The purpose of this paper is to investigate whether a dynamic Value at Risk model and high frequency realized volatility models can improve the accuracy of 1-day ahead VaR forecasting beyond the performance of frequently used models. As such, this paper constructs 60 conditional volatility...

This paper provides empirical results supporting the theoretical ones by the first author on backtesting long-horizon distributional forecasts. The problem is quite general but for us it is motivated by the regulatory requirement of backtesting evolution models used in the measurement of...

To their credit, empirical legal scholars try to live up to the highest methodological standards from the social sciences. But these standards do not always match the legal research question. This paper focuses on normative legal argument based on empirical evidence. Whether there is a normative...

Option pricing and allocation tools in portfolio construction should be prospective - based on assumptions about how prices will change in the future. Most capital market assumptions used in portfolio construction are based on retrospective analysis, boiling down to simple calculations of...

We provide evidence suggesting that the assumption on the probability distribution for return innovations is more influential for Value at Risk (VaR) performance than the conditional volatility specification. We also show that some recently proposed asymmetric probability distributions and the...

Density forecasts have become quite important in economics and finance. For example, such forecasts play a central role in modern financial risk management techniques like Value at Risk. This paper suggests a regression based density forecast evaluation framework as a simple alternative to other...