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We discuss the valuation of credit derivatives in extreme regimes such as when the time-to-maturity is short, or when payoff is contingent upon a large number of defaults, as with senior tranches of collateralized debt obligations. In these cases, risk aversion may play an important role, especially when there is little liquidity, and utility-indifference valuation may apply. Specifically, we analyze how short-term yield spreads from defaultable bonds in a structural model may be raised due to investor risk aversion.

The main theme of this volume is credit risk and credit derivatives. Recent developments in financial markets show that appropriate modeling and quantification of credit risk is fundamental in the context of modern complex structured financial products. Moreover, there is a need for further developments in our understanding of this important area. In particular modeling defaults and their correlation has been a real challenge in recent years, and still is. This problem is even more relevant after the so-called subprime crisis that hit in the summer of 2007. This makes the volume very timely and hopefully useful for researchers in the area of credit risk and credit derivatives.

This paper examines the clustering of return volatility within industries by comparing the short‐run responses of stock returns to the arrival of macroeconomic news across several industries. We hypothesize that some industries have distinctive qualities which influence the sensitivity of companies’ equity value to information releases. To test this hypothesis, we sample intraday stock price data of ten firms from three industries ‐ General Industry, Banking, and Real Estate Trusts ‐ and conduct the Brown‐Forsythe‐Modified Levene tests. The evidence shows that there exist different degrees of responses to the release of macroeconomic news and consequently different degrees of return volatility clustering: strongest in General Industry, less strong in Banking, and weak in Real Estate Investment Trusts.