Two-Scale Network Dynamic Model for Energy Commodity Processes
Joint Authors
Ladde, G. S.
Otunuga, Olusegun M.
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-59, 59 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-20
Country of Publication
Egypt
No. of Pages
59
Main Subjects
Abstract EN
In this work, we examine the relationship between different energy commodity spot prices.
To do this, multivariate stochastic models with and without external random interventions describing the price of energy commodities are developed.
Random intervention process is described by a continuous jump process.
The developed mathematical model is utilized to examine the relationship between energy commodity prices.
The time-varying parameters in the stochastic model are estimated using the recently developed parameter identification technique called local lagged adapted generalized method of moment (LLGMM).
The LLGMM method provides an iterative scheme for updating statistic coefficients in a system of generalized method of moment/observation equations.
The usefulness of the LLGMM approach is illustrated by applying to energy commodity data sets for state and parameter estimation problems.
Moreover, the forecasting and confidence interval problems are also investigated (U.S.
Patent Pending for the LLGMM method described in this manuscript).
American Psychological Association (APA)
Otunuga, Olusegun M.& Ladde, G. S.. 2020. Two-Scale Network Dynamic Model for Energy Commodity Processes. Journal of Energy،Vol. 2020, no. 2020, pp.1-59.
https://search.emarefa.net/detail/BIM-1184063
Modern Language Association (MLA)
Otunuga, Olusegun M.& Ladde, G. S.. Two-Scale Network Dynamic Model for Energy Commodity Processes. Journal of Energy No. 2020 (2020), pp.1-59.
https://search.emarefa.net/detail/BIM-1184063
American Medical Association (AMA)
Otunuga, Olusegun M.& Ladde, G. S.. Two-Scale Network Dynamic Model for Energy Commodity Processes. Journal of Energy. 2020. Vol. 2020, no. 2020, pp.1-59.
https://search.emarefa.net/detail/BIM-1184063
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1184063