This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...

This paper offers an improvement to the trade-to-trade model for event studies. While the trade-to-trade model of Maynes and Rumsey (1993) addresses the problem of thin trading by eliminating periods in which no trading is recorded, the proposed improvement addresses the influence of zero-value...

This work aims to investigate the (inter)relations of information arrival, news sentiment, volatility and jump dynamics of intraday returns. Two parametric GARCHtype jump models which explicitly incorporate both news arrival and news sentiment variables are proposed, among which one assumes news...

Density forecasts have become quite important in economics and finance. For example, such forecasts play a central role in modern financial risk management techniques like Value at Risk. This paper suggests a regression based density forecast evaluation framework as a simple alternative to other...

This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...

Portfolio sorting is ubiquitous in the empirical finance literature, where it has been widely used to identify pricing anomalies in different asset classes. Despite the popularity of portfolio sorting, little attention has been paid to the statistical properties of the procedure or to the...

The aim of this study is to provide a comprehensive description of the dependence pattern of stock returns by studying a range of quantiles of the conditional return distribution using quantile autoregression. This enables us in particular to study the behavior of extreme quantiles associated...

This paper investigates, both in finite samples and asymptotically, statistical inference on predictive regressions where time series are generated by present value models of asset prices. We show that regression-based tests, including optimal robust tests such as Jasson and Moreira's...

The aim of this study is to provide a comprehensive description of the dependence pattern of stock returns by studying a range of quantiles of the conditional return distribution using quantile autoregression. This enables us in particular to study the behavior of extreme quantiles associated...

We investigate the risk-return trade-off on the US and European stock markets. We investigate the non-linear risk-return trade-off with a special eye to the tails of the stock returns using quantile regressions. We first consider the US stock market portfolio. We find that the risk-return...