Stochastic Optimization and Economic Models

Stochastic Optimization and Economic Models
Author: Jati Sengupta
Publisher: Springer Science & Business Media
Total Pages: 381
Release: 2013-03-09
Genre: Mathematics
ISBN: 9401730857

Download Stochastic Optimization and Economic Models Book in PDF, Epub and Kindle

This book presents the main applied aspects of stochas tic optimization in economic models. Stochastic processes and control theory are used under optimization to illustrate the various economic implications of optimal decision rules. Unlike econometrics which deals with estimation, this book emphasizes the decision-theoretic basis of uncertainty specified by the stochastic point of view. Methods of ap plied stochastic control using stochastic processes have now reached an exciti~g phase, where several disciplines like systems engineering, operations research and natural reso- ces interact along with the conventional fields such as mathematical economics, finance and control systems. Our objective is to present a critical overview of this broad terrain from a multidisciplinary viewpoint. In this attempt we have at times stressed viewpoints other than the purely economic one. We believe that the economist would find it most profitable to learn from the other disciplines where stochastic optimization has been successfully applied. It is in this spirit that we have discussed in some detail the following major areas: A. Portfolio models in ·:finance, B. Differential games under uncertainty, c. Self-tuning regulators, D. Models of renewable resources under uncertainty, and ix x PREFACE E. Nonparametric methods of efficiency measurement. Stochastic processes are now increasingly used in economic models to understand the various adaptive behavior implicit in the formulation of expectation and its application in decision rules which are optimum in some sense.

Stochastic Optimization Models in Finance

Stochastic Optimization Models in Finance
Author: William T. Ziemba
Publisher: World Scientific
Total Pages: 756
Release: 2006
Genre: Business & Economics
ISBN: 981256800X

Download Stochastic Optimization Models in Finance Book in PDF, Epub and Kindle

A reprint of one of the classic volumes on portfolio theory and investment, this book has been used by the leading professors at universities such as Stanford, Berkeley, and Carnegie-Mellon. It contains five parts, each with a review of the literature and about 150 pages of computational and review exercises and further in-depth, challenging problems.Frequently referenced and highly usable, the material remains as fresh and relevant for a portfolio theory course as ever.

Stochastic Optimization Models in Finance

Stochastic Optimization Models in Finance
Author: W. T. Ziemba
Publisher: Academic Press
Total Pages: 736
Release: 2014-05-12
Genre: Business & Economics
ISBN: 1483273997

Download Stochastic Optimization Models in Finance Book in PDF, Epub and Kindle

Stochastic Optimization Models in Finance focuses on the applications of stochastic optimization models in finance, with emphasis on results and methods that can and have been utilized in the analysis of real financial problems. The discussions are organized around five themes: mathematical tools; qualitative economic results; static portfolio selection models; dynamic models that are reducible to static models; and dynamic models. This volume consists of five parts and begins with an overview of expected utility theory, followed by an analysis of convexity and the Kuhn-Tucker conditions. The reader is then introduced to dynamic programming; stochastic dominance; and measures of risk aversion. Subsequent chapters deal with separation theorems; existence and diversification of optimal portfolio policies; effects of taxes on risk taking; and two-period consumption models and portfolio revision. The book also describes models of optimal capital accumulation and portfolio selection. This monograph will be of value to mathematicians and economists as well as to those interested in economic theory and mathematical economics.

Stochastic Economics

Stochastic Economics
Author: Gerhard Tintner
Publisher: Elsevier
Total Pages: 328
Release: 2014-05-10
Genre: Mathematics
ISBN: 1483274020

Download Stochastic Economics Book in PDF, Epub and Kindle

Stochastic Economics: Stochastic Processes, Control, and Programming presents some aspects of economics from a stochastic or probabilistic point of view. The application of stochastic processes to the theory of economic development, stochastic control theory, and various aspects of stochastic programming is discussed. Comprised of four chapters, this book begins with a short survey of the stochastic view in economics, followed by a discussion on discrete and continuous stochastic models of economic development. The next chapter focuses on methods of stochastic control and their application to dynamic economic models, with emphasis on those aspects connected especially with the theory of quantitative economic policy. Some basic operational problems of applying stochastic control, particularly in economic systems and organizations for problems such as dynamic resource allocation, growth planning, and economic coordination are considered. The last chapter is devoted to stochastic programming, paying particular attention to the decision rule theory of operations research under the chance-constrained model and a method of incorporating reliability measures into a systems reliability model. This book will be of interest to economists, statisticians, applied mathematicians, operations researchers, and systems engineers.

Information and Efficiency in Economic Decision

Information and Efficiency in Economic Decision
Author: Jati Sengupta
Publisher: Springer Science & Business Media
Total Pages: 478
Release: 2012-12-06
Genre: Business & Economics
ISBN: 9400950535

Download Information and Efficiency in Economic Decision Book in PDF, Epub and Kindle

Use of information is basic to economic theory in two ways. As a basis for optimization, it is central to all normative hypotheses used in eco nomics, but in decision-making situations it has stochastic and evolution ary aspects that are more dynamic and hence more fundamental. This book provides an illustrative survey of the use of information in econom ics and other decision sciences. Since this area is one of the most active fields of research in modern times, it is not possible to be definitive on all aspects of the issues involved. However questions that appear to be most important in this author's view are emphasized in many cases, without drawing any definite conclusions. It is hoped that these questions would provoke new interest for those beginning researchers in the field who are currently most active. Various classifications of information structures and their relevance for optimal decision-making in a stochastic environment are analyzed in some detail. Specifically the following areas are illustrated in its analytic aspects: 1. Stochastic optimization in linear economic models, 2. Stochastic models in dynamic economics with problems of time-inc- sistency, causality and estimation, 3. Optimal output-inventory decisions in stochastic markets, 4. Minimax policies in portfolio theory, 5. Methods of stochastic control and differential games, and 6. Adaptive information structures in decision models in economics and the theory of economic policy.

Continuous-time Stochastic Control and Optimization with Financial Applications

Continuous-time Stochastic Control and Optimization with Financial Applications
Author: Huyên Pham
Publisher: Springer Science & Business Media
Total Pages: 243
Release: 2009-05-28
Genre: Mathematics
ISBN: 3540895000

Download Continuous-time Stochastic Control and Optimization with Financial Applications Book in PDF, Epub and Kindle

Stochastic optimization problems arise in decision-making problems under uncertainty, and find various applications in economics and finance. On the other hand, problems in finance have recently led to new developments in the theory of stochastic control. This volume provides a systematic treatment of stochastic optimization problems applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations, and martingale duality methods. The theory is discussed in the context of recent developments in this field, with complete and detailed proofs, and is illustrated by means of concrete examples from the world of finance: portfolio allocation, option hedging, real options, optimal investment, etc. This book is directed towards graduate students and researchers in mathematical finance, and will also benefit applied mathematicians interested in financial applications and practitioners wishing to know more about the use of stochastic optimization methods in finance.

Stochastic Modeling in Economics and Finance

Stochastic Modeling in Economics and Finance
Author: Jitka Dupacova
Publisher: Springer Science & Business Media
Total Pages: 394
Release: 2005-12-30
Genre: Mathematics
ISBN: 0306481677

Download Stochastic Modeling in Economics and Finance Book in PDF, Epub and Kindle

In Part I, the fundamentals of financial thinking and elementary mathematical methods of finance are presented. The method of presentation is simple enough to bridge the elements of financial arithmetic and complex models of financial math developed in the later parts. It covers characteristics of cash flows, yield curves, and valuation of securities. Part II is devoted to the allocation of funds and risk management: classics (Markowitz theory of portfolio), capital asset pricing model, arbitrage pricing theory, asset & liability management, value at risk. The method explanation takes into account the computational aspects. Part III explains modeling aspects of multistage stochastic programming on a relatively accessible level. It includes a survey of existing software, links to parametric, multiobjective and dynamic programming, and to probability and statistics. It focuses on scenario-based problems with the problems of scenario generation and output analysis discussed in detail and illustrated within a case study.

Optimization in Economics and Finance

Optimization in Economics and Finance
Author: Bruce D. Craven
Publisher: Springer Science & Business Media
Total Pages: 184
Release: 2005
Genre: Business & Economics
ISBN: 9780387242798

Download Optimization in Economics and Finance Book in PDF, Epub and Kindle

Extends the optimization techniques, in a form that may be adopted for modeling social choice problems. The models in this book provide possible models for a society's social choice for an allocation that maximizes welfare and utilization of resources. A computer program SCOM is presented here for computing social choice models by optimal control.

Optimization of Stochastic Models

Optimization of Stochastic Models
Author: Georg Ch. Pflug
Publisher: Springer
Total Pages: 382
Release: 1997-10-14
Genre: Business & Economics
ISBN: 9781461286318

Download Optimization of Stochastic Models Book in PDF, Epub and Kindle

Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research.

Stochastic Optimization Methods

Stochastic Optimization Methods
Author: Kurt Marti
Publisher: Springer
Total Pages: 389
Release: 2015-02-21
Genre: Business & Economics
ISBN: 3662462141

Download Stochastic Optimization Methods Book in PDF, Epub and Kindle

This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the probabilities and expectations involved, the book also shows how to apply approximative solution techniques. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures and differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising in engineering, economics and operations research.