION OF 130-30 INVESTMENT-STRATEGY-BASED LONG-SHORT PORTFOLIOS</title><source>Wiley Online Library Journals Frontfile Complete</source><source>Business Source Complete</source><creator>Vijayalakshmi Pai, G.A. ; Michel, Thierry</creator><creatorcontrib>Vijayalakshmi Pai, G.A. ; Michel, Thierry</creatorcontrib><description>SUMMARY
A 130–30 strategy is an attractive and viable equity investment strategy for building long–short portfolios and notionally expected to enhance investment exposure and market protection. However, the amalgamation of the strategy in the portfolio optimization problem model poses complex constraints which render the problem model difficult for solving using traditional methods, thus justifying the application of metaheuristic solutions.
We discuss a metaheuristic and integrated optimization of long–short portfolios, when the 130–30‐strategy‐based constraint, besides other investor preferential constraints, is incorporated in the problem's formulation. In the absence of reported work and for reasons of performance comparison and analysis, two metaheuristic strategies have been proposed in order to solve the problem: (i) evolution strategy with hall of fame and (ii) differential evolution (rand/1/bin) with hall of fame. The experimental studies were undertaken on the Bombay Stock Exchange (BSE200) and Tokyo Stock Exchange (Nikkei 225) data sets and specifically for the period March 1999–March 2009, which included both upturns and downturns in the global markets. The efficiencies of the portfolios obtained by the two metaheuristic methods were analysed using an efficiency improvement possibility function, a portfolio productivity indicator which is a variation of Luenberger's shortage functions. Copyright © 2012 John Wiley & Sons, Ltd.</description><identifier>ISSN: 1550-1949</identifier><identifier>EISSN: 2160-0074</identifier><identifier>DOI: 10.1002/isaf.335</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>130-30 strategy ; differential evolution ; evolution strategy ; Heuristic ; Investment policy ; Investments ; long-short portfolios ; Luenberger shortage function ; Optimization ; Optimization algorithms ; Portfolio investments ; portfolio optimization ; Stock exchanges ; Studies</subject><ispartof>Intelligent systems in accounting, finance & management, 2012-01, Vol.19 (1), p.43-74</ispartof><rights>Copyright © 2012 John Wiley & Sons, Ltd.</rights><rights>Copyright Wiley Periodicals Inc. Jan-Mar 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3615-e3a825646f3701ff73ef3c71ac8bdcb70239375485d7870baa3723e34e0e7523</citedby><cites>FETCH-LOGICAL-c3615-e3a825646f3701ff73ef3c71ac8bdcb70239375485d7870baa3723e34e0e7523</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fisaf.335$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fisaf.335$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Vijayalakshmi Pai, G.A.</creatorcontrib><creatorcontrib>Michel, Thierry</creatorcontrib><title>INTEGRATED METAHEURISTIC OPTIMIZATION OF 130-30 INVESTMENT-STRATEGY-BASED LONG-SHORT PORTFOLIOS</title><title>Intelligent systems in accounting, finance & management</title><addtitle>Intell. Sys. Acc. Fin. Mgmt</addtitle><description>SUMMARY
A 130–30 strategy is an attractive and viable equity investment strategy for building long–short portfolios and notionally expected to enhance investment exposure and market protection. However, the amalgamation of the strategy in the portfolio optimization problem model poses complex constraints which render the problem model difficult for solving using traditional methods, thus justifying the application of metaheuristic solutions.
We discuss a metaheuristic and integrated optimization of long–short portfolios, when the 130–30‐strategy‐based constraint, besides other investor preferential constraints, is incorporated in the problem's formulation. In the absence of reported work and for reasons of performance comparison and analysis, two metaheuristic strategies have been proposed in order to solve the problem: (i) evolution strategy with hall of fame and (ii) differential evolution (rand/1/bin) with hall of fame. The experimental studies were undertaken on the Bombay Stock Exchange (BSE200) and Tokyo Stock Exchange (Nikkei 225) data sets and specifically for the period March 1999–March 2009, which included both upturns and downturns in the global markets. The efficiencies of the portfolios obtained by the two metaheuristic methods were analysed using an efficiency improvement possibility function, a portfolio productivity indicator which is a variation of Luenberger's shortage functions. Copyright © 2012 John Wiley & Sons, Ltd.</description><subject>130-30 strategy</subject><subject>differential evolution</subject><subject>evolution strategy</subject><subject>Heuristic</subject><subject>Investment policy</subject><subject>Investments</subject><subject>long-short portfolios</subject><subject>Luenberger shortage function</subject><subject>Optimization</subject><subject>Optimization algorithms</subject><subject>Portfolio investments</subject><subject>portfolio optimization</subject><subject>Stock exchanges</subject><subject>Studies</subject><issn>1550-1949</issn><issn>2160-0074</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp10F1LwzAUBuAgCs4p-BOKV95kniRN017W2naBfow1OvUmdF0KnR-b7Ybu39sxEbzwJufmec8JL0KXBEYEgN40XVmPGONHaECJAxhA2MdoQDgHTDzbO0VnXbcEAM-jMEBaZiqMp74K76w0VP44vJ_KQsnAyidKpvLZVzLPrDyyCAPMwJLZQ1ioNMwULtQ-Fz_hW7_o40mexbgY51NlTfonyhOZF-fopC5fO3PxM4dIRaEKxjjJYxn4Ca6YQzg2rHQpd2ynZgJIXQtmalYJUlbufFHNBVDmMcFtly-EK2BelkxQZphtwAhO2RBdHdau29XH1nQbvVxt2_f-ovZon_QIt3t0fUBVu-q61tR63TZvZbvTBPS-PL0vT_fl9RQf6Gfzanb_Oi0LP_rjm25jvn592b5oR_Qf17Ms1jQO0hnQQj-ybzZLdn0</recordid><startdate>201201</startdate><enddate>201201</enddate><creator>Vijayalakshmi Pai, G.A.</creator><creator>Michel, Thierry</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Periodicals Inc</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>JQ2</scope></search><sort><creationdate>201201</creationdate><title>INTEGRATED METAHEURISTIC OPTIMIZATION OF 130-30 INVESTMENT-STRATEGY-BASED LONG-SHORT PORTFOLIOS</title><author>Vijayalakshmi Pai, G.A. ; Michel, Thierry</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3615-e3a825646f3701ff73ef3c71ac8bdcb70239375485d7870baa3723e34e0e7523</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>130-30 strategy</topic><topic>differential evolution</topic><topic>evolution strategy</topic><topic>Heuristic</topic><topic>Investment policy</topic><topic>Investments</topic><topic>long-short portfolios</topic><topic>Luenberger shortage function</topic><topic>Optimization</topic><topic>Optimization algorithms</topic><topic>Portfolio investments</topic><topic>portfolio optimization</topic><topic>Stock exchanges</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vijayalakshmi Pai, G.A.</creatorcontrib><creatorcontrib>Michel, Thierry</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><jtitle>Intelligent systems in accounting, finance & management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vijayalakshmi Pai, G.A.</au><au>Michel, Thierry</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>INTEGRATED METAHEURISTIC OPTIMIZATION OF 130-30 INVESTMENT-STRATEGY-BASED LONG-SHORT PORTFOLIOS</atitle><jtitle>Intelligent systems in accounting, finance & management</jtitle><addtitle>Intell. Sys. Acc. Fin. Mgmt</addtitle><date>2012-01</date><risdate>2012</risdate><volume>19</volume><issue>1</issue><spage>43</spage><epage>74</epage><pages>43-74</pages><issn>1550-1949</issn><eissn>2160-0074</eissn><abstract>SUMMARY
A 130–30 strategy is an attractive and viable equity investment strategy for building long–short portfolios and notionally expected to enhance investment exposure and market protection. However, the amalgamation of the strategy in the portfolio optimization problem model poses complex constraints which render the problem model difficult for solving using traditional methods, thus justifying the application of metaheuristic solutions.
We discuss a metaheuristic and integrated optimization of long–short portfolios, when the 130–30‐strategy‐based constraint, besides other investor preferential constraints, is incorporated in the problem's formulation. In the absence of reported work and for reasons of performance comparison and analysis, two metaheuristic strategies have been proposed in order to solve the problem: (i) evolution strategy with hall of fame and (ii) differential evolution (rand/1/bin) with hall of fame. The experimental studies were undertaken on the Bombay Stock Exchange (BSE200) and Tokyo Stock Exchange (Nikkei 225) data sets and specifically for the period March 1999–March 2009, which included both upturns and downturns in the global markets. The efficiencies of the portfolios obtained by the two metaheuristic methods were analysed using an efficiency improvement possibility function, a portfolio productivity indicator which is a variation of Luenberger's shortage functions. Copyright © 2012 John Wiley & Sons, Ltd.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/isaf.335</doi><tpages>32</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1550-1949 |
ispartof | Intelligent systems in accounting, finance & management, 2012-01, Vol.19 (1), p.43-74 |
issn | 1550-1949 2160-0074 |
language | eng |
recordid | cdi_proquest_journals_929379154 |
source | Wiley Online Library Journals Frontfile Complete; Business Source Complete |
subjects | 130-30 strategy differential evolution evolution strategy Heuristic Investment policy Investments long-short portfolios Luenberger shortage function Optimization Optimization algorithms Portfolio investments portfolio optimization Stock exchanges Studies |
title | INTEGRATED METAHEURISTIC OPTIMIZATION OF 130-30 INVESTMENT-STRATEGY-BASED LONG-SHORT PORTFOLIOS |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T13%3A29%3A57IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=INTEGRATED%20METAHEURISTIC%20OPTIMIZATION%20OF%20130-30%20INVESTMENT-STRATEGY-BASED%20LONG-SHORT%20PORTFOLIOS&rft.jtitle=Intelligent%20systems%20in%20accounting,%20finance%20&%20management&rft.au=Vijayalakshmi%20Pai,%20G.A.&rft.date=2012-01&rft.volume=19&rft.issue=1&rft.spage=43&rft.epage=74&rft.pages=43-74&rft.issn=1550-1949&rft.eissn=2160-0074&rft_id=info:doi/10.1002/isaf.335&rft_dat=%3Cproquest_cross%3E2614850501%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=929379154&rft_id=info:pmid/&rfr_iscdi=true |