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Computational Methods in Decision-Making, Economics and Finance (Hardcover, 2002 ed.): Erricos John Kontoghiorghes, B. Rustem,... Computational Methods in Decision-Making, Economics and Finance (Hardcover, 2002 ed.)
Erricos John Kontoghiorghes, B. Rustem, S. Siokos
R8,709 Discovery Miles 87 090 Ships in 12 - 17 working days

Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.

Computational Methods in Decision-Making, Economics and Finance (Paperback, Softcover reprint of hardcover 1st ed. 2002):... Computational Methods in Decision-Making, Economics and Finance (Paperback, Softcover reprint of hardcover 1st ed. 2002)
Erricos John Kontoghiorghes, B. Rustem, S. Siokos
R8,627 Discovery Miles 86 270 Ships in 10 - 15 working days

Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.
Optimization is at the core of rational decision making. Even when the decision maker has more than one goal or there is significant uncertainty in the system, optimization provides a rational framework for efficient decisions. The Markowitz mean-variance formulation is a classical example. The first part of the book is on recent developments in optimization decision models for finance and economics. The first four chapters of this part focus directly on multi-stage problems in finance. Chapters 5-8 involve the use of worst-case robust analysis. Chapters 9-11 are devoted to portfolio optimization. The final four chapters are on transportation-inventory with stochastic demand; optimal investment with CRRA utility; hedging financial contracts; and, automatic differentiation for computational finance.
The uncertainty associated with prediction and modeling constantly requires the development of improved methods and models. Similarly, as systems strive towards equilibria, the characterization and computation of equilibria assists analysis and prediction. The second part of the book is devoted to recent research in computational tools and models of equilibria, prediction, and pricing. The first three chapters of this part consider hedging issues in finance. Chapters 19-22 consider prediction and modeling methodologies. Chapters 23-26 focus on auctions and equilibria. Volatility models are investigated in chapters 27-28. The final two chapters investigate risk assessment and product pricing.
Audience: Researchers working in computational issues related to economics, finance, and management science.

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