Oil price shocks, global financial markets and their connectedness

Demirer, Rıza; Ferrer, Román; Shahzad, Syed Jawad Hussain

doi:10.1016/j.eneco.2020.104771

Cited by 125 publications

(53 citation statements)

References 48 publications

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“…The information captured by demand and supply related oil factors is highlighted in an early study by Kilian (2009) , noting that one has to account for the different sources of oil price fluctuations by distinguishing between supply and demand related shocks in order to get a more accurate assessment of oil price dynamics. Demirer et al (2020) note that the decomposition method of Kilian (2009) has several shortcomings in that it tends to give too much weight to oil-specific demand shocks relative to supply shocks. The most limiting aspect of this decomposition method, however, is that it is limited to monthly frequency only and does not allow for higher frequency analysis.…”

Section: Methodsmentioning

confidence: 99%

“… 1 See, for example, Kang et al (2015) , Basher et al (2018) , Thorbecke (2019) , Demirer et al (2020) for recent applications. …”

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confidence: 99%

“… 5 As Demirer et al (2020) argue, supply shocks in this framework relate to region-specific or event-specific information that cannot be accounted for by stock-market related pricing effects. …”

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confidence: 99%

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The predictive power of oil price shocks on realized volatility of oil: A note

et al. 2020

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This paper examines the predictive power of oil supply, demand and risk shocks over the realized volatility of intraday oil returns. Utilizing the heterogeneous autoregressive realized volatility (HAR-RV) framework, we show that all shock terms on their own, and particularly financial market driven risk shocks, significantly improve the forecasting performance of the benchmark HAR-RV model, both in- and out-of-sample. Incorporating all three shocks simultaneously in the HAR-RV model yields the largest forecasting gains compared to all other variants of the HAR-RV model, consistently at short-, medium-, and long forecasting horizons. The findings highlight the predictive information captured by disentangled oil price shocks in accurately forecasting oil market volatility, offering a valuable opening for investors and corporations to monitor oil market volatility using information on traded assets at high frequency.

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Section: Methodsmentioning

confidence: 99%

“… 1 See, for example, Kang et al (2015) , Basher et al (2018) , Thorbecke (2019) , Demirer et al (2020) for recent applications. …”

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The predictive power of oil price shocks on realized volatility of oil: A note

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“…1 Constructed as a real-time measure of uncertainty related to the state of the economy, these indexes are computed on a daily basis as a weighted average of the squared surprises derived from a set of macroeconomic releases associated with employment, Gross Domestic Product (GDP), industrial production, manufacturing index, personal income, and retail sales, where the weights are based on the contribution of the associated real activity indicator to a business condition index, in line with Aruoba et al, (2009). In the case of the oil-price demand, supply, as well as risk shocks, we follow Ready (2018) and Demirer et al (2020) and collect daily price data for the world integrated oil and gas producer index, the nearest maturity NYMEX crude-light sweet oil futures contract, and the Chicago Board Options Exchange (CBOE) volatility index (VIX). 2 We use the nearest maturity NYMEX crudelight sweet oil futures contract as a proxy for the price of crude oil.…”

Section: Datamentioning

confidence: 99%

Oil shocks and directional predictability of macroeconomic uncertainties of developed economies: Evidence from high‐frequency data^†

Shahzad

Gupta

Demirer

et al. 2021

Scottish J Political Eco

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Using high-frequency (daily) data on macroeconomic uncertainties and the partial crossquantilogram approach, we examine the directional predictability of disentangled oil-price-shocks for the entire conditional distribution of uncertainties of five advanced economies (Canada, Euro Area, Japan, the United Kingdom, and the United States). Our results show that oil-demand, supply, and financial risk-related shocks can predict the future path of uncertainty; however, the predictive relationship is contingent on the initial level of macroeconomic uncertainty and the size of the shocks. Our results suggest that macroeconomic uncertainty is indeed predictable at high frequency, and that oil-price-shocks capture valuable predictive information regarding the future path of macroeconomic uncertainties.

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“…Recent studies such as Ji et al (2018b), Xiarchos and Burnett (2018), Guhathakurta et al, (2020), and Demirer et al (2020), has adopted the connectedness measure proposed by Diebold and Yilmaz (2009, 2012, 2014, 2016. The FEVD connectedness model has been extended to the frequency domain by Barunik and Krehlik (2018) to examine connectedness in the short-, medium-, and long-term.…”

Section: Literature Reviewmentioning

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Time and Frequency Connectedness Among Oil Shocks, Electricity and Clean Energy Markets

et al. 2020

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This paper examines the time and frequency dynamics of connectedness between oil price shocks (demand and supply), and energy, electricity, carbon and clean energy markets using the methodology developed by Diebold and Yilmaz (2012) and Barunik and Krehlik (2018). The empirical findings show that there is time-varying connectedness among all variables in the sample. We find increased connectedness during the global financial crisis as well as in the shale oil revolution period. The total connectedness is more significant and higher in the short-term compared to the long-term. Net pairwise directional connectedness become more important during the shale oil revolution among oil supply, oil demand and clean energy index. The findings of the static full sample and sub-samples (GFC and SOR) provide significant evidence of the electricity futures as diversifier and safe-haven asset for oil shocks. These results can have important implications for investors and policymakers with different time horizons.

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Oil price shocks, global financial markets and their connectedness

Cited by 125 publications

References 48 publications

The predictive power of oil price shocks on realized volatility of oil: A note

The predictive power of oil price shocks on realized volatility of oil: A note

Oil shocks and directional predictability of macroeconomic uncertainties of developed economies: Evidence from high‐frequency data^†

Time and Frequency Connectedness Among Oil Shocks, Electricity and Clean Energy Markets

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Oil price shocks, global financial markets and their connectedness

Cited by 125 publications

References 48 publications

The predictive power of oil price shocks on realized volatility of oil: A note

The predictive power of oil price shocks on realized volatility of oil: A note

Oil shocks and directional predictability of macroeconomic uncertainties of developed economies: Evidence from high‐frequency data†

Time and Frequency Connectedness Among Oil Shocks, Electricity and Clean Energy Markets

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Product

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Oil shocks and directional predictability of macroeconomic uncertainties of developed economies: Evidence from high‐frequency data^†