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- Publisher Website: 10.4208/nmtma.2018.s02
- Scopus: eid_2-s2.0-85072072756
- WOS: WOS:000438884900003
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Article: A Markov-Driven Portfolio Execution Strategy with Market Impact
Title | A Markov-Driven Portfolio Execution Strategy with Market Impact |
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Authors | |
Keywords | Hamilton-Jacobi-Bellman (HJB) equation Limit Order Book (LOB) Dynamic Programming (DP) principle Market impact Quadratic Programming (QP) Regime-switching Value iteration method |
Issue Date | 2018 |
Publisher | Global 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? |
Abstract | In 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 Identifier | http://hdl.handle.net/10722/258607 |
ISSN | 2023 Impact Factor: 1.9 2023 SCImago Journal Rankings: 0.670 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Yang, Q | - |
dc.contributor.author | Ching, WK | - |
dc.contributor.author | Siu, T | - |
dc.contributor.author | Zhang, Z | - |
dc.date.accessioned | 2018-08-22T01:41:12Z | - |
dc.date.available | 2018-08-22T01:41:12Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Numerical Mathematics: Theory, Methods and Applications, 2018, v. 11 n. 4, p. 701-728 | - |
dc.identifier.issn | 1004-8979 | - |
dc.identifier.uri | http://hdl.handle.net/10722/258607 | - |
dc.description.abstract | In 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.language | eng | - |
dc.publisher | Global Science Press. The Journal's web site is located at http://www.global-sci.org/nmtma/ | - |
dc.relation.ispartof | Numerical Mathematics: Theory, Methods and Applications | - |
dc.subject | Hamilton-Jacobi-Bellman (HJB) equation | - |
dc.subject | Limit Order Book (LOB) | - |
dc.subject | Dynamic Programming (DP) principle | - |
dc.subject | Market impact | - |
dc.subject | Quadratic Programming (QP) | - |
dc.subject | Regime-switching | - |
dc.subject | Value iteration method | - |
dc.title | A Markov-Driven Portfolio Execution Strategy with Market Impact | - |
dc.type | Article | - |
dc.identifier.email | Ching, WK: wching@hku.hk | - |
dc.identifier.email | Zhang, Z: zhangzw@hku.hk | - |
dc.identifier.authority | Ching, WK=rp00679 | - |
dc.identifier.authority | Zhang, Z=rp02087 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.4208/nmtma.2018.s02 | - |
dc.identifier.scopus | eid_2-s2.0-85072072756 | - |
dc.identifier.hkuros | 286565 | - |
dc.identifier.volume | 11 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | 701 | - |
dc.identifier.epage | 728 | - |
dc.identifier.isi | WOS:000438884900003 | - |
dc.publisher.place | Hong Kong | - |
dc.identifier.issnl | 1004-8979 | - |