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...

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...

Using GARCH models for density prediction of stock index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is found between qualities of whole density forecasts, whereas the Bayesian approach exhibits significantly better left-tail forecast...