Risk measurement of oil price based on Bayesian nonlinear quantile regression model

Oil price forecasting is one of the most challenging issues since it is noisy, non-stationary, and chaotic. In this paper, we design a Bayesian Nonlinear Quantile method consisting of a Threshold Improved model and an Adaptive MCMC model to improve predicting performance. Specifically, the threshold...

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Bibliographic Details
Published in:	Alexandria Engineering Journal
Main Authors:	Jian Zhu, Haiming Long, Jingjing Deng, Wenzhi Wu
Format:	Article
Language:	English
Published:	Elsevier 2021-12-01
Subjects:	Bayes Threshold Oil price risk VaR
Online Access:	http://www.sciencedirect.com/science/article/pii/S1110016821002714

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