On the interaction between market and credit risk: a factor-augmented vector autoregressive (FAVAR) approach

The aim of the paper is to understand the interaction between market and credit risk. Using a comprehensive set of Italian data, we apply a factor model to identify the common sources of risk driving fluctuations in the real and financial sectors. The common latent factors are then inserted in a VAR framework via a Factor Augmented Vector Autoregressive (FAVAR) approach to analyse the role of risk interactions with monetary policy shocks. We find that the impact of a restrictive monetary policy shock on credit risk is amplified when considering the feedback effect deriving from macroeconomic and equity market risk. Thus, neglecting dynamic interactions among risks may lead to biased estimates of the overall risk measure. The approach provides a framework for modelling macro and financial feedback dynamics, shedding some light on the complex interdependence between the financial sector and the real economy.