The prediction of volatility is of primary importance for business applications in risk management, asset allocation and pricing of derivative instruments. This paper proposes a novel measurement model which takes into consideration the possibly time-varying interaction of realized volatility...

This paper studies the behaviour of Bitcoin returns at different sample frequencies. We consider high frequency returns starting from tick-by-tick price changes traded at the Bitstamp and Coinbase exchanges. We find evidence of a smooth intra-daily seasonality pattern, and an abnormal trade- and...

We introduce a new Stochastic Volatility model that postulates a general correlation structure between the shocks of the measurement and log volatility equations at different temporal lags. The resulting specification is able to better characterize the leverage effect and propagation in...

In this paper we propose a new class of dynamic mixture models (DAMMs) being able to sequentially adapt the mixture components as well as the mixture composition using information coming from the data. The information driven nature of the proposed class of models allows to exactly compute the...

This paper studies the behaviour of Bitcoin returns at different sample frequencies. We consider high frequency returns starting from tick-by-tick price changes traded at the Bitstamp and Coinbase exchanges. We find evidence of a smooth intra-daily seasonality pattern, and an abnormal trade- and...