Managerial bonding and stock liquidity: An analysis of dual-class firms

Given the decision to create a second class of stock through a dual-class structure, we propose that management is more (less) likely to create a liquid secondary market for both classes of shares the lower (higher) its willingness to tie its personal wealth to firm performance. If market makers recognize this relation, they should assign a higher likelihood to trades motivated by superior information in shares of firms that list both classes of stock and a lower likelihood for firms that list only one class of stock pursuant to recapitalization. Additionally, they should assign a lower likelihood to trades motivated by superior information in shares of IPOs that choose a dual-class structure and list only one class relative to IPOs that remain single-class. Our empirical tests based on IPOS and recaps between 1985 and 1988 provide support for these propositions.     

Quality dualism

We suggest a theory of quality dualism, defined in terms of the gap between the highest quality good produced in the informal sector and the lowest quality produced in the formal sector. We develop a model of vertically differentiated products, in which firms producing in the formal and informal sectors face different factor prices, and have a relative advantage in the manufacture of different qualities. We then use the model to examine the cyclical behavior of the respective sizes of the two sectors. Finally, we point out that factor price changes, which reduce or increase the size of the informal sector, may have the same or opposite effect on the degree of dualism in the economy.     

Dynamic Currency Linkages and Their Determinants: An Empirical Study for East Asian Economic Community Region

In this article, Copula GARCH models have been employed to study the inter-temporal process of currency market co-movements between ASEAN+6 countries (referred to in this study as East Asian Economic Community) and ASEAN+6 currency market index. Empirical results show that the sample countries of the region exhibit varying levels of currency co-movements with the Asian benchmark. Markov regime switching results show that many of the countries which had high dependences with the regional currency index as was found in copula estimations had also overlapping currency market cycles. Using Principal Component Analysis, we find that three statistical factors explain exchange rate co-movements which came out to be trade linkages, economic risk, and currency market openness in our dynamic panel data estimation.     

Critical success factors determining performance of cross‐border acquisition: Evidence from the African telecom market

This study investigates the factors affecting Bharti Airtel's cross‐border postacquisition performance in an African market. This study describes the relationships among various factors such as technical capability, affiliated firm's absorptive capacity, and organizational learning capabilities, which determine the successful operations of the Zain acquisition deal in South Africa. This paper adopts a qualitative approach to identify factors that influence the postacquisition performance. Seven factors are identified based on the literature. Consequently, it has become a necessity to encapsulate these factors in suitable proportions. In this study, we have developed a total interpretive structural modeling (TISM) to analyze the postacquisition performance of Bharti Airtel in South Africa. Our research has highlighted six dynamic factors (organizational learning capability, knowledge management, technology capability, technology relatedness, acquirer's absorptive capacity, and national culture difference) that affect the firm's postacquisition performance. The interpretive structural model (ISM) and total interpretive structural model for postacquisition performance are built‐up. The developed TISM will support academics and practitioners to develop their understanding of acquisition performance of parent companies in the context of telecom business in the South African market.     

The impact of crude oil inventory announcements on prices: Evidence from derivatives markets

This study examines the impact of weekly crude oil storage announcements on oil futures and options prices. We document evidence of a strong announcement day effect on both markets, and find prices to move in anticipation of the inventory surprise. Futures returns significantly decrease with positive surprises and increase with negative surprises. There is no evidence of an asymmetric impact on futures prices. Near‐the‐money options exhibit the greatest price sensitivity, and the magnitude of the price response of both futures and options declines with maturity. The results remain robust even after controlling for various macroeconomic and other storage‐related news variables.     

Losers and prospectors in the short-term options market

Intraday data for weekly options are investigated for behavioral biases implied in prospect theory (PT) and cumulative prospect theory (CPT). The results generally support both theories, with losers (winners) observed to be relatively risk-seeking (averse). On aggregate, losers (winners) overprice (underprice) their contracts and overweight (underweight) the probability of winning. Additionally, the volatility smirk observed in equity options is dampened by PT/CPT biases. The price distortions are time sensitive, especially for losing traders. Losers hold out by transacting later in the day and closer to expiration than their baseline counterparts. This betting-time effect is absent among winners.     

Effects of Mood and Elaboration on Processing and Evaluation of Goal‐Framed Appeals

Two experiments examined the influence of mood and elaboration on consumer processing and evaluation of goal‐framed appeals. Subjects displayed more favorable attitudes and purchase intent (PI) when exposed to negative goal frames than equivalent positive ones. These effects were attenuated under high‐elaboration conditions. Compared to subjects in positive moods, those in negative moods exhibited more favorable thoughts, attitudes, and PI toward negative goal frames. Finally, mood and frame valence did not affect depth of processing but had a consistent impact on style of processing, that is, positive frames and moods induced relational processing whereas negative frames and moods engendered item‐specific processing.     

Assessing time-varying stock market integration in Economic and Monetary Union for normal and crisis periods

In this paper, we examine the stock market integration process amongst 17 Economic and Monetary Union (EMU) countries from January 2002 to June 2013 over a normal period as well as for the Global Financial Crisis (GFC) and Eurozone Debt Crisis (EDC) periods. We classify the economies in three groups (A, B and C) based on their GDP to examine whether the economic size influences financial integration. Seven indicators are used for the purpose, namely, beta convergence, sigma convergence, variance ratio, asymmetric DCC, dynamic cointegration, market synchronisation measure and common components approach. The results suggest that large-sized EMU economies (termed as Group A) exhibit strong stock market integration. Moderate integration is observed for middle-sized EMU economies with old membership (termed as Group B). Small-sized economies (termed as Group C) economies seemed to be least integrated within the EMU stock market system. The findings further suggest presence of contagion effects as one moves from normal to crisis periods, which are specifically stronger for more integrated economies of Group A. We recommend institutional, regulatory and other policy reforms for Group B and especially Group C to achieve higher level of integration.     

An intelligent and secure system for predicting and preventing Zika virus outbreak using Fog computing

Zika virus is a mosquito-borne disease that spreads very quickly in different parts of the world. In this article, we proposed a system to prevent and control the spread of Zika virus disease using integration of Fog computing, cloud computing, mobile phones and the Internet of things (IoT)-based sensor devices. Fog computing is used as an intermediary layer between the cloud and end users to reduce the latency time and extra communication cost that is usually found high in cloud-based systems. A fuzzy k-nearest neighbour is used to diagnose the possibly infected users, and Google map web service is used to provide the geographic positioning system (GPS)-based risk assessment to prevent the outbreak. It is used to represent each Zika virus (ZikaV)-infected user, mosquito-dense sites and breeding sites on the Google map that help the government healthcare authorities to control such risk-prone areas effectively and efficiently. The proposed system is deployed on Amazon EC2 cloud to evaluate its performance and accuracy using data set for 2 million users. Our system provides high accuracy of 94.5% for initial diagnosis of different users according to their symptoms and appropriate GPS-based risk assessment.