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Optimisation Econometric And Financial Analysis
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Author :Erricos Kontoghiorghes Publisher :Springer Science & Business Media ISBN 13 :3540366261 Total Pages :275 pages Book Rating :4.5/5 (43 download)
Book Synopsis Optimisation, Econometric and Financial Analysis by : Erricos Kontoghiorghes
Download or read book Optimisation, Econometric and Financial Analysis written by Erricos Kontoghiorghes and published by Springer Science & Business Media. This book was released on 2007-05-17 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses issues associated with the interface of computing, optimisation, econometrics and financial modeling, emphasizing computational optimisation methods and techniques. The first part addresses optimisation problems and decision modeling, plus applications of supply chain and worst-case modeling and advances in methodological aspects of optimisation techniques. The second part covers optimisation heuristics, filtering, signal extraction and time series models. The final part discusses optimisation in portfolio selection and real option modeling.
Book Synopsis Optimisation, Econometric and Financial Analysis by : Erricos Kontoghiorghes
Download or read book Optimisation, Econometric and Financial Analysis written by Erricos Kontoghiorghes and published by Springer. This book was released on 2009-09-02 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses issues associated with the interface of computing, optimisation, econometrics and financial modeling, emphasizing computational optimisation methods and techniques. The first part addresses optimisation problems and decision modeling, plus applications of supply chain and worst-case modeling and advances in methodological aspects of optimisation techniques. The second part covers optimisation heuristics, filtering, signal extraction and time series models. The final part discusses optimisation in portfolio selection and real option modeling.
Book Synopsis Numerical Methods and Optimization in Finance by : Manfred Gilli
Download or read book Numerical Methods and Optimization in Finance written by Manfred Gilli and published by Academic Press. This book was released on 2019-08-30 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems-ranging from asset allocation to risk management and from option pricing to model calibration-can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically. This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance. Introduces numerical methods to readers with economics backgrounds Emphasizes core simulation and optimization problems Includes MATLAB and R code for all applications, with sample code in the text and freely available for download
Book Synopsis Optimization in Economics and Finance by : Bruce D. Craven
Download or read book Optimization in Economics and Finance written by Bruce D. Craven and published by Springer Science & Business Media. This book was released on 2005 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Numerical Methods and Optimization in Finance by : Manfred Gilli
Download or read book Numerical Methods and Optimization in Finance written by Manfred Gilli and published by Academic Press. This book was released on 2019-08-16 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems—ranging from asset allocation to risk management and from option pricing to model calibration—can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically. This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance. Introduces numerical methods to readers with economics backgrounds Emphasizes core simulation and optimization problems Includes MATLAB and R code for all applications, with sample code in the text and freely available for download
Book Synopsis Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) by : Cheng Few Lee
Download or read book Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) written by Cheng Few Lee and published by World Scientific. This book was released on 2020-07-30 with total page 5053 pages. Available in PDF, EPUB and Kindle. Book excerpt: This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.
Book Synopsis Financial Econometrics by : Svetlozar T. Rachev
Download or read book Financial Econometrics written by Svetlozar T. Rachev and published by John Wiley & Sons. This book was released on 2007-03-22 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to financial econometrics Financial econometrics is a quest for models that describe financial time series such as prices, returns, interest rates, and exchange rates. In Financial Econometrics, readers will be introduced to this growing discipline and the concepts and theories associated with it, including background material on probability theory and statistics. The experienced author team uses real-world data where possible and brings in the results of published research provided by investment banking firms and journals. Financial Econometrics clearly explains the techniques presented and provides illustrative examples for the topics discussed. Svetlozar T. Rachev, PhD (Karlsruhe, Germany) is currently Chair-Professor at the University of Karlsruhe. Stefan Mittnik, PhD (Munich, Germany) is Professor of Financial Econometrics at the University of Munich. Frank J. Fabozzi, PhD, CFA, CFP (New Hope, PA) is an adjunct professor of Finance at Yale University’s School of Management. Sergio M. Focardi (Paris, France) is a founding partner of the Paris-based consulting firm The Intertek Group. Teo Jasic, PhD, (Frankfurt, Germany) is a senior manager with a leading international management consultancy firm in Frankfurt.
Book Synopsis Optimization Methods in Finance by : Gérard Cornuéjols
Download or read book Optimization Methods in Finance written by Gérard Cornuéjols and published by Cambridge University Press. This book was released on 2018-08-09 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Full treatment, from model formulation to computational implementation, of optimization techniques that solve central problems in finance.
Book Synopsis Stochastic Optimization Models in Finance by : W. T. Ziemba
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.
Book Synopsis Optimizing Optimization by : Stephen Satchell
Download or read book Optimizing Optimization written by Stephen Satchell and published by Academic Press. This book was released on 2009-09-19 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: The practical aspects of optimization rarely receive global, balanced examinations. Stephen Satchell’s nuanced assembly of technical presentations about optimization packages (by their developers) and about current optimization practice and theory (by academic researchers) makes available highly practical solutions to our post-liquidity bubble environment. The commercial chapters emphasize algorithmic elements without becoming sales pitches, and the academic chapters create context and explore development opportunities. Together they offer an incisive perspective that stretches toward new products, new techniques, and new answers in quantitative finance. Presents a unique "confrontation" between software engineers and academics Highlights a global view of common optimization issues Emphasizes the research and market challenges of optimization software while avoiding sales pitches Accentuates real applications, not laboratory results
Book Synopsis Handbook of Computational Econometrics by : David A. Belsley
Download or read book Handbook of Computational Econometrics written by David A. Belsley and published by John Wiley & Sons. This book was released on 2009-08-18 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation. Each topic is fully introduced before proceeding to a more in-depth examination of the relevant methodologies and valuable illustrations. This book: Provides self-contained treatments of issues in computational econometrics with illustrations and invaluable bibliographies. Brings together contributions from leading researchers. Develops the techniques needed to carry out computational econometrics. Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation. This book will appeal to econometricians, financial statisticians, econometric researchers and students of econometrics at both graduate and advanced undergraduate levels.
Book Synopsis Optimization Methods for Gas and Power Markets by : Enrico Edoli
Download or read book Optimization Methods for Gas and Power Markets written by Enrico Edoli and published by Springer. This book was released on 2016-04-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: As power and gas markets are becoming more and more mature and globally competitive, the importance of reaching maximum potential economic efficiency is fundamental in all the sectors of the value chain, from investments selection to asset optimization, trading and sales. Optimization techniques can be used in many different fields of the energy industry, in order to reduce production and financial costs, increase sales revenues and mitigate all kinds of risks potentially affecting the economic margin. For this reason the industry has now focused its attention on the general concept of optimization and to the different techniques (mainly mathematical techniques) to reach it. Optimization Methods for Gas and Power Markets presents both theoretical elements and practical examples for solving energy optimization issues in gas and power markets. Starting with the theoretical framework and the basic business and economics of power and gas optimization, it quickly moves on to review the mathematical optimization problems inherent to the industry, and their solutions – all supported with examples from the energy sector. Coverage ranges from very long-term (and capital intensive) optimization problems such as investment valuation/diversification to asset (gas and power) optimization/hedging problems, and pure trading decisions. This book first presents the readers with various examples of optimization problems arising in power and gas markets, then deals with general optimization problems and describes the mathematical tools useful for their solution. The remainder of the book is dedicated to presenting a number of key business cases which apply the proposed techniques to concrete market problems. Topics include static asset optimization, real option evaluation, dynamic optimization of structured products like swing, virtual storage or virtual power plant contracts and optimal trading in intra-day power markets. As the book progresses, so too does the level of mathematical complexity, providing readers with an appreciation of the growing sophistication of even common problems in current market practice. Optimization Methods for Gas and Power Markets provides a valuable quantitative guide to the technicalities of optimization methodologies in gas and power markets; it is essential reading for practitioners in the energy industry and financial sector who work in trading, quantitative analysis and energy risk modeling.
Book Synopsis Optimisation in Economic Analysis by : Gordon Mills
Download or read book Optimisation in Economic Analysis written by Gordon Mills and published by Psychology Press. This book was released on 2003 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the fundamental economic problems is one of making the best use of limited resources. As a result, mathematical optimisation methods play a crucial role in economic theory. Covering the use of such methods in applied and policy contexts, this book deals not only with the main techniques (linear programming, nonlinear optimisation and dynamic programming), but also emphasizes the art of model-building and discusses fields such as optimisation over time.
Book Synopsis Elements of Optimization by : Delia Koo
Download or read book Elements of Optimization written by Delia Koo and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book attempts to present the concepts which underlie the various optimization procedures which are commonly used. It is written primarily for those scientists such as economists, operations researchers, and en gineers whose main tools of analysis involve optimization techniques and who possess a (not very sharp) knowledge of one or one-and-a-half year's calculus through partial differentiation and Taylor's theorem and some acquaintance with elementary vector and matrix terminology. Such a scientist is frequently confronted with expressions such as Lagrange multi pliers, first-and second-order conditions, linear programming and activity analysis, duality, the Kuhn-Tucker conditions, and, more recently, dy namic programming and optimal control. He or she uses or needs to use these optimization techniques, and would like to feel more comfortable with them through better understanding of their underlying mathematical concepts, but has no immediate use for a formal theorem-proof treatment which quickly abstracts to a general case of n variables and uses a style and terminology that are discouraging to people who are not mathematics majors. The emphasis of this book is on clarity and plausibility. Through examples which are worked out step by step in detail, I hope to illustrate some tools which will be useful to scientists when they apply optimization techniques to their problems. Most of the chapters may be read independently of each other-with the exception of Chapter 6, which depends on Chapter 5. For instance, the reader will find little or no difficulty in reading Chapter 8 without having read the previous chapters.
Book Synopsis Elements of Nonlinear Time Series Analysis and Forecasting by : Jan G. De Gooijer
Download or read book Elements of Nonlinear Time Series Analysis and Forecasting written by Jan G. De Gooijer and published by Springer. This book was released on 2017-03-30 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible, major supporting concepts and specialized tables are appended at the end of every chapter. In addition, each chapter concludes with a set of key terms and concepts, as well as a summary of the main findings. Lastly, the book offers numerous theoretical and empirical exercises, with answers provided by the author in an extensive solutions manual.
Book Synopsis Optimization in Economics and Finance by : Bruce Desmond Craven
Download or read book Optimization in Economics and Finance written by Bruce Desmond Craven and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Many optimization questions arise in economics and finance; an important example of this is the society's choice of the optimum state of the economy (the social choice problem). This book the usual optimization techniques, in a form that may be adopted for modeling social choice problems. Problems discussed include: when is an optimum reached; when is it unique; relaxation of the conventional convex (or concave) assumptions on an economic model; associated mathematical concepts such as invex and quasimax; multiobjective optimal control models; and related computational methods and programs. These techniques are applied to economic growth models (including small stochastic perturbations), finance and financial investment models (and the interaction between financial and production variables), modeling sustainability over long time horizons, boundary (transversality) conditions, and models with several conflicting objectives. Although the applications are general and illustrative, the models in this book provide examples of possible models for a society's social choice for an allocation that maximizes welfare and utilization of resources. As well as using existing computer programs for optimization of models, a new computer program, named SCOM, is presented in this book for computing social choice models by optimal control.
Book Synopsis Bayesian Hierarchical Models by : Peter D. Congdon
Download or read book Bayesian Hierarchical Models written by Peter D. Congdon and published by CRC Press. This book was released on 2019-09-16 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples. The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling Includes many real data examples to illustrate different modelling topics R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation Software options and coding principles are introduced in new chapter on computing Programs and data sets available on the book’s website
