Titulo:

Portfolio Optimization and Long-Term Dependence
.

Guardado en:

1794-1113

2346-2140

2011-07-01

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http://purl.org/coar/access_right/c_abf2

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spelling Portfolio Optimization and Long-Term Dependence
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 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.
León, Carlos
Reveiz, Alejandro
Portfolio optimization
Hurst exponent
long-term dependence
biased random walk
rescaled range analysis
6
Artículo de revista
Journal article
2011-07-01T00:00:00Z
2011-07-01T00:00:00Z
2011-07-01
application/pdf
Universidad Externado de Colombia
ODEON
1794-1113
2346-2140
https://revistas.uexternado.edu.co/index.php/odeon/article/view/3329
https://revistas.uexternado.edu.co/index.php/odeon/article/view/3329
eng
https://creativecommons.org/licenses/by-nc-sa/4.0/
https://revistas.uexternado.edu.co/index.php/odeon/article/download/3329/2979
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Text
Publication
institution UNIVERSIDAD EXTERNADO DE COLOMBIA
thumbnail https://nuevo.metarevistas.org/UNIVERSIDADEXTERNADODECOLOMBIA/logo.png
country_str Colombia
collection Revista ODEON
title Portfolio Optimization and Long-Term Dependence
spellingShingle Portfolio Optimization and Long-Term Dependence
León, Carlos
Reveiz, Alejandro
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
title_eng Portfolio Optimization and Long-Term Dependence
description_eng 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.
author León, Carlos
Reveiz, Alejandro
author_facet León, Carlos
Reveiz, Alejandro
topic Portfolio optimization
Hurst exponent
long-term dependence
biased random walk
rescaled range analysis
topic_facet Portfolio optimization
Hurst exponent
long-term dependence
biased random walk
rescaled range analysis
citationissue 6
publisher Universidad Externado de Colombia
ispartofjournal ODEON
source https://revistas.uexternado.edu.co/index.php/odeon/article/view/3329
language eng
format Article
rights https://creativecommons.org/licenses/by-nc-sa/4.0/
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type_content Text
publishDate 2011-07-01
date_accessioned 2011-07-01T00:00:00Z
date_available 2011-07-01T00:00:00Z
url https://revistas.uexternado.edu.co/index.php/odeon/article/view/3329
url_doi https://revistas.uexternado.edu.co/index.php/odeon/article/view/3329
issn 1794-1113
eissn 2346-2140
url2_str_mv https://revistas.uexternado.edu.co/index.php/odeon/article/download/3329/2979
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