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The book introduces the key ideas behind practical nonlinear optimization. Computational finance – an increasingly popular area of mathematics degree programs – is combined here with the study of an important class of numerical techniques. The financial content of the book is designed to be relevant and interesting to specialists. However, this material – which occupies about one-third of the text – is also sufficiently accessible to allow the book to be used on optimization courses of a more general nature. The essentials of most currently popular algorithms are described, and their performance is demonstrated on a range of optimization problems arising in financial mathematics. Theoretical convergence properties of methods are stated, and formal proofs are provided in enough cases to be instructive rather than overwhelming. Practical behavior of methods is illustrated by computational examples and discussions of efficiency, accuracy and computational costs. Supporting software for the examples and exercises is available (but the text does not require the reader to use or understand these particular codes). The author has been active in optimization for over thirty years in algorithm development and application and in teaching and research supervision.
From the Back Cover:
• The book introduces the key ideas behind practical nonlinear optimization.
• Computational finance―an increasingly popular area of mathematics degree programmes―is combined here with the study of an important class of numerical techniques.
• The financial content of the book is designed to be relevant and interesting to specialists. However, this material―which occupies about one-third of the text―is also sufficiently accessible to allow the book to be used on optimization courses of a more general nature.
• The essentials of most currently popular algorithms are described and their performance is demonstrated on a range of optimization problems arising in financial mathematics.
• Theoretical convergence properties of methods are stated and formal proofs are provided in enough cases to be instructive rather than overwhelming.
• Practical behaviour of methods is illustrated by computational examples and discussions of efficiency, accuracy and computational costs.
• Supporting software for the examples and exercises is available (but the text does not require the reader to use or understand these particular codes).
• The author has been active in optimization for over thirty years in algorithm development and application and in teaching and research supervision.
Audience
The book is aimed at lecturers and students (undergraduate and postgraduate) in mathematics, computational finance and related subjects. It is also useful for researchers and practitioners who need a good introduction to nonlinear optimization.
Title: Nonlinear Optimization with Financial ...
Publisher: Springer
Publication Date: 2005
Binding: Hardcover
Condition: New
Seller: Magus Books Seattle, Seattle, WA, U.S.A.
Hardcover. Condition: VG. used hardcover copy in illustrated boards, no jacket, as issued. light shelfwear, corners perhaps slightly bumped. pages and binding are clean, straight and tight. there are no marks to the text or other serious flaws. Seller Inventory # 1321423
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Seller: online-buch-de, Dozwil, Switzerland
Hardcover Jan 04, 2005. Condition: gebraucht; wie neu. Seller Inventory # 500-3-1-5
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Seller: Grand Eagle Retail, Mason, OH, U.S.A.
Hardcover. Condition: new. Hardcover. The book introduces the key ideas behind practical nonlinear optimization. Computational finance an increasingly popular area of mathematics degree programs is combined here with the study of an important class of numerical techniques. The financial content of the book is designed to be relevant and interesting to specialists. However, this material which occupies about one-third of the text is also sufficiently accessible to allow the book to be used on optimization courses of a more general nature. The essentials of most currently popular algorithms are described, and their performance is demonstrated on a range of optimization problems arising in financial mathematics. Theoretical convergence properties of methods are stated, and formal proofs are provided in enough cases to be instructive rather than overwhelming. Practical behavior of methods is illustrated by computational examples and discussions of efficiency, accuracy and computational costs. Supporting software for the examples and exercises is available (but the text does not require the reader to use or understand these particular codes). The author has been active in optimization for over thirty years in algorithm development and application and in teaching and research supervision. Computational finance an increasingly popular area of mathematics degree programs is combined here with the study of an important class of numerical techniques. However, this material which occupies about one-third of the text is also sufficiently accessible to allow the book to be used on optimization courses of a more general nature. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781402081101
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Condition: New. pp. 280. Seller Inventory # 26330208
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Condition: New. pp. 280 Illus. Seller Inventory # 7517759
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hardcover. Condition: New. In shrink wrap. Looks like an interesting title! Seller Inventory # Q-1402081103
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Condition: New. pp. 280. Seller Inventory # 18330218
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Hardcover. Condition: Like New. Like New. book. Seller Inventory # ERICA77314020811036
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Seller: AussieBookSeller, Truganina, VIC, Australia
Hardcover. Condition: new. Hardcover. The book introduces the key ideas behind practical nonlinear optimization. Computational finance an increasingly popular area of mathematics degree programs is combined here with the study of an important class of numerical techniques. The financial content of the book is designed to be relevant and interesting to specialists. However, this material which occupies about one-third of the text is also sufficiently accessible to allow the book to be used on optimization courses of a more general nature. The essentials of most currently popular algorithms are described, and their performance is demonstrated on a range of optimization problems arising in financial mathematics. Theoretical convergence properties of methods are stated, and formal proofs are provided in enough cases to be instructive rather than overwhelming. Practical behavior of methods is illustrated by computational examples and discussions of efficiency, accuracy and computational costs. Supporting software for the examples and exercises is available (but the text does not require the reader to use or understand these particular codes). The author has been active in optimization for over thirty years in algorithm development and application and in teaching and research supervision. Computational finance an increasingly popular area of mathematics degree programs is combined here with the study of an important class of numerical techniques. However, this material which occupies about one-third of the text is also sufficiently accessible to allow the book to be used on optimization courses of a more general nature. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781402081101
Quantity: 1 available