Blog Archives

When analysts suppress negative information

Anna Scherbina (2008), then at the University of California, Davis, noted earlier research showing firms that performed badly were often reluctant to share negative news with investors. Frequently, the bad news was suppressed not only by firms but also by

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Have investors recognized credibility of individual analysts?

Sorescu and Subrahmanyam (2006), from Texas A&M University, Commerce, Texas, and the University of California, Los Angeles, analyzed the relation between analyst attributes (years of experience, reputation of the analysts’ brokerage houses) and the short- and long-term price reactions to

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What impact have recommendation rating levels had?

Barber, Lehavy, and Trueman (2010) – from the University of California, Davis, the University of Michigan, Ann Arbor, and the University of California, Los Angeles – examined the impact of the rating levels and changes in rating levels used by

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When analysts have disagreed, how did markets behave?

Sadka and Scherbina (2007), of the University of Washington and Harvard University, examined returns of stocks with high levels of analyst disagreement about future earnings. Analysts’ earnings forecasts were taken from the Institutional Brokers Estimate System (I/B/E/S) U.S. Detail History

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How have markets reacted when analysts initiated coverage of a stock?

This trading strategy has been excerpted from my new, Kindle eBook,The Alpha Interface: Empirical Research on the Predictability of Financial Markets. Book One: Forty Trading Strategies Based on Scientific Findings About Analysts’ Forecasts. As the title suggests, this is one

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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