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Mad Money stock recommendations: market reaction and performance

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Abstract

We examine the stock recommendations of Jim Cramer televised on CNBC’s Mad Money, and document significant market reactions (i.e., announcement returns and volume) to Cramer’s recommendations, particularly for small capitalization stocks. The following findings indicate that the announcement returns are primarily due to price pressure from uninformed trading as opposed to the recommendations providing new value related information: announcement returns reverse following buy recommendations; bid-ask spreads temporarily decline; and there is no evidence of positive longer-term abnormal returns. One implication, when considered in combination with other works, is that investors should be cautious in following stock recommendations announced in the mass-media.

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Notes

  1. A typical Mad Money show during our sample period consists of two general parts: a “discussion segment” in which Cramer discusses his own stock picks; and a “lightning round” where he gives his opinion on stocks about which callers inquire.

  2. We became aware of the work of Engelberg et al. only after generating our first results for this paper and Neumann and Kenny after submitting our paper for publication.

  3. See Feinberg’s (2006) article in Kiplinger’s Personal Finance.

  4. Our request to CNBC for data summarizing earlier shows has gone unfulfilled.

  5. We group Guest Interview recommendations into Cramer’s discussion segment. During the 13 month period of our sample, there were also 6 recommendations of “hold and homework.” We exclude these 6 observations from our sample. In early 2007 and after the end of our sample period, TheStreet.com’s Mad Money summaries were changed to list additional “segments” called Featured Stock, Game Plan, Mailbag, and Sudden Death that we would consider sub-segments of either a discussion segment or a lightning round.

  6. Compared to equity analysts, Cramer is more likely to issue a sell recommendation. Womack (1996) reports that for analysts of major US brokerages “new buy recommendations occur seven times more often than sell recommendations.”

  7. Results using a four factor abnormal returns model (i.e., Fama/French factors plus a momentum factor) for buy and sell recommendations are qualitatively the same as presented in Table 4, the exceptions being that abnormal returns for sell reaffirmations and DS sells of large and mid capitalization stocks are not statistically significant.

  8. For Table 4, Initial occurrence and Buy and sell reaffirmations observations for buy and sells do not sum to the buy and sell observations in Table 4 Full sample because buy (sell) observations that first follow an earlier sell (buy) recommendation during our sample period do not appear in Table 4 Initial occurrence and Buy and sell reaffirmations.

  9. We also consider discussion segment calls to be stronger than lightning round calls because Cramer independently selects the stocks to discuss in the former but not the latter, where viewer input plays a large role.

  10. Glosten and Milgrom (1985) propose that the adverse selection component of the bid-ask spread varies with the perceived information advantage of the investor trading. The lower the perceived information advantage, the lower the bid-ask spread. By definition, uninformed traders have no information advantage.

  11. As an additional caveat, we note that ideally one would compute returns using stock prices as of immediately after Mad Money recommendations airing. However, these recommendations are made after hours and we have no access to intra-day or after hours trading data.

  12. Some recent studies that use the four factor model include; Carhart (1997); Barber et al. (2001); Kosowski et al. (2006); Chordia and Shivakumar (2006); Barber et al. (2007); and Kacpercyk and Sercu (2007).

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Correspondence to Chris R. McNeil.

Appendix: The Michaely et al.’s test for abnormal volume

Appendix: The Michaely et al.’s test for abnormal volume

This appendix details our application of the Michaely et al. (1995) test statistic for abnormal volume. Let TO denote daily turnover computed as volume divided by total outstanding shares for a stock. Compute mean TO for a 100 day pre-event period for each stock, as shown in Eq. 4, where i denotes stock i and t denotes day t.

$$\overline {TOpre_i } = \frac{{\sum\limits_{t = - 125}^{ - 26} {TO_{i,t} } }}{{100}}.$$
(4)

Abnormal portfolio volume for day t is the computed as the average (for n stocks in the sample) of day t volume divided by mean pre-event volume, and then subtracting one:

$$AV_t = \left[ {\frac{{{\raise0.7ex\hbox{${\sum\limits_{i = 1}^n {^{TO_{i,t} } } }$} \!\mathord{\left/{\vphantom {{\sum\limits_{i = 1}^n {^{TO_{i,t} } } } {TOpre_i }}}\right.\kern-\nulldelimiterspace}\!\lower0.7ex\hbox{${TOpre_i }$}}}}{n}} \right] - 1.$$
(5)

The test statistic for abnormal volume, which we denote as t-stat 2 in Table 7, is calculated using a pre-event standard deviation:

$$t{\text{ - stat}}\;2 = \frac{{AV_t }}{{\sqrt {{\text{VAR}}\left( {AV_t } \right)} }}.$$
(6)
$${\text{Var}}\left( {AV_t } \right) = \frac{1}{{.99}}\sum\limits_{t = - 125}^{ - 26} {\left( {AV_t - \overline {AV} } \right)} ^2 .$$
(7)

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Keasler, T.R., McNeil, C.R. Mad Money stock recommendations: market reaction and performance. J Econ Finance 34, 1–22 (2010). https://doi.org/10.1007/s12197-008-9033-7

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