An approach to identifying micro behavior: How banks’ strategies influence financial cycles

In this paper, we show that the values of parameters of a well-calibrated model are useful in detecting micro behavior. We use a calibration procedure suitable for validating agent-based models to show how the evolution of model parameters, obtained via a rolling window estimation, illustrates the evolution of agents’ strategies in response to different economic conditions. In this regard, we calibrate the well-known financial model of Brock and Hommes using three banking indices (i.e., the S&P SmallCap 600 Financials Index, the STOXX Europe 600 Banks, and the STOXX Asia/Pacific 600 Banks) running from 1994 to 2016. The choice of a spatially and temporally diversified dataset allows us to analyze differences and similarities in the behavior of banks belonging to the different macro areas, as well as to capture agents’ reaction to the several economic phases characterizing the time series investigated.