Blog Archives

Do reversal strategies work?

De Groot, Huij, and Zhou (2012), of Robeco Quantitative Strategies and Erasmus University, Rotterdam, The Netherlands, measured the profitability of reversal (or mean reversion) strategies applied to various market cap segments of the U.S. stock market. They examined stocks from

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Are exponential moving averages superior to simple moving averages?

Camillo Lento (2010), of Lakehead University, Thunder Bay, Ontario, Canada, examined dual moving average crossover systems, comparing simple with exponential moving averages. The analysis was conducted on the exchange traded funds for the S&P 500 (SPY), NASDAQ (QQQ), and Dow

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Does momentum-trading work with monthly charts, part 2

Wei and Yang (2012), from the University of Toronto, Canada, examined momentum in a large sample of U.S. stocks from 1964 to 2009. At the beginning of each month, stocks were sorted quintiles based on their realized past returns. Equally

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Does momentum-trading work with monthly charts, part 1

Molchanov and Stork (2010), from Massey University in New Zealand, examined monthly returns, from 1992 through 2007, of 220 of the world’s largest and most liquid stocks. The stocks came from five regions: United States (Dow Jones Industrial Average, 30

Posted in Book Two: Twenty-Four Trading Strategies Based on Scientific Findings About Technical Analysis Tagged with: , , , , , , , , , , , , , , , , , , , , , , , , , ,

Do support and resistance price levels cluster around round numbers?

Carol Osler (2003), of Brandeis University, documented clustering in currency stop-loss and take-profit orders, and used that clustering to explain two familiar predictions made by technical analysts: (1) trends tend to reverse course at predictable support and resistance levels, and

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Can market news be combined with technical analysis?

Zhai, Hsu, and Halgamuge (2007), of the University of Melbourne, Australia, have developed a unique approach for analyzing news stories in combination with market price data using a type of machine learning known as a support vector machine. The research

Posted in Book Two: Twenty-Four Trading Strategies Based on Scientific Findings About Technical Analysis Tagged with: , , , , , , , , , , , , , , , , , , , , , , ,

Technical analysis: Introduction to Book Two

Technical analysis (TA) is based on the startlingly simple idea that all relevant fundamental information about a tradable security is incorporated into the price. Therefore, all technical trading strategies are based on variations of price and volume. Technical analysis includes

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Book Three: Trading With The News

Learn about a news-based trading system that yielded a back-tested, average annualized, compounded return from 2000 to 2011 of 58.6%.

“Only once you’ve done your homework will you be able to understand how the stock market works and learn to distinguish between news and noise.” Maria Bartiromo, Use The News

Book Two: Technical Analysis

Learn about the "trend recalling" algorithm that yielded researchers a simulated annual return of greater than 400% in multiple tests.

“The scientific method is the only rational way to extract useful knowledge from market data and the only rational approach for determining which technical analysis methods have predictive power.”
David Aronson, Evidence Based Technical Analysis

Book One: Analysts’ Forecasts

Learn the strategy, based on analysts' revised forecasts, that yielded researchers an average of 1.13% - 2.19% profit per trade, for trades lasting one to two days?

Learn how certain analysts' recommendations, following brokerage hosted investment conferences, yielded profits of over 3% during a two-day holding period?

Learn how researchers found an average profitability of 1.78% for two-hour trades following an earnings announcement?

"This set of tools can help both ordinary and professional investors alike to re-think and re-vitalize their stock picking, timing and methods. A young, aspiring Warren Buffet could put this book to good use."
James P. Driscoll, PhD, investor

Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments by David Aronson (software included)

Evidence-Based Technical Analysis by David Aronson

Archive of Earlier Posts