Credit Risk Factors Research Articles

Managerial Ability, Credit Ratings, and the Cost of Debt

We test whether credit rating analysts consider managerial ability as a credit risk factor and find that higher-ability managers obtain more favorable credit ratings. Controlling for past performance, these results suggest that managerial ability is itself a significant credit rating factor. Cross-sectional analyses indicate that managerial ability is beneficial specifically in firms facing financial or competitive pressure. We find that high ability managers mitigate the adverse impact on ratings of other credit risk factors including negative earnings and low interest coverage. Our results contribute to a growing literature documenting economic benefits to hiring and retaining high quality management.

Approaches of Czech entrepreneurs to debt financing and management of credit risk

The aim of this article was to define, quantify and compare significant factors of the debt financing in the segment of SMEs. The research focused on the significant differences between groups of entrepreneurs, defined in relation to gender, education, size and age of the company, was carried out in the Czech Republic in 2015 on a sample of 1,141 respondents. We found that while the importance of the credit risk increased during the crisis, the level of knowledge of conditions under which commercial banks provide loans is relatively low between entrepreneurs. Entrepreneurs presume that the credit conditions in commercial banks are not transparent, but agree that the better knowledge of credit criteria allows for easier access to funding. Substantial differences in the assessment of the factors of credit risk by defined groups of entrepreneurs were identified.

Credit Scoring for M-Shwari using Hidden Markov Model

The introduction of mobile based Micro-credit facility, M-Shwari, has heightened the need to develop a proper decision support system to classify the customers based on their credit scores. This arises due to lack of proper information on the poor and unbanked as they are locked out of the formal banking sector. A classification technique, the hidden Markov model, is used. The poor customers’ scanty deposits and withdrawal dynamics in the M-Shwari account estimate the credit risk factors that are used in training and learning the hidden Markov model. The data is generated through simulation and customers categorized in terms of their credit scores and credit quality levels. The model classifies over 80 percent of the customers as having average and good credit quality level. This approach offers a simple and novice method to cater for the unbanked and poor with minimal or no financial history thus increasing financial inclusion in Kenya.

Credit risk, managerial behaviour and macroeconomic equilibrium within dual banking systems: Interest-free vs. interest-based banking industries

In this paper, an attempt has been made to explore the determinants of credit risk in the banking system with a particular interest toward the Islamic banking industry. We analyze the link between credit risk and a set of bank-specific and macroeconomic along with institutional variables using two complementary approaches. First, we investigate the factors of credit risk using one-step generalized method of moments (GMM) system estimator. Then, we explore the feedback between credit risk and its determinants in a panel vector autoregressive (PVAR) model. We have used a sample of Middle Eastern, North African (MENA) and Asian countries to apply our model. The major purpose of this paper is to find factors that could explain credit risk within the interest-free banking system relative to the interest-based one.

Variable Reduction and Determinants of Working Capital Management on Profits for Ghanaian Banks

Today, several factors has contributed to the profitability of Banks. Data collected on these factors often has several variables. It is a non-trivial exercise to determine which of the factors that significantly influences the profits of Banks. This paper adopts the use of Principal Component Analysis (PCA) on the several variables expected to influence the working capital management on the profits of banks of the Ghana Stock Exchange (GSE). Fifteen of the several variables captured by the GSE which affect working capital management on profit were grouped into four factors using the principal component analysis. Results of the PCA identifies Convertibility factors, Risk Factor, Short term Liquidity, Operational factors, and Credit Risk factors to be the determinants of bank profits. Consequently, these factors are used to fit a linear regression model in identifying the most significant factors. Apart from credit risk factors, all the other factors were found to be significant predictors of the profit of Ghanaian banks. Investors, stakeholders, and managers of banks can use these factors to monitor and evaluate their working capital in generating profits.

Fire Sale Risk and Corporate Yield Spreads

We investigate pricing implications of regulation-induced fire sales in corporate bonds. Insurance companies, the dominant investors in the corporate bond market, are also subject to regulatory restrictions that can induce commonalities in their investment behavior. In particular, a bond downgrade can trigger a ‘fire sale’ if greater capital requirements and other regulatory constraints prompt its widespread divestment. Using data on insurance companies’ holdings in corporate bonds, we approximate the amount of fire sale risk by the percentage of total par amount of a bond held by insurance companies. Using exogenous variation in the demand for particular bonds, we show that fire sale risk has significant explanatory power for corporate bond yield spreads, after controlling for the general effect of liquidity, credit risk and other traditional bond pricing factors. The effect of fire sale risk on bond yield spreads is more pronounced: when a bond is held by more regulatory-constrained insurance companies, for subsample of bonds with credit ratings closer to the NAIC risk categories with higher capital requirements, and during the recent financial crisis.

Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales

The analysis of the factors that influence sustainability is the key to achieving it. Based on the Theory of Resources and Capabilities (Grant, 1991), a management model that determines the explanatory factors of the sustainability of microfinance institutions (MFI) is developed. The empirical model is constructed by applying a principal component and logistic regression analysis using a sample of 313 MFI, with 31 finance variables, grouped into 6 components/factors that are theoretically associated with self-sufficiency. The results obtained showed a significant and positive relationship between size and the efficiency-productivity of the MFI and their sustainability, with the credit risk factor having an inverse relationship as regards that sustainability. Thus, it may be suggested that the MFI that wish to continue developing their activity using a self-sufficiency approach must promote a management strategy oriented towards: (1) an increase in efficiency-productivity, (2) the exhaustive control of credit risk and, (3) the increase in size in order to achieve economies of scale. The predictive capacity of the model is high, with an area under the ROC curve of 89.7%.

Impact of credit information on the banks stability: Global experience and lessons for Ukraine

A quality of the credit portfolio is one of the most important factors of banking system reliability. It is obviously, that there is a direct relationship between this indicator and financial stability of the bank. In turn, the quality of the loan portfolio depends on many factors that are investigated in scientific and educational literature. In this paper, we propose to focus on a group of factors of credit risk that are connected with the availability of information about the borrower. The low efficiency of the national system of collecting information about borrowers in Ukraine in comparison with foreign models was confirmed by the quantitative analysis. This tendency cases the high level of credit risks and low financial stability level of domestic banks. It is necessary to make active efforts on improving the effectiveness of credit bureaus in Ukraine by establishing public credit registry and also to focus on solving other problems associated with the collection and use of information about borrowers.

Determinants of Credit Risk of Commercial Banks in Ghana

Understanding the causal factors of credit risk among commercial banking is imperative due to the high risk financial industry in developing economies face in their operations. Specifically, this paper examines the determinants of credit risk of commercial banks in Ghana from 2007-2014 using Robust Least Squares regression analysis. The results show a significantly positive relation between the bank credit risk and leverage. However, a negative relationship between the credit risk and management efficiency was found. With regard to the relationship between bank credit risk and profit, the results show a significant negative association. It is recommended that commercial banks should continue to diversify their lending activities to productive sectors to mitigate credit risk.

Do global risk factors and macroeconomic conditions affect global Islamic index dynamics? A quantile regression approach

Abstract The aim of this paper is to explain global Dow Jones Islamic Market Index (DJIMI) dynamics across quantiles during the period of January 2003 to October 2014. Using quantile regression approach, we investigate the co-movement and the dependence structure between DJIMI returns and influential global financial market conditions, macroeconomic indicators and risk factors (major conventional stock market indices returns, global stock market uncertainty (VIX), crude oil prices, inflation rates, slope of the yield curves, investor sentiment indicator, and global sovereign credit risk represented by sovereign credit default swap (CDS) premiums). The empirical results demonstrate that conventional stock market returns, stock market implied volatility and the slope of the yield curve (as a proxy for future economic conditions) are significant for all the quantiles and display asymmetric tail dependence. During and after the global financial crisis, the sovereign credit risk factor has also been significant with positive coefficients, implying the impact of systemic nature of sovereign credit risk on explaining DJIMI returns. Moreover, the impact of oil prices and investor sentiment indicator is positive and significant but only for the lower quantiles.

Performance drivers of shipping loans: An empirical investigation

Credit risk is a major issue for lenders and borrowers, threatening the reliability of global logistics operations. Enhanced mechanisms of credit risk analysis are needed to safeguard banks and the flow of goods in supply chains. Little emphasis has been given to the contextual examination of such factors, either in terms of market conditions or the particular characteristics of different industries. This paper investigates the varying importance of a number of factors connected with the performance of corporate bank loans during times of financial turbulence in the shipping industry. Little extant literature exists on default risk drivers for loans made to shipping companies for new build vessels or second-hand ship purchases. A binary logit model is used to examine the criteria for assessing the security of shipping loans issued by banks. Thirty shipping loans made during the period 2005–2009 are examined. Results suggest that financial factors, non-financial factors, shipowners׳ experience, and employability and market risk indicators are the best criteria for evaluating the performance of shipping loans during turbulent market conditions and periods when financing options are restricted. The paper makes a specific contribution to the literature on risk management with regard to credit risk analysis by highlighting shipping specific factors and their importance for risk measurement. The results are of interest to banks seeking to accurately assess the credibility of shipping loans; shipowners, who can identify credit risk factors on which to focus; and supply chain participants where unfulfilled bank financing can cause disruptions to their logistics operations.

The Impact of Credit Risk Management in the Profitability of Albanian Commercial Banks During the Period 2005-2015

Albanian Financial institutions face difficulties for a multitude of reasons but the major cause of Albanian banking problems are related to the credit risk. For the Albanian banks, loans are the largest source of credit risk as they are not active is trading derivatives. Banks objective is to manage credit risk in order to prevent losses and to maximize its profitability. The main purpose of this research is to study if it exist a relationship between Credit risk management and profitability of commercial banks in Albania. The main indicators used in this study are Return on Equity, Return on Assets, Non-performing Loans Ratio and Capital Adequacy Ratio. The research collects data from the 16 banks operating in the Albanian banking system from 2005 to 2015. Statistical test are performed in order to test the relationship between the four indicators and the profitability of commercial banks in Albania. This study provides a contribution within the identification of credit risk factors that affect more the profitability of the Albania Banks and the finding of a scientific solution in order to manage the credit risk in a more efficient way. Key words: Profitability, Capital Adequacy, Return on Assets, Return on Equity, Credit risk management, Non-performing Loans Ratio.

The market price of credit risk and economic states

This paper proposes a market-wide credit risk factor for the US stock market and investigates its properties that are dependent on economic conditions. The market price of credit risk is found to be statistically significantly negative, supporting earlier studies. However, a sample-split analysis reveals that this negative payoff is nonexistent in a later subsample, indicating that the credit risk puzzle is based on temporary mispricing related to the earlier subsample. Further investigation shows that mispricing in the earlier period was mainly driven by positive payoffs of low credit risk firms, while high credit risk firms did not generate significant returns in any of the sub-periods.

The Market Price of Credit Risk and Economic States

This paper proposes a market-wide credit risk factor for the US stock market and investigates its properties that are dependent on economic conditions. The market price of credit risk is found to be statistically significantly negative, supporting earlier studies. However, a sample-split analysis reveals that this negative pay-off is non-existent in a later subsample, indicating that the credit risk puzzle is based on temporary mispricing related to the earlier subsample. Further investigation shows that mispricing in the earlier period was mainly driven by positive pay-offs of low credit risk firms, while high credit risk firms did not generate significant returns in any of the sub-periods.

Synthetic CDO pricing: the perspective of risk integration

The underlying asset pool of collateral debt obligations (CDOs) simultaneously encompasses credit risk and market risk. However, the standard CDO pricing model not only underestimates the risk to the asset pool due to a poor description of the correlation structure among obligors but is also incapable of reflecting the impacts of interdependent markets, credit risks and systematic sudden shocks on the asset pool. This paper studies the joint impact of interrelated market and credit risk factors on the key inputs of CDO pricing (default probability, default correlation and default loss rate) under the framework of factor copula CDO pricing model and constructs a risk-integrated model for CDO pricing. In addition, we extend the static integrated model to a dynamic version by allowing the risk factors driven by the copula-GARCH process. The simulation results show that, compared with an integrated model, the premium of senior tranches is significantly lower under the standard model. Such difference is mainly due to different assumptions of the distributions of risk-driving factor.

Determinants of Non-Performing Loans in Licensed Commercial Banks: Evidence from Sri Lanka

This study investigates the determinant factors of ex-post credit risk considering non-performing loans (NPLs) as a proxy variable in Sri Lanka’s commercial banking sector and is carried out with a sample of nine licensed commercial banks for the period of 1999 to 2012. The study finds that the level of NPLs can be attributed to both macroeconomic conditions and banks’ specific factors. It reveals that NPLs tends to increase with deteriorating bank’s efficiency. There is also a positive correlation between loan to asset ratio and NPLs. Meanwhile, banks with a high level of credit growth associated with a reduced level of non- performing loans. Larger banks incur lesser loan defaults compared to smaller banks. With regard to macro-economic variables, NPLs vary negatively with the growth rate of GDP and Inflation and positively with the prime lending rate.

How the Default Probability is Defined by the Credit Portfolio Models: A Comparative Analysis between the Theoretical Structural Models?

This paper is elaborate of which the main is to present a theoretical analysis between the structural models. There are currently three types of models to consider the risk of credit: the structural models (The KMV Moody’s model and the CreditMetrics model) also defined by the models of the value of the firm, reduced form models also defined by models with intensity (actuarial models) and the econometric models (The macro-factors models). The development of its three types of models is based on a theoretical basis developed by several researchers and many financial institutions. These models are dedicated to measurement the default probability of credit portfolio. The evaluation of their default frequencies and the size of the credit portfolio are expressed as functions of macro-economic and micro-economic conditions as well as unobservable credit risk factors, which explained by other factors. We developed three sections to explain the different characteristics of the structural models of credit portfolio management. The purpose of all its models is to express the probability of default.

Assessment of trade credit risk in business companies

The article‘s topic is relevant, because the importance of trade credit constantly increases. Trade credit can be one of the most important preconditions for the competitiveness of the enterprise and business development. There is a lack of scientific sources in the field of estimation of trade credit risk – there is no any particular, simple to use methodology to assess company trade credit risk. 
 The aim of the article – to compose a methodology of assessment company trade credit risk for Lithuanian small and medium enterprises.
 In the article, following scientific sources approach, the advantages, risks and key financial and non-financial trade credit risk factors were identified. Based on the scientific sources and expert evaluation, the methodology of company trade credit risk assessment was created. The methodology is based on 10 key indicators identified by the experts. 12 financial ratios and non-financial indicators are being used – current and quick ratio, gross and net profit margin, Altman Z model, debt ratio, stock and debtors turnover, enterprise age, reputation, number and dynamics of employees. The indicators have been scored. The highest possible score is 100.
 The research approves that the methodology suits to be used in practice. It is simple, reliable, cheap, non-time consuming; it is easy to collect data, the data is being formalized and quantified. The disadvantages of methodology – the data is not always reliable and some ratios are of different importance in the different economic sectors. The methodology should be modified to adapt for the different sectors of business.

Moral Hazard in Housing Policy: Takeaways from Judicial State Delinquencies

The longer foreclosure process in judicial states gives borrowers an incremental “free rent benefit,” potentially contributing to higher delinquencies compared to non-judicial counterparts. Based on rational expectations, we estimate that borrowers in judicial states perceive about 10–16 extra months in the foreclosure process, compared with non-judicial states. We estimate judicial effects (percentage increase in current-to-delinquent roll rates in judicial states, adjusted for other credit risk factors) to be about 20%. They are generally higher for higher CLTV loans, and also for higher FICO, and other stronger borrowers. For agency high CLTV pools, the concentration of loans from judicial states can be an important driver of delinquency buyout speeds. The judicial effect allows us to quantify the impact of moral hazard. Policy makers designing mortgage modification policies should take this into account, in our view. <b>TOPICS:</b>MBS and residential mortgage loans, legal/regulatory/public policy

Momentum, sovereign credit ratings and global equity markets

This article investigates the link between momentum-based trading strategies implemented in global equity markets and country-specific credit ratings. The findings indicate that only the momentum strategy based on intermediate past returns generate statistically significant profits. Notably, the winner portfolios exhibit a higher average credit rating than the other portfolio groups. Surprisingly, neither global asset pricing models nor a conducted world credit risk factor can explain these profits.