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The Evolution of Technical Analysis

Financial Prediction from Babylonian Tablets to Bloomberg Terminals

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The Evolution of Technical Analysis

Von: Andrew W. Lo, Jasmina Hasanhodzic
Gesprochen von: Paul Costanzo
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Über diesen Titel

A comprehensive history of the evolution of technical analysis from ancient times to the Internet age

Whether driven by mass psychology, fear, or greed of investors, the forces of supply and demand, or a combination, technical analysis has flourished for thousands of years on the outskirts of the financial establishment. In The Evolution of Technical Analysis: Financial Prediction from Babylonian Tablets to Bloomberg Terminals, MIT's Andrew W. Lo details how the charting of past stock prices for the purpose of identifying trends, patterns, strength, and cycles within market data has allowed traders to make informed investment decisions based in logic, rather than on luck.

The book:

  • Reveals the origins of technical analysis
  • Compares and contrasts the Eastern practices of China and Japan to Western methods
  • Details the contributions of pioneers such as Charles Dow, Munehisa Homma, Humphrey B. Neill, and William D. Gann

The Evolution of Technical Analysis explores the fascinating history of technical analysis, tracing where technical analysts failed, how they succeeded, and what it all means for today's traders and investors.

©2010 Andrew W. Lo and Jasmina Hasanhodzic (P)2012 Gildan Media Persönliche Finanzen Ökonomie
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The author took the necessary professional distance from the topic to present it objectively to the reader. He presents the historical evolution of technical analysis and its controversial image to the wider public and notably to science.

Great book, topic well explained

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Great story rolling up markets from the old Egypt to today. And the split between academic and markets. Thats worth hearing.

But the „proves“ that technical analysis works are more than weak. TA likely works sometimes in certain situations in certain environments, which is probably why computers have such a hard time with it.

And the „study“? 78 participants is not enough to call almost anything statistically significant. And showing them random charts and market charts side by side? What random numbers? A jump diffusion MC model? I highly doubt that they can distinguish those. If it’s just a normal distributed number generator, ofc. but then this is not a realistic comparison. And the side by side comparison makes the study even weaker. Show them randomly alternating and I can bet that there is no distinguishing.

Nice story, but funny proves

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