Management Entrenchment in the Market for Corporate Control

Ken C.Yook, Ph.D., is associate professor of finance. Department of Finance, The Johns Hopkins University, Washington, DC 20036. George M. McCabe, Ph.D., is professor of finance, Department of Finance, University of Nebraska-Lincoln, Lincoln, NE 68588

An Application Of An Artificial Neural Network Investment System To Predict Takeover Targets

Artificial neural networks are a robust, effective complement to traditional statistical methods in financial applications. They can incorporate qualitative and quantitative information, and recognize underlying patterns and trends in large, complex data sets.  This paper applies a neural network model to identify potential acquisition targets. The model incorporates various factors based on acquisition theories suggested in the literature.  The resulting neural network model exhibits a highly successful prediction rate and a portfolio of predicted target stocks identified by the network substantially outperformed the market

Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein’s neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution

Alliance of Genome Resources Portal: unified model organism research platform

The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource

Alliance of Genome Resources Portal: unified model organism research platform

The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource

Long-run stock performance following stock repurchases

Studies examining long-term performance after stock repurchases provide mixed results. I point out two substantive problems in samplings of early studies. First, we should distinguish whether or not firms actually repurchase shares following announcements of repurchase programs. Second, as some firms frequently announce repurchase programs, we should consider overlapping announcements during the performance estimation period to avoid any confounding effects. Using a sample that corrects for these problems and the calendar portfolio regression method, I find strong evidence that firms that announce repurchase programs infrequently and repurchase shares actually experience significant long-term abnormal returns. These findings provide an explanation of why some previous studies failed to find significant positive long-term performance.Stock repurchase program Long-run stock return Underreaction

Determinants of the Payment Method in Acquisitions

Ken C. Yook is an Associate Professor of Finance in the Department of Finance, Insurance, and Real Estate, College of Business at St. Cloud University. George M. mcCabe is Professor of Finance in the Department of Finance, College of Business Administration at the University of Nebraska-Lincoln