scholarly journals Analysis of financial and non-financial factors affecting bond ratings

Author(s):  
I Fadah ◽  
A Ayuningtyas ◽  
N Puspitasari ◽  
I B Yuswanto
2020 ◽  
Vol 9 (1) ◽  
pp. 198-216
Author(s):  
Isam Saleh ◽  
Malik Abu Afifa ◽  
Fadi Haniah

The purpose of this study is to examine the effect of financial factors on earnings management and earnings quality. Moreover, the study examines the role of earnings management as a mediator in the effect of the financial factors on earnings quality. It provides some empirical evidences from an emerging market, especially from the Jordanian market. The study uses a panel data analysis method over a ten-year period (2009-2018). The study population includes all Jordanian insurance companies listed in Jordanian market at the end of the year 2019, and the study sample consists of 20 Jordanian insurance companies (a complete population), giving a total of 200 observations for each variable. The results indicate that all financial factors in the model combined affect the earnings management and earnings quality. In addition, earnings management negatively affects earnings quality, and earnings management fully mediates the effect of financial factors on earnings quality. The study advises that policy makers ought to follow good legislation to curb the company's earnings management activities. Hence, the policy makers need to apply regulations which enrich the company’s effectiveness and efficiency whilst protecting the investors and other interested parties from risk.


2021 ◽  
Vol 6 (2) ◽  
pp. 43-61
Author(s):  
Natalia Popa Antalovschi ◽  
Raymond A. K. Cox

Purpose: The purpose of this study is to ascertain which financial factors affect the price-to-earnings ratios of Canadian firms. Methodology: A sample of 578 Canadian firms, across 11 industries, listed on the Toronto Stock Exchange during 2011 to 2018 is examined. Stock prices and financial statements accounts data is collected from S & P Capital IQ. We compute 27 financial factors to use as independent variables to regress on the price-to-earnings ratio dependent variables employing the Statistical Package for Social Sciences (SPSS) utilizing the software program’s forced, forward, and backward selection methods. Robustness tests are conducted using alternative dates (after the fiscal year end) to discover which model of financial factors best explains the forward price-to-earnings ratio as well as other statistical methods such as analysis of variance. Results: We find a unique model for each of the 3 models based on the forward price-to-earnings ratio date. The financial factors that explain each of the dates after the end of the fiscal year (1 month, 2 months, and 3 months) are the 4 variables: net profit margin, return on investment, total asset turnover, and the natural logarithm of the total assets. For model 3 (1 month after fiscal year end), in addition to the previous 4 factors, the dividends per share is part of the regression equation. All 3 models have strong statistically significant results at an alpha level of one percent. Further, industry effects are deduced and presented. Unique contribution to theory, policy, and practice: The results are unique to a Canadian sample of firms post- International Financial Reporting Standards (IFRS) adoption. Companies can utilize the empirical findings to manage their financial performance to maximize their price-to-earnings ratio. A product of a firm’s higher price-to-earnings ratio is a lower cost of capital which expands the corporation’s investment opportunities. Investors can apply this research to develop investment strategies hinged on price-to-earnings ratios to augment investment returns.


2020 ◽  
Vol 11 (2) ◽  
pp. 187
Author(s):  
Nguyen Vinh Khuong ◽  
Phung Anh Thu ◽  
Do Thi Thu Lieu ◽  
Tran Thi Phuong Anh ◽  
Nguyen Thi My Giau ◽  
...  

The study contributes by providing empirical evidence on the extent to which financial and non-financial factors affect the size of the board of director of listed firms in Vietnam. Based on the data from 80 listed firms on the Vietnam’s stock market in 11 years from 2007-2017, using quantitative research method. We concluded that financial and non-financial factors affect board independence of listed firms in Vietnam. From the research results, it is recommended that listed companies have reasonable and effective corporate management policies, consistent with accounting policies at enterprises.


Author(s):  
Nikita Mehta ◽  
Mamta Brahmbhatt

The purpose of this study is to identify the financial factors that enhance the financial competitiveness of small and medium enterprises (SMEs) in Gujarat, India. The principal component analysis has been applied to extract the financial factors from financial performance ratios of a sample size of 38 stock exchange SMEs, based in Gujarat, India. The ranking has been given to the SMEs based upon their factor score and comprehensive score. The results show that profitability, management efficiency, liquidity and leverage factors are the major factors affecting the financial competitiveness of SMEs. The study covers only one state of the country, and the findings from different states may differ and need to get verified. Despite the highest contribution of SMEs in the GDP of India, there exist very few Indian studies on SME competitiveness. This study contributes to filling this gap.


2021 ◽  
Vol 3 (2) ◽  
pp. 98-107
Author(s):  
Ruspriono ◽  
Bambang Santoso Marsoem

Bonds provide a rating signal for the issuer and investors of the ability to pay off a bond. This study aims to explain the factors that affect the ranking in terms of accounting and non-accounting aspects. This study uses all corporate bonds actively traded on the Indonesia Stock Exchange (IDX) and are denominated in rupiah as of December 31, 2019, sourced from Bloomberg, which consists of 996 companies. The method in the sample is the purposive sampling method. This sample consists of 35 companies with 111 bonds, testing the hypothesis using ordinal logistic regression analysis with SPSS Version 25.0 data processing tools. The results showed that liquidity had a positive effect on bond ratings, activity does not affect bond ratings, leverage, profitability, maturity, and auditor reputation have a negative effect on bond ratings.


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