Ratings Migration and the Business Cycle, With Application to Credit Portfolio Stress Testing

The turmoil in the capital markets in 1997 and 1998 has highlighted the need for systematic stress testing of banks' portfolios, including both their trading and lending books. We propose that underlying macroeconomic volatility is a key part of a useful conceptual framework for stress testing credit portfolios, and that credit migration matrices provide the specific linkages between underlying macroeconomic conditions and asset quality. Credit migration matrices, which characterize the expected changes in credit quality of obligors, are cardinal inputs to many applications, including portfolio risk assessment, modeling the term structure of credit risk premia, and pricing of credit derivatives. They are also an integral part of many of the credit portfolio models used by financial institutions. By separating the economy into two states or regimes, expansion and contraction, and conditioning the migration matrix on these states, we show that the loss distribution of credit portfolios can differ greatly, as can the concomitant level of economic capital to be assigned.Credit risk, stress testing, ratings migration, credit portfolio management

Modeling Liquidity Risk With Implications for Traditional Market Risk Measurement and Management

Market risk management traditionally has focussed on the distribution of portfolio value changes resulting from moves in the midpoint of bid and ask prices. Hence the market risk is really in a “pure” form: risk in an idealized market with no “friction” in obtaining the fair price. However, many markets possess an additional liquidity component that arises from a trader not realizing the mid-price when liquidating her position, but rather the mid-price minus the bid-ask spread. We argue that liquidity risk associated with the uncertainty of the spread, particularly for thinly traded or emerging market securities under adverse market conditions, is an important part of overall risk and is therefore an important component to model. We develop a simple liquidity risk methodology that can be easily and seamlessly integrated into standard value-at-risk models, and we show that ignoring the liquidity effect can produce underestimates of market risk in emerging markets by as much as 25-30%. Furthermore, we show that the BIS inadvertently is already monitoring liquidity risk, and that by not modeling it explicitly and therefore capitalizing against it, banks will be experiencing surprisingly many violations of capital requirements, particularly if their portfolios are concentrated in emerging markets

The Role of Industry, Geography and Firm Heterogeneity in Credit Risk Diversification

In theory the potential for credit risk diversification for banks could be substantial. Portfolio diversification is driven broadly by two characteristics: the degree to which systematic risk factors are correlated with each other and the degree of dependence individual firms have to the different types of risk factors. We propose a model for exploring these dimensions of credit risk diversification: across industry sectors and across different countries or regions. We find that full firm-level parameter heterogeneity matters a great deal for capturing differences in simulated credit loss distributions. Imposing homogeneity results in overly skewed and fat-tailed loss distributions. These differences become more pronounced in the presence of systematic risk factor shocks: increased parameter heterogeneity greatly reduces shock sensitivity. Allowing for regional parameter heterogeneity seems to better approximate the loss distributions generated by the fully heterogeneous model than allowing just for industry heterogeneity. The regional model also exhibits less shock sensitivity