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Fractional Integration and Asymmetric Volatility in European, American and Asian Bull and Bear Markets: Application to High‐frequency Stock Data

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  • Ola Oluwa S. Yaya
  • Luis A. Gil‐Alana
  • Olanrewaju I. Shittu

Abstract

This paper is a follow‐up to another paper by the same authors. In that paper, fractional integration and symmetric volatility modelling were considered on monthly frequency data, while the present paper considers high‐frequency data on an asymmetric volatility model. The data were first identified within the respective bull and bear phases following earlier results in the previous paper. Then, fractional integration and the asymmetric volatility model of Glosten, Jaganathan and Runkle were applied on the stock returns. Long‐range dependence was detected in the squared stock returns at each market phase, and they were more persistent than those obtained in the monthly frequency data. The estimates of asymmetry of the Glosten, Jaganathan and Runkle model actually detected the different patterns of the bad news (bear phases) and the good news (bull phases). Copyright © 2015 John Wiley & Sons, Ltd.

Suggested Citation

  • Ola Oluwa S. Yaya & Luis A. Gil‐Alana & Olanrewaju I. Shittu, 2015. "Fractional Integration and Asymmetric Volatility in European, American and Asian Bull and Bear Markets: Application to High‐frequency Stock Data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 20(3), pages 276-290, July.
  • Handle: RePEc:wly:ijfiec:v:20:y:2015:i:3:p:276-290
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    Cited by:

    1. Chen, Shuning & Zhang, Wei & Feng, Xu & Xiong, Xiong, 2020. "Asymmetry of retail investors’ attention and asymmetric volatility: Evidence from China," Finance Research Letters, Elsevier, vol. 36(C).
    2. Furuoka, Fumitaka & Yaya, OlaOluwa Simon & Ling, Pui Kiew & Al-Faryan, Mamdouh Abdulaziz Saleh & Islam, M. Nazmul, 2023. "Transmission of risks between energy and agricultural commodities: Frequency time-varying VAR, asymmetry and portfolio management," Resources Policy, Elsevier, vol. 81(C).
    3. Yaya, OlaOluwa S. & Ogbonna, Ahamuefula E. & Olubusoye, Olusanya E., 2019. "How persistent and dynamic inter-dependent are pricing of Bitcoin to other cryptocurrencies before and after 2017/18 crash?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    4. Selmi, Refk & Bouoiyour, Jamal, 2020. "Arab geopolitics in turmoil: Implications of Qatar-Gulf crisis for business," International Economics, Elsevier, vol. 161(C), pages 100-119.
    5. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Asl, Mahdi Ghaemi & Jalalifar, Saba, 2021. "Financing the green projects: Market efficiency and volatility persistence of green versus conventional bonds, and the comparative effects of health and financial crises," International Review of Financial Analysis, Elsevier, vol. 78(C).
    6. Refk Selmi & Youssef Errami & Mark E Wohar, 2020. "Are U.S. industries resilient in dealing with trade uncertainty ? The case of U.S.-China trade war," Post-Print hal-02523186, HAL.
    7. Viktor Manahov, 2021. "High‐frequency trading order cancellations and market quality: Is stricter regulation the answer?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5385-5407, October.
    8. Rangan Gupta & Mark Wohar, 2019. "The role of monetary policy uncertainty in predicting equity market volatility of the United Kingdom: evidence from over 150 years of data," Economics and Business Letters, Oviedo University Press, vol. 8(3), pages 138-146.

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