Banking and sovereign risk in the euro area

We study the determinants of sovereign bond spreads in the euro area since the introduction of the euro. We show that an aggregate risk factor is a main driver of spreads. This factor also plays an important indirect role for risk spreads through its interaction with the size and structure of national banking sectors. When aggregate risk increases, countries with large banking sectors and low equity ratios in the banking sector experience greater widening in yield spreads, suggesting that financial markets perceive a larger risk that governments will have to rescue banks, increasing public debt and therefore sovereign risk. Moreover, government debt levels and forecasts of future fiscal deficits are also significant determinants of sovereign spreads. --Sovereign bond markets,banking,liquidity,EMU

Charge carrier interaction with a purely electronic collective mode: Plasmarons and the infrared response of elemental bismuth

We present a detailed optical study of single crystal bismuth using infrared reflectivity and ellipsometry. Colossal changes in the plasmon frequency are observed as a function of temperature due to charge transfer between hole and electron Fermi pockets. In the optical conductivity, an anomalous temperature dependent mid-infrared absorption feature is observed. An extended Drude model analysis reveals that it can be connected to a sharp upturn in the scattering rate, the frequency of which exactly tracks the temperature dependent plasmon frequency. We interpret this absorption and increased scattering as the first direct optical evidence for a charge carrier interaction with a collective mode of purely electronic origin; here electron-plasmon scattering. The observation of a \emph{plasmaron} as such is made possible only by the unique coincidence of various energy scales and exceptional properties of semi-metal bismuth.Comment: 4 pages, 4 figure

On the exciton binding energy in a quantum well

We consider a model describing the one-dimensional confinement of an exciton in a symmetrical, rectangular quantum-well structure and derive upper and lower bounds for the binding energy $E_b$ of the exciton. Based on these bounds, we study the dependence of $E_b$ on the width of the confining potential with a higher accuracy than previous reports. For an infinitely deep potential the binding energy varies as expected from $1 Ry$ at large widths to $4 Ry$ at small widths. For a finite potential, but without consideration of a mass mismatch or a dielectric mismatch, we substantiate earlier results that the binding energy approaches the value $1 Ry$ for both small and large widths, having a characteristic peak for some intermediate size of the slab. Taking the mismatch into account, this result will in general no longer be true. For the specific case of a $Ga_{1-x}Al_{x}As/GaAs/Ga_{1-x}Al_{x}As$ quantum-well structure, however, and in contrast to previous findings, the peak structure is shown to survive.Comment: 32 pages, ReVTeX, including 9 figure

Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We pro- pose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis aects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more eficiently than other models, across the series considered, which should be useful for financial practitioners.Value-at-Risk; CAViaR model; Skewed-Laplace distribution; intra-day range; backtesting, Markov chain Monte Carlo.

Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We propose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis affects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more efficiently than other models, across the series considered, which should be useful for financial practitioners.Value-at-Risk; CAViaR model; Skewed-Laplace distribution; intra-day range; backtesting; Markov chain Monte Carlo