Taylor series approximations to expected utility and optimal portfolio choice
This paper revisits the subject of Taylor series approximations to expected utility and investigates the applicability of the technique to optimal portfolio choice problems. We first provide conditions under which the approximate expected utility of a given portfolio converges to its exact counterpa...
Gespeichert in:
Veröffentlicht in: | Mathematics and financial economics 2011-09, Vol.5 (2), p.121-156 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 156 |
---|---|
container_issue | 2 |
container_start_page | 121 |
container_title | Mathematics and financial economics |
container_volume | 5 |
creator | Garlappi, Lorenzo Skoulakis, Georgios |
description | This paper revisits the subject of Taylor series approximations to expected utility and investigates the applicability of the technique to optimal portfolio choice problems. We first provide conditions under which the approximate expected utility of a given portfolio converges to its exact counterpart. We then extend the analysis to the optimal portfolio choice setting and provide conditions on the distribution of asset returns under which the solution to the approximate portfolio choice problem converges to its exact counterpart. Finally, we show that, when asset returns are skewed, one can improve the precision and efficiency of the Taylor expansion by applying a simple nonlinear transformation to asset returns designed to symmetrize the transformed return distribution and shrink its support. |
doi_str_mv | 10.1007/s11579-011-0051-4 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_894722893</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2471115771</sourcerecordid><originalsourceid>FETCH-LOGICAL-c315t-610f97d51ab1dd81e2621f8514ec56893ec119ce9870787a9c6b3a8b0d579daa3</originalsourceid><addsrcrecordid>eNp1kMtOwzAQRS0EElXpB7Cz2Ac8TuLHElU8KhWxKWvLtR1wFeJgu1L797gKghWzmVmce2fmInQN5BYI4XcJoOWyIgAVIS1UzRmagWC0koyR89-Zy0u0SGlHStWUi4bM0MtGH_sQcXLRu4T1OMZw8J86-zAknAN2h9GZ7CzeZ9_7fMR6sDiMuTA9HkPMXeh9wOYjeOOu0EWn--QWP32O3h4fNsvnav36tFrerytTQ5srBqST3Lagt2CtAEcZhU600DjTMiFrZwCkcVJwwgXX0rBtrcWW2PKm1bqeo5vJt1z7tXcpq13Yx6GsVEI2nNLiUSCYIBNDStF1aozl6nhUQNQpNzXlpkpu6pSbaoqGTppU2OHdxT_j_0Xf5tBwfw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>894722893</pqid></control><display><type>article</type><title>Taylor series approximations to expected utility and optimal portfolio choice</title><source>Springer Journals</source><creator>Garlappi, Lorenzo ; Skoulakis, Georgios</creator><creatorcontrib>Garlappi, Lorenzo ; Skoulakis, Georgios</creatorcontrib><description>This paper revisits the subject of Taylor series approximations to expected utility and investigates the applicability of the technique to optimal portfolio choice problems. We first provide conditions under which the approximate expected utility of a given portfolio converges to its exact counterpart. We then extend the analysis to the optimal portfolio choice setting and provide conditions on the distribution of asset returns under which the solution to the approximate portfolio choice problem converges to its exact counterpart. Finally, we show that, when asset returns are skewed, one can improve the precision and efficiency of the Taylor expansion by applying a simple nonlinear transformation to asset returns designed to symmetrize the transformed return distribution and shrink its support.</description><identifier>ISSN: 1862-9679</identifier><identifier>EISSN: 1862-9660</identifier><identifier>DOI: 10.1007/s11579-011-0051-4</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Applications of Mathematics ; Approximation ; Economic models ; Economic theory ; Economic Theory/Quantitative Economics/Mathematical Methods ; Economics ; Expected utility ; Finance ; Insurance ; Integrals ; Macroeconomics/Monetary Economics//Financial Economics ; Management ; Mathematics ; Mathematics and Statistics ; Monte Carlo simulation ; Quantitative Finance ; Return on assets ; Statistics for Business ; Studies ; Utility functions</subject><ispartof>Mathematics and financial economics, 2011-09, Vol.5 (2), p.121-156</ispartof><rights>Springer-Verlag 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c315t-610f97d51ab1dd81e2621f8514ec56893ec119ce9870787a9c6b3a8b0d579daa3</citedby><cites>FETCH-LOGICAL-c315t-610f97d51ab1dd81e2621f8514ec56893ec119ce9870787a9c6b3a8b0d579daa3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11579-011-0051-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11579-011-0051-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Garlappi, Lorenzo</creatorcontrib><creatorcontrib>Skoulakis, Georgios</creatorcontrib><title>Taylor series approximations to expected utility and optimal portfolio choice</title><title>Mathematics and financial economics</title><addtitle>Math Finan Econ</addtitle><description>This paper revisits the subject of Taylor series approximations to expected utility and investigates the applicability of the technique to optimal portfolio choice problems. We first provide conditions under which the approximate expected utility of a given portfolio converges to its exact counterpart. We then extend the analysis to the optimal portfolio choice setting and provide conditions on the distribution of asset returns under which the solution to the approximate portfolio choice problem converges to its exact counterpart. Finally, we show that, when asset returns are skewed, one can improve the precision and efficiency of the Taylor expansion by applying a simple nonlinear transformation to asset returns designed to symmetrize the transformed return distribution and shrink its support.</description><subject>Applications of Mathematics</subject><subject>Approximation</subject><subject>Economic models</subject><subject>Economic theory</subject><subject>Economic Theory/Quantitative Economics/Mathematical Methods</subject><subject>Economics</subject><subject>Expected utility</subject><subject>Finance</subject><subject>Insurance</subject><subject>Integrals</subject><subject>Macroeconomics/Monetary Economics//Financial Economics</subject><subject>Management</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Monte Carlo simulation</subject><subject>Quantitative Finance</subject><subject>Return on assets</subject><subject>Statistics for Business</subject><subject>Studies</subject><subject>Utility functions</subject><issn>1862-9679</issn><issn>1862-9660</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp1kMtOwzAQRS0EElXpB7Cz2Ac8TuLHElU8KhWxKWvLtR1wFeJgu1L797gKghWzmVmce2fmInQN5BYI4XcJoOWyIgAVIS1UzRmagWC0koyR89-Zy0u0SGlHStWUi4bM0MtGH_sQcXLRu4T1OMZw8J86-zAknAN2h9GZ7CzeZ9_7fMR6sDiMuTA9HkPMXeh9wOYjeOOu0EWn--QWP32O3h4fNsvnav36tFrerytTQ5srBqST3Lagt2CtAEcZhU600DjTMiFrZwCkcVJwwgXX0rBtrcWW2PKm1bqeo5vJt1z7tXcpq13Yx6GsVEI2nNLiUSCYIBNDStF1aozl6nhUQNQpNzXlpkpu6pSbaoqGTppU2OHdxT_j_0Xf5tBwfw</recordid><startdate>20110901</startdate><enddate>20110901</enddate><creator>Garlappi, Lorenzo</creator><creator>Skoulakis, Georgios</creator><general>Springer-Verlag</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8BJ</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FRNLG</scope><scope>F~G</scope><scope>HCIFZ</scope><scope>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L.0</scope><scope>L6V</scope><scope>M0C</scope><scope>M7S</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYYUZ</scope><scope>Q9U</scope></search><sort><creationdate>20110901</creationdate><title>Taylor series approximations to expected utility and optimal portfolio choice</title><author>Garlappi, Lorenzo ; Skoulakis, Georgios</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c315t-610f97d51ab1dd81e2621f8514ec56893ec119ce9870787a9c6b3a8b0d579daa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Applications of Mathematics</topic><topic>Approximation</topic><topic>Economic models</topic><topic>Economic theory</topic><topic>Economic Theory/Quantitative Economics/Mathematical Methods</topic><topic>Economics</topic><topic>Expected utility</topic><topic>Finance</topic><topic>Insurance</topic><topic>Integrals</topic><topic>Macroeconomics/Monetary Economics//Financial Economics</topic><topic>Management</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Monte Carlo simulation</topic><topic>Quantitative Finance</topic><topic>Return on assets</topic><topic>Statistics for Business</topic><topic>Studies</topic><topic>Utility functions</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Garlappi, Lorenzo</creatorcontrib><creatorcontrib>Skoulakis, Georgios</creatorcontrib><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central</collection><collection>ProQuest Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>International Bibliography of the Social Sciences</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>SciTech Premium Collection</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM global</collection><collection>Engineering Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>ABI/INFORM Collection China</collection><collection>ProQuest Central Basic</collection><jtitle>Mathematics and financial economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Garlappi, Lorenzo</au><au>Skoulakis, Georgios</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Taylor series approximations to expected utility and optimal portfolio choice</atitle><jtitle>Mathematics and financial economics</jtitle><stitle>Math Finan Econ</stitle><date>2011-09-01</date><risdate>2011</risdate><volume>5</volume><issue>2</issue><spage>121</spage><epage>156</epage><pages>121-156</pages><issn>1862-9679</issn><eissn>1862-9660</eissn><abstract>This paper revisits the subject of Taylor series approximations to expected utility and investigates the applicability of the technique to optimal portfolio choice problems. We first provide conditions under which the approximate expected utility of a given portfolio converges to its exact counterpart. We then extend the analysis to the optimal portfolio choice setting and provide conditions on the distribution of asset returns under which the solution to the approximate portfolio choice problem converges to its exact counterpart. Finally, we show that, when asset returns are skewed, one can improve the precision and efficiency of the Taylor expansion by applying a simple nonlinear transformation to asset returns designed to symmetrize the transformed return distribution and shrink its support.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.1007/s11579-011-0051-4</doi><tpages>36</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1862-9679 |
ispartof | Mathematics and financial economics, 2011-09, Vol.5 (2), p.121-156 |
issn | 1862-9679 1862-9660 |
language | eng |
recordid | cdi_proquest_journals_894722893 |
source | Springer Journals |
subjects | Applications of Mathematics Approximation Economic models Economic theory Economic Theory/Quantitative Economics/Mathematical Methods Economics Expected utility Finance Insurance Integrals Macroeconomics/Monetary Economics//Financial Economics Management Mathematics Mathematics and Statistics Monte Carlo simulation Quantitative Finance Return on assets Statistics for Business Studies Utility functions |
title | Taylor series approximations to expected utility and optimal portfolio choice |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T07%3A40%3A35IST&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=Taylor%20series%20approximations%20to%20expected%20utility%20and%20optimal%20portfolio%20choice&rft.jtitle=Mathematics%20and%20financial%20economics&rft.au=Garlappi,%20Lorenzo&rft.date=2011-09-01&rft.volume=5&rft.issue=2&rft.spage=121&rft.epage=156&rft.pages=121-156&rft.issn=1862-9679&rft.eissn=1862-9660&rft_id=info:doi/10.1007/s11579-011-0051-4&rft_dat=%3Cproquest_cross%3E2471115771%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=894722893&rft_id=info:pmid/&rfr_iscdi=true |