Oil Price estimating Under Dynamic Economic Models Using Markov Chain Monte Carlo Simulation Approach
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_AMFA-6-3_013
تاریخ نمایه سازی: 20 تیر 1400
Abstract:
This study, attempts to estimate and compare four different models of jump-diffusion class combined with stochastic volatility that are based on stochastic differential equations, and their parameters latent variables are estimated by Markov chain Monte Carlo (MCMC) methods. In the Stochastic Volatility with Correlated Jumps (SVCJ) model, volatilities are scholastic, and the term jump is added to both scholastic prices and volatilities. The results of this study showed that this model is more efficient than the others are, as it provides a significantly better fit to the data, and therefore, corrects the shortcomings of the previous models and that it is closer to the actual market prices. Therefore, our estimating model under the Monte Carlo simulation allows an analysis on oil prices during certain times in the periods of tension and shock in the oil market
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Authors
Kianoush Fathi Vajargah
Department of Statistics, Islamic Azad University, North branch, Tehran, Iran,
Hossein Eslami Mofid Abadi
Department of Accounting & AMP; Management, Shahriyar Branch, Islamic Azad University, Shahriyar, Iran
Ebrahim Abbasi
Faculty of Social Sciences & AMP; Economics, Alzahra University, Thehrn, Iran
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