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.

Discrete convexity, which extends submodularity to integer vectors, has been used in the economics and management literature to characterize the behavior of optimal policies. One of its variants, called L♮-convexity, has enabled recent advances in various operations management systems. In a paper published by Operations Research in 2005, an assemble-to-order inventory system was shown to have the L♮-convexity property, which was used to motivate an efficient algorithm. In a technical note, “Error Noted in ‘Order-Based Cost Optimization in Assemble-to-Order Systems’ by Lu and Song (2005)” by Bolandnazar, Huh, McCormick, and Murota, the authors show that the proof in that paper is incorrect and L♮-convexity may not hold. Despite this error, the authors credit Lu and Song for introducing this useful concept to the operations management community.

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