scholarly journals Dilemma of deposit insurance policy in ASEAN countries: Does it promote banking industry stability or moral hazard?

2018 ◽  
Vol 18 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Suhal Kusairi ◽  
Nur Azura Sanusi ◽  
Abdul Ghafar Ismail
2006 ◽  
Vol 7 (1) ◽  
pp. 87-116
Author(s):  
Seok-Weon Lee

This is an empirical study that examines how the Federal Deposit Insurance Corporation Improvement Act (FDICIA) of 1991 in the U.S. banking industry affects the moral hazard risk-taking incentives of banks. We find that FDICIA appears to be effective in significantly reducing the systematic risk-taking incentives of the banks. Considering that the banks' asset portfolios are necessarily largely systematic risk-related, the significant decrease in their systematic risk-taking incentives provides some evidence of the effectiveness of FDICIA. However, with respect to the nonsystematic risk-taking behavior, the results generally indicate statistically insignificant decreases in the risk-taking incentives after FDICIA. To well-diversified investors who can diversify nonsystematic risk away, nonsystematic risk may not be a risk any more. However, to maintain a sound banking environment and to reduce the risk to individual banks, this result implies that regulatory agents should monitor the banks’ nonsystematic risk-taking behavior more closely, as long as it is positively related to the banks’ failures. We further test the change in the risk-taking incentives by partitioning the full sample into two groups: Banks with higher moral hazard incentives as those with larger asset size and lower capital ratio and banks with lower moral hazard incentives as those with smaller asset size and higher capital ratio. The main result for this test is that, with FDICIA, the decrease in the risk-taking incentives of the banks with higher moral hazard incentives (larger asset-size and lower capital-ratio banks) is less than that of the banks with lower moral hazard incentives (smaller asset-size and higher capital-ratio banks), with respect to both systematic and nonsystematic risk-taking measures. Furthermore, the change in the nonsystematic risk-taking incentives of the banks with higher moral hazard incentives is rather mixed, while their systematic incentives are decreased. These findings imply that the regulatory agents should allocate more time and effort toward monitoring the banks with higher moral hazard incentives with particular emphasis on their nonsystematic risk-taking behavior.


Risks ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 45 ◽  
Author(s):  
Hirbod Assa ◽  
Mostafa Pouralizadeh ◽  
Abdolrahim Badamchizadeh

While the main conceptual issue related to deposit insurances is the moral hazard risk, the main technical issue is inaccurate calibration of the implied volatility. This issue can raise the risk of generating an arbitrage. In this paper, first, we discuss that by imposing the no-moral-hazard risk, the removal of arbitrage is equivalent to removing the static arbitrage. Then, we propose a simple quadratic model to parameterize implied volatility and remove the static arbitrage. The process of removing the static risk is as follows: Using a machine learning approach with a regularized cost function, we update the parameters in such a way that butterfly arbitrage is ruled out and also implementing a calibration method, we make some conditions on the parameters of each time slice to rule out calendar spread arbitrage. Therefore, eliminating the effects of both butterfly and calendar spread arbitrage make the implied volatility surface free of static arbitrage.


1993 ◽  
Vol 75 (1) ◽  
Author(s):  
Anjan Thakor

2020 ◽  
pp. 19-19
Author(s):  
José Alejandro Fernández Fernández ◽  
Virginia Vázquez ◽  
Juan Antonio Vicente Virseda

This paper analyzes the relationship between the size of the entities in the US banking system and their economic-financial situation. The objective of this study is to group different economic and financial variables of the entities together into factors that characterize the US banking system and identify and identify how the factors vary according to the size of the entities. To do this, we start from the values taken by 32 economic-financial and regulatory ratios, obtained directly from the Federal Deposit Insurance Corporation (FDIC), for a period between the first quarter of 1990 and the penultimate of 2016. With this data it is performed a factorial analysis that allows synthesizing the 32 variables in 7 factors and, at the same time, obtaining relationships between these variables and the size and between themselves. Finally, through a neural network, the previous factors are hierarchized according to the influence that the size of the entities exerts on them. Among the conclusions reached, it should be noted that the loan structure is the factor that best classifies the size. It also determines the existence of a negative ?profitability-solvency? relationship with larger entities, (Assets> $ 250 B.) and smaller ones (Assets <$ 100 M.), as well as demonstrating the existence of moral hazard and the need for regulation that limits said risk (because the largest entities are the least solvent and assume the most risks).


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