University at Buffalo

About: University at Buffalo is a education organization based out in Buffalo, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 33773 authors who have published 63840 publications receiving 2278954 citations. The organization is also known as: UB & State University of New York at Buffalo.

Overreaction and Insider Trading: Evidence from Growth and Value Portfolios

Abstract: Insider transactions are not random across growth and value stocks. We find that insider buying climbs as stocks change from growth to value categories. Insider buying also is greater after low stock returns, and lower after high stock returns. These findings are consistent with a version of overreaction which says that prices of value stocks tend to lie below fundamental values, and prices of growth stocks tend to lie above fundamental values. Do MARKET PRICES REFLECT investor overreaction?1 The purpose of this paper is to provide evidence on this question. However, new evidence is unlikely to change many minds if the findings depend on the newly controversial capital asset pricing model (CAPM) or multifactor models, or if they involve datasnooping.2 We bypass these problems by not using CAPM or a benchmark model, and by examining a new set of data. We measure insider buying and selling in stocks that are ranked by measures such as the ratio of cash flow per share to price per share (CF/P).3 Current practice refers to stocks with low CF/P as growth stocks, and to stocks with high CF/P as value stocks. We examine the direction of insider trades along the growth/value spectrum to see if they are consistent with attempts to profit from market overreaction. By overreaction, we mean price movements that predictably reverse. This experiment does not require an asset-pricing model because we do not examine the returns accruing to insider trades.4

Jointly modeling deep video and compositional text to bridge vision and language in a unified framework

Abstract: Recently, joint video-language modeling has been attracting more and more attention. However, most existing approaches focus on exploring the language model upon on a fixed visual model. In this paper, we propose a unified framework that jointly models video and the corresponding text sentences. The framework consists of three parts: a compositional semantics language model, a deep video model and a joint embedding model. In our language model, we propose a dependency-tree structure model that embeds sentence into a continuous vector space, which preserves visually grounded meanings and word order. In the visual model, we leverage deep neural networks to capture essential semantic information from videos. In the joint embedding model, we minimize the distance of the outputs of the deep video model and compositional language model in the joint space, and update these two models jointly. Based on these three parts, our system is able to accomplish three tasks: 1) natural language generation, and 2) video retrieval and 3) language retrieval. In the experiments, the results show our approach outperforms SVM, CRF and CCA baselines in predicting Subject-Verb-Object triplet and natural sentence generation, and is better than CCA in video retrieval and language retrieval tasks.

Benefits and Costs of Using HPV Testing to Screen for Cervical Cancer

Abstract: ContextDespite quality assurance standards, Papanicolaou (Pap) test characteristics remain less than optimal.ObjectiveTo compare the societal costs and benefits of human papillomavirus (HPV) testing, Pap testing, and their combination to screen for cervical cancer.Design, Setting, and PopulationA simulation model of neoplasia natural history was used to estimate the societal costs and quality-adjusted life expectancy associated with 18 different general population screening strategies: Pap plus HPV testing, Pap testing alone, and HPV testing alone every 2 or 3 years among hypothetical longitudinal cohorts of US women beginning at age 20 years and continuing to 65 years, 75 years, or death.Main Outcome MeasureDiscounted costs per quality-adjusted life-year (QALY) saved of each screening strategy.ResultsMaximal savings in lives were achieved by screening every 2 years until death with combined HPV and Pap testing at an incremental cost of $76 183 per QALY compared with Pap testing alone every 2 years. Stopping biennial screening with HPV and Pap testing at age 75 years captures 97.8% of the benefits of lifetime screening at a cost of $70 347 per QALY. Combined biennial HPV and Pap testing to age 65 years captures 86.6% of the benefits achievable by continuing to screen until age 75 years. Human papillomavirus screening alone was equally effective as Pap testing alone at any given screening interval or age of screening cessation but was more costly and therefore was dominated. In sensitivity analyses, HPV testing would be more effective and less costly than Pap testing at a cost threshold of $5 for an HPV test.ConclusionsScreening with HPV plus Pap tests every 2 years appears to save additional years of life at reasonable costs compared with Pap testing alone. Applying age limits to screening is a viable option to maintain benefits while reducing costs.

Connectivity and resilience of coral reef metapopulations in marine protected areas: matching empirical efforts to predictive needs.

Abstract: Design and decision-making for marine protected areas (MPAs) on coral reefs require prediction of MPA effects with population models. Modeling of MPAs has shown how the persistence of metapopulations in systems of MPAs depends on the size and spacing of MPAs, and levels of fishing outside the MPAs. However, the pattern of demographic connectivity produced by larval dispersal is a key uncertainty in those modeling studies. The information required to assess population persistence is a dispersal matrix containing the fraction of larvae traveling to each location from each location, not just the current number of larvae exchanged among locations. Recent metapopulation modeling research with hypothetical dispersal matrices has shown how the spatial scale of dispersal, degree of advection versus diffusion, total larval output, and temporal and spatial variability in dispersal influence population persistence. Recent empirical studies using population genetics, parentage analysis, and geochemical and artificial marks in calcified structures have improved the understanding of dispersal. However, many such studies report current self-recruitment (locally produced settlement/settlement from elsewhere), which is not as directly useful as local retention (locally produced settlement/total locally released), which is a component of the dispersal matrix. Modeling of biophysical circulation with larval particle tracking can provide the required elements of dispersal matrices and assess their sensitivity to flows and larval behavior, but it requires more assumptions than direct empirical methods. To make rapid progress in understanding the scales and patterns of connectivity, greater communication between empiricists and population modelers will be needed. Empiricists need to focus more on identifying the characteristics of the dispersal matrix, while population modelers need to track and assimilate evolving empirical results.