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Operator Splitting Method and Its Ap...
~
Wang, Jiazhou.
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Operator Splitting Method and Its Applications in Quantitative Finance.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Operator Splitting Method and Its Applications in Quantitative Finance./
Author:
Wang, Jiazhou.
Published:
Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:
129 p.
Notes:
Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Contained By:
Dissertations Abstracts International80-10B.
Subject:
Applied Mathematics. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13424962
ISBN:
9781392059708
Operator Splitting Method and Its Applications in Quantitative Finance.
Wang, Jiazhou.
Operator Splitting Method and Its Applications in Quantitative Finance.
- Ann Arbor : ProQuest Dissertations & Theses, 2018 - 129 p.
Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Thesis (Ph.D.)--State University of New York at Stony Brook, 2018.
This item must not be sold to any third party vendors.
Numerical method plays main role in quantitative finance, such as stochastic differential equations and portfolio optimization. In this thesis, we consider two operator splitting methods as the numerical schemes. First, we consider Forward-Backward splitting in the portfolio optimization. We propose two methods: proximal gradient Newton (PGN) method and proximal gradient diagonal Hessian (PGDH) method. These two methods have significant better performance in both execution time and accuracy than other known methods. Second, we consider Peaceman-Rachford splitting in the SDEs. We propose using Peaceman-Rachford splitting as a novel scheme solving SDEs. Numerical result shows that the proposed scheme outperforms other classical numerical schemes.
ISBN: 9781392059708Subjects--Topical Terms:
1669109
Applied Mathematics.
Operator Splitting Method and Its Applications in Quantitative Finance.
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Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
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Advisor: Mullhaupt, Andrew.
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Thesis (Ph.D.)--State University of New York at Stony Brook, 2018.
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This item must not be sold to any third party vendors.
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Numerical method plays main role in quantitative finance, such as stochastic differential equations and portfolio optimization. In this thesis, we consider two operator splitting methods as the numerical schemes. First, we consider Forward-Backward splitting in the portfolio optimization. We propose two methods: proximal gradient Newton (PGN) method and proximal gradient diagonal Hessian (PGDH) method. These two methods have significant better performance in both execution time and accuracy than other known methods. Second, we consider Peaceman-Rachford splitting in the SDEs. We propose using Peaceman-Rachford splitting as a novel scheme solving SDEs. Numerical result shows that the proposed scheme outperforms other classical numerical schemes.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13424962
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