Customer Reviews

Profiting from Chaos: Using Chaos Theory for Market Timing, Stock Selection, and Option Valuation

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The topic of this book: Using Chaos Theory for Market Timing, Stock Selection and Option Valuation--corresponds to that area of Economics reflected in the current Nobel Prize in Economics Winners for 2003! This book by Tonis Vaga, "Profiting from Chaos: Using Chaos Theory for Market Timing, Stock Selection, and Option Valuation", Dec., 1994; ISBN 0-07-066786-1 is about 9 years ahead of its time. The original definition of chaos emphasized the apparent unpredictable behavior arising in a dynamic deterministic system because of great sensitivity to initial conditions. If two arbitrarily close starting points diverge exponentially so that their future behavior becomes unpredictable then chaos has arisen! This is characteristic of weather, stock markets, and commodity markets. However, short term and middle term weather forecasting is performed regularly before the long term effects of chaos sets in. This is the same type of strategy used in this book for Market Timing, Stock Selection, and Option Valuation by use of Chaos Theory. There is an underlying regularity in a function that exhibits chaos which can be revealed by systematic perturbations to the trajectory. Just like weather forecasting can be successful by redefining the short and medium term (i.e., defacto systematic perturbations) then "Profiting from Chaos" in the short and medium term is also possible. The Nobel Committee in Oslo, Norway has just confirmed the underlying thesis of Tonis Varga's book by this year's Nobel Prize in Economics award! I suspect that a revised edition will now be in the works, but get the original version before it is too late!

The coherent market hypothesis (CMH) presented in this book is an interesting alternative to the commonly used efficient market hypothesis. However, nonlinear dynamical systems have had less impact on economics than on other sciences. For good reasons. In economics there is rarely a theoretical reason for expecting to find one form of nonlinearity rather than another. As a result, the concepts presented in this book are quite interesting, but none of them is particularly convincing. In addition, the complex mathematics are not clearly explained. Empirical verification of the CMH is therefore extremely difficult, if not impossible. The practical value of this book is rather limited and does not provide enough reasons to abandon the assumptions of the efficient market hypothesis as a basis for day-to-day trading decisions.

One of the most difficult books, I've ever not been able to read. Before you purchase this book be advised that it is a highly technical book requiring an in-depth advanced understanding of Stock Market technical analysis, economics and higher math. If you have a PhD in economics and have this kind of background then this book may be for you. I am going to read more about technical analysis and chaos theory mathmatics and try reading it again in the future.