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Modelling high-frequency volatility and liquidity using multiplicative error models

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  • Hautsch, Nikolaus
  • Jeleskovic, Vahidin

Abstract

In this paper, we study the dynamic interdependencies between high-frequency volatility, liquidity demand as well as trading costs in an electronic limit order book market. Using data from the Australian Stock Exchange we model 1-min squared mid-quote returns, average trade sizes, number of trades and average (excess) trading costs per time interval in terms of a four-dimensional multiplicative error model. The latter is augmented to account also for zero observations. We find evidence for significant contemporaneous relationships and dynamic interdependencies between the individual variables. Liquidity is causal for future volatility but not vice versa. Furthermore, trade sizes are negatively driven by past trading intensities and trading costs. Finally, excess trading costs mainly depend on their own history.

Suggested Citation

  • Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2008-047
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    2. repec:hum:wpaper:sfb649dp2008-051 is not listed on IDEAS
    3. Vahidin Jeleskovic & Anastasios Demertzidis, 2018. "Comparing different methods for the estimation of interbank intraday yield curves," MAGKS Papers on Economics 201839, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    4. Chen, Shiyi & Jeong, Kiho & Härdle, Wolfgang Karl, 2008. "Recurrent support vector regression for a nonlinear ARMA model with applications to forecasting financial returns," SFB 649 Discussion Papers 2008-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Borak, Szymon & Weron, Rafal, 2008. "A semiparametric factor model for electricity forward curve dynamics," MPRA Paper 10421, University Library of Munich, Germany.
    6. Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    7. Będowska-Sójka, Barbara & Kliber, Agata, 2019. "The causality between liquidity and volatility in the Polish stock market," Finance Research Letters, Elsevier, vol. 30(C), pages 110-115.
    8. Anastasios Demertzidis & Vahidin Jeleskovic, 2021. "Empirical Estimation of Intraday Yield Curves on the Italian Interbank Credit Market e-MID," JRFM, MDPI, vol. 14(5), pages 1-23, May.
    9. repec:hum:wpaper:sfb649dp2008-050 is not listed on IDEAS
    10. Anastasios Demertzidis, 2019. "Interbank transactions on the intraday frequency: -Different market states and the effects of the financial crisis-," MAGKS Papers on Economics 201932, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

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    More about this item

    Keywords

    Multiplicative error models; volatility; liquidity; high-frequency data;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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