In this work we propose a V.a.R.-like decision method which is close to the one using the past history. In particular, we empirically reconstruct the conditional distribution of the analyzed financial returns by applying two soft-computing techniques which are respectively based on fuzzy non-parametric estimation and on polynomial neural network. Note that we, indirectly, check both the weak efficient market hypothesis and the semi-strong one.

Soft-computing algorithms for a V.a.R.-like decision method

CORAZZA, Marco
;
GIOVE, Silvio
1999-01-01

Abstract

In this work we propose a V.a.R.-like decision method which is close to the one using the past history. In particular, we empirically reconstruct the conditional distribution of the analyzed financial returns by applying two soft-computing techniques which are respectively based on fuzzy non-parametric estimation and on polynomial neural network. Note that we, indirectly, check both the weak efficient market hypothesis and the semi-strong one.
1999
S.CO.99
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5785
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