Robust Risk Measures in Real Time Settings

• Antragsteller: Professor Dr. Winfried Franz Xaver Pohlmeier
• Fachliche Zuordnung: Statistik und Ökonometrie
• Förderung: Förderung von 2010 bis 2014
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 178371044

The recent financial crisis has cast serious doubts on the accuracy and appropriateness of measures of onesided risks proposed in academia and used by financial institutions in practice. Popular measures like the Value-at-Risk and the Expected Shortfall have failed in market situations when they were needed most urgently. The research project proposed contributes to the research on the model risk of risk models. It aims at identifying the sources of these failures and at enhancing the robustness of risk measurement in real time settings. Two strategies of generalizing standard risk measures will be pursued by (i) developing real time econometric approaches for different dimensions (model choice, market setting, sampling window, etc.) to improve prediction accuracy and robustness w.r.t. changing market conditions, and by (ii) developing real time multivariate frameworks to account for multifaceted nature of risk interdependencies and their driving forces such as market liquidity. The superiority of the new approaches will be worked out theoretically as well as in terms of out-of-sample prediction performance for a wide range of securities, markets and market conditions. Evaluations of the empirical performance will be based on standard backtesting procedures, statistical goodness of fit criteria as well as economic or financial criteria.

• DFG-Verfahren: Sachbeihilfen