Faculty Publications
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Item Exchange Rate Exposure and Usage of Foreign Currency Derivatives by Indian Nonfinancial Firms(Springer Science and Business Media B.V., 2018) Prasad, K.; Suprabha, K.R.This paper investigates the usage of currency derivatives and its impact on the exchange rate exposure. A sample of 387 nonfinancial Indian firms listed in the National Stock Exchange of India were studied for a period of 5 years from 2011–2012 to 2015–2016. The currency derivatives data was collected from the annual reports of the sample firms, and the stock price data was collected from Ace Equity and Centre for Monitoring Indian Economy (CMIE) database Prowess. The results of the study indicate that the currency forward contract is the most preferred hedging instrument among the sample firms. The Indian firms showed the lower interest in exchange-traded instruments especially currency futures. This is in spite of the growth in the third-generation innovative and low-cost derivative instruments. This study also provided evidence that hedging using currency derivatives decreased the firms’ foreign exchange exposure level, while the use of foreign currency borrowing was found insignificant in decreasing the firm’s level of currency exposure. © 2018, Springer International Publishing AG.Item Modeling hybrid indicators for stock index prediction(Springer Verlag service@springer.de, 2020) Arjun, R.; Suprabha, K.R.The study aims to assess the major predictors of stock index closing using select set of technical and fundamental indicators from market data. Here two of major service sector specific indices of Bombay stock exchange (BSE) and National stock exchange (NSE) with historical data from 2004 up to 2016 are considered. By experimental simulation, the predictive estimates of index closing using automatic linear modeling, time-series based forecasting, and also artificial neural network models are analyzed. While linear models show better performance for BSE, artificial neural network based models exhibit higher predictive modeling accuracy for NSE. The design aspects are outlined for augmenting intelligent market prediction systems. © Springer Nature Switzerland AG 2020.Item Deep Learning for Stock Index Tracking: Bank Sector Case(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2021) Arjun, R.; Suprabha, K.R.; Majhi, R.The current study explores the efficacy of deep learning models in stock market prediction specific to banking sector. The secondary data of major fundamental indicators and technical variables during 2004–2019 periods of two banking indices, BSE BANKEX and NIFTY Bank of Bombay stock exchange and National stock exchange, respectively, are collected. The factors impacting market index prices were analyzed using nonlinear autoregressive neural network. Preliminary findings contradict the general random walk hypothesis theory and model improvement over previous studies. The implications from practical and theoretical perspective for stakeholders are discussed. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Impact of Contextual Factors on Adaptive Performance: A Study on Indian PSBs Using ANN Analysis(Springer Science and Business Media Deutschland GmbH, 2025) Shetty, D.S.; Suprabha, K.R.The Indian Public Sector Banks (PSBs) are at the cusp of significant structural changes and technological shifts. These radical changes have enormously altered the world of work by endlessly spinning due to the environment’s volatility, uncertainty, complexity, and ambiguity (VUCA). The maladaptive conditions created during these circumstances have increased the need for employees with stronger and steadier adaptive performance. Human capital is the asset of any organisation; thus, attracting, retaining, and maintaining these assets becomes the focal function of financial institutions like banks. Training and development activities are ongoing and crucial organizational processes to manage talents. The vitality of these activities is easily traceable in the institute’s growth graph. Thus, identifying the contextual competencies and training the employees to enhance these competencies is a challenge to any organization. This study proposes the application of Artificial Neural Network (ANN) as a tool to explore the competency in demand during disruptions in the Indian public sector banks. The use of ANN in accruing answers to research questions about employee competency management to enhance adaptive performance is a rare and inevitable study while dealing with disruptions in the banking sector. This study investigates the influence of Work Autonomy (WA), Emotional Stability (ES), Workplace Spirituality (WS), and Career Adaptability (CA) on Adaptive Performance (AP). The current study results are convincingly satisfactory and are very close to the Structural Equational Modelling (SEM) outcomes when compared with the same. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Item Influence of financial distress on exchange rate exposure: Evidence from India(Inderscience Publishers, 2018) Prasad, K.; Suprabha, K.R.; Devji, S.This paper investigates the relationship between exchange rate exposure and level of financial distress. We argue that the exchange rate movements have a higher effect on the value of the firms with higher level of financial distress. The effect of other firm level variables such as profitability, size of the firm, foreign sales and expenses and liquidity on exchange rate exposure were also studied. We use Merton's (1974) structural default model to estimate firms' distance to default as a proxy for their probability of financial distress. A sample 387 firms listed in National Stock Exchange (NSE) is studied for a period of 2012-2016. We find that the level of firms' exchange rate exposure is significantly positively related to distance to default, indicating that firms that have a greater probability of financial distress are more affected by exchange rate movements. © © 2018 Inderscience Enterprises Ltd.Item Forecasting banking sectors in Indian stock markets using machine intelligence(IOS Press BV, 2019) Arjun, R.; Suprabha, K.R.The study analyze stock index closing from myriad set of technical and fundamental analysis variables extracted from real market data to assist forecast of market closing. For this, major service sector indices of Bombay stock exchange (BSE) and National stock exchange (NSE) with historical data were taken from banking industry. The predictive model performance of index closing using statistical procedures like automatic linear modeling, time-series based econometric forecasting, vector auto regression as with artificial neural network based models were simulated and analyzed. The results indicate that BSE had higher forecast accuracy using autoregressive models and market volatility factor had major influence. Whereas, NSE was impacted by quarterly performance that can be modeled using neural networks. The empirical results were contrasted with latest state-of-art research theories to provide agenda and future research challenges of market forecast systems. © 2019 - IOS Press and the authors. All rights reserved.Item Innovation and challenges of blockchain in banking: A scientometric view(Universidad Internacional de la Rioja, 2020) Arjun, R.; Suprabha, K.R.Blockchain has been gaining focus in research and development for diverse industries in recent years. Nevertheless, innovations that impact to the banking nurture a potential for disruptive impact globally for economic reasons; however it has received less scholarly attention. Hence the effect of blockchain technologies on banking industry is systematically reviewed. The relevant literature is extracted from Scopus, Web of Science and bibliometric techniques are applied. While a bulk of earlier papers focuses only on bit coins, a broader framework is envisaged that synthesizes interdisciplinary thematic areas for advancement; hence novelty in current work. A few practical and theoretical implications for stakeholders in view of technology, law and management are discussed. © 2020, Universidad Internacional de la Rioja. All rights reserved.Item Does GRI compliance moderate the impact of sustainability disclosure on firm value?(Emerald Publishing, 2023) Sreepriya, J.; Suprabha, K.R.; Prasad, K.Purpose: This paper aims to examine the moderating role of global reporting initiative (GRI) compliance in the association between sustainability reporting and firm value. Design/methodology/approach: This study investigates a sample of 223 manufacturing firms, encompassing 11 industries from 2010 to 2019. Using GRI compliance as a moderator, the authors employed a generalized method of moments model to study how sustainability disclosure impacts firm value. Findings: The results indicate a positive and significant association between sustainability disclosure and firm value. This study reveals that GRI compliance moderates the relationship between sustainability disclosure and firm value, such that firm value increases when the firm adopts GRI in sustainability reporting. Originality/value: No prior studies have examined GRI compliance's direct and moderating effects on the association between sustainability disclosures and firm value in the Indian manufacturing sector. This study is also valuable for the managers and industry to understand the significance of implementing voluntary sustainability disclosure practices and being GRI compliant. © 2022, Emerald Publishing Limited.Item ‘CSR, sustainability and firm performance linkage’ current status and future dimensions – a bibliometric review analysis(Inderscience Publishers, 2024) Sreepriya, J.; Suprabha, K.R.Corporate social responsibility (CSR) and sustainability are gaining worldwide recognition. The question of whether CSR and sustainability programs benefit an organisation’s financial success is still being debated. This study aims to verify this phenomenon by examining the current literature pattern on this relationship using bibliometric and systematic review analysis. It further provides a taxonomy for understanding this association. VOSviewer is used to obtain comprehensive dataset mapping and clustering in the field. The manuscript offers promising insights regarding academia by assessing the pattern of publication trends, the most influential author in the area, and analysing the methodological and theoretical underpinnings of CSR, sustainability and firm performance linkage. The outcome of this study provides exploratory insights into research gaps and avenues for future research. © © 2024 Inderscience Enterprises Ltd.Item The impact of ESG disclosure on mitigating financial distress: exploring the moderating role of firm life cycle(Palgrave Macmillan, 2025) Suprabha, K.R.; Sreepriya, J.; Prasad, K.Globally, businesses are increasingly gaining recognition for their non-financial performance due to heightened stakeholder demands about ethical and environmental responsibilities. This noteworthy shift in perspective has catalyzed the inception of this research, which seeks to scrutinize the influence of environmental, social, and governance disclosure (ESGD) on financial distress. To investigate the potential capacity of ESGD in mitigating financial distress, the researchers have employed the Generalized Method of Moments. Additionally, the study takes into account the moderating role played by the firm’s life cycle in this relationship. The findings underscore that the adoption of ESGD is associated with a decreased likelihood of default, thus highlighting its effectiveness as a risk management strategy. Moreover, this investigation emphasizes the impact of the firm’s life cycle on the link between ESGD and corporate financial distress. Rooted in signalling theory as the theoretical framework, the research posits that a wide spectrum of Environmental, Social, and Governance (ESG) initiatives not only enhances the consistency of signals but also amplifies the associated signal costs. Consequently, in alignment with this theoretical perspective and substantiated by empirical evidence, our study confirms a multifaceted influence of ESGD on financial distress, contingent upon the distinctive phases of a firm's life cycle. In consequence, this study offers valuable insights for managerial decision-making, guiding the development of tailored disclosure policies that align with the specific characteristics of a firm’s life cycle. © The Author(s), under exclusive licence to Springer Nature Limited 2024.