Portfolio Optimization and Long-Term Dependence

Whilst emphasis has been given to short-term dependence of financial returns, long-term dependence remains overlooked. Despite the fact than financial literature provides evidence of long-term memory existence, serial-independence assumption prevails. This document’s long-term dependence assessment...

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Autores:
León, Carlos
Reveiz, Alejandro
Tipo de recurso:
Article of journal
Fecha de publicación:
2011
Institución:
Universidad Externado de Colombia
Repositorio:
Biblioteca Digital Universidad Externado de Colombia
Idioma:
eng
OAI Identifier:
oai:bdigital.uexternado.edu.co:001/7401
Acceso en línea:
https://bdigital.uexternado.edu.co/handle/001/7401
https://revistas.uexternado.edu.co/index.php/odeon/article/view/3329
Palabra clave:
Portfolio optimization
Hurst exponent
long-term dependence
biased random walk
rescaled range analysis
Rights
openAccess
License
http://purl.org/coar/access_right/c_abf2
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spelling León, Carlos84bd0915-22e1-46d4-8863-e582b6122c44Reveiz, Alejandro6af13554-3aeb-4e67-b804-ff748e6090752011-07-01 00:00:002022-09-08T13:38:13Z2011-07-01 00:00:002022-09-08T13:38:13Z2011-07-01Whilst emphasis has been given to short-term dependence of financial returns, long-term dependence remains overlooked. Despite the fact than financial literature provides evidence of long-term memory existence, serial-independence assumption prevails. This document’s long-term dependence assessment relies on rescaled range analysis (R/S), a popular and robust methodology designed for Geophysics but extensively used in financial literature. Results correspond to most of the previous evidence of significant long-term dependence, particularly for small and illiquid markets, where persistence is its most common kind. Persistence conveys that the range of possible future values of the variable will be wider than the range of purely random and independent variables. Ahead of R/S financial literature, authors estimate an adjusted Hurst exponent in order to properly estimate the covariance matrix at higher investment horizons, avoiding the traditional independence-reliant square-root-of-time rule. Ignoring long-term dependence within the mean-variance portfolio optimization results in concealed risk taking; conversely, by adjusting for long-term dependence the weight of high (low) persistence risk factors decreases (increases) as the investment horizon widens. This alleviates some well-known shortcomings of conventional portfolio optimization for long-term investors (e.g. central banks, pension funds and sovereign wealth managers), such as excessive risk taking in long-term portfolios, extreme weights, home bias, and reluctance to hold foreign currency-denominated assets.application/pdf2346-21401794-1113https://bdigital.uexternado.edu.co/handle/001/7401https://revistas.uexternado.edu.co/index.php/odeon/article/view/3329engFacultad de Finanzas, Gobierno y Relaciones Internacionaleshttps://revistas.uexternado.edu.co/index.php/odeon/article/download/3329/2979Núm. 6 , Año 20116Odeoninfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by-nc-sa/4.0/https://revistas.uexternado.edu.co/index.php/odeon/article/view/3329Portfolio optimizationHurst exponentlong-term dependencebiased random walkrescaled range analysisPortfolio Optimization and Long-Term DependencePortfolio Optimization and Long-Term DependenceArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Textinfo:eu-repo/semantics/articleJournal articlehttp://purl.org/redcol/resource_type/ARTREFinfo:eu-repo/semantics/publishedVersionPublicationOREORE.xmltext/xml2549https://bdigital.uexternado.edu.co/bitstreams/589eca99-f6da-4875-b0b6-6dae78b13b4e/download8c22d64a0824818e921627d6871717fbMD51001/7401oai:bdigital.uexternado.edu.co:001/74012023-08-14 15:29:26.307https://creativecommons.org/licenses/by-nc-sa/4.0/https://bdigital.uexternado.edu.coUniversidad Externado de Colombiametabiblioteca@metabiblioteca.org
dc.title.spa.fl_str_mv Portfolio Optimization and Long-Term Dependence
dc.title.translated.eng.fl_str_mv Portfolio Optimization and Long-Term Dependence
title Portfolio Optimization and Long-Term Dependence
spellingShingle Portfolio Optimization and Long-Term Dependence
Portfolio optimization
Hurst exponent
long-term dependence
biased random walk
rescaled range analysis
title_short Portfolio Optimization and Long-Term Dependence
title_full Portfolio Optimization and Long-Term Dependence
title_fullStr Portfolio Optimization and Long-Term Dependence
title_full_unstemmed Portfolio Optimization and Long-Term Dependence
title_sort Portfolio Optimization and Long-Term Dependence
dc.creator.fl_str_mv León, Carlos
Reveiz, Alejandro
dc.contributor.author.spa.fl_str_mv León, Carlos
Reveiz, Alejandro
dc.subject.eng.fl_str_mv Portfolio optimization
Hurst exponent
long-term dependence
biased random walk
rescaled range analysis
topic Portfolio optimization
Hurst exponent
long-term dependence
biased random walk
rescaled range analysis
description Whilst emphasis has been given to short-term dependence of financial returns, long-term dependence remains overlooked. Despite the fact than financial literature provides evidence of long-term memory existence, serial-independence assumption prevails. This document’s long-term dependence assessment relies on rescaled range analysis (R/S), a popular and robust methodology designed for Geophysics but extensively used in financial literature. Results correspond to most of the previous evidence of significant long-term dependence, particularly for small and illiquid markets, where persistence is its most common kind. Persistence conveys that the range of possible future values of the variable will be wider than the range of purely random and independent variables. Ahead of R/S financial literature, authors estimate an adjusted Hurst exponent in order to properly estimate the covariance matrix at higher investment horizons, avoiding the traditional independence-reliant square-root-of-time rule. Ignoring long-term dependence within the mean-variance portfolio optimization results in concealed risk taking; conversely, by adjusting for long-term dependence the weight of high (low) persistence risk factors decreases (increases) as the investment horizon widens. This alleviates some well-known shortcomings of conventional portfolio optimization for long-term investors (e.g. central banks, pension funds and sovereign wealth managers), such as excessive risk taking in long-term portfolios, extreme weights, home bias, and reluctance to hold foreign currency-denominated assets.
publishDate 2011
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2022-09-08T13:38:13Z
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dc.relation.citationedition.spa.fl_str_mv Núm. 6 , Año 2011
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dc.relation.ispartofjournal.spa.fl_str_mv Odeon
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institution Universidad Externado de Colombia
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