Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-standard errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Locked and crossed markets on NASDAQ and the NYSE

The NBBO for an average active stock is non-positive (locked or crossed) 10.58% and 4.05% of the time on, respectively, the NASDAQ and the NYSE inter-markets. Locks and crosses are frequent fleeting events that usually accompany significant price changes. Non-positive NBBOs arise because of (i) simultaneous and (ii) tardy quote updates, (iii) electronically unreachable quotes, (iv) reluctance to trade against autoquotes, (v) order transit considerations, and (vi) ECN liquidity attraction efforts. Most locks and crosses result from competitive trading practices in contemporary fragmented markets.

Competition in the market for NASDAQ securities

The study investigates competition in the market for NASDAQ stocks during a recent period in US equity markets history when three major Electronic Communication Networks (ECNs)--Archipelago, Island, and Instinet--are identifiable in the Trade and Quote (TAQ) database. We show that the ECNs compete with NASDAQ's SuperMontage on the basis of quotes, execution times, and costs. The three ECNs differ due to uniqueness of their limit order books, cost schedules, and heterogeneity of trading clienteles. Informed traders are shown to prefer venues with sufficient liquidity over those that guarantee anonymity of executions. Despite high levels of segmentation, uneven regulation, and controversial order attraction practices, quote competitiveness is found to increase the probability of executions on all four venues.