Abstract
In an article published in the Financial Analysts Journal (Treynor, 1987), Jack Treynor wrote about a series of “bean jar” experiments he conducted with students in his investments courses at the University of Southern California. In the first set of experiments, he asked students to independently estimate the number of beans contained in a full jar. While most students’ individual estimates missed the actual number by a wide margin, surprisingly, the average estimates were pretty close to being correct. In the second set of experiments, he first provided students with advice on properties of the jar, such as the air space at the top of the jar, and materials of the jar. While such information supposedly could help improve the accuracy of students’ estimates, the resulting average estimates, alas, had much larger errors than those from the first set of experiments. It seems his advice did nothing more than cause common errors among students!
This work draws from, and adds discussion to, our Management Science publication, Wei, Wermers, and Yao (2015), with permission from Informs.
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Notes
- 1.
- 2.
There is also a debate on whether herds indeed irrationally give up their own opinion and rely too much on certain influential common information sources. For example, Sias (2004) argues that herds merely infer information from each other’s trades.
- 3.
This value is calculated assuming, under the null of no herding in stock-quarter i,t, that funds trade randomly and independently of each other. With this assumption, p i,t can be assumed to follow a binomial distribution with parameters (n, \( {\overline{p}}_t \)), where n = the number of funds that trade stock i during quarter t.
- 4.
Note that RPI is the correlation, either positive or negative, between fund trading and public information.
- 5.
For example, Chen, Hong, Huang, and Kubik (2004) document decreasing returns-to-scale among mutual funds.
- 6.
Recall that buying stocks (selling stocks) with a lower buy-herding (sell-herding) measure means that the fund tends to trade against the crowd; i.e., the fund is more contrarian in its trading behavior.
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Wei, K.D., Wermers, R., Yao, T. (2017). Against the ‘Wisdom of Crowds’: The Investment Performance of Contrarian Funds. In: Guerard, Jr., J. (eds) Portfolio Construction, Measurement, and Efficiency. Springer, Cham. https://doi.org/10.1007/978-3-319-33976-4_19
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