High‐Frequency Trading and the New Stock Market: Sense And Nonsense

The stock market has been transformed during the last 25 years. Human suppliers of liquidity like the NASDAQ dealers and NYSE specialists have been replaced by algorithmic market making; stocks that once traded on a single venue now trade across twelve exchanges and a multitude of alternative trading systems. New venues like dark pools, and new participants like high‐frequency traders, have emerged to take on prominent roles. This new market has had more than its share of controversy and regulatory scrutiny, particularly in the wake of Michael Lewis’s bestseller Flash Boys. In this article, the authors analyze five of the most controversial new market practices, including various high‐frequency trading strategies and dark pool activities. They set out a simple conceptual framework based on adverse selection and agency problems, and apply that framework to assess the welfare effects of each of the five practices. While much that is criticized is indeed objectionable, other controversial practices are much more complex than popularly imagined and may in fact be socially desirable. They conclude by evaluating a range of potential reforms to equity market structure.     

Scharfe untere und obere Schranken für die Wahrscheinlichkeit der Realisation vonk untern Ereignissen

Summary LetA ₁,...,A _n be events in a probability space (,A,W). We denote byL _k the event, that at leastk events among then eventsA ₁,...A _n occur, and byK _k the event, that exactlyk events occur. If only the inequalities _i W(A _i ) _i ,i=1,...,n, are known, we calculate sharp lower and upper bounds forW(L _k ) andW(K _k ). These bounds only depend onn, k and _i , _i ,i=1,...,n. They are relevant, when treating combined tests or confidence procedures.     

Accounting for distress in bank mergers

Most bank merger studies do not control for hidden bailouts, which may lead to biased results. In this study we employ a unique data set of approximately 1000 mergers to analyze the determinants of bank mergers. We use undisclosed information on banks’ regulatory intervention history to distinguish between distressed and non-distressed mergers. Among merging banks, we find that improving financial profiles lower the likelihood of distressed mergers more than the likelihood of non-distressed mergers. The likelihood to acquire a bank is also reduced but less than the probability to be acquired. Both distressed and non-distressed mergers have worse CAMEL profiles than non-merging banks. Hence, non-distressed mergers may be motivated by the desire to forestall serious future financial distress and prevent regulatory intervention.