What drives the performance of convertible-bond funds?

This paper examines the performance of US mutual funds that invest primarily in convertible bonds. Multivariate cross-sectional analyses show a significant relation between a fund’s performance and its asset composition: the higher the difference in the percentage of assets invested in convertible bonds compared to the percentage invested in stocks, the higher the performance, on average. We show that this result can be explained by factors associated with investment opportunities in the convertible-bond market and trading strategies related to convertible arbitrage, as typically performed by hedge funds. Overall, convertible-bond fund performance measured by alpha is comparable to a passive investment in stocks, bonds, and convertible bonds. This performance is the result of weak selection skills and successful timing strategies related to convertible arbitrage.     

Estimating the basis risk of index-linked hedging strategies using multivariate extreme value theory

This paper studies the empirical quantification of basis risk in the context of index-linked hedging strategies. Basis risk refers to the risk of non-payment of the index-linked instrument, given that the hedger’s loss exceeds some critical level. The quantification of such risk measures from empirical data can be done in various ways and requires special consideration of the dependence structure between the index and the company’s losses as well as the estimation of the tails of a distribution. In this context, previous literature shows that extreme value theory can be superior to traditional methods with respect to estimating quantile risk measures such as the value at risk. Thus, the aim of this paper is to conduct an empirical analysis of basis risk using multivariate extreme value theory and extreme value copulas to estimate the underlying risk processes and their dependence structure in order to obtain a more adequate picture of basis risk associated with index-linked hedging strategies. Our results emphasize that the application of extreme value theory leads to better fits of the tails of the marginal distributions in the considered stock price sample and that traditional methods in regard to estimating marginal distributions tend to overestimate basis risk, while basis risk can in contrast be higher when taking into account extreme value copulas.     

An empirical analysis of mean reversion of the S&P 500’s P/E ratios

Numerous authors have suggested that the price-earnings (P/E) ratio can be used to predict the future movement of stock prices. Such arguments are based on the belief that P/E ratios are mean-reverting. However, are the S&P P/E ratios really mean reverting? A review of the literature finds arguments on both sides, but the issue of mean reversion has not been tested adequately. Using unit roots and multiple structural breaks, we explicitly show that the P/E ratio is stationary around multiple breaks, which means that it will eventually revert to some long-run means. This result supports evidence that high P/E ratios relative to the current long-run mean will be followed by slow growth in stock prices and/or high earnings growth.     

Measuring program success

Growth in the use of programs has led to a requirement of understanding what constitutes program success. A measurement construct for program success, which comprises four dimensions—delivery capability, organizational capability, marketing capability, and innovative capability—was developed based on 172 responses to a web‐based questionnaire to program managers. Analysis of variance (ANOVA) and canonical correlation analysis were applied to test for the relationship between program success and program context. Results showed that the measurement construct for program success was stable over different types of program contexts. It provides a tool for further investigation into program success assessment.     

Mobile number portability in Europe

This paper examines the causes and effects of mobile number portability (MNP) and provides a survey of its implementation in Europe. It first examines the competitive effects and costs of introducing MNP. Next, it discusses how to charge for MNP. It argues that a price cap regime starting from the average cost of porting is likely to provide appropriate incentives. Finally, it reviews recent experience with implementing MNP in Europe. Differences in the speed of porting and porting charges appear to explain part of the differences in the use of MNP across countries.     

Sustainability reporting: The role of “Search”, “Experience” and “Credence” information

Corporate sustainability reporting quality has been frequently criticised as being unbalanced, presenting an overly positive view or failing to address material issues. The purpose of this article is to provide a fresh explanation for poor quality sustainability reporting and to propose how quality issues may be addressed. The theoretical framework combines the legitimacy and accountability perspectives using Akerlof's (1970) Market for Lemons theory. Akerlof's approach is extended by differentiating between three types of information in sustainability reports namely search, experience and credence. The article concludes that the type of information must be considered when determining measures to improve report quality.     

Residual autocorrelation testing for vector error correction models

In applied time series analysis, checking for autocorrelation in a fitted model is a routine diagnostic tool. Therefore it is useful to know the asymptotic and small sample properties of the standard tests for the case when some of the variables are cointegrated. The properties of residual autocorrelations of vector error correction models (VECMs) and tests for residual autocorrelation are derived. In particular, the asymptotic distributions of Lagrange multiplier (LM) and portmanteau tests are given. Monte Carlo simulations show that the LM tests have satisfactory size properties only if autocorrelation of small order is tested in systems of small dimension. In contrast, portmanteau tests have roughly correct size in small samples only if higher order residual autocorrelation is tested. Their critical values have to be adjusted for the cointegration rank of the system, however.     

Stimulating the Demand for Insurance

This article acts as a review and also a guide to policymakers who are interested in understanding the determinants of insurance demand and how it affects general economic development. By providing a synopsis and evaluation of existing empirical research on the development of insurance markets, this article provides a discussion of the factors that promote insurance market development. This article then highlights certain issues that both insurance companies and policymakers can utilize further in their own markets to design future policies that can be geared to promote insurance market development.