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Liquidity-adjusted Intraday Value at Risk modeling and risk management: An application to data from Deutsche Börse

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  • Dionne, Georges
  • Pacurar, Maria
  • Zhou, Xiaozhou

Abstract

This paper develops a high-frequency risk measure: the Liquidity-adjusted Intraday Value at Risk (LIVaR). Our objective is to explicitly consider the endogenous liquidity dimension associated with order size. By reconstructing the open Limit Order Book of Deutsche Börse, changes in the tick-by-tick (ex-ante) frictionless return and actual return are modeled jointly. The risk related to the ex-ante liquidity premium is then quantified. Our model can be used to identify the impact of ex-ante liquidity risk on total risk, and to provide an estimation of the VaR for the actual return at a point in time. In our sample, liquidity risk can account for up to 32% of total risk depending on order size.

Suggested Citation

  • Dionne, Georges & Pacurar, Maria & Zhou, Xiaozhou, 2015. "Liquidity-adjusted Intraday Value at Risk modeling and risk management: An application to data from Deutsche Börse," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 202-219.
    • Handle: RePEc:eee:jbfina:v:59:y:2015:i:c:p:202-219
    DOI: 10.1016/j.jbankfin.2015.06.005
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    Cited by:

    1. Dionne, Georges & Zhou, Xiaozhou, 2016. "The Dynamics of Ex-ante High-Frequency Liquidity: An Empirical Analysis," Working Papers 15-5, HEC Montreal, Canada Research Chair in Risk Management.
    2. Helton Saulo & Jeremias Leão & Víctor Leiva & Robert G. Aykroyd, 2019. "Birnbaum–Saunders autoregressive conditional duration models applied to high-frequency financial data," Statistical Papers, Springer, vol. 60(5), pages 1605-1629, October.
    3. Theo Berger & Christina Uffmann, 2021. "Assessing liquidity‐adjusted risk forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1179-1189, November.
    4. Ramos, Henrique Pinto & Righi, Marcelo Brutti, 2020. "Liquidity, implied volatility and tail risk: A comparison of liquidity measures," International Review of Financial Analysis, Elsevier, vol. 69(C).
    5. Georges Dionne & Xiaozhou Zhou, 2020. "The dynamics of ex-ante weighted spread: an empirical analysis," Quantitative Finance, Taylor & Francis Journals, vol. 20(4), pages 593-617, April.
    6. Zhang, Heng-Guo & Su, Chi-Wei & Song, Yan & Qiu, Shuqi & Xiao, Ran & Su, Fei, 2017. "Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model," Economic Modelling, Elsevier, vol. 67(C), pages 355-367.

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    More about this item

    Keywords

    Liquidity-adjusted Intraday Value at Risk; Tick-by-tick data; Log-ACD-VARMA-MGARCH; Ex-ante liquidity premium; Limit Order Book;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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