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This is an excellent book that explores the core of our understanding of market behaviour. It is one of the best books of 2005. It challenges the way we think about markets, and the very foundations of modern portfolio theory. At heart it is about the standard bell curve. A bell curve describes a normal distribution. It tells you ‘on average’ how many events will fall within normal and extreme. This is the core foundation of risk management, portfolio construction, options trading and modern financial theory. It assumes that prices are statistically independent – like a coin toss – and that price variations are normally distributed – a standard deviation.


Mandelbrot claims this is simply wrong because it does not describe the way markets and prices operate. Markets are characterised by extremes of volatility that cluster into groups. These extremes cannot be ignored and they occur on every time scale. Mandelbrot discovered and named fractals. He believes that the volatility patterns are fractural repetitions.


In explaining how he believes modern financial theory is incorrect he provides one of the clearest explanations of modern financial theory that I have come across. This book could be heavy with mathematics.  Instead it is clearly and cogently explained with hardly a number in sight.


Mandelbrot does an excellent job of exploring the weakness of modern financial theory and in so doing raises some very serious questions about the adequacy of many of the technical analysis techniques we use that are based on moving averages  - stochastics etc - or on normal distribution – least square regression, stand deviation, Bollinger bands etc. Mandelbrot does a less successful job in showing how fractal analysis is used as an analytical tool for understanding market behaviour. This is acceptable because his intention is to identify weakness so that we can explore new areas.


I found Mandelbrot’s discussion of what is involved in trading to be less perceptive. His fascination is with prices as a number series. He believes a fractal generator can produce a chart that looks like a price chart so therefore the price chart must look like the one produced by the fractal generator. It is a flawed flow of logic because it ignores the emotional content of price. However, the observation that the price pattern is a fractal repetition is particularly useful.


He talks briefly about volatility clustering, but because he is not a trader, he misses the most significant  information inherent in volatility clustering by focusing on the extreme  extremes rather than the minimum extremes. The Guppy Multiple Moving Average is a tool for tracking volatility clustering. Markets change at two points. The first is when volatility drops. This is a minimum extreme shown when the two groups of averages compress and converge. The second is when volatility expands in a single time frame – the bubbles in the GMMA analysis.  These observations provide a trading solution based on a  better understanding of the fractal behaviour of the market.


Because he treats this as a continuous number series analysis he looks for long term price data. He starts with cotton because the data stretches back over 100 years. His analysis is based on this long price series and so he ignores the essence of trading which is the use of stop loss points to select the section of price activity that the trader finds desirable. His failure to understand the choice involved in trading leads him to some incorrect conclusions about the impact of volatility spikes. He assumes trading activity is continuous in the same way that price data is continuous. He assumes the trader buys and holds stocks for the same length of time as his long data series.


To be fair, his purpose is not to explain trading behaviour. His purpose is to understand the behaviour  of markets and to suggest  ways in which we may more effectively understand this behaviour. It is brilliant work that contains the seeds of many trading edges. If you really think about the markets, then this is the book you must have.



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