eng Science and Education Publishing Journal of Finance and Economics 2328-7276 2021-06-25 9 3 142 146 10.12691/jfe-9-3-4 JFE2021934 article Frederick Adjei 1 Mavis Adjei fadjei@semo.edu 2 Economics and Finance, Southeast Missouri State University, Cape Girardeau, USA Department of Marketing and Management, SIU Carbondale, Carbondale, USA 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 Cramer¡¯s predictive power for future stock returns over a two-year period. We find that Jim Cramer¡¯s 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 Cramer¡¯s show seems to have the highest recommendation accuracy for both positive and negative recommendations. http://pubs.sciepub.com/jfe/9/3/4/jfe-9-3-4.pdf financial analyst recommendations predictive power