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Optimization Methods in Finance.
~
Cornuejols, Gerard.
Optimization Methods in Finance.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Optimization Methods in Finance./
Author:
Cornuejols, Gerard.
other author:
Tutuncu, Reha.
Published:
Leiden :Cambridge University Press, : 2006.,
Description:
359 p.
Subject:
Finance. -
Online resource:
Click here to view book
ISBN:
9780511753886 (electronic bk.)
Optimization Methods in Finance.
Cornuejols, Gerard.
Optimization Methods in Finance.
[electronic resource]. - Leiden :Cambridge University Press,2006. - 359 p.
Cover; Half-title; Series-title; Title; Copyright; Dedication; Contents; Foreword; 1 Introduction; 2 Linear programming: theory and algorithms; 3 LP models: asset/liability cash-flow matching; 4 LP models: asset pricing and arbitrage; 5 Nonlinear programming: theory and algorithms; 6 NLP models: volatility estimation; 7 Quadratic programming: theory and algorithms; 8 QP models: portfolio optimization; 9 Conic optimization tools; 10 Conic optimization models in finance; 11 Integer programming: theory and algorithms; 12 Integer programming models: constructing an index fund
Discusses optimization problems encountered in financial models, describes the relevant theory and efficient solution methods, and shows how to apply them to practical problems in mathematical finance. Based on a successful course at CMU, the text is class-tested and meets the need for a textbook aimed at financial applications.
Electronic reproduction.
Available via World Wide Web.
Mode of access: World Wide Web.
ISBN: 9780511753886 (electronic bk.)Subjects--Topical Terms:
131585
Finance.
Index Terms--Genre/Form:
96803
Electronic books.
LC Class. No.: HG106 .C67 2007eb
Dewey Class. No.: 332.015196
Optimization Methods in Finance.
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Optimization Methods in Finance.
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[electronic resource].
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2006.
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Cambridge University Press,
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359 p.
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Cover; Half-title; Series-title; Title; Copyright; Dedication; Contents; Foreword; 1 Introduction; 2 Linear programming: theory and algorithms; 3 LP models: asset/liability cash-flow matching; 4 LP models: asset pricing and arbitrage; 5 Nonlinear programming: theory and algorithms; 6 NLP models: volatility estimation; 7 Quadratic programming: theory and algorithms; 8 QP models: portfolio optimization; 9 Conic optimization tools; 10 Conic optimization models in finance; 11 Integer programming: theory and algorithms; 12 Integer programming models: constructing an index fund
505
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13 Dynamic programming methods14 DP models: option pricing; 15 DP models: structuring asset-backed securities; 16 Stochastic programming: theory and algorithms; 17 Stochastic programming models: Value-at-Risk and Conditional Value-at-Risk; 18 Stochastic programming models: asset/liability management; 19 Robust optimization: theory and tools; 20 Robust optimization models in finance; Appendix A Convexity; Appendix B Cones; Appendix C A probabil
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Discusses optimization problems encountered in financial models, describes the relevant theory and efficient solution methods, and shows how to apply them to practical problems in mathematical finance. Based on a successful course at CMU, the text is class-tested and meets the need for a textbook aimed at financial applications.
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Electronic reproduction.
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Available via World Wide Web.
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Tutuncu, Reha.
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Click here to view book
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http://ebooks.cambridge.org/ebook.jsf?bid=CBO9780511753886
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