Do rating agencies’ decisions impact stock risks? Evidence from European markets

This article analyses the effect of rating agencies’ decisions on stock risks for European issuers concerning five kinds of events. Our approach is an extension of dummy variable regression event study methodology, using a GARCH(1,1) estimation to capture simultaneously the impact on both systematic and specific stock risks. This new methodology allows us to obtain both global results by categories of rating decisions and individual results, event by event. We document, globally, a positive impact of upgrading on systematic risk, a negative impact of rating confirmation on specific risk, and no significant impact in all other cases. Regarding event-by-event results, the proportion of rating actions exhibiting a significant effect on risk is almost always observed between 20% and 30%. The weak evidence of a global effect on systematic risk may be due to the lack of informational content of the rating decisions on the stocks’ risk, or the existence of rebalancing effects between systematic and idiosyncratic risks. Furthermore, it should be noticed that the decline in volatility in case of a rating affirmed is an insight of the certification role played by the agencies.     

A real-world analysis of healthcare costs and relative risk of hyperprolactinemia associated with antipsychotic treatments in the United States

Abstract

Aims: Antipsychotic medications are associated with an increased risk of hyperprolactinemia, but differ in their propensity to cause this complication. This study aimed to assess the economic burden of hyperprolactinemia, and to compare its risk among adult patients using atypical antipsychotics (AAs) with a mechanism of action associated with no/low vs high/moderate prolactin elevation.

Methods: This retrospective cohort study was based on US Commercial and Medicaid claims databases. Healthcare costs were compared between matched hyperprolactinemia and hyperprolactinemia-free cohorts using a two-part model. Risk of hyperprolactinemia was compared between patients receiving AAs with a mechanism of action associated with no/low (no/low prolactin elevation cohort) vs high/moderate prolactin elevation (high/moderate prolactin cohort) using logistic regression.

Results: In the commercially insured sample, compared to the hyperprolactinemia-free cohort (n?=?499), the hyperprolactinemia cohort (n?=?499) was associated with incremental total healthcare costs of $5,732 ($20,081 vs $14,349; p?=?.004), and incremental medical costs of $3,861 ($13,218 vs $9,357; p?=?.040), mainly driven by hyperprolactinemia-related costs. In the Medicaid-insured sample, compared to the hyperprolactinemia-free cohort, the hyperprolactinemia cohort was associated with incremental total healthcare costs of $10,773 ($30,763 vs $19,990; p?=?.004), and incremental medical costs of $9,246 ($20,859 vs $11,613; p?=?.004), mainly driven by hyperprolactinemia-related and mental health-related costs. The odds of hyperprolactinemia in the no/low prolactin elevation cohort were 4–5-times lower than that in the high/moderate prolactin elevation cohort (odds ratio =0.21; p?<?.001).

Limitations: Hyperprolactinemia may be under-reported in claims data.

Conclusions: Hyperprolactinemia is associated with substantial healthcare costs. AAs associated with no/low prolactin elevation reduce the risk of hyperprolactinemia by 4–5-times compared to AAs associated with moderate/high prolactin elevation. Treatment options with minimal impact on prolactin levels may contribute to reducing hyperprolactinemia burden in AA-treated patients.     

Risk and performance estimation in hedge funds revisited: Evidence from errors in variables

This paper revisits the performance of hedge funds in the presence of errors in variables. To reduce the bias induced by measurement error, we introduce an estimator based on cross sample moments of orders three and four. This Higher Moment Estimation (HME) technique has significant consequences on the measure of factor loadings and the estimation of abnormal performance. Large changes in alphas can be attributed to measurement errors at the level of explanatory variables, while we emphasize some shifts in the economic contents of the equity risk premiums by switching from OLS to HME.     

Restructuring the State-Owned Banking Sector: A Comparative Assessment of Approaches in Central Europe

MOCT-MOST: Economic Policy in Transitional Economies -     

To Do Well by Doing Good: Improving Corporate Image Through Cause-Related Marketing

As part of their corporate social responsibility, many organizations practice cause-related marketing, in which organizations donate to a chosen cause with every consumer purchase. The extant literature has identified the importance of the fit between the organization and the nature of the cause in influencing corporate image, as well as the influence of a connection between the cause and consumer preferences on brand attitudes and brand choice. However, prior research has not addressed which cause composition most appeals to consumers or the impact of cause choice on corporate image. A between-subjects field experiment in the Netherlands examines the influence of three core cause attributes??cause type, cause scope, and cause acuteness??on consumers?? perceptions of corporate image. Furthermore, this experiment examines the extent to which consumer identification with the cause mediates the influence of the cause attributes on corporate image. The findings indicate that identification with the cause leads to more positive evaluations of marketing campaigns for cause type and cause scope. Also, however, our results uncover a negative direct relationship between cause scope and corporate image. Cause acuteness is only marginally influential in corporate image perceptions. By proposing and testing a comprehensive model of the influence of cause attributes on corporate image in cause-related marketing, this article provides important implications and suggests avenues for further research.     

Factors influencing purchase intent in virtual worlds: a review of the literature

Previous empirical studies have identified several factors that seem to play a role in determining purchase intent in virtual worlds; three-dimensional online environments in which users interact while represented by their avatars. So far however, a clear overview of these factors is lacking, and the question that remains is what factors affect purchase intent most. Therefore, this study aims to create an overview of factors that influence users’ purchase intent in virtual worlds, and to subsequently identify the most influential factors. To conduct this review, relevant literature was gathered using a variety of search engines and keywords. An article had to explicitly study factors influencing purchase intent in virtual worlds in order to be included in this review. This search method resulted in a selection of twelve relevant articles that were used for further analysis. Results show that perceived enjoyment, social influence, customization and ease of use are important factors that influence purchase intent in virtual worlds. Enjoyment of the virtual world, beliefs and attitudes of others, avatar customization, and easy-to-use virtual world applications can thus increase users’ willingness to purchase products in the virtual world. Practical implications as well as limitations and suggestions for future research are discussed.     

Phases of Globalization,Wages and Inequality

Open Economies Review - To analyse the globalization-wages-inequality relationship, we extend the North-South Heckscher-Ohlin-Samuelson (HOS) model by assuming (i) that the size of the South...     

Improving VWAP strategies: A dynamic volume approach

In this paper, we present a new methodology for modelling intraday volume, which allows for a reduction of the execution risk in VWAP (Volume Weighted Average Price) orders. The results are obtained for all the stocks included in the CAC40 index at the beginning of September 2004. The idea of considered models is based on the decomposition of traded volume into two parts: one reflects volume changes due to market evolution; the second describes the stock specific volume pattern. The dynamic of the specific volume part is depicted by ARMA and SETAR models. The implementation of VWAP strategies allows some dynamic adjustments during the day in order to improve tracking of the end-of-day VWAP.