Dynamics in Crude Oil Prices: A Markov-Switching Autoregressive Approach Incorporating Sunspot Activity
Journal Title: International Journal of Multidisciplinary Research and Analysis - Year 2024, Vol 7, Issue 08
Abstract
This paper deals with the dynamic relationship between world crude oil prices and the activities of sunspots in a two-state Markov-Switching Autoregressive (MS-AR) model. The data set used was from February 1994 to May 2023, with crude oil prices and sunspot numbers as an exogenous variable. The MS-AR framework allows for regime-dependent behavior in the intercept and autoregressive coefficients and in the impact of solar activity on oil prices. The result distinguishes two regimes characterized by different degrees of persistence and sensitivity to solar activity. State 1 is highly persistent in the movement of oil prices with a lag 1 coefficient and has a much weaker negative relationship with sunspot activity. On the other hand, State 2 shows lower persistence with a lag 1 coefficient but a stronger negative relationship with sunspots. The transition probabilities denote high stability in both regimes. Asymmetric switching behaviorfavors State1, which is the more persistent state. Model diagnostics values indicate very good fits to the data. The out-of-sample performance of the model does appear quite robust, as only a slight increase in RMSE to out-of-sample occurs. These findings help add to the present understanding of the complex dynamics governing crude oil prices and provide new insights into the possible influence of solar activity on energy markets. This regime-switching behavior found in this study has a bearing on energy policy, risk management, and the interconnections between natural phenomena and economic systems. This research underlines the need for nonlinear model approaches in capturing nuanced relationships in global energy markets.
Authors and Affiliations
Vicente Montano,Romeo Pajigal,Glenndon Sobrejuanite
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