Predation by stock price manipulation

We develop a model in which feedback effects from equity markets allow uninformed traders to profit by short selling a firm's stock while going long on its product market competitor. As this strategy distorts the investment of the firm targeted by short selling to the benefit of its rival, we label it predation by stock price manipulation. A short selling ban does not prevent manipulation since the speculator can still induce a firm to underinvest by establishing a long position in its rival. Our analysis unveils how competitive interactions among firms expand the scope of manipulation, providing new insights into equity markets and short sales regulation.</p

Short selling and product market competition

We empirically investigate how short selling affects firms’ product market performance via a managerial monitoring channel. Using both historical data and exogenous shocks to short selling, we find robust evidence that short interest negatively impacts market shares, especially in large firms. Our Reg SHO results are stronger in concentrated industries and industries where firms compete in strategic substitutes. Further tests show that these effects are driven by low ex-ante stock price informativeness. The evidence suggests that the interaction between market power and price opacity generates incentives for overproduction, which short selling attenuates. Our results support policies that facilitate price discovery in the presence of market power.</p

Genome-scale modeling of the protein secretory machinery in yeast

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking. Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm was developed which mimics secretory machinery and assigns each secretory protein to a particular secretory class that determines the set of PTMs and transport steps specific to each protein. Protein abundances were integrated with the model in order to gain system level estimation of the metabolic demands associated with the processing of each specific protein as well as a quantitative estimation of the activity of each component of the secretory machinery

Carcass persistence and detectability : reducing the uncertainty surrounding wildlife-vehicle collision surveys

Carcass persistence time and detectability are two main sources of uncertainty on roadkill surveys. In this study, we evaluate the influence of these uncertainties on roadkill surveys and estimates. To estimate carcass persistence time, three observers (including the driver) surveyed 114km by car on a monthly basis for two years, searching for wildlife-vehicle collisions (WVC). Each survey consisted of five consecutive days. To estimate carcass detectability, we randomly selected stretches of 500m to be also surveyed on foot by two other observers (total 292 walked stretches, 146 km walked). We expected that body size of the carcass, road type, presence of scavengers and weather conditions to be the main drivers influencing the carcass persistence times, but their relative importance was unknown. We also expected detectability to be highly dependent on body size. Overall, we recorded low median persistence times (one day) and low detectability (<10%) for all vertebrates. The results indicate that body size and landscape cover (as a surrogate of scavengers' presence) are the major drivers of carcass persistence. Detectability was lower for animals with body mass less than 100g when compared to carcass with higher body mass. We estimated that our recorded mortality rates underestimated actual values of mortality by 2±10 fold. Although persistence times were similar to previous studies, the detectability rates here described are very different from previous studies. The results suggest that detectability is the main source of bias across WVC studies. Therefore, more than persistence times, studies should carefully account for differing detectability when comparing WVC studies