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This paper demonstrates the relationship between CAMELS ratios and credit ratings of deposit banks in Turkey. Annual data was used for the period between 2004 and 2014 in this study. Moreover, 20 deposit banks of Turkey were analyzed and 21 different ratios of CAMELS components were used. In addition to that, credit ratings of these banks were provided from Moody’s corporation or annual activity reports of the banks. After that, we created multi nominal logistic regression analysis in order to illustrate the relationship. The major finding in this study is that three components (Asset Quality, Management Quality, and Sensitivity to Market Risk) of CAMELS have effects on credit ratings whereas the ratios related to Capital Adequacy and Earnings are not effective. As a result, it was recommended that Turkish deposit banks should concentrate on the percentage of fixed assets and interest income to have a better rating. Moreover, having high market share with respect to total assets and lower interest expense are also other important points for this purpose. On the other hand, Turkish deposit banks should control the proportion of financial assets and increase the amount of FX liquid assets to prevent credit ratings to decrease. Additionally, market share of banks for loans should not reach at high level for this objective.

The capital market has an important role in the economy of a country, as it serves as a source of funds for the company as well as a source of investment for the community. Bonds are financial instruments or securities that show that bond issuers have the obligation to pay the coupons and pay off the underlying debt at the appointed time. This research focuses on financial risk that is a financial ratio consisting of profitability and liquidity. This research aims to determine the impact of profitability and liquidity on bond rating and the impact on the bond yield on non-financial companies listed on the Indonesia Stock Exchange (IDX) period 2014-2018. The methods used are descriptive and verificative. The sampling technique used in this study was Purposive Sampling. The number of companies being sampled in this study was 33 companies. This study uses the path analysis method to determine which variables have an influence on bond ratings and their impact on bond yield. The results showed that the variable profitability had a significant effect on bond ratings, liquidity had no significant effect on bond ratings, and bond ratings were significantly influential on bond yield

This study aims to empirically examine the effect of macroeconomic variables on credit risk in each business sector in Indonesia. Using time-series quarterly data during the period 2011q1-2019q2, this study utilized the Autoregressive Distributed Lag (ARDL) model. The results of this study explain that macroeconomic variables namely GDP growth in the long run have a significant negative effect on credit risk in 6 sectors and in the short term have a significant negative effect on 6 sectors. Inflation has a significant positive effect in the long run on one sector, namely the provision of accommodation and provision of food and drink, and a significant negative effect on 6 sectors, in the short term inflation has a significant positive effect on 7 sectors and a significant negative effect on one sector, namely education services. The last variable is the long-term loan interest rate which has a positive effect on 7 sectors and in the short term has a significant positive effect on 6 sectors on the high value of credit risk in each business sector in Indonesia. The result indicating that macroeconomic variables have a real impact on credit risk.

The study’s pertinence lies in its focus on the performance of green bond markets in addressing environmental concerns. The purpose of this study is to ascertain if current issuances of high credit ratings by credit rating agencies can be considered safe by investors, through the consideration of the margin of safety, amidst the prevailing high credit growth.  A quantitative research methodology determining the margin of safety of issuers, using operating incomes and interest expense, derived from annual financial statements of 30 randomly selected companies, which are considered adequate for inferential purposes, from the Climate Bond Initiative database is undertaken. The decline in EBIT before the balance after interest expense is paid becomes zero is ascertained in conjunction with the allocated credit rating.  A sampled mean of a margin of safety of 58.79 % leads to an estimated population mean results of a margin of safety above or equal 48% and below or equal to 68.41%, at 95% confidence level and a standard deviation of 27.41%. The corresponding investment credit ratings reflect a 77% in relative frequency of which 3.3% is assigned the highest AAA rating. The results demonstrate that it takes close to a minimum of 50% and a maximum of 68% deterioration in operating income before balances after interest expense are wiped out. Hence the study concludes that the prevailing credit ratings being issued by credit rating agencies can be trusted by green bond investors based on the substantive margin of safety figures of issuers.

The study’s pertinence lies in its focus on the performance of green bond markets in addressing environmental concerns. The purpose of this study is to ascertain if current issuances of high credit ratings by credit rating agencies can be considered safe by investors, through the consideration of the margin of safety, amidst the prevailing high credit growth.  A quantitative research methodology determining the margin of safety of issuers, using operating incomes and interest expense, derived from annual financial statements of 30 randomly selected companies, which are considered adequate for inferential purposes, from the Climate Bond Initiative database is undertaken. The decline in EBIT before the balance after interest expense is paid becomes zero is ascertained in conjunction with the allocated credit rating.  A sampled mean of a margin of safety of 58.79 % leads to an estimated population mean results of a margin of safety above or equal 48% and below or equal to 68.41%, at 95% confidence level and a standard deviation of 27.41%. The corresponding investment credit ratings reflect a 77% in relative frequency of which 3.3% is assigned the highest AAA rating. The results demonstrate that it takes close to a minimum of 50% and a maximum of 68% deterioration in operating income before balances after interest expense are wiped out. Hence the study concludes that the prevailing credit ratings being issued by credit rating agencies can be trusted by green bond investors based on the substantive margin of safety figures of issuers.

This study aims to empirically examine the effect of macroeconomic variables on credit risk in each business sector in Indonesia. Using time-series quarterly data during the period 2011q1-2019q2, this study utilized the Autoregressive Distributed Lag (ARDL) model. The results of this study explain that macroeconomic variables namely GDP growth in the long run have a significant negative effect on credit risk in 6 sectors and in the short term have a significant negative effect on 6 sectors. Inflation has a significant positive effect in the long run on one sector, namely the provision of accommodation and provision of food and drink, and a significant negative effect on 6 sectors, in the short term inflation has a significant positive effect on 7 sectors and a significant negative effect on one sector, namely education services. The last variable is the long-term loan interest rate which has a positive effect on 7 sectors and in the short term has a significant positive effect on 6 sectors on the high value of credit risk in each business sector in Indonesia. The result indicating that macroeconomic variables have a real impact on credit risk.

The capital market has an important role in the economy of a country, as it serves as a source of funds for the company as well as a source of investment for the community. Bonds are financial instruments or securities that show that bond issuers have the obligation to pay the coupons and pay off the underlying debt at the appointed time. This research focuses on financial risk that is a financial ratio consisting of profitability and liquidity. This research aims to determine the impact of profitability and liquidity on bond rating and the impact on the bond yield on non-financial companies listed on the Indonesia Stock Exchange (IDX) period 2014-2018. The methods used are descriptive and verificative. The sampling technique used in this study was Purposive Sampling. The number of companies being sampled in this study was 33 companies. This study uses the path analysis method to determine which variables have an influence on bond ratings and their impact on bond yield. The results showed that the variable profitability had a significant effect on bond ratings, liquidity had no significant effect on bond ratings, and bond ratings were significantly influential on bond yield

This paper demonstrates the relationship between CAMELS ratios and credit ratings of deposit banks in Turkey. Annual data was used for the period between 2004 and 2014 in this study. Moreover, 20 deposit banks of Turkey were analyzed and 21 different ratios of CAMELS components were used. In addition to that, credit ratings of these banks were provided from Moody’s corporation or annual activity reports of the banks. After that, we created multi nominal logistic regression analysis in order to illustrate the relationship. The major finding in this study is that three components (Asset Quality, Management Quality, and Sensitivity to Market Risk) of CAMELS have effects on credit ratings whereas the ratios related to Capital Adequacy and Earnings are not effective. As a result, it was recommended that Turkish deposit banks should concentrate on the percentage of fixed assets and interest income to have a better rating. Moreover, having high market share with respect to total assets and lower interest expense are also other important points for this purpose. On the other hand, Turkish deposit banks should control the proportion of financial assets and increase the amount of FX liquid assets to prevent credit ratings to decrease. Additionally, market share of banks for loans should not reach at high level for this objective.