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Impact of Macroeconomic Integration in Hybrid GARCH-GRU Volatility Modelling on Nifty Bank
In countries like India, where banking systems are closely tied to macroeconomic swings, being able to forecast volatility is critical for managing financial risk. Sudden changes in interest rates, exchange movements, or growth expectations can unsettle banks much faster than in mature markets. Econometric tools such as the Generalised Autoregressive Conditional Heteroskedasticity (GARCH) model remain popular because they capture volatility clustering well, but they fall short when the data exhibit nonlinear patterns. Neural networks-particularly Gated Recurrent Units (GRUs)-handle time-series dynamics more effectively, though they tend to miss traits specific to financial volatility. In this work, we put forward a hybrid GARCH-GRU framework that blends the traditional strengths of econometric models with the pattern-learning ability of neural networks, while also folding in key macroeconomic indicators. The framework is applied to the Nifty Bank index and draws on daily records spanning March 2010 to December 2022. Altogether, the dataset includes just over three thousand observations, covering more than a decade of varied market conditions. The framework uses a two-step design: conditional volatility from a GJR-GARCH(1,1) model is first estimated and then used as input, along with macroeconomic variables such as repo rates, exchange rates (USD/INR, CNY/INR, EUR/INR), oil prices, and GDP growth, for the GRU network. Our results indicate that the hybrid model performs noticeably better, cutting the Mean Absolute Error by about a quarter. The error falls from 0.000263 in the baseline GARCH model to 0.000199 under the hybrid design. Among the different factors considered, movements in exchange rates and changes in repo rates stand out most strongly, showing how these macroeconomic signals feed directly into risk management for Indian banks. 2025 IEEE. -
Impact of Macroeconomic Uncertainty on Stock Market Return Volatility in India : Evidence from Vector Autoregressive (VAR) Analysis
Pacific Business Review International Vol. 5, Issue 4, pp. 50-62, ISSN No. 0974-438X -
Impact of macroeconomic variables on the prices of gold /
Journal of Emerging Technologies And Innovative, Vol.6, Issue 2, pp.569-576, ISSN No: 2349-5162. -
Impact of macroeconomic variables on the stock performance of select companies in manufacturing industry
The efficient functioning of a stock market is influenced by different macro economic factors like Inflation, Interest rates, exchange rate etc. The favourable Macro Economic Variables both domestic economy and global economy inspire the organisations to go for strategic investment activities in domestic and global markets and reflect positively on the company financial performance and firms fundamentals like Revenues, Operating margins, Earnings Per Share, the Economic Value , Market value, and the Firms overall Value. These positive indicators in the fundamentals of the firms send positive signals into stock markets and generate positive perceptions about the company's stock prices in the market. Markets become so attractive to domestic and foreign investors which drive the share price of different companies , specially Blue chips upwards and creates value to the shareholders .According to the study organized the impact of macro economic variables is not uniform and the impact varies betweem various macro economic variables on the stock market performance. Serials Publications Pvt. Ltd. -
Impact of macroeconomic variables on the stock performance of select companies in manufacturing industry /
International Journal Of Economic Research, Vol.14(8), pp.321-328, ISSN: 0972-9380. -
Impact of Mahatma Gandhi National Rural Employment Guarantee Act on Rural Credit System in India: A Standard Logit Difference in Difference Approach
The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) of India is one of the most extensive social safety nets programs in the developing world. The initiative attempts to enhance rural livelihoods in India by lowering rural poor vulnerability and misery. The programs nature and extent of execution vary from state to state. Using panel data sets from the Indian Human Development Survey (IHDS), which covering India for two waves, 200405 and 201112. We used a quasi-experimental approach, such as the difference-in-difference technique of effect evaluation, to quantify the programs influence on rural families credit and debt structures. The empirical analysis shows evidence of changing the behavior of taking loans from formal sources among non-poor households actively participating in the MGNREGA program. But the difference-in-difference results shows that among poor households participating in the MGNREGA scheme, the tendency to depend on formal sources to take loans is still insignificant. That means informal lending sources are still more prevalent among poor people. This tendency has not changed even after the initiation of this program. The article finishes with policy recommendations for successfully targeting the program, notably the social safety net benefits to disadvantaged households in India. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Impact of Meltdown and Spectre Threats in Parallel Processing
Threat characterization is critical for associations, as it is an imperative move towards execution of data security. Vast majority of the current threat characterizations recorded threats in static courses without connecting risks to information system zones. The aim of this paper is to represent each threat in different areas of the information system the methodology to solve the problem. Data security is habitually represented to different kinds of threats which may cause distinctive types of harms that can prompt to critical monetary losses. Data security problems can go from small losses to entire data framework destruction. The effect of various threats vary extensively: some manipulate the integrity or confidentiality of information while others manipulate the accessibility of a framework. At present, associations are trying to comprehend what are the threats to their data resources are and what are the ways to get the significant intends to combat them which keep on representing a challenge. Springer Nature Switzerland AG 2020. -
Impact of Meltdown and Spectre Threats in Parallel Processing
[No abstract available] -
Impact of meme marketing on consumer purchase intention: Examining the mediating role of consumer engagement
This paper analyzes an emerging form of social media marketing, meme marketing, which has gained attention for its ability to entertain and engage users. Marketers and companies are recognizing the value of using memes as a tool to connect with consumers. To understand the effects of meme marketing activities, this paper aims to examine the impact of meme marketing activities on consumer purchase intentions and concurrently assess the mediating role of consumer engagement. The study encompassed 452 Indian social media users with active social media accounts and familiarity with memes and meme marketing concepts. It employed a quantitative methodology backed by robust statistical techniques. The method used for analysis was Structural Equation Modeling (SEM) through Analysis of Moment Structures (AMOS) software. The results found that meme marketing activities have a direct and significant positive impact (? = 0.257, p < 0.05) on consumer purchase intentions. It further shows that meme marketing has a direct and significant positive impact (? = 0.745, p < 0.05) on consumer engagement. It shows that consumer engagement has a direct and significant positive effect (? = 0.651, p < 0.05) on consumer purchase intention. However, the indirect impact of meme marketing activities on consumer purchase intentions is also significant, resulting in partial mediation. The study findings hold value for marketing managers, agencies, and companies that interact and engage consumers with memes and undertake meme marketing activities. Navrang Rathi, Pooja Jain, 2023. -
Impact of monetary policy changes on the Indian stock market and monetary market
Since the stock market is perceived as the channel of transmissions of monetary policy, it is worthy to study the relationship between the Monetary Policy and the volatility of stock prices in the stock market. This study has been conducted with the aim to examine the impact of monetary policy changes on the stock market. The variance methodology is applied in order to achieve the objective of this study. The concept of event window in the methodology involved as the identification of volatility of price in the stock market for11 days (i.e. 5 days before and after event day). The result shows that there is a positive influence on stock market because of change in money policy by the government. The results identified in this work having a signification amount of managerial implication to the different segment of the policy makers in Government, and Stock Market. 2019 Islamic Azad University. -
Impact of moral and exchange capital on media favourability of financial companies in India
Purpose The purpose of this study is to illuminate the influence of institutional and transactional corporate social responsibility (CSR) on media sentiments in financial companies in India. This study is conducted to understand how different CSR strategies impact media perceptions, influencing the reputation and public image of financial companies in India. Design/methodology/approach This study examines the data of 56 National Stock Exchange-listed financial companies for eight years of data from 20142015 to 20212022. Panel data regression were used to analyse the data; fixed and random effect models were chosen based on the Hausman test results. Findings Financial companies moral and exchange capital negatively impact the medias favourability of financial companies in India. Diagnostic tests like autocorrelation and heteroscedasticity are also conducted to check the effectiveness of research models. Originality/value Although prior research has examined the effect of CSR on media sentiments, little is known about the impact of moral capital and exchange capital on media favourability of financial companies in India. 2025 Emerald Publishing Limited -
Impact of Multi-domain Features for EEG Based Epileptic Seizures Classification
Accurate detection and classification of epileptic seizures play a pivotal role in clinical diagnosis and treatment. This study introduces an innovative approach that leverages multi-domain features extracted from Electroencephalogram (EEG) data in conjunction with Supervised learning classification techniques. Initially, EEG data undergoes preprocessing through data standardization, followed by the extraction of essential features per instance, encompassing combination of Time domain, Frequency domain, and Time-Frequency domain features. These extracted feature combinations are subsequently fed into the machine learning-based boosting classifier Adaptive Boosting (ADABOOST) for an accurate and precise classification of epileptic signals. Validation of the proposed method is conducted using EEG data from the BEED (Bangalore EEG Epilepsy Dataset) and BONN (University of BONN, Germany) database to detect epileptic seizures. The experimental results show remarkably high levels of classification accuracy for various conditions: 99% accuracy for BEED data, 98% accuracy for BONN data for classifying seizures from healthy states, and 91% accuracy for classifying seizure onset from seizure events. Furthermore, the study applies the Gaussian Nae Bayes (GNB) classifier to differentiate various types of epileptic seizures, employing evaluation metrics such as the confusion matrix, ROC curve, and diverse performance measures. This method demonstrates significant potential in supporting experienced neurophysiologists decision in the clinical classification of epileptic seizure types. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Impact of nanoparticles on immune cells and their potential applications in cancer immunotherapy
Nanoparticles represent a heterogeneous collection of materials, whether natural or synthetic, with dimensions aligning in the nanoscale. Because of their intense manifestation with the immune system, they can be harvested for numerous bio-medical and biotechnological advancements mainly in cancer treatment. This review article aims to scrutinize various types of nanoparticles that interact differently with immune cells like macrophages, dendritic cells, T lymphocytes, and natural killer (NK) cells. It also underscores the importance of knowing how nanoparticles influence immune cell functions, such as the production of cytokines and the presentation of antigens which are crucial for effective cancer immunotherapy. Hence overviews of bio-molecular mechanisms are provided. Nanoparticles can improve antigen presentation, boost T-cell responses, and overcome the immunosuppressive tumor environment. The regulatory mechanisms, signaling pathways, and nanoparticle characteristics are also presented for a comprehensive understanding. We review the nanotechnology platform options and challenges in nanoparticles-based immunotherapy, from an immunotherapy perspective including precise targeting, immune modulation, and potential toxicity, as well as personalized approaches based on individual patient and tumor characteristics. The development of emerging multifunctional nanoparticles and theranostic nanoparticles will provide new solutions for the precision and efficiency of cancer therapies in next-generation practice. Copyright 2024 The Authors. -
Impact of national income and public expenditure on employment and its public-private sector composition in indian economy
The paper focuses on the analysis of the impact of Gross National Income and Public Expenditure on total employment and its public and private sector components. It also examines the ratios of public and private sector employment to total employment and public sector to private sector employment. Results of summary statistics of employment, public and private sector employment, public expenditure, and gross national income are briefly discussed. Growth of total employment, public and private sector employment, gross national income and public expenditure is examined to determine the direction and magnitudes of inter-temporal changes. Growth trend of all three ratios is determined to detect and to anticipate the interrelations of change. Stationarity of time series of total employment, employment in public and private sectors, gross national income and public expenditure of Indian economy is evaluated by Random Walk Model and Dickey-Fuller test. Results show that the time series data of total, public and private sector employment approximate normal distribution with extremely low skewedness and concentration. The coefficients of variation of all 6 time series data are relatively very low. But the time series of GNI is non-stationary at 0.05 probability level, while time series of public expenditure displays negative trend. Negative change in private sector employment is determined by lagged private sector employment and private income/expenditure. Results of Engel-Granger test of co-integration show the variables to be well co-integrated in the chosen distributed lag models. 2021 DAV College. All rights reserved. -
Impact of Network Virtualization on Application Performance Metrics
The advent of network virtualization has redefined modern networking philosophies by allowing the partitioning of physical networks into virtual networks that are easily scalable, elastic, and efficient. The shift has been markedly critical to the function of applications in virtualized settings. This research examines the impact of network virtualization on key application performance indicators, including latency, throughput, packet loss, and resource utilization. The paper empirically assesses factors related to user experience and system performance by analyzing various virtualization technologies, including Software-Defined Networks (SDN), Network Functions Virtualization (NFV), and virtual overlay networks. The approach used entails deploying controlled benchmark applications on both virtualized and non-virtualized networks and measuring deviations from benchmark performance. Results indicate a strong correlation between the moderation of network performance overhead with virtualization and the presence of adaptive performance improvement schemes tailored to specific conditions. The efficiency of the hypervisor, placement of network functions, and orchestration policies significantly influence the responsiveness of the applications Additionally, the paper addresses the increasing scalability limitations of performance in cloud-native and edge-computing environments. There is a finding that indicates increased need for research 'effective intelligent resource management and adaptive network reconfiguration strategies in order to minimize latency and redundant bandwidth allocation bottlenecks'. 2025, Innovative Information Science and Technology Research Group. All rights reserved. -
Impact of New CSR Bill on Indian Standard & Poor 50
Research Revolution, Vol-1 (3), pp. 1-4. -
Impact of NiO/CuO as additives on the pseudocapacitive performance of SiO2-GO composite: Insights from experimental investigation
Recent interest in pseudocapacitive materials faces challenges like degradation and high costs, while low-cost carbon materials suffer from low capacitance. SiO2-GO composites, despite their potential, remain unexplored for pseudocapacitors. The present study addresses this gap by focusing on the synthesis and characterization of SiO2-GO composites, both in their pure form and doped with NiO and/or CuO. These materials are subsequently investigated for their suitability as electrode materials in supercapacitor applications. The obtained results have been comprehensively analyzed with respect to the bonding interactions and morphological characteristics of each material variant. This analysis aims to elucidate how the incorporation of NiO and/or CuO influences the structural integrity, surface chemistry, and electrochemical performance of the SiO2-GO composites. By investigating these aspects, we aim to contribute new insights that could lead to the development of efficient and cost-effective pseudocapacitive electrode materials. 2024 Elsevier Ltd -
Impact of Node Failures on Productivity in Multilayer Supply Chain Networks: An Influence Network Analysis in the Indian Electronics Sector
Supply chain networks are essential for the delivery of goods and information, but disruptions such as natural disasters or trade embargoes can severely impact them. Resilience of entire networks under different types of disruptions when nodes or edges fail has been extensively studied. However, the extent to which the failure of a particular company affects another company of interest within a network has not been widely explored. To address this, we created a multilayer physical supply chain network of companies in the Indian electronics industry. Through systematic node removal simulations, we examined how the productivity of one company is impacted by the removal of another. Extending these simulations to include all possible combinations of companies yielded an influence network that represents interdependence among nodes in terms of productivity. We observed that removing a critical node could lead to not only a decrease but, quite counter-intuitively, an increase as well in the productivity of affected nodes. This study identifies the factors that influence these productivity changes and offers insights to supply chain managers to maintain network resilience in the face of node failures. 2025, Binghamton University Libraries. All rights reserved. -
Impact of ohmic heating on MHD mixed convection flow of Casson fluid by considering Cross diffusion effect
Present communication aims to discuss the impact of viscous dissipation on MHD flow, heat and mass transfer of Casson fluid over a plate by considering mixed convection. Nonlinear partial differential systems are reduced to the ordinary ones through transformation procedure. The modelled nonlinear systems are computed implementing RKF-45 scheme. Convergent solutions for velocity and temperature and concentration fields are given diagrammatically. The obtained results are compared with published literatures and reasonable agreement is found. It is found that, temperature profile increases by increasing values of Dufour parameter, whereas on opposite trend is observed in concentration profile for increasing values Soret parameter. 2019 B.J. Gireesha et al. -
Impact of online cooperative learning strategies on self-directed learning among pre-service teachers
Self-directed learning (SDL) often drives learners to engage with what they want to learn. Thus, investigating teaching-learning strategies that drive SDL gains importance in this technology-driven era. The present study investigates the impact of online cooperative learning (OCL) strategies on SDL skills among pre-service teachers (PST). The study engaged 130 PSTs using a quasi-experimental non-equivalent control group design with a pretest and posttest. The study divided PST into a control group and an experimental group. The experimental group underwent OCL strategy, and the control group had a traditional online lecture method. The researchers measured the SDL of PST using the SDL scale. The paired sample t-test results indicated a significant enhancement in SDL skills among the experimental group compared to the control group. The findings underscore the importance of integrating cooperative learning (CL) strategies in online instruction to foster SDL ability among learners. Further studies may create user-friendly features in video-conferencing platforms that provide more opportunities to engage students with CL pedagogies. 2025, Intelektual Pustaka Media Utama. All rights reserved.