The Energy Journal

This paper introduces the ex-ante estimation of the variance risk premium. The novel methodology proposed is applied to forecast variance risk premium in energy markets, capturing the future degree of aversion of investors towards energy variance risks. We analyze the ex-ante variance risk premium of two energy indices, XLE and USO, during the period that spans from 2011 to 2022, and compare them to that of the SPX, the benchmark for the equity market. In the computation of the ex-ante variance risk premium, simple GARCH and Markov-switching GARCH models are exploited to forecast the realized variance, while variance swap rates are retrieved from the volatility indices VXXLE, OVX, and VIX of the three market indices. We find that the ex-ante variance risk premium succeeds to forecast the imminent periods of financial distress empirically detected in the abrupt surges and plunges of the ex-post variance risk premium. In particular,USO shows higher magnitudes of the variance risk premium than XLE and SPX, predicting that investors require on average higher premiums to bear oil variance risks.

Financialization has brought new challenges to the international energy markets, making energy systemic risk a more complicated issue. One of the important features is the development of cryptocurrency, which has become a critical part of the global financial markets. As a consequence, the rise and fall of cryptocurrency can have nonnegligible impacts on the systemic risks in the international energy sector. This paper empirically tests this hypothesis using the equity data of the top 100 energy companies from 2014 to 2021. Specifically, we explore the extreme shocks of cryptocurrency using multiple bubble tests, and then we test to what extent bubbles in cryptocurrency markets can affect systemic risk in the energy sector. Our empirical results show that the formation of cryptocurrency bubbles, especially when the bubbles burst, significantly increases systemic risks in the energy sector.This effect retains the same in the recent COVID-19 pandemic period. In addition, oil and gas companies play an essential channel in the risk spillover from cryptocurrency markets to the international energy markets.

Using network analysis on the connectedness of default factors in a credit default swap (CDS) dataset of U.S. and European energy firms, we provide the first evidence of differences in the shape and dynamics of the interconnectedness of the level, slope, and curvature, representing long-, short- and middle-term default factors, respectively. The interconnectedness of the three default factors increases during the European sovereign debt crisis (ESDC), whereas only the interconnectedness of the level factor increases during the oil price crash, and the interconnectedness of both level and slope factors spikes during COVID19. European firms contribute more to the transmission of long-term and short-term default risk from early 2011 till the beginning of the 2014–2105 oil price crash; afterwards, U.S. firms are major default transmitters despite some periods of parity with European firms. The impacts of oil demand and supply shocks on the various interconnectedness are quantile-dependent and more pronounced in the long term for the credit risk of the energy firms.

This paper provides global evidence that oil price shocks have significant impacts on bank risk. Specifically, all three oil shocks, including oil supply shocks, aggregate demand shocks, and oil specific demand shocks, have positive impacts on bank risk. In particular, oil specific demand shocks have different impacts on bank risk in oil-importing versus oil-exporting countries and in normal times versus the financial crisis period. Moreover, we find that interest rate spread could significantly explain the impacts of oil shocks on bank risk for oil-exporting countries during normal times. Our main results remain valid in various robustness tests.This study provides important practical implications for policy makers, banks, and investors around the world.

We develop two news-based investor attention measures from the news trends function of the Bloomberg terminal and investigate their predictive power for returns on crude oil futures contracts with various maturities. Our main results after controlling for relevant macroeconomic variables show that the Oil-based Institutional Attention Index is useful in predicting oil futures returns, especially during price downturn periods, while the forecasting accuracy is further improved when the Commodity Market Institutional Attention Index is used. This forecasting accuracy decreases, however, with the maturity of oil futures contracts. Moreover, we find some evidence of Granger-causality and regime-dependent interactions between investor attention measures and oil futures returns. Finally, variable selection algorithms matter before making predictions since they create the best forecasting results in many cases considered. These findings are important for informed traders and policymakers to better understand the price dynamics of the oil markets.

Due to difficulties in accessing detailed energy modelling and usage data that are required to estimate energy needs that are responsive to local circumstances, we propose an equivalence scale approach to the determination of required energy consumption. Our method requires the estimation of energy equivalence scales that are used to rescale reference household energy consumption and, thus, yield household-specific energy requirements. We apply the method using readily available income and expenditure data, finding that estimated required energy is well above actual energy expenditure for low- and middle-income households, which is consistent with an expectation that basic energy needs for poor households may not be met. The proposed approach is general enough to incorporate other features that might be deemed relevant and available in other settings, and, therefore, can be used to examine the affordability component of SDG 7, undertake energy poverty analysis or design appropriate policies.