Oil Shocks and BRIC Markets: Evidence from Extreme Quantile Approach

Naeem, Muhammad; Pham, Linh; Senthilkumar, A.; Karim, Sitara

doi:10.2139/ssrn.3957368

Cited by 4 publications

(6 citation statements)

References 29 publications

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“…The results suggest a significant influence of the outbreak crisis on the market efficiency dynamics of the energy markets. The results confirm the earlier evidence that also proposes market inefficiencies in the financial markets increased during the COVID-19 period (e.g., Naeem and Karim, 2021 , Naeem et al, 2022c , Mensi et al, 2021 , Lee et al, 2021 , Liu and Lee, 2021 ). The results follow the notion that uncertain economic conditions give rise to a higher degree of market inefficiencies ( Lee et al, 2017 ).…”

Section: Data and Empirical Resultssupporting

confidence: 90%

“…Though markets are experiencing continuous challenges due to the COVID-19 pandemic, the comparative analysis of the efficiency provides groundbreaking evidence for policymakers and investors to choose between two alternative investment streams. The efficiency/inefficiency of dirty and clean energy markets offers beneficial information to forecast future returns, explore arbitrage opportunities in the face of asymmetric information, and developing effective risk management tools ( Naeem et al, 2022b , Naeem et al, 2022c , Karim et al, 2022c , Karim et al, 2022d ). Consistently, multifractality in the markets identifies significant crisis periods with notable uncertainty preponderant among the financial markets.…”

Section: Introductionmentioning

confidence: 99%

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Comparing the asymmetric efficiency of dirty and clean energy markets pre and during COVID-19

Naeem

Karim

Farid

et al. 2022

Economic Analysis and Policy

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Section: Data and Empirical Resultssupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Comparing the asymmetric efficiency of dirty and clean energy markets pre and during COVID-19

Naeem

Karim

Farid

et al. 2022

Economic Analysis and Policy

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“…Further, Silver and Gold were the major risk emitters to commodity markets during global financial crises while WTI, rice, wheat, and corn were the risk receiver. Dahl et al (2020) and Naeem et al (2022c) also reported similar findings.…”

Section: Review Of Related Literaturesupporting

confidence: 67%

Modelling systemic risk of energy and non-energy commodity markets during the COVID-19 pandemic

et al. 2022

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COVID-19 led restrictions make it imperative to study how pandemic affects the systemic risk profile of global commodities network. Therefore, we investigate the systemic risk profile of global commodities network as represented by energy and nonenergy commodity markets (precious metals, industrial metals, and agriculture) in pre- and post-crisis period. We use neural network quantile regression approach of Keilbar and Wang (Empir Econ 62:1–26, 2021) using daily data for the period 01 January 2018–27 October 2021. The findings suggest that at the onset of COVID-19, the two firm-specific risk measures namely value at risk and conditional value of risk explode pointing to increasing systemic risk in COVID-19 period. The risk spillover network analysis reveals moderate to high lower tail connectedness of commodities within each sector and low tail connectedness of energy commodities with the other sectors for both pre- and post-COVID-19 periods. The Systemic Network Risk Index reveals an abrupt increase in systemic risk at the start of pandemic, followed by gradual stabilization. We rank commodities in terms of systemic fragility index and observe that in post COVID-19 period, gold, silver, copper, and zinc are the most fragile commodities while wheat and sugar are the least fragile commodities. We use Systemic Hazard Index to rank commodities with respect to their risk contribution to global commodities network. During post COVID-19 period, the energy commodities (except natural gas) contribute most to the systemic risk. Our study has important implications for policymakers and the investment industry.

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“…Consequent upon this shortfall, many researchers (see Anand & Paul, 2021;Ready, 2018) made efforts to recalibrate and augment the standard two-staged structural vector autoregression model of Killian (2009). Other authors, including Naeem et al (2021), Chatziantoniou et al (2022, Zhang et al (2022), among others, adopt the variants of these recalibrations. To address the identification issues, Baumeister and Hamilton (2019) provide a Bayesian extension to the Killian (2009) framework, which decomposes the shocks from oil price into four separate components as against the three components advanced in the baseline method.…”

Section: Introductionmentioning

confidence: 99%

Global Evidence of Oil Supply Shocks and Climate Risk a GARCH-MIDAS Approach

Ayinde

Adeyemi

2023

Energy RESEARCH LETTERS

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The study examines the global evidence of oil supply shocks and climate risks. Using the GARCH-MIDAS regression and a dataset spanning the period 2000 – 2018, we find that oil supply shocks are a better predictor of climate risks than the inherent environmental factors. The evidence indicates that oil supply shocks dampen climate risk challenges through the reservation and conservation channels. To reduce oil supply shocks, the study recommends the deployment of moral suasions in oil resource-rich countries.

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Oil Shocks and BRIC Markets: Evidence from Extreme Quantile Approach

Cited by 4 publications

References 29 publications

Comparing the asymmetric efficiency of dirty and clean energy markets pre and during COVID-19

Comparing the asymmetric efficiency of dirty and clean energy markets pre and during COVID-19

Modelling systemic risk of energy and non-energy commodity markets during the COVID-19 pandemic

Global Evidence of Oil Supply Shocks and Climate Risk a GARCH-MIDAS Approach

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