In this paper we address the issue of forecasting Value–at–Risk (VaR) using different
volatility measures: realized volatility, bipower realized volatility, two-scales realized …

This paper deals with bitcoin volatility forecasting, through a framework based on Long-
Short Term Memory, multiplicative error and residual analysis. This framework is based on …

This paper analyzes exchange rate turmoil with a Markov switching GARCH model. We
distinguish between two different regimes in both the conditional mean and the conditional …

Margin regulation raises two policy concerns. First, an alignment of margins to volatility can
amplify procyclicality, leading to a build-up of excess leverage in good times and a forced …

We analyze the content of the Organization of the Petroleum Exporting Countries (OPEC)
communications and whether it provides information to the crude oil market. To this end, we …

This paper exploits the fact that implied volatilities calculated from identical call and put
options have often been empirically found to differ, although they should be equal in theory …

We study the performance of recently developed linear regression models for interval data
when it comes to forecasting the uncertainty surrounding future stock returns. These interval …

We propose a novel approach to the modelling and forecasting of high-frequency trading
volumes. The new model extends the component multiplicative error model of Brownlees et …

Systematic traders employ algorithmic strategies to manage their investments. As a result of
the deterministic nature of such strategies, it is possible to determine their exact responses …

We investigate volatility estimators built by summing up quadratic functions of log-prices'
intradaily increments, highs, and lows, which we show to be consistent for integrated …