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On the Oil Price Uncertainty

Zied Ftiti and Fredj Jawadi

Year: 2019
Volume: Volume 40
Number: Special Issue
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.



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

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

Year: 2019
Volume: Volume 40
Number: Special Issue
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.



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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