For years, the Securities and Exchange Commission (SEC) accidentally distributed securities disclosures to some investors before the public. We exploit this setting, which is unique because the delay until public disclosure was exogenous and the private information window was well defined, to study informed trading with a random stopping time. Trading intensity and the pace at which prices incorporate information decrease with the expected delay until public release, but the relation between trading intensity and time elapsed varies with traders' learning process. Noise trading and relative information advantage play similar roles as in standard microstructure theories assuming a fixed time window.
Cybersecurity has become a significant concern in corporate and commercial settings, and for good reason: a threatened or realized cybersecurity breach can materially affect firm value for capital investors. This paper explores whether market arbitrageurs appear systematically to exploit advance knowledge of such vulnerabilities. We make use of a novel data set tracking cybersecurity breach announcements among public companies to study trading patterns in the derivatives market preceding the announcement of a breach. Using a matched sample of unaffected control firms, we find significant trading abnormalities for hacked targets, measured in terms of both open interest and volume. Our results are robust to several alternative matching techniques, as well as to both cross-sectional and longitudinal identification strategies. All told, our findings appear strongly consistent with the proposition that arbitrageurs can and do obtain early notice of impending breach disclosures, and that they are able to profit from such information. Normatively, we argue that the efficiency implications of cybersecurity trading are distinct-and generally more concerning-than those posed by garden-variety information trading within securities markets. Notwithstanding these idiosyncratic concerns, however, both securities fraud and computer fraud in their current form appear poorly adapted to address such concerns, and both would require nontrivial re-imagining to meet the challenge (even approximately).
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