Bombay Stock Exchange Research Articles

Psychological Determinants of Investment Decisions: Analyzing Financial Behavior in Personal Investments

Understanding the psychological factors that influence investor behavior is critical in the dynamic world of financial markets. Financial conduct encompasses the decisions and behaviors individuals exhibit in managing their finances, including investments in various asset classes. Factors such as risk tolerance, cognitive biases, emotional influences, and financial knowledge significantly shape investment outcomes. Gaining long-term financial success requires mastery over these behavioral aspects. This study investigates the influence of three psychological factors—information asymmetry, problem framing, and risk propensity—on the investment decisions of 220 active investors trading on the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE). A quantitative research approach was employed, utilizing a structured questionnaire to collect data. Statistical analyses, including regression and correlation analysis, were used to assess the relationships between these psychological variables and investment behaviors. The results reveal significant correlations between psychological factors and investment decisions. Information asymmetry, problem framing, and risk propensity were found to strongly influence individual investor choices. These findings shed light on the intricate role that cognitive biases and psychological processes play in shaping financial decision-making. The study's findings offer valuable insights into the psychological drivers behind investment behavior. By highlighting the impact of these factors, the research contributes to both academic understanding and practical applications for financial professionals. The results underscore the importance of enhancing financial literacy and investor education, enabling more informed decision-making and promoting improved financial outcomes.

Impact of intellectual capital on financial competitiveness in context of listed Indian healthcare enterprises

Purpose This study aims to determine impact of Intellectual Capital (IC) and its constituents in impacting Financial Competitiveness (FC) of Standard & Poor’s Bombay Stock Exchange Healthcare index constituents for years 2013–2023. Design/methodology/approach This research work used Modified Value-Added Intellectual Coefficients model to gauge IC, whilst an index has been used to apprehend alterations in FC of enterprises. Generalised method of moments (GMM) model was used to determine association between IC and FC of these enterprises. Findings Results demonstrated that IC in entirety had a notable role in FC of healthcare firms. Results showed that human and relational capital had an affirmative role, while structural capital, capital employed and innovation capital had adverse roles in competitiveness. Research limitations/implications This study provides important contributions to academicians, researchers, management, directors and policymakers by equipping them for preparing a roadmap for future performances. Outcomes imply that IC and its segments must be efficaciously managed in the highly knowledge intensive and intricately interconnected healthcare sector, to establish greater competitive acumen thereby rendering improved and superior results. Originality/value This work focusses in lesser researched Indian healthcare sector, scrutinising association between IC efficiency and FC for years 2013–2023.

Stock Returns and Volatility: Comparative Investigation from SAARC Countries

This research article analyses the stock return and volatility of three selected SAARC countries (Pakistan, India, and Bangladesh), focusing on the role of natural resources in influencing market performance. This study aims to determine the robustness of the performance, considering the economic significance of these countries' natural resources. The daily data from the PSX 100 index (Pakistan Stock Exchange), BSE index (Bombay Stock Exchange), and DSE index (Dhaka Stock Exchange) for the years 2019 to 2021 has been obtained from their websites. The data is treated in MS Excel to compute the daily Geometric Returns for BSE, PSX, and DSE indices. Furthermore, the data were analyzed using the specialized package EViews for Time Series Graph, Descriptive Statistics, Unit Root Test, and GARCH Model. The findings of this research show that the BSE index has the highest return value of 6.78 percent compared with 4.56 percent and 3.75 percent for DSE and PSX, respectively. The Half-life model has been applied to calculate the volatility observed by the indices. The result shows that BSE is the most volatile and takes the highest time of 45 days to revert to its mean position, followed by PSX and DSE, which take 19 and 10 days, respectively. Therefore, investing in the BSE index is better for risk-lover investors. At the same time, DSE has the fastest mean reversion compared to the other two indices. Therefore, it is feasible for risk-averse investors.

Exploring Asymmetric Volatility Spillovers among Major Bombay Stock Exchange Indices

Exploring Asymmetric Volatility Spillovers among Major Bombay Stock Exchange Indices

Does integrated reporting offer firms more legitimacy?

PurposeThe study delves into the impact of integrating reporting (IR) on three earnings management tools, namely classification shifting (CS), real-based earnings management (REM) and accrual-based earnings management (AEM) under the Indian institutional settings.Design/methodology/approachThe data analysis involved the application of panel data regression models. Our dataset comprises 2,244 firm-years listed on the Bombay Stock Exchange spanning over financial years from March 2015 to 2021. To address endogeneity and self-selection bias concerns, a propensity score matching technique has been employed.FindingsOur empirical results exhibit that IR-adopting firms are engaged in earnings management. Further, we find that IR-adopting firms have reduced their engagement in AEM and REM, however, their CS practices have been increased, indicating the substitution relationship between earnings management tools after the adoption of IR. It implies that firms shift their preference from more to less observable earnings management tools after the adoption of the IR, which aligns with the idea that firms adopt IR to gain legitimacy, however, their intention to deceive stakeholders through earnings management remains unchanged. The inclination of firms toward CS can be ascribed to its cost-effectiveness, as it leaves net profit unchanged, hence less likelihood of being detected by auditors. Overall, our results align with the principle of legitimacy theory.Research limitations/implicationsThe study focuses exclusively on three primary forms of accounting manipulation and assesses IR holistically, rather than investigating the influence of each capital individually within IR.Practical implicationsWith a shift towards less detectable methods like CS, auditors must adapt their scrutiny and be mindful of their clients' IR adoption. Investors should scrutinize IR-adopting firms' financial disclosures, especially line items, as CS does not impact the net profits.Originality/valueIt is the pioneering research to thoroughly explore the impact of IR on different earnings management tools and strengthen the conceptual frameworks of legitimacy theory by documenting that firms adopt IR to gain legitimacy, however their intention to engage in earnings management remains intact.

Impacts of corporate governance attributes on audit quality in emerging economies: The case of India

Purpose The present study examines the impact of corporate governance attributes on audit quality in the context of an emerging market, India. The study is based on data from 100 non-financial firms listed on the Bombay Stock Exchange randomly selected from the list of BSE 500 firms on 31 March 2021 for 2017–2021. Aim To measure audit quality using two input-based measures – audit fee and audit firm size (Big-4 or non-Big-4). Design/Methodology/Approach This study uses logistic regression and panel data regression models to investigate the impact of corporate governance variables on audit quality after controlling for some firm-specific variables. Furthermore, a generalised estimating equation model is used to check the robustness of the logistic regression model results. Main findings The results indicate that board independence, board gender diversity, multiple directorships, and audit committee independence positively correlate with audit quality. However, the board size, role duality, and promoter shareholding are negatively associated with the audit quality. Further, the quantile regression results indicate heterogeneous impacts of role duality and promoters’ shareholding on audit quality. Practical implications First, firms with the concentration of power in the hands of promoters directly or indirectly may engage Big-4 auditors to enhance AQ. Second, policymakers should take appropriate steps to enhance the gender quota as per international norms to improve the quality of financial reporting. Third, firms' should capitalise on the enhanced advisory capability of the directors having exposure and association with other companies. Novelty/Contribution The study enriches the existing literature by providing empirical evidence from an emerging nation characterised by the dominance of promoters’ shareholding, busy boards, and role duality.

Ownership concentration and SME IPO underpricing in India – moderating impact of board monitoring and resource provision role

PurposeThe study aims to explore how the monitoring and resource provision function of board of directors impact the association between ownership concentration and small- and medium-sized enterprise (SME) initial public offering (IPO) underpricing in the context of an emerging economy like India.Design/methodology/approachThe sample comprises 390 SME IPOs listed on Bombay Stock Exchange SME platform and National Stock Exchange EMERGE (EMERGE is the NSE new initiative for SMEs to raise the funds from investors) in India. To test the moderating impact of the board monitoring role and resource provision role, the study employs hierarchical moderated regression subject to the fulfillment of assumptions.FindingsThe findings divulge that ownership concentration significantly reduces underpricing, hinting towards the operationalization of alignment of interest hypothesis. With regards to moderating relationship, the study found that while board resource providing role negatively moderates the relationship between ownership concentration and SME IPO underpricing, board monitoring function fails to cast any significant impact on the relationship between ownership concentration and SME IPO underpricing.Research limitations/implicationsThe present study ignores larger firms listed on the main platform which have complex decision-making than smaller firms. Besides, it is confined to only a single country, i.e. India. Extending the study to other countries with similar institutional characteristics would have validated the findings. Furthermore, the moderating impact of other organizational factors like firm age, lifecycle of firm and change in technology would form an interesting avenue for future research.Practical implicationsThe findings of the study have practical implications for managers in designing the adequate board structure that significantly reduces underpricing. It thus further advices the issuers on focusing more on strengthening the resource provision role of board of directors for achieving higher rewards. The findings are helpful to policymakers in framing such policies that enhance the resource-oriented role of board of directors and resource accessibility for SMEs. Furthermore, the results advise the investors to be relatively assured about the SMEs whose board exercises its resource provision role emphatically. Accordingly, findings are helpful to investors in making investment decisions in alternative market settings characterized by the concentrated ownership structure.Originality/valueThe study furthers the debate on the importance of two prominent roles played by board as a moderating variable in the underexplored context of IPO underpricing of small and medium-sized firms in India.

Understanding the Effect of Climate Risk on Banking Business—A Panel Data Analysis of Indian Firms

The enormous phenomenon of climate change, which is affecting many organisations of different sectors today, has a special impact on the financial sector in terms of credit risk. Awareness and action on environmental, social and governance (ESG) goals and climate change impacts have been rapidly increasing worldwide. In this article, we present a firm-level panel data analysis to link ESG ratings and CO2 emissions with the default risk and solvency position of selected companies. We perform various univariate and multivariate analyses on selected top Bombay Stock Exchange (BSE) top 200 companies that have disclosures in Carbon Disclosure Project (CDP) reports over 5 years (2017–2021). We find strong empirical evidence that a firm’s risk of default is linked to its environmental performance along with the level of carbon emission. Our findings will enable banks to establish a linkage between credit risk and climate change risk. This will assist banks as well as policymakers to adjust borrower-level ratings and align their lending and investments with net zero emissions. JEL Codes: G32, G33, Q2, Q5

Stock Market Prediction using Machine Learning Techniques

Generally, the stock market index oscillating over the time periodand influencingmany factors. Different stock market indices determined from various mixture of stock may share similar trend in certain. The purpose of this research to predict market price index of Bombay Stock Exchange (BSE) on day wise closing using machine learning technique. The machine learning techniques ANN (Artificial Neural Network)including feedforward with lagged values of the as input, and Support Vector Machine (SVM) are compared. The price index was found to be most relevant and influenced the market performance. The results showed that performance of BSE index can be predicted with machine learningapproach. The machine learning approach shown ANN model better performance than the SVM model. The Mean Absolute Percentage Error (MAPE) of ANN is 0.5790 and the Root Mean Square Error (RMSE) is 472.12.

Free Cash Flows and Corporate Buybacks: A Study of Indian Firms

The present research examined the effects of cash flow volatility on the buyback decisions of Indian firms. The sample constitutes 179 Indian companies listed on the Bombay Stock Exchange from 2012-2020. Firms have been divided into two sets, i.e., permanent and volatile cash flow firms. Across these two sets, the study determines the major factors affecting their buyback decisions. The results of ordinary least square regression suggested that when firms have fluctuating cash flows each year, they prefer to opt for repurchases than dividend payments. Further, stock undervaluation is the key determinant of repurchases decisions. Thus, firms with constant cash flows are not highly motivated for buyback decisions. Further, the study explored that larger the size of the firm, lower is the tendency to repurchase shares. Large, manufacturing and mature firms with consistent cash funds are more strongly tended towards repurchases. Correspondingly, such companies engaged in buybacks because of their low market-to-book ratios and high information asymmetry. As cash based firms become more old, their propensity to purchase equity reduces.

Why do Indian exporting firms borrow in foreign currency?

Purpose Since the liberalization policy of 1991, India has focused on export-led growth. However, the performance of international trade remains poor. This study aims to examine the role of credit constraints on the choice of Indian manufacturing firms to borrow in foreign currency. First, it explores the role of export activities in foreign currency borrowing (FCB). Second, it investigates how credit constraints forced these firms for foreign currency loans. Design/methodology/approach The study analysed data from 1,412 firms listed on the Bombay Stock Exchange in the manufacturing sector, covering the period from 1991 to 2022. A random effects probit model was used to examine the role of credit constraints on FCB, incorporating the influence of micro, small and medium enterprises (MSMEs) status and export activities. Additionally, a two-step system-generalized method of moment was used for robustness checks. Findings Export activities significantly influence FCB, with exporting firms showing a higher propensity to borrow foreign currency compared to domestically operating firms because of the increased funding needs of export activities. Larger firms are more likely to secure FCB than MSMEs, benefiting from collateral advantages. MSME exporting firms exhibit a higher tendency to borrow in foreign currency compared to large exporting firms. Research limitations/implications This study focuses on firm-level data and considers only demand-side credit constraints. It does not examine supply-side credit constraints affecting FCB. Social implications This study underscores the credit constraints faced by MSME exporters in the domestic market, leading them to rely on FCB. These insights are valuable for policymakers aiming to reduce MSMEs' dependency on FCB and enhance their export performance. Originality/value The findings highlight that MSME exporting firms are more inclined to borrow in foreign currency than their larger counterparts. This tendency is driven by the credit constraints MSMEs face because of asymmetric information and underdeveloped financial markets, which compel them to seek FCB.

Economic policy uncertainty and Indian equity sectors: a quantile regression approach

PurposeThis paper aims to investigate the effect of economic policy uncertainty (EPU) shocks on Indian equity market sectors. The effect of domestic (Indian) and foreign (USA) EPU shocks is examined on ten major Bombay Stock Exchange sectors.Design/methodology/approachThe study uses data covering the period from September 2005 to July 2023 and uses the methodology of quantile regression to investigate the heterogenous response of stock market sectors under diverse market conditions explained through the analysis of conditional quantiles distribution.FindingsThe results demonstrate that domestic and foreign EPU shocks negatively affect most of the sectors in bearish market conditions. Industrials, commodities, utilities, consumer discretionary and financial services are the most affected sectors by domestic EPU. However, the information technology sector is found to be immune to domestic EPU shocks but negatively affected by foreign EPU shocks. On the other hand, energy, financial services and fast-moving consumer goods sectors are found to be immune to foreign EPU shocks but are negatively affected by domestic EPU shocks.Practical implicationsUnderstanding the heterogeneous response of different sectors to EPU shocks could help investors and portfolio managers identify portfolio diversification opportunities.Originality/valueThis study makes an inaugural attempt to examine the responses of Indian stock market sectors to domestic and foreign EPU shocks using the approach of quantile regression and unveils the previously unexamined diverse reactions of Indian stock market sectors to EPU shocks originating from both India and USA.

HOW DO DIFFERENT DEBT LEVELS INFLUENCE THE FINANCIAL PERFORMANCE OF FMCG COMPANIES IN INDIA?

This study examines the impact of capital structure on the financial performance of Fast-Moving Consumer Goods (FMCG) companies listed on the Bombay Stock Exchange (BSE) from 2011 to 2021. It focuses on how varying levels of short-term, long-term, and total debt influence key financial metrics such as Return on Assets (ROA), Return on Equity (ROE), Earnings Per Share (EPS), and Tobin’s Q. Using regression models with panel data, the research evaluates the relationship between debt ratios and financial performance, utilizing both fixed and random effects models. The findings reveal that higher levels of debt, especially long-term debt, negatively impact financial performance. Short-term debt is more commonly used in the FMCG sector, but overall, debt tends to reduce profitability and shareholder value. Notably, Earnings Per Share (EPS) had the highest average among the performance indicators, though all debt ratios demonstrated significant negative correlations with ROA, ROE, EPS, and Tobin’s Q. The study also highlights that larger and older firms are more effective at managing the negative effects of debt, performing better financially than smaller or younger firms. It recommends that FMCG companies prioritize internal funding over debt, as high debt levels can lead to financial strain. Future research could explore the impact of capital structure in other industries or include macroeconomic factors.

Boom or bust? A Comparative Analysis of Monetary Policy and Stock Market Performance in India Across Economic Cycles

This study delves into the intricate relationship between monetary policy instruments and various sectors of the Indian stock market from 2011 to 2022. By Analyzing data encompassing significant policy shifts and economic events, including the Reserve Bank of India's (RBI) transition towards inflation targeting and flexible exchange rates, the study aims to uncover the nuanced impacts of monetary policy on sectoral indices. Utilizing a Vector Autoregression (VAR) model, the study examines the dynamic interplay between key monetary policy instruments—Cash Reserve Ratio (CRR), Marginal Standing Facility Rate (MSF), Repo Rate, Reverse Repo Rate, and Treasury Bills—and ten diverse sectors represented in the Bombay Stock Exchange (BSE) indices. The findings reveal intricate sectorspecific responses to monetary policy adjustments, reflecting the complex interplay of economic dynamics and policy measures. While some sectors exhibit positive correlations with certain monetary instruments, others display negative associations, underscoring the diverse impacts of monetary policy on sectoral performance. The study highlights the significance of understanding these nuanced relationships for policymakers, investors, and market participants in navigating India's evolving economic landscape.

IMPACT OF COP26 ON INDIAN STOCK INDICES: AN EVENT STUDY APPROACH

The study aims at measuring impact of Indian government commitment on ESG100 index and BSE Manufacturing Index of Bombay Stock Exchange. The study uses the Event sturdy approach to compare pre-event and post-event Abnormal return and cumulative abnormal return. The Bootstrapping and Wilcoxon tests has been used for comparison. There is no significant difference found in abnormal return of both of the index. Mean adjusted cumulative abnormal return of both of the index es has significant differences. In BSE ESG100 index, Market adjusted cumulative abnormal return has no significant difference. In BSE Manufacturing index, Mean adjusted cumulative abnormal return has significant difference. The carbon neutrality deadline is long away, so Indian investors do not consider CoP26 seriously.

Indirect Tax Reform And Market Efficiency: An Empirical Study of Indian Stock Market

The biggest tax reform of the Indian Government in this present decade is the Goods and Services Tax (GST), which was passed in parliament on 8th September 2016 and was enforced from 1st July 2017. Eight years of data from the Bombay Stock Exchange Sensex and the National Stock Exchange Nifty50 index is studied. The data is divided into two sub-periods before GST was passed from parliament period - I and after GST was passed from the parliament of India period - II. The study intends to test the market efficiency in its weak form. To check the time series data for normality, stationarity, random walk, and autocorrelation function, Kolmogorov-Smirnov (KS) test, Augmented Dickey-Fuller (ADF) test, Phillips Perron (PP) test is used for the analyse of the time-series data. The study found that returns are not normally distributed and the market is inefficient in a weak form for both periods under study.

RELATIONSHIP BETWEEN COMMODITIES MARKET AND STOCK MARKETS EVIDENCE FROM MALAYSIA AND CHINA

The stock-commodity link affects market participants, commodity producers, policymakers, and, in emerging nations, the entire economy. The lead-lag relationship between market representative indices can be studied using many methodologies. This initiative examines the Indian stock-commodity market interaction. This project will leverage secondary data from the National Stock Exchange, Multi Commodity Exchange of India Limited, and Bombay Stock Exchange websites. Project results can be used to create an investment plan. Thus, market participants must draw crucial inferences or discover important relationships between the Indian Stock Market and Commodity Market. Statement of the Problem Market players and investors face difficult portfolio decisions. People struggle to choose stocks and commodities like gold, copper, etc. Due to a lack of credible market data on the Indian Stock Market-Commodity Market connection. The lack of research on the Indian stock-commodity market link is the issue. Such a study is needed, using some of the top marketplace contributors as examples.The project's results should help regulators and market participants understand the problem and adopt appropriate laws, rules, policies, and methods. Investors and individuals have confirmed the issue. .Objectives of the Study The following objectives are the focus of the project study. · To make important inferences about the way the Indian Stock Market and Commodity Market interact; · to ascertain the type, scope, and direction of the link between the Indian Commodity Market and the Indian Stock Market.

Spillover Effect Due to Macroeconomic Variables: Evidence from Volatility in BRICS Nations

Purpose: The aim of this study is to examine the spillover effect of volatility in macroeconomic variables on indices of emerging nations. Theoretical Framework: This research considered macroeconomic variables such as GDP, FDI, Inflation, and money supply and indices of emerging nations (Brazil, Russia, India, China and South Africa). This paper focuses on identifying how stock markets of BRICS are affected by variations in macroeconomic variables. Design/Methodology/ Approach: The data on GDP, inflation rate, FDI, Money Supply, and Indices (Chinese BOVESPA, Russian, Indian Bombay Stock Exchange, Chinese Shanghai Stock Exchange (SSE) Composite Index, and South African FTSE) was drawn for a period of 20 years from 2001 to 2021. Prices of the indices were acquired from www.investing.com. Macroeconomic indicators data was taken from the www.worldbank.org. For analysis, the VECM and VAR models are prepared. Findings: The findings show that all the economic variables are considerably leaving a spillover impact on the prices of BRICS nations. VECM models state relationship among the GDP, FDI, Inflation, and money supply and Stock markets of Brazil, Russia, India, and China. However, in the case of South Africa, these economic variables have a dynamic correlation with its stock market index as is depicted through the VAR Model. Research Practical and Social implications: The study addresses the issue of spillover effect of factors which had indirect impact on the volatility of the indices of BRICS nations. In the times of such high level of uncertainties like covid pandemic it is important to understand the direct and indirect factors and variables which may impact the variability of the stock markets. Originality/Value: This articles has conducted an extensive analyses of macroeconomic variables and their impact on indices of emerging nations. The authors provides clarity and insights in understanding the variability in markets in depth.

From Monolith to Market: Exploring IPO Issue and Market Potential of LIC of India

Insurance industry is one of the prominent sectors in India to maintain stability and enhancement of social security for efficiently building our nation's economy. The Insurance Regulatory and Development Authority of India (IRDAI) regulates a total of 57 Indian insurance companies, in which LIC is the largest and most established public utility company that covers a wide range of portfolio opportunities withholding trust and reliability of policyholders for country’s GDP development. This study is a descriptive analysis of the journey of LIC IPO, which began trading from May 17, 2022 by being listed in both Bombay Stock Exchange (BSE) and the National Stock Exchange (NSE). The IPO witnessed an overwhelming response from all categories of investors and resulted in 2.95 times oversubscriptions. Further, it shows a very stable equity market value in both the Exchanges while crossing thousand rupees during the latter part of the financial year 2023-24.

Value and quality investing strategy in Indian stock market

PurposeThe objective of the study is to shed light on the notion of quality investing in the Indian stock market. The study also attempts to combine the value and quality metrics to test their ability to generate a higher risk-adjusted return.Design/methodology/approachThe paper employs asset pricing models to examine the excess risk-adjusted returns and panel regression model (random estimates) to determine the price of quality in the cross-section of Bombay Stock Exchange (BSE) listed stocks from 2003 to 2020.FindingsThe results indicate that the quality-only strategy failed to produce substantial risk-adjusted returns in the Indian stock market. The returns to long/short hedging strategy quality-minus-junk (QMJ) are significantly positive with the majority of the returns attributable to the short leg of the stock portfolio. The findings further discovered that the explanatory effect of quality on prices is limited. In particular, a strategy that combines value and quality investing generated positive and significant alphas as well as a higher Sharpe ratio.Practical implicationsThe study provides investors and portfolio managers with valuable insights for navigating undervalued high-quality equities in the Indian stock market.Originality/valueThis is the first research of its kind to examine the performance of quality (Q score indicator) combined with value investing in the Indian stock market. As majority of research have concentrated on developed economies, this study offers out-of-sample evidence to validate the strategy’s success in an emerging market.