Browse Items (5511 total)
Sort by:
-
Convergence of retail banking interest rates to households in euro area: time-varying measurement and determinants
This study measures time-varying progress of retail banking (to households) interest rates convergence and examines its determinants for twelve countries of the euro area, between 2003 and 2014. First, we measure convergence of interest rates using five different time-varying indicators, namely asymmetric dynamic conditional correlation (ADCC), beta convergence, sigma convergence, variance ratio, and dynamic cointegration. We then estimate panel regressions for each type of interest rate to identify the determinants of convergence over pre-crisis and crisis periods. The estimated ADCC is employed as the dependent variable and explanatory variables measure potential macroeconomic, external linkages, industry-specific, institutional and sociological determinants. The results reveal that convergence is weak and heterogeneous across sub-periods (pre-crisis and crisis), economic groups (core and periphery), product type (savings and credit) and products maturities (short, medium and long). Among the fundamental determinants, inflation, output correlation, and sociological factors strongly impact convergence, however, the explanatory power of determinants weakens during the crisis period. 2019, Springer-Verlag GmbH Germany, part of Springer Nature. -
Convergence of retail banking interest rates to households in euro area: Time-varying measurement and determinants /
International Economics and Economic Policy, Vol.17, Issue 1, pp.25-65 -
Conversion of alkynes into 1,2-diketones using HFIP as sacrificial hydrogen donor and DMSO as dihydroxylating agent
A metal-free and hypervalent iodine free conversion of internal alkynes into 1,2-diketo compounds has been described. The efficacy of the present protocol rely on the use of HFIP (1,1,1,3,3,3-Hexafluoro-2-propanol) as reducing agent of alkynes and DMSO as dihydroxylating agent of olefins to acquire the desired chemical transformations. The obtained 1,2-diketones were further transformed into useful derivatives. 2020 Elsevier Ltd -
Convolutional neural network for stock trading using technical indicators
Stock market prediction is a very hot topic in financial world. Successful prediction of stock market movement may promise high profits. However, an accurate prediction of stock movement is a highly complicated and very difficult task because there are many factors that may affect the stock price such as global economy, politics, investor expectation and others. Several non-linear models such as Artificial Neural Network, fuzzy systems and hybrid models are being used for forecasting stock market. These models have limitations like slow convergence and overfitting problem. To solve the aforementioned issues, this paper intends to develop a robust stock trading model using deep learning network. In this paper, a stock trading model by integrating Technical Indicators and Convolutional Neural Network (TI-CNN) is developed and implemented. The stock data investigated in this work were collected from publicly available sources. Ten technical indicators are extracted from the historical data and taken as feature vectors. Subsequently, feature vectors are converted into an image using Gramian Angular Field and fed as an input to the CNN. Closing price of stock data are manually labelled as sell, buy, and hold points by determining the top and bottom points in a sliding window. The duration considered over a period from January 2009 to December 2018. Prediction ability of the developed TI-CNN model is tested on NASDAQ and NYSE data. Performance indicators such as accuracy and F1 score are calculated and compared to prove effectiveness of the proposed stock trading model. Experimental results demonstrate that the proposed TI-CNN achieves high prediction accuracy than that of the earlier models considered for comparison. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Cooperation affects NGO staff performance patterns
In order to optimise employee productivity and overall profitability, non-profits must invest heavily in their human resources. Contrarily, the focus of this study will be on the value of cooperation and the strategies the non-governmental organisation (NGO) should use to improve the performance of the bank as a whole. Once the data have been collected using quantitative and qualitative techniques, SPSS descriptive statistics will be utilised to maintain the findings and support the research hypothesis. According to the study, qualities like trust, camaraderie, job happiness, and benefits directly impact employees productivity at the bank. The degree of teamwork among co-workers directly affects how productive an employee is. Using the statistical program SPSS, managers and staff of NGOs were surveyed; the results revealed a favourable correlation between employee performance and NGO cooperation. When employees cooperate at work, their productivity increases, and the efficacy of the organisations they work for rises. Good news for charitable organisations. Because of this, the collaborative NGO outperforms the non-collaborative NGO in terms of productivity. It was found that better communication results in greater cooperation amongst NGOs. Copyright 2023 Inderscience Enterprises Ltd. -
Cop-edge critical generalized Petersen and Paley graphs
Cop Robber game is a two player game played on an undirected graph. In this game, the cops try to capture a robber moving on the vertices of the graph. The cop number of a graph is the least number of cops needed to guarantee that the robber will be caught. We study cop-edge critical graphs, i.e. graphs G such that for any edge e in E(G) either c(G?e) < c(G) or c(G?e) > c(G). In this article, we study the edge criticality of generalized Petersen graphs and Paley graphs. 2023 Azarbaijan Shahid Madani University. -
Coping with Public and Private Face-to-Face and Cyber Victimization among Adolescents in Six Countries: Roles of Severity and Country
This study investigated the role of medium (face-to-face, cyber) and publicity (public, private) in adolescents perceptions of severity and coping strategies (i.e., avoidant, ignoring, helplessness, social support seeking, retaliation) for victimization, while accounting for gender and cultural values. There were 3432 adolescents (ages 1115, 49% girls) in this study; they were from China, Cyprus, the Czech Republic, India, Japan, and the United States. Adolescents completed questionnaires on individualism and collectivism, and ratings of coping strategies and severity for public face-to-face victimization, private face-to-face victimization, public cyber victimization, and private cyber victimization. Findings revealed similarities in adolescents coping strategies based on perceptions of severity, publicity, and medium for some coping strategies (i.e., social support seeking, retaliation) but differential associations for other coping strategies (i.e., avoidance, helplessness, ignoring). The results of this study are important for prevention and intervention efforts because they underscore the importance of teaching effective coping strategies to adolescents, and to consider how perceptions of severity, publicity, and medium might influence the implementation of these coping strategies. 2022 by the authors. -
Copper Nanoparticles: A Review on Synthesis, Characterization and Applications
An emerging field of science Nanotechnology which is involved in manipulation of atoms and molecules has shown great potential in all fields of sciences. Nanotechnology deals with nanoparticles ranging from size 1 to 100 nm in diameter, due to small size and high surface area eventually increases the state of activity. This review focuses on metal and metal oxide nanoparticles and mainly on green synthesis, characterization and application of copper nanoparticles. Green synthesis of copper and copper oxide (Cu and CuO) is economically beneficial and ecofriendly. Copper nanoparticles are used in diverse fields such as biomedicine, pharmaceuticals, bioremediation, molecular biology, bioengineering, genetic engineering, dye degradation, catalysis, cosmetics and textiles. Structural properties and biological effects of copper nanoparticles have promising effectivity in field of life sciences 2020. All rights reserved. -
Copper oxide modified biphasic titania for enhanced hydrogen production through photocatalytic water splitting
Recently, TiO2(B) has been extensively used in catalytic and energy fields owing to its exceptional crystal structure. But being a metastable state, TiO2(B) is transformed easily into other stable crystalline forms like anatase or rutile phase, and the low crystallinity limits the application of the material in catalysis. A combination of TiO2(B) with anatase, which is benefitted by a homojunction, is proven to be blessed with high activity. Herein, hydrogen production via photocatalytic water-splitting is presented using Cu modified biphasic titania nanotubes achieved by a facile hydrothermal procedure. The systems are well characterized using SEM, TEM, XRD analysis, N2 adsorption study, FTIR, DR-UV, Raman, Photoluminescence, and X-ray photoelectron spectral analysis. The homo-junction developed in titania due to anatase TiO2 (B), as well as the heterojunction created by the co-catalyst, tune the photocatalytic activity of TiO2 nanotubes positively, as evident from the enhanced hydrogen production over the system. 2023 -
Coronal Elemental Abundances During A-Class Solar Flares Observed by Chandrayaan-2 XSM
The abundances of low first ionization potential (FIP) elements are three to four times higher in the closed loop active corona than in the photosphere, known as the FIP effect. Observations suggest that the abundances vary in different coronal structures. Here, we use the soft X-ray spectroscopic measurements from the Solar X-ray Monitor (XSM) onboard the Chandrayaan-2 orbiter to study the FIP effect in multiple A-class flares observed during the minimum of Solar Cycle 24. Using time-integrated spectral analysis, we derive the average temperature, emission measure, and the abundances of four elements Mg, Al, Si, and S. We find that the temperature and emission measure scales with the sub-class of flares while the measured abundances show an intermediate FIP bias for the lower A-flares (e.g. A1), while for the higher A-flares, the FIP bias is near unity. To investigate it further, we perform a time-resolved spectral analysis for a sample of the A-class flares and examine the evolution of temperature, emission measure, and abundances. We find that the abundances drop from the coronal values towards their photospheric values in the impulsive phase of the flares and, after the impulsive phase, they quickly return to the usual coronal values. The transition of the abundances from the coronal to photospheric values in the impulsive phase of the flares indicates the injection of fresh unfractionated material from the lower solar atmosphere to the corona due to chromospheric evaporation. However, explaining the quick recovery of the abundances from the photospheric to coronal values in the decay phase of the flare is challenging. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
Corporate Default Prediction Model: Evidence from the Indian Industrial Sector
The unprecedented pandemic COVID-19 has impacted businesses across the globe. A significant jump in the credit default risk is expected. Credit default is an indicator of financial distress experienced by the business. Credit default often leads to bankruptcy filing against the defaulting company. In India, the Insolvency and Bankruptcy Code (IBC) is the law that governs insolvency and bankruptcy. As reported by the Insolvency and Bankruptcy Board of India (IBBI), the number of companies filing for bankruptcy under IBC is on a rise, and the industrial sector has witnessed the maximum number of bankruptcy filings. The present article attempts to develop a credit default prediction model for the Indian industrial sector based on a sample of 164 companies comprising an equal number of defaulting and nondefaulting companies. A total of 120 companies are used as training samples and 44 companies as the testing samples. Binary logistic regression analysis is employed to develop the model. The diagnostic ability of the model is tested using receiver operating characteristic curve, area under the curve and annual accuracy. According to the study, return on assets, current ratio, debt to total assets ratio, sales to working capital ratio and cash flow to total assets ratio is statistically significant in predicting default. The findings of the study have significant implications in lending and investment decisions. 2021 MDI. -
Corporate diversification and firms financial performance: an empirical evidence from Indian IT sector
The aim of this research paper is to provide empirical evidence on the effect of geographic and segment diversification on the financial performance of the Indian IT sector. The study was done on 12 listed IT firms representing 93% market share on BSE/NSE. Standard econometric regression analysis on panel data was carried out to find the stated relationship. The results of the regression analysis revealed that international/geographic diversification impacted strongly on IT firms profitability whereas product/segment diversification had no significant impact on the firms profitability. This study also proves the existence of demand for Indian IT sector in other countries. These results could be useful in decision making for top managers of IT companies as they advocate the need for diversification (specialisation) and growth in size and also provide encouragement to small-scale Indian IT companies to undertake international diversification activities with confidence. Copyright 2023 Inderscience Enterprises Ltd. -
Corporate governance practices and shareholder protection in India
The present study aims to study the corporate governance practices and shareholder protection among Indian companies. For this purpose a sample of 100 companies are selected. The selected companies listed in BSE 100 Index. The required data are collected from various secondary sources like company website, annual report, notices and annual general meeting. Data were collected using a structured schedule adapted from G20/OECD principles of corporate governance. The finding of the study indicates that out of the selected companies, the level of practicing the corporate governance are not the same. The result of this study will help investors in identifying the companies for their investment, based on their priorities by keeping corporate governance scorecard as a benchmark. It will also be helpful for companies to see their scorecard and check the parameters for improvement and to attract and safeguard the investors and other stakeholders. This study will also add value to the existing literature in their relevant field. Indian Institute of Finance. -
Corporate social initiatives and wealth creation for firms-an empirical examination
Purpose: This study aims to examine whether social initiatives adopted by firms lead to improved financial performance. The authors analyse the impact of different elements of social initiatives on wealth creation for firms in terms of operating and market performance. Design/methodology/approach: The study is based on the social initiative scores of over 4,500 firms collected from Thomson Reuters' ESG database. The study uses two-stage least squares (2SLS) to analyse the relationship between social initiatives and firm performance. Findings: Profitable, mature, capital intensive and firms with high sales growth rate tend to invest more in social initiatives. Firms with high agency costs invest in social initiatives for workforce efficiency, maintaining human rights and product responsibility. The study documents evidence that social investments are value creating mechanism for firms which leads to improved financial performance in terms of operating and stock market performance. Firms with high dividend intensity invest in social initiatives for workforce welfare and human rights initiatives. Investment in employee well-being and community initiatives results in intangible benefits such as improved stock market valuation. Practical implications: The research model has not considered the impact of intervening variables to understand the relationship between corporate social performance and corporate financial performance. Social implications: Firms ought to recognize that social investment is beneficial in terms of value creation of firms as stock market perceive such investments favourably. Firms must focus more on community development initiatives and workforce initiatives for the value creation of firms compared to investments directed towards human rights initiatives and product responsibility initiatives. Originality/value: This study focusses exclusively on the social dimension of the CSR activities. The authors examine the impact of social welfare scores on firm performance by analysing the valuation effects on scores representing workforce, human rights, community and product responsibility. Moreover, the paper also examines the impact of a new dimension of product responsibility on firm performance. They also focus on both aspects of financial performance in terms of operating performance (proxied by ROE) and the joint impact of both operating and market performance (proxied by Tobins Q). This paper contributes to the research on the linkage of social performance to financial performance by observing that firms with high agency cost characteristics tend to invest in social initiatives for work force efficiency, maintaining human rights and product responsibility. 2024, Emerald Publishing Limited. -
Corporate Social Performance and Firm Location: Empirical Evidence
The study addresses the relationship between firm location and the corporate social performance (CSP) of manufacturing enterprises in India. The study argues that a higher number of multinational corporations (MNCs) at a location leads to higher social performance. An environment and social involvement (ESI) index, based on ISO26000 and National Voluntary Guidelines, has been used to measure the corporate social performance of manufacturing enterprises. The data are obtained through questionnaires from a survey of 121 medium-sized manufacturing enterprises in the national capital region in India and analyzed through one-way ANOVA and linear regression. Results reveal that the presence of MNCs at the location of enterprises is significant to their CSP. The findings of the study aggregate to make original and substantive contributions to the CSP literature on the geography of strategic management. This research is valuable for social responsibility practitioners in developing countries for start-ups and small and medium enterprises who are seeking to enhance their understanding to formulate pragmatic and effective strategies to improve CSP. 2023 IGI Global. All rights reserved. -
Corporate social responsibility assurance, board characteristics and social performance disclosure. Evidence of listed firms in India
The study examines board characteristics, corporate social responsibility (CSR) assurance and social performance disclosure of listed firms before and after mandatory CSR reporting in India. We used the Indian stock market as the testing grounds and applied panel regression and difference-in-differences to analyse 960 firm-year observations between 2010 and 2021. The first findings show that independent board directors and total board size are insignificant in CSR assurance engagement in a mandatory CSR policy period. However, CEO duality is less than likely causing CSR assurance engagement. The second findings show that CSR assurance engagement more than likely causes an increase in social performance disclosure before mandatory CSR policy implementation and increases social performance after policy implementation. The third findings show that the interactive effect of board characteristics (independent directors, total board size and CEO duality) and CSR assurance engagement causes an increase in social performance disclosure. The study sought clarity on the impact of CSR assurance and mandatory CSR reporting on information asymmetry problems to stakeholders. The study also contributes new knowledge on the influence of the interactive effect of board characteristics and CSR assurance on the social performance disclosure of listed firms in India. 2022 John Wiley & Sons Ltd. -
Corporate social responsibility: a cluster analysis of manufacturing firms in India
Purpose: This paper aims to identify the corporate social responsibility (CSR) patterns of Indian manufacturing firms using a CSR index based on ISO26000 and Indias National Voluntary CSR Guidelines. Design/methodology/approach: A total of 121 manufacturing enterprises in the national capital region (NCR) were surveyed. The questions related to the involvement of CSR in business strategy, involvement in CSR planning, involvement in environmental activities, involvement in social activities, monitoring, evaluation and involvement in CSR, reporting and policy and deployment of CSR. A two-step cluster analysis using log-likelihood measures was used to identify groupings in the data set based on their performance across the seven issues. Findings: The two distinctive segments identified adopted intermediate CSR activities, and one undertook advanced CSR activities. Research limitations/implications: This study has several limitations. First, the survey data were drawn exclusively from medium-sized enterprises in the NCR. Second, all the indicators in the CSR index were equally weighted. Originality/value: This paper contributes to the literature by grouping manufacturers CSR activities based on seven dimensions suggested in ISO26000 and Indias National Voluntary Guidelines. The results of this study can help managers, boards and regulators better understand CSR and identify ways to improve it further. 2023, Emerald Publishing Limited. -
Corporate social responsibility: Myth and reality
Companies nowadays strive to be socially conscious in the way they do business by taking up corporate social responsibility (CSR) activities besides maintaining profitability. Similarly consumers modulate their purchase choices to be made up of products that have been produced and marketed through socially responsible processes. But the congruence between achieving gain and being responsible to the community has ethical contradictions due to the presence of self interest. This paper proposes to examine the dimensions of this conflict and towards the end suggest a new orientation that foregrounds social responsibility relative to profit or gain. 2013 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (Dharmaram Vidya Kshetram, Bangalore). -
Corpus based sentimenal movie review analysis using auto encoder convolutional neural network
In natural language processing, most prominent branch is sentiment analysis. Peoples emotions and attitudes are analyzed using this sentiment analysis towards service, some product, etc. In prediction of the future scope of a product, some benefits are given by sentiment analysis. However, manual analysis of such a huge amount of documents is a highly tedious task, especially with limited time. Hence, for solving this problem, various attempts are made in literature and proposed different sentiment analysis methods. However, in generation of lexicon, popular NLP tools has some drawbacks. The accuracy of lexicons based on humans is less and they are limited too. On the other hand, lexicons based on dictionary are highly general and they are domain specific. So, a technique called Corpus Integrated Autoencoder Convolutional Neural Network based Sentiment Analysis (CI-AECNN) is proposed in this work for solving this issue. The sentiment lexicon generation based on corpus is performed in this work. Candidates sentiment orientation are computed using this and seed lexicon are added with recognized sentiment words and from seed lexicon, words with incorrect sentiment are removed. The long short-term memory (LSTM) is used for performing Word Sense Disambiguation. Conditional random fields are used for extracting features. At last, auto-encoder, convolutional neural network is used for performing classification. In MATLAB simulation environment, conducted this research works overall analysis and it indicates that better results are produced by proposed technique when compared with available techniques. 2021 Taru Publications. -
Correlated variability of the reflection fraction with the X-ray flux and spectral index for Mrk 478
The X-ray spectrum of Mrk 478 is known to be dominated by a strong soft excess that can be described using relativistic blurred reflection. Using observations from XMM-Newton, AstroSat, and Swift, we show that for the long-term (?years) and intermediate-term (days to months) variability, the reflection fraction is anticorrelated with the flux and spectral index, which implies that the variability is due to the hard X-ray producing corona moving closer to and further from the black hole. Using flux-resolved spectroscopy of the XMM-Newton data, we show that the reflection fraction has the same behaviour with flux and index on short time-scales of hours. The results indicate that both the long- and short-term variability of the source is determined by the same physical mechanism of strong gravitational light bending causing enhanced reflection and low flux as the corona moves closer to the black hole. 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.