For the next edition of our new series: Blog Spotlight, we travel across the pond to London based New Economist.
The blog offers new economic research, data, events and analysis from a London-based macroeconomist who lives in London and is an economist by training. He’s worked over the years for several governments, an investment bank and a think tank.
This is part of our ongoing short list of excellent but somewhat overlooked
blogs that deserves a greater audience. Expect to see a post from a
different featured blogger here every Tuesday and Thursday evening,
Today’s focus commentary looks at: Equity analyst recommendations and IBES: rewriting history
Equity analyst recommendations and IBES: rewriting history
Just when you though corruption allegations might be abating in equity markets, along comes an explosive new study. A paper to be delivered to the January 2007 American Finance Association annual meeting in Chicago suggests that investment analysts’ historical buy recommendations have been manipulated to put them in a better light.
Rewriting History, by Alexander P Ljungqvist (Stern School of Business, NYU), Christopher Malloy (London Business School) and Felicia Marston (University of Virginia) provides evidence that nearly 20,000 records in I/B/E/S, a database of research analyst recommendations owned by Thomson Financial and widely used by investment professionals and academics, were manipulated between September 2002 and May 2004. This took the form of selective, ex post removal of analyst’s names from some of their historical recommendations. These were not random; they were concentrated among the worst performing recommendations. Here is the authors’ abstract:
Comparing two snapshots of the entire I/B/E/S analyst stock recommendations database, taken in 2002 and 2004 but each covering the same time period 1993-2002, we identify nearly twenty thousand changes of an unusual nature: the selective removal of analyst names from historic recommendations (“anonymizations”).
This practice turns out to be pervasive and non-random: Bolder recommendations are more likely to be anonymized, as are recommendations from more senior analysts, Institutional Investor “all-stars,” and those who remain in the industry beyond 2002. Abnormal stock returns following subsequently anonymized buy recommendations are significantly lower (by up to 11.0% p.a.) than those following buy recommendations that remain untouched, suggesting that particularly embarrassing recommendations are most likely to be anonymized.
Analysts whose track records appear brighter due to anonymizations experience more favorable career outcomes over the 2003-2005 period than their track records and abilities would otherwise warrant.
As the authors note, the period not only coincided with close scrutiny of Wall Street research by regulators, Congress, and the courts, but also saw a substantial downsizing of research departments of major brokerage houses in the US. The manipulation benefited the careers of those whose dud recommendations were anonymised. The paper concludes:
Whether or not analysts were in fact behind these changes, however, their track records undeniably look better than they should, and we show that the analysts concerned apparently benefited in the sense of experiencing more favorable career outcomes than their track records and abilities would otherwise warrant: Anonymizers are more likely to move jobs, to be hired by a large brokerage firm, and to move from a small to a large firm (Hong, Kubik, and Solomon’s (2000) measure of a promotion). Anonymization easily has the largest economic effect in our career outcome models.
These are very disturbing findings, and as the authors note, given the "non-random nature of the results" it is very unlikely they are attributable to chance. While "it is possible that the brokerage firms were in fact the culprits ..the patterns we document seem at odds with this interpretation".
If this is not market manipulation, I don’t know what is. Let’s hope Eliot Spitzer or the SEC investigate.
Category: Blog Spotlight
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