The asymptotic single risk factor approach is a framework for determining regulatory capital charges for credit risk, and it has become an integral part of the second Basel Accord. Within this approach, a key parameter is the average asset correlation. We examine the empirical relationship between this parameter, firm probability of default and firm asset size measured by the book value of assets. Using data from year-end 2000, credit portfolios consisting of US, Japanese, and European firms are analyzed. The empirical results suggest that average asset correlation is a decreasing function of probability of default and an increasing function of asset size. The results suggest that these factors may need to be accounted for in the final calculation of regulatory capital requirements for credit risk.

[Since bank credit lines are a major source of corporate funding, we examine the determinants of their usage with a comprehensive database of Spanish corporate credit lines. A line's default status is a key factor driving its usage, which increases as firm financial conditions worsen. Firms with prior defaults access their credit lines less, suggesting that bank monitoring influences firms' usage decisions. Line usage has an aging effect that causes it to decrease by roughly 10% per year of its life. Lender characteristics, such as the length of a firm's banking relationships, as well as macroeconomic conditions, affect usage decisions.]

A common assumption in the academic literature and in the supervision of banking systems is that franchise value plays a key role in limiting bank risk-taking. As market power is the primary source of franchise value, reduced competition in banking markets has been seen as promoting banking stability. A recent paper by Martínez-Miera and Repullo (MMR, 2010) shows that a nonlinear relationship theoretically exists between bank competition and risk-taking in the loan market. We test this hypothesis using data from the Spanish banking system. After controlling for macroeconomic conditions and bank characteristics, we find support for this nonlinear relationship using standard measures of market concentration in both the loan and deposit markets. When direct measures of market power, such as Lerner indices, are used, the empirical results are more supportive of the original franchise value hypothesis, but only in the loan market. Overall, the results highlight the empirical relevance of the MMR model, even though further analysis across other banking markets is needed.

We use Call Report data to examine the effects of the Paycheck Protection Program (PPP) and the PPP Liquidity Facility (PPPLF) on small business and farm lending by individual commercial banks. As program participation was associated with small business lending, we adopt an instrumental variables approach to identify causal implications based on historical bank relationships with the Small Business Administration and the Federal Reserve’s discount window. Our results indicate that both programs encouraged lending growth over the first half of 2020. However, while the PPP encouraged greater lending across all banks, only small and medium-sized bank lending growth was significantly related to participation in the PPPLF.

The Monetary Control Act of 1980 requires the Federal Reserve System to provide payment services to depository institutions through the 12 Federal Reserve Banks at prices that fully reflect the costs a private-sector provider would incur, including a cost of equity capital (COE). Although Fama and French [Fama, E.F., French, K.R., 1997. Industry costs of equity. Journal of Financial Economics 43, 153–193] conclude that COE estimates are “woefully” and “unavoidably” imprecise, the Reserve Banks require such an estimate every year. We examine several COE estimates based on the CAPM model and compare them using econometric and materiality criteria. Our results suggest that the benchmark CAPM model applied to a large peer group of competing firms provides a COE estimate that is not clearly improved upon by using a narrow peer group, introducing additional factors into the model, or taking account of additional firm-level data, such as leverage and line-of-business concentration. Thus, a standard implementation of the benchmark CAPM model provides a reasonable COE estimate, which is needed to impute costs and set prices for the Reserve Banks’ payments business.

Over the past decade, commercial banks have devoted many resources to developing internal models to better quantify their financial risks and assign economic capital. These efforts have been recognized and encouraged by bank regulators. Recently, banks have extended these efforts into the field of credit risk modeling. However, an important question for both banks and their regulators is evaluating the accuracy of a model’s forecasts of credit losses, especially given the small number of available forecasts due to their typically long planning horizons. Using a panel data approach, we propose evaluation methods for credit risk models based on cross-sectional simulation. Specifically, models are evaluated not only on their forecasts over time, but also on their forecasts at a given point in time for simulated credit portfolios. Once the forecasts corresponding to these portfolios are generated, they can be evaluated using various statistical methods.

Since bank credit lines are a major source of corporate funding, we examine the determinants of their usage with a comprehensive database of Spanish corporate credit lines. A line's default status is a key factor driving its usage, which increases as firm financial conditions worsen. Firms with prior defaults access their credit lines less, suggesting that bank monitoring influences firms' usage decisions. Line usage has an aging effect that causes it to decrease by roughly 10% per year of its life. Lender characteristics, such as the length of a firm's banking relationships, as well as macroeconomic conditions, affect usage decisions. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

Abstract We use an arbitrage-free term structure model with spanned stochastic volatility to determine the value of the deflation protection option embedded in Treasury inflation-protected securities. The model accurately prices the deflation protection option prior to the financial crisis when its value was near zero; at the peak of the crisis in late 2008 when deflationary concerns spiked sharply; and in the post-crisis period. During 2009, the average value of this option at the 5-year maturity was 41 basis points on a par-yield basis. The option value is shown to be closely linked to overall market uncertainty as measured by the VIX, especially during and after the 2008 financial crisis.