東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Portfolio optimization with differen...

Hillairet, Caroline,

Linked to FindBook

Google Book

Amazon

博客來

Portfolio optimization with different information flow /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Portfolio optimization with different information flow // Caroline Hillairet, Ying Jiao.
Author:	Hillairet, Caroline,
other author:	Jiao, Ying,
Description:	1 online resource (192 pages).
[NT 15003449]:	Front Cover ; Portfolio Optimization with Different Information Flow; Copyright; Contents; Introduction; Acknowledgments; 1. Optimization Problems; 1.1. Portfolio optimization problem; 1.2. Duality approach; 1.3. Dynamic programming principle; 1.4. Several explicit examples; 1.5. Brownian-Poisson filtration with general utility weights; 2. Enlargement of Filtration; 2.1. Conditional law and density hypothesis; 2.2. Initial enlargement of filtration; 2.3. Progressive enlargement of filtration; 3. Portfolio Optimization with Credit Risk; 3.1. Model setup.
[NT 15003449]:	3.2. Direct method with the logarithmic utility3.3. Optimization for standard investor: power utility; 3.4. Decomposition method with the exponential utility; 3.5. Optimization with insider's information; 3.6. Numerical illustrations; 4. Portfolio Optimization with Information Asymmetry; 4.1. The market; 4.2. Optimal strategies in some examples of side-information; 4.3. Numerical illustrations; Bibliography; Index; Back Cover.
Subject:	Portfolio management. -
Online resource:	https://www.sciencedirect.com/science/book/9781785480843
ISBN:	9780081011775

Portfolio optimization with different information flow /
Hillairet, Caroline,

Portfolio optimization with different information flow /Caroline Hillairet, Ying Jiao. - 1 online resource (192 pages). - Optimization in insurance and finance set. - Optimization in insurance and finance set..

Includes bibliographical references (pages 165-173) and index.

Front Cover ; Portfolio Optimization with Different Information Flow; Copyright; Contents; Introduction; Acknowledgments; 1. Optimization Problems; 1.1. Portfolio optimization problem; 1.2. Duality approach; 1.3. Dynamic programming principle; 1.4. Several explicit examples; 1.5. Brownian-Poisson filtration with general utility weights; 2. Enlargement of Filtration; 2.1. Conditional law and density hypothesis; 2.2. Initial enlargement of filtration; 2.3. Progressive enlargement of filtration; 3. Portfolio Optimization with Credit Risk; 3.1. Model setup.

Portfolio Optimization with Different Information Flow recalls the stochastic tools and results concerning the stochastic optimization theory and the enlargement filtration theory.The authors apply the theory of the enlargement of filtrations and solve the optimization problem. Two main types of enlargement of filtration are discussed: initial and progressive, using tools from various fields, such as from stochastic calculus and convex analysis, optimal stochastic control and backward stochastic differential equations. This theoretical and numerical analysis is applied in different market settings to provide a good basis for the understanding of portfolio optimization with different information flow.

ISBN: 9780081011775Subjects--Topical Terms:

646616
Portfolio management.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: HG4529.5

Dewey Class. No.: 332.67/8

Portfolio optimization with different information flow /
LDR:03097cmm a2200325 i 4500 001 2185733
006 m o d
007 cr |||||||||||
008 200116t20172017enk ob 001 0 eng d
020 $a 9780081011775 $q (electronic bk.)
020 $a 0081011776 $q (electronic bk.)
020 $a 9781785480843
035 $a (OCoLC)975046185 $z (OCoLC)972627903 $z (OCoLC)972734327 $z (OCoLC)972773528 $z (OCoLC)973008994 $z (OCoLC)973019776 $z (OCoLC)973135630 $z (OCoLC)973183025 $z (OCoLC)973316230 $z (OCoLC)973367604 $z (OCoLC)973533583 $z (OCoLC)973768587 $z (OCoLC)982160138 $z (OCoLC)982233371 $z (OCoLC)982363161
035 $a els69900577
040 $a IDEBK $b eng $e rda $e pn $c IDEBK $d YDX $d EBLCP $d N$T $d NLE $d OCLCF $d OPELS $d MERER $d UPM $d OCLCQ $d IDEBK $d OTZ $d OCLCQ $d OCL $d MERUC
041 0 $a eng
050 4 $a HG4529.5
082 0 4 $a 332.67/8 $2 23
100 1 $a Hillairet, Caroline, $e author. $3 3399170
245 1 0 $a Portfolio optimization with different information flow / $c Caroline Hillairet, Ying Jiao.
264 1 $a London [England] ; $a Oxford [England] : $b ISTE Press Ltd : $b Elsevier Ltd, $c [2017]
264 4 $c ©2017
300 $a 1 online resource (192 pages).
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
490 1 $a Optimization in insurance and finance set
504 $a Includes bibliographical references (pages 165-173) and index.
505 0 $a Front Cover ; Portfolio Optimization with Different Information Flow; Copyright; Contents; Introduction; Acknowledgments; 1. Optimization Problems; 1.1. Portfolio optimization problem; 1.2. Duality approach; 1.3. Dynamic programming principle; 1.4. Several explicit examples; 1.5. Brownian-Poisson filtration with general utility weights; 2. Enlargement of Filtration; 2.1. Conditional law and density hypothesis; 2.2. Initial enlargement of filtration; 2.3. Progressive enlargement of filtration; 3. Portfolio Optimization with Credit Risk; 3.1. Model setup.
505 8 $a 3.2. Direct method with the logarithmic utility3.3. Optimization for standard investor: power utility; 3.4. Decomposition method with the exponential utility; 3.5. Optimization with insider's information; 3.6. Numerical illustrations; 4. Portfolio Optimization with Information Asymmetry; 4.1. The market; 4.2. Optimal strategies in some examples of side-information; 4.3. Numerical illustrations; Bibliography; Index; Back Cover.
520 $a Portfolio Optimization with Different Information Flow recalls the stochastic tools and results concerning the stochastic optimization theory and the enlargement filtration theory.The authors apply the theory of the enlargement of filtrations and solve the optimization problem. Two main types of enlargement of filtration are discussed: initial and progressive, using tools from various fields, such as from stochastic calculus and convex analysis, optimal stochastic control and backward stochastic differential equations. This theoretical and numerical analysis is applied in different market settings to provide a good basis for the understanding of portfolio optimization with different information flow.
650 0 $a Portfolio management. $3 646616
650 0 $a Investment analysis. $3 566988
650 0 $a Stocks. $3 646671
650 0 $a Investments. $3 566987
655 4 $a Electronic books. $2 lcsh $3 542853
700 1 $a Jiao, Ying, $e author. $3 3399171
830 0 $a Optimization in insurance and finance set. $3 3389849
856 4 0 $u https://www.sciencedirect.com/science/book/9781785480843