Bank holding companies (BHCs) can be complex organizations, conducting multiple lines of business through many distinct legal entities and across a range of geographies. While such complexity raises the costs of bank resolution when organizations fail, the effect of complexity on BHCs’ broader risk profiles is less well understood. Business, geographic, and organizational complexity can engender explicit tradeoffs between the agency problems that increase risk and the diversification, liquidity management, and synergy improvements that reduce risk. The balance of outcomes may depend on the strength of bank governance. We test these conjectures using data on large U.S. BHCs for the 1996–2018 period. Business, geographic, and organizational complexity provide diversification benefits and some reduced idiosyncratic and liquidity risk exposure. All forms of complexity tend to increase BHC systemic risks. A regulatory tightening focused on complexity reduced organizational complexity, while also curtailing systemic risk but increasing liquidity risk.

We use Markov chain methods to develop a flexible class of discrete stochastic autoregressive volatility (DSARV) models. Our approach to formulating the models is straightforward, and readily accommodates features such as volatility asymmetry and time-varying volatility persistence. Moreover, it produces models with a low-dimensional state space, which greatly enhances computational tractability. We illustrate the proposed methodology for both individual stock and stock index returns, and show that simple first- and second-order DSARV models outperform generalized autoregressive conditional heteroscedasticity and Markov-switching multifractal models in forecasting volatility.

This paper examines the trading behavior of two groups of liquidity providers (specialists and competing market makers) using a six-year panel of NYSE data. Trades of each group are negatively correlated with contemporaneous price changes. To test for return predictability, we sort stocks into quintiles based on each group’s past trades and then form long-short portfolios. Stocks most heavily bought have significantly higher returns than stocks most heavily sold over the two weeks following a sort. Cross-sectional analysis shows smaller, more volatile, less actively traded, and less liquid stocks more often appear in the extreme quintiles. Time series analysis shows the long-short portfolio returns are positively correlated with a market-wide measure of liquidity. A double sort using past trades of specialists and competing market makers produces a long-short portfolio that earns 88 basis points per week (act as complements). Finally, we identify a “chain” of liquidity provision. Designated market makers (NYSE specialists) initially trade against order flows and prices changes. Specialists later mean revert their inventories by trading with competing market makers who appear to spread trades over a number of days. Alternatively, specialists may trade with competing market makers who arrive to market with delay.

We estimate a macro-finance yield curve model for both the nominal and real forward curve for the UK from 1993 to 2008. Our model is able to accommodate a number of key macroeconomic variables and allows us to estimate the instantaneous response of the yield curve and so gauge the impact of Quantitative Easing on forward rates. We find that 10year nominal interest rates on average are lower by 46 basis points which can largely be explained by three main channels: portfolio balance; liquidity premium and signalling but there is no sizeable impact on real interest rates.

We investigate the relationships between the severity of operational loss events reported in the banking sector and various regulatory, legal, geographical, and economic indicators. Based on a data sample of over 57,000 losses incurred in more than 130 countries reported by the Operational Riskdata eXchange (ORX) consortium, we identify the most relevant exposure indicators for losses in four Basel II event categories: Internal Fraud; External Fraud; Employment Practices and Workplace Safety; and Clients, Products and Business Practices. We find evidence of significant correlations between Internal Fraud and constraints on executive power and the prevalence of insider trading. Clients, Products and Business Practices losses are significantly related to securities and shareholder protection laws, restrictions on banking activity, supervisory power, and the prevalence of insider trading. Other event types are sensitive to per-capita GDP and a governance index.

We investigate the interdependence of the default risk of several Eurozone countries (France, Germany, Italy, Ireland, the Netherlands, Portugal, and Spain) and their domestic banks during the period between June 2007 and May 2010, using daily credit default swaps (CDS). Bank bailout programs changed the composition of both banks’ and sovereign balance sheets and, moreover, affected the linkage between the default risk of governments and their local banks. Our main findings suggest that in the period before bank bailouts the contagion disperses from bank credit spreads into the sovereign CDS market. After bailouts, a financial sector shock affects sovereign CDS spreads more strongly in the short run. However, the impact becomes insignificant in the long term. Furthermore, government CDS spreads become an important determinant of banks’ CDS series. The interdependence of government and bank credit risk is heterogeneous across countries, but homogeneous within the same country.

We develop a model that analyzes competition between a non-intermediated market (such as an electronic communications network) and an intermediated market (such as via the market specialist’s structure within the NYSE) when both markets are allowed to trade the same securities. Specialists are viewed as providers of a “volatility dampening” service, a mechanism for reducing round-trip trading costs, as well as an “order execution risk management” service. The economic value of these three specialist services is determined by five key factors (the difference in spreads between the two financial market types, investors’ holding periods, the specialist’s quoted spread in relation to the asset’s price, the relative probability of executing an order in the intermediated market, and the short-term risk-free rate).

In this paper, we show (i) that the risk-return characteristics of our sample of 17 developed stock markets of the world have converged significantly toward each other during our study period 1974–2007, and (ii) that this international convergence in risk-return characteristics is driven mainly by the declining ‘country effect’, rather than the rising ‘industry effect’, suggesting that the convergence is associated with international market integration. Specifically, we first compute the risk-return distance among international stock markets based on the Euclidean distance and find that the distance thus computed has been decreasing significantly over time, implying a mean–variance convergence. In particular, the average risk-return distance has decreased by about 50% over our sample period. We also document that the risk-return characteristics of our sample of 14 emerging markets have been converging rapidly toward those of developed markets in recent years. This development notwithstanding, emerging markets still remain as a distinct asset class. Lastly, we show that the convergence in risk-return characteristics has exerted a negative impact on the efficiency of international investment during our sample period.

This paper explores the relationship between information uncertainty and auditor reputation revealed by the failure of Arthur Andersen (AA). AA’s reputation deteriorated considerably when it announced on January 10, 2002, that it had shredded documents related to its audit of Enron. AA’s demise was sealed on March 14, 2002, with its indictment for obstruction of justice. We find that on these dates the clients of AA and other Big Five auditors that are characterized by higher information uncertainty experience relatively larger share price declines compared to clients with lower information uncertainty. The findings suggest that the market relies more heavily on auditor reputation for higher information uncertainty firms, which implies that the value of an audit is greater when a firm is harder to value. Our results highlight the importance of information uncertainty in financial markets: where there is a shock to auditor reputation, firms with greater information uncertainty suffer the largest losses.

For market discipline to be effective, market factors such as changes in firm equity and debt values and returns, must influence firm decision making. In banking, this can occur directly via bank management or indirectly though supervisory examinations and oversight influencing bank management. In this study, we investigate whether equity market variables can provide timely information and add value to accounting models that predict changes in bank holding company (BOPEC) risk ratings over the 1988–2000 period. Using a variety of equity market indicators, the findings suggest that one-quarter lagged market data adds forecast value to lagged financial statement data and prior supervisory information in the logistic regressions. Furthermore, using extensive out-of-sample testing for the years 2001–2003, we find: (1) that multiple models estimated over different phases of the business and banking cycles are superior to a single model for forecasting BOPEC rating changes; (2) that equity data adds economically significant power in forecasting BOPEC rating upgrades and performs well for identifying no changes; (3) that for downgrades, the accounting model forecasts the best; (4) that modeling the three possible risk ratings categories simultaneously (downgrade, no change and upgrade) minimizes both Type I and Type II classification errors; and (5) that using multiple models to forecast risk ratings enhances the overall percentage of correct classifications.