Kishore Lakshminarayanan

The interplay between stock market performance and economic risk is a central concern in financial economics, as macroeconomic variables have a considerable impact on investment decisions and stock pricing. This relationship is particularly critical for bank stocks, as their performance is a key indicator of a country’s financial health. While extensive research has explored bank stock returns in developed economies, there exists a significant gap in understanding this dynamic within developing countries like India, particularly amid macroeconomic fluctuations underscored by the COVID-19 pandemic. Given the substantial investments in bank stocks by Indian investors, this study aims to examine the impact of macroeconomic factors on Indian bank stock returns. The study employs quarterly data from 2013–14 to 2022–23, with macroeconomic data sourced from the CMIE Economic Outlook and bank stock returns data obtained from the Bloomberg database. Using an Ordinary Least Squares regression model, the findings reveal that interest rate (β = 0.3069), inflation (β = 0.1644), GDP (β = 0.1928) and COVID-19 (β = 0.5737) exert significant positive effects on bank stock returns, while the exchange rate (β = –0.7440) has a substantial negative impact. The results highlight the sensitivity of bank stock returns to macroeconomic volatilities, with the pronounced impact of the COVID-19 pandemic further highlighting the effects of economic crises. The findings emphasize the need for incorporating these factors into the bank stock returns model, offering valuable insights for investors, banks, and financial regulators. AcknowledgmentAleena Joseph is a recipient of the Indian Council of Social Science Research Doctoral Fellowship. The article is largely an outcome of the doctoral work sponsored by ICSSR. However, the responsibility for the facts stated, opinions expressed, and the conclusions drawn is entirely that of the authors.

Background Data Envelopment Analysis (DEA) methodology is considered the most suitable approach for relative performance efficiency calculation for banks as it is believed to be superior to traditional ratio-based analysis and other conventional performance evaluations. This study provides statistical evidence on the sampling error that can creep into performance evaluation studies using the DEA methodology. Inferences are drawn based on samples, and various preventive measures must be taken to eliminate or avoid sampling errors and misleading results. This study demonstrates the possibility of sampling error in DEA with the secondary data available in financial statements and reports from a sample set of banks. Methods The samples included 15 public sectors and five leading private sector banks in India based on their market share, and the data for calculating efficiencies were retrieved from the published audited reports. The sample data was collected from 2014 to 2017 because the banking sector in India witnessed a series of mergers of public sector banks post-2017, and the data after that would be skewed and not comparable due to the demonetization policy implementation and merger process-related consolidation implemented by the Government of India. The efficiency measures thus computed are further analyzed using non-parametric statistical tests. Results We found statistically significant discrepancies in the efficiency score calculations using DEA approach when specific outlier values. Evidence is provided on statistically significant differences in the efficiencies due to the inclusion and exclusion of particular samples in the DEA. Conclusion The study offers a novel contribution along with statistical evidence on the possible sampling error that can creep into the performance evaluation of organizations while applying the DEA methodology.

Sustainability has emerged as one of the most critical factors influencing the competitiveness of maritime shipping ports. This emergence has led to a surge in research publications on port sustainability-related topics. However, despite the increasing awareness and adoption of sustainability practices, documented literature on empirical studies with survey and interview data is very limited. Moreover, the existence of validated instruments to objectively assess sustainability through sustainability practices for shipping ports in India needs to be traced. This study contributes by validating an instrument to evaluate objectively sustainability practices in shipping ports by adopting a four-stage process, starting with item identification based on an extensive literature review, instrument evaluation by subject matter experts, assessing of the instrument with suitable content validation indices, and finally evaluating the validity and reliability of the hypothesized theoretical model. For content validation, Content Validity Index, Cohens Kappa coefficient, and Lawshe’s Content Validity Ratio were computed with the assessment by a subject matter expert panel comprising six members from the port industry as well as academicians cum researchers in the field of shipping ports. The content-validated instrument was administered to 200 samples comprising officer category port employees. The measurement model was evaluated and validated using the Confirmatory Factor Analysis to assess the extent to which the measured variables represent the theoretical construct of the study and ascertain the factor structure. The empirically validated instrument met the required guidelines of model fit, reliability, and construct validity measures and was found to be a confirmed model for measuring sustainability practices in shipping ports. Structural Equation Modeling methodology was adopted to explain the variance and the path relationship between the higher-order and lower-order constructs of sustainability. The results indicate that the economic dimensions are the major contributors to the overall sustainability of the port as they drive investments in environmental and social dimensions, leading to overall sustainable development. The study’s findings will be helpful for researchers, academicians, policymakers, and industry practitioners working towards sustainability practices that contribute to sustainable growth and development in the shipping industry.

Background Data Envelopment Analysis (DEA) methodology is considered the most suitable approach for relative performance efficiency calculation for banks as it is believed to be superior to traditional ratio-based analysis and other conventional performance evaluations. This study provides statistical evidence on the sampling error that can creep into performance evaluation studies using the DEA methodology. Inferences are drawn based on samples, and various preventive measures must be taken to eliminate or avoid sampling errors and misleading results. This study demonstrates the possibility of sampling error in DEA with the secondary data available in financial statements and reports from a sample set of banks. Methods The samples included 15 public sectors and five leading private sector banks in India based on their market share, and the data for calculating efficiencies were retrieved from the published audited reports. The sample data was collected from 2014 to 2017 because the banking sector in India witnessed a series of mergers of public sector banks post-2017, and the data after that would be skewed and not comparable due to the demonetization policy implementation and merger process-related consolidation implemented by the Government of India. The efficiency measures thus computed are further analyzed using non-parametric statistical tests. Results We found statistically significant discrepancies in the efficiency score calculations using DEA approach when specific outlier values. Evidence is provided on statistically significant differences in the efficiencies due to the inclusion and exclusion of particular samples in the DEA. Conclusion The study offers a novel contribution along with statistical evidence on the possible sampling error that can creep into the performance evaluation of organizations while applying the DEA methodology.

The maritime sector has evolved as a crucial link in countries' economic development. Given that most of the trade across regions takes place through naval transportation, the performance of the seaports has been one of the focus areas of research. As the publication volume has significantly grown in the recent past, this study critically examines the publications related to the performance of ports for exploring the evolution, identifying the trends of articles, and analyzing the citations covering the publications based on relevant keywords in Scopus database for the period 1975–April 2024. Bibliometric and scientometric analysis was done using R, Python, and VOS software tools. Results indicate the core subject areas as “port efficiency”, “data envelopment analysis” (DEA), “port competitiveness”, “simulation”, “port governance”, and “sustainability,” with "sustainability" as the most discussed and highly relevant theme that has evolved in the last five years. Bibliometric data analysis on the subject area, yearly trends, top journals of publications, citation and author analysis, impact analysis, country-wise publication, and thematic analysis with clusters are also performed to outline future research directions. The analysis indicates an exponential rise in publications in recent times and with sustainability-related studies gaining more importance, especially for empirical research on port performance and demands for future empirical research on sustainability and smart port performance subject area. The study's findings are helpful for researchers, academicians, policymakers, and industry practitioners working towards a sustainable maritime port industry.

Risk aversion plays a crucial role in understanding how individuals make financial decisions and allocate their resources. This study analyzes the influence of risk aversion on behavioral intentions and explores the mediating role of attitudes, subjective norms, and perceived behavioral control. Additionally, it investigates the moderating effect of gender and financial literacy on behavioral intentions of investors. A sample of 400 people was collected from Indian retail investors by administering a structured questionnaire through stock brokering firms, and data were analyzed using Partial least squares – Structural equation modelling in the Smart PLS 3.3.9 software. The research found that risk aversion, attitude, subjective norms, and perceived behavioral control significantly impact an investor’s intention. Among all the antecedents of behavioral intentions, perceived behavioral control (β 0.481*) was found as a significant predictor of the intention compared to attitude (β 0.154*), subjective norms (β 0.224*) and risk aversion (β 0.082*) factors. Further, mediation analysis found that attitude, subjective norms, and perceived behavioral control partially mediated the relationship between risk aversion and intention. Lastly, the multi-group analysis revealed that gender and financial literacy did not moderate the association between risk aversion and intention.

Personality traits are qualities that make a person distinctive and describe stable behavior patterns. Therefore, understanding the influence of personality traits on behavioral intention will help predict investors’ investment decisions. This study aims to assess the impact of personality traits, i.e., openness to experience, neuroticism, conscientiousness, agreeableness, and extraversion, on investors’ behavioral intentions. Moreover, it assesses the mediating effect of attitude, subjective norms, and perceived behavioral control between investors’ personality traits and behavioral intention. The study employed a structured questionnaire on a sample of 413 retail investors. Further, obtained data were empirically examined on Smart-PLS 3.3 using the PLS-SEM method. The study found that perceived behavioral control, subjective norms, and attitude positively affected behavioral intention. However, the personality traits did not influence the intention directly. Further, mediation analysis revealed that attitude and subjective norm fully mediated the relationship between extraversion, neuroticism, openness, and intention. In contrast, attitude and subjective norms did not exhibit a mediating relationship between agreeableness, conscientiousness, and intention. Finally, perceived behavioral control fully mediated the relationship between personality traits and intention, except for conscientiousness. The study contributes by extending the applicability of the theory of planned behavior by examining the impact of big-five personality traits on behavioral intention and mediating the role of the theory of planned behavior’s dimension between personality traits and intention.

The investment decisions are subjected to risk and return of the financial asset. Options strategies help employ a suitable strategy to balance the risk-return trade-off. The study analyzes the risk-return trade-off of the long straddle, long strangle, long call butterfly (LCB), short straddle, short strangle, and short call butterfly (SCB) strategies. Moreover, it measures the impact of strategy risk and options premiums on strategy return using panel data analysis. Additionally, the study evaluates the performance of options strategies using the excess returns to risk approach under neutral and volatile market conditions. This paper considered companies of top-six sector indices of the National Stock Exchange from 2009 to 2020 and collected data of 18,720 option contracts and 3,744 observations for each strategy (22,464 observations). The study revealed that risks of long straddle and long strangle strategies have a positive impact, and options premiums negatively influence their payoff. ATM call premiums positively affect LCB payoff, while OTM and ITM call premiums positively influence SCB payoff. However, the risks of butterfly strategy did not influence its payoff. The risk of short straddle and short strangle strategies negatively influenced the payoff and were considered riskier strategies. Moreover, short straddle and short strangle strategies enhanced excess returns under both market conditions. The results would help the investors in choosing the appropriate strategy by analyzing the impact of risk on the payoff and the ability to enhance excess returns to the risk of various options strategies to incorporate in their investment.