Book Description
This book provides a synthesis of concepts and materials that ordinarily appear separately in time series and econometrics literature, presenting a comprehensive review of both theoretical and applied concepts. Perhaps the most novel feature of the book is its use of Kalman filtering together with econometric and time series methodology. From a technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. This technique was originally developed in control engineering but is becoming increasingly important in economics and operations research. The book is primarily concerned with modeling economic and social time series and with addressing the special problems that the treatment of such series pose.
Book Description
David Hendry is one of the world's leading econometricians, and in this major new work he and Michael Clements provide an extended formal analysis of economic forecasting with econometric models: their analysis builds in many of the features of the real world that are often overlooked in traditional, textbook analyses of forecasting. Consequently, Clements and Hendry are able to suggest ways in which existing forecasting practices can be improved, as well as providing a rationale for some of the habitual practices of forecasters that have hitherto lacked a scientific foundation.
Customer Reviews:
Good strategies for macro economic forecasting.......2000-03-28
This is a unique text that treats economic time series forecasting with emphasis on the recent advances in econometric theory such as cointegration as well as other practical strategies such as combination forecasts. Usual text books do not have the breadth of coverage this one attempts, successfully, to achieve. In short, this one text replaces many books and papers on one's shelf.
Book Description
Time Series Models for Business and Economic Forecasting is the most up-to-date and accessible guide to one of the fastest growing areas in business and economic analysis. The author is regarded as one of the most accomplished econometricians in Europe and this book is based on his highly successful lecture program for multidisciplinary, graduate and upper level undergraduate students. Early chapters of the book focus on the typical features of time series data in business and economics. Later chapters are concerned with the discussion of some important concepts in time series analysis, the techniques that can be readily applied in practice, different modeling methods and model structures, multivariate time, and the common aspects across time series.
Customer Reviews:
Good introductory book !.......2003-02-03
Full of real-life examples that provide some intuitive insight about the issues that may arise when modelling time series and forecasting. Requires some initial knowledge in statistics and algebra but if you're involved in time series modelling, it should be your first book. All the data thats used is available in the authors webbsite for downloading, very nice.
nice book on time series for statisticians and economists.......2001-07-01
To make this review short, I will say that I agree with all seven points made by the reviewer from New York, NY, whomever he or she may be. Franses is clear, concise, authoritative and up-to-date on all the advances.
I particularly like the nice coverage of GARCH models that are new to me. It is a great introductory text especially for economics majors. For more advanced books and other treatments of time series consider Kennedy's fourth edition of "A Guide to Econometrics" or the suggestion from reviewer "New York, NY". Also my listmania list on time series will give you several sources to look at.
Excellent introductory book on economic time series modeling.......2000-04-10
Recently, I reread Franses book and expanded my review, which now includes 10 benefits.
(1) Organization by key features of economic time series (trends, seasonality, outliers, conditional heteroskedasticity, non-linearity), rather than by methods, which provides a practical foundation for the various methodologies. The order in which chapters are presented reflects the order of difficulty in modeling trends, seasonality, etc. Even if there were no other benefits, this organization makes it worthwhile.
(2) Appropriate level for first book on time series models as applied to economic time series, explaining more difficult concepts GARCH and VAR without excess detail. Box and Jenksins book is more a textbook; Brockwell and Davis is also more advanced; Hamilton is comprehensive and technical, but not as friendly. This book is very approachable even if you have had only 1 or 2 statistics courses. In economics, many people are interested in forecasting, and Franeses here is a good start. If you are looking for a more advanced forecasting book, try the recent books by Clements and Hendry from Cambridge U Press.
(3) Clear distinction of the steps of model identification, estimation, diagnostics, and selection; something which other time series analysis books do not seem to do early or easily. (4) Delineates stochastic and deterministic models in the second chapter, providing a framework for when to take differences (eg. ARMA vs ARIMA). His timing is excellent. Many people I have interviewed on time series do not understand why they need to difference (eg use prices instead of returns) or why to transform the series (eg use logs instead of actual values).
(5) Generous use of examples with real not simulated data with a website to download all the data, making it possible to import, graph, and analyze on your own.
(6) A website containing printing corrections. Techincal books are likely to have some errors, but very few keep websites to list what those are.
(7) Revealing graphics, especially for conditional heteroskedasticity, the 'CH' in GARCH. Figures 7.1-7.3 illustrate the concept that large returns tend to follow large returns very cleanly.
(8) His notation is clear and consistent, yet not overwhelming: conventional Greek letters, only 1 level of subscripting, matrix noation where appropriate; even the results are neatly presented, as standard errors appear in () below their point estimates. Finally, Franses uses the same notation from chapter to chapter where the term is the same--not so common when chapters written by different authors.
(9) Great appendices: extensive and updated references, a thorough subject index, and an author index. My only suggestion for improvement is that a second edition or the website should contain some exercises. Highly recommended.
(10) The price! There are books published under Wiley at 3 to 4 times the price! under Springer Verlag for 2 to 3 times the price. Certain books are worth the money, but Cambridge University Press paperback publications, when written well, are exeptional values. I encourage the ambitious time series student to look at other time series books, including one written this year by Franses including Quantitative Models in Market Research.
Excellent introduction into time series.......2000-04-10
This book is a brilliant introduction into time series analysis. I found it a great basis for further analysis, allowing to go into deep with, for example, J.D. Hamilton's classical work. The book has a very well-defined structure, which (in my opinion) serves both auto-didact and (under)graduate teaching. Check out the author's web-page at Erasmus University Rotterdam for a list with corrections of some typos and the data sets used.
This book is exceptional.......1999-11-21
The beauty of this text is it's clarity and the author's choice to stay away from didactic lectures on formal statistical mathematics. I would highly recommend this book for anyone who has an undergraduate background in mathematics, statistics or economics and wants a medium level text to show them how to model time series.
Average customer rating:
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Neural Network Time Series: Forecasting of Financial Markets
E. Michael Azoff
Manufacturer: John Wiley & Sons
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ASIN: 0471943568 |
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Better than I expected.......1997-02-26
A good introduction to neural nets and their applicability tothe futures markets. Provides mathematical/theoretical basis fortechniques involved in neural net training, testing, chaos and touches on nonlinear systems in general. Also provides interesting benchmarks of several nets against several time series. Great bibliography. Includes Fortran source code for running trained nets but not for training a net.
Average customer rating:
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Introduction to Time-Series Modeling and Forecasting in Business and Economics
Patricia E. Gaynor , and
Rickey C. Kirkpatrick
Manufacturer: McGraw-Hill Companies
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Binding: Hardcover
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ASIN: 0070349134 |
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Applied Time Series and Box-Jenkins Models
Walter Vandaele
Manufacturer: Academic Press
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ASIN: 0127126503 |
Book Description
This book can be used in an advanced undergraduate course or beginning graduate course on time series forecasting. Such a course could be part of a business school, department of economics, or engineering curriculum. Social science departments (education, psychology, public health, medicine) have also started to introduce such a course in their curriculum and researchers in these fields are using the time series methodology covered in this book in their applied work.
Average customer rating:
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Applied Time Series for Business and Economic Forecasting (Statistics, a Series of Textbooks and Monographs)
Sufi M. Nazem
Manufacturer: Marcel Dekker Inc
ProductGroup: Book
Binding: Hardcover
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ASIN: 0824779134 |
Average customer rating:
- There is no practical value to this book
- The title of this book is extremely misleading!!!
- Chaos and Dynamical Systems, but no market footprints
- Monumental! But Oh, the math!
- deciphering arcane mathematics
|
Footprints of Chaos in the Markets: Analyzing Non-linear Time Series in Financial Markets and other Real Systems
Richard Urbach
Manufacturer: Financial Times/Prentice Hall
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ASIN: 0273635735 |
Book Description
Price movements in financial markets are not random. There are actually clues that allow sophisticated investors to uncover trends and make accurate predictions. The key to discovering this predictability lies in a new set of mathematical techniques --the application of dynamic, non-linear time series. This new science of investment is where chaos theory meets the markets. Richard Urbach offers practical advice and applications on the latest mathematical techniques and examines the opportunities these new techniques can deliver.
Customer Reviews:
There is no practical value to this book.......2003-05-20
Hundreds of pages of insanely dense math with absolutely no practical information on how to apply chaos theory to the markets. In fact, the author seems to suggest that it may be impossible to use chaos theory as a prediction tool in the financial markets.
This is akin to a recipe book written by someone who thinks cooking is impossible, so all he can really write about is grocery shopping. NOT recommended! A much better book is "Trading on the Edge" by Deboeck.
The only cool thing about the book is that you can use it to impress your friends/enemies with the title and loads of arcane equations inside.
The title of this book is extremely misleading!!!.......2001-10-11
1) first, there is hardly *any* mention of markets in the
book. I only found two references
to the market in the entire book. the first reference was
early on where a couple of plots of the S&P were shown at
daily and weekly time frames, and the author stated that the
plots resembled each other and therefore this could be taken
as evidence of self-similarity.
the title of the book is mis-leading... it would be as if
a calculus textbook were to call itself "calculus in the markets"
simply because they have a section on compound interest...
2) there is a lot of hand-waving in the theory that is covered.
the author does cover a lot of ground, so it is understandable
that more details and explanations of certain subjects are
not provided. this book *is* a good bibliographic reference,
for example if one is interested in a particular topic, it
could be looked up in this book, and references to all the
seminal works are given.
3) there are better books out there that cover similar subject
matter, and *are* centered on the marketplace: for example,
Mandlebrot's "Fractals and Scaling in Finance", Lo and
MacKinlay's "A Non-Random Walk Down Wallstreet", William Brock
et al "Nonlinear Dynamics, Chaos, and Instability", and
several books by Edgar Peters.
Chaos and Dynamical Systems, but no market footprints.......2001-09-09
I'm surprised that this book got reader reviews that
are as favorable as the reviews posted before this one.
If you are interested in the mathematics of chaos and
dynamical systems, this might be a good book for you.
However, this book is densely packed with mathematics
and unless you have a very solid mathematical background,
Peitgen, Jurgens and Saupe's wonderful book "Chaos and
Fractals: New Frontiers of Science" might be a better choice.
This book covers the basic mathematics of dynamical systems
but does not delve into graduate level mathematics.
If you are thinking of buying this book because its title
mentions markets and non-linear financial time series,
save your money. The author spends five very mathematically
laden chapters discussing dynamical systems. There is nothing
solid on applying the mathematics of dynamical systems to
financial time series other than the observation that they
sure seem chaotic. At the very end the author weakly suggests
that dynamical systems theory might be applied to market
information, but he provides no examples.
People who develop successful market models usually don't
publish much on them, since there is a lot to be gained
by trading them. So one cannot catagorically state what has
and has not been done. However, I know of no case where
dynamical systems mathematics has been used to successfully
provide predictive models (e.g., models you can trade and
make money on) of financial markets. This book certainly does
not live up to the promise of its title.
There are a number of good book on time series analysis and
modeling. For example, see "Wavelet Methods for Time Series Analysis" by Donald B. Percival, Andrew T. Walden. This book
does not deal with financial time series directly, but it does
deal with "non-stationary" time series.
Monumental! But Oh, the math!.......2001-07-29
Everything you would care to know and to spare. Exceptionally well written and comprehensive for a technical work. And the book is highly technical, both in vocabulary and exposition. The math... and there is lots of it... is a stretch for me and I have passed PhD qualifiers in Operations Research and Statistics. So this is not an easy book, nor one to take to the beach. But I assure you that you will be well rewarded for your efforts.
deciphering arcane mathematics.......2000-07-27
As an applied scientist the thought of deciphering the language of rigorous mathematics in any field can be a little off putting. This book is a pleasant change. With its intuitive approach at the start of each chapter, the reader is given a feel for the subject matter, something which is often lacking in texts of this level. Particularly illuminating were the chapters on dynamical systems and embeddings. They gave meaning to what most of my generation had only heard through James Gleik and those fiendish cyclone generating insects. One can see the potential of the subject stretches beyond the financial markets.
For new comers to this field, the collection of algorithms and references throughout the book provide a rich starting point. The writer has provided a sound reference for the researcher and clear signposts in the mesmerizing land of non-linear dynamics.
Customer Reviews:
Has All The Facts.......2004-04-11
Great reference for building market models. A lot of good examples. Real world case studies. Easy to understand math formulas. Technical - but good!
Book Description
This book is based on two Sir Richard Stone lectures at the Bank of England and the National Institute for Economic and Social Research. Largely non-technical, the first part of the book covers some of the broader issues involved in Stone's and others' work in statistics. It explores the more philosophical issues attached to statistics, econometrics and forecasting and describes the paradigm shift back to the Bayesian approach to scientific inference. The first part concludes with simple examples from the different worlds of educational management and golf clubs. The second, more technical part covers in detail the structural econometric time series analysis (SEMTSA) approach to statistical and econometric modeling.
Books:
- Foundations of Microeconomics plus MyEconLab Student Access Kit, Second Edition
- Free Trade Under Fire: Second Edition
- Freedom from the Known
- From Mutual Aid to the Welfare State: Fraternal Societies and Social Services, 1890-1967
- Game Theory with Economic Applications (2nd Edition)
- Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton Studies in Complexity)
- George Soros on Globalization
- Getting Things Done: The Art of Stress-Free Productivity
- Global Civil Society: An Answer to War
- Global Strategy (with World Map and InfoTrac )
Books Index
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Time Series Analysis by State Space Methods (Oxford Statistical Science Series)
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A Kalman Filter Primer (Statistics: Textbooks and Monographs)
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