Search results for: credit cooperatives

Authors: Mateusz Mokrogulski, Piotr Śliwka

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The aim of this paper is the identification of periods of excessive credit growth in the Polish banking sector in years 2007-2014 using different methodologies. Due to the lack of precise guidance in CRD IV regarding methods of calculating the credit gap and related deviations from the long-term trends, a few filtering methods are applied, e.g. Hodrick-Prescott and Baxter-King. The solutions based on the switching model are also proposed. The next step represent computations of both the credit gap, and the counter cyclical capital buffer (CCB) rates on a quarterly basis. The calculations are carried out for the entire banking sector in Poland, as well as for its components (commercial and co-operative banks), and different types of loans. The calculations show vividly that in the analysed period there were the times of excessive credit growth. However, the results are different for the above mentioned sub-sectors. Of paramount importance here are mortgage loans, where the outcomes are distorted by high exchange rate fluctuations. The research on the CCB is now going to gain popularity as the buffer will soon become one of the tools of the macro prudential policy under CRD IV. Although the presented method is focused on the Polish banking sector, it can also be applied to other member states. Especially to the Central and Eastern European countries, that are usually characterized by smaller banking sectors compared to EU-15.

Keywords: countercyclical capital buffer, CRD IV, filtering methods, mortgage loans

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Authors: Chokri Slim

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The objective of this research is attempting to respond to this question: Is there a significant difference between the regression model and statistical learning models in predicting credit risk management? A Multiple Linear Regression (MLR) model was compared with neural networks including Multi-Layer Perceptron (MLP), and a Support vector regression (SVR). The population of this study includes 50 listed Banks in Tunis Stock Exchange (TSE) market from 2000 to 2016. Firstly, we show the factors that have significant effect on the quality of loan portfolios of banks in Tunisia. Secondly, it attempts to establish that the systematic use of objective techniques and methods designed to apprehend and assess risk when considering applications for granting credit, has a positive effect on the quality of loan portfolios of banks and their future collectability. Finally, we will try to show that the bank governance has an impact on the choice of methods and techniques for analyzing and measuring the risks inherent in the banking business, including the risk of non-repayment. The results of empirical tests confirm our claims.

Keywords: credit risk management, multiple linear regression, principal components analysis, artificial neural networks, support vector machines

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Authors: Olufunmilayo Folaranmi

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The study aimed at assessing the effectiveness of micro-credit scheme of (COWAD) in enhancing the living standard of women in selected local government areas of Oyo State. A survey research design was adopted for the study. A sample of 250 respondents was purposively selected for the study while a structured questionnaire tagged Effectiveness of Micro-Credit Scheme of Community Women and Development and Living Standards of Women Questionnaire (EMCSCWDQ) was designed to collect data for the study. Data collected was analyzed using frequency distribution, tables, percentages and chi-square statistics. Three hypotheses were tested for the study at 0.05 level of significance. Findings from the study indicated that loan provided by COWAD for women in selected local government areas towards improving their economic conditions has improved the living conditions of the women, promoted their general welfare, and reduced their poverty level. Findings also showed that some beneficiaries were not able to pay back, therefore reducing the effectiveness for future beneficiaries. Based on the findings, it was recommended that the providers of various micro-credit schemes of the state should design a convenient pattern of payment which will provide enough time for the beneficiaries of the loan to sell their goods or work for proper and timely payment. Also, the problem of collateral should be reviewed as the majority of women involved are poor. Other recommendations include replication of COWAD facilities in other NGOs as well as sustainability of the facility.

Keywords: micro-credit scheme, welfare, women, development, poverty

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Authors: Okolo Chimaobi Valentine, Obidigbo Chizoba

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As a basic physiology need, the threat to sufficient food production is the threat to human survival. Food security has been an issue that has gained global concern. This paper looks at the food security in Nigeria by assessing the availability of food and accessibility of the available food. The paper employed multiple linear regression technique and graphic trends of growth rates of relevant variables to show the situation of food security in Nigeria. Results of the tests revealed that population growth rate was higher than the growth rate of food availability in Nigeria for the earlier period of the study. Commercial bank credit to the agricultural sector, foreign exchange utilization for food and the Agricultural Credit Guarantee Scheme Fund (ACGSF) contributed significantly to food availability in Nigeria. Food prices grew at a faster rate than the average income level, making it difficult to access sufficient food. It implies that prior to the year 2012; there was insufficient food to feed the Nigerian populace. However, continued credit to the food and agricultural sector will ensure sustained and sufficient production of food in Nigeria. Microfinance banks should make sufficient credit available to the smallholder farmer. The government should further control and subsidize the rising price of food to make it more accessible by the people.

Keywords: food, accessibility, availability, security

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Authors: Ģirts Brasliņš, Ilja Arefjevs, Nadežda Tarakanova

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The objective of countercyclical capital buffer is to encourage banks to build up buffers in good times that can be drawn down in bad times. The aim of the report is to assess such decisions by banks derived from three approaches. The approaches are the aggregate credit-to-GDP ratio, credit growth as well as banking sector profits. The approaches are implemented for Estonia, Latvia and Lithuania for the time period 2000-2012. The report compares three approaches and analyses their relevance to the Baltic states by testing the correlation between a growth in studied variables and a growth of corresponding gaps. Methods used in the empirical part of the report are econometric analysis as well as economic analysis, development indicators, relative and absolute indicators and other methods. The research outcome is a cross-Baltic comparison of two alternative approaches to establish or release a countercyclical capital buffer by banks and their implications for each Baltic country.

Keywords: basel III, countercyclical capital buffer, banks, credit growth, baltic states

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Authors: Gabriele Iannotta

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This paper investigates credit cycles by means of an experiment based on a Kiyotaki & Moore (1997) model with heterogeneous expectations. The aim is to examine how a credit squeeze caused by high lender-level risk perceptions affects the real prices of a collateralised asset, with a special focus on the macroeconomic implications of rising price volatility in terms of total welfare and the number of bankruptcies that occur. To do that, a learning-to-forecast experiment (LtFE) has been run where participants are asked to predict the future price of land and then rewarded based on the accuracy of their forecasts. The setting includes one lender and five borrowers in each of the twelve sessions split between six control groups (G1) and six treatment groups (G2). The only difference is that while in G1 the lender always satisfies borrowers’ loan demand (bankruptcies permitting), in G2 he/she closes the entire credit market in case three or more bankruptcies occur in the previous round. Experimental results show that negative risk-driven supply shocks amplify the volatility of collateral prices. This uncertainty worsens the agents’ ability to predict the future value of land and, as a consequence, the number of defaults increases and the total welfare deteriorates.

Keywords: Behavioural Macroeconomics, Credit Cycle, Experimental Economics, Heterogeneous Expectations, Learning-to-Forecast Experiment

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Authors: Ginés Hernández-Cánovas, Mª Camino Ramón-Llorens, Johanna Koëter-Kant

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This paper uses a survey data-set of 837 Spanish SMEs to analyze the association between borrower discouragement and prior firm´s strategic decisions, while controlling for firm and owner characteristics. While existing literature has neglected factors limiting the demand for resources by an overreliance on arguments which attempt to explain the existence of discouraged borrowers solely in terms of lack of access to supply of credit. The objective of this paper is to show that factors limiting the demand for resources and, therefore, reducing the availability of funds, can be traced back to the firm manager´s decision. Our hypothesis is that managers that undertake strategic decisions seeking growth or improvement in their business performance participate more in the banking market than those showing contentment with their current business situation. Our results shows that SMEs that undertake an active role in research and development activities and that achieve improvements in the operating performance of their business are less likely to be discouraged from applying for a loan. Who needs credit and who applies for credit is important for firms, prospective lenders and policymakers interested in the financial health of these firms. Credit constrained firms are less likely to invest in R&D and to introduce new products, possibly harming long-term economic growth. Knowing how important borrower discouragement is in Europe, is important for judging the priority which should be attached to government policies aimed at reducing its effects. For example, policy makers could encourage the transparency about credit eligibility and conditions in order to reduce discouragement.

Keywords: discouragement, financial constraints, SMEs financing

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Authors: Y. Fandja, O. Colot, M. Croquet

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Small and medium-sized firms (SMEs) face difficulties in accessing bank credit. Bank credit is actually the main source of external financing for SMEs. In general, SMEs are risky businesses because of the potential opacity maintained by the leader in the management of affairs, the agency conflicts between business owners and third-party funders and the potential opportunism of the leader due to the incompleteness of the contracts. These elements accentuate the problems of information asymmetries between SMEs and bankers leading to capital rationing. Moreover, the last economic crisis reinforced this rationing of capital. However, a long-term relationship between SMEs and their bank would enable the latter to accumulate a set of relevant information allowing the reduction of information asymmetry and, consequently, the reduction of credit rationing. The objective of this research is to investigate the lived experience of SMEs loan officers in their relationships with their clients in order to understand how these relationships can affect the financing structure of these SMEs. To carry out this research, an Interpretative Phenomenological Analysis is implemented. This approach is part of the constructivist paradigm and refers to the subjective narratives of the individual rather than to an objective description of the facts. The role of the researcher is to explore the lived experience of the interviewees and to try to understand the meaning they give to this experience. Currently, several sixty-minute semi-structured interviews with loan officers for SMEs have been conducted. The analysis of the content of these interviews brought out three main themes. First, the relationship between the credit officer and the company manager is complex because the credit officer is not aware of establishing a personal relationship with his client. Second; the emotional involvement in the bank financing decision is present and third, the trust in the relationship between the credit officer and his client is very important. The originality of this research is to use the interpretative phenomenological analysis more specific to psychology and sociology in order to approach in a different way the problem of the financing of SMEs through their particular relations with the bankers.

Keywords: financing structure, interpretative phenomenological analysis, relationship financing, SME

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Authors: Chowdhury Dilruba Shoma

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Gender is about equal rights that both males and females having access to responsibilities and opportunities in decision making is a fundamental human right. It is also a precondition for, and a mark of, sustainable people-oriented development. In Bangladesh, women have fewer opportunities than men do to access credit from banks and financial institutions. Entrenched patriarchal attitudes, unequal inheritance rights, and male-dominated hierarchies in the financial system, plus high interest rates and a lack of security/collateral, make it harder for women to obtain bank loans. Limited access to institutional credit is a serious restraint on the productivity and income of women entrepreneurs, (and the wider economy). These gender-biased and structural barriers inhibit women’s access to fundamental economic rights. Using a liberal feminist theoretical lens, this study provides some useful insights into the relationship between gender inequality and entrepreneurship, leading to a better understanding of women’s entrepreneurship development in Bangladesh. Recently, the Bangladesh Government, the United Nations Capital Development Fund, and Bangladesh Bank opened up the Women Entrepreneur Support Fund (WESF) ‒ Credit Guarantee Scheme (CGS) pilot project to cover collateral shortfalls for women entrepreneurs in the small and medium enterprise sector. The aim is to improve gender equality and advance women’s rights in relation to receiving credit. This article examines the challenges and prospects of the WESF-CGS, and suggests that implementation of measures in WESF-CGS policymaking, coupled with a combination of legislatory and regulatory reforms that implement the fundamental tenets of liberal feminism, can lead to a comprehensive and effective credit policy to boost women’s agency and economic empowerment. This may ultimately lead to more sustainable development in Bangladesh.

Keywords: Bangladesh, credit guarantee scheme, liberal feminist theory, women entrepreneur support fund

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Authors: Petra Buzkova, Milos Kopa

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Reliability of the credit default swap market had been questioned repeatedly during the EMU debt crisis. The article examines whether this development influenced sovereign EMU CDS prices in general. We regress the CDS market price on a model risk neutral CDS price obtained from an adopted reduced form valuation model in the 2009-2013 period. We look for a break point in the single-equation and multi-equation econometric models in order to show the changes in relations between CDS market and model prices. Our results differ according to the risk profile of a country. We find that in the case of riskier countries, the relationship between the market and model price changed when market participants started to question the ability of CDS contracts to protect their buyers. Specifically, it weakened after the change. In the case of less risky countries, the change happened earlier and the effect of a weakened relationship is not observed.

Keywords: chow stability test, credit default swap, debt crisis, reduced form valuation model, seemingly unrelated regression

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Authors: Jan Henrik Wosnitza

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The logistic regression has developed into a standard approach for estimating conditional probabilities in a wide range of applications including credit risk prediction. The article at hand contributes to the current literature on logistic regression fourfold: First, it is demonstrated that the binary logistic regression automatically meets its model assumptions under very general conditions. This result explains, at least in part, the logistic regression's popularity. Second, the requirement of homoscedasticity in the context of binary logistic regression is theoretically substantiated. The variances among the groups of defaulted and non-defaulted obligors have to be the same across the level of the aggregated default indicators in order to achieve linear logits. Third, this article sheds some light on the question why nonlinear logits might be superior to linear logits in case of a small amount of data. Fourth, an innovative methodology for estimating correlations between obligor-specific log-odds is proposed. In order to crystallize the key ideas, this paper focuses on the example of credit risk prediction. However, the results presented in this paper can easily be transferred to any other field of application.

Keywords: correlation, credit risk estimation, default correlation, homoscedasticity, logistic regression, nonlinear logistic regression

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Authors: R. Niranchana, K. Meena Alias Jeyanthi

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As a result of the present climate change dilemma, the energy balancing strategy is to construct a sustainable environment has become a top concern for researchers worldwide. The environment itself has always been a solution from the earliest days of human evolution. Carbon capture begins with its accurate estimation and monitoring credit inventories, and its efficient use. Sustainable urban planning with deliverables of re-use energy models might benefit from assessment methods like biomass carbon credit ranking. The term "biomass energy" refers to the various ways in which living organisms can potentially be converted into a source of energy. The approaches that can be applied to biomass and an algorithm for evaluating carbon credits are presented in this paper. The micro-climate evaluation using Computational Fluid dynamics was carried out across the location (1 km x1 km) at Dindigul, India (10°24'58.68" North, 77°54.1.80 East). Sustainable Urban design must be carried out considering environmental and physiological convection, conduction, radiation and evaporative heat exchange due to proceeding solar access and wind intensities.

Keywords: biomass, climate assessment, urban planning, multi-regression, carbon estimation algorithm

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Authors: Mehdi Janbaz

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The global financial crisis and the credit crunch that followed magnified the importance of credit risk management and its crucial role in the stability of all financial sectors and the whole of the system. Many believe that risks faced by the sovereign sector are highly interconnected with banking risks and most likely to trigger and reinforce each other. This study aims to examine (1) the impact of banking and interbank risk factors on the sovereign credit risk of Eurozone, and (2) how the EU Credit Default Swaps spreads dynamics are affected by the Crude Oil price fluctuations. The hypothesizes are tested by employing fitting risk measures and through a four-staged linear modeling approach. The sovereign senior 5-year Credit Default Swap spreads are used as a core measure of the credit risk. The monthly time-series data of the variables used in the study are gathered from the DataStream database for a period of 2008-2019. First, a linear model test the impact of regional macroeconomic and market-based factors (STOXX, VSTOXX, Oil, Sovereign Debt, and Slope) on the CDS spreads dynamics. Second, the bank-specific factors, including LIBOR-OIS spread (the difference between the Euro 3-month LIBOR rate and Euro 3-month overnight index swap rates) and Euribor, are added to the most significant factors of the previous model. Third, the global financial factors including EURO to USD Foreign Exchange Volatility, TED spread (the difference between 3-month T-bill and the 3-month LIBOR rate based in US dollars), and Chicago Board Options Exchange (CBOE) Crude Oil Volatility Index are added to the major significant factors of the first two models. Finally, a model is generated by a combination of the major factor of each variable set in addition to the crisis dummy. The findings show that (1) the explanatory power of LIBOR-OIS on the sovereign CDS spread of Eurozone is very significant, and (2) there is a meaningful adverse co-movement between the Crude Oil price and CDS price of Eurozone. Surprisingly, adding TED spread (the difference between the three-month Treasury bill and the three-month LIBOR based in US dollars.) to the analysis and beside the LIBOR-OIS spread (the difference between the Euro 3M LIBOR and Euro 3M OIS) in third and fourth models has been increased the predicting power of LIBOR-OIS. Based on the results, LIBOR-OIS, Stoxx, TED spread, Slope, Oil price, OVX, FX volatility, and Euribor are the determinants of CDS spreads dynamics in Eurozone. Moreover, the positive impact of the crisis period on the creditworthiness of the Eurozone is meaningful.

Keywords: CDS, crude oil, interbank risk, LIBOR-OIS, OVX, sovereign credit risk, TED

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Authors: Sudipto Sarkar

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Capital is the primary fuel for starting and running a business. Since capital is crucial for every business, entrepreneurs must successfully acquire adequate capital for executing their projects. Sources for the necessary capital for entrepreneurs include their own personal funds from existing bank accounts, or lines of credit or loans from banks or financial institutions, or equity funding from investors. The most commonly selected source of capital is a bank loan. However, acquiring a loan by any entrepreneur requires adhering to strict guidelines, conditions and norms. Because not only they have to show evidence for viability of the project, but also the means to return the acquired loan. On the bank’s part, it requires that every loan officer performs a thorough credit appraisal of the prospective borrowers and makes decisions about whether or not to lend money, how much to lend, and what conditions should be attached to it. Moreover, these credit decisions in general were often based on biases, analytical techniques, or prior experience. A loan can either turn out to be good or poor, irrespective of what type of credit decisions were followed. However, based on prior experience, the loan officers seem to differentiate between a good and a bad loan by examining the borrower’s credit history, pattern of borrowing, volume of borrowing, frequency of borrowing, and reasons for borrowing. As per an article written by Maureen Wallenfang on postcrescent.com dated May 10, 2010, it is observed that borrowers with good credit, solid business plans and adequate collateral security were able to procure loans very easily in the Fox Valley region. Since loans are required to run businesses, and also with the propensity of loans to become bad, loan officers tend to be very critical and cautious before approving and disbursing the loans. The pressure to be critical and cautious, at least partly, is a result of increased scrutiny by the Securities and Exchange Commission. As per Wall Street Journal (Sidel & Eaglesham, March, 3 2011, online), the Securities and Exchange Commission scrutinized banks that have restructured troubled loans in order to make them appear healthier than they really are. Therefore, loan officers’ loan criteria are of immense importance for entrepreneurs and banks alike.

Keywords: entrepreneur, loans, marketing, banks

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Authors: Siddharth Krishnaswamy

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Problem Statement: Currently, when analyzing household food security, the most commonly studied food access indicators are household income and expenditure. Larger studies do take into account other indices such as credit and employment. But these are baselines studies and by definition are conducted infrequently. Food security analysis for access is usually dedicated to analyzing income and expenditure indicators. And both these indicators are notoriously inconsistent. Yet this data can very often end up being the basis on which household food access is calculated; and by extension, be used for decision making. Objectives: This paper argues that along with income and expenditure, credit and debit information should be collected so that an accurate analysis of household food security (and in particular) food access can be determined. The lack of collection and analysis of this information routinely means that there is often a “masking” of the actual situation; a household’s food access and food availability patterns may be adequate mainly as a result of borrowing and may even be due to a long- term dependency (a debt cycle). In other words, such a household is, in reality, worse off than it appears a factor masked by its performance on basic access indicators. Procedures/methodologies/approaches: Existing food security data sets collected in 2005 in Azerbaijan, 2010 across Myanmar and 2014-15 across Uganda were used to support the theory that analyzing income and expenditure of a HHs and analyzing the same in addition to data on credit & borrowing patterns will result in an entirely different scenario of food access of the household. Furthermore, the data analyzed depicts food consumption patterns across groups of households and then relates this to the extent of dependency on credit, i.e. households borrowing money in order to meet food needs. Finally, response options that were based on analyzing only income and expenditure; and response options based on income, expenditure, credit, and borrowing – from the same geographical area of operation are studied and discussed. Results: The purpose of this work was to see if existing methods of household food security analysis could be improved. It is hoped that food security analysts will collect household level information on credit and debit and analyze them against income, expenditure and consumption patterns. This will help determine if a household’s food access and availability are dependent on unsustainable strategies such as borrowing money for food or undertaking sustained debts. Conclusions: The results clearly show the amount of relevant information that is missing in Food Access analysis if debit and borrowing of the household is not analyzed along with the typical Food Access indicators that are usually analyzed. And the serious repercussions this has on Programmatic response and interventions.

Keywords: analysis, food security indicators, response, resilience analysis

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Authors: Oduntan Oluwakemi, Obisesan Adekemi Adebisola, Ayo-Bello Taofeeq Ayodeji

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The study examined the factors influencing the adoption of climate-smart agricultural practices among maize farmers in Ondo State, Nigeria. A Multi-stage sampling procedure was used to randomly select one hundred respondents for the study. Primary data were collected from the respondents with the aid of a structured questionnaire and analysed using descriptive statistics and a probit regression model. The results of this study showed that crop diversification was the most adopted climate-smart agricultural practice by the respondents, and adoption of Climate Smart Agricultural practices is still very low among the respondents. Results of probit regression revealed that marital status, access to extension services, farming experience, membership of farmers’ association, and access to credit had a positive influence on the adoption of climate-smart agricultural practices, while age, farm size, and total income had a negative influence. Based on the findings of the study, it was recommended that government should develop suitable policies that will encourage farmers, especially rural farmers, to adopt and utilize Climate Smart Agricultural Practices (CSAP). Equally, the study also recommended government should be geared towards supporting improved extension services, providing on-farm demonstration training, disseminating information about climate-smart agricultural practices, and providing credit facilities through the Agricultural Credit Guarantee Scheme Fund and bank credit to farmers in order to enhance the adoption.

Keywords: adoption, agriculture, climate-smart, farmers, maize, Nigeria

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Authors: ChunYi Peng, Wei Hsuan CHeng, Shyh Kuang Ueng

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Peng, Chun-Yi, Chen, Wei-Hsuan, Ueng, Shyh-Kuang

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Denys Osipenko, Jonathan Crook

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Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models.

Keywords: multinomial regression, conditional logistic regression, credit account state, transition probability

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Authors: Oguzhan Cepni, Doruk Kucuksarac, M. Hasan Yilmaz

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Changes in the global risk appetite cause co-movement in emerging market risk premiums. However, the sensitivity of the changes in risk premium to the global risk appetite may vary across emerging markets. In this study, how the global risk appetite affects Credit Default Swap (CDS) premiums in emerging markets are analyzed using Principal Component Analysis (PCA) and rolling regressions. The PCA results indicate that the first common component derived by the PCA accounts for almost 76 percent of the common variation in CDS premiums. Additionally, the explanatory power of the first factor seems to be high over the sample period. However, the sensitivity to the global risk factor tends to change over time and across countries. In this regard, fixed effects panel regressions are used to identify the macroeconomic factors driving the heterogeneity across emerging markets. The panel regression results point to the significance of government debt to GDP and international reserves to GDP in explaining sensitivity. Accordingly, countries with lower government debt and higher reserves tend to be less subject to the variations in the global risk appetite.

Keywords: credit default swaps, emerging markets, principal components analysis, sovereign risk

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Authors: Oguzhan Cepni, Doruk Kucuksarac, M. Hasan Yilmaz

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Risk premium of emerging markets are moving altogether depending on the momentum and shifts in the global risk appetite. However, the magnitudes of these changes in the risk premium of emerging market economies might vary. In this paper, we focus on how global risk factor affects credit default swaps (CDS) premiums of emerging markets using principal component analysis (PCA) and rolling regressions. PCA results indicate that the first common component accounts for almost 76% of common variation in CDS premiums of emerging markets. Additionally, the explanatory power of the first factor seems to be high over sample period. However, the sensitivity to the global risk factor tends to change over time and across countries. In this regard, fixed effects panel regressions are employed to identify the macroeconomic factors driving the heterogeneity across emerging markets. There are two main macroeconomic variables that affect the sensitivity; government debt to GDP and international reserves to GDP. The countries with lower government debt and higher reserves tend to be less subject to the variations in the global risk appetite.

Keywords: emerging markets, principal component analysis, credit default swaps, sovereign risk

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Authors: Babak Salekmahdy

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Microfinance is often seen as a means of repairing credit markets and unleashing the potential contribution of impoverished people who rely on self-employment. Since the 1990s, the microfinance industry has expanded rapidly, opening the path for additional kinds of social entrepreneurship and social investment. However, current data indicate relatively few average consumer effects, opposing pushback against microfinance. This research reconsiders microfinance statements, stressing the variety of data on impacts and the essential (but limited) role of reimbursements. The report finishes by explaining a shift in thinking: from microfinance as a strictly defined enterprise finance to microfinance as a more widely defined home finance. Microfinance, under this perspective, provides advantages by providing liquidity for various requirements rather than just by increasing income.

Keywords: microfinance, small business, economic development, credit markets

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Authors: Xu Wang

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This research builds linear regressions of U.S. macroeconomic condition and volatility measures in the investment grade and high yield Credit Default Swap index spreads using monthly data from March 2009 to July 2016, to study the relationship between different dimensions of macroeconomy and overall credit risk quality. The most significant contribution of this research is systematically examining individual and joint effects of macroeconomic condition and volatility on CDX spreads by including macroeconomic time series that captures different dimensions of the U.S. economy. The industrial production index growth, non-farm payroll growth, consumer price index growth, 3-month treasury rate and consumer sentiment are introduced to capture the condition of real economic activity, employment, inflation, monetary policy and risk aversion respectively. The conditional variance of the macroeconomic series is constructed using ARMA-GARCH model and is used to measure macroeconomic volatility. The linear regression model is conducted to capture relationships between monthly average CDX spreads and macroeconomic variables. The Newey–West estimator is used to control for autocorrelation and heteroskedasticity in error terms. Furthermore, the sensitivity factor analysis and standardized coefficients analysis are conducted to compare the sensitivity of CDX spreads to different macroeconomic variables and to compare relative effects of macroeconomic condition versus macroeconomic uncertainty respectively. This research shows that macroeconomic condition can have a negative effect on CDX spread while macroeconomic volatility has a positive effect on determining CDX spread. Macroeconomic condition and volatility variables can jointly explain more than 70% of the whole variation of the CDX spread. In addition, sensitivity factor analysis shows that the CDX spread is the most sensitive to Consumer Sentiment index. Finally, the standardized coefficients analysis shows that both macroeconomic condition and volatility variables are important in determining CDX spread but macroeconomic condition category of variables have more relative importance in determining CDX spread than macroeconomic volatility category of variables. This research shows that the CDX spread can reflect the individual and joint effects of macroeconomic condition and volatility, which suggests that individual investors or government should carefully regard CDX spread as a measure of overall credit risk because the CDX spread is influenced by macroeconomy. In addition, the significance of macroeconomic condition and volatility variables, such as Non-farm Payroll growth rate and Industrial Production Index growth volatility suggests that the government, should pay more attention to the overall credit quality in the market when macroecnomy is low or volatile.

Keywords: autoregressive moving average model, credit spread puzzle, credit default swap spread, generalized autoregressive conditional heteroskedasticity model, macroeconomic conditions, macroeconomic uncertainty

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Authors: Gospel Iyioku, Jana Mazancova, Jiri Hejkrlik

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The “Agricultural Promotion Policy (2016–2020)” represents a strategic initiative by the Nigerian government to address domestic food shortages and the challenges in exporting products at the required quality standards. Hindered by an inefficient system for setting and enforcing food quality standards, coupled with a lack of market knowledge, the Federal Ministry of Agriculture and Rural Development (FMARD) aims to enhance support for the production and activities of key crops like cashew. By collaborating with farmers, processors, investors, and stakeholders in the cashew sector, the policy seeks to define and uphold high-quality standards across the cashew value chain. Given the challenges and opportunities faced by Nigerian cashew farmers, active participation in cashew marketing groups becomes imperative. These groups serve as essential platforms for farmers to collectively navigate market intricacies, access resources, share knowledge, improve output quality, and bolster their overall bargaining power. Through engagement in these cooperative initiatives, farmers not only boost their economic prospects but can also contribute significantly to the sustainable growth of the cashew industry, fostering resilience and community development. This study explores the perceptions and intentions of farmers regarding their involvement in cashew marketing cooperatives, utilizing an expanded version of the Theory of Planned Behaviour. Drawing insights from a diverse sample of 321 cashew farmers in Southwest Nigeria, the research sheds light on the factors influencing decision-making in cooperative participation. The demographic analysis reveals a diverse landscape, with a substantial presence of middle-aged individuals contributing significantly to the agricultural sector and cashew-related activities emerging as a primary income source for a substantial proportion (23.99%). Employing Structural Equation Modelling (SEM) with Maximum Likelihood Robust (MLR) estimation in R, the research elucidates the associations among latent variables. Despite the model’s complexity, the goodness-of-fit indices attest to the validity of the structural model, explaining approximately 40% of the variance in the intention to join cooperatives. Moral norms emerge as a pivotal construct, highlighting the profound influence of ethical considerations in decision-making processes, while perceived behavioural control presents potential challenges in active participation. Attitudes toward joining cooperatives reveal nuanced perspectives, with strong beliefs in enhanced connections with other farmers but varying perceptions on improved access to essential information. The SEM analysis establishes positive and significant effects of moral norms, perceived behavioural control, subjective norms, and attitudes on farmers’ intention to join cooperatives. The knowledge construct positively affects key factors influencing intention, emphasizing the importance of informed decision-making. A supplementary analysis using partial least squares (PLS) SEM corroborates the robustness of our findings, aligning with covariance-based SEM results. This research unveils the determinants of cooperative participation and provides valuable insights for policymakers and practitioners aiming to empower and support this vital demographic in the cashew industry.

Keywords: marketing cooperatives, theory of planned behaviour, structural equation modelling, cashew farmers

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Authors: Vangelis Papadimitropoulos

Abstract:

The paper is part of the research project “Techno-Social Innovation in the Collaborative Economy'', funded by the Hellenic Foundation of Research and Innovation for the years 2022-2024. The research project examines the normative and empirical conditions of grassroots technologically driven innovation, potentially enabling the transition towards a commons-oriented post-capitalist economy. The project carries out a conceptually led and empirically grounded multi-case study of the digital commons, open-source technologies, platform cooperatives, open cooperatives and Distributed Autonomous Organizations (DAOs) on the Blockchain. The methodological scope of research is interdisciplinary inasmuch as it comprises political theory, economics, sustainability science and computer science, among others. The research draws specifically on Michel Bauwens and Vasilis Kostakis' model of open cooperativism between the commons, ethical market entities and a partner state. Bauwens and Kostakis advocate for a commons-based counter-hegemonic post-capitalist transition beyond and against neoliberalism. The research further employs Laclau and Mouffe's discourse theory of hegemony to introduce a post-hegemonic conceptualization of the model of open cooperativism. Thus, the paper aims to outline the theoretical contribution of the research project to contemporary political theory debates on post-capitalism and the collaborative economy.

Keywords: open cooperativism, techno-social innovation, post-hegemony, post-capitalism

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Authors: Mohammad Yousaf Safi Mohibullah Afghan

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The study made on Islamic and conventional banks scrutinizes the risks interconnected with credit and liquidity on the productivity performance of Islamic and conventional banks that operate in Pakistan. Among the banks, only 4 Islamic and 18 conventional banks have been selected to enrich the result of our study on Islamic banks performance in connection to conventional banks. The selection of the banks to the panel is based on collecting quarterly unbalanced data ranges from the first quarter of 2007 to the last quarter of 2017. The data are collected from the Bank’s web sites and State Bank of Pakistan. The data collection is carried out based on Delta-method test. The mentioned test is used to find out the empirical results. In the study, while collecting data on the banks, the return on assets and return on equity have been major factors that are used assignificant proxies in determining the profitability of the banks. Moreover, another major proxy is used in measuring credit and liquidity risks, the loan loss provision to total loan and the ratio of liquid assets to total liability. Meanwhile, with consideration to the previous literature, some other variables such as bank size, bank capital, bank branches, and bank employees have been used to tentatively control the impact of those factors whose direct and indirect effects on profitability is understood. In conclusion, the study emphasizes that credit risk affects return on asset and return on equity positively, and there is no significant difference in term of credit risk between Islamic and conventional banks. Similarly, the liquidity risk has a significant impact on the bank’s profitability, though the marginal effect of liquidity risk is higher for Islamic banks than conventional banks.

Keywords: islamic & conventional banks, performance return on equity, return on assets, pakistan banking sectors, profitibility

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Authors: Ellis Kofi Akwaa-Sekyi, Jordi Moreno Gené

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Managerial actions which negatively profile banks and impair corporate reputation are addressed through effective internal control systems. Disregard for acceptable standards and procedures for granting credit have affected bank loan portfolios and could be cited for the crises in some European countries. The study intends to determine the effectiveness of internal control systems, investigate whether perceived agency problems exist on the part of board members and to establish the relationship between internal controls and credit risk among listed banks in the European Union. Drawing theoretical support from the behavioural compliance and agency theories, about seventeen internal control variables (drawn from the revised COSO framework), bank-specific, country, stock market and macro-economic variables will be involved in the study. A purely quantitative approach will be employed to model internal control variables covering the control environment, risk management, control activities, information and communication and monitoring. Panel data from 2005-2014 on listed banks from 28 European Union countries will be used for the study. Hypotheses will be tested and the Generalized Least Squares (GLS) regression will be run to establish the relationship between dependent and independent variables. The Hausman test will be used to select whether random or fixed effect model will be used. It is expected that listed banks will have sound internal control systems but their effectiveness cannot be confirmed. A perceived agency problem on the part of the board of directors is expected to be confirmed. The study expects significant effect of internal controls on credit risk. The study will uncover another perspective of internal controls as not only an operational risk issue but credit risk too. Banks will be cautious that observing effective internal control systems is an ethical and socially responsible act since the collapse (crisis) of financial institutions as a result of excessive default is a major contagion. This study deviates from the usual primary data approach to measuring internal control variables and rather models internal control variables in a quantitative approach for the panel data. Thus a grey area in approaching the revised COSO framework for internal controls is opened for further research. Most bank failures and crises could be averted if effective internal control systems are religiously adhered to.

Keywords: agency theory, credit risk, internal controls, revised COSO framework

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Authors: Alexandru-Ion Marinescu

Abstract:

There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

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Authors: Laurent Maurin, Mervi Toivanen

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This paper estimates euro area banks’ internal target capital ratios and investigates whether banks’ adjustment to the targets have an impact on credit supply and holding of securities during the financial crisis in 2005-2011. Using data on listed banks and country-specific macro-variables a partial adjustment model is estimated in a panel context. The results indicate, firstly, that an increase in the riskiness of banks’ balance sheets influences positively on the target capital ratios. Secondly, the adjustment towards higher equilibrium capital ratios has a significant impact on banks’ assets. The impact is found to be more size-able on security holdings than on loans, thereby suggesting a pecking order.

Keywords: Euro area, capital ratios, credit supply, partial adjustment model

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Authors: Xiaoyu Shen, Fang Fang, Chujun Qiu

Abstract:

Herewith we present a Fourier method for credit risk quantification and allocation in the factor-copula model framework. The key insight is that, compared to directly computing the cumulative distribution function of the portfolio loss via Monte Carlo simulation, it is, in fact, more efficient to calculate the transformation of the distribution function in the Fourier domain instead and inverting back to the real domain can be done in just one step and semi-analytically, thanks to the popular COS method (with some adjustments). We also show that the Euler risk allocation problem can be solved in the same way since it can be transformed into the problem of evaluating a conditional cumulative distribution function. Once the conditional or unconditional cumulative distribution function is known, one can easily calculate various risk metrics. The proposed method not only fills the niche in literature, to the best of our knowledge, of accurate numerical methods for risk allocation but may also serve as a much faster alternative to the Monte Carlo simulation method for risk quantification in general. It can cope with various factor-copula model choices, which we demonstrate via examples of a two-factor Gaussian copula and a two-factor Gaussian-t hybrid copula. The fast error convergence is proved mathematically and then verified by numerical experiments, in which Value-at-Risk, Expected Shortfall, and conditional Expected Shortfall are taken as examples of commonly used risk metrics. The calculation speed and accuracy are tested to be significantly superior to the MC simulation for real-sized portfolios. The computational complexity is, by design, primarily driven by the number of factors instead of the number of obligors, as in the case of Monte Carlo simulation. The limitation of this method lies in the "curse of dimension" that is intrinsic to multi-dimensional numerical integration, which, however, can be relaxed with the help of dimension reduction techniques and/or parallel computing, as we will demonstrate in a separate paper. The potential application of this method has a wide range: from credit derivatives pricing to economic capital calculation of the banking book, default risk charge and incremental risk charge computation of the trading book, and even to other risk types than credit risk.

Keywords: credit portfolio, risk allocation, factor copula model, the COS method, Fourier method

Procedia PDF Downloads 118