LES DÉTERMINANTS DE LA PERFORMANCE DE REMBOURSEMENT DES MICROCRÉDITS EN TUNISIE

Our work is part of the quest for sustainability of MFIs. To ensure sustainability, an MFI must be effective. It must, among others, face many risks and in particular the default risk. A question arises: what are the determinants of portfolio quality of MFIs? In other words, what are the determinants that influence delays in payment of MFIs? The interest of this research is twofold. The first is practical: knowing the importance of performance measures of microcredit as a precondition for the efficiency and financial performance of MFIs, this study identified determinants of the reimbursement rate in an MFI of Tunisia. It may even give an evidence for banks to intervene on the market of micro credit. The second is methodological: to find the determinants of reimbursement behaviour in MFIs, a binary logistic regression is used, while differing in explanatory variables between key variables and moderators’ ones, which was not met previously in the literature. The results showed that among the variables related to the characteristics of the loan, the loan amount and the borrower's experience with the MFI affect the rate of reimbursement. The credit increases the likelihood of default. Unlike, when borrower's experience with the MFI increases, the risk of default decreases. A relationship between the industry and the repayment rate has not been verified. For variables related to the characteristics of the borrower, age, educational level and marital status of the borrower appear to affect the relationship between the risk of default and the amount of credit. The effect of the credit amount on the default risk decreases as age and level of education increases. In addition, this effect is more important for married compared to the unmarried. For gender, we found that the effect of maturity on the risk of default is not the same for men or women borrowers. It seems that when the maturity increases, men provide reimbursement rates lower than women.     

Markets liquidity risk under extremal dependence: Analysis with VaRs methods

Value-at-Risk (VaR) is a widely used tool for assessing financial market risk. In practice, the estimation of liquidity extreme risk by VaR generally uses models assuming independence of bid–ask spreads. However, bid–ask spreads tend to occur in clusters with time dependency, particularly during crisis period. Our paper attempts to fill this gap by studying the impact of negligence of dependency in liquidity extreme risk assessment of Tunisian stock market. The main methods which take into account returns dependency to assess market risk is Time series–Extreme Value Theory combination. Therefore we compare VaRs estimated under independency (Variance–Covariance Approach, Historical Simulation and the VaR adjusted to extreme values) relatively to the VaR when dependence is considered. The efficiency of those methods was tested and compared using the backtesting tests. The results confirm the adequacy of the recent extensions of liquidity risk in the VaR estimation. Therefore, we prove a performance improvement of VaR estimates under the assumption of dependency across a significant reduction of the estimation error, particularly with AR (1)-GARCH (1,1)-GPD model.