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Peer-to-Peer (P2P) lending, which makes borrowers and investors meet directly through online platforms bypassing traditional financial institutions, is an emerging financing market after the traditional financial institutions crushed during the global financial crisis from 2007 to 2009. P2P lending platforms meet the credit demand more efficiently and play a vital role for the credit market and economic activity. This study sheds light on whether the credit spread of P2P lending is well predictive of economic activity compared to the bond credit spread which has been fully investigated in prior studies. Our findings show that the P2P credit spread performs similarly in predicting the economic activity as bond credit spread only during the financial crisis. However, the predictive power of P2P credit spread becomes inverse during the noncrisis periods since P2P lending platforms provide an alternative and easier financing channel to individuals who hardly borrow money for refinancing from traditional financial institutions. This study highlights the alternative role of P2P lending platform in financing and provides the evidence of different predictive powers of P2P credit spread on economic activity in different time periods.

We set out, in this paper, to extend the Das and Sundaram (2000) model as a means of simultaneously considering correlated default risk structure and counter-party risk. The multinomial model established by Kamrad and Ritchken (1991) is subsequently modified in order to facilitate the development of a computational algorithm for valuing two types of active credit derivatives, credit-spread options and default baskets. From our numerical examples, we find that along with the correlated default risk, the existence of counter-party risk results in a substantially lower valuation of credit derivatives. In addition, we find that different settings of the term structure of interest rate volatility also have a significant impact on the value of credit derivatives.

This chapter provides a comprehensive overview of the young, but rapidly growing sovereign credit default swap (CDS) market, describes the function, trading, history, market participants, key statistical and stylized facts about CDS prices, determinants, price discovery, and risk issues.

This chapter reassesses the economics of interest rate risk management in light of the global financial crisis by developing a derivative-based integrated treatment of interest rate and credit risk interrelation. The decade-long historical data on credit default swap spreads and interest rate swap rates are used as proxy measures for credit risk and interest rate risk, respectively. An elasticity of interest rate risk and credit risk, considered a function of the business cycle phases, maturity of instruments, economic sector, creditworthiness, and other macroeconomic parameters, is investigated for optimizing economic capital. This chapter sheds light on how financial institutions may address hedge strategies against downside risks implementing the proposed derivative-based integrated treatment of interest rate and credit risk assessment allowing for optimization of interest rate swap contracts. The developed framework of integrated interest rate and credit risk management is of special importance for emerging markets heavily dependent on foreign capital as it potentially allows emerging market banks to improve risk management practices in terms of capital adequacy and Basel III rules. Analyzing diversification versus compounding effects, it allows enhancing financial stability through jointly optimizing Pillar 1 and Pillar 2 economic capital.

This study investigates the impacts of operational risks and corporate governance on bond yield spreads, examining their impacts on bond yield spreads during the COVID-19 pandemic. The results indicate that operational risks significantly raise yield spreads, especially for high-leverage firms. Moreover, a higher independent director percentage reduces debt costs. Furthermore, the results reveal more pronounced effects of operational risks on yield spreads during the COVID-19 pandemic, with these risks increasing the financing costs for large firms. When the effect of the independent director percentage on the yield spreads increases, this consequently raises the debt costs for large firms.

Pledging collateral to secure loans is a prominent feature in financing contracts around the world. Existing theories disagree on why borrowers pledge collateral. It is even more challenging to understand why in some countries collateral coverage exceeds, for example, 300% of the value of a loan. This study looks at the association between collateral coverage and country-level governance and various institutional proxies. It investigates the economic implications of steep collateral coverage and sketches policy options to lower ex-ante asymmetric information and ex-post agency problems. Within this framework, should a lender collect the debt forcibly on default and liquidated assets fetch prices below outstanding loan values, the lender’s loss is covered through credit insurance, which would significantly reduce the need for steep collateral coverage. This proposal may increase level of private credit, investment and growth; particularly, in a number of developing countries where collateral spread is the main inhibitor of finance.

The credit migration process contains important information about the dynamics of a firm's credit quality, therefore, it has a significant impact on its relevant credit derivatives. We present a jump diffusion approach to model the credit rating transitions which leads to a partial integro-differential equation (PIDE) formulation, with defaults and rating changes characterized by barrier crossings. Efficient and reliable numerical solutions are developed for the variable coefficient equation that result in good agreement with historical and market data, across all credit ratings. A simple adjustment in the credit index drift converts the model to be used in the risk-neutral setting, which makes it a valuable tool in credit derivative pricing.