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

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

MoreLess

Year of publication:	2019
Authors:	Rzayev, Khaladdin
Other Persons:	Ibikunle, Gbenga (contributor)
Publisher:	[2019]: [S.l.] : SSRN
Subject:	Handelsvolumen der Börse \| Trading volume \| Theorie \| Theory \| Informationswert \| Information value \| Zustandsraummodell \| State space model

freely available

Full text |

More access options

doi.org

Check Google Scholar

In German libraries (KVK)

I need help

Which error do you want to report?

Report: URL of this record is broken

Please note: Sometimes more than one URL is available for a resource. Please click on "More Options" to display these URLs

Report: Addition of an URL to that resource

Please note: Sometimes more than one URL is available for a resource. Please click on "More Options" to display these URLs

Report: The language(s) of that resource is/are…

Please note: Required language not in the list? Please use comment field

Report: Addition of an identifier to that resource

Report: report typo

Report: Add statement

Report: Add keywords

Please use the commentary box to describe other errors

Would you like to receive a feedback?

Commentary

Please type the code from the image

For general questions please use this address.

Persistent link: https://www.econbiz.de/10012900185