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Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements

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  • Mensi, Walid
  • Hammoudeh, Shawkat
  • Yoon, Seong-Min

Abstract

This paper analyzes the dual long memory properties of four major foreign exchange markets of the world oil exporter Saudi Arabia, using the ARFIMA–FIGARCH model under several global events. It discerns the impacts of both scheduled and unscheduled news announcements and structural changes on changing persistence. The results show little evidence of long memory in the conditional mean but provide strong support for long memory in conditional volatility for the four Saudi exchange rates versus major currencies. Moreover, scheduled news announcements have no significant impact on both expectations and volatility, while unscheduled news announcements demonstrate significant effects on the conditional volatility for all exchange rates. Furthermore, we detect at least five structural changes for the exchange rate with the yen and four for the rest of the exchange rates. The structural breaks seem to have greater impacts on changing persistence, and that the ARFIMA–FIGARCH model coupled with the dummy variables of the unscheduled news announcements and the structural changes is the most suitable for examining the long memory processes of these foreign exchange markets in in-sample. Finally, the out-of-sample forecasts provide mixed results and indicate that none of the specifications of the volatility model is appropriate for analyzing the LM dynamics in the Saudi Arabian exchange market. Overall, our results have implications for portfolio managers and policy makers in oil-producing countries.

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  • Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.
  • Handle: RePEc:eee:reveco:v:30:y:2014:i:c:p:101-119
    DOI: 10.1016/j.iref.2013.10.004
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    2. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2015. "Structural breaks, dynamic correlations, asymmetric volatility transmission, and hedging strategies for petroleum prices and USD exchange rate," Energy Economics, Elsevier, vol. 48(C), pages 46-60.
    3. Alexopoulos, Michelle & Cohen, Jon, 2015. "The power of print: Uncertainty shocks, markets, and the economy," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 8-28.
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    5. Al-Shboul, Mohammad & Anwar, Sajid, 2016. "Fractional integration in daily stock market indices at Jordan's Amman stock exchange," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 16-37.
    6. Zhu, Xiaoqian & Xie, Yongjia & Li, Jianping & Wu, Dengsheng, 2015. "Change point detection for subprime crisis in American banking: From the perspective of risk dependence," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 18-28.
    7. Rodríguez-Aguilar, Román & Cruz-Aké, Salvador & Venegas-Martínez, Francisco, 2014. "A Measure of Early Warning of Exchange-Rate Crises Based on the Hurst Coefficient and the Αlpha-Stable Parameter," MPRA Paper 59046, University Library of Munich, Germany.
    8. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    9. repec:eee:jrpoli:v:53:y:2017:i:c:p:88-102 is not listed on IDEAS

    More about this item

    Keywords

    Dual long memory; Structural breaks; News announcements; ARFIMA–FIGARCH model; Out-of-sample forecasts;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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