Download or read book Stochastic Programming Applications In Finance Energy Planning And Logistics written by Horand I Gassmann and published by World Scientific. This book was released on 2012-11-28 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows the breadth and depth of stochastic programming applications. All the papers presented here involve optimization over the scenarios that represent possible future outcomes of the uncertainty problems. The applications, which were presented at the 12th International Conference on Stochastic Programming held in Halifax, Nova Scotia in August 2010, span the rich field of uses of these models. The finance papers discuss such diverse problems as longevity risk management of individual investors, personal financial planning, intertemporal surplus management, asset management with benchmarks, dynamic portfolio management, fixed income immunization and racetrack betting. The production and logistics papers discuss natural gas infrastructure design, farming Atlantic salmon, prevention of nuclear smuggling and sawmill planning. The energy papers involve electricity production planning, hydroelectric reservoir operations and power generation planning for liquid natural gas plants. Finally, two telecommunication papers discuss mobile network design and frequency assignment problems./a

Download or read book Essays on Economic Behavior Under Uncertainty written by Michael Balch and published by North-Holland. This book was released on 1974 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Financial Decision Making Under Uncertainty written by ANDERSON ANDERSON WEBSTER and published by Academic Press. This book was released on 2014-06-28 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Dec Making under Uncertainty

Download or read book Decision Making under Uncertainty in Financial Markets written by Jonas Ekblom and published by Linköping University Electronic Press. This book was released on 2018-09-13 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis addresses the topic of decision making under uncertainty, with particular focus on financial markets. The aim of this research is to support improved decisions in practice, and related to this, to advance our understanding of financial markets. Stochastic optimization provides the tools to determine optimal decisions in uncertain environments, and the optimality conditions of these models produce insights into how financial markets work. To be more concrete, a great deal of financial theory is based on optimality conditions derived from stochastic optimization models. Therefore, an important part of the development of financial theory is to study stochastic optimization models that step-by-step better capture the essence of reality. This is the motivation behind the focus of this thesis, which is to study methods that in relation to prevailing models that underlie financial theory allow additional real-world complexities to be properly modeled. The overall purpose of this thesis is to develop and evaluate stochastic optimization models that support improved decisions under uncertainty on financial markets. The research into stochastic optimization in financial literature has traditionally focused on problem formulations that allow closed-form or `exact' numerical solutions; typically through the application of dynamic programming or optimal control. The focus in this thesis is on two other optimization methods, namely stochastic programming and approximate dynamic programming, which open up opportunities to study new classes of financial problems. More specifically, these optimization methods allow additional and important aspects of many real-world problems to be captured. This thesis contributes with several insights that are relevant for both financial and stochastic optimization literature. First, we show that the modeling of several real-world aspects traditionally not considered in the literature are important components in a model which supports corporate hedging decisions. Specifically, we document the importance of modeling term premia, a rich asset universe and transaction costs. Secondly, we provide two methodological contributions to the stochastic programming literature by: (i) highlighting the challenges of realizing improved decisions through more stages in stochastic programming models; and (ii) developing an importance sampling method that can be used to produce high solution quality with few scenarios. Finally, we design an approximate dynamic programming model that gives close to optimal solutions to the classic, and thus far unsolved, portfolio choice problem with constant relative risk aversion preferences and transaction costs, given many risky assets and a large number of time periods.

Download or read book Dynamic Optimization Under Uncertainty written by Peter Jason Kalman and published by . This book was released on 1974 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book IMF Staff papers Volume 39 No 1 written by International Monetary Fund. Research Dept. and published by International Monetary Fund. This book was released on 1992-01-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper focuses on exchange rate economics. Two main views of exchange rate determination have evolved since the early 1970s: the monetary approach to the exchange rate (in flexible-price, sticky-price, and real interest differential formulations); and the portfolio balance approach. In this paper, the literature on these views is surveyed, followed by a discussion of the empirical evidence and likely future developments in the area of exchange rate determination. The literature on foreign exchange market efficiency, exchange rates and “news,” and international parity conditions is also reviewed.

Download or read book Stochastic Optimization Models in Finance written by William T. Ziemba and published by World Scientific. This book was released on 2006 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Stochastic Analysis And Applications To Finance Essays In Honour Of Jia an Yan written by Tusheng Zhang and published by World Scientific. This book was released on 2012-07-17 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a collection of solicited and refereed articles from distinguished researchers across the field of stochastic analysis and its application to finance. The articles represent new directions and newest developments in this exciting and fast growing area. The covered topics range from Markov processes, backward stochastic differential equations, stochastic partial differential equations, stochastic control, potential theory, functional inequalities, optimal stopping, portfolio selection, to risk measure and risk theory.It will be a very useful book for young researchers who want to learn about the research directions in the area, as well as experienced researchers who want to know about the latest developments in the area of stochastic analysis and mathematical finance.

Download or read book Quantitative Analysis In Financial Markets Collected Papers Of The New York University Mathematical Finance Seminar written by Marco Avellaneda and published by World Scientific. This book was released on 1999-10-27 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: This invaluable book contains lectures delivered at the celebrated Seminar in Mathematical Finance at the Courant Institute. The lecturers and presenters of papers are prominent researchers and practitioners in the field of quantitative financial modeling. Most are faculty members at leading universities or Wall Street practitioners.The lectures deal with the emerging science of pricing and hedging derivative securities and, more generally, managing financial risk. Specific articles concern topics such as option theory, dynamic hedging, interest-rate modeling, portfolio theory, price forecasting using statistical methods, etc.

Download or read book Applied Stochastic Models and Control for Finance and Insurance written by Charles S. Tapiero and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Stochastic Models and Control for Finance and Insurance presents at an introductory level some essential stochastic models applied in economics, finance and insurance. Markov chains, random walks, stochastic differential equations and other stochastic processes are used throughout the book and systematically applied to economic and financial applications. In addition, a dynamic programming framework is used to deal with some basic optimization problems. The book begins by introducing problems of economics, finance and insurance which involve time, uncertainty and risk. A number of cases are treated in detail, spanning risk management, volatility, memory, the time structure of preferences, interest rates and yields, etc. The second and third chapters provide an introduction to stochastic models and their application. Stochastic differential equations and stochastic calculus are presented in an intuitive manner, and numerous applications and exercises are used to facilitate their understanding and their use in Chapter 3. A number of other processes which are increasingly used in finance and insurance are introduced in Chapter 4. In the fifth chapter, ARCH and GARCH models are presented and their application to modeling volatility is emphasized. An outline of decision-making procedures is presented in Chapter 6. Furthermore, we also introduce the essentials of stochastic dynamic programming and control, and provide first steps for the student who seeks to apply these techniques. Finally, in Chapter 7, numerical techniques and approximations to stochastic processes are examined. This book can be used in business, economics, financial engineering and decision sciences schools for second year Master's students, as well as in a number of courses widely given in departments of statistics, systems and decision sciences.

Download or read book Reinforcement Learning and Stochastic Optimization written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2022-03-15 with total page 1090 pages. Available in PDF, EPUB and Kindle. Book excerpt: REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of “decision, information, decision, information,” are ubiquitous, spanning virtually every human activity ranging from business applications, health (personal and public health, and medical decision making), energy, the sciences, all fields of engineering, finance, and e-commerce. The diversity of applications attracted the attention of at least 15 distinct fields of research, using eight distinct notational systems which produced a vast array of analytical tools. A byproduct is that powerful tools developed in one community may be unknown to other communities. Reinforcement Learning and Stochastic Optimization offers a single canonical framework that can model any sequential decision problem using five core components: state variables, decision variables, exogenous information variables, transition function, and objective function. This book highlights twelve types of uncertainty that might enter any model and pulls together the diverse set of methods for making decisions, known as policies, into four fundamental classes that span every method suggested in the academic literature or used in practice. Reinforcement Learning and Stochastic Optimization is the first book to provide a balanced treatment of the different methods for modeling and solving sequential decision problems, following the style used by most books on machine learning, optimization, and simulation. The presentation is designed for readers with a course in probability and statistics, and an interest in modeling and applications. Linear programming is occasionally used for specific problem classes. The book is designed for readers who are new to the field, as well as those with some background in optimization under uncertainty. Throughout this book, readers will find references to over 100 different applications, spanning pure learning problems, dynamic resource allocation problems, general state-dependent problems, and hybrid learning/resource allocation problems such as those that arose in the COVID pandemic. There are 370 exercises, organized into seven groups, ranging from review questions, modeling, computation, problem solving, theory, programming exercises and a “diary problem” that a reader chooses at the beginning of the book, and which is used as a basis for questions throughout the rest of the book.

Download or read book The Hamiltonian Approach to Dynamic Economics written by David Cass and published by Academic Press. This book was released on 2014-05-10 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Hamiltonian Approach to Dynamic Economics focuses on the application of the Hamiltonian approach to dynamic economics and attempts to provide some unification of the theory of heterogeneous capital. Emphasis is placed on the stability of long-run steady-state equilibrium in models of heterogeneous capital accumulation. Generalizations of the Samuelson-Scheinkman approach are also given. Moreover, conditions are sought on the geometry of the Hamiltonian function (that is, on static technology) that suffice to preserve under (not necessarily small) perturbation the basic properties of the Hamiltonian dynamical system. Comprised of eight essays, this book begins with an introduction to Hamiltonian dynamics in economics, followed by a discussion on optimal steady states of n-sector growth models when utility is discounted. Optimal growth and decentralized or descriptive growth models in both continuous and discrete time are treated as applications of Hamiltonian dynamics. Theproblem of optimal growth with zero discounting is considered, with emphasis on a steepness condition on the Hamiltonian function. The general problem of decentralized growth with instantaneously adjusted expectations about price changes is also analyzed, along with the global asymptotic stability of optimal control systems with applications to the theory of economic growth. This monograph will be of value to mathematicians and economists.

Download or read book Stochastic Optimization Models in Finance written by W. T. Ziemba and published by Academic Press. This book was released on 2014-05-12 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Reengineering the University written by William F. Massy and published by JHU Press. This book was released on 2016-03-15 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: Higher education expert William F. Massy’s decades as a professor, senior university officer, and consultant have left him with a passionate belief in the need for reform in America’s traditional universities. In Reengineering the University, he addresses widespread concerns that higher education’s costs are too high, learning falls short of objectives, disruptive technology and education models are mounting serious challenges to traditional institutions, and administrators and faculty are too often unwilling or unable to change. An expert microeconomist, Massy approaches the challenge of reform in a genuinely new way by applying rigorous economic principles, informed by financial data and other evidence, to explain the forces at work on universities and the flaws in the academic business model. Ultimately, he argues that computer models that draw on data from college transaction systems can help both administrators and faculty address problems of educational performance and cost analysis, manage the complexity of planning and budgeting systems, and monitor the progress of reform in nonintrusive and constructive ways. Written for institutional leaders, faculty, board members, and policymakers who bear responsibility for initiating and carrying through on reform in traditional colleges and universities, Reengineering the University shows how, working together, administrators and faculty can improve education, research, and affordability by keeping a close eye on both academic values and the bottom line. "Massy's in-depth yet highly accessible analysis is a must-read for any academic leader."—Academic Leader "William Massy is a complex, deeply knowledgeable man: half hopeless romantic about the value and high purposes of higher education and half pragmatic engineer focused on costs, efficiency, and metrics. That combination proves to be just right for this wise and insightful book."—Michael S. McPherson, The Spencer Foundation "Reengineering the University spells out the efforts that William Massy has made throughout his extraordinary career to develop models to aid academic institutions in improving their cost efficiency and academic quality. Written in clear and concise form, academic administrators and faculty concerned about the future of their institutions should read it."—Ronald G. Ehrenberg, Cornell Higher Education Research Institute "This book is a game changer. It cogently deals with the problem of long-term sustainability of universities by addressing the core problems of quality in relation to cost and margin. Massy builds a strong case for his 'reengineering tools' which any university leader would find remarkably helpful in tackling critical issues of quality-conscious cost containment."—Paula Myrick Short, University of Houston "Reengineering the University is a tough love prescription for making the nation's colleges and universities more affordable by reengineering them to be more efficient. It is Bill Massy at his best."—Robert Zemsky, Founder of the Institute for Research on Higher Education at the University of Pennsylvania "Only Bill Massy could provide this perspective on an extraordinary moment in higher education, offering leaders a variety of adaptive tools and methods to engage this moment and strengthen the important work of creating sustainable futures for our universities."—John J. DeGioia, Georgetown University William F. Massy, a higher education consultant, is professor emeritus of education and business administration and a former vice president and vice provost at Stanford University. The author of Honoring the Trust: Quality and Cost Containment in Higher Education, he is the former president of the Jackson Hole Higher Education Group.

Download or read book Applied Intertemporal Optimization written by Klaus Wälde and published by Klaus Wälde. This book was released on 2012 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Models of a Man written by Mie Augier and published by MIT Press. This book was released on 2022-11-01 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essays that pay tribute to the wide-ranging influence of the late Herbert Simon, by friends and colleagues. Herbert Simon (1916-2001), in the course of a long and distinguished career in the social and behavioral sciences, made lasting contributions to many disciplines, including economics, psychology, computer science, and artificial intelligence. In 1978 he was awarded the Nobel Prize in economics for his research into the decision-making process within economic organizations. His well-known book The Sciences of the Artificial addresses the implications of the decision-making and problem-solving processes for the social sciences. This book (the title is a variation on the title of Simon's autobiography, Models of My Life) is a collection of short essays, all original, by colleagues from many fields who felt Simon's influence and mourn his loss. Mixing reminiscence and analysis, the book represents "a small acknowledgment of a large debt." Each of the more than forty contributors was asked to write about the one work by Simon that he or she had found most influential. The editors then grouped the essays into four sections: "Modeling Man," "Organizations and Administration," "Modeling Systems," and "Minds and Machines." The contributors include such prominent figures as Kenneth Arrow, William Baumol, William Cooper, Gerd Gigerenzer, Daniel Kahneman, David Klahr, Franco Modigliani, Paul Samuelson, and Vernon Smith. Although they consider topics as disparate as "Is Bounded Rationality Unboundedly Rational?" and "Personal Recollections from 15 Years of Monthly Meetings," each essay is a testament to the legacy of Herbert Simon—to see the unity rather than the divergences among disciplines.

Download or read book Optimal Decisions Under Uncertainty written by J.K. Sengupta and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the stochastic enviornment is as much important to the manager as to the economist. From production and marketing to financial management, a manager has to assess various costs imposed by uncertainty. The economist analyzes the role of incomplete and too often imperfect information structures on the optimal decisions made by a firm. The need for understanding the role of uncertainty in quantitative decision models, both in economics and management science provide the basic motivation of this monograph. The stochastic environment is analyzed here in terms of the following specific models of optimization: linear and quadratic models, linear programming, control theory and dynamic programming. Uncertainty is introduced here through the para meters, the constraints, and the objective function and its impact evaluated. Specifically recent developments in applied research are emphasized, so that they can help the decision-maker arrive at a solution which has some desirable charac teristics like robustness, stability and cautiousness. Mathematical treatment is kept at a fairly elementary level and applied as pects are emphasized much more than theory. Moreover, an attempt is made to in corporate the economic theory of uncertainty into the stochastic theory of opera tions research. Methods of optimal decision rules illustrated he re are applicable in three broad areas: (a) applied economic models in resource allocation and economic planning, (b) operations research models involving portfolio analysis and stochastic linear programming and (c) systems science models in stochastic control and adaptive behavior.