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The Dog That Did not Bark:
Insider Trading and Crashes
Jose M. Marin
Universitat Pompeu Fabra and CREA
Jacques Olivier
HEC School of Management, GREGHEC and
CEPR
Research Seminar Finrisk
University of Zurich - 12/15/2006
Motivation (1)
 A famous quote from Sir Arthur Conan
Doyle (« Silver Blaze »):
‘Is there any other point to which you would
wish to draw my attention?’
‘To the curious incident of the dog in the nighttime’
‘The dog did nothing in the night-time’
‘That was the curious incident’ remarked
Sherlock Holmes
Research Seminar Finrisk
University of Zurich - 12/15/2006
Motivation (2)
 This paper:
– The mystery: why the price of individual
stocks sometimes crashes without the arrival
of fundamental news?
– The dog: Insiders
– The hypothesis: crashes may be caused by
the absence of dog barking (insiders trading)
Research Seminar Finrisk
University of Zurich - 12/15/2006
Outline of the Talk
 Theory
– Outline of the model and key predictions
 Existing literature
– Models of crashes
– Existing evidence on insider trading
– What we can learn from the data





The data
Basic results
Our story vs. competing hypotheses
Robustness checks
Conclusions
Research Seminar Finrisk
University of Zurich - 12/15/2006
The Theory (1)
 Theoretical Model:
– Static CARA-normal REE model with floor constraints on holdings
(e.g. short-sales constraints)
– Uninformed investors:
 Rational, risk averse
 Observe the equilibrium price
– Insiders:




Rational, risk averse
Income risk à la Bhattacharya-Spiegel
Observe a noisy signal about fundamentals
Subject to floor constraint on holdings
– Key element: no noise traders, thus trading by insiders is known
by uninformed investors
Research Seminar Finrisk
University of Zurich - 12/15/2006
Research Seminar Finrisk
University of Zurich - 12/15/2006
The Theory (2)
 When insiders are selling:
– Uninformed investors observe the sales
– Partial downward adjustment of price proportional to insider sales
 When insiders do not trade but floor constraint nonbinding
– No adjustment of prices
 When insiders do not trade but floor constraint binding
– Uninformed investors suspect that the insiders received bad
news (they don’t buy and they cannot sell)
– Uninformed investors cannot infer how bad the news received by
insiders really are
– Lower expected payoff + higher uncertainty → stock price
crashes
Research Seminar Finrisk
University of Zurich - 12/15/2006
The Theory (3)
 Multiple equilibria with similar qualitative properties:
Research Seminar Finrisk
University of Zurich - 12/15/2006
The Theory (4)
 Testable Implications:
– Crash occurs when floor constraint is binding, thus:
 Insider sales in the past should raise the probability of a
crash today
– Crash occurs when insiders are not trading, thus:
 Insider sales today should lower the probability of a crash
today
– No ceiling constraint, thus:
 No symmetric finding for (positive) jumps of stock price
Research Seminar Finrisk
University of Zurich - 12/15/2006
Existing Literature (1)
 Two broad families of models of crashes
– Models where crashes bring prices closer to fundamental
values:
 Bubbles (e.g. Allen, Morris and Postlewaite, 1993)
 Herding (e.g. Devenou and Welch, 1996)
 Trading constraints or transaction costs (e.g. Cao, Coval and
Hirschleifer, 2002 ; Harrison and Hong, 2003)
– Models where crashes are periods of higher uncertainty about
true value
 E.g. Barlevy-Veronesi (2003), Yuan (2005), us
 What the data can tell us: do crashes coincide with
informed investors (insiders) getting into the market or
out of the market?
Research Seminar Finrisk
University of Zurich - 12/15/2006
Existing Literature (2)
 Consensus of existing literature on insider
trading (e.g. Lakonishok and Lee, 2001,
Friederich et al., 2002, Fidrmuc et al. 2006)
– Insider purchases contain information
– Insider sales mostly driven by liquidity
 What our model tells us: impact of insider sales
on returns theoretically ambiguous
 What the data can tell us: do insider sales
contain information about crashes?
Research Seminar Finrisk
University of Zurich - 12/15/2006
The Data (1)
 Insider Transactions:
– TFIF Database
– All insiders transactions for stocks traded on NYSE,
NASDAQ, AMEX between 1985 and 2002
– Cleaning procedure taken directly from Lakonishok
and Lee (2001)
 Returns data: CRSP
 Earning announcement dates: Compustat
Research Seminar Finrisk
University of Zurich - 12/15/2006
The Data (2)
 Crash variables:
– Constraint imposed by our model:
 Has testable implications about when a crash occurs
 Does not have testable implications about size of crash (because
of multiple equilibria)
 Thus, define crash variable as a 0/1 variable
– Constraint imposed by regulation:
 Prior to 2002, insider trade may be reported only month after trade
 Thus, work at monthly frequencies
– Constraint imposed by our model:
 Makes sense at individual stock level
 Makes less sense at the level of the market
 Thus need to correct for market fluctuations
Research Seminar Finrisk
University of Zurich - 12/15/2006
The Data (3)
 Crash variables (continued):
– Thus, two alternative measures of crashes:
 ERCRASHi,t = 1 if excess return of stock i in month t is more
than 2 standard deviations away and below average excess
return (computed over a 5-year rolling window)
 MMCRASHi,t computed the same way as ERCRASH using 1factor beta adjustment
 Average threshold for a monthly return to be considered a crash:
- 22%
Research Seminar Finrisk
University of Zurich - 12/15/2006
The Data (4)
 Insider trading variables
– INSSAL, INSPURCH and INSTV
– Normalized by market capitalization of the stock at the close of the
transaction day
 Past returns
– Included for two reasons:
 Found to predict insider trading by existing literature
 Found to predict negative skewness by existing literature
 Total trading volume
– Included for two reasons:
 Found to predict negative skewness by existing literature
 Want to make sure that insider trading is not a proxy for total trading volume
Research Seminar Finrisk
University of Zurich - 12/15/2006
Basic Results (1)
 Preliminary regression: do crashes coincide with
insiders getting into the market or out of the market ?
Research Seminar Finrisk
University of Zurich - 12/15/2006
Basic Results (2)
 Leading regression: does the pattern of insider sales
predict crashes the way suggested by the theory?
Research Seminar Finrisk
University of Zurich - 12/15/2006
Competing Stories (1)
 Insiders trying to evade SEC scrutiny:
– SEC investigates insider trades close to date of large stock market
fluctuations
– Insiders who do not want to see their trades investigated only exploit
long-lived information
– Thus selling by insiders today unlikely to coincide with crash in near
future
 Key factual element: SEC prosecutes at least as much insiders
having purchased stocks before (positive) jumps as they do insiders
having sold shares before crashes (e.g. Meulbroek, 1992)
 Implication:
– If the “evading SEC scrutiny” story is correct then pattern of insider
purchases prior to (positive) jumps should be at least as strong as
pattern of insider sales prior to crashes
– If our story is correct, then pattern should disappear
Research Seminar Finrisk
University of Zurich - 12/15/2006
Competing Stories (2)
 Is the pattern of insider purchases prior to jumps the
same as pattern of insider sales prior to crashes?
Research Seminar Finrisk
University of Zurich - 12/15/2006
Competing Stories (3)
 Result could be a pure artefact:
– Many crashes occur on earning announcement dates
– Insiders are not allowed to trade before earning announcement
dates
– Thus we observe in the data that times at which insiders have
not traded also correspond to times at which crashes are more
frequent
 Implication:
– If the “earning announcement date” story is correct then pattern
of insider sales prior to crashes should disappear once we
remove all observations corresponding to months where earning
announcement occurred
– If our story is correct, then the evidence should be at least as
strong as in the entire sample
Research Seminar Finrisk
University of Zurich - 12/15/2006
Competing Stories (4)
 What is the evidence in the subsample without
earning announcement dates?
Research Seminar Finrisk
University of Zurich - 12/15/2006
Robustness Checks (1)
 Estimation procedure:
– This version: OLS with Newey-West standard errors
– Next version: Conditional Logit with Fixed Effects
Research Seminar Finrisk
University of Zurich - 12/15/2006
Robustness Checks (2)
 Definition of crash variable
– Crashes defined using raw returns
– One of two variables loses significance
 Dividing the sample into two subsamples
– Before and after 1996
– Stronger results after 1996
 Window for past insider trading
– 6 months vs. 1 year vs. 2 years
– Retain significance
– 2 years works slightly better than 1 year which works slightly
better than 6 months
Research Seminar Finrisk
University of Zurich - 12/15/2006
Conclusions
 Insiders get out of the market shortly before it
crashes
– Implication: crashes are periods of higher uncertainty
 Pattern of insider sales help predict crashes
– Implication: insider sales also contain information
 Pattern of insider sales before crashes and
pattern of insider purchases before jumps are
different
Research Seminar Finrisk
University of Zurich - 12/15/2006