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Dynamic Autoregressive Liquidity (DArLiQ)

Author

Listed:
  • Hafner, Christian M.

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Linton, Oliver B.
  • Wang, Linqi

Abstract

We introduce a new class of semiparametric dynamic autoregressive models for the Amihud illiquidity measure, which captures both the long-run trend in the illiquidity series with a nonparametric component and the short-run dynamics with an autoregressive component. We develop a generalized method of moments (GMM) estimator based on conditional moment restrictions and an efficient semiparametric maximum likelihood (ML) estimator based on an iid assumption. We derive large sample properties for our estimators. Finally, we demonstrate the model fitting performance and its empirical relevance on an application. We investigate how the different components of the illiquidity process obtained from our model relate to the stock market risk premium using data on the S&P 500 stock market index.

Suggested Citation

  • Hafner, Christian M. & Linton, Oliver B. & Wang, Linqi, 2023. "Dynamic Autoregressive Liquidity (DArLiQ)," LIDAM Reprints ISBA 2023027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2023027
    DOI: https://doi.org/10.1080/07350015.2023.2238790
    Note: In: Journal of Business & Economic Statistics, 2023
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    More about this item

    Keywords

    Kernel ; Nonparametric estimation ; Semiparametric model;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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