Implications of alternative operational risk modeling techniques

Quantification of operational risk has received increased attention with the inclusion of an explicit capital charge for operational risk under the new Basle proposal. The proposal provides significant flexibility for banks to use internal models to estimate their operational risk, and the associated capital needed for unexpected losses. Most banks have used variants of value at risk models that estimate frequency, severity, and loss distributions. This paper examines the empirical regularities in operational loss data. Using loss data from six large internationally active banking institutions, we find that loss data by event types are quite similar across institutions. Furthermore, our results are consistent with economic capital numbers disclosed by some large banks, and also with the results of studies modeling losses using publicly available “external” loss data.Bank capital ; Risk management ; Basel capital accord

The potential impact of explicit Basel II operational risk capital charges on the competitive environment of processing banks in the United States

Basel II replaces Basel I’s implicit capital charge on operational risk with an explicit charge. Certain U.S. banks concentrated in processing-related business lines – which have significant operational risk – could thus face an increase in overall minimum regulatory capital requirements. Some have argued that, as a result, these so-called “processing banks” would be disadvantaged vis-à-vis competitors not subject to regulatory capital requirements for operational risk. This paper evaluates these concerns.Bank capital ; Risk management ; Basel capital accord

Does feedback trading drive returns of cross-listed shares?

This paper examines the role of cross-listing in stock return dynamics with particular reference to feedback trading based on a sample of five most frequently traded cross-listed shares. We find that a long-run equilibrium relationship among the cross-listed share prices exists, but find no evidence of long-run co-movements among different shares traded in the same exchange. Furthermore, the VAR Granger causality tests indicate bi-directional feedback relations among the returns of cross-listed shares, while there is no consistent causality among different stocks within the markets. We also find that the cross-listed shares demonstrate strong volatility spillovers, which is driven by the covariance structure that are formed by variance and correlation terms. In addition, we report liquidity spillover effects and spillovers running from liquidity to volatility for some firms but no evidence that spillover effects run from volatility to liquidity