Like security prices, retail deposit interest rates cluster around integers and “even” fractions. However, explanations for security price clustering are incompatible with deposit rate clustering. A theory based on the limited recall of retail depositors is proposed. It predicts that banks tend to set rates at integers and that rates are “sticky” at these levels. The propensity for integer rates increases with the level of wholesale interest rates and deposit market concentration. When banks set noninteger rates, rates are more likely to be just above, rather than just below, integers. The paper finds substantial empirical support for the theory's implications.

Chen, Sean Chen, and Harry Sharma. We also benefited from discussions with our colleagues Ivan Brick, Oded Palmon, Emilio Venezian, and John Wald. We are particularly indebted to the anonymous referee and the editor, Paul Malatesta, for their valuable suggestions that greatly improve the paper. All errors are our own.

ABSTRACT Like security prices, retail deposit interest rates cluster around integers and “even” fractions. However, explanations for security price clustering are incompatible with deposit rate clustering. A theory based on the limited recall of retail depositors is proposed. It predicts that banks tend to set rates at integers and that rates are “sticky” at these levels. The propensity for integer rates increases with the level of wholesale interest rates and deposit market concentration. When banks set noninteger rates, rates are more likely to be just above, rather than just below, integers. The paper finds substantial empirical support for the theory's implications.

This paper presents a flexible, lattice-based structural credit risk model that uses equity market information and a detailed depiction of a financial institution’s liability structure to analyze default risk. The model is applied to examine the term structure of default probabilities for Lehman Brothers prior to its demise. The results indicate, as early as March, that the firm would likely lose access to external capital within two years. The model can be used as both a diagnostic tool for the early detection of financial distress and a prescriptive tool for addressing the sources of risk in large, complex financial institutions.