Value-at-risk (VaR) and conditional value-at-risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of a Neyman-Pearson type binary solution. We add a constraint on expected return to investigate...

This article aims to investigate the similarity of public and private real estate returns and risks over the relatively long horizon using data for the U.S and the U.K. The results show evidence of a one-to-one relationship between publicly traded REIT performance and privately traded direct...

Average skewness, which is defined as the average of monthly skewness values across firms, performs well at predicting future market returns. This result still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. We also find that average...

Financial analysts typically estimate volatilities and correlations from monthly or higher frequency returns when determining the optimal composition of a portfolio. Although it is widely acknowledged that these measures are not necessarily stationary across samples, most analysts assume...

Bei einer wohnwirtschaftlichen Portfoliobewertung ist eine qualifizierte Wertermittlung auf Einzelobjektebene insbesondere in einer frühen Transaktionsphase aus Zeit- und Kostengründen nicht machbar. Stefan Haas entwickelt eine Bewertungsmethodik, welche standardisiert einen...

This study deals with the dynamic hedging of single-tranche collateralized debt obligations (STCDOs). As a first step, we specify a top-down affine factor model in which a catastrophic risk component is incorporated in order to capture the dynamics of super-senior tranches. Next, we derive the...

We study the pricing and hedging of derivative securities with uncertainty about the volatility of the underlying asset. Rather than taking all models from a prespecified class equally seriously, we penalise less plausible ones based on their "distance" to a reference local volatility model. In...