Morgan Stanley used deep learning and artificial intelligence to study the text of its own analyst reports and has developed a market-beating trading strategy based on how computers read the author’s sentiment.
For each of the brokerage’s 41,758 company research reports from January 2013 to May 2019, Morgan Stanley’s model produces a score reflecting how confident the artificial intelligence was that the analyst was bullish or bearish on the stock.
Buying after the notes that the AI was most certain were bullish tended to outperform the broader market. Later refining the analysis to only reports that include price target adjustments, the new Morgan Stanley model showed 9.6% outperformance between the group of stocks top-rated by the model and the lowest group.
“Rather than isolating key words as in existing sentiment models, we used a deep learning approach to analyze complete sentences,” stock strategist Qingyi Huang wrote in a note to clients.
“Overlaying revised price targets…
