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Adaptive Monte Carlo methods to estimate financial risk models

People

Leaders

Mira A.

(Responsible)

Barone Adesi G.

(Co-Responsable USI)

Collaborators

Peluso S.

(Collaborator)

Abstract

We plan to study a new adaptive Monte Carlo importance sampling algorithm and to use it to estimate a novel model to predict volatility. The model will be cast both in a Bayesian and a classical framework and the predictive power of the two will be compared. A non-parametric version of the Bayesian model will be also proposed to gain higher flexibility.

Additional information

Start date
01.10.2010
End date
01.10.2012
Duration
24 Months
Funding sources
Status
Ended