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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