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

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

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.

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  • Fredj Jawadi, Waël Louhichi, Hachmi Ben Ameur, and Zied Ftiti, 2019. "Do Jumps and Co-jumps Improve Volatility Forecasting of Oil and Currency Markets?," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    • Handle: RePEc:aen:journl:ej40-si2-louhichi
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    1. Domenico Ferraro & Ken Rogoff & Barbara Rossi, 2011. "Can Oil Prices Forecast Exchange Rates?," Working Papers 11-05, Duke University, Department of Economics.
    2. Barnett, William A., 2012. "Getting it Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262516888, December.
    3. Suzanne S. Lee & Per A. Mykland, 2008. "Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics," The Review of Financial Studies, Society for Financial Studies, vol. 21(6), pages 2535-2563, November.
    4. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    5. Reboredo, Juan Carlos & Rivera-Castro, Miguel A. & Zebende, Gilney F., 2014. "Oil and US dollar exchange rate dependence: A detrended cross-correlation approach," Energy Economics, Elsevier, vol. 42(C), pages 132-139.
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    Cited by:

    1. Fredj Jawadi & Mohamed Sellami, 2022. "On the effect of oil price in the context of Covid‐19," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3924-3933, October.
    2. Vincenzo Candila & Denis Maximov & Alexey Mikhaylov & Nikita Moiseev & Tomonobu Senjyu & Nicole Tryndina, 2021. "On the Relationship between Oil and Exchange Rates of Oil-Exporting and Oil-Importing Countries: From the Great Recession Period to the COVID-19 Era," Energies, MDPI, vol. 14(23), pages 1-18, December.
    3. Louhichi, Waël & Ftiti, Zied & Ameur, Hachmi Ben, 2021. "Measuring the global economic impact of the coronavirus outbreak: Evidence from the main cluster countries," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    4. Oguzhan Cepni, Duc Khuong Nguyen, and Ahmet Sensoy, 2022. "News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    5. Zhang, Yue-Jun & Zhang, Han, 2023. "Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?," International Review of Financial Analysis, Elsevier, vol. 85(C).
    6. Cui, Xin & Sensoy, Ahmet & Nguyen, Duc Khuong & Yao, Shouyu & Wu, Yiyao, 2022. "Positive information shocks, investor behavior and stock price crash risk," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 493-518.
    7. Ftiti, Zied & Ben Ameur, Hachmi & Louhichi, Waël, 2021. "Does non-fundamental news related to COVID-19 matter for stock returns? Evidence from Shanghai stock market," Economic Modelling, Elsevier, vol. 99(C).

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