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1

A NEW GARCH PROCESS WITH HYPERBOLIC NOISE

100%
Talar P.
Przegląd Statystyczny
|
2007
|
vol. 54
|
issue 2
28-46
EN
In this article the author discusses the application of the hyperbolic (HYP) distributions in modeling of a volatility in the financial and real estate markets. He analyses and builds a new GARCH-type process with hyperbolic noise (the HYP-GARCH (p,q) process). He derives moment structure for this new process and necessary and sufficient conditions for the existence of the unconditional order moments of the strictly stationary and ergodic solution in this process. Moreover, he computes the log likelihood function for the HYP-GARCH(p,q) process in Theorem 5.1 and, at the end, he discusses the quality of the adjustment of the (1,1)-version of the analysed process to the real estate market (empirical) data.
2

MODELING A DISTRIBUTION OF MORTGAGE CREDIT LOSSES

88%
Gapko P., Šmíd M.
Ekonomický časopis (Journal of Economics)
|
2012
|
vol. 60
|
issue 10
1005 – 1023
EN
In our paper, we focus on the credit risk quantification methodology. We demonstrate that the current regulatory standards for credit risk management are at least not perfect. Generalizing the well-known KMV model, standing behind Basel II, we build a model of a loan portfolio involving a dynamics of the common factor, influencing the borrowers’ assets, which we allow to be non-normal. We show how the parameters of our model may be estimated by means of past mortgage delinquency rates. We give statistical evidence that the non-normal model is much more suitable than the one which assumes the normal distribution of risk factors. We point out in what way the assumption that risk factors follow a normal distribution can be dangerous. Especially during volatile periods comparable to the current crisis, the normal-distribution-based methodology can underestimate the impact of changes in tail losses caused by underlying risk factors.
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