Financial Ratios
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2021 ◽  
pp. 1-13

NBFIs play an important role in economic development through ensuring proper mobilization of funds in Bangladesh. This study represents a comparison of nine NBFIs operating their business in Bangladesh within the period from 2016 to 2019 through using financial ratios and other measures. To analyze the financial performance this study has used ratio analysis, such as ROA, ROE, ROCE, Institutional size/ Total assets and total equity etc. The outcome of this study says that for generating return the NBFIs performance based on efficiency ratio is different from the performance based on liquidity ratio, capital ratio and other financial measures. This study suggests to NBFIs to be more conscious about loan selection and establish a brand image through providing more efficient services. It also suggests the NBFIs to finds more income generating areas to be more competitive. In the coming years NBFIs will have more prospects that will ensure the economic development of our country.


2021 ◽  
Vol 39 (12) ◽  
Author(s):  
Murniati Murniati ◽  
Ghozali Maski ◽  
Iswan Noor ◽  
Marlina Ekawaty

Tourism as one of the potential resources in Indonesia significantly affects the country's development. However, it has not been well-managed due to many obstacles such as financing, promotion, and natural disasters. This study aimed to identify tourism attractions in Banyuwangi Regency as a newly developing district in Indonesia. The quantitative approach with the descriptive analysis applied in this study indicated that that the leading tourist attractions in Banyuwangi have excellent economic growth potential and good financial ratios. Based on the results of Financial Analysis analyzed through variables Payback Period (PP), Average Rate of Return (ARR), Net Present Value (NPV), Internal rate of Return (IRR), and Profitability Index (PI), Banyuwangi has the potential feasible for investment in the tourism sector. This research would provide further consideration for investors before investing in the tourism sector in Banyuwangi Regency.


2021 ◽  
Vol 5 (S4) ◽  
Author(s):  
Marián Smorada ◽  
Andrea Lukáčková ◽  
Zuzana Hajduová ◽  
Ľudovít Šrenkel ◽  
Ján Havier

The focus of this presented work is the application of one-dimensional discriminant analysis in specific conditions of economic practice. The research sample of the enterprises has shown, that even these methods can better warn against nearing bankruptcy by predicting whether business will or will not be sustainable. Generally, these discriminant analyses use the financial ratios methods. The future situation of an enterprise can be predicted, among other things, by means of one-dimensional and multidimensional discriminant analysis methods, which are dealt with by several authors. Given the different approaches of authors, one-dimensional discriminant analysis methods that are "older" can be assumed to have a different reliability than multidimensional discriminant analysis methods. The assumptions of our research were verified in a group consisting of prosperous and non-prosperous business entities. The results of the original research show that one-dimensional discriminatory methods had a higher reliability than the multidimensional ones on the sample of enterprises surveyed. At the same time, it has not been established that a 100% reliable method will be found, but it is good to know the assumptions on which these existing methods work and use a combination of multiple methods.


2021 ◽  
Vol 4 (2) ◽  
pp. 192-214
Author(s):  
Bahri Bahri ◽  
Dicky Arnendra Dwi Nugraha

The Covid-19 pandemic in Indonesia is still ongoing to this day causing the performance and health level of banking profitability to decline and the financial condition of the country disrupted. Banking profitability can be seen in the value of Return On Asset (ROA) to see the effectiveness of banking in making profits by utilizing total assets. The study aims to analyze the effect of financial ratios consisting of Capital Adequacy Ratio (CAR), Non-Performing Loan (NPL), Loan to Deposit Ratio (LDR), Operating Expenditures to Operating Income (BOPO), and Net Interest Margin (NIM) on Return On Asset (ROA) on banking going public listed on the Indonesia Stock Exchange (IDX) during 2020 during the Covid-19 pandemic. The population in this study was 40 banks with 160 data. Data analysis methods use descriptive statistical tests, classical assumption tests, multiple linear regression tests, t-tests, f-tests, and determination coefficient tests. The results of the study proved that partially the variables CAR, LDR, and BOPO had a negative and significant effect on ROA. NIM has a positive and significant influence on ROA. While NPL has no influence and is not significant to ROA in banks registered with IDX in 2020. Simultaneously car, NPL, LDR, BOPO, and NIM variables have a significant effect on ROA. The implications of the results of the study prove that in the time of the Covid-19 pandemic, the condition of banks registered with the IDX is still healthy and meeting the minimum CAR ratio below 8%, meaning that banks still earn profits from the results of credit capital management to customers. The level of insecurity of the number of bad loans is still low and can still overcome. The value of the operating expense ratio of banking operating.


2021 ◽  
Vol 39 (11) ◽  
Author(s):  
Sallama Ibrahim Ali ◽  
Hakeem Hammood Flayyih

In the first decade of the third millennium, shareholding companies faced several crises, with four major crises affecting financial markets, beginning with the collapses of a group of large companies following the Enron Energy company and similar companies in various countries, followed by the financial crisis and the collapse of global oil prices, which quickly ended until the sta As a result, the purpose of this study is to shed light on the role of external audit in assessing bank continuity, as Iraqi banks are among the first institutions and companies to move toward the application of international standards as well as being committed to accounting principles and assumptions, and they face a wide range of risks, the most dangerous of which is financial instability. Furthermore, the Kida model has been adopted in assessing the stability of banks and their ability to meet their obligations and perform their duties through a set of financial ratios that distinguish successful banks from those whose ability is suspect and vulnerable to financial failure, as well as trying to identify the nature of their activities at an early stage. However, using financial ratios, Kida's model was applied to a sample of three Iraqi banks, and the research concluded that the external auditor should use financial analysis models to know and evaluate the banks' continuity in terms of anticipating financial collapse.


2021 ◽  
pp. 231971452110534
Author(s):  
Isha Gupta ◽  
T. V. Raman ◽  
Naliniprava Tripathy

This article aims to examine the impact of mergers and acquisitions (M&A) on the financial performance of the construction and real estate industry, using the broad spectrum of financial ratios. The period of study is from 2011 to 2020, and paired t-test methodology has been used. It is hypothesized that there is a significant difference in the pre-M&A period and post-M&A period. The study findings conclude that profitability ratio and liquidity ratio have improved significantly, whereas leverage ratio exhibits no change in performance. In the efficiency ratio, the fixed-assets turnover ratio substantially improves, but the total asset turnover ratio and current asset turnover ratio show a slight improvement. The study concludes that the Indian construction and real estate company’s financial performance has improved overall for the acquiring firms during the post-M&A period. The study implies that the construction sector supports the synergy hypothesis, stating that M&A will improve synergy during the post-M&A period because of the consolidation of two firms’ resources.


2021 ◽  
Vol 13 (6) ◽  
pp. 38
Author(s):  
Hassan Kablay ◽  
Victor Gumbo

Capital Adequacy Ratio (CAR) plays a very important role in the financial success of banks and acts as a buffer to prevent and absorb any unexpected losses. This study examines explanatory variables that influence CAR for nine banks in Botswana. Multiple linear regression was used for analysis, with CAR as the dependent variable and thirteen financial ratios as the independent variables. The study period is 2015-2019. Based on the data for this period, it was established that out of the thirteen financial ratios utilised, only four were found to have significant impact on the CAR of the nine banks under study, which are: Asset to Equity Ratio (A E), Return on Equity (ROE), Non-Performing Loans Ratio (NPL RATIO) and the Cost-to-Income Ratio (C I). The A E Ratio was found to be the most influential driver of the CAR and the NPL Ratio was found to be the least influential driver of the CAR for the banks under study.


Nova Scientia ◽  
2021 ◽  
Vol 13 (27) ◽  
Author(s):  
Martín P. Pantoja Aguilar ◽  
Guadalupe de Montserrat Pizano Ramírez ◽  
Berenice Lerma Torres ◽  
Miguel Ángel Zavala Vargas

Introduction: in 1968, Altman developed a multivariable predictive Z-score model to assess the probability of a public manufacturing company going to bankruptcy based on financial ratios. Later, Altman (1983) re-stated a more improved Z’’-Score model designed to apply in public or private, manufacturing, or non-manufacturing firms, but also in emerging countries. Prediction of the updated model proved to be highly efficient. This research was conducted to prove the level of accuracy of the Z’’-Score model applied to firms listed in the Mexican Stock Exchange (MSE) since there is little relevant research on this subject.                     Method: this research was conducted under a quantitative approach as a census and its scope was situational with a non-experimental and longitudinal research design. The period covered by this research was 2012-2019 since the data was available for those years under a somehow stable economic situation without significant economic ups and downs. This research considered the integration of a large financial database and the design of a typology to classify and analyze 155 firms based on a standard deviation and average results of 837 Z’’-scores. A second analysis was conducted to prove if the predicted situation (area) by the Z’’-Score corresponded to the real situation in the marketplace for every company. Results: the results showed that the accuracy level of the Altman model decreased when applied to Mexican firms. The error of the model applied to Mexican companies related to those classified in the bankruptcy prediction area was 75 % of misclassification cases. The total error of the model included all areas, or cases, was 18 % of misclassification cases. This model is supposed to be effective within a time frame of two years before a possible bankruptcy. Even considering a longer time frame, the companies located in the bankruptcy prediction area continued having misclassifications representing 57 % of error. The error for the model considering all cases and all areas, was 14 % of misclassification cases. This represented a high level of inefficiency of the model applied to an emerging country companies, such as Mexico. Discussion or conclusion: the model is certainly effective while predicting companies in the areas of non-bankrupt sector and grey, but it was inefficient when predicting the possibility of bankruptcy. It was also demonstrated that the time frame of two years is no longer effective when applying the model to Mexican companies. As a result, more research cases are needed to update the model to perform efficiently in emerging countries including country-specific conditions and considering a different time frame to predict bankruptcy.


Risks ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 200
Author(s):  
Youssef Zizi ◽  
Amine Jamali-Alaoui ◽  
Badreddine El Goumi ◽  
Mohamed Oudgou ◽  
Abdeslam El Moudden

In the face of rising defaults and limited studies on the prediction of financial distress in Morocco, this article aims to determine the most relevant predictors of financial distress and identify its optimal prediction models in a normal Moroccan economic context over two years. To achieve these objectives, logistic regression and neural networks are used based on financial ratios selected by lasso and stepwise techniques. Our empirical results highlight the significant role of predictors, namely interest to sales and return on assets in predicting financial distress. The results show that logistic regression models obtained by stepwise selection outperform the other models with an overall accuracy of 93.33% two years before financial distress and 95.00% one year prior to financial distress. Results also show that our models classify distressed SMEs better than healthy SMEs with type I errors lower than type II errors.


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