Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/342675
Type: Artigo
Title: Multidimensional calibration of crude oil and refined products via semidefinite programming techniques
Author: Saldivar, Carolina Effio
Herskovits, Jose
Luna, Juan Pablo
Sagastizabal, Claudia
Abstract: To describe the joint dynamics of prices of crude oil and refined products we extend twofactor models to a multidimensional setting. The new model captures directly the general correlation structure between the different commodities in the form of certain covariance matrix. Since the associated state-space formulation makes use of such correlations, the feasible set of the resulting estimation problem includes the cone of positive semidefinite matrices. Tractability is ensured by means of an interior point method, specially tailored for nonlinear semidefinite programming problems. For different sets of historical prices of crude oil, heating oil, and gasoline, the empirical out-of-sample forecasts obtained with the approach proposed in this work systematically provide an excellent fit to data
Subject: Programação semidefinida
Country: Singapura
Editor: World Scientific
Rights: Fechado
Identifier DOI: 10.1142/S0219024918500565
Address: https://www.worldscientific.com/doi/abs/10.1142/S0219024918500565
Date Issue: 2019
Appears in Collections:IMECC - Artigos e Outros Documentos

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