Search results for: credit portfolio

Authors: M. Chumburidze, N. Salia, T. Namchevadze

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This work deal with case processing problems in business. The task of strategic credit requirements management of cases portfolio is discussed. The information model of credit requirements in a binary tree diagram is considered. The algorithms to solve issues of prioritizing clusters of cases in business have been investigated. An implementation of priority queues to support case management operations has been presented. The corresponding pseudo codes for the programming application have been constructed. The tools applied in this development are based on binary tree ordering algorithms, optimization theory, and business management methods.

Keywords: credit network, case portfolio, binary tree, priority queue, stack

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Authors: Sergey Podluzhnyy

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One of the most important tasks of investment and pension fund management is building decision support system which helps to make right decision on corporate bond portfolio formation. Today there are several basic methods of bond portfolio management. They are duration management, immunization and convexity management. Identified methods have serious disadvantage: they do not take into account credit risk or insolvency risk of issuer. So, identified methods can be applied only for management and evaluation of high-quality sovereign bonds. Applying article proposes mathematical model for building an optimal in case of risk and yield corporate bond portfolio. Proposed model takes into account the default probability in formula of assessment of bonds which results to more correct evaluation of bonds prices. Moreover, applied model provides tools for visualization of the efficient frontier of corporate bonds portfolio taking into account the exposure to credit risk, which will increase the quality of the investment decisions of portfolio managers.

Keywords: corporate bond portfolio, default probability, effective boundary, portfolio optimization task

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Authors: Yuri Katz, Kun Liu, Arunram Atmacharan

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Due to illiquidity, mispricing on Credit Markets is inevitable. This creates huge challenges to banks and investors as they seek to find new ways of risk valuation and portfolio management in a post-credit crisis world. Here, we analyze the difference in behavior of the spread-to-maturity in investment and high-yield categories of US corporate bonds between 2014 and 2023. Deviation from the theoretical dependency of this measure in the universe under study allows to identify multiple cases of mispriced credit risk. Remarkably, we observe mispriced bonds in both categories of credit ratings. This identification is supported by the application of the state-of-the-art machine learning model in more than 90% of cases. Noticeably, the ML-driven model-based forecasting of a category of bond’s credit ratings demonstrate an excellent out-of-sample accuracy (AUC = 98%). We believe that these results can augment conventional valuations of credit portfolios.

Keywords: credit risk, credit ratings, bond pricing, spread-to-maturity, machine learning

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Authors: Kostas Metaxiotis

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Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.

Keywords: evolutionary algorithms, portfolio optimization, skewness, stock selection

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Authors: Pranvera Shehaj

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Unlike any prior analysis on the withholding tax rates negotiated in tax treaties, this study looks at the treaty heterogeneity content, by investigating the impact of the residence country’s double tax relief method and of tax-sparing agreements, on the difference between developing countries’ domestic withholding taxes on dividends on one side, and treaty negotiated withholding taxes at source on portfolio dividends on the other side. Using a dyadic panel dataset of asymmetric double tax treaties between 2005 and 2019, this study suggests first that the difference between domestic and negotiated WHTs on portfolio dividends is higher when the OECD member uses the credit method, as compared to when it uses the exemption method. Second, results suggest that the inclusion of tax-sparing provisions vanishes the positive effect of the credit method at home on the difference between domestic and negotiated WHTs on portfolio dividends, incentivizing developing countries to negotiate higher withholding taxes.

Keywords: double tax treaties, asymmetric investments, withholding tax, dividends, double tax relief method, tax sparing

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Authors: Yuan-lin Liu, Ye Li, Tian Xia

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There are some shortcomings in Chinese existing taxi management modes. This paper suggests to establish the third-party comprehensive information management platform and put forward an evaluation model based on credit. Four indicators are used to evaluate the drivers’ credit, they are passengers’ evaluation score, driving behavior evaluation, drivers’ average bad record number, and personal credit score. A weighted clustering method is used to achieve credit level evaluation for taxi drivers. The management of taxi industry is based on the credit level, while the grade of the drivers is accorded to their credit rating. Credit rating determines the cost, income levels, the market access, useful period of license and the level of wage and bonus, as well as violation fine. These methods can make the credit evaluation effective. In conclusion, more credit data will help to set up a more accurate and detailed classification standard library.

Keywords: credit, mobile internet, e-hailing taxi, management mode, weighted cluster

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Authors: Pao-Peng Hsu, Ying-Hsiu Chen

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Historical data shows that there were high correlations among TAIEX Futures, Electronic Sector Index Futures, Finance Sector Index Futures and Taiwan Top 50 ETF. The performance under various futures is also discussed. We found that the worst portfolio is consisted of T50-ETF and T50-ETF futures and best portfolio is consisted of T50-ETF and TF. It implies that the annual return of a portfolio increases if a portfolio’s risk diversifies.

Keywords: arbitrage opportunities, ETF, futures, TAIEX

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Authors: B. Marasović, S. Pivac, S. V. Vukasović

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Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk.

Keywords: Croatian capital market, Markowitz model, fractional quadratic programming, portfolio optimization, transaction costs

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Authors: Mazura Mokhtar, Adibah Shuib, Daud Mohamad

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Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.

Keywords: portfolio optimization, mathematical programming, multi-objective programming, solution approaches

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Authors: Kujhin Jeong, Sungjoo Lee

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In the past, cross-licensing was made up of various application or commercial patents. Today, cross-licensing is restricted to essential patents, which has emphasized their importance significantly. Literature has shown that patent portfolio provides information for patent protection or strategy decision-making, but little empirical research has found strategic tool of essential patents. This paper will highlight four types of essential patent portfolio and analysis about each strategy in the field of LTE-A. Specifically we collected essential patents of mobile communication company through ETSI (European Telecommunication Standards Institute) and build-up portfolio activity, concentration, diversity, and quality. Using these portfolios, we can understand each company’s strategic character about the technology of LTE-A and comparison analysis of financial results. Essential patents portfolio displays a mobile communication company’s strategy and its strategy’s impact on the performance of a company.

Keywords: essential patent, portfolio, patent portfolio, essential patent portfolio

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Authors: Imad Zeyad Ramadan

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In this paper a genetic algorithm was developed to construct the optimal portfolio based on the Treynor method. The GA maximizes the Treynor ratio under budget constraint to select the best allocation of the budget for the companies in the portfolio. The results show that the GA was able to construct a conservative portfolio which includes companies from the three sectors. This indicates that the GA reduced the risk on the investor as it choose some companies with positive risks (goes with the market) and some with negative risks (goes against the market).

Keywords: oOptimization, genetic algorithm, portfolio selection, Treynor method

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

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In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: portfolio selection, optimization techniques, financial models, stochastic, heuristics

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Authors: Swathi Sampath, V. Kalaichelvi

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The assessment of the risk posed by a borrower to a lender is one of the common problems that financial institutions have to deal with. Consumers vying for a mortgage are generally compared to each other by the use of a number called the Credit Score, which is generated by applying a mathematical algorithm to information in the applicant’s credit report. The higher the credit score, the lower the risk posed by the candidate, and the better he is to be taken on by the lender. The objective of the present work is to use fuzzy logic and linguistic rules to create a model that generates Credit Scores.

Keywords: credit scoring, fuzzy logic, mortgage, risk assessment

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Authors: Marc S. Paolella, Pawel Polak

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The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The latter, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.

Keywords: comfort, financial crises, portfolio optimization, risk monitoring

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Authors: Luisa Unda, Kamran Ahmed, Paul Mather

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We examine the effect of board characteristics on the performance and asset quality of credit unions in Australia, using a large sample covering the period 2004-2012. Credit unions are unique in that they are customer-owned financial institutions and directors are democratically elected by members, which is distinctly different from other financial institutions, such as commercial banks. We find that board remuneration, board expertise, and attendance at board meetings have significantly positive impacts on credit union performance and asset quality, while board members who hold multiple directorships (busy directors), have a significant negative impact on credit union performance. Financial performance also improves with larger boards and long-tenured directors in credit unions. All of these relations hold after we control for alternative measures of performance, credit union characteristics and endogeneity problem.

Keywords: credit unions, corporate governance, board of directors, financial performance, Australia, asset quality

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Authors: Xiaoyu Shen, Fang Fang, Chujun Qiu

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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

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Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira

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Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.

Keywords: credit risk assessment, rule generation, genetic programming, feature selection

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Authors: Saud Al Mahdi

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Traditionally,portfolio managers have been discouraged from timing the market. This means, for example, that equity managers have been forced to adhere strictly to a benchmark with static or relatively stable components, such as the SP 500 or the Russell 3000. This means that the portfolio’s exposures to all risk factors should mimic as closely as possible the corresponding exposures of the benchmark. The main risk factor, of course, is the market itself. Effectively, a long-only portfolio would be constrained to have a beta 1. More recently, however, managers have been given greater discretion to adjust their portfolio’s risk exposures (in particular, the beta of their portfolio) dynamically to match the manager’s beliefs about future performance of the risk factors themselves. This freedom translates into the manager’s ability to adjust the portfolio’s beta dynamically. These strategies have come to be known as smart beta strategies. Adjusting beta dynamically amounts to attempting to "time" the market; that is, to increase exposure when one anticipates that the market will rise, and to decrease it when one anticipates that the market will fall. Traditionally, market timing has been believed to be impossible to perform effectively and consistently. Moreover, if a majority of market participants do it, their combined actions could destabilize the market. The aim of this project is to investigate so-called smart beta strategies to determine if they really can add value, or if they are merely marketing gimmicks used to sell dubious investment strategies.

Keywords: beta, alpha, active portfolio management, trading strategies

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Authors: Manpreet Kaur

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When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.

Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card

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Authors: Lynmar M. Didal, Ramises G. Manzano Jr., Jacque Bon-Isaac C. Aboy

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This study analyzes the performance of global minimum variance and naive portfolios across different economic periods, using monthly stock returns from the Philippine Stock Exchange Index (PSEI), S&P 500, and Dow Jones Industrial Average (DOW). The performance is evaluated through the Sharpe ratio, Sortino ratio, Jensen’s Alpha, Treynor ratio, and Information ratio. Additionally, the study investigates the impact of short selling on portfolio performance. Six-time periods are defined for analysis, encompassing events such as the global financial crisis and the COVID-19 pandemic. Findings indicate that the Naive portfolio generally outperforms the GMV portfolio in the S&P 500, signifying higher returns with increased volatility. Conversely, in the PSEI and DOW, the GMV portfolio shows more efficient risk-adjusted returns. Short selling significantly impacts the GMV portfolio during mid-GFC and mid-COVID periods. The study offers insights for investors, suggesting the Naive portfolio for higher risk tolerance and the GMV portfolio as a conservative alternative.

Keywords: portfolio performance, global minimum variance, naïve portfolio, risk-adjusted metrics, short-selling

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Authors: Abraham Castellanos, Christophe Durville, Sophie Echenim

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In this article, a portfolio optimization problem is performed in a Solvency II context: it illustrates how advanced optimization techniques can help to tackle complex operational pain points around the monitoring, control, and stability of Solvency Capital Requirement (SCR). The market SCR of a portfolio is calculated as a combination of SCR sub-modules. These sub-modules are the results of stress-tests on interest rate, equity, property, credit and FX factors, as well as concentration on counter-parties. The market SCR is non convex and non differentiable, which does not make it a natural optimization criteria candidate. In the SCR formulation, correlations between sub-modules are fixed, whereas risk-driven portfolio allocation is usually driven by the dynamics of the actual correlations. Implementing a portfolio construction approach that is efficient on both a regulatory and economic standpoint is not straightforward. Moreover, the challenge for insurance portfolio managers is not only to achieve a minimal SCR to reduce non-invested capital but also to ensure stability of the SCR. Some optimizations have already been performed in the literature, simplifying the standard formula into a quadratic function. But to our knowledge, it is the first time that the standard formula of the market SCR is used in an optimization problem. Two solvers are combined: a bundle algorithm for convex non- differentiable problems, and a BFGS (Broyden-Fletcher-Goldfarb- Shanno)-SQP (Sequential Quadratic Programming) algorithm, to cope with non-convex cases. A market SCR minimization is then performed with historical data. This approach results in significant reduction of the capital requirement, compared to a classical Markowitz approach based on the historical volatility. A comparative analysis of different optimization models (equi-risk-contribution portfolio, minimizing volatility portfolio and minimizing value-at-risk portfolio) is performed and the impact of these strategies on risk measures including market SCR and its sub-modules is evaluated. A lack of diversification of market SCR is observed, specially for equities. This was expected since the market SCR strongly penalizes this type of financial instrument. It was shown that this direct effect of the regulation can be attenuated by implementing constraints in the optimization process or minimizing the market SCR together with the historical volatility, proving the interest of having a portfolio construction approach that can incorporate such features. The present results are further explained by the Market SCR modelling.

Keywords: financial risk, numerical optimization, portfolio management, solvency capital requirement

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Authors: Kaleb Shiferaw, Berhanu Geberemedhin, Dereje Legesse

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Access to credit is often viewed as a key to transform semi-subsistence smallholders into market oriented producers. However, only a few studies have examined factors that affect farmers’ decision to allocate credit on farm activities in general and livestock production in particular. A trivariate probit model with double selection is employed to identify factors that affect farmers’ decision to allocate credit on livestock production using data collected from smallholder farmers in Ethiopia. After controlling for two sample selection bias – taking credit for the production season and decision to allocate credit on farm activities – land ownership and access to a livestock centered extension service are found to have a significant (p<0.001) effect on farmers decision to use credit for livestock production. The result showed farmers with large land holding, and access to a livestock centered extension services are more likely to utilize credit for livestock production. However since the effect of land ownership squared is negative the effect of land ownership for those who own a large plot of land lessens. The study highlights the fact that improving access to credit does not automatically translate into more productive households. Improving farmers’ access to credit should be followed by a focused extension services.

Keywords: livestock production, credit access, credit allocation, household decision, double sample selection

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Authors: Peng Liu

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Deep Q networks (DQNs) represent a significant advancement in reinforcement learning, utilizing neural networks to approximate the optimal Q-value for guiding sequential decision processes. This paper presents a comprehensive introduction to reinforcement learning principles, delves into the mechanics of DQNs, and explores its application in portfolio optimization. By evaluating the performance of DQNs against traditional benchmark portfolios, we demonstrate its potential to enhance investment strategies. Our results underscore the advantages of DQNs in dynamically adjusting asset allocations, offering a robust portfolio management framework.

Keywords: deep reinforcement learning, deep Q networks, portfolio optimization, multi-period optimization

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Authors: Todor Nickolov Stoyanov

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These factors appear as a reason for difficulties in financing from programs for rural development of the European Union. Credit conditions for commercial banks are difficult to implement, and its interest rate is too high. One of the possibilities for short-term loans at preferential conditions for the small and medium-sized agricultural and forest owners is credit cooperative. After the changes, occurred in the country after 1990, the need to restore credit cooperatives raised. The purpose for the creation of credit cooperatives is to assist private agricultural and forest owners to take care for them, to assist in the expansion and strengthening of their farms, to increase the quality of life and to improve the local economy. It was found that: in Bulgaria there is a legal obstacle for credit cooperatives to expand their business in the deposit and lending sphere; private forest and agricultural owners need small loans to solve a small problem for a certain season; providing such loans is not attractive for banks, but it is extremely necessary for owners of small forests and lands; if a special law on credit cooperatives is adopted, as required by the Cooperatives Act, it will allow more local people to be members of such credit structures and receive the necessary loans. In conclusion, proposals to create conditions for the development of credit cooperatives in the country are made and positive results expected from the creation of credit cooperatives, are summarized.

Keywords: cooperatives, credit cooperatives, forestry, forest owners

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Authors: Darius Danesh, Michael J. Ryan, Alireza Abbasi

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Project Portfolio Management (PPM) is an essential component of an organisation’s strategic procedures, which requires attention of several factors to envisage a range of long-term outcomes to support strategic project portfolio decisions. To evaluate overall efficiency at the portfolio level, it is essential to identify the functionality of specific projects as well as to aggregate those findings in a mathematically meaningful manner that indicates the strategic significance of the associated projects at a number of levels of abstraction. PPM success is directly associated with the quality of decisions made and poor judgment increases portfolio costs. Hence, various Multi-Criteria Decision Making (MCDM) techniques have been designed and employed to support the decision-making functions. This paper reviews possible option to improve the decision-making outcomes in the organisational portfolio management processes using the Analytic Hierarchy Process (AHP) both from academic and practical perspectives and will examine the usability, certainty and quality of the technique. The results of the study will also provide insight into the technical risk associated with current decision-making model to underpin initiative tracking and strategic portfolio management.

Keywords: analytic hierarchy process, decision support systems, multi-criteria decision making, project portfolio management

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Authors: Sheng-Ching Wu

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This paper examines the interaction between mutual fund performance and portfolio turnover. Active trading could affect fund performance, but underperforming funds could also be traded actively at the same time to perform well. Therefore, we used two-stage least squares to address with simultaneity. The results indicate that funds with higher portfolio turnovers exhibit inferior performance compared with funds having lower turnovers. Moreover, funds with poor performance exhibit higher portfolio turnover. The findings support the assumptions that active trading erodes performance, and that fund managers with poor performance attempt to trade actively to retain employment.

Keywords: mutual funds, portfolio turnover, simultaneity, two-stage least squares

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Authors: Juhan Kim, Jinsoo Kim

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South Korea cannot import natural gas in any form other than LNG because of the division of South and North Korea. Further, the high proportion of natural gas in the national energy mix makes this resource crucial for energy security in Korea. Expansion of Panama Canal will allow for reducing the cost of shipping between the Far East and U.S East. Panama Canal expansion can have significant impacts on South Korea. Due to this situation, we review the natural gas optimal portfolio by considering the uniqueness of the Korean Natural gas market and expansion of Panama Canal. In order to assess Korea’s natural gas optimal portfolio, we developed natural gas portfolio model. The model comprises two steps. First, to obtain the optimal long-term spot contract ratio, the study examines the price level and the correlation between spot and long-term contracts by using the Markowitz, portfolio model. The optimal long-term spot contract ratio follows the efficient frontier of the cost/risk level related to this price level and degree of correlation. Second, by applying the obtained long-term contract purchase ratio as the constraint in the linear programming portfolio model, we determined the natural gas optimal import portfolio that minimizes total intangible and tangible costs. Using this model, we derived the optimal natural gas portfolio considering the expansion of Panama Canal. Based on these results, we assess the portfolio for natural gas import to Korea from the perspective of energy security and present some relevant policy proposals.

Keywords: natural gas, Panama Canal, portfolio analysis, South Korea

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Authors: Imen Dhaou

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This study examines conditional Value at Risk by applying the GJR-EVT-Copula model, and finds the optimal portfolio for eight Dow Jones Islamic-conventional pairs. Our methodology consists of modeling the data by a bivariate GJR-GARCH model in which we extract the filtered residuals and then apply the Peak over threshold model (POT) to fit the residual tails in order to model marginal distributions. After that, we use pair-copula to find the optimal portfolio risk dependence structure. Finally, with Monte Carlo simulations, we estimate the Value at Risk (VaR) and the conditional Value at Risk (CVaR). The empirical results show the VaR and CVaR values for an equally weighted portfolio of Dow Jones Islamic-conventional pairs. In sum, we found that the optimal investment focuses on Islamic-conventional US Market index pairs because of high investment proportion; however, all other index pairs have low investment proportion. These results deliver some real repercussions for portfolio managers and policymakers concerning to optimal asset allocations, portfolio risk management and the diversification advantages of these markets.

Keywords: CVaR, Dow Jones Islamic index, GJR-GARCH-EVT-pair copula, portfolio optimization

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Authors: E. O. Fakoya, B. G. Abiona, W. O. Oyediran, A. M. Omoare

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This study examined the socio-economic effects of micro-credit on small scale poultry farmers’ livelihood in Ado Odo-Ota Local Government area of Ogun State. Purposive sampling method was used to select eighty (80) small scale poultry farmers that benefited in micro credit. Interview guide was used to obtain information on the respondents’ socio-economic characteristic, sources of micro-credit and the effects of micro-credit on their livelihood. The results revealed that most of the respondents (77.50 %) were males while half (40.00%) of the respondents were between the ages of 31-40 years. A high proportion (72.50%) of the respondents had formal education. The major sources of micro credit to small scale poultry farmers were cooperative society (47.50%) and personal savings (20.00%). The findings also revealed that micro-credit had positive effect on the assets and livelihoods of small scale poultry farmers’ livelihood. Results of t-test analysis showed a significant difference between the effects before and after micro-credit on small-scale poultry farmers’ Livelihood at p < 0.05. The study recommends that formal lending institution should be given necessary support by government to enable poultry farmers have access to credit facilities in the study area.

Keywords: micro-credit, effects, livelihood, poultry farmers, socio-economic, small scale

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Authors: Mati Ullah, Shams Ur Rahman

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The purpose of this research study is to investigate the effect of macroeconomic and bank-specific factors on credit risk in Islamic banking in Pakistan. The future of financial institutions largely depends on how well they manage risks. Credit risk is an important type of risk affecting the banking sector. The current study has taken quarterly data for the period of 6 years, from 1st July 2014 to 30 Jun 2020. The data set consisted of secondary data. Data was extracted from the websites of the State Bank and World Bank and from the financial statements of the concerned banks. In this study, the Ordinary least square model was used for the analysis of the data. The results supported the hypothesis that macroeconomic factors and bank-specific factors have a significant effect on credit risk. Macroeconomic variables, Inflation and exchange rates have positive significant effects on credit risk. However, gross domestic product has a negative significant relationship with credit risk. Moreover, the corporate rate has no significant relation with credit risk. Internal variables, size, management efficiency, net profit share income and capital adequacy have been proven to influence positively and significantly the credit risk. However, loan to deposit-has a negative insignificance relationship with credit risk. The contribution of this article is that similar conclusions have been made regarding the influence of banking factors on credit risk.

Keywords: credit risk, Islamic banks, macroeconomic variables, banks specific variable

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