Download Practical Financial Optimization eBook. PDF book with title Practical Financial Optimization suitable to read on your Kindle device, PC, phones or tablets. Available in PDF, EPUB, and Mobi Format.

Practical Financial Optimization

Practical Financial Optimization Author : Soren S Nielson
Release : 2010-02-05
Publisher : John Wiley & Sons
ISBN : 1444317237
File Size : 77.36 MB
Format : PDF, Mobi
Download : 775
Read : 1191

In Practical Financial Optimization: A Library of GAMS Models, the authors provide a diverse set of models for portfolio optimization, based on the General Algebraic Modelling System. ‘GAMS’ consists of a language which allows a high-level, algebraic representation of mathematical models and a set of solvers – numerical algorithms – to solve them. The system was developed in response to the need for powerful and flexible front-end tools to manage large, real-life models. The work begins with an overview of the structure of the GAMS language, and discusses issues relating to the management of data in GAMS models. The authors provide models for mean-variance portfolio optimization which address the question of trading off the portfolio expected return against its risk. Fixed income portfolio optimization models perform standard calculations and allow the user to bootstrap a yield curve from bond prices. Dedication models allow for standard portfolio dedication with borrowing and re-investment decisions, and are extended to deal with maximisation of horizon return and to incorporate various practical considerations on the portfolio tradeability. Immunization models provide for the factor immunization of portfolios of treasury and corporate bonds. The scenario-based portfolio optimization problem is addressed with mean absolute deviation models, tracking models, regret models, conditional VaR models, expected utility maximization models and put/call efficient frontier models. The authors employ stochastic programming for dynamic portfolio optimization, developing stochastic dedication models as stochastic extensions of the fixed income models discussed in chapter 4. Two-stage and multi-stage stochastic programs extend the scenario models analysed in Chapter 5 to allow dynamic rebalancing of portfolios as time evolves and new information becomes known. Models for structuring index funds and hedging interest rate risk on international portfolios are also provided. The final chapter provides a set of ‘case studies’: models for large-scale applications of portfolio optimization, which can be used as the basis for the development of business support systems to suit any special requirements, including models for the management of participating insurance policies and personal asset allocation. The title will be a valuable guide for quantitative developers and analysts, portfolio and asset managers, investment strategists and advanced students of finance.

Practical Financial Optimization

Practical Financial Optimization Author : Soren S Nielson
Release : 2010-02-01
Publisher : Wiley-Blackwell
ISBN : 9781405133715
File Size : 82.93 MB
Format : PDF, Kindle
Download : 885
Read : 347

In Practical Financial Optimization: A Library of GAMS Models, the authors provide a diverse set of models for portfolio optimization, based on the General Algebraic Modelling System. ‘GAMS’ consists of a language which allows a high-level, algebraic representation of mathematical models and a set of solvers – numerical algorithms – to solve them. The system was developed in response to the need for powerful and flexible front-end tools to manage large, real-life models. The work begins with an overview of the structure of the GAMS language, and discusses issues relating to the management of data in GAMS models. The authors provide models for mean-variance portfolio optimization which address the question of trading off the portfolio expected return against its risk. Fixed income portfolio optimization models perform standard calculations and allow the user to bootstrap a yield curve from bond prices. Dedication models allow for standard portfolio dedication with borrowing and re-investment decisions, and are extended to deal with maximisation of horizon return and to incorporate various practical considerations on the portfolio tradeability. Immunization models provide for the factor immunization of portfolios of treasury and corporate bonds. The scenario-based portfolio optimization problem is addressed with mean absolute deviation models, tracking models, regret models, conditional VaR models, expected utility maximization models and put/call efficient frontier models. The authors employ stochastic programming for dynamic portfolio optimization, developing stochastic dedication models as stochastic extensions of the fixed income models discussed in chapter 4. Two-stage and multi-stage stochastic programs extend the scenario models analysed in Chapter 5 to allow dynamic rebalancing of portfolios as time evolves and new information becomes known. Models for structuring index funds and hedging interest rate risk on international portfolios are also provided. The final chapter provides a set of ‘case studies’: models for large-scale applications of portfolio optimization, which can be used as the basis for the development of business support systems to suit any special requirements, including models for the management of participating insurance policies and personal asset allocation. The title will be a valuable guide for quantitative developers and analysts, portfolio and asset managers, investment strategists and advanced students of finance.

Practical Financial Optimization

Practical Financial Optimization Author : Stavros A. Zenios
Release : 2008-05-19
Publisher : Wiley-Blackwell
ISBN : 9781405132015
File Size : 31.67 MB
Format : PDF, ePub, Docs
Download : 470
Read : 1301

Practical Financial Optimization is a comprehensive guide to optimization techniques in financial decision making. This book illuminates the relationship between theory and practice, providing the readers with solid foundational knowledge. Focuses on classical static mean-variance analysis and portfolio immunization, scenario-based models, multi-period dynamic portfolio optimization, and the relationships between classes of models Analyizes real world applications and implications for financial engineers Includes a list of models and a section on notations that includes a glossary of symbols and abbreviations

Financial Optimization

Financial Optimization Author : Stavros A. Zenios
Release : 1996-10-28
Publisher : Cambridge University Press
ISBN : 9780521577779
File Size : 59.64 MB
Format : PDF, Mobi
Download : 703
Read : 1171

This book clearly presents the exciting symbiosis between the fields of finance and management science and operations research.

Simulation and Optimization in Finance

Simulation and Optimization in Finance Author : Dessislava A. Pachamanova
Release : 2010-09-23
Publisher : John Wiley & Sons
ISBN : 9780470882122
File Size : 30.73 MB
Format : PDF
Download : 281
Read : 387

An introduction to the theory and practice of financial simulation and optimization In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty. This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications. Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB) Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.

Nonlinear Optimization with Financial Applications

Nonlinear Optimization with Financial Applications Author : Michael Bartholomew-Biggs
Release : 2006-07-21
Publisher : Springer Science & Business Media
ISBN : 0387241493
File Size : 27.14 MB
Format : PDF
Download : 616
Read : 520

This instructive book introduces the key ideas behind practical nonlinear optimization, accompanied by computational examples and supporting software. It combines computational finance with an important class of numerical techniques.

Practical C++ Financial Programming

Practical C++ Financial Programming Author : Carlos Oliveira
Release : 2015-03-12
Publisher : Apress
ISBN : 143026716X
File Size : 30.78 MB
Format : PDF
Download : 690
Read : 160

Practical C++ Financial Programming is a hands-on book for programmers wanting to apply C++ to programming problems in the financial industry. The book explains those aspects of the language that are more frequently used in writing financial software, including the STL, templates, and various numerical libraries. The book also describes many of the important problems in financial engineering that are part of the day-to-day work of financial programmers in large investment banks and hedge funds. The author has extensive experience in the New York City financial industry that is now distilled into this handy guide. Focus is on providing working solutions for common programming problems. Examples are plentiful and provide value in the form of ready-to-use solutions that you can immediately apply in your day-to-day work. You’ll learn to design efficient, numerical classes for use in finance, as well as to use those classes provided by Boost and other libraries. You’ll see examples of matrix manipulations, curve fitting, histogram generation, numerical integration, and differential equation analysis, and you’ll learn how all these techniques can be applied to some of the most common areas of financial software development. These areas include performance price forecasting, optimizing investment portfolios, and more. The book style is quick and to-the-point, delivering a refreshing view of what one needs to master in order to thrive as a C++ programmer in the financial industry. Covers aspects of C++ especially relevant to financial programming. Provides working solutions to commonly-encountered problems in finance. Delivers in a refreshing and easy style with a strong focus on the practical.

Mathematical Methods for Finance

Mathematical Methods for Finance Author : Sergio M. Focardi
Release : 2013-09-04
Publisher : John Wiley & Sons
ISBN : 1118421493
File Size : 47.63 MB
Format : PDF, Kindle
Download : 475
Read : 808

The mathematical and statistical tools needed in the rapidlygrowing quantitative finance field With the rapid growth in quantitative finance, practitionersmust achieve a high level of proficiency in math and statistics.Mathematical Methods and Statistical Tools for Finance, partof the Frank J. Fabozzi Series, has been created with this in mind.Designed to provide the tools needed to apply finance theory toreal world financial markets, this book offers a wealth of insightsand guidance in practical applications. It contains applications that are broader in scope from what iscovered in a typical book on mathematical techniques. Most booksfocus almost exclusively on derivatives pricing, the applicationsin this book cover not only derivatives and asset pricing but alsorisk management—including credit risk management—andportfolio management. Includes an overview of the essential math and statisticalskills required to succeed in quantitative finance Offers the basic mathematical concepts that apply to the fieldof quantitative finance, from sets and distances to functions andvariables The book also includes information on calculus, matrix algebra,differential equations, stochastic integrals, and much more Written by Sergio Focardi, one of the world's leading authorsin high-level finance Drawing on the author's perspectives as a practitioner andacademic, each chapter of this book offers a solid foundation inthe mathematical tools and techniques need to succeed in today'sdynamic world of finance.

Stochastic Optimization Models in Finance

Stochastic Optimization Models in Finance Author : W. T. Ziemba
Release : 2006
Publisher : World Scientific
ISBN : 9812773657
File Size : 74.6 MB
Format : PDF
Download : 320
Read : 191

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. Sample Chapter(s). Chapter 1: Expected Utility Theory (373 KB). Contents: Mathematical Tools: Expected Utility Theory; Convexity and the Kuhn-Tucker Conditions; Dynamic Programming; Qualitative Economic Results: Stochastic Dominance; Measures of Risk Aversion; Separation Theorems; Static Portfolio Selection Models: Mean-Variance and Safety First Approaches and Their Extensions; Existence and Diversification of Optimal Portfolio Policies: Effects of Taxes on Risk Taking; Dynamic Models Reducible to Static Models: Models That Have a Single Decision Point; Risk Aversion over Time Implies Static Risk Aversion; Myopic Portfolio Policies; Dynamic Models: Two-Period Consumption Models and Portfolio Revision; Models of Optimal Capital Accumulation and Portfolio Selection; Models of Option Strategy; The Capital Growth Criterion and Continuous-Time Models. Readership: Postdoctoral and graduate students, researchers, academics, and professionals interested in portfolio theory and stochastic optimization.

Efficient Asset Management

Efficient Asset Management Author : Richard O. Michaud
Release : 1998
Publisher : Oxford University Press
ISBN :
File Size : 74.24 MB
Format : PDF, Docs
Download : 785
Read : 1177

Presents new approaches to defining optimal portfolios and details techniques that managers can use to enhance the value of optimized portfolios

Financial Optimization

Financial Optimization Author : Hercules Vladimirou
Release : 2007
Publisher :
ISBN :
File Size : 34.49 MB
Format : PDF, Mobi
Download : 147
Read : 740

Stochastic Optimization Methods in Finance and Energy

Stochastic Optimization Methods in Finance and Energy Author : Marida Bertocchi
Release : 2011-09-15
Publisher : Springer Science & Business Media
ISBN : 9781441995865
File Size : 84.87 MB
Format : PDF, Mobi
Download : 328
Read : 394

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.

Fuzzy Portfolio Optimization

Fuzzy Portfolio Optimization Author : Pankaj Gupta
Release : 2014-03-17
Publisher : Springer
ISBN : 3642546528
File Size : 24.64 MB
Format : PDF, Kindle
Download : 181
Read : 571

This monograph presents a comprehensive study of portfolio optimization, an important area of quantitative finance. Considering that the information available in financial markets is incomplete and that the markets are affected by vagueness and ambiguity, the monograph deals with fuzzy portfolio optimization models. At first, the book makes the reader familiar with basic concepts, including the classical mean–variance portfolio analysis. Then, it introduces advanced optimization techniques and applies them for the development of various multi-criteria portfolio optimization models in an uncertain environment. The models are developed considering both the financial and non-financial criteria of investment decision making, and the inputs from the investment experts. The utility of these models in practice is then demonstrated using numerical illustrations based on real-world data, which were collected from one of the premier stock exchanges in India. The book addresses both academics and professionals pursuing advanced research and/or engaged in practical issues in the rapidly evolving field of portfolio optimization.

Numerical Methods and Optimization in Finance

Numerical Methods and Optimization in Finance Author : Manfred Gilli
Release : 2011-06-30
Publisher : Academic Press
ISBN : 0123756634
File Size : 56.9 MB
Format : PDF, ePub
Download : 392
Read : 1321

This book describes computational finance tools. It covers fundamental numerical analysis and computational techniques, such as option pricing, and gives special attention to simulation and optimization. Many chapters are organized as case studies around portfolio insurance and risk estimation problems. In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website. Shows ways to build and implement tools that help test ideas Focuses on the application of heuristics; standard methods receive limited attention Presents as separate chapters problems from portfolio optimization, estimation of econometric models, and calibration of option pricing models

Natural Computing in Computational Finance

Natural Computing in Computational Finance Author : Anthony Brabazon
Release : 2008-05-09
Publisher : Springer Science & Business Media
ISBN : 3540774769
File Size : 26.46 MB
Format : PDF, ePub
Download : 617
Read : 1074

Natural Computing in Computational Finance is a innovative volume containing fifteen chapters which illustrate cutting-edge applications of natural computing or agent-based modeling in modern computational finance. Following an introductory chapter the book is organized into three sections. The first section deals with optimization applications of natural computing demonstrating the application of a broad range of algorithms including, genetic algorithms, differential evolution, evolution strategies, quantum-inspired evolutionary algorithms and bacterial foraging algorithms to multiple financial applications including portfolio optimization, fund allocation and asset pricing. The second section explores the use of natural computing methodologies such as genetic programming, neural network hybrids and fuzzy-evolutionary hybrids for model induction in order to construct market trading, credit scoring and market prediction systems. The final section illustrates a range of agent-based applications including the modeling of payment card and financial markets. Each chapter provides an introduction to the relevant natural computing methodology as well as providing a clear description of the financial application addressed. The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, in the fields of both natural computing and finance.

Investment Risk Management

Investment Risk Management Author : H. Kent Baker
Release : 2014-12-03
Publisher : Oxford University Press
ISBN : 0190214082
File Size : 21.65 MB
Format : PDF
Download : 774
Read : 373

All investments carry with them some degree of risk. In the financial world, individuals, professional money managers, financial institutions, and many others encounter and must deal with risk. Risk management is a process of determining what risks exist in an investment and then handling those risks in the best-suited way. This is important because it can reduce or augment risk depending on the goals of investors and portfolio managers. The main purpose of Investment Risk Management is to provide an overview of developments in risk management and a synthesis of research involving these developments. The book examines ways to alter exposures through measuring and managing those exposures and provides an understanding of the latest strategies and trends within risk management. The scope of the coverage is broad and encompasses the most important aspects of investment risk management. Its 30 chapters are organized into six sections: (1) foundations of risk management, (2) types of risk, (3) quantitative assessment of risk, (4) risk and risk classes, (5) hedging risk and (6) going forward. The book should be of particular interest to sophisticated practitioners, investors, academics, and graduate finance students. Investment Risk Management provides a fresh look at this intriguing but complex subject.

Practical Energy Efficiency Optimization

Practical Energy Efficiency Optimization Author : G. G. Rajan
Release : 2006
Publisher : PennWell Books
ISBN : 9781593700515
File Size : 79.95 MB
Format : PDF
Download : 666
Read : 1047

Keeping a power plant running at optimal efficiency makes a significant contribution to a company's bottom line. That means power plant and energy managers at industrial facilities face the difficult tasks of consistently generating power at minimal cost. And with energy costs consuming up to 65% of heavy industry budgets, maintaining efficiency has never been more critical. Practical Energy Efficiency Optimization presents basic information for optimizing power plants. Whether at a major utility, or at an industrial facility, these formulas are proven to increase power plant efficiency. Review exercises and practical case studies provide real-world applications on maintaining optimal efficiency.

Practical Applications of Evolutionary Computation to Financial Engineering

Practical Applications of Evolutionary Computation to Financial Engineering Author : Hitoshi Iba
Release : 2012-02-15
Publisher : Springer Science & Business Media
ISBN : 3642276482
File Size : 28.40 MB
Format : PDF, Kindle
Download : 838
Read : 218

“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.

Market Risk Analysis, Practical Financial Econometrics

Market Risk Analysis, Practical Financial Econometrics Author : Carol Alexander
Release : 2008-04-30
Publisher : John Wiley & Sons
ISBN : 0470771038
File Size : 45.24 MB
Format : PDF, Docs
Download : 780
Read : 367

Written by leading market risk academic, Professor Carol Alexander, Practical Financial Econometrics forms part two of the Market Risk Analysis four volume set. It introduces the econometric techniques that are commonly applied to finance with a critical and selective exposition, emphasising the areas of econometrics, such as GARCH, cointegration and copulas that are required for resolving problems in market risk analysis. The book covers material for a one-semester graduate course in applied financial econometrics in a very pedagogical fashion as each time a concept is introduced an empirical example is given, and whenever possible this is illustrated with an Excel spreadsheet. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD-ROM . Empirical examples and case studies specific to this volume include: Factor analysis with orthogonal regressions and using principal component factors; Estimation of symmetric and asymmetric, normal and Student t GARCH and E-GARCH parameters; Normal, Student t, Gumbel, Clayton, normal mixture copula densities, and simulations from these copulas with application to VaR and portfolio optimization; Principal component analysis of yield curves with applications to portfolio immunization and asset/liability management; Simulation of normal mixture and Markov switching GARCH returns; Cointegration based index tracking and pairs trading, with error correction and impulse response modelling; Markov switching regression models (Eviews code); GARCH term structure forecasting with volatility targeting; Non-linear quantile regressions with applications to hedging.

Portfolio Optimization

Portfolio Optimization Author : Michael J. Best
Release : 2010-03-09
Publisher : CRC Press
ISBN : 1420085840
File Size : 59.75 MB
Format : PDF, Docs
Download : 946
Read : 683

Eschewing a more theoretical approach, Portfolio Optimization shows how the mathematical tools of linear algebra and optimization can quickly and clearly formulate important ideas on the subject. This practical book extends the concepts of the Markowitz "budget constraint only" model to a linearly constrained model. Only requiring elementary linear algebra, the text begins with the necessary and sufficient conditions for optimal quadratic minimization that is subject to linear equality constraints. It then develops the key properties of the efficient frontier, extends the results to problems with a risk-free asset, and presents Sharpe ratios and implied risk-free rates. After focusing on quadratic programming, the author discusses a constrained portfolio optimization problem and uses an algorithm to determine the entire (constrained) efficient frontier, its corner portfolios, the piecewise linear expected returns, and the piecewise quadratic variances. The final chapter illustrates infinitely many implied risk returns for certain market portfolios. Drawing on the author’s experiences in the academic world and as a consultant to many financial institutions, this text provides a hands-on foundation in portfolio optimization. Although the author clearly describes how to implement each technique by hand, he includes several MATLAB® programs designed to implement the methods and offers these programs on the accompanying CD-ROM.