Street Earnings Activation Delay

Street earnings are non-GAAP earnings, adjusted for consistency with the analyst majority basis and disseminated by forecast data providers (FDPs). We find that the time it takes an FDP to incorporate street earnings in its products (activation delay, hereafter) reflects variation in the difficulty of constructing street earnings, investor demand for timely street earnings, and FDPs' limited attention and resources. Furthermore, the market reaction to reported earnings is more timely when activation delay is shorter, and price discovery is highly concentrated during the hour after street earnings are activated. Finally, activation delay increases the delay with which street earnings are incorporated in analyst forecasts. We conclude that frictions in information processing prevent market participants from instantaneously constructing and incorporating street earnings in their decisions, and that FDPs play a key role in alleviating these frictions

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment

Determinants and Consequences of Information Processing Delay: Evidence from the Thomson Reuters Institutional Brokers’ Estimate System

We present new evidence that highlights the role of information intermediaries in the distribution and processing of earnings estimates in capital markets. We find that the time taken to activate an analyst’s earnings forecast in the Thomson Reuters Institutional Brokers’ Estimate System is related to measures of investor demand for timely information processing, processing difficulty, and limited attention. Furthermore, we find that forecast announcement returns are muted and post-announcement drift is magnified for forecasts with longer unexpected activation delay and that market inefficiency is concentrated in neglected stocks and is potentially exploitable. Finally, analyzing intra-day returns, we find that activations facilitate price discovery

Forecasting earnings using k-nearest neighbor classification

We use a simple k-nearest neighbors (k-NN) model to forecast a subject firm’s annual earnings by matching its recent earnings history to earnings histories of comparable firms, and then extrapolating the forecast from the comparable firms’ lead earnings. Out-of-sample forecasts generated by our model are more accurate than forecasts generated by the random walk; more complicated k-NN models; the matching approach developed by Blouin, Core, and Guay (2010); and popular regression models. These results are robust. Our model’s superiority holds for different error metrics, for firms that are followed by analysts and firms that are not, and for different forecast horizons. Our model also generates a novel ex ante indicator of forecast inaccuracy. This indicator, which equals the interquartile range of the comparable firms’ lead earnings, is reliable and useful. It predicts forecast accuracy and it identifies situations when our forecasts are strong (weak) predictors of future stock returns

Dual-Reporter Mycobacteriophages (Φ2DRMs) Reveal Preexisting Mycobacterium tuberculosis Persistent Cells in Human Sputum

Persisters are the minor subpopulation of bacterial cells that lack alleles conferring resistance to a specific bactericidal antibiotic but can survive otherwise lethal concentrations of that antibiotic. In infections with Mycobacterium tuberculosis, such persisters underlie the need for long-term antibiotic therapy and contribute to treatment failure in tuberculosis cases. Here, we demonstrate the value of dual-reporter mycobacteriophages (Φ2DRMs) for characterizing M. tuberculosis persisters. The addition of isoniazid (INH) to exponentially growing M. tuberculosis cells consistently resulted in a 2- to 3-log decrease in CFU within 4 days, and the remaining ≤1% of cells, which survived despite being INH sensitive, were INH-tolerant persisters with a distinct transcriptional profile. We fused the promoters of several genes upregulated in persisters to the red fluorescent protein tdTomato gene in Φ2GFP10, a mycobacteriophage constitutively expressing green fluorescent protein (GFP), thus generating Φ2DRMs. A population enriched in INH persisters exhibited strong red fluorescence, by microscopy and flow cytometry, using a Φ2DRM with tdTomato controlled from the dnaK promoter. Interestingly, we demonstrated that, prior to INH exposure, a population primed for persistence existed in M. tuberculosis cells from both cultures and human sputa and that this population was highly enriched following INH exposure. We conclude that Φ2DRMs provide a new tool to identify and quantitate M. tuberculosis persister cells