Stochastic Optimization Models In Finance 2006 Edition
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Stochastic Optimization Models In Finance
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Author : W. T. Ziemba
language : en
Publisher: Academic Press
Release Date : 2014-05-12
Stochastic Optimization Models In Finance written by W. T. Ziemba and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-12 with Business & Economics categories.
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 Optimization Models In Finance 2006 Edition
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Author : William T Ziemba
language : en
Publisher: World Scientific
Release Date : 2006-09-11
Stochastic Optimization Models In Finance 2006 Edition written by William T Ziemba and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-11 with Business & Economics categories.
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.
Optimization In Economics And Finance
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Author : Bruce D. Craven
language : en
Publisher: Springer
Release Date : 2011-01-05
Optimization In Economics And Finance written by Bruce D. Craven and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-05 with Business & Economics categories.
Some recent developments in the mathematics of optimization, including the concepts of invexity and quasimax, have not yet been applied to models of economic growth, and to finance and investment. Their applications to these areas are shown in this book.
Stochastic Optimization Methods In Finance And Energy
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Author : Marida Bertocchi
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-09-15
Stochastic Optimization Methods In Finance And Energy written by Marida Bertocchi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-15 with Business & Economics categories.
This volume presents a collection of contributions dedicated to applied problems in the financial and energy sectors that have been formulated and solved in a stochastic optimization framework. The invited authors represent a group of scientists and practitioners, who cooperated in recent years to facilitate the growing penetration of stochastic programming techniques in real-world applications, inducing a significant advance over a large spectrum of complex decision problems. After the recent widespread liberalization of the energy sector in Europe and the unprecedented growth of energy prices in international commodity markets, we have witnessed a significant convergence of strategic decision problems in the energy and financial sectors. This has often resulted in common open issues and has induced a remarkable effort by the industrial and scientific communities to facilitate the adoption of advanced analytical and decision tools. The main concerns of the financial community over the last decade have suddenly penetrated the energy sector inducing a remarkable scientific and practical effort to address previously unforeseeable management problems. Stochastic Optimization Methods in Finance and Energy: New Financial Products and Energy Markets Strategies aims to include in a unified framework for the first time an extensive set of contributions related to real-world applied problems in finance and energy, leading to a common methodological approach and in many cases having similar underlying economic and financial implications. Part 1 of the book presents 6 chapters related to financial applications; Part 2 presents 7 chapters on energy applications; and Part 3 presents 5 chapters devoted to specific theoretical and computational issues.
Reinforcement Learning And Stochastic Optimization
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Author : Warren B. Powell
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-15
Reinforcement Learning And Stochastic Optimization written by Warren B. Powell and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-15 with Mathematics categories.
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.
Stochastic Optimization In Continuous Time
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Author : Fwu-Ranq Chang
language : en
Publisher: Cambridge University Press
Release Date : 2004-04-26
Stochastic Optimization In Continuous Time written by Fwu-Ranq Chang and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-26 with Business & Economics categories.
First published in 2004, this is a rigorous but user-friendly book on the application of stochastic control theory to economics. A distinctive feature of the book is that mathematical concepts are introduced in a language and terminology familiar to graduate students of economics. The standard topics of many mathematics, economics and finance books are illustrated with real examples documented in the economic literature. Moreover, the book emphasises the dos and don'ts of stochastic calculus, cautioning the reader that certain results and intuitions cherished by many economists do not extend to stochastic models. A special chapter (Chapter 5) is devoted to exploring various methods of finding a closed-form representation of the value function of a stochastic control problem, which is essential for ascertaining the optimal policy functions. The book also includes many practice exercises for the reader. Notes and suggested readings are provided at the end of each chapter for more references and possible extensions.
Stochastic Programming
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Author : Horand Gassmann
language : en
Publisher: World Scientific
Release Date : 2013
Stochastic Programming written by Horand Gassmann and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Business & Economics categories.
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.
Numerical Methods In Finance And Economics
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Author : Paolo Brandimarte
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-06
Numerical Methods In Finance And Economics written by Paolo Brandimarte and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-06 with Mathematics categories.
A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance. Reflecting this development, Numerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition bridges the gap between financial theory and computational practice while showing readers how to utilize MATLAB?--the powerful numerical computing environment--for financial applications. The author provides an essential foundation in finance and numerical analysis in addition to background material for students from both engineering and economics perspectives. A wide range of topics is covered, including standard numerical analysis methods, Monte Carlo methods to simulate systems affected by significant uncertainty, and optimization methods to find an optimal set of decisions. Among this book's most outstanding features is the integration of MATLAB?, which helps students and practitioners solve relevant problems in finance, such as portfolio management and derivatives pricing. This tutorial is useful in connecting theory with practice in the application of classical numerical methods and advanced methods, while illustrating underlying algorithmic concepts in concrete terms. Newly featured in the Second Edition: * In-depth treatment of Monte Carlo methods with due attention paid to variance reduction strategies * New appendix on AMPL in order to better illustrate the optimization models in Chapters 11 and 12 * New chapter on binomial and trinomial lattices * Additional treatment of partial differential equations with two space dimensions * Expanded treatment within the chapter on financial theory to provide a more thorough background for engineers not familiar with finance * New coverage of advanced optimization methods and applications later in the text Numerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition presents basic treatments and more specialized literature, and it also uses algebraic languages, such as AMPL, to connect the pencil-and-paper statement of an optimization model with its solution by a software library. Offering computational practice in both financial engineering and economics fields, this book equips practitioners with the necessary techniques to measure and manage risk.
The Harriman House Book Of Investing Rules
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Author : Philip Jenks
language : en
Publisher: Harriman House Limited
Release Date : 2008
The Harriman House Book Of Investing Rules written by Philip Jenks and has been published by Harriman House Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Business & Economics categories.
For the first time, the tactics, strategies and insightsrelied on by 150 of the world's most respected financialexperts are revealed in a concise, digestible form. Learnhow you really make money in the markets from: fundmanagers of billion-pound equity funds; traders in theoptions and futures markets; industry-rated analysts;economists ......
Problems In Portfolio Theory And The Fundamentals Of Financial Decision Making
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Author : Leonard C Maclean
language : en
Publisher: World Scientific Publishing Company
Release Date : 2016-09-29
Problems In Portfolio Theory And The Fundamentals Of Financial Decision Making written by Leonard C Maclean and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-29 with Business & Economics categories.
This book consists of invaluable introductions, tutorials and problems which are helpful for teaching purposes and have a very broad appeal and usage. The problems cover many aspects of static and dynamic portfolio theory as well as other important subjects such as arbitrage and asset pricing, utility theory, stochastic dominance, risk aversion and static portfolio theory, risk measures, dynamic portfolio theory and asset allocation. This material could be used with important books that cover these topics including MacLean-Ziemba's The Handbook of the Fundamentals of Financial Decision Making, and Ziemba-Vickson's Stochastic Optimization Models in Finance.