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10 pages, 786 KiB

Open AccessArticle

Leverage, Growth Opportunities, and Credit Risk: Evidence from Italian Innovative SMEs

by Alberto Manelli, Roberta Pace and Maria Leone

Risks 2022, 10(4), 74; https://doi.org/10.3390/risks10040074 - 1 Apr 2022

Cited by 4 | Viewed by 2565

The link between leverage and growth opportunities has been a topic issue in corporate finance for many years. The present paper aims to investigate the link between credit risk, leverage, and growth opportunities in a sample of Italian innovative small-and-medium enterprises (SMEs), given [...] Read more.

The link between leverage and growth opportunities has been a topic issue in corporate finance for many years. The present paper aims to investigate the link between credit risk, leverage, and growth opportunities in a sample of Italian innovative small-and-medium enterprises (SMEs), given the lack of empirical literature on the subject. The results of the WLS model confirm the relationship between investments, leverage, and credit risk highlighted by the literature—in particular, a negative relationship emerges between credit risk and investments and between leverage and investments, while the analysis reveals a positive relationship between investments and liquidity. Furthermore, in consideration of the significant economic differences existing between the regional macro-areas into which Italy is divided, the firms were classified by geographical areas. The results show that the northeast area is the region characterised by the most reliable and significant results. The paper is organised as follows: Introduction provides a review of the theoretical and empirical literature on the link between leverage, investments, and growth opportunities and on credit risk; Materials and Methods explain the model; Results explain the WLS regression; Discussions contain the main finding of the analysis; Conclusions summarize the study. Full article

(This article belongs to the Special Issue Credit Risk Management)

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13 pages, 585 KiB

Open AccessArticle

The Volatility of the “Green” Option-Adjusted Spread: Evidence before and during the Pandemic Period

by Alessandra Ortolano and Eugenia Nissi

Risks 2022, 10(3), 45; https://doi.org/10.3390/risks10030045 - 22 Feb 2022

Cited by 6 | Viewed by 2374

Abstract

The paper is an investigation on the impact of financial markets on the volatility of the green bonds credit risk component, measured by the option-adjusted spread/swap curve (OAS) before and during the pandemic period. To this purpose, after observing the dynamic joint correlations [...] Read more.

The paper is an investigation on the impact of financial markets on the volatility of the green bonds credit risk component, measured by the option-adjusted spread/swap curve (OAS) before and during the pandemic period. To this purpose, after observing the dynamic joint correlations between all the variables, we adopt Exponential and Generalized AutoRegressive Conditional Heteroskedasticity models, putting the OAS as dependent variable. Our main results show that the conditional variance parameters are significant and persistent in both times, testifying the overall impact of the other markets on the OAS. In more detail, we highlight that the gamma in the two Exponential models is positive: so, the “green” credit risk volatility is more sensitive to positive shocks than to negative ones. With reference to the conditional mean, we note that if during the non-pandemic period only the stock market is significant, during the pandemic also conventional bonds and gold are impacting. To the best of our knowledge this is the first study that analyzes the specific credit risk component of the green bond yields: we deem our findings useful to observe the change of green bonds creditworthiness in a complex market context and interesting in terms of policy implications. Full article

(This article belongs to the Special Issue Credit Risk Management)

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16 pages, 5056 KiB

Open AccessArticle

The Wavelet Analysis: The Case of Non-Performing Loans in China

by Elisa Di Febo and Eliana Angelini

Risks 2022, 10(2), 32; https://doi.org/10.3390/risks10020032 - 2 Feb 2022

Cited by 1 | Viewed by 3529

Abstract

China has accelerated its banking sector reform in recent years, paying particular attention to non-performing loans (NPLs). The paper’s scope is to analyse the relationship between NPLs and macroeconomic variables in China using quarterly data from 2008/Q1 to 2021/Q1 applying wavelet analysis, which [...] Read more.

China has accelerated its banking sector reform in recent years, paying particular attention to non-performing loans (NPLs). The paper’s scope is to analyse the relationship between NPLs and macroeconomic variables in China using quarterly data from 2008/Q1 to 2021/Q1 applying wavelet analysis, which allows the study to scan both short- and long-term causal relationships and connections. The analysis produces interesting results. The GDP does not appear to be as important and as much of a driving force in the dynamics of NPLs as in other emerging countries. On the other hand, inflation shows a highly dynamic dependence on NPLs as it varies over time; however, the most interesting data is the relationship between NPLs and economic policy uncertainty. In the short term, the variables are in phase. In the long term, an increase of EPU has a reduction effect on NPLs, indicating that it affects commercial bank loan sizes by reducing enterprise demand for and bank supply of credit resources. Full article

(This article belongs to the Special Issue Credit Risk Management)

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21 pages, 452 KiB

Open AccessArticle

On the Diversification of Fixed Income Assets

by Olivier Le Courtois

Risks 2022, 10(2), 31; https://doi.org/10.3390/risks10020031 - 1 Feb 2022

Viewed by 1952

Abstract

This article introduces a new approach for dealing with the diversification/concentration risk of fixed income assets. Because Government bonds, corporate bonds, and mortgage backed securities constitute a large proportion of the assets of institutional investors in most countries, it is important to be [...] Read more.

This article introduces a new approach for dealing with the diversification/concentration risk of fixed income assets. Because Government bonds, corporate bonds, and mortgage backed securities constitute a large proportion of the assets of institutional investors in most countries, it is important to be able to determine the number of lines/issuers of such assets, not only for portfolio management but also for risk management purposes. The approach that I introduce shows the dependence of the critical number of lines of fixed income assets on the main interest rate risk and credit risk drivers. Specifically, I examine the importance of volatility risk, force of mean reversion, default risk, recovery risk, and default dependence risk on the critical number of assets in a fixed income portfolio. The methodology in this paper relies on the use of the coefficient of variation for the computation of the critical number of credit-sensitive securities in a fixed income portfolio. To the best of my knowledge, this paper is the first to develop such an approach. Full article

(This article belongs to the Special Issue Credit Risk Management)

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13 pages, 506 KiB

Open AccessEditor’s ChoiceArticle

Non-Performing Loans and Macroeconomics Factors: The Italian Case

by Matteo Foglia

Risks 2022, 10(1), 21; https://doi.org/10.3390/risks10010021 - 12 Jan 2022

Cited by 26 | Viewed by 8726

Abstract

The purpose of this work is to investigate the influence of macroeconomics determinants on non-performing loans (NPLs) in the Italian banking system over the period 2008Q3–2020Q4. We mainly contribute to the literature by being the first empirical article to study this relationship in [...] Read more.

The purpose of this work is to investigate the influence of macroeconomics determinants on non-performing loans (NPLs) in the Italian banking system over the period 2008Q3–2020Q4. We mainly contribute to the literature by being the first empirical article to study this relationship in the Italian context in the recent period, thus providing fresh evidence on the macroeconomic impact on NPLs, i.e., on the credit risk of Italian banks. By employing the Autoregressive Distributed Lag (ARDL) cointegration model, we are able to investigate the short and long-run effects of macroeconomic factors on NPLs. The empirical findings show that gross domestic product and public debt have a negative impact on NPLs. On the other hand, we find that the unemployment rate and domestic credit positively influence impaired loans. Finally, we find evidence of the “gamble for resurrection” approach, i.e., Italian banks tend to support “zombie firms”. Full article

(This article belongs to the Special Issue Credit Risk Management)

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26 pages, 452 KiB

Open AccessArticle

Drivers of Individual Credit Risk of Retail Customers—A Case Study on the Example of the Polish Cooperative Banking Sector

by Rafał Balina and Marta Idasz-Balina

Risks 2021, 9(12), 219; https://doi.org/10.3390/risks9120219 - 2 Dec 2021

Cited by 1 | Viewed by 3609

Abstract

The main aim of the research was to determine the key factors determining the level of credit risk of individual clients (clients in the form of natural persons, excluding companies) on the example of Polish cooperative banks according to the following features: transaction [...] Read more.

The main aim of the research was to determine the key factors determining the level of credit risk of individual clients (clients in the form of natural persons, excluding companies) on the example of Polish cooperative banks according to the following features: transaction characteristics, socio-demographic characteristics of the customer, the customer’s financial situation, the customer’s history of cooperation with the cooperative bank where they applied for a loan, and the customer’s history of cooperation with other financial institutions. For the research gathered data from 1000 credit applications submitted by individual customers when applying for a credit in five different cooperative banks were used for the analyses. To assess the credit risk of retail clients we use logit regression models, and additionally, score cards were calculated. The results of the research indicate that among the factors with high predictive power there were the features characterizing the client’s history of cooperation with the cooperative bank, where they applied for a loan. It may mean that when assessing credit risk related to financing individual customers, cooperative banks due to their local character, have an advantage over other financial institutions. Full article

(This article belongs to the Special Issue Credit Risk Management)

15 pages, 1041 KiB

Open AccessArticle

Scoring Models and Credit Risk: The Case of Cooperative Banks in Poland

by Krzysztof Kil, Radosław Ciukaj and Justyna Chrzanowska

Risks 2021, 9(7), 132; https://doi.org/10.3390/risks9070132 - 13 Jul 2021

Cited by 3 | Viewed by 4566

Abstract

The aim of the research presented in the article was to analyse the legitimacy of the use of scoring models in banking activities, together with the assessment of the effectiveness of this tool in reducing the high value of the NPL ratio in [...] Read more.

The aim of the research presented in the article was to analyse the legitimacy of the use of scoring models in banking activities, together with the assessment of the effectiveness of this tool in reducing the high value of the NPL ratio in Polish cooperative banks on the example of banks belonging to the BPS S.A. association in the period between 2004 and 2020. We used a variety of research methods for this purpose including a depth review of the literature, analysis of statistical data regarding the sector of Polish cooperative banks, analysis of financial data of cooperative banks, construction of an econometric panel model, and the designing a questionnaire (which was later sent to the management board of selected cooperative banks). Our research confirmed the significant impact of the use of scoring models in lending activities on the value of the NPL ratio in cooperative banks. The analysed cooperative banks, which used the scoring models proposed by BIK in their lending activity, showed significantly lower values of the NPL ratio in each analysed year than banks that used other scoring models. Our study also confirmed the different direction of the impact of the models offered by BIK and individual scoring models on the value of the NPL ratio. We have also shown that the scoring models proposed by BIK have a statistically significant negative impact on the level of the NPL ratio, and the banks’ own scoring models have a statistically significant positive impact on the level of the NPL ratio. Full article

(This article belongs to the Special Issue Credit Risk Management)

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23 pages, 3258 KiB

Open AccessEditor’s ChoiceArticle

Credit Risk Management of Property Investments through Multi-Criteria Indicators

by Marco Locurcio, Francesco Tajani, Pierluigi Morano, Debora Anelli and Benedetto Manganelli

Risks 2021, 9(6), 106; https://doi.org/10.3390/risks9060106 - 2 Jun 2021

Cited by 17 | Viewed by 3917

Abstract

The economic crisis of 2008 has highlighted the ineffectiveness of the banks in their disbursement of mortgages which caused the spread of Non-Performing Loans (NPLs) with underlying real estate. With the methods stated by the Basel III agreements, aimed at improving the capital [...] Read more.

The economic crisis of 2008 has highlighted the ineffectiveness of the banks in their disbursement of mortgages which caused the spread of Non-Performing Loans (NPLs) with underlying real estate. With the methods stated by the Basel III agreements, aimed at improving the capital requirements of banks and determining an adequate regulatory capital, the banks without the skills required have difficulties in applying the rigid weighting coefficients structures. The aim of the work is to identify a synthetic risk index through the participatory process, in order to support the restructuring debt operations to benefit smaller banks and small and medium-sized enterprises (SME), by analyzing the real estate credit risk. The proposed synthetic risk index aims at overcoming the complexity of Basel III methodologies through the implementation of three different multi-criteria techniques. In particular, the integration of objective financial variables with subjective expert judgments into a participatory process is not that common in the reference literature and brings its benefits for reaching more approved and shared results in the debt restructuring operations procedure. Moreover, the main findings derived by the application to a real case study have demonstrated how important it is for the credit manager to have an adequate synthetic index that could lead to the avoidance of risky scenarios where several modalities to repair the credit debt occur. Full article

(This article belongs to the Special Issue Credit Risk Management)

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17 pages, 422 KiB

Open AccessArticle

Is Economic Uncertainty a Risk Factor in Bank Loan Pricing Decisions? International Evidence

by Badar Nadeem Ashraf

Risks 2021, 9(5), 81; https://doi.org/10.3390/risks9050081 - 23 Apr 2021

Cited by 5 | Viewed by 2869

Abstract

Uncertainty in economic environment leads economic agents to act cautiously. In this paper, we postulate that such uncertainty leads banks to charge higher interest rate on loans. Measuring aggregate country-level economic uncertainty with the World Uncertainty Index (WUI) and using a bank-level dataset [...] Read more.

Uncertainty in economic environment leads economic agents to act cautiously. In this paper, we postulate that such uncertainty leads banks to charge higher interest rate on loans. Measuring aggregate country-level economic uncertainty with the World Uncertainty Index (WUI) and using a bank-level dataset from 88 countries over the period 1998–2017, we find that heightened economic uncertainty increases bank loan interest rates. Specifically, bank loan interest rates rise by 20.67 basis points with a one standard deviation increase in WUI. Our results are robust when we use alternative proxy of uncertainty, include additional controls in the model, and extend the sample size. We also observe that WUI index is better at measuring local economic uncertainty as compared to the Economic Policy Uncertainty (EPU) index. Overall, this study provides evidence that bank price in economic uncertainty is an important risk while setting interest rates on bank loans. Full article

(This article belongs to the Special Issue Credit Risk Management)

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