Corporate defaults exhibit two key characteristics that have profound implications for default risk management. First, default risk is correlated through time. Bankruptcies are normally the end of a process that begins with adverse economic shock and end with financial distress. Although some bankruptcies are unexpected and, therefore, are point events, like Enron and Worldcom, investors become aware of the company’s difficulties some years prior to the bankruptcy event. Second, financial wealth of companies in the same industry, or within the same economic area, is a function of managers’ skills and common factors that introduce correlations.
Companies’ default risk is linked through sector-specific and/or macroeconomic factors. Whilst a great deal of effort has been made by practitioners to measure and explain companies’ default correlations, academics have only recently began to devote attention to this issue. The existing literature on default correlations can be divided into two approaches: the structural approach that models default correlations through companies’ assets values; and the reduced-form approach that models default correlations through default intensities. While financial institutions, namely banks, are aware of these relationships, their ability to model such correlations is still not fully developed. Basle Committee on Banking and Supervision (BCBS 1999, p. 31) states “… the factors affecting the credit worthiness of obligors sometimes behave in a related manner…” which “… requires consideration of the dependencies between the factors determining credit related losses”. Whilst there are many different models and approaches to compute default probabilities, there is no consensus on the importance of different factors that drive default correlations. BCBS (1999) report points out that whilst practitioners have been managing and studying this dependence, there is a lack of theoretical and empirical work on this issue that tests the robustness of the frameworks.
In this paper, we concentrate our empirical investigation on the determinants of default correlation. Our analysis comprises three stages: First, we apply a set of structural models, Merton (M, 1974), Longstaff and Schwartz (LS, 1995) and Ericsson and Reneby (ER, 1998), to compute companies’ expected default probabilities (EDPs). Second, based on cross-sectional tests we analyse the effect of volatility and idiosyncratic risk on EDPs. Given that unexpected events or fraudulent defaults lead to market-wide jumps in credit spreads, which reduce the ability to diversify this risk, it is important to examine the relationship between company’s idiosyncratic risk and bankruptcy. Third, using a factor-analytical technique, we extract common or latent factors that explain default correlations. This analysis enables us to assess the extent to which default correlation can be ascribed to the latent factors and to the systematic variables from capital and bond markets.
