Abstract
In this study, using a unique dataset collected by web-scraping (using Python Programming Language), we assess analyst predictive power and whether analyst experience is associated with predictive power by tracking Jim Cramerâs predictive power for future stock returns over a two-year period. We find that Jim Cramerâs accuracy may be limited to positive and buy recommendations. Additionally, we find that there is improvement in recommendation accuracy with increase in analyst experience. However, the improvements are concentrated in the positive and buy recommendations. Finally, the featured stock segment of Jim Cramerâs show seems to have the highest recommendation accuracy for both positive and negative recommendations.
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