In density forecasts, respondents are asked to assign probabilities to a response scale with pre-specified ranges of inflation. In two large-scale experiments, one conducted in the US and one in Germany, we show how the specifics of the response scale determine the responses: Shifting,...

The stochastic error distance (SED) introduced by Diebold & Shin (2017) ranks forecast models by divergence between distributions of the errors of the actual and prefect forecast models. The basic SED is defined by the variation distance and provides a representation of the mean absolute error,...

This paper studies a basket of risk statistics that are widely used to measure investment performance. Those risk statistics were used to rank the performance of the assets. The dependent information was removed from the set of risk measures that were used in the test. The risk statistics were...

Standard realized volatility (RV) measures estimate the latent volatility of an asset price using high frequency data with no reference to how or where the estimate will subsequently be used. This paper presents methods for “tailoring” the estimate of volatility to the application in which...

Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data,...