Based on the UCP 500 and UCP 600, this paper analyses the two principles of letter of credit, in order to prepare the theory basis for the risks analysis afterwards. For the different parties (exporter, importer, banks), possible risks and frauds are shown with case studies. The paper also puts forward the advice for various risks and intends to indicate that risks still exit in letter-of-credi...

We model the effects on banks of the introduction of a market for credit derivatives; in particular, credit-default swaps. A bank can use such swaps to temporarily transfer credit risks of their loans to others, reducing the likelihood that defaulting loans trigger the bank’s financial distress. Because credit derivatives are more flexible at transferring risks than are other, more established ...

We study the role of labour and credit market imperfections for the determination of equilibrium unemployment. In the credit market loan contracts are negotiated between financiers and firms, both possessing bargaining power, while the firms and organized labour bargain over the base wage. The sequential labour and credit market negotiations are assumed to take place conditional on the firm hav...

In this paper, we study industry equilibrium under the assumptions that (1) #rms need outside #nancing and (2) they have a moral hazard problem in taking potentially excessive risks. We characterize an industry equilibrium with credit rationing, where #rms choose not to take risks, and compare this to the industry equilibrium in the absence of credit rationing. In both cases, we show that compe...

Empirical evidence documents a tight link between aggregate and firm-level investment and corporate credit spreads. Moreover, it has been shown that credit spreads largely reflect a compensation for bearing macroeconoimc risks. We use a tractable model with recursive preferences and time varying macroeoconomic risk to investigate the link between aggregate risk and corporate policies in a produ...

Corporate credit scoring is important for investors and banks in risk management. However, the high dimensional data available from public financial statements make credit analysis difficult. To address the problem, dimensionality reduction is a key step to enhance scoring accuracy. By using semi-supervised discriminant analysis (SSDA) and support vector machines (SVMs), this study develops a n...