Oil Price estimating Under Dynamic Economic Models Using Markov Chain Monte Carlo Simulation Approach

Advances in Mathematical Finance and Applications

مقاله 13، دوره 6، شماره 3، مهر 2021، صفحه 631-651   

نوع مقاله: Research Paper

شناسه دیجیتال (DOI): 10.22034/amfa.2020.1902265.1446

نویسندگان

Kianoush Fathi Vajargah^{* 1}؛ Hossein Eslami Mofid Abadi²؛ Ebrahim Abbasi³

¹Department of Statistics, Islamic Azad University, North branch, Tehran, Iran,

²Department of Accounting & AMP; Management, Shahriyar Branch, Islamic Azad University, Shahriyar, Iran

³Faculty of Social Sciences & AMP; Economics, Alzahra University, Thehrn, Iran

چکیده

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

کلیدواژه‌ها

Oil Prices؛ Stochastic Volatility؛ Jump-Diffusion Process؛ Markov chain Monte Carlo Simulation

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