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Introduction: The government has taken many initiatives for the overall growth of India after liberalisation and remarkably performed to make India an emerging economy. Due to changes in macroeconomic conditions, investment in companys’ shares includes the possibility of bearing high risk, which cannot be eliminated but, to some extent, minimised. The persistence of risks motivates investors to invest in different available options of investment. Gearing measures, a company’s financial leverage, represent the risk afforded within the company’s capital structure.

Purpose: The research aims to identify the risk-return analysis of financial geared stocks of Nifty 50 companies in India, which have debt equity ratios of more than 1.

Methodology: Convenience and cluster sampling techniques were used to identify companies with debt equity ratios of more than 1. The considered time period is 2010–2019.

Findings: This research found capital structure ratios, debt equity ratio, and total debt ratio. The total equity ratio does not have any visible effect on any of the dependent variables, i.e., Return on equity (ROE), Return on Assets (ROA), Earnings per share (EPS), Return on capital employed (ROCE). It explains the impact of high-levered firms’ performance on profitability and functioning. The study highlights that highly geared companies do not significantly impact the ROA, proving Modigliani and Miller’s (1958) irrelevant theory.

The impact of the intellectual capital disclosure (ICD) on the cost of equity capital (COEC) is not well established in the aspect of the Indian scenario. So the objective of this paper is to examine not only the overall effect of ICD but also the individual effect of human capital disclosure (HCD), relational capital disclosure (RCD) and structural capital disclosure (SCD) on COEC.

This research work is conducted by regressing COEC, firm size, leverage, industry type and disclosure index. The disclosure index is prepared based on content analysis of disclosure made in the annual reports of a sample of 50 companies listed in the Nifty 50 index for the year 2018–2019. But in this paper 20 companies are eliminated due to their negative COEC and rest 30 companies are used as the sample companies for this study.

The outcome of this study indicates a negative association between the disclosure of intellectual capital (IC) as a whole and the COEC. But a negative association only for two components (human capital and structural capital) with the COEC is found only when the association of COEC with the categories of ICD is considered.

This is the first study that examines the nexus between the level of ICD and its impact on the COEC in India context.

It intends to help the learners assess the scenarios of volatility in the Indian capital market which was caused by unpredictable market forces. It also helps in understanding how analysts struggle to predict the direction of the market and what options strategies can be recommended to be deployed by the investors to maximize returns in such compelling scenarios.

This case study presents snapshots of high volatilities caused by the market and economic forces in the Indian capital market. It depicts how analysts struggled to predict the direction of the market; and how high volatility can put them in trouble. It also exemplifies as to how by selecting the apt strategies, investors maximize their immediate returns in a volatile period and can produce large returns in a short time.

The best time to discuss the case is during the completion of options strategies in the course of Derivatives or Portfolio/Investment Management.

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CSS 1: Accounting and Finance.

The purpose of this paper is to investigate whether the investor attention using the Google search volume index (GSVI) can be used to forecast stock returns. The authors also find the answer to whether the “price pressure hypothesis” would hold true for the Indian stock market.

The authors employ a more recent fully balanced panel data for the period from July 2012 to Jun 2017 (260 weeks) of observations for companies of NIFTY 50 of the National Stock Exchange in the Indian stock market. The authors are motivated by Tetlock (2007) and Bijl et al. (2016) to employ regression approach of econometric estimation.

The authors find that high Google search volumes lead to positive returns. More precisely, the high Google search volumes predict positive and significant returns in the subsequent fourth and fifth weeks. The GSVI performs as an useful predictor of the direction as well as the magnitude of the excess returns. The higher quantiles of the GSVI have corresponding higher excess returns. The authors notice that the domestic investor searches are correlated with higher excess returns than the worldwide investor searches. The findings imply that the signals from the search volume data could be of help in the construction of profitable trading strategies.

To the best of the authors knowledge, no paper has examined the relationship between Google search intensity and stock-trading behavior in the Indian stock market. The authors use a more recent data for the period from 2012 to 2017 to investigate whether search query data on company names can be used to predict weekly stock returns for individual firms. This study complements the prior studies by investigating the relationship between search intensity and stock-trading behavior in the Indian stock market.

This paper investigates herding behavior and its persistence among foreign institutional investors (FIIs) in the individual stocks of the energy sector of Indian stock exchange by focusing on post turmoil period. The study also examines the relation of herding with the individual return, market return, trading volume and conditional volatility of individual and market return.

The presence of herding is investigated by Lakonishok et al. (1992) model, value-based and count-based herd ratio measure among FIIs in individual stock of energy sector post turmoil period. Further, run test was employed to check the persistency in herding and multivariate distributed lag to investigate the relationship with the market determinant.

The result indicates the existence of herding in most of the companies and strong persistence in all the companies. The intensity of buy side herding is higher than sell side. Herding and individual return both are significant driving forces of FIIs herding, while trading volume and market volatility in few companies exhibit inverse relationship.

This study is limited to investigation of energy sector stock.

Stock market is significantly influenced by FIIs and their propensity to herd may generate instability in the stock market. Therefore, regulatory authority should continuously monitor the flow of fund by FIIs.

Herding in the individual stock of the energy sector was not previously performed.

The purpose of this paper is to construct the social and environmental disclosure index for Indian companies in order to examine the relationship between social and environmental disclosure and select corporate attributes.

The sample covers annual reports of companies for financial year 2011-2012. The sample represents both financial and non-financial companies that constitute Nifty 50 Index companies as on March 31, 2012. The actual size of the sample analyzed represented 41 companies. The unweighted disclosure index approach has been used to measure the extent of disclosure of social and environmental information where an item scores 1 if disclosed and 0 if not disclosed. The authors built a model using regression which indicates the variables that are significant in determining the social and environmental disclosure of a company. The regression model can be used to predict the degree of disclosure of a company given the values of explanatory variables. Content analysis from annual reports of the companies has been used in constructing the dependent variable.

Regression results indicate that location (place where the registered office of company is located), number of operations of company, turnover, sales and administration expenses, age of company, employee cost and interest paid by company are significant in determining the disclosure index of the company.

Sample size can be increased by considering more companies. In addition, a longitudinal study would enable in drawing comparison over a period of time with respect to disclosure index. The increased sample size would help in validating the disclosure score by dividing the data set into two: one as observation window and the other as validation window.The model explains 23 percent variation in disclosure index. More variation may be explained by incorporating more explanatory variables in the model.

The authors indicate the level of disclosure in case of Indian companies which may prove to be an indicator for prospective investors especially in the present era of global financial and economic downturn. The paper may assist the regulators in framing policies regarding corporate governance. This will enable the regulators of corporate sector to frame laws in order to predict the degree of disclosure of a company based on certain explanatory variables.

The authors focus especially on Indian companies for constructing the disclosure index which to the best of knowledge has not been attempted till date.

Ample literature is available on the impact of socio-cultural and political conditions on corporate social responsibility (CSR), but the reverse has not been adequately studied. COVID-19 pandemic disrupted humankind and business, but CSR was resilient. COVID-19, an unprecedented crisis, developed into a disaster but had some positives too. In fact, it championed the businesses' role and relationships between businesses and regulators, society, stakeholders, environment at large. Some available literature analyses how CSR metamorphosised itself and disrupted and converged into all similar and associated phenomenon like philanthropy, charity, governance, sustainability, and as a regular business activity. The present research uses mixed methods to analyse the CSR data published by the government of India during COVID-19 years and refer to the firms' disclosures in the CSR reports. Findings offer a nuanced input to the understanding of the impact of COVID-19 on CSR by studying it in a regulated environment where firms emerged as responsible corporate citizens attending to the needs of all the stakeholders. Firms acts of responsibility transcended law and contributed in form of funds (PM relief funds) and other necessary health equipment like PPE kits, oxygen cylinders, masks, sanitizers, vaccines, etc. Interestingly, the government amended the law to include contributions to COVID-19 mitigation as a part of CSR. While the current study is based on a data from a limited time, it lays a ground for future studies analysing the nature of shift (short term or long term) and how changes have impacted the policies (public and organisational policies).

The motivation for this study is to understand the stressful situations leading to great resignation and evaluate the cognitions of psychological attachment (PA) and organizational attractiveness (OA) to mitigate this crisis, using the attachment theory as the theoretical basis.

A cross-sectional study was conducted on individuals employed in Indian organizations (Nifty 50) to identify the most impactful cognitions underlying the dynamics between person–job fit (P-J fit) and the intention to stay (ITS).

This study highlighted that a serial mediation relationship between PA (specifically “internalization”) and OA is influenced by the P-J “needs–supplies” fit, particularly during extraordinarily stressful times. Managers must re-emphasize PA and OA as core organizational resources that must be prioritized, maintained and refined to reinforce employees' intent to stay in their organizations.

No research has studied P-J fit, PA, OA, underpinned by the attachment theory to reinforce the ITS given the context of the great resignation triggered by the pandemic's extraordinarily stressful situation.

The purpose of this paper is to understand the impact of components of marketing expenditures, i.e. advertising and distribution expenditures on intangible value of firm (measured in terms of Tobin's Q). The relationship is studied in the context of branding approaches (corporate and house of brands) that various firms follow.

The data are collected from databases of Centre for Monitoring Indian Economy (CMIE) and from the web site of National Stock Exchange. Time series regression is performed using SPSS software to test the model.

Advertising expenditure has a positive impact on the intangible value of the firm and this relationship is stronger for firms following corporate branding than for firms that follow house of brands strategy. Distribution expenditure has negative impact on the intangible value of the firm and this relationship is stronger for firms following corporate branding than for firms that follow house of brands strategy.

Since most of the data retrieved for the analysis were of B2B (business to business) firms, the findings may not be generalized for all firms.

Advertising expenditure has a diminishing marginal utility in creating intangible value. It would be useful for firms to understand where they are on this continuum and whether their advertising expenditure is giving adequate returns or may be better spent elsewhere.

In the literature, researchers have expressed mixed viewpoints regarding the impact of total marketing spend on intangible value. The marketing expenditures are found to have both positive and negative impact on intangible value, with respect to various contexts. However, the impact of major components of marketing expenditures is not addressed. This gap is addressed in this research paper.