Book Description
Designed to form the basis of an undergraduate course in mathematical finance, this book builds on mathematical models of bond and stock prices and covers three major areas of mathematical finance that all have an enormous impact on the way modern financial markets operate, namely: Black-Scholes’ arbitrage pricing of options and other derivative securities; Markowitz portfolio optimization theory and the Capital Asset Pricing Model; and interest rates and their term structure. Assuming only a basic knowledge of probability and calculus, it covers the material in a mathematically rigorous and complete way at a level accessible to second or third year undergraduate students. The text is interspersed with a multitude of worked examples and exercises, so it is ideal for self-study and suitable not only for students of mathematics, but also students of business management, finance and economics, and anyone with an interest in finance who needs to understand the underlying theory.
Customer Reviews:
Mathematics for Finance: A useful tool for the unskillled investor.......2007-03-19
I enjoyed reading the book and solving exercises in it. I have a Ph.D.in chemistry and my wife and I did our his and her's MBA in the 1990s. I wanted to learn more concepts in finance and needed an easy entry, something I could enjoy, and without spending much money. The book by Capinski came recommended from a friend who teaches Economics at Cal State. I can speak for myself: I feel reasonably informed and I feel the book gave me concepts I can use to handle my own portfolio.
In the future, this text should be offered with an interactive CD that contains Xls, matrix, calculus, and graphing capabilities so one (I) can visualize the outcomes of proposed solutions.
Incoherent.......2007-01-18
Anyone can scribble a bunch of equations on paper and call it a book. Without sufficient context, they are useless.
Insufficient and disappointing. Not even a good introductury text........2006-05-15
As a graduate student in Financial Engineering I have found this book useless.
The title of the book is "Mathematics for Finance", but can you find in it even an elementary introduction to the stochastic processes? No. Ditto for the Ito's lemma and many other topics. The derivation of the Black Scholes formula is just sketched, and the insight that you can get from it is very limited.
Nevertheless, I wouldn't mind these limitations if this book provided a clear introduction to more advanced topics: unfortunately this book is not good even in that. In comparison to other textbooks the theorems and definitions are convoluted and do not go straight to the point. For example, in Shreve's "Stochastic Calculus for Finance" or Baxter & Rennie "Financial Calculus" the Fundamental Theorem of Asset Pricing is stated in this way: "In a market with risk neutral probability there is no arbitrage". Can you find such a simple and explanatory definition in Capinski's book? Not at all. The theorem at page 83 (you can see it yourself by searching inside the book) basically says the same thing using 8 lines of text and little financial intuition.
The only good thing that I can say about this book is that all exercises are resolved.
Overall, "Mathematics for Finance" has been a big disappointment: it doesn't have either the mathematical depth of Shreve's books or the conciseness in explaining financial concepts of Baxter & Rennie.
Whatever is the level of education that you are pursuing, graduate or undergraduate, I don't see any point in using it.
Great Book for Undergrad Quants.......2005-08-29
Mathematics for Finance (An Introduction to Financial Engineering) is a book intended for undergrad students "IN MATHEMATICS" or other discipline with a relative high mathematical content.
The book assumes some basic notion of Calculus and Probability Theory and it is focused more on the mathematics than in its theory and application of Finance. If you are looking to dwell into the mathematics (Proof of Equations) this is a great book, but if you are looking for a book that is rich in theory and in application then you should consider "Option, Future and Other Derivatives" or "Quantitative Methods for Finance" as an alternative. Both books are "a most" for any finance student and are of great help. Now if you want an introduction into the mathematics behind Finance then this book is a perfect purchase.
Important to state that all the problems presented in this book are solved meaning that it is great for self teaching. Marek Capinsi and Thomas Zastawniak have done a great job on this book.
I gave it four stars, because it has room for impovement.
Joining the chorus.......2005-08-03
I can only echo the other reviewers. As far as I can tell this book has no serious competition. This is an excellent introduction to mathematical finance for those with a solid undergraduate level understanding of higher math but without graduate level exposure. I agree that it is ideal for self study as that is exactly what I am using it for. The price is right especially in contrast with its overpriced brethren. Five stars!
Book Description
Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The text avoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.
Customer Reviews:
Clear, rigorous, fascinating.......2007-01-20
I'm a Ph.D. student in biophysics. This is the best treatment of systems biology that I've encountered. It treats both the math and the biology with clarity, rigor, and respect. It simplifies without dumbing down. It's beautifully written. If you doubt that systems biology is a real scientific discipline, this book will change your mind.
Building Mathematical Models of Cells.......2006-09-25
The history of science over the past few centuries is to become ever more specialized. The physicists, becomming ever more concerned with the very large (stars, galaxies, the cosmos) or the very tiny (first atoms, then atomic components, now sub-components. The biologists on the other hand were studying much larger things, such as the cells that make up life. Both sciences developed techniques to facilitate their study.
In recent years, researchers have discovered that sometimes these specialized techniques can be used to develop greater insight into what is happening in other sciences.
In this book, Dr. Alon uses his training in physics to examine certain aspects of biology and to use the terminology and mathematics to describe the way these biological networks work.
The goal of the book is to begin the formulation of general laws that apply to biological networks. This is done by providing a mathematical framework in which some of the design principles of biological systems can help to understand biological networks. In looking at the results, an underlying simplicity not seen before appears in biological systems.
Great Job.......2006-09-09
A superb intro to the field. The math is moderate and helpful. Network concepts and their ties to examples and theory are clearly and succinctly presented. This is a textbook but reads easily like a book. Covers key elements while connecting them by at least mention to up-to-date further research. The basics and the grandeur of systems biology. I am trying to remember now anything on the negative side and cannot.
Book Description
This introductory text provides a clear understanding of the intuition behind derivatives pricing, how models are implemented, and how they are used and adapted in practice. M. Joshi covers the strengths and weaknesses of such models as stochastic volatility, jump diffusion, and variance gamma, as well as the Black-Scholes. Examples and exercises, with answers, as well as computer projects, challenge the mind and encourage learning how to become a good quantitative analyst.
Customer Reviews:
An excellent starting point. ... .......2007-01-24
This book is excellent for a deeper introductory look at mathematical
finance. It is well-written, and strikes a nice balance
between sophistication and accessiblity. Its companion volume on
C++ development in the context of quantitative finance is also well
worth examining. I look forward to seeing the follow up volume, which
will cover additional, more advanced topics.
Very Good.......2006-11-03
I'm totally satisfied. About the timing of the shipment, to me very quick and about the quality of the product, that was in good condition.
Very useful book.......2006-02-01
This is a great book for those who want to learn quantitative finance, but don't have the benefit of being enrolled in a financial engineering program. It has the advantage of being self-contained and begins instruction from the ground up: you can "cold start" on the subject with this book. Just a basic knowledge of differential equations (non-stochastic) is required.
It is natural to compare Joshi's book with Hull, but I would recommend reading them together as they have complementary strengths. Hull is over-simplified but provides financial intuition and descriptions of real-world practices. However it does not have modern notation. It also does not teach you how to solve actual pricing problems from the mathematical or computational point of view. Joshi's book does all of that and even helps you develop some mathematical intuition for the models. It also has some computing projects in c++ that a student could do.
The real comparison should be with Neftci's mathematical finance book and Baxter and Rennie. I think Joshi's book is much better than either of the two. I could barely read Neftci after a while because of the errors and bad organization. B&R is way too formal in my opinion for such an applied subject. Joshi's book has good notation and organization which builds confidence in the author, plus it is very applied so you feel you are learning something useful. It has none of that lemma-proof style which can be so unappealing to non-pure mathematicians.
If you already know the field.......2005-10-11
If you already know almost everything it is a very good book. No error and the guy knows what he is doing. However, if you know everything, why do you want to buy this book?
Unfortunately, if you do not know everything, the book is very difficult to understand. At a first lecture I never get the point. After reading some others books and implement the problem, I can indeed understand the chapter... but what is the use? Maybe we (the author and me) do not have the same way of thinking...
Another bad point is that there is no implementation. So if you are blocked somewhere you are dead.
Moreover the authors spend 16 chapter of 18 on equities and 2 on interest rate. But this last field correspond to 90% of the market! ...
Well,..., However,... not so bad ... so, 3 stars
This is a highly recommended work for any quant........2005-06-18
As I write this in June of 2005, quantitative finance has grown up. What was once a cross-over subfield of finance with a veneer of mathematics is now a field unto itself, and hence, in the past decade there have been an explosion of books which often replicate or restate what has been said before with little new to add. Also, there remains an unforgiving gap between introductory texts that are too superficial and specialists' mathematics books that are rigorous and difficult works beyond the commitment for mastery of the busy, intelligent, practical front-line quant. In addition, works that were once adequate are now simplistic and under serve their readers by lulling them into false confidence. Into this fray Dr. Mark S. Joshi's "The Concepts and Practice of Mathematical Finance" enters with a modern voice and delivers what previous texts have only promised and failed to. The work lives up to its title by presenting both concepts and practicalities, and makes other works that do neither well obsolete. Those familiar with my other reviews on quantitative finance texts know that I place a premium on clarity, and on this front Joshi deserves six stars, for he is a master of what William Strunk called "the plain style." I am always sensitive to the fact that many of the world's best quants come from nations where English is not the first language. Readers from China, France, Germany, Greece, Italy, Norway, Sweden, Russia and eastern Europe will enjoy Joshi's clarity and find his English easy to follow. It would be impossible to cover everything in quanfin in a single volume, however there is nothing horribly glossed over here and neither is there a single wasted word or equation.
I recommend Amazon review readers refer to the table of contents in the "Look Inside" feature to see what Joshi covers, but my own highlight is how welcome it is that Joshi focuses on risk from the very first word. Since Louis Bachelier risk measurement is what separates quantitative finance from "finance." Other books, including some quantitative finance works, start with cash flows, valuation, and discounting, and only add risk as an antecedent. Joshi correctly emphasizes risk first, last, and always, and for that elevation alone his work deserves five stars. From this foundation Joshi then covers very well pricing methods and arbitrage, simple and high dimensional trees, and the useful shortcuts of Ito calculus that makes tractable Zeno's paradox. Joshi also covers risk neutral and martingale methods, continuous barrier options, multi-look exotic options and incomplete markets and jump processes with an aim of showing these as typical problems for the working quant. Joshi's own references, index, and footnotes testify that by no means is he offering the first, nor the last, word on these knotty subjects, but his treatment is welcome just the same.
The target audience who would benefit from this text over others is four-fold. The primary audience is for first semester students in a graduate financial engineering program, for Joshi's "Concepts and Practice" will be handy throughout his or her studies and career. For those students unsure of their skills and with a limited budget considering between this and an introductory quantitative finance text I recommend Joshi over, say, Wilmott, for this work is more rigorous and in the long run will provide the better value as a practical companion. Within this audience I include professors looking for a high level foundational text for teaching practical risk management and derivatives pricing: this is the book to adopt, yes, even over Hull.
The second audience is for those trained in other science fields: pure mathematics, statistics, physics, etc. who are moving to finance jobs. This volume is an easy "one-stop shop" for you to re-tool your own background towards those topics and techniques used on a quant desk. While by no means covering everything, Joshi speaks your language and after digesting this work all else will fall into place and be understood and used with greater efficiency.
The third and broadest audience is one I am a member of: the already trained and practical "quant." Why should we need this book? My observation is that between reading (for example) Hull and Wilmott, Joshi's "Concepts" unavoidably covers many of the same topics, but also some things they do not and in ways they never could. Joshi is an expert practitioner at the top of his art, and that practical spirit is in every single page. For example, while Hull and Wilmott cover the concept and mathematics of stochastic volatility, Joshi writes from the point of view of the coding quant and discusses the issues of implementation. Joshi's "Concepts and Practice" serves a two fold purpose for a qaunt: it provides an additional voice and explanation of inescapably fundamental material, while bridging the gap of technical deployment for front line practitioners. This is not to say that Joshi offers us up a cookbook, for by no means is this such. Anyone who thinks they can simply buy this book and in a sleepy afternoon plug away code and technique and be done is missing the point: for this is a teaching text. Moreover, each house and set of problems and instruments and structured products to offer are different, to say nothing of the platforms one will be working on. That is why they call it "work." Therefore the practical quant should look to this text as a reference guidebook in a tool box.
As a fourth audience I cautiously recommend this book for those who are going into exotic product sales, but only those who have a good grounding in upper level calculus, linear and matrix algebra, time series analysis, and trees. Why? Simply put, you will be offering products built by quants who simply assume the knowledge in this book is a given. In addition, your better clients will (or should) have quants speaking this language, and the greater your own understanding of the concerns of your team and your clients the better your sales. If this work is too rigorous, then Wilmott's "Introduction to Quantitative Finance" quickly followed by Joshi's "Concepts and Techniques" is the course to follow.
Who is this work not for? Here are some tests. If you are a quant who can type at five lines of code a minute and can read Shreve and Karatzas drinking beer, then this work is too redundant for you. On my desk is a paper on a stochastic process with drift and viscosity under regime switching. If you are reading the same journal, then this work is too simple for you. If you have no idea what I've written about in the past three sentences, then this work is too hard for you.
In summary, Dr. Mark Joshi advances his excellent reputation as an intelligent, practical, and generous quant in offering "The Concepts and Practice of Mathematical Finance" and I recommend this book's wide adoption in graduate programs and its addition to reference libraries.
Book Description
The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering, and other applications. The authors focus on examining the way a response variable depends on a combination of explanatory variables, treatment, and classification variables. They give particular emphasis to the important case where the dependence occurs through some unknown, linear combination of the explanatory variables. The Second Edition includes topics added to the core of the first edition, including conditional and marginal likelihood methods, estimating equations, and models for dispersion effects and components of dispersion. The discussion of other topics-log-linear and related models, log odds-ratio regression models, multinomial response models, inverse linear and related models, quasi-likelihood functions, and model checking-was expanded and incorporates significant revisions. Comprehension of the material requires simply a knowledge of matrix theory and the basic ideas of probability theory, but for the most part, the book is self-contained. Therefore, with its worked examples, plentiful exercises, and topics of direct use to researchers in many disciplines, Generalized Linear Models serves as ideal text, self-study guide, and reference.
Customer Reviews:
As promised, on time.......2006-03-21
I got this book in time and in perfect condition. Prompt delivery!!!
first great treatment of generalized linear models.......2000-08-09
Nelder and Wedderburn wrote the seminal paper on generalized linear models in the 1970s. Since then John Nelder has pioneered the research and software development of the methods. This is the first of several excellent texts on generalized linear models. It illustrates how through the use of a link function many classical statistical models can be unified into one general form of model. This unification is helpful both theoretically and computationally. Various applications are presented in a clear manner.
Very comprehensive, very helpful........2000-04-02
The first edition is already a well-known text and reference, this expanded version is even better. Very comprehensive and very helpful.
One of the best books on modelling.......2000-04-01
This is an important book. It is a mature, deep introduction to generalized linear models.
General linear models extend multiple linear models to include cases in which the distribution of the dependent variable is part of the exponential family and the expected value of the dependent variable is a function of the linear predictor. Besides the normal (Gaussian) distribution, the binomial distribution, the Poisson distribution and the Gamma distribution, are just some of the exponential family members most frequently encountered in the scientific literature. Using appropriate functions to join the dependent variable to the linear predictor many classic models of applied statistics are included in the broad frame of generalized linear models: "logistic regression", log-linear models, Cox's proportional hazards models are just some of them.
Further extensions to the "base" family of generalized linear models, such as those based on the use of quasi-likelihood functions, and models in which both the expected value and the dispersion are function of a linear predictor, are well presented in the book.
Examples, and exercises, introduce many non-banal, useful, designs.
There are some minor drawbacks. Some more advanced topics might have been introduced more smoothly (i.e. conditional likelihood). Some other topics are better understood when you are already familiar with the specific object of study (i.e. Cox's proportional hazards models as a generalized linear model). The book does not provide software examples, nor is it related with any specific statistical package. However, the maturity of the reader to whom the book is addressed should be so high that translating the majority of the examples presented in the book in the "language" of a familiar statistical package should not be a problem.
Average customer rating:
- It might be a good finance book,
- superb coverage of subject matter
- good but not excellent
- Good book to understand quantitative finance
- Investment Science must have
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Investment Science
David G. Luenberger
Manufacturer: Oxford University Press, USA
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ASIN: 0195108094 |
Book Description
Fueled in part by some extraordinary theoretical developments in finance, an explosive growth of information and computing technology, and the global expansion of investment activity, investment theory currently commands a high level of intellectual attention. Recent developments in the field are being infused into university classrooms, financial service organizations, business ventures, and into the awareness of many individual investors. Modern investment theory using the language of mathematics is now an essential aspect of academic and practitioner training. Representing a breakthrough in the organization of finance topics, Investment Science will be an indispensable tool in teaching modern investment theory. It presents sound fundamentals and shows how real problems can be solved with modern, yet simple, methods. David Luenberger gives thorough yet highly accessible mathematical coverage of standard and recent topics of introductory investments: fixed-income securities, modern portfolio theory and capital asset pricing theory, derivatives (futures, options, and swaps), and innovations in optimal portfolio growth and valuation of multiperiod risky investments. Throughout the book, he uses mathematics to present essential ideas of investments and their applications in business practice. The creative use of binomial lattices to formulate and solve a wide variety of important finance problems is a special feature of the book. In moving from fixed-income securities to derivatives, Luenberger increases naturally the level of mathematical sophistication, but never goes beyond algebra, elementary statistics/probability, and calculus. He includes appendices on probability and calculus at the end of the book for student reference. Creative examples and end-of-chapter exercises are also included to provide additional applications of principles given in the text. Ideal for investment or investment management courses in finance, engineering economics, operations research, and management science departments, Investment Science has been successfully class-tested at Boston University, Stanford University, and the University of Strathclyde, Scotland, and used in several firms where knowledge of investment principles is essential. Executives, managers, financial analysts, and project engineers responsible for evaluation and structuring of investments will also find the book beneficial. The methods described are useful in almost every field, including high-technology, utilities, financial service organizations, and manufacturing companies.
Customer Reviews:
It might be a good finance book,.......2007-08-14
but it's a terrible math book.
Too often, explanations, examples, and problems do not clearly explain the meanings of variables and applicable assumptions. This poor presentation of material makes the book barely usable to someone trying to learn the material for the first time.
superb coverage of subject matter.......2007-07-30
Prof. Luenberger currently teaches at Stanford and this book is used as the textbook for a 2-quarter series in investment science there. The coverage is concise and the math is manageable and yet extremely practical. I agree that this an excellent self-study book in the subject of investment science.
good but not excellent.......2007-03-15
This book serves very good introduction to mathematical finance. Particularly,
I enjoyed the discussion of bonds immunization, mean-variance theory, CAPM, APT.
It's most suitable for senior undergraduates or any junior graduate students.
But it doesn't deserve 5 star for the following reasons:
1) Most of the theories discussed so far in the book are TOO idealized and
over simplified. Financial data is dynamic and massive. In model quantitative/computational finance, the most important thing is to understand what the data says rather than what one thinks the data structure might be. With the book, one probably can only do some macroeconomic/very coarse analysis. Author should incorporate more data analysis evidence together with proposed theories.
2) The proof of ito's lemma is wrong(i.e. "Deltaz^2 --> deterministic as Deltat --> 0"). It's surprising since most books make the same mistake. It is the law of the large number contributes to the equality!(i.e. integration sense). The misunderstanding of the proof might lead to the misunderstanding of the hedging process.
3) In the commodity option pricing session, author demonstrated the use of futher market to price the option. This should be discussed further (i.e. black's model).
4) The volatility pumping session should be further researched. The explanation is
not satisfactory.
Good book to understand quantitative finance.......2005-06-10
Luenberger was a professor of optimization and his books on that subject are also very good. Clear and Precise. But sometimes he is extremely concise, so that you need to work a bit to completely understand a point.
In this book, we have again the same style (after all, it is the author style): Clear and precise book, GOOD choice of notation (I cant say the same thing about HULL's books) but sometimes extremely concise.
Overall, a good book to start learning and on a solid foundation.
Investment Science must have.......2005-03-24
Great book, covers lots of material and goes beyond by using the log utility to portfolio growth. Great buy!!!!
Book Description
Finance is one of the fastest growing areas in the modern banking and corporate world. This, together with the sophistication of modern financial products, provides a rapidly growing impetus for new mathematical models and modern mathematical methods. Indeed, the area is an expanding source for novel and relevant "real-world" mathematics. In this book, the authors describe the modeling of financial derivative products from an applied mathematician's viewpoint, from modeling to analysis to elementary computation. The authors present a unified approach to modeling derivative products as partial differential equations, using numerical solutions where appropriate. The authors assume some mathematical background, but provide clear explanations for material beyond elementary calculus, probability, and algebra. This volume will become the standard introduction for advanced undergraduate students to this exciting new field.
Customer Reviews:
Good Buy.......2007-08-29
maps one to one with many chapters in Hull. more elaborate derivations than Hull. Fixed income area treatment is very slim though. Good Buy for the Price.
Okay but not an introduction.......2006-07-31
If you want an introduction, read another book like Hull. If you want to learn how to apply Partial Differential Equations (PDEs) approach to finance then it is a useful book. However, it is better to read an elementary PDEs book before reading this book. At least, learn how to solve parabolic PDEs analytically because the technical notes in the book would not help much.
Introduction to partial differential equations in finance.......2005-10-13
This book treats only the partial differential equations
in Finance and how to treat them using Finite Differences
and Tree. For this purpose it is very well written and
understandable. A very good beginning for student. Even
undergraduate.
Now after reading it you should understand the martingales reading the baxter and how to implement Monte Carlo using, for example Glasserman (see my reviews)
A good introduction to the PDE approach.......2005-10-10
Contrary to what many readers believe, this book explains the pricing of derivatives much better than Hull. Hull gives an overview of the mechanics and properties of the derivative pricing industry, along with its pricing methodologies, and this book provides an in depth method to one of the pricing methods.
Financial derivatives can be priced by a wide range of methodologies, among some the elegant equivalent martingale measure approach (or risk-neutral pricing), replication, multinomial tree approximation, Monte Carlo simulation, partial differential equations etc etc.
This book gives an excellent introduction, and an insight to the PDE approach. Although being a big fan of the Girsanov-change-of-measure method myself, these analytical methods often fail in the valuation of highly complex derivatives like the exotics. Pricing americans prove to be hard and inefficient too, even with simulation and the risk-neutral approach.
This is where PDE methods come in. Since most derivatives (or term structures) have a PDE describing its evolution, solving the PDE seems to be a good (or sometimes the best) way, no matter how complex the derivative can get. PDEs on the other hand, have very robust and easy methods for solving. Therefore, this book brings the reader through basic PDE solving methods, analytical solutions, techniques for fast and efficient numerical approximations as well as rigorous technical explanations for some of the mathematics of partial differential equations (which arise in the financial industry).
The authors are famous for their research in the field of Industrial and Applied Mathematics, and this book continues to be a classic for undergraduates in mathematics in Oxford. If you want to have an overview of the pde approach to option valuation, without the hassle of learning up Radon-Nikodým and martingales, I highly recommend this book!
waste of time.......2005-03-10
This book is very bad, lacks almost everything you can think of, but if you don't know any better you probably won't care. It certainly needs to be supplemented by a respectable book if you want to learn derivatives (c.f. Hull's textbook, for example), and on the other hand, the math isn't rigorous at all, so you'll need a book on stochastic calculus (e.g. Michael Steele's, actually there are tons of better books out there, it's not hard to find better).
Book Description
In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques. An Introduction to Credit Risk Modeling supplies both the bricks and the mortar of risk management. In a gentle and concise lecture-note style, it introduces the fundamentals of credit risk management, provides a broad treatment of the related modeling theory and methods, and explores their application to credit portfolio securitization, credit risk in a trading portfolio, and credit derivatives risk. The presentation is thorough but refreshingly accessible, foregoing unnecessary technical details yet remaining mathematically precise. Whether you are a risk manager looking for a more quantitative approach to credit risk or you are planning a move from the academic arena to a career in professional credit risk management, An Introduction to Credit Risk Modeling is the book you've been looking for. It will bring you quickly up to speed with information needed to resolve the questions and quandaries encountered in practice.
Customer Reviews:
read this before going for it.......2007-04-23
Well first off I would like to tell anyone who doesn't have a solid working knowledge of calculus (including multivariate) to avoid this book as it requires multiple integrals and infinite series and sequences. Now onto the good and the bad:
THE GOOD:
This text explains concepts very well and is FULL of examples. I mean literally 3/4 of the book, maybe more, is examples. Every chapter also has a section of problems that have partial solutions, which can come in very handy. This is pretty much all that is good about this text, but keep in mind that explaination is the most important part of any textbook.
THE BAD:
The proofs skip plenty of steps. And I mean plenty, so much that a proof in the book would take 5 lines but when my professor proved it in class it would take him nearly 15. Also while there are tonnes of examples, too many are theoretical and very hard. The book costs a hefty amount of change and is suprisingly small, Author couldl have given few more examples to make it interesting. However the worst thing about this book is how the author leaves important things in with the text often. However most these things are small, and overall the text is a good intro to probability theory.
a very good book.......2006-10-31
The authors wanted to write the book that they themselves would have liked to read before starting a profession in risk management. I am working for a treasury consultancy firm. This book was the best of the five I bought. The text is very clear yet does not assume too much prior knowledge. It covers theory as well as industry practice. The book contains much advanced statistics and readers must have some background in order to handle this. The authors keep it simple but not too simple. Their approach is pragmatic throughout. I am really happy to have read this book when I started doing work in credit risk management.
good combination of math and finance.......2006-02-22
As indicated on the back of the book, the authors are aiming at audience who have some knowledge in both math and finance but may be weak in one and strong in another. Either way, this is a good book to read on credit risk.
Clear and comprehensive.......2005-10-27
This book clearly articulates basic concepts of credit risk modeling. At the same time it is mathematically rigorous. This book enables non mathematician with some (basic) knowledge in probability statistic to better understand and develop his risk management skills.
A good read!.......2004-08-19
Easy to understand with not a tremendous amount of complicated math to dicipher. Just what the doctor ordered.
Average customer rating:
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Encyclopedia of Optimization
Manufacturer: Springer
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ASIN: 0792369327 |
Book Description
Optimization problems are widespread in the mathematical modeling of real world systems and their applications arise in all branches of science, applied science and engineering. The goal of the
Encyclopedia
of Optimization is to introduce the reader to a complete set of topics in order to show the spectrum of recent research activities and the richness of ideas in the development of theories, algorithms and the applications of optimization. It is directed to a diverse audience of students, scientists, engineers, decision makers and problem solvers in academia, business, industry, and government.
Average customer rating:
- A deep grasp of algebraic coding theory
- Channel Coding gone wild
- Students beware!
- horrible text
|
Algebraic Codes for Data Transmission
Richard E. Blahut
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Hardcover
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Similar Items:
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Error Control Coding, Second Edition
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Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
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Information Theory and Reliable Communication
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Probability and Random Processes: With Applications to Signal Processing and Communications
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Introduction to Coding Theory
ASIN: 0521553741 |
Book Description
Error-correcting codes play a fundamental role in modern communications and data-storage systems. This volume provides an accessible introduction to the basic elements of algebraic codes and discusses their use in a variety of applications. The author describes a range of important coding techniques, including Reed-Solomon codes, BCH codes, trellis codes, and turbocodes. Throughout the book, mathematical theory is illustrated by reference to many practical examples. The book is written for graduate students of electrical and computer engineering and practicing engineers whose work involves communications or signal processing.
Download Description
The need to transmit and store massive amounts of data reliably and without error is a vital part of modern communications systems. Error-correcting codes play a fundamental role in minimizing data corruption caused by defects such as noise, interference, crosstalk and packet loss. This book provides an accessible introduction to the basic elements of algebraic codes, and discusses their use in a variety of applications. The author describes a range of important coding techniques, including Reed-Solomon codes, BCH codes, trellis codes, and turbocodes. Throughout the book, mathematical theory is illustrated by reference to many practical examples. The book is aimed at graduate students of electrical and computer engineering, and at practising engineers whose work involves communications or signal processing.
Customer Reviews:
A deep grasp of algebraic coding theory.......2006-09-19
The book is well organized and mathematically rigorous. It depicts a full picture of conventional algebraic coding theory in a systematic fashion. As a specialist in coding theory, I give my highest rank.
Channel Coding gone wild.......2006-06-25
I used this textbook for an introduction to Channel Coding class I took (graduate level). I think that the material is difficult, but this book is remarkably clear, considering that. I had no experience with Galois Fields or any of that kind of math before starting with this book, but I was able to grasp it. I think the main thing missing in this book are good summaries for each chapter, giving highlights of the important stuff. Sometimes it's hard to get an overall picture of the material, I got bogged down in math sometimes. Visually, the book is beautiful, good fonts, charts, etc...
Students beware!.......2006-05-28
I am taking an error correcting code class as a graduate EE student where this text is assigned. The book is a reference manual for people who already know the material. It is not for those who are new to algebraic codes or galois field arithmetic.
The book is introduced as an introductory book, but it is nothing of the sort.
horrible text.......2006-02-18
This book is not for beginners.All about is math.Impossible to understand.I try to give ZERO star.
Average customer rating:
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Quantitative Business Modeling
Jack R. Meredith ,
Scott M. Shafer , and
Efraim Turban
Manufacturer: South-Western College Pub
ProductGroup: Book
Binding: Hardcover
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Contemporary Strategy Analysis: Concepts, Techniques, Applications
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Managerial Accounting
ASIN: 032401600X |
Book Description
Rather than giving instruction in models and solving problems, this textbook focuses on the process of modeling and the use of models in analyzing various managerial situations. The process of modeling is highly relevant to all business disciplines and is a critical skill for all professionals. The emphasis of this text will be on the integration and development of modeling skills including problem recognition, data collection, model formulation, analysis, and communicating and implementing the results.
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