Measuring liquidity with return volatility: An analytical approach based on heavy-tailed Censored-GARCH model

Wandi Zhao, Yang Gao and Mingjin Wang

The North American Journal of Economics and Finance, 2022, vol. 62, issue C

Abstract: The measurement of liquidity based on low-frequency data is a crucial issue in the financial market microstructure literature. This paper extends the commonly used LOT liquidity model by incorporating the characterization of the volatility dynamics and distributional properties of return series, thereby significantly improving both the goodness-of-fit of liquidity model and the estimation performance of the existing low-frequency liquidity measures. The new models, which have a special form of heavy-tailed Censored-GARCH model, have challenges in estimation. We then provide an approximate maximum likelihood estimation method to circumvent this problem. A real data analysis is conducted to evaluate the performance of the new liquidity measures. The results show overwhelming evidence that our new measures have advantages over the existing measures in both estimation error and correlation coefficient with high-frequency bid-ask spread. The robustness check analysis further illustrates that the advantages of our new measures are stable across different stock industries and different turnover levels.

Keywords: Liquidity; LOT Model; GARCH Model; t-Distribution (search for similar items in EconPapers)
JEL-codes: C16 C24 G12 G14 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:62:y:2022:i:c:s1062940822001164

DOI: 10.1016/j.najef.2022.101774

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