Oil Price Risk Research Articles

Geopolitical Oil Price Risk and Economic Fluctuations

Geopolitical Oil Price Risk and Economic Fluctuations

Diversifying crude oil price risk with crude oil volatility index: The role of volatility-of-volatility

To understand the diversification benefit of crude oil volatility, we examine the return-volatility relation in the crude oil market, given the interaction of the volatility (VOL) and the volatility-of-volatility (VOV). We develop a novel empirical model of the crude oil price and crude oil volatility index (OVX) returns incorporating both time-varying and state-dependent variances and correlations, thus allowing us to identify distinct market regimes of VOL and VOV. We find that the behavior of the return-volatility relation is contingent on the prevailing VOV regimes. Specifically, in a low (high) VOV regime, the relation becomes less (more) negative as VOL increases. These empirical results therefore imply that the diversification benefit of crude oil volatility is far from uniform across the different market states. Finally, using our proposed empirical model, we demonstrate the economic significance of recognizing both the time-varying and state-dependent variances/correlations in portfolio risk forecasting and construction.

Heterogeneity of regional carbon emission markets in China: Evidence from multidimensional determinants

The Chinese carbon markets are heterogeneously distributed with different regional economies and natural resource endowments. This paper examines how carbon prices behave across regional emission markets in China using the dynamic model averaging (DMA) approach. The results show that the Beijing, Guangdong, and Hubei markets are increasingly affected by various factors. In contrast, the Shanghai market gradually becomes less affected after 2020, both in the current and forecast periods. Moreover, geopolitical risk and new energy price are important variables for the concurrent relation, and domestic oil price and geopolitical risk are important variables for predicting carbon prices. Nevertheless, there are significant differences in intensity and signs among the four carbon markets affected by various factors, as well as large differences between the results for the current and forecast periods. These results indicate the heterogeneity of regional carbon markets; therefore, caution should be taken when using a single carbon market to represent the entire Chinese market.

Geopolitical Oil Price Risk and Economic Fluctuations

Geopolitical Oil Price Risk and Economic Fluctuations

Extreme co-movements between decomposed oil price shocks and sustainable investments

This paper investigates the extreme co-movements between three types of decomposed oil price shocks, e.g., supply shock, demand shock, and risk shock, and sustainable investments, using the generalized extreme value - autoregressive conditional Fréchet - tail quotient correlation coefficient (GEV-AcF-TQCC) analytical framework. The empirical results have identified that there are regular extreme co-movements between the three types of oil shocks and sustainable investments under extreme market conditions, especially, during the 2014–2016 oil crisis, the COVID-19 pandemic and the event of negative oil prices in 2020, according to the dynamic tail quotient correlation coefficient (TQCC) method. Specifically, the upside and downside trends of supply shocks, the downside trend of demand shocks, and the upside trend of risk shocks act as transmitters of the tail risks between oil prices and sustainable investments. The results also have demonstrated that the tail risk indexes for both the upside and downside trends of decomposed oil price shocks and sustainable investments have time-varying and asymmetric characteristics. Additionally, the static TQCC results have validated that among the three types of oil shocks, demand shocks exhibit the most pronounced tail risk spillover effects on sustainable investments, followed by supply and risk shocks, whose tail risk spillovers are close to each other. A series of alternative analyses ensure the robustness of the findings presented in this paper, which can offer valuable guidance and insights to policymakers and financial investors.

Is geopolitical oil price uncertainty forcing the world to use energy more efficiently? Evidence from advanced statistical methods

This paper argues that energy efficiency is a potent shield against oil price uncertainty in an increasingly interconnected world fraught with geopolitical tensions. By reducing dependence on oil, enhancing economic resilience, and improving energy security, energy efficiency measures offer multifaceted benefits for both national economies and global stability. Specifically, a wavelet coherence analysis is conducted to study the response of global energy efficiency to geopolitical oil price uncertainty. Quantile-on-quantile and quantile regressions are additionally employed to separate the impacts of various geopolitical oil price risk quantiles on the quantiles of energy efficiency. These methods are utilized in the examination of global time-series data covering the timeframe 2004:Q1–2020:Q4. The wavelet coherence outcomes indicate a positive correlation between geopolitical oil price uncertainty and energy efficiency, particularly during the energy crisis of the 2000s and the COVID-19 pandemic. The results also reveal that geopolitical oil price uncertainty leads to energy efficiency, indicating that an upsurge in geopolitical oil price uncertainty causes energy efficiency to increase. Moreover, the results from quantile-on-quantile and quantile regressions affirm the predominantly positive effects of geopolitical oil price uncertainty on global energy efficiency. Our conclusion therefore is that through strategic investments, innovative policies, and international collaborations relating to energy efficiency, nations can fortify themselves against the destabilizing effects of geopolitical conflicts on energy markets. This would ensure a more sustainable and secure energy future for all.

Welfare gains from market insurance: The case of Mexican oil price risk

Mexico has a long-standing practice of hedging oil price risk through the purchase of put options. We examine the resulting welfare gains using a standard sovereign default model calibrated to Mexican data. We show that hedging increases welfare by reducing income volatility and reducing risk spreads on sovereign debt. We find welfare gains equivalent to a permanent increase in consumption of 0.44 percent with 90 percent of these gains stemming from lower risk spreads.

Oil Price and Geopolitics Risk: New Causality Insights in Frequency-Domain

Oil Price and Geopolitics Risk: New Causality Insights in Frequency-Domain

Crude Oil Price Bubble Identification and Risk Assessment From Different Spot Markets: Establishing a Sustainable Energy Policy

Crude oil, as a strategic energy resource for social development, has witnessed substantial price fluctuations in recent years, impacting the sustainability of economy, ecological environment, and energy security. This paper utilized weekly crude oil price data from January 2003 to March 2023 to examine price bubbles in different markets using the SADF and GSADF methods, identified the duration of price bubbles by comparing the BSADF series with critical value series, assessed the risk of price bubbles in different markets using the established comprehensive indicators, and explored sustainable energy policies from the perspectives of both crude oil importers and exporters. The findings of this study indicate that bubbles exist in the world’s major crude oil markets, with linkages and differences in their origin and termination across different markets. The risk of price bubbles varies widely across different crude oil markets and has significant geographical characteristics, with a higher risk in the markets such as OPEC, Oman, and Dubai, and a lower risk in the markets such as WTI, Brent, and Daqing. This paper proposes sustainable energy policies from the perspective of energy importers and exporters. This is of great importance to enhance the ability of different countries to cope with the risk of crude oil price bubbles and to ensure the sustainability of economic development, ecological environment, and energy security.

ANÁLISIS DE FACTORES MACROECONÓMICOS QUE AFECTAN LA COTIZACIÓN DE ACCIONES DE LAS COMPAÑÍAS AÉREAS

Change in stock prices and development of the market vary depending on decisions made by investors. Decisions made by investors are determined by corporate performance, the country’s economic situation, political developments and changes in macroeconomic factors. In this study, the relationship between stock prices of airlines and macroeconomic variables was analyzed. To accomplish this, daily macroeconomic data of 14 airlines covering the years 2009-2018 were analyzed by Toda Yomamato and HatemiJ asymmetric causality tests, and macroeconomic factors (Brent oil price, dollar exchange rate and interest rate) determining stock prices were identified. According to the results of the Toda and Yomamato causality test, it was found that there was a significant relationship among variables of the dollar exchange rate, the price of oil and stock prices of airlines. Except for one airline, there was no significant relationship between interest rate and stock price. According to the results of the Hatemi-J asymmetric causality test, it was found that there were significant relationships among variables of the dollar exchange rate, oil price, interest rate, and airline stock prices. In light of these findings, innovation and adoption of alternative fuel technology by the aviation industry and airlines can be a successful alternative to oil price risk. Results on exchange rate and interest rate changes indicate that airlines and related governments should focus on policies that increase growth of the aviation industry

The role of renewable energy in hedging against oil price risks: A study of OECD net oil importers

The role of renewable energy in hedging against oil price risks: A study of OECD net oil importers

The Effects of Energy Prices on Oil-Gas Sectoral Stock Returns for BRIC Countries: Evidence from Space State Models

This paper examines the effects of oil and natural gas prices on the oil and gas sectors of the BRIC countries (Brazil, Russia, India, and China) over the period over from 20013 to 2022. Unlike previous studies, it employs a time-varying capital asset pricing model based on the estimation of state-space mode. In brief, the findings highlight significant changes in the asset-pricing model parameters across all countries, indicating the limitations of using time-invariant estimates. Specifically, Brazil shows the highest volatility in oil price risk, followed by Russia, both being oil-exporting countries, while market beta values remain relatively stable. Time-varying estimates further suggest that natural gas parameters are relatively lower and less significant than those of oil prices. The Russian-Ukrainian conflict's energy crisis adversely affects the performance of oil and gas sectoral stock returns. This war has had a negative and significant impact on China's oil-gas stock return.

Spillover connectedness nexus geopolitical oil price risk, clean energy stocks, global stock, and commodity markets

This study aims to investigate the volatility connectedness among geopolitical oil price risk, clean energy stocks, global equity, and commodity markets by utilizing novel empirical methods, namely Diebold and Yilmaz (2012) and Baruník and Křehlík (2018), to examine the volatility connectedness among the sample markets based on time and frequency domains. The study employed monthly data spanning from September 2004 to September 2020. The results are as follows. First, geopolitical oil price risk and global equity markets act as net volatility transmitters, while the gold market serves as the sole net volatility receiver within the system. Second, geopolitical oil price risk transmits the highest volatility spillovers to the gold market. Third, we confirm the time-varying nature of volatility connectedness among geopolitical oil price risk, clean-energy, global equity, and commodity markets. We also observe that the volatility interlinkage among these markets intensifies during worldwide crisis periods, such as the Arab Spring, oil supply glut, and the COVID-19 pandemic crisis. Lastly, long-term connectedness plays the most dominant role in the system, indicating that volatility spillovers among markets are persistent and long-lasting. This suggests lower portfolio diversification opportunities for investors in the long run. Robustness checks for our empirical findings are also provided, and policy implications are discussed.

RETRACTED: Geopolitical oil price uncertainty transmission into core inflation: Evidence from two of the biggest global players

This research argues that inflation indirectly correlates with geopolitics through the oil markets. The argument is that uncertainties generated by geopolitics are often transmitted into core inflation through oil prices, and we provide empirical evidence to support this by establishing an uncertainty-oil-macroeconomy nexus for the biggest oil importing countries, the U.S. and China. The study specifically examines whether there are indirect contributions of geopolitical oil price uncertainty to inflation that appear in core inflation, excluding the more volatile food and energy prices. It employs a non-parametric quantile causality technique for analyzing how geopolitical oil price uncertainty and core inflation interact in both countries and conducts rolling windows-based non-parametric quantile causality analysis for robustness. The full-time non-parametric quantile causality results show that geopolitical oil price risk strongly affects core inflation both in mean and variance, especially in the mid-quantiles, and that its effect is greater in variance relative to mean for both countries. The rolling windows-based outcomes indicate that geopolitical oil price risk exerts an increasing influence on core inflation during important geopolitical events such as the Euro crisis, Brexit, presidential elections, trade wars, and COVID-19, and these impacts differ not only between countries, but also according to whether causality is mean or variance. Finally, the significance of the findings is discussed.

Early warning of exchange rate risk based on structural shocks in international oil prices using the LSTM neural network model

The Russia–Ukraine conflict has caused an external shock to the oil market as the exchange rate risk increased with significant depreciation of major currencies relative to the U.S. dollar (USD). In this paper, structural shocks to oil prices calculated by the Ready (2018) method are introduced in addition to traditional exchange rate predictor variables such as oil prices. Utilising a long short-term memory neural network model, we verify the early warning effect of structural shocks to international oil prices on exchange rate risk in the context of the Russia–Ukraine geo-conflict. We have several empirical findings. First, the variance decomposition method indicates that oil price shocks affect the euro-dollar exchange rate risk. After the conflict between Russia and Ukraine, the euro exchange rate risk continued to rise significantly, mainly affected by supply shocks. Second, compared with traditional prediction models, the LSTM neural network model has a higher prediction accuracy, which is conducive to improving the early warning performance of exchange rate risks and maintaining the stability of the foreign exchange market. Third, the introduction of oil price shock can fully extract and use the information from oil price changes, which significantly improves the learning performance of the oil price early warning model of exchange rate risk. Fourth, the introduction of oil price risk shocks in the whole sample, the introduction of oil price demand shocks before the Russia-Ukraine conflict, and the introduction of oil price supply shocks, especially negative supply shocks, after the conflict between Russia and Ukraine, can warn exchange rate risks more effectively. This study proposes a new method for early warning of exchange rate risk that can help cross-border enterprises and government policymakers to respond to unexpected events and effectively mitigate associated risks.

Exploring the vital role of geopolitics in the oil market: The case of Russia

Investigating the essential role of geopolitics in the oil market is significant for investors to optimize their portfolios. This paper takes Russian geopolitics into consideration and innovatively conducts the sub-sample test to explore the time-dependent interaction between oil price (OP) and Russian geopolitical risk (RGR). The outcomes refer to that RGR could positively and adversely affect OP. The positive effects point out that high RGR might boost the oil market, resulting in an increase in OP. However, this opinion can not be evidenced by the adverse influences, which mainly due to the apolitical factors. In turn, there exist positive impacts of OP on RGR, suggesting that high OP might deteriorate the geopolitical circumstance in Russia, and the oil market could be considered as an indicative factor to grasp RGR more comprehensively. In the context of increasingly complex geopolitics in Russia, investors could benefit from the oil market to reduce potential losses and gain profits from their investment. Besides, Russian government could predict RGR on the basis of OP to protect the health of their citizens and national security.

Asymmetric and Lag Effects of Industry Risk Factors on the Malaysian Oil and Gas Stocks

This study examines asymmetric and the lag effects of oil price, gas price, and exchange rate on stock performance of the Malaysian oil and gas sub-industries. Using company-level data and multi factor asset pricing models, this study found that oil price, gas price, exchange rate, and common systematic risk factors such as market, size, and book-to-market have significant effects on the stock performance of Malaysian oil and gas sub-industries, but these exposures remain heterogeneous. Oil price and exchange rate show strong asymmetrical impacts on stock performance when decomposed into oil price increases (decreases) and exchange rate depreciation (appreciation). Increases in oil price and exchange rate depreciation have a greater impact on stock performance of oil and gas industry than decreases in oil price and exchange rate appreciation. Oil price, gas price, and exchange rate exhibit lag effects on the performance of oil and gas stocks. The findings have important asset pricing implications for profitable investment and portfolio strategies based on oil and gas risk factors for oil-exporting country.JEL Classifications: C13; C58; G10; G12; G14; Q4

Managerial performance and oil price shocks

Using an innovative method that segregates oil shocks into supply, consumption demand, and inventory demand factors, we find empirical evidence that managerial ability can have a significant but varying influence on firm performance under these circumstances. Generally, high-ability managers are most beneficial to manufacturing firms during oil shocks. In the event of oil supply shocks that are associated with negative economic implications, talented managers strongly outperform in (i) energy, (ii) agriculture, forestry, & fishing, and (iii) services industries. However, during oil demand consumption shocks that are symbolic of economic growth, competent managers underperform in the (a) energy, (b) mining, (c) construction, (d) retail, and (e) services sectors. Notably, high-ability managers in energy firms are associated with significant outperformance and underperformance during oil supply and consumption shocks, respectively. It is probable that these adept managers employ more active hedging programs to reduce financial distress or minimize earnings volatility to safeguard against oil price downturns. Similarly, in other industries, it is plausible that skillful managers may actively engage in oil price risk management (e.g., reducing reliance, alternatives, hedging, etc.). During supply shocks, the associated benefits outweigh the costs, and vice versa during oil consumption demand shocks.

Knowledge Discovery to Support WTI Crude Oil Price Risk Management

The high volatility of commodity prices and various problems that the energy sector has to deal with in the era of COVID-19 have significantly increased the risk of oil price changes. These changes are of the main concern of companies for which oil is the main input in the production process, and therefore oil price determines the production costs. The main goal of this paper is to discover decision rules for a buyer of American WTI (West Texas Intermediate) crude oil call options. The presented research uses factors characterizing the option price, such as implied volatility and option sensitivity factors (delta, gamma, vega, and theta, known as “Greeks”). The performed analysis covers the years 2008–2022 and options with an exercise period up to three months. The decision rules are discovered using association analysis and are evaluated in terms of the three investment efficiency indicators: total payoff, average payoff, and return on investment. The results show the existence of certain ranges of the analyzed parameters for which the mentioned efficiency indicators reached particularly high values. The relationships discovered and recorded in the form of decision rules can be effectively used or adapted by practitioners to support their decisions in oil price risk management.

The impact of oil and natural gas prices on overnight risk in exchange rates based on the MVMQ-CAViaR models

Existing research has not yet studied the impact of oil and gas prices on the overnight risk in exchange rates. This paper examines the impact of oil and natural gas prices on the overnight risk in the RMB, HKD, and Yen. An MVMQ-CAViaR model of multiple markets and an MVMQ-CAViaR model of combined influence are proposed to measure the impact of oil and natural gas prices on the overnight risk in the Yen, HKD, and RMB from 2013 to 2019. The empirical results show that the overnight risk in the RMB, HKD, and Yen are impacted by lagged risk and that the RMB suffer from the largest risks. The three exchange rates' overnight risks are impacted by the risk in oil prices and natural gas prices. However, the Yen suffers from the largest risk, and the HKD suffers from the smallest risk. This shows the fragility of Japan's energy sector and its extreme dependence on energy imports. This shows that the energy sector has little impact on the Hong Kong economy, which is dominated by finance and trading. The two industries of trading and finance do not require much energy. The impact of natural gas price risks on the overnight risk in the RMB, HKD, and Yen is smaller than that of oil price risks. All overnight risks are affected by the combined influence of oil prices and natural gas prices. The Yen exchange rate suffers from the greatest influence relative to the HKD exchange rate and RMB exchange rate. Thus, when oil prices and natural gas prices fall at the same time, more attention should be paid to the effect of their combined influence on national exchange rates. Financial regulators need to be ready for exchange rate fluctuations. The MVMQ-CAViaR model of combined influence is more accurate than the MVMQ-CAViaR model of multiple markets, especially at the 1% significance level and for HKD, and the MVMQ-CAViaR model of combined influence produces better estimates.