The Effect of Voluntary Disclosure on Firm Risk and Firm Value: Evidence from Management Earnings Forecasts

This study investigates whether the voluntary disclosure of management earnings forecasts influences investors’ assessment of firm risk and firm value. We find a significant negative relationship between the issuance of management earnings forecasts and a variety of measures of firm risk (idiosyncratic risk, stock return volatility, beta, and bid-ask spreads), with more frequent, more precise and more accurate earnings forecasts further decreasing firm risk. Our results therefore suggest that information quality is an important determinant of both diversifiable risk and nondiversifiable systematic risk. We also demonstrate that management earnings forecasts are positively associated with firm value as captured by Tobin’s Q while more frequent, precise and accurate forecasts further enhance valuation premiums. Finally, we find that management earnings forecasts impact firm value not only through a reduction in firm risk, but also through changing investors\u27 perceptions about future cash flows. Our results are robust to various sensitivity checks. Overall, releasing high-quality management earnings forecasts is associated with important capital market benefits

Seeking Environmental Stewardship One Garden at a Time

Master Gardeners and teachers in Anne Arundel County MD partnered to give hands-on educational experiences promoting environmental stewardship, how we treat the environment when nobody is watching. The partnership supports and teaches ecological reconciliation by building and caring for 4964 ft2 (1578 m2) of native plant gardens. This reproducible project encourages environmental stewardship without rhetoric, one spadeful at a time

General Tests of Latent Variable Models and Mean-Variance Spanning

The methods of Gibbons and Ferson (1985) are extended, relaxing the assumption that expected returns are linear functions of predetermined instruments. A model of conditional mean-variance spanning generalizes Huberman and Kandel (1987). The empirical results indicate that more than a single risk premium is needed to model expected stock and bond returns, but the number of common factors in the expected returns is small. However, when size-based common stock portfolios proxy for the risk factors, we reject the hypothesis that four of them describe the conditional expected returns of the other assets

Retail Financial Advice: Does One Size Fit All?

Using unique data on Canadian households, we show that financial advisors exert substantial influence over their clients\u27 asset allocation, but provide limited customization. Advisor fixed effects explain considerably more variation in portfolio risk and home bias than a broad set of investor attributes that includes risk tolerance, age, investment horizon, and financial sophistication. Advisor effects remain important even when controlling flexibly for unobserved heterogeneity through investor fixed effects. An advisor\u27s own asset allocation strongly predicts the allocations chosen on clients\u27 behalf. This one‐size‐fits‐all advice does not come cheap: advised portfolios cost 2.5% per year, or 1.5% more than life cycle funds

Double Then Nothing: Why Stock Investments Relying on Simple Heuristics May Disappoint

ABSTRACT Behavioral researchers argue that while individuals often rely on heuristics or rules of thumb that reduce the complexity involved in predicting values, such heuristics can lead to severe and systematic errors. I test this argument in an investment context by focusing on a simple heuristic whereby momentum traders are attracted to buying stocks that have recently doubled in price in anticipation of further gains. I show that such a strategy can lead to predictable disappointment for these investors and severe underperformance relative to the market (-28% over a four-year period), whereas investors who avoid relying on this simple heuristic are likely to perform as expected, on average similar to the overall market. I also find that underperformance is more severe for stocks that have doubled faster. The "doubling" variable is a significant predictor of future price reversals in addition to past performance per se, as uncovered by JEL Codes: G11, G12, G1

Speckle tracking as a method to measure hemidiaphragm excursion

Introduction: Diaphragm excursion measured via ultrasound may be an important imaging outcome measure of respiratory function. We developed a new method for measuring diaphragm movement and compared it to the more traditional M‐mode method. Methods: Ultrasound images of the right and left hemidiaphragms were collected to compare speckle tracking and M‐mode measurements of diaphragm excursion. Speckle tracking was performed using EchoInsight (Epsilon Imaging, Ann Arbor, Michigan). Results: Six healthy subjects without a history of pulmonary diseases were included in this proof‐of‐concept study. Speckle tracking of the diaphragm is technically possible. Unlike M‐mode, speckle tracking carries the advantage of reliable visualization and measurement of the left hemidiaphragm. Conclusions: Speckle tracking accounted for diaphragm movement simultaneously in the cephalocaudad and mediolateral directions, unlike M‐mode, which is 1‐dimensional. Diaphragm speckle tracking may represent a novel, more robust method for measuring diaphragm excursion, especially for the left hemidiaphragm. Muscle Nerve 55: 125–127, 2017Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135149/1/mus25380.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135149/2/mus25380_am.pd

In Vivo 3D Digital Atlas Database of the Adult C57BL/6J Mouse Brain by Magnetic Resonance Microscopy

In this study, a 3D digital atlas of the live mouse brain based on magnetic resonance microscopy (MRM) is presented. C57BL/6J adult mouse brains were imaged in vivo on a 9.4 Tesla MR instrument at an isotropic spatial resolution of 100 μm. With sufficient signal-to-noise (SNR) and contrast-to-noise ratio (CNR), 20 brain regions were identified. Several atlases were constructed including 12 individual brain atlases, an average atlas, a probabilistic atlas and average geometrical deformation maps. We also investigated the feasibility of using lower spatial resolution images to improve time efficiency for future morphological phenotyping. All of the new in vivo data were compared to previous published in vitro C57BL/6J mouse brain atlases and the morphological differences were characterized. Our analyses revealed significant volumetric as well as unexpected geometrical differences between the in vivo and in vitro brain groups which in some instances were predictable (e.g. collapsed and smaller ventricles in vitro) but not in other instances. Based on these findings we conclude that although in vitro datasets, compared to in vivo images, offer higher spatial resolutions, superior SNR and CNR, leading to improved image segmentation, in vivo atlases are likely to be an overall better geometric match for in vivo studies, which are necessary for longitudinal examinations of the same animals and for functional brain activation studies. Thus the new in vivo mouse brain atlas dataset presented here is a valuable complement to the current mouse brain atlas collection and will be accessible to the neuroscience community on our public domain mouse brain atlas website