This paper investigates the impact of the opening of US stock markets on the German stock market. Quantiles of the S&P 500 return distribution are used to distinguish good, bad, and no news days. We find that the German market reacts to the US news announcements which typically precede the...

We use quantile regressions to demonstrate that volatility persistence and the asymmetric "leverage" effect are high volatility phenomena. More specifically, we find that (i) low volatility is not persistent, but high volatility all the more, even featuring properties of explosive processes;...

We propose to estimate the variance of a time series of financial returns through a quantile autoregressive model (QAR) and demonstrate that the return QAR model contains all information that is commonly captured in two separate equations for the mean and variance of a GARCH-type model. In...

There is a well documented asymmetric return - volatility effect of equity returns, that is, negative shocks increase volatility by more than positive shocks. This paper analyzes the return - volatility relationship of commodity price changes and finds an inverted asymmetric effect with a...

We estimate quantile autoregression (QAR) models to analyze variations in the autoregressive coefficients of 55 international stock index returns and demonstrate that it is important to allow the autoregressive parameters to vary with quantiles. The empirical results identify distinctively...

This paper studies the dynamics of stock market volatility and retail investor attention measured by internet search queries. We find a strong co-movement of stock market indices’ realized volatility and the search queries for their names. Furthermore, Granger causality is bi-directional: high...

This paper studies the dynamics of stock market volatility and retail investor attention measured by internet search queries. We find a strong co-movement of stock market indices' realized volatility and the search queries for their names. Furthermore, Granger causality is bi-directional: high...