An empirical investigation of operational risk in the United States financial sectors

This research studies the market value impact of operational risk events on both announcing and non-announcing firms in the U.S. Financial sectors and provides models to quantify operational risk. I begin by conducting an event study analysis of the impact of operational loss events on the market values of banks and insurance companies, using the OpVar database. I focus on financial institutions because of the increased market and regulatory scrutiny of operational losses in these industries. The results reveal a strong, statistically significant negative stock price reaction to announcements of operational loss events. Moreover, the market value loss significantly exceeds the amount of the operational loss reported, implying that such losses convey adverse implications about future cash flows. Next, I conduct an event study analysis of the market value impact of operational loss events on non-announcing firms in the U.S. banking and insurance industries. The two principal hypotheses investigated in the study are the contagion hypothesis, i.e., that operational risk events have a negative effect on stock prices of non-announcing firms, and the competition hypothesis, i.e., that operational risk events lead to wealth transfers from announcing to non-announcing firms. The results indicate that operational risk events cause strong intra and inter-sector contagion, i.e., the stock prices of non-announcing firms respond negatively to operational loss announcements. Regression analysis reveals that the negative effect represents information-based rather than pure contagion. Finally, I provide a framework that allows the use of both external data and firm specific information to quantify operational risk so that firm specific capital calculation can be made. I utilize a model from Bayesian credibility theory to estimate the frequency distribution and introduce covariates in the estimation of severity distribution. A simulation procedure is presented to construct the entire aggregate distribution of operational risk exposure