Suchergebnisse

Purpose
This paper aims to develop a barrier cap option model, i.e. a cap option model where default can occur at any time before the maturity date, to evaluate the equity and the default risk of a bank. The model implies the bank as a liquidity provider that one institution carriers out both lending and deposit-taking functions under the same roof. This paper studies the impacts of demand deposits and capital regulation on the optimal bank interest margin, i.e. the spread between the loan rate and the deposit rate.


Design/methodology/approach
This paper characterizes the bank's equity value by a barrier cap option framework. In the model, default can occur at any time before the maturity and loan markets are imperfectly competitive.


Findings
This paper has two main results. First, increases in demand deposits reduce the bank's interest margin and further increase the bank's default risk. The negative effect on the optimal bank interest margin which ignores the barrier leads to significant overestimation; the positive effect on the default risk which ignores the barrier leads to underestimation. Second, the same pattern of capital regulation as previously applies. Capital regulation as such makes the bank more prone to loan risk-taking, thereby adversely affecting the stability of banking system.


Originality/value
This paper reintroduces the knock-out value and bank interest margin determination within a synergy banking function to the cap option model. The results confirm the need to model bank equity as a barrier cap option and demonstrate its usefulness in capital regulation.

In this paper, we develop a contingent claim model to evaluate the equity, default risk, and efficiency gain/loss from managerial overconfidence of a shadow-banking life insurer under the purchases of distressed assets by the government. Our paper focuses on managerial overconfidence where the chief executive officer (CEO) overestimates the returns on investment. The investment market faced by the life insurer is imperfectly competitive, and investment is core to the provision of profit-sharing life insurance policies. We show that CEO overconfidence raises the default risk in the life insurer&rsquo ; s equity returns, thereby adversely affecting the financial stability. Either shadow-banking involvement or government bailout attenuates the unfavorable effect. There is an efficiency gain from CEO overconfidence to investment. Government bailout helps to reduce the life insurer&rsquo ; s default risk, but simultaneously reduce the efficiency gain from CEO overconfidence. Our results contribute to the managerial overconfidence literature linking insurer shadow-banking involvement and government bailout in particular during a financial crisis.

There is an increasing influence of machine learning in business applications, with many solutions already implemented and many more being explored. Since the global financial crisis, risk management in banks has gained more prominence, and there has been a constant focus around how risks are being detected, measured, reported and managed. Considerable research in academia and industry has focused on the developments in banking and risk management and the current and emerging challenges. This paper, through a review of the available literature seeks to analyse and evaluate machine-learning techniques that have been researched in the context of banking risk management, and to identify areas or problems in risk management that have been inadequately explored and are potential areas for further research. The review has shown that the application of machine learning in the management of banking risks such as credit risk, market risk, operational risk and liquidity risk has been explored; however, it doesn't appear commensurate with the current industry level of focus on both risk management and machine learning. A large number of areas remain in bank risk management that could significantly benefit from the study of how machine learning can be applied to address specific problems.

In this paper, we develop a contingent claim model to examine the optimal bank interest margin, i.e., the spread between the domestic loan rate and the deposit market rate of an international bank in distress. The framework is used to evaluate the cross-border lending efficiency for a bank that participates in a government capital injection program, a government intervention used in response to the 2008 financial crisis. This paper suggests that government capital injection is an appropriate way to recapitalize the distressed bank, enhancing the bank interest margin and survival probability. Nevertheless, the government capital injection lacks efficiency when the bank's cross-border lending is high. Stringent capital regulation, suggested to prevent future crises by literature, leads to superior lending efficiency when the government capital injection is low.