Dynamic Autoregressive Liquidity (DArLiQ)

Christian M. Hafner (), Oliver Linton and Linqi Wang
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Christian M. Hafner: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2023027, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

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.

Keywords: Kernel; Nonparametric estimation; Semiparametric model (search for similar items in EconPapers)
JEL-codes: C12 C14 (search for similar items in EconPapers)
Pages: 92
Date: 2023-11-30
Note: In: Journal of Business & Economic Statistics, 2023
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Related works:
Journal Article: Dynamic Autoregressive Liquidity (DArLiQ) (2024)
Working Paper: Dynamic Autoregressive Liquidity (DArLiQ) (2022)
Working Paper: Dynamic Autoregressive Liquidity (DArLiQ) (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2023027

DOI: 10.1080/07350015.2023.2238790

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