We consider nonlinear models for expected asset returns, employing neural network architectures. These models can be interpreted in terms of financial common risk factors. We investigate competing inferential approaches through a simulation experiment, implemented in a parallel environment.
Stochastic simulation of models for expected asset returns based on neural networks: a parallel experience
ZANGHIRATI, Gaetano
1998
Abstract
We consider nonlinear models for expected asset returns, employing neural network architectures. These models can be interpreted in terms of financial common risk factors. We investigate competing inferential approaches through a simulation experiment, implemented in a parallel environment.File in questo prodotto:
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