In Fractal Market Analysis, Peters describes complex concepts in an easy-to-follow manner for the non-mathematician. He uses fractals, rescaled range analysis and nonlinear dynamical models to explain behavior and understand price movements. These are specific tools employed by chaos scientists to map and measure physical and now, economic phenomena.
The first purpose of this book is to introduce the Fractal Market Hypothesisa basic reformulation of how, and why, markets function. The second purpose of the book is to present tools for analyzing markets within the fractal framework. Many existing tools can be used for this purpose. I will present new tools to add to the analyst’s toolbox, and will review existing ones. ‘
This book is not a narrative, although its primary emphasis is still conceptual. Within the conceptual framework, there is a rigorous coverage of analytical techniques. As in my previous book, I believe that anyone with a firm grounding in business statistics will find much that is useful here. The primary emphasis is not on dynamics, but on empirical statistics, that is, on analyzing time series to identify what we are dealing with.
The book is divided into five parts, plus appendices. The final appendix contains fractal distribution tables. Other relevant tables, and figures coordinated to the discussion, are interspersed in the text. Each part builds on the previous parts, but the book can be read nonsequentially by those familiar with the concepts of the first book.
- Part One: Fractal Time Series
- Part Two: Fractal (R/S) Analysis
- Part Three: Applying Fractal Analysis
- Part Four: Fractal Noise
- Part Five: Noisy Chaos
While reading the book, many of you will wonder, where is this leading? Will this help me make money? This book does not offer new trading techniques or find pockets of inefficiency that the savvy investor can profit from. It is not a book of strategy for making better predictions. Instead, it offers a new view of how markets work and how to test time series for predictability. More importantly, it gives additional information about the risks investors take, and how those risks change over time. If knowledge is power, as the old cliche goes, then the information here should be conducive, if not to power, at least to better profits.
- Introduction to Fractal Time Series
- Failure of the Gaussian Hypothesis
- A Fractal Market Hypothesis
- Measuring Memory-The Hurst Process and R/S Analysis
- Testing R/S Analysis
- Finding Cycles: Periodic and Nonperiodic
- Case Study Methodology
- Dow Jones Industrials, 1888-1990: An Ideal Data Set
- S&P 500 Tick Data, 1989-1992: Problems with Oversampling
- Volatility: A Study in Antipersistence
- Problems with Undersampling: Gold and U.K. Inflation
- Currencies: A True Hurst Process
- Fractional Noise and R/S Analysis
- Fractal Statistics
- Applying Fractal Statistics
- Noisy Chaos and R/S Analysis
- Fractal Statistics, Noisy Chaos, and the FMH
- Understanding Markets
Fractal Market Analysis: Applying Chaos Theory to Investment and Economics By Edgar E. Peters pdf