Variable Returns Research Articles

Eleven sectors’ reaction to the political event 2023: evidence from Indonesia Stock Exchange

Research aims: This study analyzes the differences in market reaction towards eleven sectors in the Indonesia Stock Exchange (IDX) during the political event, i.e., the announcement of the Indonesian presidential and vice-presidential nominees in 2023.Design/Methodology/Approach: This study applied the event study method with indicators of abnormal return, trading volume activity, security return variability, and bid-ask spread. The hypothesis test was a non-parametric test by Wilcoxon Signed Rank Test with a window period of seven days of observation (-3, 0, +3).Research findings: The Wilcoxon Signed Rank Test results revealed a mixed reaction by eleven sectors in IDX to this political event, in which there was a difference and no difference in the reactions.Theoretical contribution/Originality: This study contributes to providing insight into the reaction of eleven different sectors in the IDX to the different announcements of the Indonesian presidential and vice-presidential nominees in 2023. Previous research usually focused on stock indices or only testing one particular sector. Hence, this study investigated eleven sectors in the capital market to compare the different reactions and to expand the results.Practitioner/Policy implication: Research on capital market reactions to political events provides important information for investors to make investment decisions based on investor sentiment that assesses the electability of prospective heads of state to advance the Indonesian economy.Research limitation/Implication: The scope of this study is the announcement of the Indonesian presidential and vice-presidential nominees in 2023; future researchers can continue research on capital market reactions to the Indonesian presidential election 2024 events and add relevant variables, such as foreign sales and foreign buys.

An examination of the characteristics versus covariance debate for contemporary asset‐pricing models: Australian evidence

AbstractAs contemporary asset‐pricing models have expanded to include new factors, the empirical literature has carefully studied the time‐series fit of competing model specifications. In contrast, comparison of the roles played by characteristics and factor loadings in explaining cross‐sectional return variation has received less attention. This paper re‐examines the characteristics versus covariance debate. The findings overwhelmingly support the characteristics explanation. Firm size, book‐to‐market, profitability and investment characteristics are important for understanding differences in returns, over and above how a stock loads on common risk factors. Portfolios designed to be a pure play on a given characteristic generate economically significant trading profits.

Pengaruh ROA, Proporsi Dewan Komisaris Independen, ACHANGE, LEV, DCHANGE Terhadap Tax Avoidance

The background to this research focuses on several companies that carry out deliberate tax avoidance actions such as not remitting taxes that have been collected by not submitting Tax Returns (SPT). Tax avoidance or tax avoidance is an activity to reduce or eliminate tax debts that should be paid by the company by not violating existing laws. This study aims to detect whether there is a significant relationship between the independent variables in detecting tax avoidance in trading industry companies listed on the Indonesia Stock Exchange during the 2017-2021 period. This study uses a quantitative approach with sample data obtained from annual reports of trading industry companies that have been published on the Indonesia Stock Exchange during the 2017-2021 period. The sample selection technique used was purposive sampling, and data was obtained from 30 samples. The method used is descriptive statistical analysis and multiple regression analysis. The results of this study indicate that the variables Return On Assets (ROA) and Pressure from Outside (LEV) have positive and significant results on tax avoidance. Other factors which include the Proportion of Independent Commissioners, Financial Stability (ACHANGE), and Change of Directors (DCHANGE) do not have a significant effect on tax avoidance.

Data envelopment analysis: From non-monotonic to monotonic scale elasticities

The concept of returns to scale (RTS) or local scale elasticities in data envelopment analysis (DEA)—stemming from variable returns to scale (VRS) technology—has been recently criticized because of its misbehavior in the case of decreasing returns to scale (DRS). Here, the instrument should imply a downsizing force for improving productivity. In classical VRS technologies, however, it can hide respective improvement potentials: the more, the larger a company is. The non-monotonic behavior of local scale elasticities can address this effect. This study shows this phenomenon does not apply when using multiplicative DEA models. Therefore, we propose a new global scaling index that works in the classical VRS technology. We prove the new index is weakly monotonic and illustrate our theoretical findings in a banking context.

THE CO-INTEGRATION AND CAUSALITY EFFECT BETWEEN GLOBAL COVID-19 PANDEMIC AND THE STOCK MARKET RETURN IN MALAYSIA: AN EXPLORATORY SEQUENTIAL MIXED METHODS APPROACH

The COVID-19 pandemic is one of the most unparalleled disasters the world has ever seen. Previously, the global community hasfaced the Middle East Respiratory Syndrome (MERS), Ebola Virus Disease (EVD), and Severe Acute Respiratory (SARS). However,the tremendous rate of infection created by the global COVID-19 pandemic is unmatchable with its rapid spread all over the world. Therefore, it is considered as a Black Swan event as created previously by the 2008 financial crisis, SARS, and 9/11 terrorist attack. All these events have triggered panic selling that affected the confidence of investors and businesses. Subsequently, stock market performance has affected the choice of investment decisions that translated into stock return. Therefore, this paper was undertaken to investigate the co-integration and causality relationship among global COVID-19 daily infected cases, COVID-19 recoveries rate, COVID-19 death rate, investor sentiment, government policy, foreign exchange rate, Malaysia gold price, and crude oil price towards the KLCI stock market return. This study employed an exploratory sequential mixed methods approach along with Johansen and Julius Co-Integration and Granger Causality in explaining the Malaysia stock market return. The empirical analysis concluded that COVID-19 daily cases, COVID-19 recoveries rate, government policy and foreign exchange have had a long-term effect in explaining the Malaysia stock return. On the other hand, all the study variables, except for government policy indicated a short-term effect on the Malaysia stock return. This study will contribute significantly to the body of finance literature on the impact of a disease outbreak, with highlights on the considerations of investors on the global COVID-19 pandemic in illuminating the variation of Malaysia stock market returns.

Efficiency and sustainability: Evaluating and optimizing energy use and environmental impact in cucumber production

This study assesses the energy-economic-environmental aspects of cucumber production in the face of environmental issues and resource scarcity, which threaten global food security and demand sustainable agriculture solutions. Data were collected by questionnaire and analyzed for inputs from planting to harvesting. The results indicated that diesel fuel (37.41%) and nitrate fertilizer (37.22%) constitute the primary inputs. The energy ratio, energy efficiency and net energy gain were 0.43, 0.54 kgMJ−1 and -30,153.31 MJha−1, respectively. Input optimization by Data Envelopment Analysis (DEA) reduced the carbon footprint from 178.433 to 168.900 kg CO2 per ton, the abiotic depletion from 1228.291 to 964.305 MJ and the acidification from 0.838 to 0.749 kg SO2 eq. Also, the results of DEA showed that 52.5% and 35% of the units were fully efficient under Variable Return to Scale (VRS) and Constant Return to Scale (CRS) models, respectively, while the others were inefficient to varying degrees. The average of technical, pure technical and scale efficiencies were 92.88%, 97.64%, and 95.07%, respectively. The results of economic evaluation showed that production cost is 6058.84 $ha−1 with a benefit-cost ratio of 1.71. Based on the primary results, it is suggested to use precision agriculture techniques and the exploration of alternative energy sources, such as biofuel for machinery. Additionally, using slow-release fertilizers or organic substitutes can decrease nitrogen fertilizer dependency while maintaining crop yields and improve the sustainability in this production.

Evaluating the Efficiency of Indonesian Library and Information Science Journals: A Data Envelopment and Bibliometric Analysis

This study evaluates the efficiency of Indonesian Library and Information Science journals indexed by SINTA by applying Data Envelopment Analysis (DEA) using a Variable Return to Scale (VRS) model. The primary aim is to assess the performance of these journals to identify areas of strength and inefficiency. The study encompasses twenty-one journals, which served as decision-making units (DMUs). The input variables considered include Article Processing Charges (APC), Editorial Team, Number of Authors, and Number of Publications, while the output variables were Number of Citations and H5-Index. Data were collected from journal websites and the Sinta database covering 2018 to 2022. The analysis was conducted using MaxDEA software. An efficiency score of 1 indicated an efficient journal, whereas scores below 1 denoted inefficiency. The study reveals six journals as efficient: Jurnal Kajian Informasi & Perpustakaan, Khizanah Al-Hikmah: Jurnal Ilmu Perpustakaan, Informasi, dan Kearsipan, IQRA': Jurnal Perpustakaan dan Informasi, Bibliotech: Jurnal Ilmu Perpustakaan dan Informasi, PUBLIS (Publication Library and Information Science), and Imam Bonjol Journal: Kajian Ilmu Informasi dan Perpustakaan. However, most journals were found to be inefficient, with an average efficiency score of 0.809. These findings are significant as they provide valuable insights for journal editors and policymakers. The results offer guidance on optimizing resource allocation and developing strategies to enhance the quality and impact of scholarly publications within the Library and Information Science field.

Common factors in the returns on cryptocurrencies

We find that the three risk factors of Liu et al. (2022) capture only one-third of the variation in cryptocurrency excess returns. The remaining variation is mostly driven by a single common component that lies outside the three factor model framework. Although we cannot explain this fully using a large set of 135 global macroeconomic and financial variables as candidate proxies, the unknown common component seems to be associated with the value of fiat money. The role of the common component in cryptocurrency valuation becomes more dominant during monetary easing than during tightening periods.

Profitability measurement of selected Islamic Shariah-based private commercial banks in Bangladesh: A comparative Study

The purpose of this study is to analyze the profitability of five selected five Islami banks with a Shariah foundation and to determine whether these banks are more or less profitable. This study makes use of secondary data that was gathered from selected banks' annual reports between 2013 and 2022. This study employed a parametric approach; comparisons were assessed using descriptive analysis; the ANOVA test was used to assess reliability; and multiple regressions was utilized to assess impact. SPSS version 2014 is utilized for multiple regression analysis, and Excel 10 is used for ANOVA tests. The results indicate that the profitability of the selected banks is fairly high, with every bank under examination achieving favorable outcomes. The percentage of deposits with assets and the distribution of assets among the sample banks are not moderate. The inadequate asset allocation of FSIBPLC is indicated by its low return on assets. Furthermore, the bank has a deficiency in the area of net profit margin (NPM). Additionally, SIBL's debt collection and repayment are inadequate. Investors will be deterred from investing by the significant variations in return on equity found in almost every bank during the research period. Reducing overhead costs and enhancing the appropriate distribution of loans and advances will boost operating income and net profit efficiency. Above all, FSIBPLC and AIBPLC have fared well across the board. To optimize their profitability, the three remaining banks—IBBPLC, SIBL, and UBBPLC—had to step up their efforts.

Pengaruh Return On Equity Dan Debt To Equity Ratio Terhadap Return Saham Pada Pt. Astra International, Tbk.

The purpose of this study is to determine the effect of Return On Equity and Debt to Equity Ratio on Stock Return at PT. Astra International, Tbk. The type of data used in this study is quantitative data, the source of data used is secondary data. The analysis methods used are descriptive analysis methods and multiple linear regression, determination coefficient, correlation coefficient, t test, and f test. The results of the regression equation Y = -14.765 + 0.576X1 – 0.093X2 + e. Simultaneously it does not have a significant effect on the variables Return On Equity and Debt to Equity Ratio to Return Shares at PT. Astra International, Tbk. Return On Equity positively does not have a significant effect on Share Return at PT. Astra International, Tbk. Debt to Equity Ratio does not affect Share Return at PT. Astra International, Tbk.

PENGARUH LEVERAGE KEUANGAN, LIKUIDITAS, EARNING PER SHARE DAN RETURN ON ASSET TERHADAP RETURN SAHAM PADA PERUSAHAAN MANUFAKTUR SEKTOR FOOD AND BEVERAGE DI BURSA EFEK INDONESIA

The aim of this research is to determine and explain the influence of financial leverage, liquidity, earnings per share (EPS), and return on assets (ROA) on stock returns in manufacturing companies in the food and beverage sector on the Indonesian Stock Exchange. either simultaneously or partially. The population in this study was 72 companies. The sampling technique used was purposive sampling technique to obtain a sample of 24 companies with a research period of 4 years. The analysis technique used is a multiple linear regression model with descriptive statistical tests, classical assumption tests, and hypothesis testing. The results of the t test research show that the Financial Leverage variable (Debt to Equity Ratio) has a negative and insignificant effect on stock returns, Liquidity (Current Ratio) has a positive and significant effect on stock returns, Earning Per Share (EPS) has a positive and significant effect on stock returns, Return on Assets (ROA) has a positive and significant effect on stock returns in Manufacturing Companies in the Food and Beverage Sector on the Indonesian Stock Exchange. And the results of the F test show that the independent variables, namely Financial Leverage (Debt to Equity Ratio), Liquidity (Current Ratio), Earning Per Share (EPS) and Return On Assets (ROA) have a significant effect on the dependent variable, namely Stock Returns in Food Sector Manufacturing Companies. and Beverage on the Indonesian Stock Exchange. The coefficient of determination is 40.3%, meaning that variations in Financial Leverage (Debt to Equity Ratio), Liquidity (Current Ratio), Earning Per Share (EPS) and Return on Assets (ROA) are able to explain variations in stock returns of 40.3%. Meanwhile, the remaining 59.7% is influenced by other variables.

PENGARUH ROA, ROE, LDR, CR, DAN NPL TERHADAP KONDISI FINANCIAL DISTRESS PADA PERUSAHAAN PERBANKAN YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2019-2022”

The study aims to predict financial distress through the financial ratio variables Return on Asset, Return On Equity, Loan to Deposit Ratio, Current Ratio, and Non-Performing Loan, from one, two and three years before occurring in banking companies listed on the Indonesian Stock Exchange. The population in this study is 47 banking companies. Sampling techniques are purposive sampling according to certain criteria so that 35 samples are obtained from the company. Data obtained from the Indonesian Stock Exchange for the years 2019-2022. The data analysis technique used in this study is logistic regression analysis. The results of the research show that the return on asset, return on equity, Loan to Deposit Ratio, Current ratio, and Non-Performing Loan, together, significantly influenced the probability of financial distress in banking companies listed on the Indonesian Stock Exchange for one, two and three years before it occurred. The degree of accuracy of the prediction of the influence of the financial variable ratio on the probability of financial distress for one, two and three years before having suffered financial distresses was 88.6 per cent, 88.6, and 82.9 per cent. The test results partially showed that the Return on Asset from the first, second and third years before the financial distress has a positive and non-significant effect on the likelihood of financial distress, the Return on Equity from one, two and three years before the financial distress had a negative and significant impact on the probability of the financial distress, the Loan to Deposit Ratio from one, two and three years before the financial distress had a negative and significant impact on the probability of the financial distress, the Ratio of Current Ratio from one and two years before financial distress has a negative and no significant effect on financial distress probability, and the Non-Performing Loan from three years prior to financial distress have a significant negative and positive impact on financial distress probability.

THE EFFECT OF FINANCIAL PERFORMANCE ON STOCK PRICE AT PT. ACE HARDWARE INDONESIA Tbk

This research was conducted to analyze the effect of financial performance (EPS, ROE, DER) on stock prices. The sample of this research is PT. ACE Hardware Indonesia Tbk. The data collection technique used is the documentation method. Data analysis techniques used normality, multicollinearity, heteroscedasticity, autocorrelation, multiple regression analysis, hypothesis testing t-test and F-test. Partial research results The Earning Per Share (EPS) variable partially has a significant effect on stock prices, variable Return On Equity (ROE) partially has no significant effect on stock prices, Variable Debt to Equity Return (DER) partially has a significant effect on stock prices, variable simultaneously Earning Per Share (EPS), variable Return On Equity (ROE), and the variable Debt to Equity (DER) significant effect on stock prices

EVALUATING THE EFFICIENCY OF COUNTRIES' DIGITALIZATION IN TERMS OF FINANCIAL INCLUSION BY USING DEA

The aim of the study is to evaluate the efficiency of countries in digitalization in terms of financial inclusion, in other words, their success in digitalization. Within the scope of the study, 117 countries were grouped as high, upper-middle, lower middle and low income and subjected to Data Envelopment Analysis. In the study conducted for the year 2021, four input variables related to the utilization and access of digital financial services were identified, along with ten corresponding output variables. Efficient countries were determined in the study based on the constant and variable return scale model for output. Digital efficiency has been identified in financial inclusion was detected in 25 countries based on variable returns and 18 countries based on constant returns in high-income countries. In upper-middle-income countries, digital efficiency in financial inclusion was identified in 12 countries based on variable returns and 9 countries based on constant returns. 16 countries in the lower middle and low income categories demonstrated digital efficiency in financial inclusion using variable returns, while 9 countries detected digital efficiency using constant returns. In the study, the comprehensive analysis of the success of digitalization in financial inclusion at the level of countries divided into income groups by using data envelopment analysis reveals the originality of the study.

The Impact of Financial Ratios on Profit Growth of Public Health Sector Companies

The purpose of this research is to determine the influence of Debt to Asset Ratio, Total Asset Turnover, and Return on Asset on the profit growth of public healthcare sector companies listed on the Indonesia Stock Exchange during the period of 2017-2021. The population of this study consists of public healthcare sector companies listed on the Indonesia Stock Exchange. The sample was determined using purposive sampling technique, and the selected sample consists of 3 public healthcare sector companies. The data analysis technique used in this research is panel data regression analysis with the assistance of EViews 12 software. The research findings indicate that the variable Debt to Asset Ratio does not have a significant influence on profit growth, Total Asset Turnover has a significant negative influence on profit growth, while the variable Return on Asset has a significant positive influence on profit growth. Keywords: Debt to Asset Ratio, Total Asset Turnover, Return on Asset, profit growth, healthcare sector

COAALA: A Novel Approach to Understanding Extreme Stock–Bond Comovement

Abstract This article proposes a novel copula model to understand the dependence between extreme variations in stock and government bond returns. This model is used to introduce a tail-based extension of the safe haven concept, which we refer to as a tail risk dampener. Our findings reveal significant cross-country differences in stock–bond local tail dependence and tail risk dampening abilities. Some countries’ bond market can lessen the impact on portfolio returns of extreme negative stock returns, while for others no such negative tail comovement is found. This tail comovement is also not always aligned with global comovement between stocks and bonds. The article concludes that a comprehensive understanding of the comovement and the resulting diversification potential between stock and bond returns necessitates complementing global measures of dependence with local tail measures.

Investment Portfolio Optimization in Renewable Energy Stocks in Indonesia Using Mean-Variance Risk Aversion Model

Climate change is a phenomenon that has been occurring for quite some time. However, the increasingly felt impacts of climate change necessitate human action to mitigate these effects. One way to address this issue is by transitioning from conventional or non-renewable energy sources to renewable energy. This step undoubtedly has implications for various aspects, such as investments. Naturally, investors are beginning to turn their attention to the field of renewable energy as a new target. Investments are inherently associated with risks and returns One approach to maximizing returns is through portfolio optimization. One well-known method in portfolio optimization is the Mean-Variance method, also known as the Markowitz method, as it was first introduced by Harry Markowitz. In this research, an optimal portfolio is generated with weights of 0.1470 for ADRO; 0.1939 for MEDC; 0.2143 for ITMG and 0.4449 for RAJA. With this composition of optimal portfolio weights, the expected return is obtained at 0.002252, and the return variance is 0.000496.

Peer-to-peer electricity trading model for urban virtual power plants considering prosumer preferences and power demand heterogeneity

Peer-to-peer electricity trading has emerged as a critical way to meet the varied demands of prosumers within urban virtual power plants. To better support supply-demand balance and ensure the stable, low-carbon and efficient peer-to-peer electricity trading, both prosumer trading preferences and power demand heterogeneity need to be considered. This study proposes a peer-to-peer electricity trading model for urban virtual power plants that considers both preference of prosumers and power demand heterogeneity. First, to effectively meet the trading demands of diverse prosumers and enhance the penetration of renewable energy, prosumers are classified based on variations in financial returns, green electricity preferences and risk avoidance. Power demand is further classified based on the trading preferences of prosumers. Then, a peer-to-peer electricity trading model incorporating a game model and a market bidding mechanism is proposed to enable efficient and dynamic matching between supply and demand. Finally, to mitigate the impact of renewable energy uncertainty on peer-to-peer electricity trading, real-time auctions are implemented across multiple virtual power plants. The results show that the proposed model is capable of more effectively accommodating the diverse demands of prosumers, and facilitates a more stable, low-carbon and efficient peer-to-peer electricity trading.

Assessing and enhancing operational efficiency in Sierra Leone's retail banking sector: A comparative analysis using CCR and BCC DEA models

AbstractThis study assesses the operational efficiency of 14 Sierra Leone commercial banks from 2020 to 2022, focusing on the adoption of financial innovation, such as digital banking, mobile services, and online payments. The research evaluates banks' performance by leveraging innovations using data envelope analysis (DEA) with constant and variable returns to scale models. Findings show varied efficiency, with some banks excelling and others lagging. The study underscores the need for strategic management and optimization so that banks can benefit fully from financial innovations. The insights inform policymakers and bank managers on enhancing the sector's operational performance through technology integration.

The Distinction of Evaluation on Companies in Different Fields

This paper explores the variations in Return on Equity (ROE) and Price-to-Sales Ratio among publicly traded companies across different time periods and market capitalizations. The analysis employs Linear Regression and Correlation Coefficients to examine the relationships between ROE, Price-to-Sales Ratio, Market Capitalization, and economic conditions during these periods. The findings reveal that Price-to-Sales Ratio serves as a reliable indicator of a company's market capitalization. Furthermore, companies within the same industry exhibit substantial disparities in Market Capitalization, ROE, Price-to-Sales Ratio, Price-to-Earnings (P/E) Ratio, and PEG Index due to differing corporate strategies and backgrounds. For instance, in the new energy sector, both BYD and NIO display a negative correlation between market capitalization, while Tesla contradicts this trend. This discrepancy is attributed to internal factors such as asset composition, liabilities, and shareholder structure, which significantly influence a company's financial performance. The Market Capitalization of these new energy companies is predicted to rise due to global interest in AI technology, with technology companies being at the forefront of AI development. In the technology sector, companies like Google have solidified their positions by advancing AI concepts. New entrants, like Apple, combining Artificial Intelligence and Robotics, are gaining consumer support, indicating potential Market Cap. growth. The fashion industry also demonstrates distinctive strategies, with companies like NIKE, Adidas, and Anta focusing on sustainability and carbon neutrality. Therefore, future company evaluations should consider both financial indices and a company's long-term vision and sustainability practices to predict their future value effectively.