High frequency market microstructure noise estimates and liquidity measures

By Yacine Aït-Sahalia, Jialin Yu. 2009

166 citations recorded by the source corpus.

Using recent advances in the econometrics literature, we disentangle from high frequency observations on the transaction prices of a large sample of NYSE stocks a fundamental component and a microstructure noise component. We then relate these statistical measurements of market microstructure noise to observable characteristics of the underlying stocks and, in particular, to different financial measures of their liquidity. We find that more liquid stocks based on financial characteristics have lower noise and noise-to-signal ratio measured from their high frequency returns. We then examine whether there exists a common, market-wide, factor in high frequency stock-level measurements of noise, and whether that factor is priced in asset returns.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/7cdbb7d6e915e96746dda4b9fc415f4debc6b9ff

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Citations in the corpus

Does Realized Skewness Predict the Cross-Section of Equity Returns? (2015, background): “These parameter values are similar to those employed by Ait-Sahalia and Yu (2009).”
Quasi-maximum likelihood estimation of volatility with high frequency data (2010, unknown): “All errors are mine.”
Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes (2015, unknown): “Numerous measures of market liquidity exist in the literature (see Hautsch and Podolskij (2013); At-Sahalia and Yu (2009), for examples).”
Is the diurnal pattern sufficient to explain intraday variation in volatility? A nonparametric assessment (2017, unknown): “A¨ıt-Sahalia and Yu, 2009).”