We examine the significance of twenty-one potential drivers of bitcoin returns for the period
2010–2017 (2533 daily observations). Within a LASSO framework, we examine the effects of …

We review the literature and examine the effects of shocks on bitcoin returns. We assess the
effects of factors such as stock market returns, exchange rates, gold and oil returns, FED's …

Penalized quantile regressions are proposed for the combination of Value-at-Risk forecasts.
The primary reason for regularization of the quantile regression estimator with the elastic …

The asset allocation decision often relies upon correlation estimates arising from short-run
data. Short-run correlation estimates may, however, be distorted by frictions. In this paper …

This study proposes a modified VAR-deGARCH model, denoted by M-VAR-deGARCH, for
modeling asynchronous multivariate financial time series with GARCH effects and …

In this study, a network autoregressive model with GARCH effects, denoted by NAR-
GARCH, is proposed to depict the return dynamics of stock market indices. A GARCH filter is …

This study investigates whether the inclusion of news information can help predict tail risk in
the Chinese market. To quantify information from news, we develop an information volume …

A vector autoregression (VAR) model is powerful for analyzing economic data as it can be
used to simultaneously handle multiple time series from different sources. However, in the …

This study considers prediction intervals for time series and applies the results to portfolio
selection. The dynamics of the high and low underlying returns are depicted by time series …

Выявление причинности между значениями показателей бирж, распределенных в
разных временных зонах, является достаточно типичной задачей финансовой …