Search results

The purpose of this paper is to evaluate the importance of financial liquidity and solvency on US commercial and domestic banks’ cost efficiency while accounting for internal and external factors.

The Stochastic Frontier Analysis and Data Envelopment Analysis estimators are used to estimate the cost efficiency of 11,044  US commercial and domestic banks from 2005 to 2017. Using Tobit regression model, the importance of financial liquidity and solvency on cost efficiency is examined.

The results provide evidence that the financial liquidity and solvency negatively impact the cost efficiency of US commercial and domestic banks. Overall, US commercial and domestic banks were inefficient during the financial crisis in comparison to the tranquil period. The importance of financial solvency on the cost efficiency was not statistically significant, while the financial liquidity negatively collapsed because of contagion. Finally, the results provide evidence that the amount of total assets matters in the improvement of the cost efficiency.

This paper estimates and identifies the 2007-2009 financial crisis with liquidity, solvency or both financial factors.

This paper aims to analyse the weekday effect on the Nifty Shariah indices as per the Islamic calendar. The study is intended to know about the return and volatility of these indices during Ramadhan and non-Ramadhan days.

The study focuses on analysing the Nifty Shariah indices and Sensex daily returns collected from NSE India and BSE India, respectively, during the period of 1 August 2016 to 31 July 2022. Descriptive statistics are used to analyse the data, while the Ordinary Least Square method is used to determine the impact of weekdays on the Nifty Shariah indices. Additionally, the study applies the GARCH statistical model to examine the influence of Ramadhan on the returns and volatility of the Nifty Shariah indices.

All of the Nifty Shariah indices produced positive returns during the overall sample period. According to the study, Tuesday index returns outperform other weekdays. The GARCH model indicated that the coefficient values for the Nifty 50 Shariah and Nifty 500 Shariah indices were negative. Ramadhan has a strong negative effect on volatility, according to this study.

The outcomes of the research are beneficial for investors aiming to exploit daily or weekly price fluctuations, rather than pursuing extended investment periods. Furthermore, fund managers can employ these findings to shape trading strategies, and academics can examine the performance of Shariah indices in the Indian context. This enables devout investors to make significant financial choices, thus advancing ethical values in society and upholding standards of both public and private morality.

The consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the United States is investigated based on cluster analysis while accounting for the yearly variation in banks.

Due to the importance of efficiency measures for policy and managerial decision-making, the cost efficiency measures of SFA and DEA estimators are examined according to four criteria: levels, rankings, stability over time and stability over clustering groups. In this paper, we present two clustering methods, Gap Statistic and Dindex, that involve SFA and DEA cost efficiency measures. The clustering approach creates homogeneous groups of banks offering a similar mix of efficiency levels. Hence, each evaluated bank knows the cluster to which it belongs. Furthermore, this paper provides nonparametric statistical tests of SFA and DEA cost efficiency measures estimated with and without a clustering approach.

The results suggest that the clustering approach plays a considerable role in the rankings of US banks. Furthermore, the average SFA and DEA cost efficiency measures over time of the homogeneous US banks are substantially higher than those of the heterogeneous US banks.

This research is the first to provide comparative efficiency measures needed for desirable policy conclusions of heterogeneous and homogeneous US banks.

This paper evaluates the importance of both liquidity and solvency risk factors on variations in efficiency measures of US commercial and domestic banks from 2005 to 2017.

The analysis is conducted using the true random effect stochastic cost model to examine the role of both liquidity and solvency risk factors. To this end, the author uses the exponential stochastic cost function and adds new variables, including bank size, crisis as an indicator of the financial crisis and the Dodd–Frank Act and Basel II Accord as regulatory dummies.

The results show that both liquidity and solvency risk factors positively affect the variance of cost inefficiency measures and thus have negative impact on the cost efficiency measures. In addition, banks increased the cost of financial intermediation during the financial crisis, whereas regulatory factors of Basel II Accord and Dodd–Frank Act play a crucial role in explaining the cost efficiency measures.

These results are the first to quantify the impact of both liquidity and solvency on the variations in cost efficiency measures.

Long-term forecasts about commodity market indicators play an important role in informing policy and investment decisions by governments and market participants. Our study examines whether the accuracy of the multi-step forecasts can be improved using deep learning methods.

We first formulate a supervised learning problem and set benchmarks for forecast accuracy using traditional econometric models. We then train a set of deep neural networks and measure their performance against the benchmark.

We find that while the United States Department of Agriculture (USDA) baseline projections perform better for shorter forecast horizons, the performance of the deep neural networks improves for longer horizons. The findings may inform future revisions of the forecasting process.

This study demonstrates an application of deep learning methods to multi-horizon forecasts of agri-cultural commodities, which is a departure from the current methods used in producing these types of forecasts.

This paper aims to show the pragmatic studies that examine whether novel COVID-19 affects the national and international stock markets and reinforces the existing literature by highlighting the factors that are resultant from COVID 19.

The systematic literature review and bibliometric approach have been used in the study covering 585 selected articles published in journals of high repute from January 2020 to January 2022. The process of bibliometric analysis has been divided into three stages, namely, assembling, arranging and assessing. From the Scopus database, one of the most reliable and authentic database total of 585 records were collected, out of which 12 were specifically focused on communities, and information gathered in the comma-separated value documents design was compared and interpreted based on year, document types, subject area, country and research fields with the help of graphs and pie charts. The study has analyzed fact-based and reliable studies to draw inferences from existing literature regarding the pandemic impacting the financial markets. In the extant study, an attempt has been made to explore the factors that are resultant from the COVID-19 pandemic and affects the stock market performance, which can be further classified into a few common factors by using factor analysis.

It originated from the majority of the studies that the stock market retorted destructively to the upsurge in the figure of COVID-19 cases and fatalities. It also emphasized that the market has reacted differently in comparison to earlier catastrophes such as the great depression of 2008 and the Spanish flu. Various factors such as fear of losing capital, standstill economy, lower valuation, increased mortality rate, halt in business operations, retrenchment, trade war, liquidity issues, panic buying and selling, digitalization, negative media coverage, government interference, financial behavior of investors, hoarding of COVID supplies, promotion of start-up in health-care and education sector, news bulletins, prevention campaigns, use of medical devices and COVID-19 vaccination, etc. have been conferred from the studies that have an immediate consequence on the actions of investors in the stock market. It was further highlighted in the study that the Indian stock market has been less explored in respect of implications of COVID-19 contagion as the majority of studies were based on either international stock exchanges or combinations of varied nation’s stock markets. It was witnessed in the interpretation section that the number of studies is increasing at a fast pace as new variants of COVID-19 are emerging over time. Significant contribution has been done in enhancing the literature on COVID-19 and the stock market by China and the USA. The maximum contribution in this domain has been done in the form of articles in the present literature. Few studies were focusing on communities, so the present study will try to fill this research gap to some extent.

This conceptual paper is demarcated by unsatisfactory analyses of writings from multi-discipline to get a comprehensive scope of notional understanding. Furthermore, there is a perchance that some other imperative phenomena or variables that prejudiced trading bustle have not been captured by present reviews of research papers. The influences of other macroeconomic variables should be explored to understand the concrete results of this pandemic.

Most of the studies were based on foreign stock exchanges, so there is an opportunity to explore the Indian stock market concerning the implications of the coronavirus pandemic. In the literature, it was examined that short-term studies have been undertaken, which cannot determine the long-term implications of COVID-19. Over time, besides COVID-19, various other factors have started impacting the stock market, so it has become difficult to examine the influence of COVID-19 on the stock market in isolation.

The study will be helpful for future learnings in the arena of the stock market as it provides vast exposure to the present literature related to the impact of COVID-19 on economic markets. On the other hand, investors will also become aware of factors that are resultant of COVID-19 and will take the right decisions to save their investments in light of pandemic implications. The extensive review of studies will also help enterprising communities to take judicial steps to remain active in the period of economic slowdown.

The paper provides significant implications to the investors in the stock market, and it will provide useful insight to improve their returns on their portfolios. The learning from the study will help investors to take fruitful decisions considering the uncertainty during the pandemic period. The inferences drawn from rich existing literature will be guiding enterprises to take timely actions to avoid the situation of loss in the market and adapt new models to ensure continuity of business operations. Different markets had reacted differently, so investors need to be cautious before taking trading decisions.

The purpose of this study is to eliminate voltage harmonics and instantly measure the positive sequence fundamental voltage during unbalanced grid conditions, the dual second-order generalized integrator-phase locked loop used in series hybrid filter structures is often used in grid synchronisation in three-phase networks. The preferred series active hybrid power filter simultaneously compensates for voltage balancing and current harmonics generated by non-linear loads.

This paper examines the use of renewable energy–based microgrid (MG) to support linear and non-linear loads. It is capable of synchronising with both the utility and the diesel generator unit. Power is transferred from the grid throughout a stable grid situation with minimum renewable energy generation and maximum load demand. It synchronises with diesel generator set to supply the load and form an AC MG during outages and minimum renewable power generation. In islanded and grid-connected mode, the voltage and power quality issues of the MG are controlled by static synchronous compensator and series hybrid filter.

Because of the presence of non-linear loads, reactive loads in the distribution system and the injection of wind power into the grid integrated system result power quality issues like current harmonics, voltage fluctuations, reactive power demand, etc.

The voltage at the load (linear and non-linear) is regulated, and the power factor and total harmonic distortions were improved with the help of the series hybrid filter.

Debt, dividend and investment policy constitutes a company's important financial decisions to determine firm performance. The research emphasizes on the problem of overinvestment, a phenomenon that worsens firm operation. Furthermore, it clarifies the moderation role of debt and dividend policy in mitigating the negative effect of overinvestment on firm performance in the case of Vietnamese listed companies.

The research uses all financial statement of non-financial Vietnamese listed companies on Ho Chi Minh and Hanoi Stock Exchange in the period of 2008–2018. The data are collected from Thomson Reuters Eikon. The final data set is comprised of 669 listed companies. The study measures overinvestment though investment demand function and HP filter. Moreover, the research employs the dynamic model, so it has to apply the SGMM method to deal with the problem of endogeneity caused by the lagged dependent variable.

The research finds that overinvestment is negatively associated with firm performance. Debt or dividend policy separately can moderate the negative effect of overinvestment on firm performance. However, when these two policies are combined, they lessen the positive interaction impact of each policy due to the substitution between debt and dividend policy.

The research may have two limitations. Firstly, the research measures overinvestment indirectly through investment demand function and HP filter. These two measures only help identify the sign that companies may have the problem of overinvestment because we cannot determine whether they overinvest or not in reality. Secondly, when using interaction variables, the problem of multicollinearity may be higher, and this may adjust the signs and significance level of variables in the models.

Practically, the research proposes three policy recommendations. Firstly, a company can exploit debt or dividend policy to limit excessive free cash flow in order to constrain the problem of overinvestment. Secondly, a company should enhance its corporate governance to resolve agency problems. Thirdly, the government should make the financial sector more transparent and effective to improve monitoring functions of various parties in the capital market.

Overinvestment sometimes can cause social issues. Overinvestment means that companies make ineffective investment. If they continue this situation over a long time, companies may have financial distress or even go bankruptcy. As a result, it will slow down economic growth and increase unemployment in the economy.

The research is supposed to make two great contributions to the existing empirical studies in two aspects. Firstly, it is the first attempt to take into consideration the interaction between overinvestment and financial policies. Secondly, it helps enhance the fundamental stance of the agency theory, which supports the interdependence of debt, dividend and investment policy.

The objective of this paper is twofold. First, to study the safe-haven characteristic of the Islamic stock indexes and Ṣukūk during the crises time. Second, to evaluate this property in the last pandemic. This study employs the daily dataset from June 15, 2015, to June 15, 2020, for the most affected countries by the earlier disease.

This study uses the Markov-switching Capital Asset Pricing Model (CAPM) approach and the basic CAPM for the main analysis and the safe haven index (SHI) recently developed by Baur and Dimpfl (2021) for the robustness test.

Based on Baur and Lucey's (2010) definition, empirical findings indicate that Islamic stock indexes cannot be a refuge throughout the crisis regime for all selected conventional markets. However, Ṣukūk are a strong refuge in Brazilian, Russian and Malaysian markets. For the remainder countries, except Italy, the USA and Spain, the Ṣukūk index offers weak protection against serious conventional market downturns. Similar conclusions are obtained during the COVID-19 global crisis period. Finally, results are confirmed by using the SHI.

To the best of the authors’ knowledge, this paper is the first study that evaluates the safe haven effectiveness of the Islamic index and Ṣukūk using the SHI in the most impacted countries by the COVID-19 outbreak.