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  • Cited by 31
Publisher:
Cambridge University Press
Online publication date:
July 2018
Print publication year:
2018
Online ISBN:
9781107297340

Book description

Optimization methods play a central role in financial modeling. This textbook is devoted to explaining how state-of-the-art optimization theory, algorithms, and software can be used to efficiently solve problems in computational finance. It discusses some classical mean–variance portfolio optimization models as well as more modern developments such as models for optimal trade execution and dynamic portfolio allocation with transaction costs and taxes. Chapters discussing the theory and efficient solution methods for the main classes of optimization problems alternate with chapters discussing their use in the modeling and solution of central problems in mathematical finance. This book will be interesting and useful for students, academics, and practitioners with a background in mathematics, operations research, or financial engineering. The second edition includes new examples and exercises as well as a more detailed discussion of mean–variance optimization, multi-period models, and additional material to highlight the relevance to finance.

Reviews

Review of first edition:'This book will be useful as a textbook for students in financial engineering at the MS level. … The book will also be of interest to researchers and graduate students in optimization who are interested in applications of optimization to financial problems.'

Brian Borchers Source: Journal of Online Mathematics and its Applications

Review of first edition:'This book would certainly appeal to someone with a mathematical background, perhaps in operations research, wishing to update and apply their knowledge to the financial world.'

Source: Mathematics TODAY

Review of first edition:'Until now, there has been no comprehensive optimization book aimed at quantitative analysts in the financial industry. The book by Cornuejols and Tutuncu fills this void … an excellent source for quantitative financial analysts and graduate students to learn about basic optimization theory, computational methods, and available software. At the same time, it can be used by academic researchers and students in optimization as an introduction to various interesting problems in financial applications.'

Source: International Review of Economics & Finance

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