6 papers
Causal effect of regulated Bitcoin futures on volatility and volume
Fiammetta Menchetti, Fabrizio Cipollini, Fabrizia Mealli
In December 2017, two leading derivative exchanges, CBOE and CME, introduced the first regulated Bitcoin futures. Our aim is estimating their causal impact on Bitcoin volatility an…
Multiplicative Error Models: 20 years on
Fabrizio Cipollini, Giampiero M. Gallo
Several phenomena are available representing market activity: volumes, number of trades, durations between trades or quotes, volatility - however measured - all share the feature t…
Estimating the causal effect of an intervention in a time series setting: the C-ARIMA approach
Fiammetta Menchetti, Fabrizio Cipollini, Fabrizia Mealli
The Rubin Causal Model (RCM) is a framework that allows to define the causal effect of an intervention as a contrast of potential outcomes. In recent years, several methods have be…
Doubly Multiplicative Error Models with Long- and Short-run Components
Alessandra Amendola, Vincenzo Candila, Fabrizio Cipollini +1
We suggest the Doubly Multiplicative Error class of models (DMEM) for modeling and forecasting realized volatility, which combines two components accommodating low-, respectively,…
A dynamic conditional approach to portfolio weights forecasting
Fabrizio Cipollini, Giampiero M. Gallo, Alessandro Palandri
We build the time series of optimal realized portfolio weights from high-frequency data and we suggest a novel Dynamic Conditional Weights (DCW) model for their dynamics. DCW is be…
Copula--based Specification of vector MEMs
Fabrizio Cipollini, Robert F. Engle, Giampiero M. Gallo
The Multiplicative Error Model (Engle (2002)) for nonnegative valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation proces…