Stochastic Economics

Stochastic Economics PDF

Author: Gerhard Tintner

Publisher: Elsevier

Published: 2014-05-10

Total Pages: 328

ISBN-13: 1483274020

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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.

Stochastic Modeling in Economics and Finance

Stochastic Modeling in Economics and Finance PDF

Author: Jitka Dupacova

Publisher: Springer Science & Business Media

Published: 2005-12-30

Total Pages: 394

ISBN-13: 0306481677

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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.

Security Markets

Security Markets PDF

Author: Darrell Duffie

Publisher: Academic Press Incorporated

Published: 1988-07-28

Total Pages: 682

ISBN-13:

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This is an introduction to the theory of security markets, dealing principally with the allocational role and valuation of financial securities in a competitive setting.

Stochastic Dominance and Applications to Finance, Risk and Economics

Stochastic Dominance and Applications to Finance, Risk and Economics PDF

Author: Songsak Sriboonchita

Publisher: CRC Press

Published: 2009-10-19

Total Pages: 455

ISBN-13: 9781420082678

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Drawing from many sources in the literature, Stochastic Dominance and Applications to Finance, Risk and Economics illustrates how stochastic dominance (SD) can be used as a method for risk assessment in decision making. It provides basic background on SD for various areas of applications. Useful Concepts and Techniques for Economics ApplicationsThe

Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population

Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population PDF

Author: JOEL COHEN

Publisher: Springer Science & Business Media

Published: 1998-09-29

Total Pages: 170

ISBN-13: 9780817640828

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Some of the possible implications among these comparisons remain open questions. The results in this book establish a new field of investigation for both mathematicians and scientific users interested in the variations among multiple probability distributions.

Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations

Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations PDF

Author: Steven R. Dunbar

Publisher: American Mathematical Soc.

Published: 2019-04-03

Total Pages: 232

ISBN-13: 1470448394

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Mathematical Modeling in Economics and Finance is designed as a textbook for an upper-division course on modeling in the economic sciences. The emphasis throughout is on the modeling process including post-modeling analysis and criticism. It is a textbook on modeling that happens to focus on financial instruments for the management of economic risk. The book combines a study of mathematical modeling with exposure to the tools of probability theory, difference and differential equations, numerical simulation, data analysis, and mathematical analysis. Students taking a course from Mathematical Modeling in Economics and Finance will come to understand some basic stochastic processes and the solutions to stochastic differential equations. They will understand how to use those tools to model the management of financial risk. They will gain a deep appreciation for the modeling process and learn methods of testing and evaluation driven by data. The reader of this book will be successfully positioned for an entry-level position in the financial services industry or for beginning graduate study in finance, economics, or actuarial science. The exposition in Mathematical Modeling in Economics and Finance is crystal clear and very student-friendly. The many exercises are extremely well designed. Steven Dunbar is Professor Emeritus of Mathematics at the University of Nebraska and he has won both university-wide and MAA prizes for extraordinary teaching. Dunbar served as Director of the MAA's American Mathematics Competitions from 2004 until 2015. His ability to communicate mathematics is on full display in this approachable, innovative text.

Stochastic Discounted Cash Flow

Stochastic Discounted Cash Flow PDF

Author: Lutz Kruschwitz

Publisher: Springer Nature

Published: 2020-02-28

Total Pages: 256

ISBN-13: 303037081X

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This open access book discusses firm valuation, which is of interest to economists, particularly those working in finance. Firm valuation comes down to the calculation of the discounted cash flow, often only referred to by its abbreviation, DCF. There are, however, different coexistent versions, which seem to compete against each other, such as entity approaches and equity approaches. Acronyms are often used, such as APV (adjusted present value) or WACC (weighted average cost of capital), two concepts classified as entity approaches. This book explains why there are several procedures and whether they lead to the same result. It also examines the economic differences between the methods and indicates the various purposes they serve. Further it describes the limits of the procedures and the situations they are best applied to. The problems this book addresses are relevant to theoreticians and practitioners alike.

An Introduction to Stochastic Modeling

An Introduction to Stochastic Modeling PDF

Author: Howard M. Taylor

Publisher: Academic Press

Published: 2014-05-10

Total Pages: 410

ISBN-13: 1483269272

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An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Stochastic Models of Buying Behavior

Stochastic Models of Buying Behavior PDF

Author: William F. Massy

Publisher: MIT Press (MA)

Published: 1970

Total Pages: 488

ISBN-13:

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Approaches to stochastic modeling; Estimating and testing stochastic models; Brand-choice models; Zero-order models; Two state markov models; Linear learning models for brand choice; A probability diffusion model; Application of the probability diffusion model; Purchase incidence models; Models for purchase timing and market penetration; A stochastic model for monitoring new product adoption; Parameter estimations and some emperical results for STEAM; Extension to STEAM.

Stochastic Dominance

Stochastic Dominance PDF

Author: Haim Levy

Publisher: Springer Science & Business Media

Published: 2006-08-25

Total Pages: 439

ISBN-13: 0387293116

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This book is devoted to investment decision-making under uncertainty. The book covers three basic approaches to this process: the stochastic dominance approach; the mean-variance approach; and the non-expected utility approach, focusing on prospect theory and its modified version, cumulative prospect theory. Each approach is discussed and compared. In addition, this volume examines cases in which stochastic dominance rules coincide with the mean-variance rule and considers how contradictions between these two approaches may occur.