Positive EVA Research Articles

Financial Performance Analysis Using Economic Value Added and Market Value Added Methods

This study aims to determine and analyze financial performance with the Economic Value Added and Market Value Added methods in the Cement Sub-sector companies listed on the Indonesia Stock Exchange for the 2017-2021 period. The research method used is a quantitative method with a descriptive approach and the sampling technique in this study is a purposive sampling technique. The data collection techniques used used secondary data through library studies and documentation studies obtained through the website https://www.idx.co.id in the form of a Balance Sheet and Profit and Loss Report for the Year 2017-2021. The results of this study are that the three cement companies have a positive EVA value which means they have succeeded in creating economic value, and one company has a negative EVA value at PT Semen Baturaja Tbk which means the company is not able to provide added value in 2021. means providing added value through market capitalization value.

Financial performance analysis using economic valued added method on the sub sector of cigarette listed on the Indonesia Stock Exchange

This study aims to determine the financial performance using the Economic Value Added method in the cigarette sub-sector listed on the Indonesia Stock Exchange for the last five years. The research method used is a quantitative method with a descriptive approach. The data used is secondary data in the form of Company Financial Statements obtained from the official website of the Indonesia Stock Exchange. The results of the study are based on an analysis using the EVA method from five food and beverage companies that have good financial performance (positive EVA) during the 2016-2020 period, namely, GGRM and WIIM. Analysis of the company's performance with the method shows the EVA fluctuating results. This is because the value of NOPAT and capital charges is very influential on EVA results. Where if the NOPAT value is greater than the value of capital charges, the resulting EVA will increase and vice versa.

Employee Value Added: A New Measure of Gain‐Sharing between Labor and Capital

Most investors are aware of economic profit concepts that compare company profits with the opportunity cost of the capital used to generate those profits, but few investors try to compute similar value added measures for employees, or to assess whether employee value added is aligned with investor value added or whether such alignment is beneficial for investors. The fact that 85% of public companies do not report total employee pay suggests an opportunity for companies to improve both their disclosure practices and their ability to measure stakeholder outcomes and their alignment with shareholder interests.In this article, the authors show how to estimate the following for U.S. public companies: employee pay (for those that don't already report it); average alternative or “market” pay; and employee value added, which is the aggregate after‐tax difference between actual and market pay. Reflecting the tendency of public companies to pay more than other private‐ and public‐sector “civilian” employers, the authors show that the aggregate employee value added at S&P 1500 companies in 2020 represented 30% of the total value added of investors and employees—a number that has been rising more or less steadily from zero since the early 1990s. The not so good news, however, is that the authors find little difference in employee value added between positive and negative EVA companies.To further explore the relationship between employee and investor value added, the authors present a methodology for measuring four key dimensions of employee value added: alignment with investor value added; employee pay leverage; relative pay risk; and the employee pay premium for baseline performance (at zero investor value added). After illustrating those measures in a comparison between Costco and Walmart, the authors' analysis shows that a small number of companies like Costco treat employees more like equity holders with high alignment, but also higher pay risk and a lower pay premium at zero investor value added. The vast majority of U.S. companies appear to be more like Walmart than Costco in treating employees more like bond holders with low alignment with investors, but also lower pay risk and a higher pay premium for baseline performance (or zero investor value added).

Performance Evaluation of BUMN Perkebunan After Restructuring

SOE’s (BUMN) restructuring is one of the government's efforts to improve the performance and competitiveness of companies. However, this doesn’t necessarily occur due to differences in the challenges of change in each SOE. Therefore, to understand the impact of restructuring research on the performance evaluation of BUMN Perkebunan is needed. Data collection was carried out in May-November 2017 at Holding Perkebunan Office, Jakarta. The data used is secondary data in the form of company financial statements for the period 2012-2016. The data was processed by EVA methods to determine the economic value added to the company. The results showed that the highest and the only positive EVA was achieved before the restructuring, namely in 2012. After that, the EVA continued to decline and was at its lowest point in the third year after restructuring, namely in 2016. This decrease occurred due to the influence of components that support EVA, such as corporate income and expenditure, beta (s), return market (rm), risk-free (rf), and the capital structure. To increase the EVA, the company has to make improvements by increasing the income, reducing the expenditure, reviewing the interest rate (rf), and keeping the proportion of capital structure.Keywords: Restructuring, BUMN Perkebunan, Performance Evaluation, EVA

ANALISIS ECONOMIC VALUE ADDED / EVA (Studi Analisis pada Perusahaan Manufaktur Sub Sektor Rokok di BEI)

This study aims to determine the financial performance of cigarette manufacturing companies listed on the BEI by using EVA analysis, and prove positive accounting earnings will have or do not have a positive EVA value. By using sample 4 (four) cigarette manufacturing companies listed on BEI, the result of this research mention that there are 3 of 4 or (75%) cigarette manufacturing companies listed on BEI experiencing EVA > 0 value, and profit positive accounting does not necessarily make the EVA value positive as well. This is due to an increase in the cost of equity capital that contributes the largest cost to the WACC figure which results in high capital charger borne by the company.

Kinerja Keuangan Bank Umum Syariah Di Indonesia Dengan Pendekatan Metode Market Value Added (MVA)

This study aims to determine the financial performance of the 2014-2016 Market Value Added (MVA) method in Islamic commercial banks in Indonesia. The sample determination technique used in this study is to use the type of purposive sampling, namely the criteria of having financial reports published and audited in the period 2014 to 2016 and complete financial statements from the period 2014 to 2016 with calculations using the MVA method (Market Value Added. The results show that the financial performance of BUS in this period has a positive average value using EVA and MVA. This situation shows that the positive EVA and MVA values are in good condition and have more economic added value after the company pays all obligations to the funders or creditors according to their expectations, so that the company's profits provide economic value for the company.

KINERJA KEUANGAN DENGAN METODE EVA (ECONOMIC VALUE ADDED) PADA BPR TANJUNGPINANG

EVA is a method of financial management to measure the economic profit in a company that states that prosperity can only be created when the company is able to meet all operating costs and capital costs. With EVA method can be known whether PT BPR Central Sejahtera Tanjungpinang happened addition to its economic value. The research method used is qualitative descriptive method. The EVA classification can be calculated from the NOPAT (Net Operating Profit After Tax) component, WACC (Weighted Average Cost of Capital) and IC (Invested Capital) contained in the financial statements of PT BPR Central Sejahtera Tanjungpinang with data from 2012 until 2017. This research reveals a positive EVA result in 2012 with an EVA of 63,515,000, in 2013 with EVA of 2,138,086,000, in 2014 with EVA of 73,105,000, in 2013 with EVA of 797,470,000 and in 2014 with an EVA value of 714.750.000. In addition to these positive results, the study also revealed negative EVA results in 2015 with an EVA value of minus 65.06 million. From the analysis results obtained conclusion that the financial performance of PT BPR Central Sejahtera Tanjungpinang quite good. PT BPR Central Sejahtera Tanjungpinang can add value to the company in 2012,2013,2014,2016 and 2017, except in 2015, PT BPR Central Sejahtera Tanjungpinang is considered failed to increase its economic value

Pengaruh Kinerja Berbasis Penciptaan Nilai Dan Variabel Makroekonomi Terhadap Return Saham Industri Pakan Ternak

The creation of value-based performance measurement can be an alternative in measuring the company's financial performance. Results can be used as indicators of assessments by investors, and these indicators can influence the stock returns. Besides, macroeconomic variables also affect stock returns. This study aimed to analyze the financial performance of companies in the process of creation of value-added with EVA, MVA, and Tobin's Q approach. Impacts of these performance measurements and macroeconomic variables (exchange rates, interest rates, and inflation) on stock returns of the subsector animal feed industry were studied. Descriptive analysis was applied in analyzing the company's financial performance. The impacts of the company financial performance and macroeconomic variables were assessed by using panel data regression analysis. The results related to the company's performance showed that 1) EVA performance dominantly obtained a positive EVA value; 2) MVA performance predominantly produced a positive MVA value in 3 companies and a negative MVA value in the other company; 3) Tobin’s Q performance predominantly generated a value of Q>1 in 2 companies and a value of Q<1 in the other 2 companies. The results of the panel data regression analysis concluded the independent variables influencing the stock return were the performance variables while the macroeconomic variables had no effects on stock return. Keywords: macroeconomic variables, panel data regression, stock return, subsector of animal feed, value-based performance

Prediction of Economic Value Added status of Tehran Stock Exchanges by using Genetic Algorithm

The main purpose of this article is to present a model to predict the status of economic value added of Tehran Stock Exchanges by using Genetic Algorithms. Investors’ concern of the return of principle as well as profit of their investment has led us to forecast status of economic value added as a basis to evaluate companies’ performance. Predicting the status of economic value added is one of the ways that can be used to exploit investment opportunities and also to avoid waste of resources. Firstly, necessary warnings can alert companies toward their future performance, moreover investors can recognize good and unfavorable investment opportunities. In this research, independent variables are defined as: Equity premium Reserve, R &amp; D Reserve, Precautionary Reserve, Legal Reserve, Special Reserve, Capital expenditures, Interest Bearing Liabilities, Finance Costs, Capital, Sum of Equity, Long Term Receivables, Nopat, Return of Capital, Investing, Accumulated Profit and Loss, Earning after interest and tax, Receivable Financing Facility and Economic Value Added is as a Dependent variable. The studied population is the accepted companies in Tehran Stock Exchange for the period of 1385 to 1391. At first, by using average test among the variables, those variables that have a significant difference in the two groups of firms with positive EVA and negative EVA are specified. To do so, independent sample T Test from SPSS software is used. Then, using the techniques of Genetic Algorithms, Which is one of the best evolutionary algorithms, variables with greatest ability to distinguish between positive EVA and negative EVA are specified then the predictive model is derived. Derived model from the algorithm enabled us to classify the companies with negative economic value added into the correct categories of negative and positive economic value added, one year prior to the occurrence of negative EVA, with an accuracy of 83%.

Prediction of Economic Value Added status of Tehran Stock Exchanges by using Genetic Algorithm

The main purpose of this article is to present a model to predict the status of economic value added of Tehran Stock Exchanges by using Genetic Algorithms. Investors’ concern of the return of principle as well as profit of their investment has led us to forecast status of economic value added as a basis to evaluate companies’ performance. Predicting the status of economic value added is one of the ways that can be used to exploit investment opportunities and also to avoid waste of resources. Firstly, necessary warnings can alert companies toward their future performance, moreover investors can recognize good and unfavorable investment opportunities. In this research, independent variables are defined as: Equity premium Reserve, R &amp; D Reserve, Precautionary Reserve, Legal Reserve, Special Reserve, Capital expenditures, Interest Bearing Liabilities, Finance Costs, Capital, Sum of Equity, Long Term Receivables, Nopat, Return of Capital, Investing, Accumulated Profit and Loss, Earning after interest and tax, Receivable Financing Facility and Economic Value Added is as a Dependent variable. The studied population is the accepted companies in Tehran Stock Exchange for the period of 1385 to 1391. At first, by using average test among the variables, those variables that have a significant difference in the two groups of firms with positive EVA and negative EVA are specified. To do so, independent sample T Test from SPSS software is used. Then, using the techniques of Genetic Algorithms, Which is one of the best evolutionary algorithms, variables with greatest ability to distinguish between positive EVA and negative EVA are specified then the predictive model is derived. Derived model from the algorithm enabled us to classify the companies with negative economic value added into the correct categories of negative and positive economic value added, one year prior to the occurrence of negative EVA, with an accuracy of 83%.

Does manager in better economic value added’s companies feeling more satisfied? An investigation of EVA’s role in mitigating agency problem proxies: empirical research from emerging market sample, namely Indonesia

This research is formulating the cause of agency conflict into three factors. The first one is agent unsatisfactory on the existing compensation system. The second is the high ratio of free cash flow in the company. The last is the absence of good monitoring on the company operation. Based on those three factors, this research aims to find a full perspective of these occurrences. One of the tools to investigate it is using EVA® as investigator tools, which is relatively new as a performance measurement in Emerging Market. The proxy variables on agency conflict are new investment ratio and total asset turn over. The control variables are dividend payout ratio and leverage. There are two research questions that being addressed in this research. The first, if there are any differences in agency conflict proxies between companies that have positive EVA® in their performance and companies with negative EVA®. The Second is to analyze if EVA® has significant role to influence the behavior of manager which tend to trigger the agency conflict within the company. The Methodology of this research was paired t-test data comparison between positive EVA companies and negative EVA. In addition, we analyzed the relationship of variable within the model with Data pool from 2002 until 2011To sum up the methodology; we tested the model with robustness test and Causality Test as well. The research finds out that Manager in companies with better EVA® tend to have lower agency conflict level. In conclusion, EVA® is strongly supporting the control variable in explaining its influence on dependent variables or agency conflict proxies.

Does the Wealth Profile of a Company Matter in Discounted Cash Flow Analysis? Valuation Implications for Investorsand Managers

This article examines the prospective valuation relationship between MVA and EVA. The author classified companies in the Stern Stewart Performance 1000 Universe in terms of whether they are in a tier 1 wealth profile (top-100 MVAranked companies), a tier 5 wealth profile, or a tier 10 wealth profile (bottom-100 MVA-ranked companies). Overall, the results that the market discounts economic earnings and that the wealth profile of a company matters in particular. Specifically, indicate the market discounts economic earnings for wealth creators, as opposed to the middle-to-low MVAranked companies. Consistent with financial theory, this implies that reliably positive EVA—such as that evident in the wealth creators—has intrinsic value, whereas relatively lowto-negative EVA—as present in low MVA-ranked companies—has questionable fundamental value. The author argues that wealth creators know how to rationalize capital, as they pursue positive NPV opportunities where the return on capital is higher than the cost of capital. On the other hand, low-to-negative MVA-ranked companies face risk pricing challenges as investors question the efficacy of their ability to create shareholder value. Although caveats apply, this prospective valuation of EVA has important pricing implications for investors and managers. <b>TOPICS:</b>Fundamental equity analysis, accounting and ratio analysis, statistical methods

Economic Contribution of Public Passenger Transport Organisations—An Application of EVAR Methodology

Economic Value Added (EVAR) has immense potential for evaluating State Owned Enterprises as it provides an excellent methodology for capturing social and economic contributions of these organisations, instead of merely going by financial returns. If EVA is applied in private enterprises to correct accounting distortions, in public enterprises it can be applied to correct earnings distortions. In this paper we have attempted to extend the EVA Methodology to a State Passenger Road Transport Undertaking (SRTU) in India. This SRTU is relatively a better performing one on operational parameters though it is loss making. This paper captures the opportunity cost of the following three factors which make significant difference to their performance: 1. Loss of revenue from providing concessional fares to students. 2. Opportunity cost of providing services in interior rural areas. 3. Opportunity cost of providing unviable urban schedules. Motor Vehicle Tax is another factor considered. The analysis shows that EVA reflects better performance of SRTUs than accounting profits. The analysis also shows this SRTU has positive EVA under all alternatives for the six years considered, though it has been loss making according to accounting statements. EVA gives a valuable framework for inter and intra-organizational performance evaluation across SRTUs.

Penerapan Economic Value Added untuk Memaksimalkan Nilai Perusahaan: Studi Kasus PT XYZ

EVA is an indicator about the value creation from an investation. Positive EVA indicate that a company is sucess in creating added value for share holders. That sincronize with the purpose to maximize the company value. Applying EVA concepts on company will encourage the management to find out the true cost of capital of the company so the level of clean return from capital will be shown clearly.

Shareholder Value Creators and Shareholder Value Destroyers in USA: Year 2001

In this paper, we quantify shareholder value creation for 276 American companies. We provide the created shareholder value for each and every company for years 1998, 1999, 2000 and 2001. The market value of the 276 companies was 8,716 billion dollars in 2001 and 9,729 billion dollars in 2000. We define created shareholder value and provide the ranking of created shareholder value for the 276 companies. In 2001 Microsoft was the leading shareholder value creator and, on the other end of the spectrum, Cisco was the top shareholder value destroyer. We also calculate the cumulative created shareholder value of selected American companies during the four-year period 1998-2001. Wal-Mart Stores was the first company in created shareholder value companies during the four-year period 1998-2001. We also claim that EVA does not properly measure Wealth Creation. We have compared EVA calculated by Stern Stewart and Co with created shareholder value of 269 companies. The correlation of EVA with created shareholder value was only 17.66%. 60 companies had negative EVA and positive created shareholder value. 64 companies had positive EVA and negative created shareholder value. On average, the difference of shareholder value creation minus EVA was -434% of EVA. The absolute value of the difference of shareholder value creation minus EVA was 8972% of EVA. With this evidence, we conclude that EVA does not properly measure Wealth Creation.

Surface characterization of EVA copolymers and blends using XPS and ToF‐SIMS

AbstractThe surface chemistries of semi‐crystalline copolymers of ethylene (CH2CH2) and vinyl acetate (CH2CHCO2CH3) (EVAs) and blends of these copolymers with low‐density polyethylene (LDPE) have been examined critically for the first time using angle‐resolved XPS and time‐of‐flight SIMS (ToF‐SIMS) analyses. Specimens were fabricated using a variety of methods (commercial extrusion, spin coating and thermal compression) to determine the influence of processing conditions on EVA surface chemistry. The XPS and ToF‐SIMS analysis of these specimens has provided techniques for identifying surface EVA (also thermal oxidation), has provided both XPS and ToF‐SIMS methods for quantitative EVA analysis and has revealed the details of EVA surface chemistry. The XPS core‐level spectra indicate the presence of the ester (VA) and ether (surface oxidation) species, but do not provide positive EVA identification. The ToF‐SIMS spectra show features specific to both the ethylene and vinyl acetate portions of the polymer. Both XPS and ToF‐SIMS analyses have been calibrated to provide quantitative VA (error &lt; 2 wt.% VA) and oxygen (error &lt; 1.0 at.% oxygen) analyses. Surface VA content was found to increase linearly with bulk VA content, and was not influenced by the type of fabrication method used. The EVA surfaces appear to consist of two layers. The near‐surface region (&gt; 20 Å depth) is dominated by a VA‐poor (ethylene‐rich) layer. This region is covered by a thin (⩽20 Å thick) VA‐enriched layer.