The Hillcrest Management Sentiment Indicator

Brian Bruce and Douglas Stark

Chapter 8 in Handbook of Applied Investment Research, 2020, pp 127-140 from World Scientific Publishing Co. Pte. Ltd.

Abstract: The advent of big data has created new opportunities for money managers. In the field of earnings expectations big data will fuel the next leap forward in modeling. The first breakthrough in the field was the creation of quantitative models using expectations of future earnings collected from analysts. The earnings surprise model was the first model to take advantage by comparing expectations to actual earnings. Next came the earnings revision models which looked at how estimates changed over time. Both proved highly predictive of future firm performance. Models since then have been limited to manipulating the data collected by vendors and put into databases. Big data allows money managers to bypass the data vendors and collect information directly from the source. In the case of earnings expectations, managers can get information directly from company management in the form of earnings call transcripts. This information can be processed by the manager to create signals that are as powerful as the original earnings surprise and earnings revision signals.

Keywords: Applied Investments; Financial Forecasting; Portfolio Theory; Investment Strategies; Fundamental and Economic Anomalies; Behaviour of Investors (search for similar items in EconPapers)
JEL-codes: G1 G11 G17 (search for similar items in EconPapers)
Date: 2020
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