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Long Memory in Oil and Refined Products Markets

Kyongwook Choi and Shawkat Hammoudeh

Year: 2009
Volume: Volume 30
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol30-No2-5
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Abstract:
We test for the presence of long memory in daily oil and refined products prices absolute return, squared return and conditional volatility, using several parametric and semiparametric methods. This study finds strong evidence of long memory (LM) in the daily absolute and squared spot and futures returns for crude oil, gasoline and heating oil but at different degrees. The FIGARCH model also demonstrates strong evidence of LM for volatility for most of oil and products prices returns, with also different resilience levels. Structural breaks have only the partial effects of slightly reducing persistence for just absolute and squared returns. Examining the forecasting behavior of two competing models, the less parsimonious ARFIMA which satisfies the LM property, and the parsimonious ARMA with short-term processes, the ARFIMA model provides significantly better out-of-sample forecasts at all forecasting horizons for all three petroleum types.



What Should be Taken into Consideration when Forecasting Oil Implied Volatility Index?

Panagiotis Delis, Stavros Degiannakis, and Konstantinos Giannopoulos

Year: 2023
Volume: Volume 44
Number: Number 5
DOI: 10.5547/01956574.44.4.pdel
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Abstract:
This study forecasts the oil volatility index (OVX) incorporating information from other implied volatility (IV) indices. We provide evidence for the existence of long memory in the OVX in order to justify the use of the Heterogeneous AutoRegressive (HAR) model. We extend the HAR model by implementing a dynamic model averaging (DMA) method in order to allow for IV indices from other asset classes to be applicable at different time periods. Apart from the statistical evaluation, a straddle options trading strategy validates our results from an economic point of view. The IV of Dow Jones is highly significant for short- and mid-run forecasting horizons, whereas, at longer horizons, the IV of Energy Sector provides accurate forecasts but only from an economic point of view.



Understanding Intraday Oil Price Dynamics during the COVID-19 Pandemic: New Evidence from Oil and Stock Investor Sentiments

Mohamed Arbi Madani and Zied Ftiti

Year: 2024
Volume: Volume 45
Number: Number 3
DOI: 10.5547/01956574.45.3.mmad
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Abstract:
This study employed intraday stock market and oil investor sentiment data related to news and social media (i.e., the Thomson Reuters MarketPsych Indices [TRMI] sentiment index) to gauge investors' interest in the West Texas Intermediate (WTI) crude oil futures market during the recent health crisis. We proposed an original nonlinear empirical framework by considering oil price dynamics' complexity and its potential interaction with investor sentiment. The analysis revealed three noteworthy findings. First, we observed evidence of nonlinearity in the relationship between excess returns on WTI crude oil futures and investor sentiment data. Second, the causality direction moved only from oil and stock market investor sentiment to oil returns. Third, the impacts of oil and stock market sentiment data on crude oil returns (i.e., volatility) were always negative. Furthermore, sentiment data related to social media showed a more pronounced cross-correlation than that of news.





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