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Our Quantamental Research group leverages the uniqueness and depth of our combined data and analytics offerings to uncover new investment insights.
The Quantamental Research group uncovers new anomalies to identify differentiated stock investments.
Insights from Recent Research
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At the 71st CFA Institute Annual Conference, S&P Global Market Intelligence’s Managing Director of Quantamental Research, David Pope, CFA, discussed using natural language processing to unlock new insights in corporate earnings sentiment analysis.
Our Primer demystifies the many aspects of Natural Language Processing (NLP). Three illustrations, with accompanying Python code, will show you how NLP can be used to quantify the sentiment of earnings calls. This piece answers everything from "What is NLP?" to "Where do I start?".
In a recent report examining the stock performance of the "Buy the Dip’ ("BTD") strategy within the Russell 1000 Index from January 2002 through October 2017, the team explores how a BTD strategy can be improved by overlaying three other classes of stock selection signals: institutional ownership level, stock price trend, and company fundamentals.
Exploring the performance of a trend strategy derived from gross profitability (“GP”), our back-tests confirm that Gross profitability trend ("GPtrend") has historically been an effective stock selection signal globally, with the added benefit of low to moderate correlation with commonly used investment strategies.