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Adaptive Monte Carlo methods to estimate financial risk models

People

 

Mira A.

(Responsible)

Barone Adesi G.

(Co-responsible)

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
30.09.2012
Duration
24 Months
Funding sources
SNSF
Status
Ended
Category
Swiss National Science Foundation / Project Funding / Division II - Mathematics, Natural and Engineering Sciences