Blame the professors: Just as the option backdating scandal started with academic researchers noting mathematical anomalies, so too might the next brewing scandal: the I/B/E/S Analyst ratings back dating scandal.
According to a Barron’s article by Bill Alpert (buried on page 39), several professors have discovered what they describe as 54,729 non-random, ex-post changes out of 280,463 observations — a little over 19.5% of analyst recs (abstract below):
"The professors found
almost 55,000 changes that had been made in the I/B/E/S database of
stock-analyst recommendations maintained by Thomson, the Stamford,
Conn., firm that is a leading vendor of financial data. The alterations
made Wall Street’s record of recommendations look more conservative —
hiding Strong Buy recommendations and adding Sell recommendations from
1993 to 2002. That is a period for which Wall Street has drawn heat and
government sanctions for touting Internet bubble stocks.
As a result of the changes, the stock picks shown in
the database would have created annual gains that were 15% to 42%
better than the originally recorded recommendations, using a trading
strategy based on analysts’ recommendations."
The firms were the most significant participants in the data backdating were also the firms who had the closest relationship between banking and research and were the hardest hit by the Spitzer enforced settlement.
From page four of the academic working paper notes exactly how significant this was:
"Why do the historical data now look different than they once did? The contents of the database changed at some point between September 2002 and May 2004, a period that 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 at most major brokerage firms in the U.S.
The paper outlines four types of data changes: 1) non-random removal of analyst names from historic recommendations (anonymizations); 2) the addition of new records not previously part of the database; 3) the removal of records that had been in the data; and 4) alterations to historical recommendation levels.
The net result of this was to make many specific trading strategies appear better in retrospect than they actually were. Buying top rated stocks and shorting lowest rated stocks, based on the changed data, now perform 15.9% to 42.4% better on the 2004 revised data than on the 2002 tape, the professors state.
Further, the profs observe the career paths of many analyst recs: "Analysts
whose track records are affected are associated with more favorable
career outcomes over the 2003-2005 period than their track records and
abilities would otherwise warrant."
to communication received from Thomson Financial (the owner of I/B/E/S)
in November and December 2006, the anonymizations were caused by a
series of software glitches, introduced in 2002-2003.1 Surprisingly,
despite the seemingly random nature of this type of shock to the data,
the resulting patterns have apparently systematic components, rather
than appearing random. For instance, bolder recommendations are more
likely to be anonymized, as are recommendations from more senior
analysts and Institutional Investor all-stars.
The characteristics of the additions and
deletions are similarly unusual. Additions disproportionately consist
of holds and sells; indeed, in the case of one prominent brokerage
firm, 91.5% of its 234 additions are sells, and these increase the
number of sells the firm has on the 2002 tape by a factor of 20.
Deletions, on the other hand, disproportionately consist of strong
buys, while alterations disproportionately consist of buys and strong
buys (which are typically revised down). Perhaps most strikingly, all
four types of changes correlate strongly with survival by both the
brokerage firm and by the analyst.
Follow the correlation:
firms associated with these changes are substantially larger, both in
terms of the size of their investment banking operations and the size
of their research departments. Most remarkably, they employ between
eight and 16 times more analysts on average in 2002 than do unaffected
brokerage firms. . . In fact, continuing to publish research appears to
be a pre-condition for a brokerage firm’s recommendations to have
changed: Not a single recommendation associated with one of the 89
brokerage firms that have ceased publishing investment research by 2002
has been anonymized, whereas an astonishing 85.4% of the 280 firms that
continue publishing research had some recommendations anonymized.
Similar, though slightly less extreme patterns hold for alterations,
deletions, and additions.
And lastly, consider this:
"A former Thomson executive with knowledge
of the I/B/E/S database told me he was skeptical that Thomson’s
validation procedures could prevent a concerted effort by Wall Street
to retouch its track record. The Thomson data are maintained by
overworked, inexperienced clerks, said the former executive."
Ouch . . .
This may turn out to be the most overlooked financial story of the weekend.
DISCLOSURE: We have a modest short position in Thomson Corp (TOC)
Mysterious Changes in Key Wall Street Data
Barron’s, MONDAY, MARCH 5, 2007
New York University
CHRISTOPHER J. MALLOY
London Business School
FELICIA C. MARSTON
University of Virginia
February 20, 2007, AFA 2007 Chicago Meetings Paper http://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID963981
Abstract: Comparing two snapshots of the historical I/B/E/S database of research
analyst stock recommendations, taken in 2002 and 2004 but each covering
the same time period 1993-2002, we identify 54,729 ex post changes (out
of 280,463 observations), including alterations of recommendation
levels, additions and deletions of records, and removal of analyst
names. The changes appear non-random across brokerage firms, analysts,
and tickers, and have a significant impact on the overall distribution
of recommendations across stocks and within individual stocks and
brokerage firms. They also affect trading signal classifications,
back-testing inferences, track records of individual analysts, and
models of analysts’ career outcomes in the three years following the