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A marked point process model for intraday financial returns: modeling extreme risk

Author

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  • Rodrigo Herrera

    (Universidad de Talca)

  • Adam Clements

    (Queensland University of Technology)

Abstract

Forecasting the risk of extreme losses is an important issue in the management of financial risk and has attracted a great deal of research attention. However, little attention has been paid to extreme losses in a higher frequency intraday setting. This paper proposes a novel marked point process model to capture extreme risk in intraday returns, taking into account a range of trading activity and liquidity measures. A novel approach is proposed for defining the threshold upon which extreme events are identified taking into account the diurnal patterns in intraday trading activity. It is found that models including covariates, mainly relating to trading intensity and spreads offer the best in-sample fit, and prediction of extreme risk, in particular at higher quantiles.

Suggested Citation

  • Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
  • Handle: RePEc:spr:empeco:v:58:y:2020:i:4:d:10.1007_s00181-018-1600-y
    DOI: 10.1007/s00181-018-1600-y
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    2. Stindl, Tom, 2023. "Forecasting intraday market risk: A marked self-exciting point process with exogenous renewals," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 182-198.
    3. Fadugba, Sunday Emmanuel, 2020. "Homotopy analysis method and its applications in the valuation of European call options with time-fractional Black-Scholes equation," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).

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    More about this item

    Keywords

    Hawkes process; Peaks over threshold; Bid-ask spread; Extreme risk; High frequency;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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