Chaos and Time-Series Analysis

Book Description

This book provides a broad coverage and has acessible style of exposition. Emphasis is on physical concepts and useful results, rather than rigorous mathematical proofs. Completeing this volume is free and user-friendly software.

Customer Reviews:

Clear and comprehensive.......2004-01-20

I had heard about this book from a friend with an interest in nonlinear dynamics; this is surprising in itself, since the book has been out for less than a year and already seems to be getting a positive reputation. The book more than lived up to my friend's recommendation. It is encyclopedic and remarkably clear. For anyone who is interested in linking nonlinear dynamical theory with empirical methodology, this is the best place that I know of to start.

Best book on chaos/complexity theory & data analysis.......2003-05-26

For those wishing to upgrade their grasp of chaos theory, dynamics, nonlinear data analysis, with an introduction to related aspects of complexity including fractals and complex systems, this is the best book I have yet seen, and supplements the excellet visual dynamics books by Ralph Abraham. It arose from the upper level course taught by Sprott at the University of Wisconsin. The book is well supported by his website, which will always keep the book updated. It is nicely hands-on with lots of exercises and a programming project with each chapter. For those impatient to write programs, having a program like Berkeley Madonna to solve systems equations is handy for exploring some of the example systems. It has three excellent appendices, one a catalog of 62 dynamical systems, another useful mathematical formulas, and the last a compilation of useful journals. I found it incredibly comprehensive covering all aspects of the many subjects. And exceptionally clear, updating any necessary mathematics with clear explanations...

Nonlinear Time Series Analysis: Methods and Applications (Nonlinear Time Series and Chaos)

Average customer rating:

Passion
Extremely disappointing.
Dramatic, chaotic and yet analytic.

Nonlinear Time Series Analysis: Methods and Applications (Nonlinear Time Series and Chaos)
Cees Diks
Manufacturer: World Scientific Publishing Company
ProductGroup: Book
Binding: Hardcover

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Customer Reviews:

Passion.......2001-03-02

Of course there are many books dealing with the relationship between non-linear time series and chaos. It resembles the situation where one has to choose among two women that you both love, but after spending a weekend without passion with one of them, you know where to go for. After reading the book by Diks, and comparing it to related work, I can only come to the conclusion that it stands out. The book is clear, well written, and obviously relevant to theorists working in such divergent fields as statistics, finance, and physics. To each professor supervising a Ph.D. student I would therefore like to say: put it on the required reading list and if necessary use to force to make them on the subjects discussed by Diks.

Extremely disappointing........2001-02-26

This is not my first book about nonlinear time series and chaos theory and really i'm just wondering how it get published. I'm trying to find something positive to say but i cannot. I cannot recall what i did learn from it: just one thing, testing for reversibility. Ok, that's rather short for a book, a paper would have been sufficient, and less costly. I've just wasted my money on this. In addition, i'm not the kind of reviewer who is used to give 1 star to a good book, it has to be very bad to get that.

Rather go to Kantz or Abarbanel for useful books on nonlinear time series analysis...

Dramatic, chaotic and yet analytic........2000-05-04

Seldomly I have read a book on this subject which was so clear and well written. Diks turns out to be a captivating writer, who does not scare away from truth, equations, or Greek letters. I'm waiting for part 2, to see how the story ends.

Nonlinear Time Series Analysis (Cambridge Nonlinear Science Series)

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Good for both beginners and advanced practitioners
Excellent for practitioners

Nonlinear Time Series Analysis (Cambridge Nonlinear Science Series)
Holger Kantz , and Thomas Schreiber
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Hardcover

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Systems Analysis & Design | Computer Science | Computers & Internet | Subjects | Books

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ASIN: 0521551447

Book Description

Deterministic chaos provides a novel framework for the analysis of irregular time series. Traditionally, nonperiodic signals are modeled by linear stochastic processes. But even very simple chaotic dynamical systems can exhibit strongly irregular time evolution without random inputs. Chaos theory offers completely new concepts and algorithms for time series analysis which can lead to a thorough understanding of the signal. The book introduces a broad choice of such concepts and methods, including phase space embeddings, nonlinear prediction and noise reduction, Lyapunov exponents, dimensions and entropies, as well as statistical tests for nonlinearity. Related topics like chaos control, wavelet analysis and pattern dynamics are also discussed. Applications range from high quality, strictly deterministic laboratory data to short, noisy sequences which typically occur in medicine, biology, geophysics or the social sciences. All material is discussed and illustrated using real experimental data.

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The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.

Customer Reviews:

Good for both beginners and advanced practitioners.......2003-10-22

In my search for good material on time series analysis, I have come across many books packed with information, yet so dry as to make them unreadable (readers of Hamilton's "Time Series Analysis" will know what I mean - Amazing book, but unreadably boring).

Kantz and Schreiber do not suffer from that all too common problem. They write clearly and in a very readable style. Their use of real-world datasets and numerous (though not overwhelming) charts makes their work quickly accessible even to beginniners in the field. They provide enough mathematical formalisms to make use of what they present, but not so many as to require a PhD in math to follow the flow of the text. For more advanced readers, they cover a wide range of topics useful both for analysis and for forecasting. Chapter 12, in particular, opened me to a whole world of new techniques.

As my one negative comment on this book, I would have liked that same chapter 12 fleshed out more, to the point that I would buy a follow-up book covering nothing but an elaboration on that single chapter.

If you have an interest in time series analysis and forecasting, and have grown tired of dry material that provides nothing more than yet another extension to ARIMA or Kalman filtering, you will love this book.

Excellent for practitioners.......2001-02-23

This book provides an excellent overview of chaos theory concepts applied to time series analysis. First part constitutes a good tutorial on chaos theory and its implications on time series analysis while the second part discusses in detail aspects of time-series related chaos theory concepts (with an historical perspective of the related research). Time series analysts will certainly benefit from it thanks to its balanced exposition of issues of chaos theory concepts for non-infinite data sets...

Book Description

Chaos in Real Data studies the range of data analytic techniques available to study nonlinear population dynamics for ecological time series. Several case studies are studied using typically short and noisy population data from field and laboratory. A range of modern approaches, such as response surface methodology and mechanistic mathematical modelling, are applied to several case studies. Experts honestly appraise how well these methods have performed on their data. The accessible style of the book ensures its readability for non-quantitative biologists. The data remain available, as benchmarks for future study, on the worldwide web.

Chaos Theory in Economics: Methods, Models and Evidence (International Library of Critical Writings in Economics)

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Chaos Theory in Economics: Methods, Models and Evidence (International Library of Critical Writings in Economics)

Manufacturer: Edward Elgar Pub
ProductGroup: Book
Binding: Hardcover

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Dimension Estimation and Models (Nonlinear Time Series and Chaos, Vol 1)

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Dimension Estimation and Models (Nonlinear Time Series and Chaos, Vol 1)

Manufacturer: World Scientific Pub Co Inc
ProductGroup: Book
Binding: Hardcover

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ASIN: 9810213530

Footprints of Chaos in the Markets: Analyzing Non-linear Time Series in Financial Markets and other Real Systems

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
ProductGroup: Book
Binding: Hardcover

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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.

Book Description

The only integrative approach to chaos and random fractal theory

Chaos and random fractal theory are two of the most important theories developed for data analysis. Until now, there has been no single book that encompasses all of the basic concepts necessary for researchers to fully understand the ever-expanding literature and apply novel methods to effectively solve their signal processing problems. Multiscale Analysis of Complex Time Series fills this pressing need by presenting chaos and random fractal theory in a unified manner.

Adopting a data-driven approach, the book covers:

DNA sequence analysis
EEG analysis
Heart rate variability analysis
Neural information processing
Network traffic modeling
Economic time series analysis
And more

Book Description

An authoritative presentation on an important emerging field.

Discrete event systems are ubiquitous in modern society, and we rely heavily on their proper design, correct operation, and performance. Written by leaders in the field who have helped establish the foundations of the theory and applied the methods to a wide variety of applications, Stability Analysis of Discrete Event Systems is useful both as a textbook (homework problems are included) and for researchers in systems and control theory. This book includes many examples and three detailed case studies: computer network load balancing, manufacturing system scheduling, and intelligent control systems.

Important features of this book include:

A concise introduction to discrete event system modeling—including Petri nets
Comprehensive treatment of stability concepts and Lyapunov analysis methods
Stability of Petri models
Case studies in
Computer network load balancing system behavior and analysis
Manufacturing system scheduler design and analysis
Intelligent control system modeling and analysis (for expert control systems)
An outlook on the role of stability concepts and analysis in intelligent, autonomous, and hybrid systems.

Disappearing evidence of chaos in security returns: a simulation.: An article from: Quarterly Journal of Business and Economics

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Disappearing evidence of chaos in security returns: a simulation.: An article from: Quarterly Journal of Business and Economics
Michael D. Atchison , and Mark White
Manufacturer: University of Nebraska-Lincoln
ProductGroup: Book
Binding: Digital

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Book Description

This digital document is an article from Quarterly Journal of Business and Economics, published by University of Nebraska-Lincoln on March 22, 1996. The length of the article is 3720 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker immediately after purchase. You can view it with any web browser.

From the supplier: The tenets of chaos theory are now being applied to the statistical analysis of stock market returns. At present, the evidence seems to suggest that stock market returns can, in fact, be characterized by deterministic nonlinear processes as predicted by chaos theory. This view challenges the fundamental assumptions of the theory of efficient markets. One way to seek for evidence of chaos in the financial markets would be for researchers to observe the trading patterns of individual securities rather than of aggregate portfolios or market indices.

Citation Details
Title: Disappearing evidence of chaos in security returns: a simulation.
Author: Michael D. Atchison
Publication: Quarterly Journal of Business and Economics (Refereed)
Date: March 22, 1996
Publisher: University of Nebraska-Lincoln
Volume: v35 Issue: n2 Page: p21(17)

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