Product Description
The Mathematics of Technical Analysis by Clifford J. Sherry and Jason W. Sherry promises to revolutionize how we think about the markets. In this ground-breaking work, the authors challenge the random walk hypothesis – the idea that there is neither rhyme nor reason to the markets. This far-reaching text describes a series of simple but statistically rigorous methods for analyzing time series. Originally developed to study information processing in the nervous sys… More >>
The Mathematics of Technical Analysis: Applying Statistics to Trading Stocks, Options and Futures
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Sherry’s book provides a series of screening tools that you should apply to your historical data, such as prices, price changes, or volume. If your data passes these tests, then it is much more likely that your technical tools will work effectively and lead to profitable trades. Get an autographed copy of this book and an opportunity to discuss the tools with the author for up to 1 hour as listed on Ebay.
Rating: 5 / 5
Books which teach trade-methodology never give you any real result. They will show you some successful examples but never tell you what is the real chance of their systems. So you can learn different kinds of trading systems from those books but you can not do any real comparison for them. I have bought the Sherry’s book with the hope that I can learn some analysis for real results. I was dissapointed. It is not difficult to understand the math in the book if you have college degree. However, there is not sufficient discussion on connecting probability/statistic theory to financial market.
Rating: 3 / 5
I am a professional trader, have an MBA from a major business school, and a decent amount of Finance PhD coursework, so I do know a bit of what I’m talking about. This is one of the worst trading books I have seen. It presents extremely simple time-series analysis, using methods the author developed in some cases (and mis-applied from existing techniques in other cases). The problem is, the math and tools to do these analysis already exists and is implemented in every statistical software available.
If you need more proof of this author’s misunderstanding, turn to the last chapter where he discusses portfolio theory. You would think someone writing a book on stats would understand this, but he makes a fundamental error that no one who ever took a single finance class could make: He claims that “Beta-type risk” (market risk) can be reduced by holding a diversified portfolio if the correlations are negative!! This is absolutely wrong on two fronts — Beta risk is specifically non-diversifiable (and to reduce company-specific risk the correlations just need to be less than 1, not negative). This is one example of the many many errors in this book.
One of the authors is an “investment advisor for Morgan Stanley”?! I wonder how that is working out…
Rating: 1 / 5