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Using business and financial news, part 4

Groß-Klußmann and Hautsch (2011) confirmed the usefulness of the machine-indicated relevance of news items. Significant market responses to news were only observable for items which were identified as being relevant. Their results showed that the classification was crucial to filter out

Posted in Book Three: Twenty-Five Trading Strategies Based on Scientific Findings About Business and Financial News Tagged with: , , , , , , , , , , , , , , , , , , , , , , ,

Using business and financial news, part 3

Prototype experiments for predicting market reaction to financial news. The research literature has described a number of prototypes for predicting market’s reaction to news. The first recorded approach was by the trader Victor Niederhoffer in the early 1970’s. Niederhoffer organized

Posted in Book Three: Twenty-Five Trading Strategies Based on Scientific Findings About Business and Financial News Tagged with: , , , , , , , , , , , , , , , , , , , , , , , , ,

The correlation between volume and price direction, part 2

However, the primary result (as presented in the previous blog post, Part 1) did not hold in the price-winner, high-volume and price-winner, low-volume portfolios. Overall, high volume led to continuation in weekly returns while low volume led to reversal in

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

The correlation between volume and price direction, part 1

Alsubaie and Najand (2009), from the Department of Public Administration, Saudi Arabia, and Old Dominion University, Norfolk, Virginia, examined the relationship between abnormal changes in trading volume and short-term price behavior in the Saudi stock market. Considering prior research and

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

Enhancing reversal strategies with artificial intelligence

Li, Hoi, Zhao, and Gopalkrishnan (2012), from Nanyang Technological University, Singapore, and the Deloitte Analytics Institute (Asia), Singapore, developed a very sophisticated algorithm for portfolio selection that they labelled the “Confidence Weighted Mean Reversion” (CWMR) strategy. The principle of mean

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

Log periodic signature associated with bubbles and crashes.

Johansen, Sornette, and Ledoit (1999) and Johansen, Ledoit, and Sornette (2000), all from UCLA at that time, argued that financial bubbles and crashes exhibited unique mathematical signatures known as log-periodic oscillations. This refers to a sequence of oscillations with progressively

Posted in Bubbles and Crashes Tagged with: , , , , , , , , , , , , , , , , , , , , , , ,

Do momentum strategies work for weekly stock returns?

Gutierrez and Kelley (2008), from the University of Oregon and the University of Arizona, hypothesized that weekly stock returns would show a momentum effect. They were aware of research from the 1990s that found a short-term reversal effect. In those

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

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: , , , , , , , , , , , , , , , , , , , , , , ,

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