Synopses & Reviews
A leading pioneer in the field offers practical applications of this innovative science. 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.
Strongly applications oriented, Fractal Market Analysis replaces conventional capital market theory with a more realistic way of accessing the randomness and determinism that characterizes today's stock, bond, and commodities market. Whatever your trading and investment goals, the book delivers economic
Business Week hailed it as the "bible of market chaologists". Financial Analysts Journal ranked it "among the most provocative financial books of the past few years". With the publication of Chaos and Order in the Capital Markets, Edgar E. Peters won universal acclaim for describing chaos theory for the stock, bond, and commodities markets of the 1990s. Now the most respected author on the subject of chaos theory gives traders and investors everywhere what they've been eagerly awaiting - the first applications-oriented book on using chaos as a sophisticated market analysis tool. In Fractal Market Analysis, Edgar Peters tackles head-on tradition bound capital market theories and asset pricing models that depend on symmetry and smoothness, base their results on regular, periodic market and economic cycles, and seek to explain away as "anomalies" such recurring events as market stampedes and crashes. In its place, the author proposes a new "fractal market hypothesis", which opens a window into the way the financial world actually is, rather than the way we would like it to be. Based on current chaos theory and using fractals - objects whose disparate parts are self-similar and which thrive on market roughness and asymmetry - the book provides a valuable new framework for accurately understanding and precisely modeling the turbulence, discontinuity, and nonperiodicity that truly characterize today's capital markets. Fractal Market Analysis delivers a robust tool for understanding the conflicting market randomness and determinism we experience every trading and investing day. Called "rescaled range (R/S) analysis", it actually thrives on noise, measurement, and volatility, and is free of themathematical limitations of traditional Gaussian statistics. By following the guide's numerous step-by-step case studies, you'll learn how to apply R/S analysis to your own area of interest - bonds, equities, interest rates, foreign currencies, and gold - to more accurately determine the number and length of both nonperiodic and periodic market and economic cycles to enhance your portfolio selection. Here, finally, is the first professional guide to reconcile the rational, but limited approach of traditional quantitative management with the practical experience of actually dealing with the markets. By merging chaos theory, fractal statistics, and nonlinear dynamic modeling. Fractal Market Analysis leads you to ever-finer levels of market resolution. With it, you'll better understand short- and long-term developments, undertake more precise time series and cycle modeling, and use your conclusions to create realistic market models.
Includes bibliographical references (p. 296-305) and index.
Table of Contents
FRACTAL TIME SERIES.
Failure of the Gaussian Hypothesis.
A Fractal Market Hypothesis.
FRACTAL (R/S) ANALYSIS.
Measuring Memory--The Hurst Process and R/S Analysis.
Testing R/S Analysis.
Finding Cycles: Periodic and Nonperiodic.
APPLYING FRACTAL ANALYSIS.
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.
Currencies: A True Hurst Process.
Fractional Noise and R/S Analysis.
Applying Fractal Statistics.
Noisy Chaos and R/S Analysis.
Fractal Statistics, Noisy Chaos, and the FMH.