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The authors analyze the relationship between exchange rate fluctuations of a number of major currencies and its impact on US stock market returns, as proxied by the S&P 500. Many studies have explored this topic since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This study takes a different look at this hypothesis and investigates the pairwise relationship between various exchange rates and the United States stock market returns (S&P 500 INDEX) from January 2000 to December 2019.

The authors test the data for unit roots using Phillip-Perron method. They use Johansen cointegration model to determine whether returns on S&P 500 are integrated with S&P 500. They use the VAR/VECM analysis to test whether there are any interdependencies between exchange rates and stock market return. Finally, they use various GARCH models, including the EGARCH and TGARCH models, to determine whether there exist volatility spillovers from exchange rate fluctuations in various markets to the volatility in the US stock market.

Using GARCH modeling, the authors find volatility in Australian dollar, Canadian dollar and the euro impact market return, and the volatility of Australian dollars and euro spills over to the volatility of S&P 500. They also find that the spillover is asymmetric for Australian dollars.

One of the limitations could be that the authors use different bivariate GARCH models rather than the MV-GARCH models. For future project(s), they plan to do this analysis from the perspective of a European Union or a British investor and use returns in those markets to see the impact of exchange rates on those markets. It would be interesting to know how the relationship will change during periods of financial crises. This could be achieved by employing structural break methodology.

Many studies have explored the relation between stock market returns and exchange rates since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This paper contributes by adding to the existing literature on impact of exchange rate on stock returns and by providing a detailed and different empirical analysis to support the results.

The purpose of this paper is to determine the best way to hedge currency risk using futures contracts. Various techniques of hedging currency risk are compared, and a new method is proposed. This paper also documents the duration and the expiration effects on the optimal hedge ratio. The main finding of this paper is that, of the techniques examined, the hedge ratio derived by Vishwanath (1993) performs the best. This paper also finds that as the duration of the hedge increases, the hedge ratio increases. For one week and two weeks duration hedges, as the time left to futures contract expiration increases, the hedge ratio increases and there is linear relationship. The results are not as pronounced for four and six-week duration hedges.

The purpose of this paper is to examine if the volatility in the US dollar interest rate swap market impacts the volatility of the swap rates in the Indian swap market.

The authors use GARCH, EGARCH, and TGARCH modeling to examine volatility spillover between the US and Indian interest rate swap markets.

Evidence is found of volatility transmission from the US dollar interest rate swap markets to the Indian swap markets. There is no evidence of spillover from the Indian swap markets to the US swap markets. Furthermore, the spillover impact from the US markets to the Indian markets is also asymmetric. The impact on volatility is asymmetric for one‐year swaps, but not for five‐year swaps.

Findings from this study will also identify any arbitrage opportunities that may exist between different segments of the US dollar interest rate swap markets and help to improve interest rate swap market efficiency.

If the financial market liberalization process in these nations has been successful in integrating their market into the pool of the world market, then a foreign investor would not demand a risk‐premium in the returns on deposits in these markets. The findings of this paper are also relevant for other emerging markets' policy makers, as they try to become more integrated in the global economy and try to resolve market inefficiencies and country risk so that obstacles to foreign investments can be removed.

The purpose of this study is to review the literature on work–life interface (WLI) studies conducted in India, including how cultural and institutional factors affect the work–life balance perception of Indian employees and how they differ from the west.

The preferred reporting items for systematic reviews and meta analyses (PRISMA) framework was used to select studies included in this systematic review.

Employees in India prioritize their family first because of the collectivist culture as opposed to the west, where work forms the role of root identity. Further, it was found that institutional support in India is lower than in developed western countries, resulting in difficulty for Indian employees to balance their work and life domains. Additionally, methodological advancement and large-scale multilevel research are much needed in India, as research on work–life studies is still in its infancy.

This study is limited to qualitative synthesis of PRISMA framework. Adopting more advanced “meta-analysis” techniques to review quantitative studies could result in more comprehensive and informative results.

Since 2009, there has been an increase in empirical studies conducted on work–life studies in India, but no systematic review has been conducted to understand the various theories and variables used by researchers. In this study, we developed a conceptual model to increase the theoretical knowledge of WLI constructs.

Mobile phones have become one of the most favored devices to maintain social connections as well as logging digital information about personal lives. The privacy of the metadata being generated in this process has been a topic of intense debate over the last few years, but most of the debate has been focused on stonewalling such data. At the same time, such metadata is already being used to automatically infer a user’s preferences for commercial products, media, or political agencies. The purpose of this paper is to understand the predictive power of phone usage features on individual privacy attitudes.

The present study uses a mixed-method approach, involving analysis of mobile phone metadata, self-reported survey on privacy attitudes and semi-structured interviews. This paper analyzes the interconnections between user’s social and behavioral data as obtained via their phone with their self-reported privacy attitudes and interprets them based on the semi-structured interviews.

The findings from the study suggest that an analysis of mobile phone metadata reveals vital clues to a person’s privacy attitudes. This study finds that multiple phone signals have significant predictive power on an individual’s privacy attitudes. The results motivate a newer direction of automatically inferring a user’s privacy attitudes by leveraging their phone usage information.

An ability to automatically infer a user’s privacy attitudes could allow users to utilize their own phone metadata to get automatic recommendations for privacy settings appropriate for them. This study offers information scientists, government agencies and mobile app developers, an understanding of user privacy needs, helping them create apps that take these traits into account.

The primary value of this paper lies in providing a better understanding of the predictive power of phone usage features on individual privacy attitudes.

This study aims to investigate the influence of customer satisfaction on four facets of customer engagement: customer influencer behavior, knowledge behavior, referral behavior and purchase behavior. Furthermore, its (in)direct influence on affective attitude, price perception and loyalty is investigated.

Two studies were conducted. First, an experimental scenario design was set up to investigate the hypothesized relations between customer engagement; customers’ affective attitude and their loyalty; and their price perceptions. Second, a survey at a national forest park center helped to secure external validity.

The results indicate that engaged customers develop a more positive affective attitude, which leads to increased future loyalty and positive price perceptions. In addition, the results suggest that assessing cognitive approaches exclusively is not sufficient for understanding customers’ price perceptions.

Future research should investigate antecedents of customer engagement behaviors (CEBs) other than satisfaction, and extend this research by taking into account further mediators that might be cognitive rather than affective.

The results are of superior importance for services or tourism destinations. Fostering CEB can help in improving a destinations’ performance.

This research expands the current state of literature by investigating several dimensions of CEB at one time, as well as by examining customers’ affective attitude toward the organization as a potential mediator, extending previous research approaches.

A vaccination strategy to cover the susceptible population is key to containing the spread of any virus during a healthcare emergency. This study quantifies the susceptibility of a region based on initial infection rates to prioritize optimal vaccine distribution strategies. The authors propose a metric, the regional vulnerability index (RVI), that identifies the degree of susceptibility/vulnerability of a region to virus infections for strategically locating hubs for vaccine storage and distribution.

A two-phase methodology is used to address this problem. Phase 1 uses a modified Susceptible-Infected-Recovered (SIR) model, ModSIR, to estimate the RVI. Phase 2 leverages this index to model a P-Center problem, prioritizing vulnerable regions through a Mixed Integer Quadratically Constrained Programming model, along with three variations that incorporate the RVI.

Results indicate a weighting scheme based on the population-to-RVI ratio fosters fair distribution and equitable coverage of vulnerable regions. Comparisons with the public distribution strategy outlined by the Government of India reveal similar zonal segregations. Additionally, the network generated by our model outperforms the actual distribution network, corroborated by network metrics such as degree centrality, weighted degree centrality and closeness centrality.

This research presents a novel approach to prioritizing vaccine distribution during pandemics by applying epidemiological predictions to an integer-programming framework, optimizing COVID-19 vaccine allocation based on historical infection data. The study highlights the importance of strategic planning in public health response to effectively manage resources in emergencies.

The purpose of this paper is to examine the joint effects of personality (agreeableness and conscientiousness) and perceived supervisory career mentoring (SCM) on occupational commitment (OC) in the Indian context. In addition, the role of SCM support as a predictor of OC was also analyzed.

A cross-sectional survey-based research design was adopted using data from 121 employees of public and private sector organizations in North India.

The results showed that the relationship between perceived SCM and OC was stronger for employees reporting high levels of agreeableness in contrast to low agreeableness. Further, perceived SCM support was observed as a significant predictor of OC in the Indian context.

This study suggests that for fostering an occupationally committed workforce, it is critical for supervisory mentors to understand how to deal with employees of different personality traits. Further, supervisory mentors need to be trained and empowered to render vocational support to employees at all levels.

The work advances the existing work on mentoring and vocational outcomes by demonstrating the crucial role of supervisory career support and personality interactions in predicting OC.