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A new combined approach on Hurst exponent estimate and its applications in realized volatility

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  • Luo, Yi
  • Huang, Yirong

Abstract

The purpose of this paper is to propose a new estimator of Hurst exponent based on the combined information of the conventional rescaled range methods. We demonstrate the superiority of the proposed estimator by Monte Carlo simulations, and the applications in estimating the Hurst exponent of daily volatility series in Chinese stock market. Moreover, we indicate the impact of the type of estimator and structural break on the estimating results of Hurst exponent.

Suggested Citation

  • Luo, Yi & Huang, Yirong, 2018. "A new combined approach on Hurst exponent estimate and its applications in realized volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1364-1372.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:1364-1372
    DOI: 10.1016/j.physa.2017.11.063
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    Citations

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    Cited by:

    1. Lahmiri, Salim & Bekiros, Stelios & Bezzina, Frank, 2020. "Multi-fluctuation nonlinear patterns of European financial markets based on adaptive filtering with application to family business, green, Islamic, common stocks, and comparison with Bitcoin, NASDAQ, ," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    2. Zeinali, Narges & Pourdarvish, Ahmad, 2022. "An entropy-based estimator of the Hurst exponent in fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    3. Ayesha Siddiqui & Mohd Shamim & Mohammad Asif & Mamdouh Abdulaziz Saleh Al-Faryan, 2022. "Are Stock Markets among BRICS Members Integrated? A Regime Shift-Based Co-Integration Analysis," Economies, MDPI, vol. 10(4), pages 1-25, April.
    4. Farid Makhlouf & Refk Selmi, 2021. "The role of remittances in times of socio-political unrest: Evidence from Tunisia," Working Papers hal-03263815, HAL.
    5. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    6. Ding, Liang & Luo, Yi & Lin, Yan & Huang, Yirong, 2021. "Revisiting the relations between Hurst exponent and fractional differencing parameter for long memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    7. Huang, Yirong & Luo, Yi, 2024. "Forecasting conditional volatility based on hybrid GARCH-type models with long memory, regime switching, leverage effect and heavy-tail: Further evidence from equity market," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).

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