I analyze efficient estimation of a cointegrating vector when the regressand is observed at a lower frequency than the regressors. Previous authors have examined the effects of specific temporal aggregation or sampling schemes, finding conventionally efficient techniques to be efficient only...

Logging is an important yet tough decision for OSS developers. Machine-learning models are useful in improving several steps of OSS development, including logging. Several recent studies propose machine-learning models to predict logged code construct. The prediction performances of these models...

In this study, we evaluate the quantile forecasts of the daily equity returns on three of the most liquid stocks traded on the Prague Stock Exchange. We follow the recent findings that consider the potential value of intraday information for volatility forecasting and, instead of proxying...