LIQUIDITY AND ASSET PRICING UNDER THE THREE‐MOMENT CAPM PARADIGM

We examine whether the use of the three‐moment capital asset pricing model can account for liquidity risk. We also make a comparative analysis of a four‐factor model based on Fama–French and Pástor–Stambaugh factors versus a model based solely on stock characteristics. Our findings suggest that neither of the models captures the liquidity premium nor do stock characteristics serve as proxies for liquidity. We also find that sensitivities of stock return to fluctuations in market liquidity do not subsume the effect of characteristic liquidity. Furthermore, our empirical findings are robust to differences in market microstructure or trading protocols between NYSE/AMEX and NASDAQ.     

On efficiency of the ratio estimator

Summary The exact mean square error for the ratio estimator of a finite population total based on simple random sampling without replacement is shown to have an expected value less than that of the variance of the ratio estimator based on Midzuno’s scheme, under a usual super-population model.     

Bank mergers and components of risk: An evaluation

The present study empirically examines the contribution of the acquired banks in only the nonconglomerate types of mergers (i.e., banks with banks), where the bulk of the payment is in the form of equity to the acquiring bank and finds overwhelmingly statistically significant evidence that nonconglomerate types of mergers definitely reduce the total as well as the unsystematic risk while having no statistically significant effect on systematic risk. Therefore, it seems that diversification may be a possible motive for bank mergers.     

Prediction of the Indian summer monsoon using a stacked autoencoder and ensemble regression model

The study of climatic variables that govern the Indian summer monsoon has been widely explored. In this work, we use a non-linear deep learning-based feature reduction scheme for the discovery of skilful predictors for monsoon rainfall with climatic variables from various regions of the globe. We use a stacked autoencoder network along with two advanced machine learning techniques to forecast the Indian summer monsoon. We show that the predictors such as the sea surface temperature and zonal wind can predict the Indian summer monsoon one month ahead, whereas the sea level pressure can predict ten months before the season. Further, we also show that the predictors derived from a combination of climatic variables can outperform the predictors derived from an individual variable. The stacked autoencoder model with combined predictors of sea surface temperature and sea level pressure can predict the monsoon (June-September) two months ahead with a 2.8% error. The accuracy of the identified predictors is found to be superior to the state-of-the-art predictions of the Indian monsoon.     

Global marketing of industrial products: Are interpersonal relationships always critical?

The present paper examines the issue of whether interpersonal relationships are critical for global marketing of industrial products. The fields of relationship marketing, IMP group research, sales research, and network theory have stressed the importance of interpersonal relationships in the business-to-business or industrial marketing context. In contrast to this emphasis on interpersonal relationships, we argue that industrial firms can both conceive and enhance marketing strategies based on developing high quality and consistent processes, products, services or outcomes (consistent processes and outcomes). Such strategies are especially important given the fact that developing interpersonal relationships is expensive due to their reliance on frequent and/or face-to-face communications. In this paper, we examine industry and country contexts that lead to the choice of alternative industrial product marketing strategies and highlight some future research directions and managerial implications.     

Perceptions of poverty attributions in Europe: a multilevel mixture model approach

The perception of the causes of poverty has long been recognized as a very important factor in the broader study of this social phenomenon. This study covers 15 European Union countries and considers three types of poverty attributions: individualistic, societal, and fatalistic. The individualistic view perception believes the poor are responsible for their situation, the societal perspective blames society for poverty and the fatalistic view considers poverty to be the result of bad luck or fate. A multilevel mixture model with three clusters of countries and six clusters of individuals was identified. Despite the generalization of the social explanations of poverty at the individual or micro level, there are also groups that emphasize more individualistic explanations, blaming the poor for their condition. At the country or macro level, the most developed cluster believes in the individualistic and fatalistic causes of poverty, whereas the least developed clusters explain poverty based on the injustices of society. There is diversity in the way these countries perceive poverty.     

Financialization of Housing in Brazil: New Frontiers

The financialization of housing has been increasingly identified as an important driver of social and economic change in contemporary capitalism. Focusing on the Brazilian context, this article considers the extent to which recent changes in housing regulations, policies and markets confirm or challenge narratives about the financialization of housing in the international academic debate. I argue that while many of the trends stressed in the literature are apparent, more extreme processes of financialization within the Brazilian housing sector remain limited––not only because of institutional and regulatory constraints, path dependence or political resistance, but also because of fundamental structural conditions of Brazil's position as a peripheral economy. Three different but mutually reinforcing processes are scrutinized in order to evaluate the financialization of housing and its limits in Brazil: the re‐regulation of the real estate financial sector initiated in the 1990s; the changing funding patterns among real estate companies since the mid‐2000s; and the increasing commodification of housing induced by a large‐scale and heavily subsidized housing program launched in 2009.