Various GARCH models are applied to daily returns of more than 1200 constituents of major stock indices worldwide. The value-at-risk forecast performance is investigated for different markets and industries, considering the test for correct conditional coverage using the false discovery rate...

We investigate the time-variation of the cross-sectional distribution of asymmetric GARCH model parameters over the S&P 500 constituents for the period 2000-2012. We find the following results. First, the unconditional variances in the GARCH model obviously show major time-variation, with a high...

A novel simulation-based methodology is proposed to test the validity of a set of marginal time series models, where the dependence structure between the time series is taken ‘directly’ from the observed data. The procedure is useful when one wants to summarize the test results for several...

We propose to compute the implied expected returns from several candidate mean-variance efficient portfolios, exploiting the fundamental relation between the expected returns, covariance matrix and the corresponding set of mean-variance efficient portfolios. Over the 1987-2012 period and for the...

An essential component in the analysis of (hedge) fund returns is to measure its performance with respect to the group of peer funds. Through the analysis of risk-adjusted return percentiles an answer is given to the question how many funds are out-performed by the focal fund. In case all funds...

The Entropy Pooling approach in Meucci (2008) is a versatile, general framework to process market views in portfolio construction and generalized stress-tests in risk management. Here we present an efficient algorithm to implement Entropy Pooling with fully general views in multivariate normal...

This discussion paper resulted in an article in <I>Economics Letters</I> (2012). Vol. 116(3), 322-325.<p> Using well-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is...</p></i>

This note presents the R package bayesGARCH (Ardia, 2007) which provides functions for the Bayesian estimation of the parsimonious and effective GARCH(1,1) model with Student-<I>t</I> innovations. The estimation procedure is fully automatic and thus avoids the tedious task of tuning a MCMC sampling...</i>

This discussion paper resulted in a publication in the <I>Journal of Statistical Software<I> (2009). Vol. 29(3), 1-32.<P> This paper presents the R package AdMit which provides functions to approximate and sample from a certain target distribution given only a kernel of the target density function. The...</p></i></i>

We analyze the impact of the estimation frequency–updating parameter estimates on a daily, weekly, monthly or quarterly basis–for commonly used GARCH models in a large-scale study, using more than twelve years (2000–2012) of daily returns for constituents of the S&P 500 index. We assess...