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Technological innovation (TI) has become a competitive advantage to firm sustainability and survival; however, stakeholders struggle to embrace this revolution. There is a fear that technology innovation leads to massive job loss. Therefore, the purpose of this paper is to investigate TI, employee disability (EDI) and financial performance.

Using the Indian stock market as a testing ground, the authors used panel regression to analyse 80 sustainability-reporting firms (640 firm-year observations) between 2010 and 2017.

The findings show that technology innovation has a positive association with EDI. It further indicates EDI with TI improves the financial performance (return on assets and return on equity) of firms. Also, the study shows that EDI in the service and manufacturing sector are the critical contributors when combined with TI towards an increase in financial performance.

The implication for the study allows firms to increase employment of people with disabilities in the workplace because TI has a positive effect on EDI. The results from the study confirm the service sector as the highest contributor to financial performance in the emergence of TI.

The novelty of this research provides empirical evidence that the service sector contributes more to financial performance when EDI combines with TI.

The purpose of this study is to investigate the impact of the choice of an assurance service provider on financial and social performance in an emerging economy. The study also examines whether the chief executive officer’s (CEO) characteristics influence the choice of an assurance service provider.

This study uses descriptive statistics, ordinary least square and probit regression to examine the 800 firm-year observations for the period 2010–2019 and with the Indian stock market as a testing ground.

The study shows that the engagement of assurance service providers reduces financial performance (stock price returns and Tobin’s q). The study also shows that consulting firms and auditing firms improve the social performance disclosure of the firm in an emerging economy. However, consulting firms outweigh auditing firms in improving social performance disclosure. Also, the implementation of mandatory reporting may slightly impede instead of an increase in social performance disclosure in an emerging economy. The study also shows that ageing CEOs prefer consulting firms over auditing firms in assurance service provision. Finally, the study shows that an extended stay in office by a CEO improves the choice of consulting firms, but the effect has a near-neutral significance.

The choice of CEO characteristics as an independent variable adds to the factors or drivers that cause the choice of an assurance service provider in an emerging economy. Also, the measurement variable of stock price returns and Tobin’s q expands the financial performance measurement in the relationship with assurance service providers.

Studies on employee volunteerism have inconsistency in results. This study aims to examine whether employee volunteerism contributes to financial performance, and if employee volunteerism creates community benefit for firm legitimacy.

The data covers 80 companies (640 firm-year observations) and uses the Indian stock market for the period 2010-2017 as a testing ground. Canonical correlation analysis, panel regression and panel probit regression are used in this study.

The first findings of the study show employee volunteerism through employee skill contribution, number of hours spent on volunteerism, employee cash contribution and employee material contribution provide the substantive contributions to community benefit and financial performance and also contribute a possible positive reflection on employee commitment. The second findings show that return on asset and return on equity do not improve the practice of employee volunteerism. However, the stock price return (SPR) improves the practice of employee volunteerism. The third findings show that the engagement of third-party assurance (TPA) improves the practice of employee volunteerism. Finally, TPA and SPR are more likely to cause a firm to undertake employee volunteerism.

The research study is limited to large firms on the Indian stock market that submit sustainability reports.

An implication from the study suggests that the critical driver of employee volunteerism is employee skill contribution, and firms stand to benefit if well managed.

TPA and financial performance contribute an increase in employee volunteerism, and therefore deepens the scholarly debate on employee volunteerism. Employee volunteerism–community benefit nexus creates a new dimension to the theory of legitimacy for firms in an emerging economy.

The main purpose of this research study is to investigate the impact of quarterly earnings announcements on stock price movement of the firms constituting the SENSEX under two different market conditions – booming followed by recessionary. Analysis of price effect of quarterly earnings announcements during the five-year period prior to trading suspension, which is also characterized by a booming market condition have been made. Similar analysis during the five-year period following the trading suspension and marked by recessionary market condition has also been carried out side by side.

Event study methodology using daily returns and market model has been used for the purpose of analyzing the quarterly earnings announcement effects on the security prices of the firms. A sign test has also been used along with the event study.

The study reveals that quarterly earnings announcement does not have statistically significant effect on stock returns during the booming as well as the recessionary market conditions. The impact of quarterly earnings announcements on stock price movement of firms constituting the SENSEX has been similar for both periods undertaken in the study.

The study has been undertaken using the firms listed in BSE SENSEX. The effect of the quarterly earnings announcement with reference to firms listed in other indices, if covered, may provide different sets of results.

The paper identifies the informational value of quarterly earnings announcement of BSE-SENSEX.

The purpose of the study is to examine the effect of corporate social responsibility (CSR) on debt financing (natural logarithm of debt and leverage ratios) of listed firms.

Using content analysis for data extraction, the study examines listed firms on the Bombay Stock Exchange (BSE) from 2010 to 2019 financial year. It uses a quantile regression and panel fixed effect regression as the model's application.

The study shows that CSR expenditure has a positive and strong correlation with debt financing (i.e. natural logarithm of long-term and short-term debts). The first findings show that CSR expenditure has a negative and statistically significant association with total leverage ratio, using conditional mean and median percentile. However, there is a positive and statistically significant association between CSR expenditure and long-term leverage ratio at the 25th and 50th percentile. The second findings show that CSR expenditure has a positive and statistically significant association with long-term debt but an insignificant association with short-term debt and total debt under a conditional mean average. The application of quantile regression addresses the values that fall outside the confidence interval and therefore document a positive and statistically significant association between CSR expenditure and debt financing (short-term debt, long-term debt and total debt) at the 25th, 50th and 75th percentile.

The introduction of quantile regression gives a novelty in CSR and debt financing study, which to the best of the authors’ knowledge, has not received any attention. Similarly, firms have better information on how to position their CSR expenditure to attract providers of debt financing.

Corporate treasurers manage the currency risk of their organization by hedging through futures contracts. The purpose of this paper is to evaluate the effectiveness of hedging by US currency futures contracts by taking into account the efficiency of the currency market.

The static models for calculating hedge ratio are as popular as dynamic models. But the main disadvantage with the static models is that they do not consider important properties of time series like autocorrelation and heteroskedasticity of the residuals and also ignore the cointegration of the market variables which indicate short-run market disequilibrium. The present study, therefore, measures the hedging effectiveness in the US currency futures market using two dynamic models – constant conditional correlation multivariate generalized ARCH (CCC-MGARCH) and dynamic conditional correlation multivariate GARCH (DCC-MGARCH).

The study finds that both the dynamic models used in the study provide similar results. The relative comparison of CCC-MGARCH and DCC-MGARCH models shows that CCC-MGARCH provides better hedging effectiveness result, and thus, should be preferred over the other model.

The findings of the study are important for the company treasurers since the new updated Indian accounting standards (Ind-AS), applicable from the financial year 2016–2017, make it mandatory for the companies to evaluate the effectiveness of hedges. These standards do not specify a quantitative method of evaluation but provide the flexibility to the companies in choosing an appropriate method which justifies their risk management objective. These results are also useful for the policy makers as they can specify and list the appropriate methods for evaluating the hedge effectiveness in the currency market.

Majorly, the studies on Indian financial market limit themselves to either examining the efficiency of that market or to evaluate the effectiveness of the hedges undertaken. Moreover, most of such works focus on the stock market or the commodity market in India. This is one of the first studies which bring together the concepts of efficiency of the market and effectiveness of the hedges in the Indian currency futures market.

This study aims to compare the fundamental indexation (FI) portfolio vis-à-vis the cap-weighted index (CWI). It also explored the return-generating attributes of the FI portfolios.

This study extracted relevant data from the Centre for Monitoring Indian Economy’s Prowess database from March 1996 to March 2017 from a sample of National Stock Exchange (NSE) 500 companies. The FI portfolios were constructed with First_50 and Next_50 stocks using the latest and five years of trailing average aggregations. Further, the regression technique was used to identify the return-generating attributes of FI portfolios.

It was found that the FI portfolios based on First_50 and Next_50 stocks outperformed the CWI (i.e. NSE_First_50 and NSE_Next_50) in the Indian capital market, and between the two, the FI portfolios based on Next_50 stocks were superior to the FI portfolios based on First_50 stocks. The cross-sectional superiority of FI portfolios is obvious if they are sorted according to four fundamentals, namely, total income, sales, operating cash flows and profit before depreciation interest tax and amortisation. The return-generating process of FI portfolios is well-explained by market premium followed by value premium and investment premium.

This study may enable portfolio managers and investors to measure FI portfolios’ superiority in the Indian capital market and identify the return-generating attributes of FI portfolios so that the loadings can be switched amongst different priced factors for higher yield. Further, this study extends the FI literature, providing evidence from one of the world’s fastest-growing economies.

To the best of the knowledge, this is amongst the first few studies to explore the performance of FI portfolios vis-à-vis CWIs in India, and to use Fama and French (2015) asset pricing models to understand the return-generating attributes of FI portfolios. It is also novel in the sense that it considers the FI portfolios for a longer duration, predating 1997 and coinciding with the inception of CWIs, namely, NSE_First_50 (inception: 1995) and NSE_Next_50 (inception: 1996), reducing the apprehensions of data-snooping biases.

Asset pricing revolves around the core aspects of risk and expected return. The main objective of the study is to test different asset pricing models for the Indian securities market. This paper aims to analyse whether leverage and liquidity augmented five-factor model performs better than Capital Asset Pricing Model (CAPM), Fama and French three-factor model, leverage augmented four-factor model and liquidity augmented four-factor model.

The data for the current study comprises records on prices of securities that are part of the Nifty 500 index for a time frame of 14 years, that is, from October 2004 to September 2017 consisting of 183 companies using time series regression.

The results indicate that the five-factor model performs better than CAPM and the three-factor model. The model outperforms leverage augmented and liquidity augmented four-factor models. The empirical evidence shows that the five-factor model has the highest explanatory power among the entire asset pricing models considered.

The present study bears certain useful implications for various stakeholders including fund managers, investors and academicians.

This study presents a five-factor model containing two additional factors, that is, leverage and liquidity risk along with the Fama-French three-factor model. These factors are expected to give more value to the model in comparison to the Fama-French three-factor model.

Fama–French model (FFM) has been successful in helping to predict the financial markets, but investors have been interested in creating more sophisticated models to better predict the performance of the stock market. The objective of the extended version is to create a more robust econometric model to better predict the performance of the Mexican Stock Market.

The study divides the Mexican Stock Market into six different portfolios. The criteria to build those portfolios are the same one used in Fama–French (1992). The study comprises 78 stocks listed in the Mexican Stock Market that are analyzed monthly during 1997–2018. The study analyzes the period before and after the 2008–2009 financial crisis to identify whether there are important changes. The estimation applies the traditional and an extended version of the FFM that include macroeconomic variables such as country risk, economic activity, inflation rate, and exchange rate and some financial variables recommended in the literature.

Results indicate that classic FFM variables are statistically significant in most cases, but relevant macroeconomic variables such as the interest rate, exchange rate and country risk stand out for being weakly relevant in most of the portfolios. However, it is noticed that some of these macroeconomic variables became relevant for different portfolios only after the 2008–2009 crisis, especially in portfolios which include small market capitalization firms.

The study includes the stocks listed in the Mexican Stock Market. One limitation is the small number of stocks available, which reduces the possibility of creating well diversified portfolios. This study includes 78 stocks. The stocks removed from the sample are from firms that were not listed during six consecutive months or whose market capitalization did not change in the same period. Outlier data were removed from the sample to capture in better way the general performance of the stock market.

The objective of the extended version is to create a more robust econometric model than the traditional model. It is expected that such estimations can be helpful to investors to make better decisions when they try to predict performance in the stock market.

An extended version of the FFM can be helpful to investors to make better decisions when they try to predict performance in the stock market.

To the best of our knowledge there are no more studies in the literature of the Mexican financial market that apply the same methodology.

The purpose of this study is to focus on examining whether third-party assurance (TPA) and mandatory corporate social responsibility reporting (MCSR) matter in the association between philanthropic giving (PHG) and listed firms’ financial performance.

Using the Indian stock market as a testing ground, the study used interactive regression and panel regression to analyse 80 sustainability-reporting firms with 800 firm-year observations between 2010 and 2019.

The first findings show a positive association between PHG and financial performance (return on assets, ROA and stock price returns, SPR). Also, the study shows that the interactive variable of MCSR and PHG has a mixed association with financial performance. The second findings show a positive and statistically significant association between TPA and SPR. Also, the interactive effect of TPA and PHG has a negative association with return on equity (ROE) and a positive association with SPR. The third findings show a negative association between MCSR and financial performance (ROA and ROE) and a positive association with SPR. However, when a firm combines MCSR and TPA, the outcome is a negative association with ROE. The fourth findings show that MCSR has a positive association with TPA. The study control for any form of heteroscedasticity, serial correlation and endogeneity effects.

Managers, if given a choice, must opt for TPA over MCSR because the βcoefficient is higher in TPA than MCSR in PHG-financial performance nexus.

The study addresses the information asymmetry problem from the application of TPA and MCSR, which is new to an emerging economy context.