Product Description
The latest developments in chaos theory — from an industry expert Chaos and Order in the Capital Markets was the first book to introduce and popularize chaos as it applies to finance. It has since become the classic source on the topic. This new edition is completely updated to include the latest ripples in chaos theory with new chapters that tie in today's hot innovations, such as fuzzy logic, neural nets, and artificial intelligence.
Critical praise for Peters and the first edition of Chaos and Order in the Capital Markets
"The bible of market chaologists." — BusinessWeek
"Ed Peters has written a first-class summary suitable for any investment professional or skilled investor." — Technical Analysis of Stocks & Commodities
"It ranks among the most provocative financial books of the past few years. Reading this book will provide a generous payback for the time and mental energy expended." — Financial Analysts Journal
This second edition of Chaos and Order in the Capital Markets brings the topic completely up to date with timely examples from today's markets and descriptions of the latest wave of technology, including genetic algorithms, wavelets, and complexity theory.
Chaos and Order in the Capital Markets was the very first book to explore and popularize chaos theory as it applies to finance. It has since become the industry standard, and is regarded as the definitive source to which analysts, investors, and traders turn for a comprehensive overview of chaos theory. Now, this invaluable reference — touted by BusinessWeek as "the bible of market chaologists" — has been updated and revised to bring you the latest developments in the field.
Mainstream capital market theory is based on efficient market assumptions, even though the markets themselves exhibit characteristics that are symptomatic of nonlinear dynamic systems. As it explores — and validates — this nonlinear nature, Chaos and Order repudiates the "random walk" theory and econometrics. It shifts the focus away from the concept of efficient markets toward a more general view of the forces underlying the capital market system.
Presenting new analytical techniques, as well as reexamining methods that have been in use for the past forty years, Chaos and Order offers a thorough examination of chaos theory and fractals as applied to investments and economics. This new edition includes timely examples from today's markets and descriptions of cutting-edge technologies-genetic algorithms, wavelets, complexity theory-and hot innovations, such as fuzzy logic and artificial intelligence.
Beyond the history of current capital market theory, Chaos and Order covers the crucial characteristics of fractals, the analysis of fractal time series through rescaled range analysis (R/S), the specifics of fractal statistics, and the definition and analysis of chaotic systems. It offers an in-depth exploration of:
- Random walks and efficient markets — the development of the efficient market hypothesis (EMH) and modern portfolio theory
- The linear paradigm — why it has failed
- Nonlinear dynamic systems — phase space, the Henon Map, Lyapunov exponents
- Applying chaos and nonlinear methods — neural networks, genetic algorithms
- Dynamical analysis of time series — reconstructing a phase space, the fractal dimension
Tonis Vaga's Coherent Market Hypothesis — the theory of social imitation, control parameters, Vaga's implementations
Plus, Chaos and Order now contains a Windows-compatible disk including data sets for running analyses described in the appendices.
Written by a leading expert in the field, Chaos and Order in the Capital Markets has all the information you need for a complete, up-to-date look at chaos theory. This latest edition will undoubtedly prove to be as invaluable as the first.
Average Customer Review:
0 of 0 people found the following review helpful:
Investing in the markets? Read this., 2009-09-28
Nutshell review - 10+ years after reading this book for the first time I still find the material fascinating. It offers an engaging tour through the worlds of random walks, fractals, chaos and nonlinear dynamic systems for the layman. The author's approach is primarily a conceptual discussion of the topics under review rather than taking a mathematical approach and so it will be accessible to most all readers.
The real message to take away from this book is not whether the markets can be described using fractal geometry or whether the market is a chaotic, nonlinear system. Rather it is that if you are a believer in the efficient market hypothesis, the capital asset pricing model, and the random walk models of market behaviour then you might be in for a nasty surprise.
Other very interesting books in this vein are The Black Swan: The Impact of the Highly Improbable by Nassim Nicholas Taleb, and The (MIS)Behaviour of Markets: A Fractal View of Risk, Ruin, and Reward by Benoit B. Mandelbrot.
2 of 4 people found the following review helpful:
Poorly explained, 2004-02-03
I have a university maths degree and found the book very obvious and drawn out for the first few chapters. In spite of this I looked forward to what was going to be explained later. Suddenly from a very simple and easy to understand explanation on the EMH he starts to use mathematics in his equations that I had a lot of difficulty following. There was very little or no explanation of how these equations were arrived at and a lot of mathematics and statisics is assumed. This book does not apply the theory in ny meaningful way to the markets let alone the capital markets in my opinion. I found that I took very little away from this book and would not recommend it to anyone who has basic mathematics like myself or is looking for some deeper insight into the markets. I would hate to have Mr Peters as a teacher based on his book.
7 of 7 people found the following review helpful:
A very good introduction, 2004-01-31
I read this book, the 1991 version, years ago. Around 1980 my own attempts to crack share prices statistically convinced me that all share prices behaved like a Gaussian random walk meaning that all speculation was comparable with playing roulette and I am not one of those guys who usually wins when gambling. This view was strengthened when the option pricing model came up, meaning that even the real pro's in the field assume that share prices are nothing but a random walk. This book has opened my eyes to the fact that there is much more to randomness than just the Gaussian curve. Share prices are not fully random. Impressive is the demonstration that an RS analysis on the real data is different when applying the same RS analysis on scrambled data. So there is information hidden in these time series, somewhere. Since then I have picked up the subject of cracking time series again with great pleasure. I think this book is exceptionally well written and without it I doubt if I would have been able to follow Mandelbrot's book "scaling and fractals in finance" that I bought later. The book is about understanding a subject, not about learning a simple formula to apply on a time series.
15 of 16 people found the following review helpful:
A dated overview, with little real meat, 2003-02-10
The second edition of this book was published in 1996. The book
seems to be largely based on Feder's 1988 book "Fractals". The
dated nature of this book means that it is missing later work
on long memory processes, which Peters estimates using the Hurst
exponent.As one reviewer already noted, don't assume that this book will
provide much in the way of useful equations. For anyone who wants
more than an overview, this book is a disappointment. Peters does
a poor job of explaining the equations and I did not find enough
detail to implement the algorithms discussed (I turned to Feder's
book and various journal articles). The book does come with a
"floppy" disk containing the Visual Basic algorithms. This is
a poor choice, since C is pretty much the lingua franca for
algorithms.
The various chaos and fractal techniques are applied to a handful
of financial data sets, but this is far from even a solid
suggestion that these techniques might be useful to anyone
developing real market models.
Some of the conclusions that Peters draws (cycles in financial
data) do not seem to be supported the evidence he presents.
In summary, if you are looking for something beyond an overview,
save your money. Feder ("Fractals") has a better description of
RS calculation. "A Non-Random Walk Down Wall Street" by Lo
and MacKinlay has a chapeter on the application of the RS
statistic and long-memory processes which is much better than
Peters. For those who need to simulate fractal brownian motion
(data sets with a particular Hurst exponent) "The Science of
Fractal Images" by Barnsley et all is a good reference.
11 of 11 people found the following review helpful:
Good overview, bad balance, 2001-03-22
If you're looking for a purely conceptual introduction to how chaos theory can be applied to financial markets, this book is as good a source as any. Peters's discussion of R/S statistics and the graphical examples drawn from the markets are clear and intuitive (Ch. 7-8). The key point demonstrating long-term memory effects in the market is well made.
However he spends an inordinate amount of time attacking the foundations of the efficient market hypothesis (EMH) to the point of being boring, yet the argument boils down to "it has errors when compared to reality". Duh, so does every other theory, including fractal. The real issue is "for the error in theory A, how bad are the results X, and is theory B much better at it?" If you're not going to do that, don't spend 40 pages (Ch. 1-4) on it. This is misleading to those not familiar with EMH, and boring to those who are.
Don't look to this book for good math. In my edition (1991), careless and erroneous notations abound. Also, the equations are written in BASIC notation which is notoriously hard to visualize, but this is probably the fault of the editor/publisher. Peters makes frequent and unannounced jumps between the apparent rigor of math and loose conjectures. The math is distracting to a qualitative reader, and the conjectures irritating to the quantitative one. Better to cater to one audience, and do it well.
Still, I would recommend this book as a good conceptual introduction to the subject. But if you're planning to go deeper, use the equations in this book at your own perils. Go to the source.