Investors' reactions to management earnings guidance: The joint effect of investment position, news valence, and guidance form

We report the results of an experiment that shows that investors' earnings- and investment-related judgments are jointly influenced by their investment position (long versus short), the news valence of guidance issued by management, and the amount of ambiguity in the guidance. Prior research indicates that guidance form (point versus range) has no effect on investors' earnings estimates made in reaction to management guidance. We extend this research by showing that guidance form matters, conditional on investment position and news valence. Similarly, prior research indicates that investors who hold long (short) positions in a stock are more optimistic (pessimistic) about the company's prospects. We extend this research by showing that the effect of investment position documented in prior studies is conditional on news valence and guidance form. We contribute to prior literature on the effects of investment position and guidance form by delineating boundary conditions for each of these effects. © 2009 University of Chicago on behalf of the Accounting Research Center.postprin

When does analyst reputation matter? Evidence from analysts’ reliance on management guidance

We investigate the joint effects of analyst reputation, uncertainty and guidance news valence on analysts’ reliance on management guidance. We find that, compared to less reputable analysts, reputable analysts rely less on guidance when they issue earnings forecasts. This analyst reputation effect is stronger when earnings and information uncertainty are higher or when the guidance contains good news. Further analysis suggests that both reputable and less reputable analysts sacrifice their forecast accuracy when they rely less on guidance; however, reputable analysts are compensated to a greater extent by the increased informativeness of their forecasts. Finally, we find that analysts’ future career advancement is enhanced when their reliance is low

The impact of point mutations in the human androgen receptor : classification of mutations on the basis of transcriptional activity

Peer reviewedPublisher PD

Microtubules gate tau condensation to spatially regulate microtubule functions.

Tau is an abundant microtubule-associated protein in neurons. Tau aggregation into insoluble fibrils is a hallmark of Alzheimer's disease and other types of dementia1, yet the physiological state of tau molecules within cells remains unclear. Using single-molecule imaging, we directly observe that the microtubule lattice regulates reversible tau self-association, leading to localized, dynamic condensation of tau molecules on the microtubule surface. Tau condensates form selectively permissible barriers, spatially regulating the activity of microtubule-severing enzymes and the movement of molecular motors through their boundaries. We propose that reversible self-association of tau molecules, gated by the microtubule lattice, is an important mechanism of the biological functions of tau, and that oligomerization of tau is a common property shared between the physiological and disease-associated forms of the molecule

The stellar and sub-stellar IMF of simple and composite populations

The current knowledge on the stellar IMF is documented. It appears to become top-heavy when the star-formation rate density surpasses about 0.1Msun/(yr pc^3) on a pc scale and it may become increasingly bottom-heavy with increasing metallicity and in increasingly massive early-type galaxies. It declines quite steeply below about 0.07Msun with brown dwarfs (BDs) and very low mass stars having their own IMF. The most massive star of mass mmax formed in an embedded cluster with stellar mass Mecl correlates strongly with Mecl being a result of gravitation-driven but resource-limited growth and fragmentation induced starvation. There is no convincing evidence whatsoever that massive stars do form in isolation. Various methods of discretising a stellar population are introduced: optimal sampling leads to a mass distribution that perfectly represents the exact form of the desired IMF and the mmax-to-Mecl relation, while random sampling results in statistical variations of the shape of the IMF. The observed mmax-to-Mecl correlation and the small spread of IMF power-law indices together suggest that optimally sampling the IMF may be the more realistic description of star formation than random sampling from a universal IMF with a constant upper mass limit. Composite populations on galaxy scales, which are formed from many pc scale star formation events, need to be described by the integrated galactic IMF. This IGIMF varies systematically from top-light to top-heavy in dependence of galaxy type and star formation rate, with dramatic implications for theories of galaxy formation and evolution.Comment: 167 pages, 37 figures, 3 tables, published in Stellar Systems and Galactic Structure, Vol.5, Springer. This revised version is consistent with the published version and includes additional references and minor additions to the text as well as a recomputed Table 1. ISBN 978-90-481-8817-

Enhancing gold recovery from electronic waste via lixiviant metabolic engineering in Chromobacterium violaceum

10.1038/srep02236Scientific Reports3

Data analysis issues for allele-specific expression using Illumina's GoldenGate assay.

BACKGROUND: High-throughput measurement of allele-specific expression (ASE) is a relatively new and exciting application area for array-based technologies. In this paper, we explore several data sets which make use of Illumina's GoldenGate BeadArray technology to measure ASE. This platform exploits coding SNPs to obtain relative expression measurements for alleles at approximately 1500 positions in the genome. RESULTS: We analyze data from a mixture experiment where genomic DNA samples from pairs of individuals of known genotypes are pooled to create allelic imbalances at varying levels for the majority of SNPs on the array. We observe that GoldenGate has less sensitivity at detecting subtle allelic imbalances (around 1.3 fold) compared to extreme imbalances, and note the benefit of applying local background correction to the data. Analysis of data from a dye-swap control experiment allowed us to quantify dye-bias, which can be reduced considerably by careful normalization. The need to filter the data before carrying out further downstream analysis to remove non-responding probes, which show either weak, or non-specific signal for each allele, was also demonstrated. Throughout this paper, we find that a linear model analysis of the data from each SNP is a flexible modelling strategy that allows for testing of allelic imbalances in each sample when replicate hybridizations are available. CONCLUSIONS: Our analysis shows that local background correction carried out by Illumina's software, together with quantile normalization of the red and green channels within each array, provides optimal performance in terms of false positive rates. In addition, we strongly encourage intensity-based filtering to remove SNPs which only measure non-specific signal. We anticipate that a similar analysis strategy will prove useful when quantifying ASE on Illumina's higher density Infinium BeadChips.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are