A State-Space Modeling of the Information Content of Trading Volume

Journal of Financial Markets, Forthcoming

51 Pages Posted: 29 Jan 2018 Last revised: 4 Sep 2019

See all articles by Khaladdin Rzayev

Khaladdin Rzayev

University of Edinburgh; Koc University

Gbenga Ibikunle

University of Edinburgh; European Capital Markets Cooperative Research Centre

Date Written: January 22, 2018

Abstract

We propose a state-space modeling approach for decomposing trading volume into its liquidity-driven and information-driven components. Using a set of high-frequency S&P 500 stock data, we show that informed trading is linked with a reduction in volatility, illiquidity, and toxicity/adverse selection. We observe that our estimated informed trading component of volume is a statistically significant predictor of one-second stock returns; however, it is not a significant predictor of one-minute stock returns. This disparity is explained by high-frequency trading activity, which eliminates pricing inefficiencies at low latencies.

Keywords: trading volume, permanent component, transitory component, market quality, time series models, state-space modeling, high-frequency trading

JEL Classification: G12, G14, G15

Suggested Citation

Rzayev, Khaladdin and Ibikunle, Gbenga, A State-Space Modeling of the Information Content of Trading Volume (January 22, 2018). Journal of Financial Markets, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3106599 or http://dx.doi.org/10.2139/ssrn.3106599

Khaladdin Rzayev (Contact Author)

University of Edinburgh ( email )

Old College
South Bridge
Edinburgh, Scotland EH8 9JY
United Kingdom

Koc University ( email )

Rumelifeneri Yolu
34450 Sar?yer
Istanbul, 34450
Turkey

Gbenga Ibikunle

University of Edinburgh ( email )

Old College
South Bridge
Edinburgh, Scotland EH8 9JY
United Kingdom

European Capital Markets Cooperative Research Centre ( email )

Viale Pidaro 42
Pescara, 65121
Italy

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