The performance effects of board heterogeneity: What works for EU banks?

We examine the impact of board heterogeneity on the performance of EU listed banks in the wake of the global financial crisis. In a comprehensive set-up, we consider standard board features (type, tenure, size, and age of board members) as well as board diversity features (gender diversity, employee representation, internationalisation, and age diversity). We propose a diversity index, which summarises the different dimensions of diversity and control for unobserved heterogeneity and reverse causality. Our analysis uncovers a complex relationship between board heterogeneity and bank performance, which is influenced by market conditions and by national culture. Overall board diversity does not seem to affect bank performance, but it does decrease performance variability during the Eurozone crisis and in countries culturally more open to diversity. Different board and diversity features have a positive impact on bank performance (size, tenure, and employee representation); the relationship is non-linear, with the effect of diversity being more relevant when there is a significant proportion of minority representatives. While substantial board internationalisation has a negative impact on bank performance, the presence of foreign directors appears to be less detrimental during the Eurozone crisis and in countries that are more welcoming towards diversity

On forecasting daily stock volatility: the role of intraday information and market conditions

Several recent studies advocate the use of nonparametric estimators of daily price vari- ability that exploit intraday information. This paper compares four such estimators, realised volatility, realised range, realised power variation and realised bipower variation, by examining their in-sample distributional properties and out-of-sample forecast ranking when the object of interest is the conventional conditional variance. The analysis is based on a 7-year sample of transaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH framework and relies on several loss functions. The realized range fares relatively well in the in-sample .t analysis, for instance, regarding the extent to which it brings normality in returns. However, overall the realised power variation provides the most accurate 1-day-ahead forecasts. Fore- cast combination of all four intraday measures produces the smallest forecast errors in about half of the sampled stocks. A market conditions analysis reveals that the additional use of intraday data on day t .. 1 to forecast volatility on day t is most advantageous when day t is a low volume or an up-market day. The results have implications for value-at-risk analysis.

On Sovereign Credit Migration: A Study of Alternative Estimators and Rating Dynamics

This paper investigates the finite-sample behaviour of sovereign credit migration estimators and analyzes the properties of the rating process. Through bootstrap simulations, we compare a discrete multinomial estimator and two continuous hazard rate methods which differ in that one neglects time-heterogeneity in the rating process whereas the other accounts for it. The study is based on Moody's ratings 1981-2004 for 72 industrialized and emerging economies. Hazard rate estimators yield more accurate default probabilities. The time homogeneity assumption leads to underestimating the default probability and greater migration risk is inferred upon relaxing it. There is evidence of duration dependence and downgrade momentum effects in the rating process. These findings have important implications for economic and regulatory capital allocation and for the pricing of credit sensitive instruments.Sovereign credit risk; Rating transitions, Markov chain, Time heterogeneity, Rating momentum, Duration dependence.

The role of correlation dynamics in sector allocation

This paper assesses the economic value of modeling conditional correlations for mean–variance portfolio optimization. Using sector returns in three major markets we show that the predictability of models describing empirical regularities in correlations such as time-variation, asymmetry and structural breaks leads to significant performance gains over the static covariance strategy. Investors would be willing to pay a fee of up to 983 basis points to switch from the static to the dynamic correlation portfolio and about 100 basis points more for capturing asymmetries and shifts in correlations. The gains are robust to the crisis, transaction costs and are most pronounced for monthly rebalancing

ECB Policy and Eurozone Fragility: Was De Grauwe Right? CEPS Working Document No. 397, June 2014

Paul De Grauwe’s fragility hypothesis states that member countries of a monetary union such as the eurozone are highly vulnerable to a self-fulfilling mechanism by which the efforts of investors to avoid losses from default can end up triggering the very default they fear. The authors test this hypothesis by applying an eclectic methodology to a time window around Mario Draghi’s “whatever it takes” (to keep the eurozone on firm footing) pledge on 26 July 2012. This pledge was soon followed by the announcement of the Outright Monetary Transactions (OMT) programme (the prospective and conditional purchase by the European Central Bank of sovereign bonds of eurozone countries having difficulty issuing debt). The principal components of eurozone credit default swap spreads validate this choice of time frame. An event study reveals significant pre announcement contagion emanating from Spain to Italy, Belgium, France and Austria. Furthermore, time-series regression confirms frequent clusters of large shocks affecting the credit default swap spreads of the four eurozone countries but solely during the pre-announcement period. The findings of this report support the fragility hypothesis for the eurozone and endorse the Outright Monetary Transactions programme

Return and Volatility Spillover among Banks and Insurers: Evidence from Pre-Crisis and Crisis Periods

We investigate the return and volatility interdependencies among the US, the UK, the EU, and Japanese banks and insurers during the period of 2003 to 2009. We find strong return and volatility transmissions within and across banking and insurance industries, strengthened contagious spillover effects during the crisis of 2007 to 2009, and a leading role played by the US financial institutions as information providers in global markets. Furthermore, we find that firm characteristics such as size and leverage drive the interdependencies among major banking firms. Our findings have important implications for effective hedging and diversification strategies, asset pricing and risk management, and the formulation of regulatory and monetary policies

Dependence in Credit Default Swap and Equity Markets: Dynamic Copula with Markov Switching

Theoretical credit risk models à la Merton (1974) predict a non-linear negative link between the default likelihood and asset value of a firm. This motivates us to propose a flexible empirical Markov-switching bivariate copula that allows for distinct time-varying dependence between credit default swap (CDS) spreads and equity prices in “crisis” and “tranquil” periods. The model identifies high-dependence regimes that coincide with the recent credit crunch and the European sovereign debt crises, and is supported by in-sample goodness-of-fit criteria relative to nested copula models that impose within-regime constant dependence or no regime-switching. Value-at-Risk forecasts that aim to set day-ahead trading limits for the hedging of CDS-equity portfolios reveal the economic relevance of the model from the viewpoints of both regulatory and asymmetric piecewise linear loss functions

The anatomy of sovereign risk contagion

The channels for the cross-border propagation of sovereign risk in the international sovereign debt market are analysed. Identifying sovereign credit events as extraordinary jumps in CDS spreads, we distinguish between the immediate effects of such events and their longer term spillover effects. To analyse “fast and furious” contagion, we use daily CDS data to conduct event studies around a total of 89 identified credit events in a global country sample. To analyse “slow-burn” spillover effects, we apply a multifactor risk model, distinguishing between global and regional risk factors. We find that “fast and furious” contagion has been primarily a regional phenomenon, whilst “slow-burn” spillover effects can often be global in scope, especially those of the recent European debt crisis. The global risk factors are found to be driven by investor risk appetites and debt levels, whilst the regional factors depend on economic fundamentals of countries within a region

ECB policy and Eurozone fragility: Was De Grauwe right?

Paul De Grauwe's Eurozone fragility hypothesis states that sovereign debt markets in a monetary union without a lender-of-last-resort are vulnerable to self-fulfilling dynamics fuelled by pessimistic investor sentiment that can trigger default. We test this contention by applying an eclectic methodology to a two-year window around Mario Draghi's “whatever-it-takes” pledge that can be understood as the implicit announcement of the Outright Monetary Transactions (OMT) program. A principal components analysis reveals that the perceived commonality in default risk among peripheral and core Eurozone sovereigns increased after the announcement. An event study reveals significant pre-announcement news transmission from Spain to Italy, France, Belgium and Austria that clearly dissipates post-announcement. Country-specific regressions of CDS spreads on systematic risk factors reveal frequent days of large adverse shocks affecting simultaneously those five Eurozone countries, but only during the pre-announcement period. Altogether these findings support the fragility hypothesis and endorse the OMT program

On forecasting daily stock volatility: The role of intraday information and market conditions

Several recent studies advocate the use of nonparametric estimators of daily price variability that exploit intraday information. This paper compares four such estimators, realised volatility, realised range, realised power variation and realised bipower variation, by examining their in-sample distributional properties and out-of-sample forecast ranking when the object of interest is the conventional conditional variance. The analysis is based on a 7-year sample of transaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH framework and relies on several loss functions. The realized range fares relatively well in the in-sample fit analysis, for instance, regarding the extent to which it brings normality in returns. However, overall the realised power variation provides the most accurate 1-day-ahead forecasts. Forecast combination of all four intraday measures produces the smallest forecast errors in about half of the sampled stocks. A market conditions analysis reveals that the additional use of intraday data on day t-1 to forecast volatility on day t is most advantageous when day t is a low volume or an up-market day. These results have implications for option pricing, asset allocation and value-at-risk