Variable Returns Research Articles

Bystander Response and Out-of-Hospital Cardiac Arrest Outcomes (Bro. Study) in 3 Gulf Countries: Protocol for a Prospective, Observational, International Collaboration Study

Background : Globally, there is significant variation in the out-of-hospital cardiac arrest (OHCA) survival rate. Early links in the chain of survival, including bystander cardiopulmonary resuscitation (CPR) and the use of an automated external defibrillator at the scene, are known to be of crucial importance, with strong evidence of increased survival rate with good neurological outcomes. The data from the Middle East are limited and report variable rates of bystander CPR and survival. It is crucial to get prospective, reliable data on bystander response in these regions to help plan interventions to improve bystander response and outcomes. Objective This international collaborative study aims to describe the characteristics, including bystander interventions and outcomes, of OHCAs brought to hospitals enrolled in the study from Abu Dhabi, United Arab Emirates; Doha, Qatar; and Muscat, Oman. It also aims to describe the strength of the association between bystander response and OHCA outcomes, including the return of spontaneous circulation, survival to hospital admission, survival to discharge, and good neurological outcome at discharge in the local context of low bystander CPR rates. Methods This multicenter, prospective, noninterventional observational study (Bro. Study) will be conducted at the emergency departments of 4 participating tertiary care hospitals in 3 countries. The data will be collected prospectively according to the Utstein style (a set of internationally accepted guidelines for uniform reporting of cardiac arrests) on demographic variables (age, sex, nationality, country, participating center, and comorbidities), peri–cardiac arrest variables (location, witnessed or not, bystander CPR, use of automated external defibrillator, time of emergency medical services arrival, initial rhythm, number of shocks, and time of prehospital CPR), and outcome variables (return of spontaneous circulation, survival to discharge, and neurological outcome at discharge and 3 months). Univariate and multivariate analysis with logistic regression models will be used to measure the strength of the association of bystander interventions with outcomes using SPSS (version 22). Results Data collection began in November 2023 and will continue for 2 years, with publication expected by early 2026. Conclusions Bystander response to an OHCA is critical to a favorable outcome. The reliable, baseline bystander CPR data will be a cornerstone in the team’s next planned projects, which are to qualitatively identify the barriers to bystander CPR, conduct a scoping review of community interventions in the Gulf and other Asian countries, and design and implement strategies to help improve the bystander CPR rate in the community. International Registered Report Identifier (IRRID) DERR1-10.2196/58780

Regular Variable Returns to Scale Production Frontier and Efficiency Measurement

Breakthrough in Measuring Efficiency with Respect to Nonconvex Technology The variable returns to scale (VRS) frontier, commonly used in data envelopment analysis, has a convex technology set and follows a specific “regular VRS” structure in economics. This structure demonstrates increasing, constant, and then, decreasing returns to scale, and it is the standard in data envelopment analysis. When the convexity assumption is relaxed, modeling regular VRS becomes challenging, and no satisfactory solution currently exists for multioutput production. In “Regular Variable Returns to Scale Production Frontier and Efficiency Measurement,” Li, Tsang, Lee, and He introduce a new framework for analyzing regular variable returns to scale and propose an innovative empirical production frontier. This new frontier can more accurately measure technical efficiency without the convexity assumption. The implications of this research are extensive, impacting fields like manufacturing, agriculture, healthcare, banking, etc., with crucial findings for informed decision making and effective policy implementation.

Do ETFs increase the comovements of their underlying assets? Evidence from a switch in ETF replication technique

We investigate the impact of Exchange-Traded Funds (ETFs) on the comovements of their constituent securities using a novel identification that exploits the switch from synthetic to physical replication of a large French ETF. After the switch, constituent stocks experience greater commonality, in both returns and liquidity. For both the full sample of ETF constituents and the least liquid ETF constituents, a larger part of the variation in individual stock returns or liquidity is explained by market-wide variations. We present evidence that ETF creation and redemption is the transmission mechanism of the comovements. Moreover, we show that the comovements do not appear excessive.

Measurement of the Macro-Efficiency of Hydropower Plants in Nigeria Using Transfer Functions and Data Envelopment Analysis

Persistent power challenges plague Nigeria, with hydropower constituting a vital component of the country's energy mix. This study assessed the macro efficiency of three operational hydropower plants in Nigeria using three distinct methods: Constant Return to Scale Method of Data Envelopment Analysis (DEA-CRS), Input-oriented Variable Return to Scale Method of Data Envelopment Analysis (DEA-VRS), and System's Coefficient of Performance Methodology (SCOPM) employing transfer functions. Input factors included man-hours, plant capacity, and water flow, while energy generation was the output. DEA-VRS revealed Shiroro and Jebba as the most efficient, while Kainji was the least. DEA-CRS indicated Shiroro as the most efficient and Kainji as the least. SCOPM indicated Jebba as the most efficient and Shiroro as the least. SCOPM's higher standard deviation suggests better discrimination among plants. DEA-VRS result showed that the scale of the biggest power plant, Kainji, has some effects on its efficiency. The study recommends the adoption of SCOPM by electricity utility operators and regulators for performance improvement due to its robust results. The contributions of the research are significant because of the novel application of DEA and SCOPM to measure the efficiency of power plants in Nigeria, and SCOPM for measurement of macro efficiency of power plants.

Kinerja Keuangan Terhadap Return Saham

This research aims to see the effect of financial performance on stock returns. Stock returns in this study are the dependent variable while financial performance is represented by liquidity and leverage proxies.This type of research is quantitative. The research sample is companies that issue sukuk listed on the Indonesia Stock Exchange in 2017-2021, consisting of 7 companies with five years of observation and the sample determination method used is purposive sampling. The analytical method in this research uses panel data regression analysis with a fixed effects model using Eviews version 10.0. The research results show that the variables liquidity and leverage simultaneously influence stock returns. Meanwhile, partially the Liquidity variable has an effect on Stock Returns. The leverage variable influences stock returns.

Banks’ financial performance analysis: an experience from an Islamic economy

Purpose This study aims to analyze the performance efficiency of private commercial banks in Iran as an Islamic economy. Design/methodology/approach A meticulously chosen sample comprising 15 private banks from 2020 to 2023 has been examined. This study uses data envelopment analysis (DEA) models, specifically the Constant Returns to Scale (CCR) with input orientation and the Variable Returns to Scale (BCC) with input orientation, to scrutinize performance efficiency relative to the banking sector’s average efficiency ratio. Findings The findings indicate that the performance of decision making units is superior in BCC models when determined with CCR models. The CCR-I analysis spanning 2020–2023 reveals that only two banks consistently demonstrated full efficiency performance, attaining a 100% efficiency score across all years. The observed fluctuations in banks’ efficiency performance are attributed to disparities between the growth or reduction in inputs and the corresponding augmentation or diminution in outputs. Research limitations/implications This paper has some limitations. First, selecting inputs and outputs for the DEA models is crucial, as this study’s results are sensitive to these choices. Second, this research focused exclusively on the efficiency of private banks and did not assess the efficiency of governmental banks. Practical implications The insights from this study can be valuable for bank managers in evaluating performance, regulators in maintaining financial stability and investors and market analysts in enhancing their investment strategies through bank performance analysis. Originality/value To the best of the authors’ knowledge, this study is the first to propose a framework for evaluating and forecasting commercial bank performance in an Islamic background. This model for prediction performance would be helpful for future research on the banking sector. In addition to improving Islamic banking literature, this research contributes to the literature regarding the analysis methods usually used.

Cross-Sectionnal Patterns in Moroccan Sock Returns: A Fama-French Perspective

Drawing on the Fama and French models, we examine the role of market factor (beta), fundamental characteristics (size, book-to-market, profitability and investment) and the momentum in explaining cross-sectional stock returns in the Moroccan market. The sample consists of non-financial stocks over the period from July 2008 to June 2020. In this research and for the first time, we contribute to the current body of asset pricing literature by embracing three different empirical methodologies. First, we use an adaptation of cross-sectional methodologies from Fama and MacBeth (1973) and Fama and French (1992). Second, we opt for portfolios as dependent variables to reduce potential estimation errors associated with individual stocks. Third, we specifically adjust for the errors-in-variables issue using the methodology proposed by Brennan et al. (1998). Our results indicate that beta coefficients are statistically insignificant in both first and second methodologies. Furthermore, none of the characteristic’s variables meet the criteria for a good explanatory variable, as they fail to consistently exhibit a significant level of significance in all cases. Generally, the momentum factor emerges as the most promising variable. We conclude that the tested models are incomplete in explaining variations in Moroccan stock returns. Even after adjusting for model risk, some effects persist.

Using the SPY Index for Linear Regression Analysis of AAPL Stock Returns

This study investigates the predictive relationship between Apple’s (AAPL) stock returns and the SPY index, representing the S&P 500. Utilizing a linear regression model, we aim to quantify the extent to which changes in the SPY index can explain variations in AAPL returns. Our findings show that the model parameters—an intercept (Beta0) of 0.001 and a slope (Beta1) of 1.067—indicate a strong positive correlation between these variables. The model’s predictive accuracy is validated using Root Mean Square Error (RMSE), with an in-sample RMSE of 0.000123 and an out-of-sample RMSE of 0.000234. We also introduce a hedging strategy to mitigate risks associated with market volatility. This research contributes to the field by providing a robust, data-driven framework for predicting stock returns and managing risk.

Analysis of the Impact of the Merger on Trading Volume, Return and Abnormal Return of BSI Shares

This study discusses in trading volume, return and abnormal return of Bank Syariah Indonesia (BSI) stocks before and after merger. The purpose of this study was to determine the results of the analysis of differences in trading volume, stock return and abnormal returns before and after the merger of Bank Syariah Indonesia (BSI). The variables used are trading volume activity (TVA), stock returns and abnormal returns. The sample in this study was 10 days before and 10 days after the merger of PT Bank Syariah Indonesia Tbk. As for the sampling technique using Purposive Sampling. The results of this study are based on results of the different Paired Sample T Test on the TVA variable showing the Sig. (2-tailed) value of 0,002 < 0,05. Based on the results of the Wilcoxon different test, the value Sig. (2-tailed) value on the stock return variable was 0,114 > 0,05, then Sig. (2-tailed) value on the stock abnormal return variable was 0,139 > 0,05. So it can be stated that there are differences in Bank Syariah Indonesia (BSI) before and after the merger based on the TVA variable and there are no difference in Bank Syariah Indonesia (BSI) before and after the merger based on the return and abnormal stock returns variables.

The Use of the Data Envelopment Analysis–Malmquist Approach to Measure the Performance of Digital Transformation in EU Countries

Currently, the process of the digital transformation of EU countries is very important and often discussed. It will not only bring new opportunities for companies and the broader population but will also enable the transition to a more ecological economy. An important goal is to speed up the digitalization processes taking place in companies. It is very important to use already established digitalization elements more efficiently. This also resulted in the motivation for the given research. The aim of this paper is to quantify the change in the efficiency of the digital transformation of EU countries. As part of this research, the Variable Returns to Scale Data Envelopment Analysis (VRS DEA) model and the Malmquist index (MI) based on the DEA approach were applied. The results of the model made it possible to assess how the changes in technical efficiency and technological changes contributed to the changes in efficiency. The long-term theoretical added value of this paper lies in its proposal for countries and their governments to monitor not only the number of introduced digital elements, but also the efficiency of their use relative to some aggregate output; for example, GDP (Gross Domestic Product) or unemployment rate. The added value of this research is that less developed countries use digitalization elements more effectively than developed countries.

Pitfalls in the assessment of higher education learning gains in Brazil through multilevel regression: handling the ceiling effect.

This work assesses the validity of the Brazilian Indicator of the Difference between Observed and Expected Performances (IDD), which applies a multilevel regression model to rank university courses. It proposes a methodology to test for inconsistencies and research for the causes. With this objective, we develop an experimental methodology, applied to a database with 4,432 production engineering students distributed over 329 undergraduate courses, from the government’s National Institute for Educational Studies and Research. We display a graphical analysis of the expected and achieved grades in final graduation exams, the gap in which determines the learning gains for every course. Then we apply the multilevel linear regression model of the IDD in a particular scenario, to test for consistency in value-added learning measurements using the technique reductio ad absurdum. The result reveals that the present methodology for the calculation of the IDD is inadequate and inconsistent, and that this can be explained by the ceiling effect. It needs to be radically revised to prevent unfair judgements. Finally, we propose and implement a production frontier technique to correct for the ensuing ceiling effect, namely a variable returns to scale data envelopment analysis model for adjusting the measurements using evidence based benchmarks.

FORECASTING THE REALIZED VOLATILITY OF ISLAMIC EQUITIES USING MULTIVARIATE HAR-TYPE MODELS

This study proposes nine multivariate intraday models using various realized variation measures with the aim to improve volatility forecasting in the Islamic stock market in Malaysia using a dataset from 1st April 2008 to 31st March 2018. The findings show that considering independently the jump-robust realized volatility, additional daily jump realized volatility, and continuous and discontinuous jump sample path variations improved the in-sample predictive regressions compared to using the standard realized volatility. For the out-of-sample volatility forecasts evaluation, it is observed that the volatility models that disentangled the realized volatility into its continuous and discontinuous jump components have outperformed the rest of the proposed models. This is because both the continuous and discontinuous variation of returns exhibit distinctive substantial information in yielding the final volatility dynamic and thus should be modeled disjointedly. However, the empirical results suggest that the simple autoregressive specification using the standard realized volatility is often performing better or as well as the new extension models. Lastly, this study may provide useful insight in portfolio management, risk assessment, and asset pricing, particularly in the Shariah-compliant equities.

Analysis of the relationship among technical efficiency, competitive strategy, and export performance in the cocoa agroindustry in Indonesia

The goals of the current study are to analyze the technical efficiency of the Decision Making Unit (DMU) of the cocoa agroindustry and the relationship among technical efficiency, export performance, and competitive strategy in the cocoa agroindustry in Indonesia. Respondents in this study are production and marketing managers at 42 active DMUs. The results show that the average DMU technical efficiency value is 0.963 and 0.985 based on the models of Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS), with the distribution of the full technical efficiency category of 80.95%, the high category of 16.67%, the medium category of 2.38%, and the low category of 0%. This study finds a model for increasing the export performance of the cocoa agroindustry, in which the technical efficiency variable has a significant positive effect on the export performance variable with competitive strategy variables as an intervening variable.

Evaluating and Improving Relative Efficiency The Banking Sector in Iraq Using Data Envelopment Analysis of The Output-Oriented VRS Model With Application

The banking sector is one of the important sectors in Iraq, and the last stage witnessed the emergence of several private banks in the competition market, and in order to determine the efficiency of existing banks, the resources available to government and private banks were analyzed and compared with two international banks to determine their efficiency ratios for the surveyed banks using data envelopment analysis, the research problem was diagnosed in the lack of interest in measuring the efficiency of banks by exploiting the resources available to maximize profits, the aim of the research is to determine the efficiency of the banks studied according to the direction of outputs and to conduct continuous analysis of the results in order to come up with recommendations that contribute to improving the banking sector. The research focused on the direction of increasing outputs with constant inputs in order to maximize returns. The( Deap2.1) data analysis program was used, and the research adopted data for 2022 to measure efficiency. For 22 banks operating in Iraq (governmental and private) and two banks outside iraq, the variable volume returns (VRS) model was used, and the most prominent results achieved were the achievement of banks The following banks (Rasheed, industrial, TBI, Al-Ahli, Asia, National,trans-Iraq, Jordanian capital, Lloyds Banking Group London) achieved high efficiency100% as they used their resources optimally. The investment bank achieved 90.8%, which is a good percentage, with the ability to benefit from the expertise of industrial and national banks, Jordanian capital, and Lubd's Banking Group London to reach 100% efficiency in 2022.

Application of DEA Models to Develop Strategies for Improving the Energy Efficiency of National Economies: Focusing on SDGs and Best Practices in European Countries

Objective: This study aims to develop a strategy for improving the energy efficiency of national economies through the application of DEA (Data Envelopment Analysis) models. The research focuses on adopting the best practices from European countries in the context of SDGs. Theoretical Framework: The research is grounded in the framework of sustainable development and energy efficiency, focusing on the UN Sustainable Development Goals (SDG 12). DEA models are utilized to assess energy efficiency across various European economies, considering economic, environmental, and energy-related factors. Method: DEA models were applied to assess energy efficiency by analyzing input variables such as energy intensity, CO₂ emissions, and energy consumption. The model used a comparative analysis of 38 European countries, with special attention to the weights (λ) in the VRS model, allowing for variable returns to scale. The data were sourced from Eurostat and the World Bank. Results and Discussion: The results indicated that countries like Ireland and Albania serve as key reference units for Ukraine, highlighting the effectiveness of transitioning to renewable energy sources and reducing dependence on fossil fuels. The analysis demonstrated that inefficient countries could improve their performance by following the strategies of their reference units, specifically in reducing energy consumption and emissions. Research Implications: The study provides practical insights into how less efficient countries, like Ukraine, can enhance their energy policies by adopting successful practices from European nations, ultimately contributing to global sustainability goals. Originality/Value: This research contributes to the literature by offering a structured methodology for enhancing energy efficiency in national economies through DEA modeling. It emphasizes the significance of renewable energy in sustainable development and presents a comparative framework applicable to a broad range of countries.

Pengaruh Rasio Profitabilitas & Solvabilitas terhadap Harga Saham Perusahaan SubSektor Makanan dan Minuman yang Terdaftar di BEI Periode 2017-2021

The purpose of this study is to investigate how debt to equity ratio and return on equity affect the stock price of publicly traded food and beverage companies on the Indonesia Stock Exchange between 2017 and 2021. This research technique takes a quantitative approach. For this investigation, eight food and beverage companies listed on the Indonesia Stock Exchange were carefully selected using a purposeful selection technique. From 2017 to 2021, sampling was carried out every three months. SPSS 27 software, which consists of a number of tests including traditional assumption tests, was then used to evaluate the data. Normality, multicollinearity, autocorrelation, and heteroscedasticity of the data were assessed with this test. Furthermore, the coefficient of determination, partial test, simultaneous test, and descriptive statistical test were run. The results of this study indicate that in the period from 2017 to 2021, the variables Return on Equity and Debt to Equity Ratio will partially and simultaneously affect the stock price of food and beverage companies listed on the Indonesia Stock Exchange.

Bond market structure and volatility

AbstractWe apply variance ratio methodologies to examine market quality in the US corporate bond market. We find that the open‐to‐open to close‐to‐close return variance ratio is greater than one suggesting that the corporate bond market is less efficient during the opening hours than during the closing hours. We show that the higher variance ratio at the open is related to the market power of dealers at the open and the sources of power are from lower cost of inventory, lower asymmetric information, and more flexibility to intermediate a trade. Dealers appear to exert less market power for bonds with low volume and credit rating. The results are consistent with dealers behaving strategically to unload risky assets and take on safer assets.

CORPORATE GOVERNANCE, INVESTMENT STRATEGY, MACROECONOMIC VARIABLES AND FINANCIAL PERFORMANCE OF PENSION SCHEMES IN KENYA

<p>The study investigated the impact of corporate governance (CG), investment strategy (IS) and macroeconomic variables on the financial performance of pension schemes in Kenya, thereby addressing the key research question: What is the effect of CG, IS and macroeconomic variables on the financial performance of pension funds in Kenya? Qualitative, quantitative and correlational research designs were used to assess the effect of these factors on the financial performance of pension funds. Quantitative data on the annual return of pension funds and macroeconomic variables from 2012 to 2020, as well as qualitative data on CG indicators and IS, were used in the study. Return on investments proxied pension fund performance. Primary data was collected using survey questionnaires from the pension schemes from both the CG and IS indicators to develop both CG and IS indices. The findings show that CG, as well as IS and macroeconomic variables, impact pension funding differently. The effect of CG indicators on pension performance was positive and significant. The intervening effect of IS on the link between CG and pension performance was significant, while the moderating effect of macroeconomic variables was significant. The individual contribution of both CG indicators and macroeconomic factors on pension performance, nonetheless, varied. The main conclusion of the study is that pension fund financial performance is influenced by CG, IS and macroeconomic factors implying that there is a need to take into account the impact of these factors in the execution of investment plans of pension funds to ensure the generation of adequate funds for retirement benefits.</p><p> </p><p><strong>JEL: </strong>G23, G32, G34, E44, O55<strong></strong></p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0715/a.php" alt="Hit counter" /></p>

Efficiency decomposition and frontier projection of two-stage network DEA under variable returns to scale

The efficiency decomposition and frontier projection of traditional two-stage network data envelopment analysis (DEA) model under variable returns to scale (VRS) are often not equivalent; which not only contradicts DEA theory, but also reduces the scientificity of the model. The main reason for this inequivalence is that there is a synergistic effect of variable scale return in two different stages. Therefore, this paper describes the production frontier of two-stage DEA under VRS for analyzing this synergistic effect, and then the efficiency evaluation pitfalls of two-stage DEA under VRS are identified. From the input orientation, output orientation, non-orientation perspectives, different two-stage network DEA models under VRS are respectively constructed to solve these evaluation pitfalls, and the equivalence relationships of their multiplier model and envelopment model are proved; and then the efficiency decomposition and frontier projection with equivalence relationship can be obtained to meet the different needs of decision-makers. Furthermore, variable intermediate element is discussed in the non-orientation model for achieving the Pareto optimality of two stages during the process of efficiency decomposition and frontier projection. By these models, the theoretical foundation of two-stage network DEA under VRS has been further improved. Finally, two examples are provided to illustrate the effectiveness of the new models.

Valuation and Returns on Stock Return Volatility

ABSTRACT This paper provides an accounting-based valuation model that predicts that cross-sectional variation in firm-level returns to investments in both stock and stock return volatility are related to cross-sectional variation in firm-level fundamentals. The model predicts that expected stock returns have a positive quadratic relation with stock return variance and a negative quadratic relation with gains to trading in stock return variance. Consistent with these predictions, firms with high model-implied expected stock returns have high future stock return variance, and the relation is roughly quadratic. In contrast, firms with high expected stock returns have low future returns to trading in stock return variance through option contracts because these firms have high option-implied variance relative to future realized variance, i.e., low variance risk premia (VRP). The study provides a framework for using fundamentals for trading in individual stocks and options. JEL Classifications: G12; G14; G17.