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Marked Hawkes process modeling of price dynamics and volatility estimation

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  • Kyungsub Lee
  • Byoung Ki Seo

Abstract

A simple Hawkes model have been developed for the price tick structure dynamics incorporating market microstructure noise and trade clustering. In this paper, the model is extended with random mark to deal with more realistic price tick structures of equities. We examine the impact of jump in price dynamics to the future movements and dependency between the jump sizes and ground intensities. We also derive the volatility formula based on stochastic and statistical methods and compare with realized volatility in simulation and empirical studies. The marked Hawkes model is useful to estimate the intraday volatility similarly in the case of simple Hawkes model.

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  • Kyungsub Lee & Byoung Ki Seo, 2019. "Marked Hawkes process modeling of price dynamics and volatility estimation," Papers 1907.12025, arXiv.org.
    • Handle: RePEc:arx:papers:1907.12025
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    Cited by:

    1. Herrera, R. & Clements, A.E., 2018. "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 161-175.
    2. Sobin Joseph & Shashi Jain, 2024. "Non-Parametric Estimation of Multi-dimensional Marked Hawkes Processes," Papers 2402.04740, arXiv.org.
    3. Lee, Kyungsub, 2023. "Recurrent neural network based parameter estimation of Hawkes model on high-frequency financial data," Finance Research Letters, Elsevier, vol. 55(PA).
    4. Kyungsub Lee, 2023. "Recurrent neural network based parameter estimation of Hawkes model on high-frequency financial data," Papers 2304.11883, arXiv.org.
    5. Ji, Jingru & Wang, Donghua & Xu, Dinghai & Xu, Chi, 2020. "Combining a self-exciting point process with the truncated generalized Pareto distribution: An extreme risk analysis under price limits," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 52-70.
    6. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    7. Konark Jain & Nick Firoozye & Jonathan Kochems & Philip Treleaven, 2024. "Limit Order Book Simulations: A Review," Papers 2402.17359, arXiv.org, revised Mar 2024.
    8. Kyungsub Lee, 2024. "Discrete Hawkes process with flexible residual distribution and filtered historical simulation," Papers 2401.13890, arXiv.org.
    9. Timoth'ee Fabre & Ioane Muni Toke, 2024. "Neural Hawkes: Non-Parametric Estimation in High Dimension and Causality Analysis in Cryptocurrency Markets," Papers 2401.09361, arXiv.org, revised Nov 2024.
    10. Lee Kyungsub, 2024. "Multi-kernel property in high-frequency price dynamics under Hawkes model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(4), pages 605-624.

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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