Book Description
This is the first comprehensive introduction to the concepts, theories, and applications of pricing and revenue optimization. From the initial success of “yield management” in the commercial airline industry down to more recent successes of markdown management and dynamic pricing, the application of mathematical analysis to optimize pricing has become increasingly important across many different industries. But, since pricing and revenue optimization has involved the use of sophisticated mathematical techniques, the topic has remained largely inaccessible to students and the typical manager.
With methods proven in the MBA courses taught by the author at Columbia and Stanford Business Schools, this book presents the basic concepts of pricing and revenue optimization in a form accessible to MBA students, MS students, and advanced undergraduates. In addition, managers will find the practical approach to the issue of pricing and revene optimization invaluable.
Customer Reviews:
Basic tool for RM.......2007-06-11
One of the best tool I have read about RM, with a great organization of each topic.
Pricing and Revenue Optimization.......2006-03-11
This is an excellent book and should be in every pricing professionals library. The only critisism I could make is that the author should be very explicit with the examples and walk the reader through the techniques used in detail.
Pricing and Revenue Optimization.......2005-08-23
Pricing and Revenue Optimization fills the need for a rigorous yet accessible introduction to the field more commonly known as revenue management. The author presents key pricing decisions such as airline revenue management, markdown management, and customized pricing as constrained optimization problems. It is the only broadly accessible consistent treatment of these topics in one place. The intended audience is MBA and MS level students and managers with solid quantitative backgrounds. Linear programming, probabilistic modeling, and some calculus is used. This book neatly fills the space between the popular treatment in Cross's "Revenue Management" and the much more mathematical "Theory and Practice of Revenue Management" by Talluri and van Ryzin. The book is well written and presents plenty of real-world grounding as well as the necessary mathematics. It is written as a textbook but would also serve for any quantitatively-oriented analyst or manager wanting to know how math models can be used to improve pricing. As a textbook, it is a little short of problems and I would have liked to see chapters on forecasting and price-response estimation. It is the best available introduction to this important topic for the MBA-level student or practitioner.
Book Description
This completely revised and updated edition of
Applied Risk Analysis includes new case studies in modeling risk and uncertainty as well as a new risk analysis CD-ROM prepared by Dr. Mun. On the CD-ROM you'll find his Risk Simulator and Real Options Super Lattice Solver software as well as many useful spreadsheet models.
"Johnathan Mun's book is a sparkling jewel in my finance library. Mun demonstrates a deep understanding of the underlying mathematical theory in his ability to reduce complex concepts to lucid explanations and applications. For this reason, he's my favorite writer in this field."
—Janet Tavakoli, President, Tavakoli Structured Finance, Inc. and author of Collateralized Debt Obligations and Structured Finance
"A must-read for product portfolio managers . . . it captures the risk exposure of strategic investments, and provides management with estimates of potential outcomes and options for risk mitigation."
—Rafael E. Gutierrez, Executive Director of Strategic Marketing and Planning, Seagate Technology, Inc.
"Once again, Dr. Mun has created a 'must-have, must-read' book for anyone interested in the practical application of risk analysis. Other books speak in academic generalities, or focus on one area of risk application. [This book] gets to the heart of the matter with applications for every area of risk analysis. You have a real option to buy almost any book?you should exercise your option and get this one!"
—Glenn Kautt, MBA, CFP, EA, President and Chairman, The Monitor Group, Inc.
Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Customer Reviews:
A 600-Page Advertisement.......2007-04-26
I found the discussion on nonparametric simulation, though brief, to be very helpful. The book also inspired me to use Excel's Solver in ways I had not considered before.
Beyond that, I was disappointed. The book is poorly edited and lacks a coherent structure. Once in a while, entire strings of paragraphs are repeated in two different parts of the book. More serious, however, is the fact that the book is largely an advertisement for the author's proprietary software.
If you are looking for a few techniques that you can apply in an Excel environment, you will find a few nuggets here and there. However, you will mostly be skimming through the 600 pages of rambling discussion.
Applying Monte Carlo Simulation.......2007-03-30
In the first few chapters the author is certainly successful in making the argument why one should use simulation rather than point estimates. However, the case studies are somewhat vague because the author presents the problem and discusses results of the simulation (using the Risk Simulator S/W) but leaves you wondering how he setup up the model to run this simulation and come up with the results(not even available in the excel examples on the CD). Clear examples of this case include the example on pages 75, 76 & the "Financial Planning" example on page 219.
As an IT Project manager, I didn't find it very helpul in addressing my problems and I wouldn't recommend it for people who want to learn about simulation without going too technical
Book Description
Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems.
For this new edition the book has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field. The authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side.
There is a selected solutions manual for instructors for the new edition.
Customer Reviews:
good quality.......2007-09-27
It is a very important book to me, so I was very glad when I received a really brand new one.
outstanding.......2007-05-15
This book is a well-written, outstanding reference for anyone interested in understanding, using, and/or implementing state-of-the-art techniques in nonlinear optimization. Ample attention is paid to both constrained and unconstrained problem types, with a healthy and refreshing emphasis on trust-region strategies, and modern SQP and Interior-Point algorithms. Sufficient detail is paid to most topics while overall perspectives are well-maintained. This book is the very best of its kind for its intended audience. I strongly recommend it.
A book for understanding numerical optimization algorithms.......2006-10-06
This books focuses on practical methods for continuous unconstrained
and constrained optimization. It does not cover problem
formulation. In all methods, the presentation tries to motivate the
approach using basic principles, rather than throw a mechanical
algorithm to the user. Thus the algorithms all make intuitive
sense. This is best demonstrated in the presentation of the KKT
conditions for constrained optimization. Below are a list of topics
covered.
Unconstrained optimization looks for a point with gradient 0. In
terms of search directions, most importantly are two: steepest
descent, Newton direction. Newton direction is based on a quadratic
approximation, and the direction is obtained by solving for the
gradient to be 0 using Newton method. We also know quasi-Newton and
Conjugate gradient. The control is in line search and trust region
method to make sure that for each step there is sufficient
descent. Line search modifies Hessian to make it positive definite.
Constrained optimization is based on KKT condition on Lagrangian
function. KKT just says that at the solution, the gradient of the
objective function is a linear combination of the gradients of the
active constraints. All interior point method form the KKT equation
and solve it using Newton equation method. Inequality constrains become
equality by adding slack variables and simple bounds on the slack
variables. The solver will make the solution to balance the total
reduction (because of the complementarity constraints) of all
variables, and the closeness to the boundary (one variable become 0).
The active set method tries to guess a set of active constraints,
minimize it by ignoring the reset of the constraints, try to update to
the minimizer. If this makes an inactive constraint become active, add
it into the active set. Once we are at the minimizer of the current
active set, we calculate the Lagrange Multipliers, if an inequality
active constraint's multiplier is negative, it is dropped from the
active set and the next iteration begin. Under some assumptions, the
next iteration will be able to reduce the objective function. Because
the subproblem only has equality constraint, can be solved using KKT
equation directly or null space method. For linear programming
problem, the addition of a constraint and dropping a constraint from
the active set happens at the same time. Each active set corresponds
to a basic feasible point.
There are also penalty, barrier, modified multiplier method to convert
the problem to solving a series of unconstrained problem. The
sequential quadratic programming method is to approximate the
objective function by quadratic model and use linear approximation to
the constraints. Solve the resulting QP subproblem using either active
set/interior point/direct KKT/gradient projection. The search
direction is safeguarded in line search by following the Wolfe
condition.
Too much explanation, relative to the required background; some omissions in motivation.......2006-09-24
While I acknowledge the many good points that the other reviewers pointed out, I found this book less than "optimal" in a number of respects.
The text is very wordy and yet still sometimes lacks critical explanations. In particular, I found that the motivation for the ideas in earlier chapters is insufficient for the skeptical and questioning reader--one needs to put more trust in the author than I was comfortable with. The lines of reasoning used to motivate the methods are vague: Nocedal spends too much time talking about optimization from a distance. I would have appreciated a book that was more concise and that had more airtight reasoning, exploring questions more thoroughly.
I also feel that this book is impoverished with respect to algorithms. One does not encounter enough algorithms early on, and the book does not encourage enough experimentation. It also suffers from the very common "sin" among Numerical mathematics texts--it talks extensively about the convergence of algorithms before cultivating a deep understanding of those algorithms. The effect is that the reader gets bogged down with technical details. While the motivated reader can go off on her own and experiment to fill in these gaps and piece together the puzzle, I think most people who have this level of initiative and intellectual curiosity would be better served by a book that is more concise.
Following on this same theme, the level of explanation is not consistent with the level of background required to read the book. Some things are explained in a level of detail appropriate to an introductory undergraduate text, but the book requires substantial background in multivariable calculus and linear algebra. Someone without prior background in numerical linear algebra will probably find the notation in the book unintuitive and cumbersome; the appendices are of little help. But anyone with sufficient background to fully understand the material in this book will probably find it has too much explanation and moves too slowly.
I haven't found a better book on the topic yet; solving such an optimization problem seems to beyond the scope of the algorithms covered in this text. But I do feel confident that this book is not the best, due to the flaws I've mentioned above!
Outstanding reference.......2006-07-17
Within the range that this intends to cover, it is an outstnading reference. The first two chapters lay out the mathematical preliminaries, and get the book off to a fast start. The next four chapters discuss basic classes of algorithms for nonlinear optimization and choices of stopping criteria. This includes conjugate gradient methods adapted from the CG method for solving linear systems - since, in nearly all cases, non-linear optimization breaks down into iterations over locally linear approximations.
The emphasis thoughout is on practical algorithms and efficient computation. First and second derivatives are used heavily throughout this book, but symbolic differentiation of the nonlinear functions is usually unavailable. As a result, significant emphasis goes into approximation techniques, and into the common cases of sparse systems. Despite its heavily mathematical orientation, this really is a book about the practicalities of computation.
A bit further on, Nocedal and Wright get to the topic that brought me to this book in the first place: nonlinear least squares. As always, the presentation is clear but very dense. Other topics follow, including solutions of nonlinear equations (i.e. minimizing the error in approximating the exact solution), simplex and polynomial-order techniques for linear systems, and more.
This is a book for someone who's completely at home with differential calculus and linear algebra, and who's willing to spend time extracting the full meaning from terse descriptions. It's also for a reader who is comfortable translating dense notation into working numerical code - not a task to be undertaken lightly. That reader will be rewarded with wide-ranging and very practical discussions of many problems and the techniques used for each. As it says in the introduction, this doesn't address the whole world of optimization problems - combinatorics, discrete problems, and jagged search spaces are not the subject here. If, however, this book touches on your topic, you'll find it handled very well. This has my highest recommendation.
//wiredweird
Book Description
The use of mathematical models in financial management is today common business practice. The state of the art is constantly being advanced by academia and refined by industry. This book achieves two objectives. First, it brings together the (apparently) diverse fields of finance and management science/operations research. It presents a variety of techniques used in complex problems for financial management: optimization, simulation, stochastic programming and supercomputing. Second, it links current industrial practices with academic research to a degree unparalleled by any previous publication in the field.
Customer Reviews:
Excellent organization of conference and contents.......2001-02-21
This book is a compilation of conferent at Wharton school, one topic was financial engineering. The editor, Zenios, categorizes the conferences in great organization. Even though it was from conference, I almost have no feeling or conference paper reading at all. The book consists of 3 parts. Part I is the general idea of financial engineering with methodology (e.g. risk management, stochastic optimization). Part II is the experience from practitioners (very good). Part III is more advanced issue in methodology. In sum, this is an intermediate book for senior undergrad or grad student or even practitioner in this area for the contents and presentation matter.
A must for all Quantatative Financial Managers.......2000-03-31
The book is on the prescribed reading list of the Society of Actuaries Fellowship Investments Examination and the reason why is pretty obvious! The book basically explains how techniques from the Applied Mathematics field can be applied to Finance and Investments and the benefits of this application. It explains in Chapter 12 why the traditional actuarial approach to Immunization Theory is too simplistic and how to generalize this theory so it becomes a useful tool in practice. In Chapter 5, actuaries are taught the advantages of using modern simulation techniques for valuing SPODA's, a very topical subject in the US today. My only critisism of the book is that not in all chapters are numerical examples given so that becomes more alive and meaningful. The book is useful not only to actuaries, but to all the Financial Engineering community.
Book Description
Financial Models and Tools for Managing Lean Manufacturing provides an understanding of the impact that traditional accounting practices have on operational improvement programs. This book shows managers of supply chains how to prepare for and present the impact of Lean Manufacturing to top management and stakeholders of a company. To illustrate the impact of lean manufacturing on the income statement, it presents a multi-month, Excel™ and Pro-Model™ based manufacturing operation environment that incorporates actual sales, sales forecasts, and production results. This text offers the financial skills that supply chain managers need to successfully manage Lean Manufacturing and its impacts.
Book Description
Financial Models Using Simulation and Optimization offers the most in-depth treatment to date of the use of decision-support software to address financial models in business problems. It is intended for anyone who builds or reviews financial models and for anyone who wants to learn more about decision-support software. Step-by-step instructions take the reader through over 60 examples. Topics covered include options pricing, portfolio optimization, acquisitions modeling, VAR, hedging with futures, risk-neutral approach, and more.
Customer Reviews:
Financial Models Using Simulation and Optimization: A Step-By-Step Guide With Excel and Palisade's Decisiontools Software.......2006-04-02
I highly recommend this book to anyone working with Excel & Financial Models. The author has straight forward examples that highlight approaches & methods that will help you leverage the power of Microsoft Excel. Incorporating Excels Solver can be very beneficial for financial planning and this text helps accelerate you along the learning curve at a rapid pace. I have used his "yield curve" technique, "Linear Regression" technique, and "Modeling Relationships Involving More than One Independent Variable" technique. I used this last technique to model prepayment speeds of mortgage loans consisting mainly of ARM loans (COFI & MTA). The investment in the text is small compared to the wealth of information at your disposal. It will make a great reference book.
Nice book.......2005-10-14
nice book for the starters and great concepts to learn excel in an exciting way.
Good guide to learn to develop financial models.......2001-03-18
This book has good examples that one can use to get up and going with basic to intermediate financial models. If you have to start somewhere, this is certainly it.
An execellent guide to intermediate/advanced models.......2000-12-08
This book does what it says it does in the title. It is a hand-on, step-by-step guide to constructing spreadsheet models to assist with decision making. The book guides the reader through intermediate to advanced modelling topics and is written at a level that is accessable to the novice and intermediate user. Advanced users are probably already familiar with the techniques presented.
Someone interested in the tiresome advanced mathematics behind the models should look instead to academic journals . . . someone interested in APPLYING that stuff to something useful should consider this book.
Excellent resource for marketing or finance manager.......1999-10-16
The book provides step-by-step method to guide you to build financial models for your company. Once you understand the basic foundation, you could use the tools to build more complex models.
Book Description
Traditionally engineers devised communication services without reference to how they should be priced. In today's environment pricing is a very complex subject and in practice depends on many parameters of the actual market - including amount of traffic, architecture of the network, technology, and cost. The challenge is to provide a generic service model which accurately captures aspects such as quality and performance, and can be used to derive optimal pricing strategies.
Recent technology advances, combined with the deregulation of the telecommunication market and the proliferation of the internet, have created a highly competitive environment for communication service prividers. Pricing is no longer as simple as picking an appropriate model for a particular contract. There is a real need for a book that explains the provision of new services, the relation between pricing and resource allocation in networks; and the emergence of the internet and how to price it.
Pricing Communication Networks provides a framework of mathematical models for pricing these multidimensional contracts, and includes background in network services and contracts, network techonology, basic economics, and pricing strategy. It can be used by economists to fill in the gaps in their knowledge of network services and technology, and for engineers and operational researchers to gain the background in economics required to price communication services effectively.
- Provides a broad overview of network services and contracts
- Includes a primer on modern network technology and the economic concepts relevant to pricing and competition
- Includes discussion of mathematical models of traffic flow to help describe network capability and derive pricing strategies
- Includes coverage of specialist topics, such as regulation, multicasting, and auctions
- Illustrated throughout by detailed real examples
- Suitable for anyone with an understanding of basic calculus and probability
Primarily aimed at graduate students, researchers and practitioners from electrical engineering, computer science, economics and operations research Pricing Communication Networks will also appeal to telecomms engineers working in industry.
Download Description
"Recent advances in technology, combined with the deregulation of the telecommunication market and the proliferation of the Internet, have created a highly competitive environment for communication service providers. There is no simple recipe for pricing network service contracts in all contexts. Pricing is a complex subject, which depends on parameters of the actual market - including the degree of competition and customer demand - and parameters of technology, such as resource consumption, network architecture, resource availability, and cost. Pricing Communication Networks: Economics, Technology and Modelling covers many important issues in providing new services, the relation between pricing and resource allocation in networks, and the emergence of the Internet and its pricing. It provides a framework of mathematical models for pricing multidimensional contracts with quality of service guarantees, and includes a useful background on network services and contracts, network technology, basic economics, and pricing strategy.Provides a broad overview of network services and contracts. Includes a primer on modern network technology a nd the economic concepts relevant to pricing and competition. Discusses mathematical models for multiplexing bursty traffic flows, and applies these to measuring network capability and deriving pricing strategies for services with statistical quality guarantees. Discusses definitions of cost for communication networks and explains the intricacies of cost-based pricing. Explains congestion pricing and its potential applications in the Internet. Illustrated throughout by detailed examples and figures. Includes coverage of specialist topics, such as regulation, multicasting, interconnection, and auctions. Pricing Communication Networks: Economics, Technology and Modelling is an essential reference for graduate students, researchers and practitioners from electrical engineering, computer science, economics and operations resear
Book Description
This textbook provides a comprehensive modeling, reformulation and optimization approach for solving production planning and supply chain planning problems, covering topics from a basic introduction to planning systems, mixed integer programming (MIP) models and algorithms through the advanced description of mathematical results in polyhedral combinatorics required to solve these problems. This book addresses solving real life or industrial production planning problems (involving complex production structures with multiple production stages) using MIP modeling and reformulation approach. It is based on the twenty years worth of research in which the authors have played a significant role. One of the goals of this book is to allow non-expert readers, students in business, engineering, applied mathematics and computer science to solve such problems using standard modeling tools and MIP software. To achieve this the book provides an introduction to MIP modeling and to planning systems, as well as a unique collection of reformulation results, integrating them into a comprehensive modeling and reformulation approach, as well as an easy to use problem-solving library. Moreover this approach is demonstrated through a series of real life case studies, exercises and detailed illustrations. Graduate students and researchers in operations research, management, science and applied mathematics wishing to gain a deeper understanding of the formulations and mathematics underlying this approach will find this book useful because of its detailed treatment of the polyhedral structure of the basic lot-sizing problems and simple mixed integer sets that arise in more complicated problems. Reading this book will allow the reader to improve formulations of non-standard MIP models much more effectively and produce state-of-the-art models and algorithms.
Average customer rating:
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Nonlinear Optimization with Financial Applications
Michael Bartholomew-Biggs
Manufacturer: Springer
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Similar Items:
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Financial Optimization
-
Optimization Methods in Finance (Mathematics, Finance and Risk)
ASIN: 1402081103 |
Book Description
The book introduces the key ideas behind practical nonlinear optimization. Computational finance – an increasingly popular area of mathematics degree programs – is combined here with the study of an important class of numerical techniques. The financial content of the book is designed to be relevant and interesting to specialists. However, this material – which occupies about one-third of the text – is also sufficiently accessible to allow the book to be used on optimization courses of a more general nature. The essentials of most currently popular algorithms are described, and their performance is demonstrated on a range of optimization problems arising in financial mathematics. Theoretical convergence properties of methods are stated, and formal proofs are provided in enough cases to be instructive rather than overwhelming. Practical behavior of methods is illustrated by computational examples and discussions of efficiency, accuracy and computational costs. Supporting software for the examples and exercises is available (but the text does not require the reader to use or understand these particular codes). The author has been active in optimization for over thirty years in algorithm development and application and in teaching and research supervision.
Book Description
First published in 1998, Financial Models Using Simulation and Optimization quickly became one of the most widely used references for the application of simulation and optimization techniques to financial problems. Now, author Wayne Winston has done it again with a totally new volume! Financial Models II is packed with real-life examples that demonstrate how @RISK, Evolver and Excel can be used to make better financial decisions. Winston's straightforward, step-by-step approach makes his innovative techniques accessible to anyone who uses Microsoft Excel.
Topics covered include:
o Modeling future stock prices and hedging stock price and interest rate risk. Examples include Value At Risk (VAR), incorporating analyst forecasts, correlating stock forecasts, and bootstrapping.
o Portfolio optimization, including minimizing a portfolio's risk, finding the Efficiency Frontier, minimizing the probability of loss, and maximizing the Sharpe Ratio.
o Valuing a firm or a stock price, including modeling key drivers of firm value, incorporating simulation into Proforma models, forecasting income of a corporation, and modeling profitability of a new product.
o Real options and options pricing analysis, including valuing options by arbitrage methods, Black-Scholes pricing, estimating volatility using the historical and implied volatility approaches, option pricing using the risk neutral approach, binomial and lognormal pricing models.
o Pricing and marketing models, including optimal product bundling, price response to currency fluctuations, conjoint analysis, and discrete choice analysis.
o Plus: playing craps with @RISK and simulating the NBA finals!
Examples in this book have been developed and used successfully at companies such as GM, Microsoft, Intel, and Cisco. All files discussed are included on CD-ROM. The book is suitable for advanced undergraduates, MBAs, and most of all practicing financial professionals for both self-study or education classes.
Customer Reviews:
Disappointment.......2006-10-10
I have just received this book and had a look at. It is not what I had expected before buying. The author shows excellent knowledge of Microsoft Excel and does not care about explanations where he takes formulas from. There is very little about the underground Real Options technology. There is almost nothing about "Financial Models" themselves - just how to make calculations using ready to use formulas and Excel.
In my opinion it is not a big deal to use Excel when you know formulas.
What I was really after by buying this book was how to build mathematical models in finance, what kind of numerical methods they use and how they use Excel for getting results. I still believe that Excel is not the best tool for resolving systems of differential equations using numerical methods (Particularly big systems).
I myself am a Russian rocket scientist who has spent more the 15 years in building mathematical models in mechanical engineering. To my surprise differential equations that they use in finance are same type as we have used in mechanical engineering. Now I live in New Zealand and I am trying to enter finance world by building math models in this area. I decided to introduce myself for proving that I know the subject that I am talking about
I am sorry but this book is waste of money- at least for me.
Completely useless !.......2005-12-22
The example files were not included in the CD-Rom and the trial software expires in 10 days. Not enough time to go through a fraction of the material. Don't waste your time with this book.
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