The role of oil price uncertainty shocks on oil-exporting countries

Śmiech, Sławomir; Papież, Monika; Rubaszek, Michał; Snarska, Małgorzata

doi:10.1016/j.eneco.2020.105028

Cited by 38 publications

(11 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The financial and economic sectors are closely associated with energy and environmental markets (Nasir et al, 2019 ). The literature reports some initiatives from authors to address the issues related to the energy market (Maghyereh & Abdoh, 2020 ; Śmiech et al, 2021 ; Van Eyden et al, 2019 ), the environment (Sharif et al, 2019 ; Waheed et al, 2019 ; Yao et al, 2019 ), and risk management (Brenner et al 2006 ). Still, there are ample opportunities to study these issues in more detail, which have motivated us to embark on this task and set the theme of this SI titled “ Financial Modelling and Risk Management of Energy and Environmental Instruments and Derivatives ”.…”

Section: Introductionmentioning

confidence: 99%

Financial modeling, risk management of energy and environmental instruments and derivatives: past, present, and future

et al. 2022

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Financial modeling, risk management of energy and environmental instruments and derivatives: past, present, and future

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Mien [32] finds that oil prices and revenues have increased the currency value of oil-exporting economies and not the internal real exchange rate for manufacturing goods. Oil price uncertainty shocks are studied by Smiech et al [33] who find that they decrease industrial production while Norway faces imminent temporary currency devaluations.…”

Section: Introductionmentioning

confidence: 99%

The Macroeconomic Results of Diligent Resource Revenues Management: The Norwegian Case

Perifanis¹

2022

Energies

View full text Add to dashboard Cite

Many commodity-exporting countries saw their revenues plummet and experienced fiscal deficits during the pandemic. The economic rebound will restore resource exports/revenues and a new round of debate will be initiated on revenues utilization. Countries will decide either to internalize revenues or capitalize them with investments abroad. Our autoregressive distributed lag (ARDL) models provide evidence of the benefits Norway enjoys since it has not internalized revenues. The currency rate, long-term bond yields, and GDP growth are insulated from prices volatility. Furthermore, the country can absorb currency appreciations/devaluations and long-term credit rate hikes through government expenditure. However, monetary steering is favored in the long term (absorbs yield increases), while in the short run it can allow for speculative activities by credit investors. Countries should not internalize resource revenues to avoid experiencing decreased competitiveness and economic growth and increased credit rates. However, the temptation will be high enough since deficits and support packages cost a lot. This study also includes years of low prices. Thus, our research reveals the extent and limitations of diligent revenue management from a country considered as a role model.

show abstract

“…Literature has also identified the impact of oil price shocks on macroeconomic aggregates such as the level of investment, stock prices and returns [12][13][14][15][16][17], inflation rate [18], industrial production and exchange rates [19][20][21][22][23], as well as financial and monetary policy [24]. There has also been a large number of studies concerning the impact of crude oil prices on various groups of commodities such as: gold [25,26], silver, platinum and palladium [27], zinc, copper and molybdenum [28], agricultural [29][30][31][32], and energy commodities [33][34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of Artificial Neural Networks in Hedging against WTI Crude Oil Price Risk

2021

View full text Add to dashboard Cite

Despite the growing share of renewable energy sources, most of the world energy supply is still based on hydrocarbons and the vast majority of world transport is fuelled by oil products. Thus, the profitability of many companies may depend on the effective management of oil price risk. In this article, we analysed the effectiveness of artificial neural networks in hedging against the risk of WTI crude oil prices increase. This was reformulated from a regressive problem to a classification problem. The effectiveness of our approach, using artificial neural networks to classify observations, was verified for over ten years of WTI futures quotes, starting from 2009. The data analysis presented in this paper confirmed that the buyer of a call option was more often likely to incur a loss as a result of its purchase than make a profit after the final payoff from the call option. The results of the conducted research confirm that neural networks can be an effective form of protection against the risk of price fluctuations. The effectiveness of a network’s operation depends on the choice of assessment indicators, but analyses show that the networks which, for the indicator that was selected, gave the best results for the training set, also resulted in positive rates of return for the test set. Significantly, we also showed interdependence between seemingly unrelated indicators: percentage of the best possible results achieved in the analysed period of time by the proposed method and percentage of all available call options that were purchased based on the results from the networks that were used.

show abstract

The role of oil price uncertainty shocks on oil-exporting countries

Cited by 38 publications

References 43 publications

Financial modeling, risk management of energy and environmental instruments and derivatives: past, present, and future

Financial modeling, risk management of energy and environmental instruments and derivatives: past, present, and future

The Macroeconomic Results of Diligent Resource Revenues Management: The Norwegian Case

Effectiveness of Artificial Neural Networks in Hedging against WTI Crude Oil Price Risk

Contact Info

Product

Resources

About