We
develop a straightforward method to find manipulation by corporate
insiders of stock option award or exercise dates.  We test the method
against disclosed backdating companies and find the method to be
extremely reliable.  The study can be downloaded at the following link:
(http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1326517). 


 

In
our study completed in June 2009, we offer an analysis of the economic
consequences of stock option backdating into areas that previous
researchers have been unable to address.  We are the first study to
explore the economic consequences associated with backdating that has
remained undisclosed to the public (and therefore to the
research community).  We find that undisclosed backdating companies
suffer negative stock returns, lower accounting returns, and a rate of
negative stock market delisting reasons that are all at least as bad,
in some cases worse, than disclosed backdating companies.  This has
significant theoretical implications, suggesting that market
participants are able to identify and punish backdating companies even
if regulators do not, and that vigorous disclosure and enforcement may
actually mitigate losses associated with backdating.

 

Previous
authors (e.g., Lie 2005) have asserted, and the community has
apparently accepted, that public filings and stock price data alone
cannot be used to establish a sample of companies that committed
backdating.  Thus, previous studies have either directly aggregated
grant-level data (e.g., Lie 2005, Heron and Lie 2009) or used samples
of publicly-disclosed backdating companies (e.g., Bernile and Jarrell
2009, Armstrong and Larcker 2009).  Our study now makes clear that both
approaches have (a different set of) significant shortcomings, and that
neither can be used to investigate the economic consequences to
undisclosed backdating. 

 

We have spent the last
two years developing a statistical test that can determine if a
company’s entire pattern of grants is abnormally favorable at a
pre-determined cutoff level.  This allows us to derive the first sample
of both disclosed and undisclosed backdating companies that is free
from biases due to the disclosure process.  While the technique and the
sample are not ends in themselves, they are necessary means to an end
of determining the economic consequences to undisclosed backdating
companies.

 

We also expand the analysis to
include, for example, associating characteristics with undisclosed
backdating companies and investigating aspects of the disclosure
process itself.  We find that small market capitalization companies are
strongly overrepresented in the sample of undisclosed backdating
companies, indicating a bias in the discovery and disclosure process. 
We have also produced the most rigorous measure to date of the ratio of
disclosed to undisclosed backdaters.  This is a hotly debated question
in the backdating literature, and our extensively supported results (we
devote many pages to this and the related issues of error analysis,
control testing, and extrapolation from the tested sample to the parent
population) strongly challenge the conclusions of a recently published
study (e.g., Heron and Lie 2009).

 

In our study,
we also perform a series of control tests, reported in Section 4.7.,
that increased our confidence and allowed us to slightly relax the
sample cutoff from 0.04% to 0.05%.  That expanded the high probability
(of) backdating sample from 131 to 141 companies.  We have also
shortened and improved the efficiency of the SAS code provided in the
appendix. 

 

The two additional applications of the
statistical technique are to test for backdating at the managerial
level (e.g., CFO, CEO, inside and outside directors) and at the
individual level, leading to a new finding that managers backdate much
more frequently than outside directors.  This last result argues
against the suggestion (Dierker and Hemmer 2008, Gao and Mahmudi 2008)
that backdating is an efficient contracting mechanism knowingly entered
into by managers and directors.  At the individual level, we offer
empirical evidence that an individual-level analysis can detect stock
option backdating, in some cases, when a company probability value is
higher. 

 

In sum, we offer a direct test of
whether companies or individuals appear to have obtained extremely
favorable pricing of stock option awards.

more:  http://www.glgroup.com/News/How-Stock-Option-Backdating-Can-Be-Detected-41707.html