The Mathematics of Technical Analysis: Applying Statistics to Trading Stocks, Options and Futures

Book 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 hypothesisthe 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 system, they have been modified to analyze economically important time series. These statistical techniques allow traders to determine if a time series is stationary/non-stationary, independent/dependent, and/or random/non-random. These statistical questions are vital for traders because if a time series is non-stationary, independent, and random, it is unlikely that any analysis method, technical or fundamental, will work because the underlying rules that generate the time series change from time to time without warning. However, if a time series is stationary, dependent and non-random, the underlying rules generating prices demonstrate a consistency that will allow analysts to identify low risk/high reward trades.Author Bio: Clifford Sherry has written extensively on applying statistics to investments. He holds a Ph.D. from the Illinois Institute of Technology. He is a senior analyst and CEO of Intuitive Concepts Innovative Testing, LLC. Jason Sherry, a graduate of the University of Texas, Austin, is a financial advisor for Morgan Stanley Dean Witter.Book 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 hypothesisthe 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 system, they have been modified to analyze economically important time series. These statistical techniques allow traders to determine if a time series is stationary/non-stationary, independent/dependent, and/or random/non-random. These statistical questions are vital for traders because if a time series is non-stationary, independent, and random, it is unlikely that any analysis method, technical or fundamental, will work because the underlying rules that generate the time series change from time to time without warning. However, if a time series is stationary, dependent and non-random, the underlying rules generating prices demonstrate a consistency that will allow analysts to identify low risk/high reward trades.Author Bio: Clifford Sherry has written extensively on applying statistics to investments. He holds a Ph.D. from the Illinois Institute of Technology. He is a senior analyst and CEO of Intuitive Concepts Innovative Testing, LLC. Jason Sherry, a graduate of the University of Texas, Austin, is a financial advisor for Morgan Stanley Dean Witter.