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A semi-parametric point process model of the interactions between equity markets

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Abstract

A novel point process framework to examine the links between transaction data across equity markets is proposed. Moving beyond a simple exponential kernel specification, it is shown that the kernel matrix can be estimated by solving a system of integral equations which is uniquely characterised by second order cumulants. The cumulant based estimator is shown to be asymptotically normally distributed and consistent and is shown to perform well in a small simulation study. Applying this method to data from U.S and U.K. equity markets when both are open, reveals that two-way interaction between trades is significant. Moreover, this interaction is characterised by both complex short term dynamics and long memory, which cannot be captured by conventioanl exponential kernels.

Suggested Citation

  • Clements, A.E. & Hurn, A.S. & Lindsay, K.A. & Volkov, V.V, 2017. "A semi-parametric point process model of the interactions between equity markets," Working Papers 2017-06, University of Tasmania, Tasmanian School of Business and Economics.
    • Handle: RePEc:tas:wpaper:23504
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    File URL: http://eprints.utas.edu.au/23504/1/2017-06_Clements_Hurn_Lindsay_Volkov.pdf
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    Keywords

    point processes; high-frequency data; conditional intensity;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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