Edited by Stavros A. Zenios
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Financial Optimization by Stavros A. Zenios
Book DescriptionThe use of formal mathematical models and optimization in finance has become common practice in the 1980s and 1990s. This book clearly presents the exciting symbiosis between the fields of finance and management science/operations research. Prominent researchers present the state of the art in financial optimization, while analysts from industry discuss the latest business techniques practised by financial firms in New York, London and Tokyo. The book covers a wide range of topics: portfolio management of equities and fixed income investments, the pricing of complex insurance, mortgage and other asset-backed products, and models for risk-management and diversification.
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Book DetailsISBN: 9780521577779
(228mm x 152mm x 21mm)
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 28-Oct-1996
Country of Publication: United Kingdom
Books By Author Stavros A. Zenios
Practical Financial Optimization, Hardback (May 2009)
This title provides a stable of General Algebraic Modeling System (GAMS) models which can be adapted for use for particular optimization purposes.
Handbook of Asset and Liability Management, Hardback (July 2007)
Focuses on applications and case studies in asset and liability management. This volume portrays ALM in practice which addresses the theories and methodologies behind these models. It describes and analyzes models used in banking, insurance, money management, individual investor financial planning, pension funds, and social security.
Performance of Financial Institutions, Paperback (May 2000)
This volume addresses the importance of the efficient operation of financial intermediaries with respect to the efficient functioning of the present and future financial systems.
Parallel Optimization, Hardback (September 1997)» View all books by Stavros A. Zenios
This text provides an introduction to the methods of parallel optimization by introducing parallel computing ideas and techniques into both optimization theory and numerical algorithms for large-scale optimization problems.
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