Local Volatility Models in Commodity Markets and Online Calibration

33 Pages Posted: 22 Aug 2017

See all articles by Vinicius Albani

Vinicius Albani

Federal University of Santa Catarina

Uri Ascher

University of British Columbia (UBC)

Jorge P. Zubelli

Instituto de Matematica Pura e Aplicada (IMPA)

Date Written: August 18, 2017

Abstract

We introduce a local volatility model for the valuation of options on commodity futures by using European vanilla option prices. The corresponding calibration problem is addressed within an online framework, allowing the use of multiple price surfaces. Since uncertainty in the observation of the underlying future prices translates to uncertainty in data locations, we propose a model-based adjustment of such prices that improves reconstructions and smile adherence. In order to tackle the ill-posedness of the calibration problem we incorporate a priori information through a judiciously designed Tikhonov-type regularization. Extensive empirical tests with market and synthetic data are used to demonstrate the effectiveness of the methodology and algorithms.

Keywords: commodity future options, local volatility calibration, online approach, inverse problem, Tikhonov-type regularization

Suggested Citation

Albani, Vinicius and Ascher, Uri and Zubelli, Jorge P., Local Volatility Models in Commodity Markets and Online Calibration (August 18, 2017). Journal of Computational Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3021776

Vinicius Albani

Federal University of Santa Catarina ( email )

Campus Trindade
Florianopolis, Santa Catarina 88040-900
Brazil
+554837216560 (Phone)
+554837214612 (Fax)

HOME PAGE: http://mtm.ufsc.br/~v.albani/

Uri Ascher

University of British Columbia (UBC) ( email )

2329 West Mall
Vancouver, British Columbia BC V6T 1Z4
Canada

Jorge P. Zubelli (Contact Author)

Instituto de Matematica Pura e Aplicada (IMPA) ( email )

Estrada Dona Castorina 110
Jardim Botanico
Rio de Janeiro, 22460
Brazil

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
0
Abstract Views
495
PlumX Metrics