The G-Martingale Approach for G-Utility Maximization

In this paper, we study representative investor's G-utility maximization problem by G-martingale approach in the framework of G-expectation space proposed by Peng \cite{Pe19}. Financial market has only a bond and a stock with uncertainty characterized by G-Brownian motions. The routine idea of...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:arXiv.org 2022-06
Hauptverfasser: Chen, Qiguan, Song, Yulin, Wang, Zengwu, Yuan, Zengting
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Chen, Qiguan
Song, Yulin
Wang, Zengwu
Yuan, Zengting
description In this paper, we study representative investor's G-utility maximization problem by G-martingale approach in the framework of G-expectation space proposed by Peng \cite{Pe19}. Financial market has only a bond and a stock with uncertainty characterized by G-Brownian motions. The routine idea of \cite{Wxz} fails because that the quadratic variation process of a G-Brownian motion is also a stochastic process. To overcome this difficulty, an extended nonlinear expectation should be pulled in. A sufficient condition of G-utility maximization is presented firstly. In the case of log-utility, an explicit solution of optimal strategy can be obtained by constructing and solving a couple of G-FBSDEs, then verifying the optimal strategy to meet the sufficient condition. As an application, an explicit solution of a stochastic interest model is obtained by the same approach. All economic meanings of optimal strategies are consistent with our intuitions.
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2676394337</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2676394337</sourcerecordid><originalsourceid>FETCH-proquest_journals_26763943373</originalsourceid><addsrcrecordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mQwCclIVXDX9U0sKsnMS0_MSVVwLCgoyk9MzlBIyy8CyoSWZOZkllQq-CZWZOZmViWWZObn8TCwpiXmFKfyQmluBmU31xBnD12gzsLS1OKS-Kz80qI8oFQ80CIzY0sTY2NzY-JUAQANPzQt</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2676394337</pqid></control><display><type>article</type><title>The G-Martingale Approach for G-Utility Maximization</title><source>Free E- Journals</source><creator>Chen, Qiguan ; Song, Yulin ; Wang, Zengwu ; Yuan, Zengting</creator><creatorcontrib>Chen, Qiguan ; Song, Yulin ; Wang, Zengwu ; Yuan, Zengting</creatorcontrib><description>In this paper, we study representative investor's G-utility maximization problem by G-martingale approach in the framework of G-expectation space proposed by Peng \cite{Pe19}. Financial market has only a bond and a stock with uncertainty characterized by G-Brownian motions. The routine idea of \cite{Wxz} fails because that the quadratic variation process of a G-Brownian motion is also a stochastic process. To overcome this difficulty, an extended nonlinear expectation should be pulled in. A sufficient condition of G-utility maximization is presented firstly. In the case of log-utility, an explicit solution of optimal strategy can be obtained by constructing and solving a couple of G-FBSDEs, then verifying the optimal strategy to meet the sufficient condition. As an application, an explicit solution of a stochastic interest model is obtained by the same approach. All economic meanings of optimal strategies are consistent with our intuitions.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Brownian motion ; Economic models ; Martingales ; Maximization ; Optimization ; Stochastic processes</subject><ispartof>arXiv.org, 2022-06</ispartof><rights>2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>780,784</link.rule.ids></links><search><creatorcontrib>Chen, Qiguan</creatorcontrib><creatorcontrib>Song, Yulin</creatorcontrib><creatorcontrib>Wang, Zengwu</creatorcontrib><creatorcontrib>Yuan, Zengting</creatorcontrib><title>The G-Martingale Approach for G-Utility Maximization</title><title>arXiv.org</title><description>In this paper, we study representative investor's G-utility maximization problem by G-martingale approach in the framework of G-expectation space proposed by Peng \cite{Pe19}. Financial market has only a bond and a stock with uncertainty characterized by G-Brownian motions. The routine idea of \cite{Wxz} fails because that the quadratic variation process of a G-Brownian motion is also a stochastic process. To overcome this difficulty, an extended nonlinear expectation should be pulled in. A sufficient condition of G-utility maximization is presented firstly. In the case of log-utility, an explicit solution of optimal strategy can be obtained by constructing and solving a couple of G-FBSDEs, then verifying the optimal strategy to meet the sufficient condition. As an application, an explicit solution of a stochastic interest model is obtained by the same approach. All economic meanings of optimal strategies are consistent with our intuitions.</description><subject>Brownian motion</subject><subject>Economic models</subject><subject>Martingales</subject><subject>Maximization</subject><subject>Optimization</subject><subject>Stochastic processes</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mQwCclIVXDX9U0sKsnMS0_MSVVwLCgoyk9MzlBIyy8CyoSWZOZkllQq-CZWZOZmViWWZObn8TCwpiXmFKfyQmluBmU31xBnD12gzsLS1OKS-Kz80qI8oFQ80CIzY0sTY2NzY-JUAQANPzQt</recordid><startdate>20220613</startdate><enddate>20220613</enddate><creator>Chen, Qiguan</creator><creator>Song, Yulin</creator><creator>Wang, Zengwu</creator><creator>Yuan, Zengting</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20220613</creationdate><title>The G-Martingale Approach for G-Utility Maximization</title><author>Chen, Qiguan ; Song, Yulin ; Wang, Zengwu ; Yuan, Zengting</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_26763943373</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Brownian motion</topic><topic>Economic models</topic><topic>Martingales</topic><topic>Maximization</topic><topic>Optimization</topic><topic>Stochastic processes</topic><toplevel>online_resources</toplevel><creatorcontrib>Chen, Qiguan</creatorcontrib><creatorcontrib>Song, Yulin</creatorcontrib><creatorcontrib>Wang, Zengwu</creatorcontrib><creatorcontrib>Yuan, Zengting</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Qiguan</au><au>Song, Yulin</au><au>Wang, Zengwu</au><au>Yuan, Zengting</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>The G-Martingale Approach for G-Utility Maximization</atitle><jtitle>arXiv.org</jtitle><date>2022-06-13</date><risdate>2022</risdate><eissn>2331-8422</eissn><abstract>In this paper, we study representative investor's G-utility maximization problem by G-martingale approach in the framework of G-expectation space proposed by Peng \cite{Pe19}. Financial market has only a bond and a stock with uncertainty characterized by G-Brownian motions. The routine idea of \cite{Wxz} fails because that the quadratic variation process of a G-Brownian motion is also a stochastic process. To overcome this difficulty, an extended nonlinear expectation should be pulled in. A sufficient condition of G-utility maximization is presented firstly. In the case of log-utility, an explicit solution of optimal strategy can be obtained by constructing and solving a couple of G-FBSDEs, then verifying the optimal strategy to meet the sufficient condition. As an application, an explicit solution of a stochastic interest model is obtained by the same approach. All economic meanings of optimal strategies are consistent with our intuitions.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2022-06
issn 2331-8422
language eng
recordid cdi_proquest_journals_2676394337
source Free E- Journals
subjects Brownian motion
Economic models
Martingales
Maximization
Optimization
Stochastic processes
title The G-Martingale Approach for G-Utility Maximization
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T00%3A22%3A06IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=The%20G-Martingale%20Approach%20for%20G-Utility%20Maximization&rft.jtitle=arXiv.org&rft.au=Chen,%20Qiguan&rft.date=2022-06-13&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2676394337%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2676394337&rft_id=info:pmid/&rfr_iscdi=true