Returns Volatility and Other Comprehensive Income Components

I examine whether other comprehensive income (OCI) component volatilities are associated with returns volatility for banks. I predict that OCI component volatilities have associations with returns volatility that vary in strength, and that inferences regarding the usefulness of OCI can be improved by analyzing associations between OCI component volatilities and returns volatility. I use returns volatility as the measure of total risk for a bank, consistent with the FASB’s conceptual framework, and disaggregate OCI into its four primary components: available-forsale (AFS) securities adjustments; cash-flow hedge adjustments; pension-related adjustments; and foreign currency translation adjustments. Using hand-collected data, I further disaggregate AFS securities adjustments and cash-flow hedge adjustments into their unrealized and recycled subcomponents. I find that volatilities of unrealized (recycled) gains and losses on available-forsale securities and cash-flow hedges are negatively (positively) associated with returns volatility. I also find that associations between volatilities of these unrealized (recycled) gains and losses and returns volatility are more negative (stronger) when OCI is presented in a performance statement. The results indicate that volatilities of unrealized gains and losses, typically deemed beyond managers’ control, are negatively associated with risk, while volatilities of recycled gains and losses, over which managers have relatively more control, are positively associated with risk. *Correspondence information: 100 Fuqua Drive, Box 90120, Durham, NC 27708-0120, USA, tel: (919) 660-7957. I thank Ervin Black, Michael Bradbury, Shane Dikolli, Scott Dyreng, Peter Easton, Frank Ecker, Jennifer Francis, Amanda Gonzales, Ryan Kerr, Christian Lundblad, Per Olsson, Katherine Schipper, Thomas Steffen, Mohan Venkatachalam, Norman Wong, and workshop participants at Duke University and the AFAANZ Doctoral Symposium for helpful conversations and comments. I thank the Deloitte Foundation for financial support and the Institute for Digital Research and Education (IDRE) at UCLA for providing helpful programming information. All errors are my own.