Uncertainty and energy-sector equity returns in Iran: a Bayesian and quasi-Monte Carlo time-varying analysis

Abstract

This study investigates whether the implied crude oil volatility and the historical OPEC price volatility can impact the return to and volatility of the energy-sector equity indices in Iran. The analysis specifically considers the refining, drilling, and petrochemical equity sectors of the Tehran Stock Exchange. The parameter estimation uses the quasi-Monte Carlo and Bayesian optimization methods in the framework of a generalized autoregressive conditional heteroskedasticity model, and a complementary Bayesian network analysis is also conducted. The analysis takes into account geopolitical risk and economic policy uncertainty data as other proxies for uncertainty. This study also aims to detect different price regimes for each equity index in a novel way using homogeneous/non-homogeneous Markov switching autoregressive models. Although these methods provide improvements by restricting the analysis to a specific price-regime period, they produce conflicting results, rendering it impossible to draw general conclusions regarding the contagion effect on returns or the volatility transmission between markets. Nevertheless, the results indicate that the OPEC (historical) price volatility has a stronger effect on the energy sectors than the implied volatility has. These types of oil price shocks are found to have no effect on the drilling sector price pattern, whereas the refining and petrochemical equity sectors do seem to undergo changes in their price patterns nearly concurrently with future demand shocks and oil supply shocks, respectively, gaining dominance in the oil market.

The COVID-19 storm and the energy sector: The impact and role of uncertainty

“…Panel A of Table 4 shows that Δ CV 19 I t has a statistically significant and negative effect on global energy sector returns with a β i ,∆ CV 19 I of −0.0028, and on all national energy sectors. These results are consistent with the nascent literature on the negative impact of COVID-19 uncertainty on market aggregates ( Costola et al, 2020 ; Liu et al, 2020 ; Smales, 2021 amongst others) and mirror prior studies on the sensitivity of this sector to uncertainty ( Bianconi and Yoshino, 2014 ; Fazelabdolabadi, 2019 ; Nikkinen and Rothovius, 2019 ).…”

“…These results constitute evidence that COVID-19 related uncertainty triggers volatility for most national energy sectors. In line with this, Fazelabdolabadi (2019) reported that oil price uncertainty contributed to increased volatility in the Iranian energy sector while Liu (2020) found that COVID-19 related uncertainty fuelled greater Chinese stock return volatility. Smales (2021) also reported increased stock market return volatility in response to COVID-19 uncertainty, similarly measured using Google search trends for individual markets that comprise the G7 grouping.…”

“… Zhu et al (2020) reported that investor sentiment was significantly related to the pricing of securities in the oil and gas sector as it contributes to pricing anomalies. Fazelabdolabadi (2019) discovered that implied crude oil price uncertainty and economic policy uncertainty had a negative impact on Iranian energy sector returns and resulted in increased volatility. These results are consistent with a broader body of literature which finds that uncertainty negatively impacts asset prices and is crucial to investment decisions ( Anderson et al, 2009 ; Bams et al, 2017 ; Naeem et al, 2020 ).…”

Overall profit Malmquist productivity index under data uncertainty

“…Hatami-Marbini et al (2018) developed an overarching evaluation process for estimating the RTS of DMUs under imprecise DEA (IDEA), where the input and output data lie within bounded intervals. For more on IDEA, see Shabani et al (2019), Ebrahimi (2018), Fazelabdolabadi (2019), Toloo et al (2018), Shokouhi et al (2014), Hatami-Marbini et al (2017), Ureña et al (2019), Zhang et al (2019), Kao et al (2014) and the references therein.…”

The role of global economic policy uncertainty in predicting crude oil futures volatility: Evidence from a two-factor GARCH-MIDAS model

“…A large number of studies show that the commodity futures are valuable sources of diversification investment for investors and portfolio managers (Arouri et al, 2011;Fazelabdolabadi, 2019;Klein, 2017;Lucey et al, 2017). Geman and Kharoubi (2008) explore the diversification effect brought by crude oil futures contracts into a portfolio of stocks.…”