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.File in questo prodotto:
File | Dimensione | Formato | |
---|---|---|---|
1999-Corazza_Giove-Soft_computing_algorithms_for_a_VaR-like_decision_method-SCO.pdf
non disponibili
Descrizione: Articolo nella versione dell'editore.
Tipologia:
Versione dell'editore
Licenza:
Accesso chiuso-personale
Dimensione
859.79 kB
Formato
Adobe PDF
|
859.79 kB | Adobe PDF | Visualizza/Apri |
I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.