The inhomogeneity of the cross-sectional distribution of realized assets’ volatility is explored and used to build a novel class of GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models. The inhomogeneity of the cross-sectional distribution of realized volatility is captured...

Let {Yt}, t=1,..., T be a time series generated according to the model: Yt=f(Xt)+et t=1, ..., T where f is a non linear continuous function, Xt = (X1t, X2t, ...,Xdt) is a vector of d non stochastic explanatory variables defined on a compact X belonging Rd , and {et} are zero mean random...

One of the most critical issues when using neural networks is how to select appropriate network architectures for the problem at hand. Practitioners usually refer to information criteria which might lead to over-parameterized models with heavy consequence on overfitting and poor ex-post forecast...