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.
Book Description
Learn math the fun way with FUNDAMENTALS OF ALGEBRAIC MODELING! Algebraic modeling concepts and solutions are presented in non-threatening, easy-to-understand language with numerous step-by-step examples to illustrate ideas. Whether you are going on to study early childhood education, graphic arts, automotive technologies, criminal justice, or something else, you will discover that the practical applications of mathematical modeling will continue to be useful well after you have finished this course.
Book Description
Computational science is a quickly emerging field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. However, limited educational materials exist in this field. Introduction to Computational Science fills this void with a flexible, readable textbook that assumes only a background in high school algebra and enables instructors to follow tailored pathways through the material. It is the first textbook designed specifically for an introductory course in the computational science and engineering curriculum.
The text embraces two major approaches to computational science problems: System dynamics models with their global views of major systems that change with time; and cellular automaton simulations with their local views of how individuals affect individuals. While the text is generic, an extensive author-generated Web-site contains tutorials and files in a variety of software packages to accompany the text.
- Generic software approach in the text
- Web site with tutorials and files in a variety of software packages
- Engaging examples, exercises, and projects that explore science
- Additional, substantial projects for students to develop individually or in teams
- Consistent application of the modeling process
- Quick review questions and answers
- Projects for students to develop individually or in teams
- Reference sections for most modules, as well as a glossary
- Online instructor's manual with a test bank and solutions
Book Description
The main methods, techniques and issues for carrying out multilevel modeling and analysis are covered in this book. The book is an applied introduction to the topic, providing a clear conceptual understanding of the issues involved in multilevel analysis and will be a useful reference tool. Information on designing multilevel studies, sampling, testing and model specification and interpretation of models is provided. A comprehensive guide to the software available is included. Multilevel Analysis is the ideal guide for researchers and applied statisticians in the social sciences, including education, but will also interest researchers in economics, and biological, medical and health disciplines.
Average customer rating:
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Introduction to Modeling and Control of Internal Combustion Engine Systems
Lino Guzzella , and
Christopher H. Onder
Manufacturer: Springer
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Vehicle Propulsion Systems: Introduction to Modeling and Optimization
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Automotive Control Systems: For Engine, Driveline, and Vehicle
ASIN: 354022274X |
Book Description
Internal combustion engines still have a potential for substantial improvements, particularly with regard to fuel efficiency and environmental compatibility. These goals can be achieved with help of control systems.
Modeling and Control of Internal Combustion Engines (ICE) addresses these issues by offering an introduction to cost-effective model-based control system design for ICE. The primary emphasis is put on the ICE and its auxiliary devices. Mathematical models for these processes are developed in the text and selected feedforward and feedback control problems are discussed. The appendix contains a summary of the most important controller analysis and design methods, and a case study that analyzes a simplified idle-speed control problem. The book is written for students interested in the design of classical and novel ICE control systems.
Book Description
In recent years the growing importance of derivative products financial markets has increased the demand for mathematical skills in financial institutions. The purpose of this book is to introduce the mathematical methods of financial modelling to provide a clear explanation of the most useful models. Introduction to Stochastic Calculus begins with an elementary presentation of discrete models, including the Cox-Ross-Rubenstein model. This book will be valued by derivatives trading, marketing, and research divisions of investment banks and other institutions, and also by graduate students and research academics in applied probability and finance theory.
Customer Reviews:
Very good.......2007-07-03
I am quite familiar with this book since I enjoyed it when it was used (along with many other good books as it should) in Purdue Computational Finance program. I got to do a number of exercises from it. Some Matlab code is available on my website (click on my name above).
A very efficient book for the right audience.......2007-01-21
Introduction to Stochastic Calculus Applied to Finance, translated from French, is a widely used classic graduate textbook on mathematical finance and is a standard required text in France for DEA and PhD programs in the field.
Most folks familiar with Steve Shreve's Stochastic Calculus Models for Finance will be surprised at its brevity, for this work is aimed at different audiences.
Whereas Shreve's work is aimed at mathematicians and physicists who are coming to finance, and building on the commonalities of understandings of time series and data sets and signals, Lamberton & Lapeyre's work is aimed at an audience of mathematically trained engineers, who look at data sets as information for solving problems. Shreve's work, is, therefore, to help people come up with mathematical proofs, and L&L's is to help people solve problems.
Both probabilistic and partial differential equation approaches are covered, so both those from electrical and telecommunication engineering and mechanical engineering will be satisfied and on familiar ground. Numerical and algorithmic methods are also covered for those with systems analysis and operations management backgrounds.
This book, however, is decidedly for those who have had significant mathematical training. Whereas with Hull, Wilmott, Neftci, or Joshi you can play around with their approaches almost instantly in Excel or other programming tools (VBA, C, etc.), Lamberton and Lapeyre's work is for those who think out loud with a white board and others do the dirty work of coding. This work lacks specific examples, data sets, etc. Which makes it difficult to place. Its clarity and brevity are welcome, and it expands the knowledge beyond Hull of those who are not trained in math and came up the practical coding grunt side of quantfin. But it also is not a complete theoretical treatment for the first string math and theory set.
In short, the book is what it is: a short primer on a large area of mathematics in finance for those well-trained in a variety of engineering and applied mathematical subjects. In other words, this book is for the French, because all the best French students are always Engineers first and something else afterwards. If you also happen to be trained as an engineer and find Hull, Wilmott, Joshi & Neftci too easy, and Shreve too hard, then this is the book for you. Or if you are like me, and you've banged your head against this stuff for years just through the happenstance of your career and want to see how a mathematician writes about your gritty world, this is a great book for shedding light in areas filled with cobwebs.
Clear and concise introduction to mathematical finance........2001-07-25
This book, translated from French, is by now a classic graduate textbook on mathematical finance, and provides a clear and concise introduction to the basic and important aspects of the theory. Although one of the first textbooks on the subject, it still remains in my opinion one of the best.
The book has been written for engineering students not mathematicians and avoids the theorem/proof format, going straight to essentials.
Also, while most textbooks on mathematical finance exclusively adopt either a probabilistic (like Baxter & Rennie) or a PDE approach to the theory (Wilmott et al, Wilmott), this book maintains the balance between the two aspects. Moreover, it does not neglect numerical methods and gives details on several algorithms for option pricing ( trees, Finite Difference, Monte Carlo) Finally, and perhaps this point is very important, the book maintains a reasonable volume while treating all these topics AND maintaining a high level of scientific rigor: all statements and notations are precise and oversimplification is avoided. Advanced topics such as variational inequalities for American options and HJM theory of interest rates are also included.
Some drawbacks of the book are: - a complete absence of empirical data/ real life figures - no description of various kinds of derivative products, why they are used,... But then, what can you ask for in such a small volume?
If you are an engineering/maths student and you want to discover what mathematical finance is about, I recommend you this book instead of John Hull's book.
A good INTRODUCTION to ONE part of finance.......1999-03-14
As precisely mentioned in the title, this book is only an introduction; and it is not an introduction to finance, but to stochastic calculus applied to finance.
The buyer of this book should therefore be aware of three facts:
1. After having read this book you are not (yet) an expert on stochastic calculus applied to finance. You have to continue with other books mentioned in Lamberton/Lapeyre. But this book is an excellent framework that leads you to many important results, omiting proofs that are only technical.
2. Mathematics is used in many other areas of Finance too (Time Series Analysis for example). What is treated in this book is only a very small part of Finance Mathematics, but an important one.
3. One should read another book with more economic background at the same time.
The authors begin with discrete-time models to present many important ideas in a (mathematically) simple environment before treating the contiuous models. Introduction to stochastic integration and stochastic differential equations is brief. Stochastic integration is only with respect to the standard browning motion. After having reached the Black-Scholes model and american options, the approach via partial differential equations is treated, followed by interest rate models, models with jumps and, a good idea: a chapter on simulations.
The book has very few mistakes, no important ones, only a strange layout failure on pages 6 to 7.
So I highly recommend this book as an INTRODUCTION to ONE important part of finance mathematics if read in combination with another book with more economic background. It can especially be used for upper graduate student seminars or as a basis for lecture courses.
A stochastic approach of finance for engineers!.......1998-07-28
The french initial version of this book has been one of my first technical papers that deal with stochastic calculus towards finance. It is written by and for engineers I must admit, but students in actuarial sciences (like me) won't be lost by so many formulas and equations if they agree to read with a piece of paper and a pencil on the hand. I have worked on the Vasicek's model and the simulations described have helped me a lot. Too bad that the lattice model is not explored. Anyway it is a good preparation before the opening of "Brownian Motion and Stochastic Calculus" from Karatzas & Shreve.
Average customer rating:
- A great supplement and right sized for travel too!
- thought that this book was wonderful, but...
- Great on algorithm design, not that good on analysis
- Not good for beginners
- fantastic
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Introduction to Algorithms: A Creative Approach
Udi Manber
Manufacturer: Addison Wesley
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Introduction to Algorithms
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Oracle 10g Programming: A Primer
ASIN: 0201120372 |
Customer Reviews:
A great supplement and right sized for travel too!.......2007-01-25
I really like this book as a supplement to the algorithm bible (Introduction to Algorithms, Thomas Cormen et al). This book is tiny and portable yet every major algorithm is covered. Basics, like mathematical induction are reviewed and illustrated with relevant examples.
One of the ways that Udi Manber packs so much information into such a small package is by keeping verbosity to a minimum. In his proofs, only the most complicated steps are justified or explained. As a result the reader may find herself spending time justifying steps in the proofs that are unrelated to the problem at hand. I did not mind doing this; others may. Regardless, the persistent reader will find that within the pages of this book lies all of the information required to understand all of the algorithms covered (and of course, it never hurts to keep a notebook, pencil and several erasers handy).
I would not recommend this book as a reference; rather, it provides a refreshingly new perspective on algorithms that may seem old and dusty. I've spent more time and energy per page on this book than any other CS book I've had but the ROI has been well worth the effort.
thought that this book was wonderful, but..........2006-04-10
...I changed my mind after trying to use this book alone to implement FFT. Its description is quite clear and simple, much simpler than the Rivest et al book or wikipedia. Unfortunately, though clear, it is not complete and it is not possible to actually implement FFT using this book alone. I ended up having to use the Rivest et al book (which I had on CD via DDJ) along with this book to implement it. (Wikipedia was truly hopeless for trying to understand the FFT algorithm.) I was able to implement FFT in a single page of Python code because of Manber's description.
For giving very simple explanations of a number of algorithms, this book is fantastic. Just don't rely on it for the technical details.
Great on algorithm design, not that good on analysis.......2005-04-25
I like this book a lot. I think it's a good reference and introductory text, maybe as a supplement. It's much easier to read than Cormen's, but not half as deep.
Pros:
- Easy to read. You can understand an algorithm much faster if you go to this book first.
- Good examples and pictures.
- Explain the ideas that lead to efficient algorithmic designs.
Cons:
- Doesn't go into enough details about the proofs of correctness and complexity.
- The approach is different than most books and may take some time to get used to.
Not good for beginners.......2004-07-08
The book is complete and correct, no argument there. However, I had a lot of trouble learning from it. I had to re-read the same paragraph a number of times in order to derive comprehensive meaning from the author's scant explanations. The author usually walks through a sample problem, but then provides little or no guidance for solving an arbitrary problem of the same type. Likewise, although the book centers on induction, it was extremely difficult to follow with no prior induction education.
The author often presents the answer to some given problem with words like "obviously" or "clearly" without making things at all clear or obvious to the student. I kept wishing that the author wouldn't be so tight-lipped and would spend some extra time clarifying the issues at hand.
fantastic.......2003-10-25
It's a very perfect book to become familiar with main
methods of producing effective algorithms.
Average customer rating:
- Great Book for Anyone
- Great interdisciplinary book on environmental modeling
- Modeling the Environment
|
Modeling the Environment: An Introduction To System Dynamics Modeling Of Environmental Systems
Andrew Ford
Manufacturer: Island Press
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Dynamic Modeling of Environmental Systems (Modeling Dynamic Systems)
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Understanding Capitalism: Competition, Command, and Change
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Capitalism 3.0: A Guide to Reclaiming the Commons (Bk Currents)
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Dynamic Modeling (Modeling Dynamic Systems)
ASIN: 1559636017 |
Book Description
Modeling the Environment is the first introductory textbook for a technique of rapidly growing importance. It requires little or no mathematical background, and is appropriate for undergraduate environmental students as well as professionals new to modelling. Developed from the author's own introductory course, it is classroom-tested and represents an important contribution to the field of system dynamics.
Modeling techniques that allow managers and researchers to see in advance the consequences of actions and policies are becoming increasingly important to environmental management. The models produced are vital analytical tools that aid the policy-setting and implementation process, and help us to understand how environmental systems respond to management interventions.
Modeling the Environment is a basic introduction to one of the most widely known and used modeling techniques, system dynamics. The book is designed to build the skills of students as they progress from learning fundamental ideas to constructing models of increasing complexity. Written in a clear and comprehensible style, the book:
- presents basic concepts of modeling using system dynamics
- illustrates the mechanics of model construction through a range of working models
- offers a rich array of exercises for students to use in applying the principles and techniques described in the text
- walks students through the design and application of models of specific types of environmental systems
.
In addition, the book contains more than 300 figures and model illustrations, and provides a guide to an interactive website where students can use the text to "navigate" management flight simulators ? models of both real and hypothetical systems developed by the author. The book also contains appendixes that help students review the necessary math, and which provide additional concepts and exercises for further study.
Customer Reviews:
Great Book for Anyone.......2006-12-12
This is a great book for anyone who wants to gain a thorough understanding of Stella software. The book is easy to read, and the examples and case studies are well chosen.
Great interdisciplinary book on environmental modeling.......2000-05-24
A highly readable introduction to environmental modeling. What distinguishes the book from other environmental science and environmental modeling works is its interdisciplinary treatment. In particular, the models integrate the physical world and the world of human behavior. Far too many environmental models fail to close the feedbacks between human behavior and the state of the environment, instead taking waste inputs or resource use as exogenous. This book helps students learn to model human behavior (social and economic) as an integral part of the ecological system. The models and software mean the book encourages active learning, and enable students to explore important issues on their own if they choose.
Modeling the Environment.......2000-04-24
This book is easy to read and contains clear examples of how to use stella software to model the environment. The marvel here is the software, not the book. For the software timid, it might suppliment the software users guide.
Book Description
Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets, illustrate the various modeling procedures and a concluding chapter provides a brief introduction to a number of more advanced topics, including Bayesian inference and spatial extremes. All the computations are carried out using S-PLUS, and the corresponding datasets and functions are available via the Internet for readers to recreate examples for themselves. An essential reference for students and researchers in statistics and disciplines such as engineering, finance and environmental science, this book will also appeal to practitioners looking for practical help in solving real problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the first recipient of the Royal Statistical Society's research prize. He has published widely in the statistical literature, principally in the area of extreme value modeling.
Customer Reviews:
Practical text on extreme values statistics.......2006-11-10
Stuart Coles, who is well published on the open literature, has delivered this practical text on extreme values statistics by providing extreme values theory in a simplified manner with worked examples. Further, Coles has removed much of the complicating aspects (long mathematical proofs and overly complex notation) typical of statistical literature. The text provides any engineer or scientists with the tools required to complete routine extreme values analysis.
A clearly written intro book on extremes.......2002-10-05
I recently used the software accompanied to this book kindly made available by the author and was led to know more about this book and the author's other works. I like what I saw and think the author has done a supeb job in explaining the difficult theory in plain language and in the context of data analysis. Thus it is an "action" book instead of the "just theory" as with most other books. The book provides a balanced treatment of different approaches to extreme value analysis. Personally I prefer the generalized Pareto approach, though theoretically the point process approach may be very neat, if it can be realized.
I think extreme value theory in general is an important statistical area, since in practice one may be forced to deal with analyzing extreme events, such as in financial engineering, environmental or climate analysis, or network design. I wholeheartedly recommend this book for anyone who want to learn this area from one of the leading researchers.
well written with a nice mix of theory and application.......2002-01-29
This book is the most current text available on the theory of extreme values. The author eloquently provides us with an understanding of the theory and it vast applications. It is intended for researchers students and practitioners. So it provides an in-depth account of the theory with many real world examples. It contains an excellent up-to-date bibliography. Important theorems are presented with their implications but without mathematical proofs. Computations are done in SPlus. The author provides an appendix on computational aspects that tells the reader where to go to download examples and find the SPlus functions that are used.
Topics include classical extreme value theory and models, threshold models, extremes in dependent stationary cases, extremes for some nonstationary stochastic processes, the point process approach, multivariate extremes and some special topics including extremes in spatial processes and the Bayesian approach to extremes (with examples employing MCMC methods).
Book Description
In todays information age, scientists and engineers must quickly and efficiently analyze extremely large sets of data. One of the best tools to accomplish this is Interactive Data Language (IDL®), a programming and visualization environment that facilitates numerical modeling, data analysis, and image processing. IDLs high-level language and powerful graphics capabilities allow users to write more flexible programs much faster than is possible with other programming languages.
An Introduction to Programming with IDL enables students new to programming, as well as those with experience in other programming languages, to rapidly harness IDLs capabilities: fast, interactive performance; array syntax; dynamic data typing; and built-in graphics. Each concept is illustrated with sample code, including many complete short programs.
·Margin notes throughout the text quickly point readers to the relevant sections of IDL manuals
·End-of-chapter summaries and exercises help reinforce learning
·Students who purchase the book are eligible for a substantial discount on a student version of the IDL software
Customer Reviews:
A Book for Beginning IDL Users.......2006-01-27
Nothing is more intimidating to a new user of IDL than to sit down at a computer with an empty command line prompt and a stack of manuals on their desk and be told to write an IDL program. Where to begin!? And the experience is especially frightening to a new user with little or no programming experience in any language, let alone IDL.
Ken Bowman has written an IDL book specifically for this user. It is intended as an introductory computer programming course for the research user with little or no training in any computer language, and it evolved from notes Ken uses in his own undergraduate IDL programming courses. It is meant to get the new IDL user analyzing and plotting data as soon as possible.
It is a narrow path he treads, because it is just as easy to offer too much detail as it is to offer too little information to the beginning user. Ken, for the most part, gets it exactly right in covering a broad selection of topics. I quibble with just two chapters. He sweeps aside the complexity of PostScript output by offering the new user two utility programs he fails to explain in the text, and his theoretical explanation of the FFT function left me gasping for breath and lamenting I hadn't paid closer attention in those long-ago math classes.
This is a book that will get you started, but probably won't answer all your questions when you turn your attention to more difficult research problems. Ken doesn't pretend it is anything other than what it is, however, and provides generous and helpful suggestions for where you can find additional information as you become ready for it. Readers already familiar with another programming language will appreciate this introduction to IDL, but might become frustrated with the slower pace and lack of specific detail on many topics.
The book has an associated web page, where you can find, among other things, the source code for all the programs mentioned in the book. Pay particular attention to the Errata section, especially if you are interested in structures in IDL. A printer glitch removed all the curly brackets from Ken's IDL code in the structure chapter and none of the examples will work as written in the book. A software problem, no doubt. (The example programs for the chapter are correct.) It serves as a reminder to me of how complex a topic software programming can be. This friendly book will be a welcome introduction to the subject for many a potential IDL programmer.
Books:
- An Introduction to Systems Biology: Design Principles of Biological Circuits (Chapman & Hall/Crc Mathematical and Computational Biology Series)
- An Introduction to Systems Biology: Design Principles of Biological Circuits (Chapman & Hall/Crc Mathematical and Computational Biology Series)
- Animal Architects: Building and the Evolution of Intelligence
- Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence
- Applied Numerical Methods with MATLAB for Engineers and Scientists
- Applied Numerical Methods with MATLAB for Engineers and Scientists
- Applied Numerical Methods with MATLAB for Engineers and Scientists
- Bioaerosols Handbook
- Brief Calculus: An Applied Approach
- Children's Mathematics: Cognitively Guided Instruction
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