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The Energy Journal
Volume 40, Special Issue



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Understanding Oil Price Dynamics and their Effects over Recent Decades: An Interview with James Hamilton

Fredj Jawadi


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Abstract:
The following interview with Prof. James Hamilton was conducted in April 2018 by Dr. Fredj Jawadi with the assistance of Professors Jim Smith and Adonis Yatchew during the 5th International Symposium in Computational Economics and Finance (ISCEF) held in Paris, France. The interview includes 21 questions related to oil price dynamics. The aim of the discussion was, first, to help the reader gain a better understanding of the factors driving changes in oil prices, second, to examine the impact of oil price shocks on the economy and, third, to understand the dynamics of oil prices in the future. The recent related literature on oil price uncertainty is also discussed. We hope that this interview will give the reader clearer insights into the causes and consequences of oil price change and its evolution over time.




Introduction to Topics on “Uncertainty and Recent Challenges in Oil and Commodity Markets

Fredj Jawadi and Apostolos Serletis

DOI: 10.5547/01956574.40.SI2.aser
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Abstract:
This ISCEF special issue of The Energy Journal presents new results in the area of energy economics to provide new insights on commodity markets, which will be helpful for investors, policymakers and analysts. In particular, this issue focuses on studies that use recent modeling techniques and empirical design. It introduces seven studies, presented at the fifth International Symposium in Computational Economics and Finance organized in Paris on April 12�14th, 2018 (www.iscef.com). These studies focus on the investigation of the dynamics of commodity markets, discuss the consequences of uncertainty on energy prices and their effects on the real economy and financial markets, and use high frequency data and recent econometric methods to empirically investigate the interactions between commodity markets and financial markets.




On the Oil Price Uncertainty

Zied Ftiti and Fredj Jawadi

DOI: 10.5547/01956574.40.SI2.zfti

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Abstract:
This study focuses on oil price volatility and uncertainty over the period January 1986-December 2018, covering episodes of oil price increases and collapses. Accordingly, in line with Poon and Granger (2003), and Terasvirta and Zhao (2011), we propose three different specifications of stochastic oil volatility: standard stochastic volatility, stochastic volatility moving average, leverage stochastic volatility models. We compute the out-of-sample forecasts for the uncertainty in oil prices using the estimates for these three stochastic oil price volatility models and we discuss its effects. Our findings show that the standard stochastic volatility model outperforms the other two models when focusing on oil price uncertainty. This finding is relevant to better forecast and understand the effects of oil price uncertainty on the real economy.




Location Basis Differentials in Crude Oil Prices

Phat V. Luong, Bruce Mizrach, and Yoichi Otsubo

DOI: 10.5547/01956574.40.SI2.pluo

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Abstract:
We examine the long-run pricing relationship among crude oil prices at the North Sea (Brent) and Cushing (WTI) delivery points. The Brent-WTI location basis differential is stable until December 2009, but it widens to record levels in the next two years. We report on recent changes in the crude oil market that causes the prices to move apart. Brent and WTI prices are cointegrated prior to this structural break, but not between 2010 and 2015. Since the U.S. lifted the crude oil export ban in December 2015, Brent and WTI prices have reintegrated. U.S. retail gasoline prices respond to Brent and WTI before January 2010 and then only to Brent afterwards.




Drilling Down: The Impact of Oil Price Shocks on Housing Prices

Valerie Grossman, Enrique Martínez-García, Luis Bernardo Torres, and Yongzhi Sun

DOI: 10.5547/01956574.40.SI2.vgro

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Oil Prices and Banking Instability: A Jump-Diffusion Model for Bank Capital Structure

Willi Semmler and Samar Issa

DOI: 10.5547/01956574.40.SI2.wsem

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Abstract:
We develop an empirical model of bank capital structure to study the impact of large oil shocks on overleveraging of banks which presents severe challenges for banks' balance sheet management. The measure of overleveraging builds on the Stein (2012) model by adding a jump-diffusion component that captures the jump size and intensity of predictors such as oil prices and political instability. Overleveraging is derived and estimated for a sample of six banks in three oil-producing countries and Western countries using the Markov Chain Monte Carlo (MCMC) method, for the years 2006-2016. The estimation of the optimal debt shows that most of the banks in this context had a high optimal debt around 2008, overlapping with the oil price shock. In addition, most of the predictors, namely oil prices and political instability factors proxied by terrorism, political corruption, and military expenses, regularly appeared in volatility and jump intensity factors.




Oil Prices and the Stock Markets: Evidence from High Frequency Data

Sajjadur Rahman and Apostolos Serletis

DOI: 10.5547/01956574.40.SI2.srah

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Abstract:
We use the highest frequency data that have ever been studied before to investigate the relationship between the price of oil and stock market returns. In the context of a bivariate (identified using heteroscedasticity in daily data) structural VAR in stock market returns and the change in the price of oil, we find evidence that positive oil price shocks have negative and statistically significant effects on stock market returns. Our results are robust to the use of different types of market returns, including aggregate and disaggregate U.S. market returns, aggregate and disaggregate U.S. excess returns, returns of the energy sector, returns of the major oil and gas companies, and global, eurozone, and some country specific stock market returns. They are also robust to the use of weekly data.




Do Jumps and Co-jumps Improve Volatility Forecasting of Oil and Currency Markets?

Fredj Jawadi, Waël Louhichi, Hachmi Ben Ameur, and Zied Ftiti

DOI: 10.5547/01956574.40.SI2.fjaw

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Abstract:
This paper aims at modeling and forecasting volatility in both oil and USD exchange rate markets using high frequency data. We test whether extreme co-movements (co-jumps) between these markets, as well as intraday unexpected news, help to improve volatility forecasting or not. Accordingly, we propose different extensions of Corsi (2009)'s model by including co-jumps and news. Our analysis provides two interesting findings. First, we find that both markets exhibit significant co-jumps driven by unexpected macroeconomic news. Second, we show that our model outperforms Corsi (2009)'s model and provides more accurate forecasts. In particular, while co-jumps constitute a key variable in forecasting oil price volatility, the unexpected news is relevant to forecasts of USD exchange rate volatility.




Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets

Jozef Baruník and Evžen Kocenda

DOI: 10.5547/01956574.40.SI2.jbar
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Abstract:
We analyze total, asymmetric and frequency connectedness between oil and forex markets using high-frequency, intra-day data over the period 2007-2017. By employing variance decompositions and their spectral representation in combination with realized semivariances to account for asymmetric and frequency connectedness, we obtain interesting results. We show that divergence in monetary policy regimes affects forex volatility spillovers but that adding oil to a forex portfolio decreases the total connectedness of the mixed portfolio. Asymmetries in connectedness are relatively small. While negative shocks dominate forex volatility connectedness, positive shocks prevail when oil and forex markets are assessed jointly. Frequency connectedness is largely driven by uncertainty shocks and to a lesser extent by liquidity shocks, which impact long-term connectedness the most and lead to its dramatic increase during periods of distress.




 

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