Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test

Recent studies have analysed the ability of measures of uncertainty to predict movements in macroeconomic and financial variables. The objective of this paper is to employ the recently proposed nonparametric causality-in-quantiles test to analyse the predictability of returns and volatility of sixteen U.S. dollar-based exchange rates (for both developed and developing countries) over the monthly period of 1999:01–2012:03, based on information provided by a news-based measure of relative uncertainty, i.e., the differential between domestic and U.S. uncertainties. The causality-in-quantile approach allows us to test for not only causality-in-mean (1st moment), but also causality that may exist in the tails of the joint distribution of the variables. In addition, we are also able to investigate causality-in-variance (volatility spillovers) when causality in the conditional-mean may not exist, yet higher order interdependencies might emerge. We motivate our analysis by employing tests for nonlinearity. These tests detect nonlinearity, as well as the existence of structural breaks in the exchange rate returns, and in its relationship with the EPU differential, implying that the Granger causality tests based on a linear framework is likely to suffer from misspecification. The results of our nonparametric causality-in-quantiles test indicate that for seven exchange rates EPU differentials have a causal impact on the variance of exchange rate returns but not on the returns themselves at all parts of the conditional distribution. We also find that EPU differentials have predictive ability for both exchange rate returns as well as the return variance over the entire conditional distribution for four exchange rates.     

A note on assessing the relation between CEO characteristics and stock performance: Alpha Above Replacement

Many studies examine the relation between stock performance and CEO characteristics. We approach the topic in a different way, using the alphas generated by the Fama‐French three‐factor model as the dependent variable in a CEO characteristic model. We find several traits are significantly related to alpha. CEOs who are younger, own a larger fraction of firm equity and hold a graduate degree provide greater alphas. CEOs who are also the founder of the firm deliver larger alphas. Our results provide useful information for boards assessing the performance of CEOs and considering CEO succession.     

Knowledge flows within multinational corporations

Pursuing a nodal (i.e., subsidiary) level of analysis, this paper advances and tests an overarching theoretical framework pertaining to intracorporate knowledge transfers within multinational corporations (MNCs). We predicted that (i) knowledge outflows from a subsidiary would be positively associated with value of the subsidiary’s knowledge stock, its motivational disposition to share knowledge, and the richness of transmission channels; and (ii) knowledge inflows into a subsidiary would be positively associated with richness of transmission channels, motivational disposition to acquire knowledge, and the capacity to absorb the incoming knowledge. These predictions were tested empirically with data from 374 subsidiaries within 75 MNCs headquartered in the U.S., Europe, and Japan. Except for our predictions regarding the impact of source unit's motivational disposition on knowledge outflows, the data provide either full or partial support to all of the other elements of our theoretical framework. Copyright © 2000 John Wiley & Sons, Ltd.     

The impact of external forces on cartel network dynamics: Direct research in the diamond industry

This paper describes the impact of external environmental forces on cartel networks. Using a case research approach, this report examines two leading business networks within one industry, over time. The results suggest that (a) bargaining power of intermediaries increases with the advent of new and powerful actors, (b) process activities that cartels previously controlled are being outsourced to new actors sometimes based in developing countries, (c) other actors are acquiring resources once dominated by a cartel, (d) external forces triggered by the illegal diamond trade, such as international regulatory constraints, no longer favour cartels like De Beers, and (e) over time, these and additional environment factors are forcing actors like De Beers who perform rigid process activities to become more flexible. For example, forces are moving cartels which relied previously on hand-picked intermediaries in highly controlled networks to market their products to adopt a flexible market-focused expansion of operations in retail contexts.     

Information Transmission between Mature and Emerging Equity Markets During Normal and Crisis Periods: An Empirical Examination

In this paper, we examine the price discovery and volatility spillovers between eight mature market economies (MMEs) and eight emerging market economies (EMEs) from January 2003 to July 2014, covering three sub-periods—prior to the 2007–09 global financial crisis (GFC), during the crisis, and post-crisis. The results of price discovery indicate that MMEs lead EMEs in the pre-crisis and post-crisis periods. All MMEs are cointegrated with China in the pre-crisis period but not in the post-crisis period. Dynamic cointegration results reconfirm our findings from Johansen’s co-integration test. The asymmetric dynamic conditional correlation (ADCC-GARCH) coefficients suggest a regional pattern among MMEs and EMEs, except in the case of European MMEs with South Africa. Employing BEKK-GARCH model, we find that volatility spillovers of MMEs with China and of Italy with EMEs weakened in the post-crisis period as compared to the pre-crisis period implying that the GFC damaged the information transmission process, particularly for China and Italy. While China is a large economy with strong trade linkages with the rest of the world, Italy is one of the larger European economies which was in relatively greater distress during the EDC. The findings have implications for policy makers and investors.

     

Predicting the antecedents of consumers' intention toward purchase of mutual funds: A hybrid PLS-SEM-neural network approach

The current study intends to identify the behavioural antecedents of investors' attitude and investment intention toward mutual funds using a robust SEM-ANN approach. It focuses on novel factors in the purview of the COVID-19 pandemic, increasing digitalization and social media usage. The research outcome indicates that attitude (ATB), awareness (AW) and investment decision involvement (IDI) have a significant positive relation with investment intention (BI). In contrast, perceived barrier (PBR) negatively relates to investment intention. Herd behaviour (HB) and social media influence (SMI) do not influence investment intention toward mutual funds. Moreover, all the tested predictors share direct relation with the attitude toward mutual fund investment, barring perceived risk (PR), which has an inverse relationship. As per the outcome of ANN sensitivity analysis, attitude is the most crucial determinant of investment intention. It is followed by awareness (AW), perceived barriers (PBR) and investment decision involvement (IDI). Among the significant determinants of attitude, self-efficacy (SE) is the most important determinant, followed by perceived usefulness (PU), perceived emergency (PEMER), subjective norms (SN) and perceived risk (PR).