Book Description
The last decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.
The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.
Customer Reviews:
Excellent book in time series.......2007-06-29
I don't think there is another book out ther that would outperform this book in time series econometrics. A must have if you are a graduate student in economics.
No complaints. .......2007-02-14
No complaints. I received the book before deadline and book is same as descrition. 100% recomended seller
Absolutely Excellent (for what it is).......2007-02-06
Hamilton is often dubbed, "too hard to understand." That may be true, but actually it seems to be much more reasonable and readable than other econometrics texts I have attempted to read.
I would definitely not start out into econometrics with this book though. You probably will not be able to appreciate how good this book is until you have tried to read something as atrocious as Greene.
As is typical with almost every upper level econometrics book, it assumes you have a wide mathematical and statistical knowledge base that you may or may not have. I would not recommend it as a beginning graduate econometrics book but it is a great reintroduction to time series methods. I will say that I haven't found a single book yet in intermediate econometrics that I felt was written clearly or concisely.
Still, overall, this has been by far the best among the worst and I would highly recommend reading it to anyone who is beginning to study time series econometrics in some detail.
Awesome book for TS.......2006-03-06
If you are thinking of mastering TS this is the book to start with. Do not get intimidated however with all the symbols and notations, the author does a pretty good job explaining each and every equation. A seperate book is needed for application eg RATs handbook by Enders.
A review of Time Series Analysis.......2005-08-05
The book provides a good overview of the analysis of time series and it also gives a good treatise of the economitric background of the use of estimation methods.
Average customer rating:
- Good Companion Book
- Good book
- Very thoughtful and clear explanation of financial math
- sophisticated maths
- Remarkable Introduction to Serious Math, Serious Finance, and Real-World Applications
|
Introduction to the Mathematics of Financial Derivatives
Salih N. Neftci
Manufacturer: Academic Press
ProductGroup: Book
Binding: Hardcover
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Similar Items:
-
Options, Futures and Other Derivatives (6th Edition)
-
Principles of Financial Engineering (Academic Press Advanced Finance)
-
Financial Calculus : An Introduction to Derivative Pricing
-
Heard on the Street: Quantitative Questions from Wall Street Job Interviews
-
Stochastic Calculus for Finance II: Continuous-Time Models (Springer Finance)
ASIN: 0125153929 |
Book Description
This popular text, publishing Spring 1999 in its Second Edition, introduces the mathematics underlying the pricing of derivatives. The increase of interest in dynamic pricing models stems from their applicability to practical situations: with the freeing of exchange, interest rates, and capital controls, the market for derivative products has matured and pricing models have become more accurate. Professor Neftci's book answers the need for a resource targeting professionals, Ph.D. students, and advanced MBA students who are specifically interested in these financial products. The Second Edition is designed to make the book the main text in first year masters and Ph.D. programs for certain courses, and will continue to be an important manual for market professionals.
Customer Reviews:
Good Companion Book.......2007-08-29
good companion book for the other book "Principles of Financial Engineering" by the same author
Clear and easy to understand treatment. The author does not assume a high level of math knowledge of the reader.
Good book.......2007-05-09
As title states this is a good Introduction to the mathematics of derivatives.
If you're looking for some book with C/C++/C#/Java code samples this isn't the book. Indeed a good mathematical introduction; its pre-requirements are a good mathematical and statistical ones.
Very thoughtful and clear explanation of financial math.......2007-02-05
I turn to this book after I get frustrated with Tomas Bojork's book "Arbitrage Theory in Continuous Time." As I am not from a strict math background, this Neftci's book makes much more sense to me. What I particularly like about this book is explanation in plain English of why the mathematical formulae are so, and how they are connected to the bigger picture. Also Neftci has a good grasp of how many real-life examples included in this book so that it doesn't lose its focus on the real math in finance.
sophisticated maths.......2006-06-16
Neftci takes us on a mathematically sophisticated tour of financial derivatives. The treatment is on a level akin to a senior-level undergrad text on physics or engineering. Indeed, to a reader who might come from that background, there will be a lot of similarities and familiar ideas.
For example, partial differential equations arise naturally in the pricing of derivative assets. But unlike many places in physics, here it is not sufficient to assume smoothly varying variables. The inherently discrete nature of most financial variables means that derivatives have to be approximated numerically.
Neftci also describes the various types of options, like basket, knock-out, multi-asset and so on. Each has a slightly different modelling. Another key idea involves the time aspect of pricing. So Wiener processes naturally arise, and the text shows how to handle these.
Much more is covered in the book. Perhaps just as importantly, it gives you enough maths preparation that you should be able to analyse other new types of financial instruments. Maybe even ones that you create yourself.
Remarkable Introduction to Serious Math, Serious Finance, and Real-World Applications.......2006-06-14
Neftci's book is easily grouped into a large number of texts that provide graduate level (considerable more rigorous than the MBA version) introductions to mathematical finance. Some are written for MBA with want to be exposed to as little math as possible without short changing the financial and valuation aspects and with considerable attention to a broad range of financial products and applications (Hull's classic comes to mind). Others are extremely implementation driven and are more a hybrid of finance and computer programming (Duffy, London, Wilmont). Still others are math books that speak above the heads of almost all practitioners and cover the finance topics poorly (or not at all).
Netfci's book is a rare gem in this field. Excellent coverage of financial topics and fundamentals (Arbitrage Theorem, Forwards Futures, Equity Derivatives, Interest Rate Derivatives), serious graduate level review of financial math and mathematical techniques (Probability, Numeric Processes, Binomial Methods, Stochastic Calculus, Finite Difference, Martingales, Monte Carlo methods), and applications (Bond Pricing, Term Structure Modeling, Exotic Options, Rare Event Modeling).
Best of all, it start assuming very little, builds aggressively, and progresses logically.
The biggest drawbacks are a lack of coverage for credit modeling and credit derivatives, Merton-model and contingent claim models for distressed equity, and more common financial engineering applications (hedging, rebalancing).
It is also remarkable well-written.
Average customer rating:
- Excelent reference both for theory and practice
- A definite guide
- bloated
- Convex Optimization
|
Convex Optimization
Stephen Boyd , and
Lieven Vandenberghe
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Hardcover
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Similar Items:
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Matrix Analysis
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Numerical Optimization (Springer Series in Operations Research and Financial Engineering)
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Nonlinear Programming
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Combinatorial Optimization: Algorithms and Complexity
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Matrix Computations (Johns Hopkins Studies in Mathematical Sciences)(3rd Edition)
ASIN: 0521833787 |
Book Description
Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.
Customer Reviews:
Excelent reference both for theory and practice.......2006-03-02
The book provides sound theoretical basis in a non-intimidating way. It also presents many examples that help the reader understand and relate his or her specific needs to general convex optimization problems. I think this book is a really good compromise between theory and practice: it can please the more mathematics-oriented with proofs, definitions, and bibliography; as well as the more application-oriented with examples, implementations, and heuristics. The authors have been very generous in allowing the free download of the full book from their website.
A definite guide.......2006-01-15
The book excels in readability and style. A perfect balance on the theoretical and practical aspets of the convex optimization. As the name implies, and also as the authors put in preface, it is about recognizing, formulating, and solving convex optimization problems. Provides necessary mathematical background in the first part---not as deeply as a gradute level convex analysis book---and therefore helps reader build a working knowledge. If something is not covered in this part but essential for a working knowledge, then it is in the appendices for sure. Provides a wealth of examples, exercises, and applications. Perfect for self-study as well as classroom use.
bloated.......2005-12-02
as most engineering books, this one lacks depth and rigor. the development of the theories is often cluttered with TOO many examples.
this seems a swing to another extreme from most mathematical books where the naration is often too formal and lacks examples. (that old fool Rockafellar's book doesn't have one single figure in the entire book!)
IMHO, something in between is needed.
Convex Optimization.......2005-05-03
This is an absolutely wonderful work on the subject. It delivers precisely what the preface promises -- a very comprehensive introduction to convex optimization for users. Moreover, it delivers far more, for it is incredibly well-written and unusually accessible. It's a joy to read.
Book Description
APPLIED REGRESSION ANALYSIS applies regression to real data and examples while employing commercial statistical and spreadsheet software. Covering the core regression topics as well as optional topics including ANOVA, Time Series Forecasting, and Discriminant Analysis, the text emphasizes the importance of understanding the assumptions of the regression model, knowing how to validate a selected model for these assumptions, knowing when and how regression might be useful in a business setting, and understanding and interpreting output from statistical packages and spreadsheets.
Customer Reviews:
Great Minitab Resource.......2007-05-15
Dr. Dielman was a professor of mine. The book is well organized and useful for all people on all levels.
Excellent.......2006-12-26
For my class, the professor assigned Kleinbaum et al's textbook rather than this one. As I mentioned in my review for that book, it was so confusing and poorly organized. Luckily, I found this book in the library and used it instead and ended up a lot less confused in class than my classmates who were trying to understand the Kleinbaum book. Dielman's book is very well organized and laid out. It doesn't have colorful bells and whistles since it's a fairly upper level book, but it does have a very user-friendly layout. Furthermore, the formulas are never presented without an accompanying explanation in plain English and examples of how and when to use them. Another thing I really like about this book is that it gives thorough directions on how to do a lot of the analyses on some common statistical packages. Many of the instructions are accompanied by screenshots. They're at the end of each chapter rather than interspersed in the text, which makes them easy to find. This is actually becoming a great SAS manual for me.
For anyone struggling with the Kleinbaum book, or for any instructor considering using the Kleinbaum book, I would highly recommend this one instead.
A Cross-platform textbook.......2006-05-15
I have bought Dr. Dielman's Applied Regression 4e textbook in Taiwan) for preparing my MBA thesis regarding the interaction effects. Given the widespread use of commercially available packages, this book provided considerately coverage on ALL computer packages about the field of regression work.
Book Description
This book is a revised, updated and greatly expanded version of the authors' "Probability and Random Processes: Problems and Solutions", first published in 1992. The 1000+ exercises contained within are not merely drill problems but have been chosen to illustrate the concepts, illuminate the subject, and both inform and entertain the student. Topics cover a broad range of subjects, including: elementary aspects of probability and random variables; sampling; Markov chains; convergence; stationary processes; renewals; queues; Martingales; diffusion; mathematical finance and the Black-Scholes model. This text is intended for general use, and to serve students as a companion text for elementary, intermediate and advanced courses in probability and random processes. Useful for anyone needing a large source of problems in these areas and at all levels. This book also acts as a companion volume to the new edition of Probability and Random Processes 3/e, (OUP - 2001), providing the solutions for the problems and exercises.
Customer Reviews:
Great, fast.......2006-03-18
I get the book soon even if I make a mistake for the address!
On balance, this is a great book.......2002-08-29
Grimmett & Stirzaker's book, *One Thousand Exercises in Probability, 2nd ed.,* contains exercises with answers/solutions to each and every exercise covering a wide range of topics from probability. Although this book is a companion to G & S's 3rd edition of *Probability and Random Processes,* the authors strove to make the *Exercises* book stand on its own.
The 2 previous reviewers took a widely different view of this book. I wanted to have a balanced approach to reviewing this book. I hope this helps.
-- This book has exercises that cover a wide range of topics in probability. It starts from basic issues in probability and eventually covers topics like queueing, Monte Carlo (& Markov Chain Monte Carlo), Ito's lemma & financial option valuation, etc. Any one vaguely interested in probability realizes that the topics covered by Grimmett & Stirzaker are *hot topics* and very useful to those who want to try to get a sense of how important probability theory is in real life. I can't think of a comparable book that is so ambitious and covers so much useful ground in one place. [At least not one with answers to every question.]
-- I am not personally familiar with Grimmett's work (I believe he is at Cambridge University). I am, however, familiar with Strizaker's work (he is at Oxford). I consider him to be one of the finest expositers of probability theory. Stirzaker's views on probability theory (which I read in a different work) is one of the most lucid and sensible I have ever come across. Anyone seriously interested in probability should try to get exposure to Stirzaker's thoughts on the matter.
-- I believe this book is GREAT for self-study. One of the major problems I have with many math, science, engineering, and other technical books is that -- even very good books -- do not provide answers/solutions to the questions they pose. As someone who is very interested in self-study, I find a book like this one -- which has the answers/solutions to ALL of the questons -- to be extremely refreshing and welcomed.
To address the prior criticism that this book does not contain a sufficient amount of detail in the solutions .... I would suggest that such a criticism is unfair. As I pointed out above (and most people know) it is very rare to have technical books like this where there are a great deal of interesting and useful exercises given plus answers/solutions to all of the questions posed. For 2 emminent Oxbridge dons to write such a book is even more exciting.
In all fairness, Grimmett & Stirzaker wrote this book with the intent that it be used along with an appropriate probability textbook(s). Any one willing to take the time to look at the solutions given along with a companion text should be able to work out what went wrong (or right) with any question that the reader attempts to work out.
In closing, I highly recommend this book to anyone who is interested in going from a novice level at probability to a point where you can approach and solve useful problems in probability.
Well worth the effort.......2002-01-18
I appreciate the other reviewer's oppinion as it is indeed true
that some of the problems' solutions are succinct.
However it is clearly not the point of the set of books to provide
the reader with fully worked solutions to every problem. It is
often like this in maths, you just got to go for it, no matter.
If you kick off from the first chapter and attempt the problems
in increasing order of diffculty keeping the course book by your
side, you should be fine, really.
This course is very rewarding.
Lots of answers, not many solutions.......2002-01-10
This book was a big disappointment for me. I give it two stars for providing the answers to the problems. It would get much more if it actually provided adequate solutions to the problems. It is a good book if you know basically how to do the problems and just want to check answers. I guess I'm just stupid because I could use some guidance for starting and proceeding through the problems. The "solutions" often omit what I would deem to be crucial startup steps for many of the problems; without those critical steps, the "solution" that is given (which sometimes consists of nothing but the final answer) can be extremely difficult to comprehend. I had high hopes when I purchased this book; I thought it would be well worth my money to get solutions to the problems so I could figure out the errors in my reasoning. Unfortunately I was gravely mistaken.
Other reviews indicate that this is typical and I would agree, it's not written to those who need help but those who have a strong grasp on the topic. It doesn't matter to me who has written a book, if it's not helpful it's just not worth the money.
Book Description
In the 2nd edition some sections of Part I are omitted for better readability, and a brand new chapter is devoted to volatility risk. As a consequence, hedging of plain-vanilla options and valuation of exotic options are no longer limited to the Black-Scholes framework with constant volatility.
The theme of stochastic volatility also reappears systematically in the second part of the book, which has been revised fundamentally, presenting much more detailed analyses of the various interest-rate models available: the authors' perspective throughout is that the choice of a model should be based on the reality of how a particular sector of the financial market functions, never neglecting to examine liquid primary and derivative assets and identifying the sources of trading risk associated. This long-awaited new edition of an outstandingly successful, well-established book, concentrating on the most pertinent and widely accepted modelling approaches, provides the reader with a text focused on practical rather than theoretical aspects of financial modelling.
Customer Reviews:
Excellent introductory book to financial math.......2006-11-03
This book takes you through the math of finance step-by-step, passing through very simple examples first and then slowly adding complexity to the models studied. It is written very clearly and the prerequisites to reading this book are only some basic notions of probabilities (sigma-fields, probability measures).
Sometimes, the problem with math books is that they are "dry" and contain only a succession of theorems and proofs. In this one, the authors make a point of explaining in detail how different theorems and models relate to each other, and make extensive comparisons between them so that you get a better feel for how they work in practice.
The book is primarily a math book and can be light on market specifics. Do not buy this book as a practical "howto" in derivatives trading.
At the Forefront of Modern Mathematical Finance.......2005-05-23
This advanced text provides an excellent account of the current state-of-the art of options pricing/hedging models and interest rate term structure models. The book is accessible to both advanced practitioners of mathematical finance as well as to pure researchers in the field.
The book is in written in a mathematical style and contains rigorous proofs of many results. However, the main focus of the text is to describe the frontier of knowledge in the subject. Each section contains copious references to the literature and is so current that several references are to working papers. Many sections detail open problems and other areas suitable for scholarly research.
In their second edition, the authors provide an extremely useful critique of each modeling paradigm that they investigate. They also provide evidence for their position in the form of literature references which instruct the reader as to the shortcomings/limitations of a particular model. This information should prove quite valuable to model practitioners and implementers.
The authors assume an advanced background from the field of stochastic analysis, although they do provide an appendix which summarizes key results needed from the field. For the stochastic calculus prerequisites, I recommend Rogers & Williams "Diffusions, Markov Processes and Martingales" volumes I and II. Suitable prerequisites are also covered by Karatzas and Shreve in "Brownian Motion and Stochastic Calculus" 2nd edition. A good foundation in arbitrage pricing theory is also needed. I recommend the nice treatment by Bjork in "Arbitrage Theory in Continuous Time" 2nd edition.
The book is divided into two parts. The first part deals with options pricing in equity markets. Chapter 1 sets premlinaries required for the arbitrage theoretic framework, while Chapter 2 has a very nice treatment of discrete time models and finite financial markets.
In Chapter 3, the authors develop the Black-Scholes model along with the Bachelier model using arbitrage techniques. The models are compared and used as benchmark continuous time models and form the basis for all subsequent analysis.
Chapter 4 provides a nice survey of techniques used to price/hedge options in foreign equity and currency markets. The authors assume familarity of the basic workings of foriegn markets.
Chapter 5 is a terrific chapter on valuing American-style options. The American call option is thoroughly studied and approximation techniques for the American put option are introduced. The explicit derivations of the formulas are referenced to the literature.
Chapter 6 provides an introduction to exotic options, although the authors vary their use of the term 'exotic' to meaning 'not a standard European-style or American-style' in this chapter to meaning 'no readily available liquid market' in Chapter 7. The descriptions are quite accessible and the basic properties of the options are described along with pricing formulas (assuming the Black-Scholes framework).
Chapter 7 provides as complete an accounting as I have ever seen of the generalizations of the Black-Scholes model and motivates this from the point of view of volatility surfaces. Many of the well-known models are studied in detail, such as CEV, local volatility, and mixture models. The strengths and weaknesses of each model are analyzed. The stochastic volatility models of Wiggins (via Orenstien-Uhlenbeck processes), Hull-White, and Heston are studied, as is the SABR model. The chapter wraps up with a study of the SIV models, describes how the stochastic volatility models can be obtained via limits of GARCH models and surveys Jump-diffusion processes and Levy processes.
The second part of the book is concerned with term structure models and interest rate derivatives. The authors are quite well-know for their many contributions to this study and their treatment is authoritative.
Martingales & Finance.......2003-04-12
I have used this book for two courses in my MSc degree in Financial Maths...well this book is hard to understand at first glance, but, once you are introduced with a good course on stochastic analysis and applied probability, this is an illuminating book...I particularly enjoyed the part on foreing equity derivatives and exotic derivatives.....Harmed with patience this is definitely the book by which you can effectively gain a sound a knowledge on modern mathematical finance theory....reading in conjunction with Bingham-Kiesel book, could help understanding the foundation of the subject.
yes, but ..........2000-03-17
I've been using this book on and off over the last year. At first I was very impressed with the level of detail in the mathematics, especially as it was the only book at the time focussing on risk-neutral methods and covering BGM. But I've become increasing disillusioned with it of late. It's difficult to explain, but although the whole book is written in traditional theorem-proof style, there are no real proofs! (I have a PhD in math and have done research for 10 years so I should know a little about proofs.) The only "proofs" provided are basically symbol shifting, but the heart of the math is strangely absent. This is especially strange given the Springer series in which it appears.
In short, if you want a catalogue of methods this book does the job, but if you want a deeper understanding try Lars Nielsens book.
excellent book for post-John-Hull readers.......1999-08-17
This book covers essentially everything needed for a serious financial math study. It captures the spirit of modern financial math. For people with math, physics or engineering background, when you feel comfortable woth John Hull's books, then this book is right one, and a must one.
Book Description
Focusing on the many advances that are made possible by simulation, this book describes the new generation of discrete choice methods. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Download Description
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum simulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. No other book incorporates all these fields, which have arisen in the past 20 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Customer Reviews:
An excellent and thorough book.......2006-03-08
This book is one of the best for introduction to Discrete choice models. I had been using Ben-Akiva & Lerman, but feel this book should be read along with that one for a better understanding of choice models. Also, Train covers recent advances in the field and provides a good introduction to Halton draws. He really makes sure you get the concepts and the online lecture series are really excellent.
Probably the best of its kind. Good for MS students and up .......2005-04-24
-Enjoyable read
-Does not assume PhD level of econometrics
-Explanations are clear and concise
Actually, an advanced undergrad may find this book usefull as well.
Is this the best discrete choice methods book ever published?
Let y = 1 or 0 where 1 = yes, this is the best and 0 = No, the book is not the best. Also let P = Prob (y=1). My results show P = 0.98 (see forthcoming Econometrica article).
While finishing a Master's Thesis in applied econ which focuses on a multinomial logit model, I have sought good info on this topic. Not having gone through the rigors of a PhD program, I have gone through many of the important books and articles which address discrete choice modeling methods some of which address a post-doc audience only. Dr. Train's is by far the best I have encountered. His explanations are concise yet not too dense (see Amemiya). I first encountered many of the concepts in other publications but did understand them until reading Train's book. In my opinion Train has that rare quality of being, not only an exceptional economist, but quite enjoyable to read.
excellent discussion of what the models mean.......2005-03-17
If I could give this book six stars I would. It's simply one of the best statistics books I've ever read.
This book is very well-written by one of the experts in the field. It covers logit models and the various generalizations (GEV, mixed logit, probit, etc.) in detail, along with a thorough discussion of modern estimation of these models. What I find most useful about it is that the words-to-equations density is highly favorable. The equations you need are there, but the words you need are there too, making sure you understand the model assumptions inside and out. Each equation is explained thoroughly and the surrounding discussion probes the model to bring the reader to a critical understanding of what exactly is implied by the model. Too often complex statistical models are treated in a "black box" fashion. The dirty little secret is that it's easier for the author to do this. Train doesn't take the easy way out. The fact that his web site has truly excellent support--including a large number of webinars in addition to the more usual papers, software, etc.--makes this book a doubly valuable item. See http://elsa.berkeley.edu/~train/distant.html for even more.
Book Description
This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied in economics, engineering, and the natural and social sciences. The book assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This second edition contains detailed instructions on the use of the new totally windows-based computer package ITSM2000, the student version of which is included with the text. Expanded treatments are also given of several topics treated only briefly in the first edition. These include regression with time series errors, which plays an important role in forecasting and inference, and ARCH and GARCH models, which are widely used for the modeling of financial time series. These models can be fitted using the new version of ITSM. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include the Burg and Hannan-Rissanen algorithms, unit roots, the EM algorithm, structural models, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introductions are also given to cointegration and to non-linear, continuous-time and long-memory models.
Customer Reviews:
good basic intro.......2006-11-10
A decent basic introduction covering a lot of topics. It's much more accessible for learning the subject for the first time then many other books which pile on the mathematical notation and obscure the actual meaning of things. The accompanying CD is very nice, although it gets annoying very fast that you're restricted to very small dataset sizes---but it does help in learning. The only two things that are somewhat of a problem with this book are 1) many times, rather than clearly stating "here's the algorithm you need to implement", you are referred to 3 or 4 other sections of the book for pieces of the algorithm, often without a clear explanation of exactly how that earlier section is supposed to be worked into the current desired algorithm and 2) there aren't a lot of practical insights as to how to actually initialize many of the algorithms (everything is great if you already know all the parameters in advance but starting from scratch with just raw data isn't dealt with I think as fully as would be useful). All in all, though, the book is helpful and, as I said, very good for learning the essential concepts for the first time.
When is an Introduction not an Introduction?.......2006-11-05
In the process of building a website targeted to those good folks that are striving valiantly to make a living through Internet marketing, you might think that an early objective would be to assemble a library of good reference material. After all, if you are planning on providing sensible information to your readers, then you should have a few good text books on hand to refer to when you need to be sure that some little tidbit of information might actually work. Well, at least I did. So, I have been scouring the Internet for textbook on the subject of Forecasting, which we share a common interest in. I have purchased a few and, for the most part, they are really quite informative and will be useful when the time comes. There is, however, an exception to this.
One book I purchased bears the title "Introduction to Time Series and Forecasting, Brockwell, Peter J and Richard A Davis". Being an intelligent sort of chap, I naturally took the word "Introduction" to mean just that. You know, you've been introduced to people before and becoming introduced usually means that 1. You look at the face. 2. You grasp their hand and shake firmly and 3. You exchange pleasantries, such as "Hello, it's nice to meet you".
Now, I never blame the person making the introduction if the relationship doesn't work out. After all, it's not their fault that two people hopefully sharing a common interest (after all, why bother making an introduction?) aren't all that compatible. There are likely to be many reasons for the incompatibility, the first of which could be that people travel in different circles and your circle isn't ever going to be part of their circle. Sort of an exclusionary relationship, you might say. And, not to be overly judgmental of others, of course, there may be plenty of good reasons for that. If everyone existed in one social circle, after all, the world would be beyond boring.
Anyways, the text book is a wonderful creation, that is, if you're a post-graduate or doctoral candidate. Upon opening the cover, expecting to be warmly introduced, I was rather amazed at the depth of equations and formulas gracing practically every page. I felt intimidated immediately. Remember the movie "The Ring"? This had to be rocket science, or more correctly, forecasting science at its most extreme! Wow! I should have really paid more attention during my statistics classes. So, I quickly closed the cover and tried to get a refund from the seller. Note the word Tried here. They didn't want it back either.
The good Post-Grand and PhD. candidates of the science of forecasting probably don't need an "Introduction" to Time Series and Forecasting. Next time I buy a book, I think I'll look for something with "Sandbox" in the title.
May all your Forecasts be Good Forecasts at [...]
Awesome.......2006-08-04
this book is excellent because it provides us with many examples and detailed explanations.
Not sure if it is introductory.......2005-12-24
I think the book is not written in a very organized way. It's not a book for picking up time series quickly. It's saturated with information, which I'm not sure if it's necessary for implementation. I have no problem following the math, however, if I want to pick up something and implement it within a day or two, the book is a bit harder to digest. Wouldn't think this is an undergraduate course book as it covers convergence in probability or mean-squared, which I learnt in PhD courses, not even master level.
Great book for a great price.......2004-02-12
This is one of those books that you can't find much cons to it. The book is inexpensive, and it's unbelievably lightweight. The material is rich, and yet easy to understand. The author actually brings you step by step from elementary to theorectical proofs.
Book Description
Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata. As an expert in Stata, the author successfully guides readers from the basic elements of Stata to the core econometric topics. He first describes the fundamental components needed to effectively use Stata. The book then covers the multiple linear regression model, linear and nonlinear Wald tests, constrained least-squares estimation, Lagrange multiplier tests, and hypothesis testing of nonnested models. Subsequent chapters center on the consequences of failures of the linear regression model's assumptions. The book also examines indicator variables, interaction effects, weak instruments, underidentification, and generalized method-of-moments estimation. The final chapters introduce panel-data analysis and discrete- and limited-dependent variables and the two appendices discuss how to import data into Stata and Stata programming. Presenting many of the econometric theories used in modern empirical research, this introduction illustrates how to apply these concepts using Stata. The book serves both as a supplementary text for undergraduate and graduate students and as a clear guide for economists and financial analysts.
Customer Reviews:
good crash intro to necessary STATA commands.......2007-05-14
This book gives a good overview of some of the commands one would need to do regression analysis with STATA. I needed something to give me a quick intro to STATA and this book has helped me a lot. Howver, just like MS Excel, STATA has tons of commands that I probably will never touch!
much cheaper from stata-press website.......2007-01-27
Not a review, sorry, but a tip for potential purchasers:
This book is much cheaper from stata-press dot com.
Average customer rating:
- I agree. He did it again.
- Very Good Introduction
- Learn the stuff before writing a textbook
- Better than any of the courses I had attented.
- Elements of Dynamic Optimization
|
Elements of Dynamic Optimization
Alpha C. Chiang
Manufacturer: Waveland Pr Inc
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ASIN: 157766096X |
Book Description
In this volume Dr. Chiang introduces readers to the most important methods of dynamic optimization used in economics. The classical calculus of variations, optimal control theory, and dynamic programming in its discrete form are explained in the usual Chiang fashion--with patience and thoroughness. The economic examples, selected from both classical and recent literature, serve not only to illustrate applications of the mathematical methods, but also to provide a useful glimpse of the development of thinking in several areas of economics. Outstanding features include: (1) written with clarity and a comparable level of expository patience; (2) reinforces discussions of mathematical techniques with numerical illustrations, economic examples, and exercise problems; (3) presents a simple problem with a well- known solution in several different alternative formulations in the numerical illustrations; and (4) explains economic models in a step-by-step manner (from the initial construction through the intricacies of mathematical analysis to its final solution).
Customer Reviews:
I agree. He did it again........2007-09-02
Yes, he did it again. He simply explains it clearly.
Not a serious book for graduate students, but for undergraduates: this book is just in the middle of two levels.
Very Good Introduction.......2005-03-23
This book provides an introduction to the advanced subject of dynamic optimization in an easy to comprehend manner. For students with no previous background in the subject, it is the best book in the market.If you are familiar with Chiang's Fundamental Methods of Mathematical Economics, you can expect the same level of comfort. There are plenty of examples in the text and all the aspects of the subject are covered. A valuable book to own and deserves the 5 stars.
Learn the stuff before writing a textbook.......2002-08-30
This book may be great for students. I has many good examples, is well written and generally looks good. HOWEVER, for anyone who actually knows optimal control theory it is clear that the book has several flaws. The worst example is the section on transversality conditions in infinite horizon problems. Chiang simply has no idea what he is talking about.
Better than any of the courses I had attented........2001-02-22
The book of professor Chiang is not simply a good introductory text to dynamic optimization in the continuous-time form, but also provides a tight explanation of the related original economic models. It is better than any of the courses most people had attented before. I wish a similar book will appear soon, developing dynamic optimization tools, and especially optimal control in the discret-time form.
Elements of Dynamic Optimization.......2000-07-17
Very few people have the quality of expressing ideas and concepts with such clarity and simplicity as Professor Chinag has done. If you are new to dynamic optimization, particularly calculus and variation and optimal control theory you had better start with this treatise.
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