Exchange rate returns and volatility: the role of time-varying rare disaster risks

This paper provides empirical evidence to the theoretical claim that rare disaster risks have predictability for exchange rate returns and volatility using a nonparametric quantile-based methodology. Using dollar-based exchange rates for Brazil, Russia, India, China, and South Africa, the quantile-causality test shows that indeed rare disaster-risks affects both returns and volatility over the majority of their respective conditional distributions. In addition, these effects are much stronger when compared to those using the British pound, especially in terms of currency returns.     

“Opt out” or kept out? The effect of stigma,structure, selection,and sector on the labor force participation of married women in India

Using the 61st and 68th rounds of National Sample Survey data, we investigate the role of stigma, the economy’s structure, potential selection bias, and sectoral differences in explaining the low labor force participation (LFP) of middle and secondary educated women in India relative to low‐ and high‐educated women (the “U‐shape”). Estimating LFP regressions on a sample of prime‐aged married women, we show that, controlling for background characteristics, if a woman’s husband works in a white‐collar job in a region with a high share of blue‐collar jobs, she is less likely to participate in the labor market (stigma). We also find a positive effect of an increase in an index of white‐collar job growth (structure) on married women’s LFP. These effects are present in both rural and urban sectors but are strongest in the rural sector. However, middle and secondary educated women are still found to have substantially lower LFP than low‐ and graduate‐educated women in both sectors. Indeed, over time, the U‐shape persists in the rural sector and deepens in the urban sector. Because unobservables are quite large in the urban sector, we use the method of instrumental variables and find an increasing return at middle levels but stagnation at higher levels.     

Do Countries Matter More in Determining the Relationship Between Employee Welfare and Financial Performance?

Extant literature suggests that employee‐friendly practices influence corporate decision‐making. Using a bargaining framework, we examine the role of country‐level determinants in influencing employee‐friendly practices and their impact on value creation. Utilizing a comprehensive sample of 25,483 firm‐year observations from 56 countries, we find that firms domiciled in countries with weak employment protection and regulations can potentially benefit by voluntarily undertaking employee‐friendly practices. Also, in countries with flexible labor market conditions, firm value is enhanced by undertaking employee‐friendly practices. Furthermore, the importance of employee‐friendly practices in value creation is observed strongly in countries that provide better infrastructure, productivity, and incentives.     

Trade uncertainties and the hedging abilities of Bitcoin

In this paper, we first estimate the monthly realised correlation, based on daily data, between stock returns of the United States (US) and Bitcoin returns. Then, we relate the realised correlation over the period October 2011 to May 2019 with a news-based measure of the growth of trade uncertainty of the US. Our results show that the realised correlation is negatively impacted by increases in trade uncertainty, which continues to hold under alternative robustness checks, suggesting that Bitcoin can act as a hedge relative to the conventional stock market in the wake of heightened trade policy-related uncertainties, and provide diversification benefits for investors.     

Some general results for moments in bivariate distributions

The purpose of this paper is to present a closed formula to compute the moments of a general function from the knowledge of its bivariate survival function. The result is derived by utilizing an integration by parts formula for two variables, which is not readily available in the literature. Many of the existing results are obtained as special cases. Finally, two examples are presented to illustrate the results. In both the examples, mixed moments as well as moments for the series system and parallel system are obtained. The integration by parts formula in two variables, derived here, is of interest in its own right and we hope that it will be useful in other investigations. The integration by parts formula in two variables is derived as a special case of a general formula in n variables.     

Forecasting US consumer price index: does nonlinearity matter?

The objective of this article is to predict, both in sample and out of sample, the consumer price index (CPI) of the US economy based on monthly data covering the period of 1980:1–2013:12, using a variety of linear (random walk (RW), autoregressive (AR) and seasonal autoregressive integrated moving average (SARIMA)) and nonlinear (artificial neural network (ANN) and genetic programming (GP)) univariate models. Our results show that, while the SARIMA model is superior relative to other linear and nonlinear models, as it tends to produce smaller forecast errors; statistically, these forecasting gains are not significant relative to higher-order AR and nonlinear models, though simple benchmarks like the RW and AR(1) models are statistically outperformed. Overall, we show that in terms of forecasting the US CPI, accounting for nonlinearity does not necessarily provide us with any statistical gains.     

Economic integration and stock market dynamic linkages: evidence in the context of Australia and Asia

Countries are becoming economically integrated and it is contended that this will also lead to their financial markets becoming integrated. This contention is important since international financial market integration diminishes portfolio diversification benefits and creates contagion risk. We test this contention in this article in the context of the Australasian region. Australia and Asia have experienced very significant economic integration through a rapid growth in their bilateral trade. We utilize a battery of econometric techniques – cointegration, asymmetric generalized dynamic conditional correlations and panel regression models. As expected, we find that trade intensity significantly drives the interdependence between their stock markets in both the short run and the long run. Thus, given the ever increasing economic integration in this region, this finding implies that their stock markets face the risk of contagion, and that investors in these markets would also be confronted with the prospect of lower diversification benefits.     

A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices

The popular sentiment-based investor index S^BW introduced by Baker and Wurgler (2006, 2007) is shown to have no predictive ability for stock returns. However, Huang et al. (2015) developed a new investor sentiment index, S^PLS, which can predict monthly stock returns based on a linear framework. However, the linear model may lead to misspecification and lack of robustness. We provide statistical evidence that the relationship between stock returns, S^BW and S^PLS is characterized by structural instability and inherent nonlinearity. Given this, using a nonparametric causality approach, we show that neither S^BW nor S^PLS predicts stock market returns or even its volatility, as opposed to previous empirical evidence.