We examine how the use of high-frequency data impacts the portfolio optimization decision. Prior research has documented that an estimate of realized volatility is more precise when based upon intraday returns rather than daily returns. Using the framework of a professional investment manager...

We estimate the EU Commission loss preferences for major economic forecasts of 12 Member States. Based on a recently proposed method by Elliott, Komunjer and Timmermann (2005) the paper provides evidence of asymmetries in the underlying forecast loss preference of the Commission that tend to...

Bayesian priors are often used to restrain the otherwise highly over-parametrized vector autoregressive (VAR) models. The currently available Bayesian VAR methodology does not allow the user to specify prior beliefs about the unconditional mean, or steady state, of the system. This is...

We study the relation between individual preferences for job amenities (e.g., type of work, job security) and compensating wage differentials in cross-section. To this end, we estimate a partial equilibrium job search model on panel data from eight European countries. There are five non-wage job...

This paper presents Monte Carlo simulations for the Johansen cointegration test which indicate that the critical values applied in a number of econometrics software packages are inappropriate. This is due to confusion in the specification of the deterministic terms included in the vector error...

How to measure and model volatility is an important issue in finance. Recent research uses high-frequency intraday data to construct ex post measures of daily volatility. This paper uses a Bayesian model-averaging approach to forecast realized volatility. Candidate models include autoregressive...