Credit market, Price fluctuations, Market interactions, Interest rate dynamics, Nonlinear dynamics, C02, C6, E4,

Due to recent developments in credit markets, the interdependencies among fixed rate mortgages (FRMs) and adjustable rate mortgages (ARMs) markets are analysed in the study of the interactions within credit markets since it appears very suitable and interesting. A meaningful and complete database of information on Financial Institutions (FIs) in Italy (1997Italy ( :q1 -2011) hold by the Banca d'Italia shows that the relative importance of these markets recently displayed significant fluctuations since in 2005 fixed interest rate mortgage loans were about 10% while in 2009 they raised up to 70%. In the context of the FRMs and ARMs characteristics in Italian markets as well as the available database, among the proposed models for the study of interconnected markets (see Hommes (1997, 1998), Westerhoff (2009, 2010) and related literature citetd therein), the models recently developed by Casellina et al. ( 2011) is applied to test its capacity to capture the dynamics of the observed data. It is worth stressing that the involved real data (volume of contracts and average interest rate in the FRMs and ARMs markets) are not sample information but they are evaluated on the entire population. The obtained findings point out the good level to fit the interest rates dynamics. Moreover, the model captures the switching mechanism and it catches the structural breaks when they occurs.

Heterogeneity, Interaction, Agent-based-models, Statistical mechanics, Master equation, Kramers–Moyal expansion, Fokker–Planck equation, Mean field theory, C02, E20,

Credit risk migration rates matrices with entries, migrations of stayers and exits are simulated;A mathematical procedure to extrapolate future dynamics conditional to a macroeconomic scenario is developed; IFRS9 segmentation into buckets and prospective estimates of Expected Loss are introduced.

No abstract