This paper uses the Markov-switching multifractal (MSM) model and generalized autoregressive conditional heteroscedasticity (GARCH)-type models to forecast oil price volatility over the time periods from January 02, 1875 to December 31, 1895 and from January 03, 1977 to March 24, 2014. Based on...

This paper investigates the driving forces behind banks' link formation in the interbank market by applying the stochastic actor oriented model (SAOM) developed in sociology. Our data consists of quarterly networks constructed from the transactions on an electronic platform (e-MID) over the...

This paper proposes a stochastic model of a bipartite credit network between banks and the non-bank corporate sector that encapsulates basic stylized facts found in comprehensive data sets for bank-firm loans for a number of countries. When performing computational experiments with this model,...

We explore the issue of estimating a simple agent-based model of price formation in an asset market using the approach of Alfarano et al. (2008) as an example. Since we are able to derive various moment conditions for this model, we can apply generalized method of moments (GMM) estimation. We...

This paper applies Markov-switching multifractal (MSM) processes to model and forecast carbon dioxide (CO2) emission price volatility, and compares their forecasting performance to the standard GARCH, fractionally integrated GARCH (FIGARCH) and the two-state Markov-switching GARCH (MS-GARCH)...