What Drives the Aggregate Credit Risk: The Case of the Czech Republic
|Author:||Mgr. Jan Málek|
|Year:||2013 - summer|
|Leaders:|| PhDr. Jakub Seidler Ph.D.
|Work type:|| Finance, Financial Markets and Banking
|Awards and prizes:|
|Abstract:||There has been a long discussion about macroeconomic variables influencing the level of aggregate
credit risk in the economy. While literature provides both empirical evidence and theoretical explanation
of the influence of the business cycle on credit risk, the effect of other macroeconomic variables
has not been explored sufficiently. In addition, recent literature suggests the existence of a latent risk
factor behind aggregate credit risk, which is regularly interpreted as the latent default cycle.
This thesis provides in its first part a discussion of potential aggregate credit risk drivers, which have
been previously suggested in literature. We verify using a linear regression model whether the effect
of these macroeconomic variables is also apparent in the Czech Republic. Results seem to be stable
for both different model specifications and different clients segments and are in line with previous
The second part of this thesis explicitly models the latent factor that is assumed behind aggregate
credit risk by adding an unobserved component to the already existing model constructed earlier in
this thesis. The unobserved component can be estimated by applying Kalman filter. We subsequently
discuss the sources of the latent component and whether it can be interpreted as the default cycle.
The contribution of this paper is due to our belief twofold. First, we add a latent component to the
linear regression model. Secondly, we analyze if and under which circumstances the latent component
extension improves the fit of the regression model and discuss whether the explicit estimate of the
unobserved component has a feasible interpretation as the default cycle.