The Impact of Corporate Governance on Banks Performance and Loan Quality： Evidence From Italian Cooperative Banks

In the banking system, a context characterized by growing instability and by the speed of evolution of business dynamics, the system of corporate governance plays a key role, both for large banks and for banks with a smaller size. The paper aims to investigate the influence of corporate governance of the banks that operate in the cooperative credit system on performance and quality of loans, over the years 2010-2011-2012. In order to achieve this aim, the following research hypotheses have been formulated： There is a statistically significant relationship between the size and the structure of the board and banks Performance operating in the cooperative credit system; there is a statistically significant relationship between the size and structure of the board and the credit quality of banks operating in the cooperative credit system. The analysis is conducted on a sample composed of 48 Italian banks, divided into 24 cooperative banks and 24 popular banks. The sample is made up of banks from all over Italy and very different in terms of dimension. For the sample construction, data relative to governance of banks were collected from the balance sheets in the period from June to August 2014. Financial-economic data were collected from the Financial Statements and from Bankscope database. The methodology of analysis is based on multivariate OLS （ordinary least squares） regression models. The main results refer to the presence of significant relationships between board dimension and the quality of loans and among the number of committees and performance and the quality of loans. The presence of a significant and negative relationship between the board dimension and the ratio of impaired loans to gross loans indicates the possibility that enlargement of board dimension allows a better quality of loans. The presence of a positive relationship between the number of committees and the ratio of impaired loans to gross loans signals the possibility that a greater number of committees can produce a worse quality of loans. The presence of a negative relationship between the number of committees and bank performance suggests to limit and manage the complexity of governance in banks operating in the cooperative credit system.

The Effects of Intangible Assets （IA） on the Loan Interest Rates for Small- and Medium-Sized Enterprises （SMEs） in Taiwan

This study is motivated by the lack of direct empirical research on the relationship between intangible assets （IA） and loan interest rates for small- and medium-sized enterprises （SMEs） in emerging markets. This study uses a multivariate regression to investigate the effects of 1A on loan interest rates by focusing on SMEs. Using a panel sample of 186 publicly-listed SMEs with 952 annual observations in Taiwan from 2001 to 2006, the empirical findings indicate that an SME＇s IA does negatively affect loan interest rates. The main contribution of this study lies in its direct testing of whether IA can affect the loan interest rates for SMEs in an emerging market. The finding provides empirical evidence that an SME with greater IA leads to lower interest rates on bank loans, implying that SMEs should strive to invest in IA and enhance their knowledge management for obtaining more benefits of loan interest rates. Furthermore, the findings may provide empirical evidence for SMEs in emerging markets and can be compared with those for firms in industrialized economies.

Multi-period Bank Hedging with Interest Rate Futures

In this paper, a model for multi-period bank hedging with interest rate futures is set up. Formulas for the optimal dynamic multi-period bank and static bank hedge ratio are derived. The described model offers the potential benefits of： （1） although these formulas are developed for the case of direct sheet balance multi-period hedging, the framework used is sufficiently flexible so that these formulas can be applied to bank loan or deposit multi-period hedging situations respectively. （2） Periodic modification and updating of the interest rate futures position, as suggested by interest rates, throughout the bank hedging horizons. （3） This paper examines a situation in which the return of loan, the interest rate of deposit and the equity capital of bank, and interest rate futures prices are cointergrated, Multi-period bank hedging formulas are derived under three-dimensional stochastic volatility model. However, empirical research is required for validating this model.