Monday returns and asset pricing

The seasonal patterns observed on Monday stock returns are still unexplained by different asset pricing models. We attempt to fill this gap in the finance literature by using the Fama-French (Journal of Financial Economics 33:3–56, 1993) risk factors to explain the Monday seasonal. The results in the study show that Monday returns are explained by risk factors such as the market return, the size of the firms, and the book-to-market ratios of firms.     

Deriving joint space positioning maps from consumer preference ratings

Joint space multidimensional scaling maps are often utilized for positioning analyses and are estimated on survey samples of consumer preferences, choices, considerations, or intentions so as to provide a concise spatial depiction of the competitive landscape including relevant dimensions or attributes, competing brands, and consumers in the same joint space representation. Care has to be given concerning the underlying scale properties of such survey data so as not to distort the resulting joint space positioning map. We present a new joint space multidimensional scaling procedure for positioning analyses for displaying the structure in such survey data when such common ordered successive category measurement scales such as Likert, Edwards, semantic differential, etc., are employed. We present the technical details of this stochastic ordered preference multidimensional scaling vector model as well as the maximum likelihood estimation-based algorithm devised for parameter estimation. Favorable comparisons are made with several existent multidimensional scaling methods in representing the internal structure for such data in marketing positioning studies. An actual commercial positioning application concerning large sports utility vehicles consideration to buy judgments is presented with predictive validation comparisons with other multidimensional scaling joint space procedures.     

A two-stage technology foresight model with system dynamics simulation and its application in the Chinese ICT industry

Technology foresight is a process that identifies the critical technologies a country or industry needs to develop in order to shape a desired future. In this paper, a two-stage technology foresight approach is proposed. During the first stage, critical technologies are identified and evaluated by nationwide experts through Delphi surveys. In the second stage, a system dynamics simulation model is used to estimate how critical parameter values are likely to impact the attainment of foresight goals. A detailed illustration of this two-stage process is provided by a technology foresight case study in the Chinese information and communication technologies (ICT) industry. Because it was identified by the first-stage Delphi method as a critical technology, the diffusion of 4th generation wireless telecommunication technology (4G) was simulated, and experimentation was conducted. Suggestions are provided regarding how the Chinese information industry would need to expand the IP network infrastructure in order to support technology foresight goals under different scenarios.     

The Impact of No-Fault Legislation on Automobile Insurance

Abstract

Since its inception, the effectiveness of no-fault legislation has been highly debated. Although some research suggests that no-fault laws are effective in reducing costs, other evidence suggests that the current no-fault systems may not meet the original objectives. This study provides a detailed assessment of the relation of no-fault laws and automobile insurance losses for the period 1994 to 2007. By examining total automobile insurance losses along with liability and personal injury protection losses, we are able to determine if and how specific provisions of the laws are related to claims costs. We find a negative relation between the presence of a no-fault law and total losses, which suggests that no-fault systems are associated with lower losses than the traditional tort system. In addition, an examination of no-fault-only states suggests that specific provisions of no-fault laws, such as thresholds and limitations on benefits, have some effect on losses. With the sunset of Colorado’s no-fault legislation in 2003, the recent passage of Personal Injury Protection Reform in Florida, and proposed federal choice legislation, the overall impact of no-fault as well as the specific components of the laws are of heightened importance to consumers, insurers, and lawmakers.