Fundamental innovation usually involves huge upfront costs, but the benefits are spread across various sectors of the economy. Given the large costs and limited appropriability of the benefits associated with fundamental innovations, individual firms underinvest in these innovations relative to...

This study predicts stock splits using two ensemble machine learning techniques: gradient boosting machines (GBMs) and random forests (RFs). The goal is to form implementable portfolios based on positive predictions to generate abnormal returns. Since splits are rare events, we use SMOTE...

The finite sample performance of a number of linear regression estimators is investigated in a variety of parametric settings involving outliers. A Bayesian approach is shown to have good overall comparative performance. It is then shown how the same Bayesian methodology can be easily extended...

Purpose: Collusion is a common behavior of oligarch enterprises aiming to get an advantage in market competition. The purpose of the research is to explore positive or negative effects from the electricity generation manufacturers' collusion through statistical analysis approach. To be exact,...

This study was conducted to advance methodology of utilizing leading indicators in prediction of occupational health and safety losses. The qualitative association between leading and lagging indicators is not well documented in the literature. A method was proposed to link leading indicators to...

Purpose: Collusion is a common behavior of oligarch enterprises aiming to get an advantage in market competition. The purpose of the research is to explore positive or negative effects from the electricity generation manufacturers' collusion through statistical analysis approach. To be exact,...

To assess the required capital for insurance companies, which usually have several business lines, estimates of the joint tail probabilities of aggregate losses are needed. Under the collective risk model, these aggregate losses are sums of random number of random variables, whose distributions...

This paper studies in detail simulation methods for simulating tail probability and tail mean of both univariate and bivariate compound variables. We first reviewed some basic variance reduction methods, then we proposed several novel combinations of variance reduction methods specifically for...