Journal of Finance and Economics
ISSN (Print): 2328-7284 ISSN (Online): 2328-7276 Website: https://www.sciepub.com/journal/jfe Editor-in-chief: Suman Banerjee
Open Access
Journal Browser
Go
Journal of Finance and Economics. 2021, 9(3), 142-146
DOI: 10.12691/jfe-9-3-4
Open AccessArticle

TV Financial Analyst Predictive Power: The Case of Jim Cramer of Mad Money

Frederick Adjei1 and Mavis Adjei2,

1Economics and Finance, Southeast Missouri State University, Cape Girardeau, USA

2Department of Marketing and Management, SIU Carbondale, Carbondale, USA

Pub. Date: June 25, 2021

Cite this paper:
Frederick Adjei and Mavis Adjei. TV Financial Analyst Predictive Power: The Case of Jim Cramer of Mad Money. Journal of Finance and Economics. 2021; 9(3):142-146. doi: 10.12691/jfe-9-3-4

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 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.

Keywords:
financial analyst recommendations predictive power

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  Brennan, M.J., and A. Subrahmanyam (1995). Investment analysis and price formation in securities markets, Journal of Financial Economics, 38, 361-381.
 
[2]  Irvine, Paul (2003). The incremental impact of analyst initiation of coverage. Journal of Corporate Finance, 9 (4), 431-451.
 
[3]  Harvey, Campbell, Khalil Mohammed, and Sandy Rattray (2011). Do Analyst Experience, Location and Gender Affect the Performance of Broker Recommendations in Europe? Working paper.
 
[4]  Li, Xi, Rodney Sullivan, Danielle Xu and Guodong Gao. (2013). Sell-Side Analysts and Gender: A Comparison of Performance, Behavior, and Career Outcomes, Financial Analyst Journal 69 (2), 83-94.
 
[5]  Malloy, Christopher (2005). The geography of equity analysts, Journal of Finance 60, 719-755.
 
[6]  Clement, M. (1999). Analyst Forecast Accuracy: Do Ability, Resources and Portfolio Complexity Matter? Journal of Accounting and Economics, 27 (3), 285-303.
 
[7]  Hong, H., and J. D. Kubik (2003). Analyzing the Analysts: Career Concerns and Biased Earnings Forecasts. Journal of Finance, 58, 313-351.
 
[8]  Brown, L. and E. Mohammad (2001). Profiting from Predicting Individual Analyst Earnings Forecast Accuracy, working paper, Georgia State University.
 
[9]  Li, X. (2005). The Persistence of Relative Performance in Stock Recommendations of Sell-Side Financial Analysts.” Journal of Accounting and Economics, 40, 129-152.
 
[10]  Hong, H.; J. D. Kubik; and A. Solomon (2000). Security Analysts’ Career Concerns and Herding of Earnings Forecasts. RAND Journal of Economics, 3, 121-144.
 
[11]  Driskill, M., M. Kirk, and J. W. Tucker (2018). Concurrent Earnings Announcements and Analysts’ Information Production. The Accounting Review, forthcoming.
 
[12]  Hirshleifer, D., Y. Levi, B. Lourie, and S. H. Teoh (2018). Decision fatigue and heuristic analyst forecasts. Working paper.
 
[13]  Corwin, S. A., S. A. Larocque, and M. A. Stegemoller (2017). Investment banking relationships and analyst affiliation bias: The impact of the global settlement on sanctioned and non-sanctioned banks. Journal of Financial Economics, 124 (3), 614-631.
 
[14]  Fama, Eugene (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. Journal of Finance, 25 (2), 383-417.
 
[15]  Barber, Brad, Reuven Lehavy, Maureen McNichols, and Brett Trueman (2001). Can investors profit from the prophets? Security analyst recommendations and stock returns, Journal of Finance, 56 (2), 531-563.
 
[16]  Fama E. F. and K. R. French (1989). Business conditions and expected returns on stocks and bonds, Journal of Financial Economics 25, 23-49.
 
[17]  Li, Y., D. Ng, and B. Swaminathan (2013). Predicting market returns using aggregate implied cost of capital, Journal of Financial Economics, 110 (2), 419-436.
 
[18]  Hansen, Lars Peter (1982). Large Sample Properties of Generalized Method of Moments Estimators, Econometrica, 50(4), 1029-1054.
 
[19]  Richardson, M. and J.H. Stock (1989). Drawing inferences from statistics based on multiyear asset returns, Journal of Financial Economics 25, 323-348.
 
[20]  Azevedo, Vitor and Sebastian Müller (2020). Analyst Recommendations and Anomalies Across the Globe, working paper.
 
[21]  Coleman, Braiden , Kenneth J. Merkley, and Joseph Pacelli (2021). Human versus Machine: A Comparison of Robo-Analyst and Traditional Research Analyst Investment Recommendations, working paper.
 
[22]  Dong, Yi and Nan Hu (2016). The Impact of NASD Rule 2711 and NYSE Rule 472 on Analyst Behavior: The Strategic Timing of Recommendations Issued on Weekends, Journal of Business Finance & Accounting, 43 (7-8), 950-975.
 
[23]  Park, Sung Jun and Ki Young Park (2018). Can Investors Profit from Security Analyst Recommendations? working paper.
 
[24]  Chemmanur Thomas J., Igor Karagodsky and Francesca Toscano (2020). Incentives, Clienteles, and Information Production: New Evidence from Investor-paid and Issuer-Paid Agency Credit Ratings and Equity Analyst Recommendations, working paper.