The exposure of shipping firms’ stock returns to financial risks and oil prices: a global perspective

Shipping is an industry that is highly geared towards international trade and therefore, would seem to be highly susceptible to fluctuations in macroeconomic factors. This article investigates the impact of exchange rates, interest rates and oil prices on stock returns of 143 shipping companies from 16 countries. We also investigate the factors which determine the extent to which firm are sensitive to macroeconomic variables. Our results indicate that the low incidence of significant exposure to exchange rate and interest rates suggests that most shipping firms have utilised reasonably successful hedging strategies to reduce the impact of these macroeconomic risks. Finally, we find that, for the minority of shipping firms significantly affected by oil price increases, the effects have usually been beneficial

Stakeholder engagement: Investors' environmental risk aversion and corporate earnings

How does investors' aversion to environmental risk affect their reaction towards firms' earnings announcements? We explore this by analyzing earnings announcements made by U.S. firms between 2002 and 2016. The results show that environmental performance at the firm level is important for investors as this influences the investment behaviors of investors who have some degree of aversion to environmental risk. These investors appreciate the earnings by firms that exhibit a high level of environmental performance, i.e., firms that have successfully addressed environmental risks. However, earnings are of secondary importance for investors who are highly averse to environmental risk since environmental concerns take precedence

DETERMINATION OF PROBABILITY DISTRIBUTIONS FOR MODELLING AIR POLLUTANTS FROM VEHICULAR EMISSIONS IN LAGOS STATE

Statistical analysis of emission data in the literature has been mostly limited to description of air pollutants variability. The use of probability distribution for modelling emission data needed for environmental quality management has received little attention. Appropriate probability distribution to model air pollutants is necessary for better understanding of emission variability. This study was aimed at determining probability distributions for modeling air pollutants from vehicular emissions in Lagos State. Secondary Data from Lagos State Traffic Management Agency were collected for Imota, Maryland, and Ikotun and Oshodi, representing low, medium and high vehicular traffic areas respectively. The data collected was between May 2007 and April 2008 on the selected sample locations. The data covers air pollutants from vehicular emission of Total Suspended Particulate (TSP), Particulate Matter 10 (PM10), Particulate Matter 2.5 (PM2.5), Carbon (II) Oxide (CO), Sulphur (IV) Oxide (SO2), and Nitrogen (IV) Oxide (NO2). Commonly used positively skewed probability distributions (PDs) were investigated using standard distribution software to select the PDs that best describe the data on each pollutant. Mean and standard deviation were used to characterise the distributions. Kolmogorov-Smirnov test statistic was used for testing the goodness-of-fit of the distributions. National Environmental Standards and Regulations Enforcement Agency (NESREA) air quality standard rates were inserted into the probability density function of the selected distributions. Each of the examined air pollutants from vehicular emissions had different probability distributions for describing variability of vehicular emission in Lagos State. Johnson S.B. (3P) (p<0.0003) was found suitable for modeling TSP, Beta (p<0.003) for PM10, Pearson 6 (4P) (p<0.0005) for PM2.5, Log-logistics (3P) (p<0.0035) for SO2, Pearson 5 (3P) (p<0.0024) for NO2 and CO had no specific distribution that fit. The mean concentration of TSP, PM10, PM2.5, CO, SO2 and NO2 were 585.0'363.6 'g/m3, 285.2'193.2 'g/m3, 150.4 '108.4 'g/m3, 2.9'0.8 ppm, 27.6'9.7 ppbv and 31.1'30.0 ppbv respectively. The skewness values were 1.5, 1.3, 2.3, 0.8, 0.2, and 1.4 while the kurtosis values were 3.2, 2.9, 7.6, 0.004, 1.0 and 1.1. The test statistics for the skewness and kurtosis are 0.2?G?1.5 and 0.7?Z?8.3. The mean of TSP and PM10 were above the standard while the mean of CO, SO2 and NO2 were below. But, the mean of PM2.5 is equal to that of the standard value. The hazard rates of the air pollutants from vehicular emission were 0.9, 0.7, 0.4, 0.1 and 0.1 respectively, while the survival rates are 0.1, 0.3, 0.6, 0.9 and 0.9 respectively. The appropriate distributions for modelling selected air pollutants from vehicular emission in Lagos State were determined. Measures of the hazard and survival rates in relation to vehicular emission have been provided. Implementation and enforcement of environmental laws on air pollutants of vehicular emission must be taken with all seriousness and enforced towards the safety of life of all and sundry

Does Gender Diverse Board Mean Less Earnings Management?

We examine the effect board gender diversity has on earnings management in European countries. The findings reveal that a gender diverse board mitigates earnings management in countries where gender equality is high. This provides an explanation to the inconclusive findings in the literature. Finance Research Letters Journal Impact Factor on ResearchGate - Impact Factor Rankings (2013, 2014 and 2015). Available from: http://www.researchgate.net/journal/1544-6123_Finance_Research_Letters [accessed Aug 24, 2015]

Investors’ reaction under uncertainty

This study investigates investors’ reaction to good/bad earnings news when faced with market- and industry-wide uncertainties. Our results provide little support for the discount rate explanation that investors’ reaction to good news is dampened during high market volatility. However, the results strongly support the learning hypothesis that earnings news provides value-relevant information for investors during periods of high-market volatility, but that investors cannot learn as much from earnings news under industry-wide uncertainty. These findings also support the conservation hypothesis that investors react more strongly to bad earnings news when faced with market-wide uncertainty

Is the market surprised by the surprise?

This study examines how the market reacts to earnings surprises with different characteristics such as future earnings prospects and historical surprises embedded in the earnings announced. We also explore the effect of corporate governance on market reaction to earnings information disseminated through earnings announcements. The sample comprises of 1,620 US firms for the period 2002 – 2016. Using a regression-based approach, the results reveal that the market reacts to earnings surprises, particularly, to their sign, magnitude, persistence, and the future earnings prospects. Moreover, these different characteristics of earnings surprises are more important for negative surprises than for positive surprises. Furthermore, we find evidence for the information transparency theory that earnings announcements are a relatively more important source of information for low corporate governance firms than for high corporate governance firms. Finally, historical earnings information is more relevant for low corporate governance firms, whereas prospective earnings information is more important for high corporate governance firms. This study contributes to the extant literature by revealing that the market does not only react to the magnitude/sign of the surprises but also to other additional characteristics of earnings surprises. The study also reveals that firm governance influences how the market reacts to earnings information announced. Consequently, managers should be mindful that strengthening firm corporate governance could improve investors’ confidence in earnings announced

A variable impact neural network analysis of dividend policies and share prices of transportation and related companies

The purpose of this research is to investigate dividend policy,including its impact on share prices of transportation providers and related service companies, by comparing generalized regression neural networks with conventional regressions. Our results using regressions reveal that for Europe and for the US and Canada the market-to-book-value, as a surrogate for growth opportunities,fulfils expectations of pressures on dividends leading to a negative association with dividend yields in accordance with the pecking order theory. Neural network analysis indicates a clear role for growth opportunities for the US and Canada pointing to an underlying confidence on the part of transportation companies in their own internal policies. Finally, risk is rewarded especially in Europe

Expanding the beauty spectrum: a case study of Lupita Nyong’o as the brand ambassador for Lancôme cosmetics

In 2014, Lupita Nyong’o became the first black spokeswoman for Lancôme Paris cosmetics, the first in the company’s 80-year history. Previously, the advertising industry took issue with using models outside of the European standard of beauty for various reasons including perceptions of consumer relatability and response, but Nyong’o’s contract is a direct challenge to this notion. The intent of this study to explore news coverage of the first year (April 2014 – April 2015) of Nyong’o’s contract with Lancôme to determine why Nyong’o was chosen as the first black ambassador, how the decision was received, and what the implications are for the beauty standards, especially the black beauty standard. (Published By University of Alabama Libraries