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Article: A Markov-Driven Portfolio Execution Strategy with Market Impact

TitleA Markov-Driven Portfolio Execution Strategy with Market Impact
Authors
KeywordsHamilton-Jacobi-Bellman (HJB) equation
Limit Order Book (LOB)
Dynamic Programming (DP) principle
Market impact
Quadratic Programming (QP)
Regime-switching
Value iteration method
Issue Date2018
PublisherGlobal Science Press. The Journal's web site is located at http://www.global-sci.org/nmtma/
Citation
Numerical Mathematics: Theory, Methods and Applications, 2018, v. 11 n. 4, p. 701-728 How to Cite?
AbstractIn this paper, we propose a framework for studying optimal agency execution strategies in a Limit Order Book (LOB) under a Markov-modulated market environment. The Almgren-Chriss’s market impact model [1] is extended to a more general situation where multiple venues are available for investors to submit trades. Under the assumption of risk-neutrality, a compact recursive formula is derived, using the value iterative method, to calculate the optimal agency execution strategy. The original optimal control problem is then converted to a constrained quadratic optimization problem, which can be solved by using the Quadratic Programming (QP) approach. Numerical examples are given to illustrate the efficiency and effective of our proposed methods.
Persistent Identifierhttp://hdl.handle.net/10722/258607
ISSN
2017 Impact Factor: 0.695
2015 SCImago Journal Rankings: 0.548
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYang, Q-
dc.contributor.authorChing, WK-
dc.contributor.authorSiu, T-
dc.contributor.authorZhang, Z-
dc.date.accessioned2018-08-22T01:41:12Z-
dc.date.available2018-08-22T01:41:12Z-
dc.date.issued2018-
dc.identifier.citationNumerical Mathematics: Theory, Methods and Applications, 2018, v. 11 n. 4, p. 701-728-
dc.identifier.issn1004-8979-
dc.identifier.urihttp://hdl.handle.net/10722/258607-
dc.description.abstractIn this paper, we propose a framework for studying optimal agency execution strategies in a Limit Order Book (LOB) under a Markov-modulated market environment. The Almgren-Chriss’s market impact model [1] is extended to a more general situation where multiple venues are available for investors to submit trades. Under the assumption of risk-neutrality, a compact recursive formula is derived, using the value iterative method, to calculate the optimal agency execution strategy. The original optimal control problem is then converted to a constrained quadratic optimization problem, which can be solved by using the Quadratic Programming (QP) approach. Numerical examples are given to illustrate the efficiency and effective of our proposed methods.-
dc.languageeng-
dc.publisherGlobal Science Press. The Journal's web site is located at http://www.global-sci.org/nmtma/-
dc.relation.ispartofNumerical Mathematics: Theory, Methods and Applications-
dc.subjectHamilton-Jacobi-Bellman (HJB) equation-
dc.subjectLimit Order Book (LOB)-
dc.subjectDynamic Programming (DP) principle-
dc.subjectMarket impact-
dc.subjectQuadratic Programming (QP)-
dc.subjectRegime-switching-
dc.subjectValue iteration method-
dc.titleA Markov-Driven Portfolio Execution Strategy with Market Impact-
dc.typeArticle-
dc.identifier.emailChing, WK: wching@hku.hk-
dc.identifier.emailZhang, Z: zhangzw@hku.hk-
dc.identifier.authorityChing, WK=rp00679-
dc.identifier.authorityZhang, Z=rp02087-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.4208/nmtma.2018.s02-
dc.identifier.hkuros286565-
dc.identifier.volume11-
dc.identifier.issue4-
dc.identifier.spage701-
dc.identifier.epage728-
dc.identifier.isiWOS:000438884900003-
dc.publisher.placeHong Kong-

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