The empirical relationship between intraday volatility and trading volume : evidence from Chinese Stocks

Gary G. Tian; Mingyuan Guo; Kevin James Daly; Tom J. Valentine; Craig Ellis

The empirical relationship between intraday volatility and trading volume : evidence from Chinese Stocks

Gary G. Tian, Mingyuan Guo, Kevin James Daly, Tom J. Valentine, Craig Ellis

Research output: Chapter in Book / Conference Paper › Conference Paper

Abstract

![CDATA[This paper investigates the empirical relationship between intraday volatility and trading volume. Our primary data set consists of 5-minute returns and trading volumes for the period between January 1, 2000 and December 31, 2002, for a subset of thirty-nine stocks from the Shanghai Stock Exchange 180 Index. Taking in consideration the excess kurtosis in high-frequency data, this study, unlike previous studies, estimated GARCH with generalized error distribution (GED) residuals. Similar to Rahman et al (2002), our results indicated that the GARCH (1,1) model best describes the volatility of intraday returns. Current volatility can be explained by past volatility that persists over time. Our results also show that the persistence in volatility remains in the intraday return series even after the lagged log-volume is included in the model as an explanatory variable.]]

Original language	English
Title of host publication	Proceedings of the 3rd Financial Markets Asia-Pacific Conference 2005
Publisher	University of Western Sydney
Number of pages	1
ISBN (Print)	1741080967
Publication status	Published - 2005
Event	Financial Markets Asia-Pacific Conference - Duration: 1 Jan 2005 → …

Conference

Conference	Financial Markets Asia-Pacific Conference
Period	1/01/05 → …

Keywords

stocks
intraday returns
trading volume
volatility
stock exchanges
China

Cite this

@inproceedings{cfc09d700e5c4551bedfda3fa0c80d8f,

title = "The empirical relationship between intraday volatility and trading volume : evidence from Chinese Stocks",

abstract = "![CDATA[This paper investigates the empirical relationship between intraday volatility and trading volume. Our primary data set consists of 5-minute returns and trading volumes for the period between January 1, 2000 and December 31, 2002, for a subset of thirty-nine stocks from the Shanghai Stock Exchange 180 Index. Taking in consideration the excess kurtosis in high-frequency data, this study, unlike previous studies, estimated GARCH with generalized error distribution (GED) residuals. Similar to Rahman et al (2002), our results indicated that the GARCH (1,1) model best describes the volatility of intraday returns. Current volatility can be explained by past volatility that persists over time. Our results also show that the persistence in volatility remains in the intraday return series even after the lagged log-volume is included in the model as an explanatory variable.]]",

keywords = "stocks, intraday returns, trading volume, volatility, stock exchanges, China",

author = "Tian, {Gary G.} and Mingyuan Guo and Daly, {Kevin James} and Valentine, {Tom J.} and Craig Ellis",

year = "2005",

language = "English",

isbn = "1741080967",

booktitle = "Proceedings of the 3rd Financial Markets Asia-Pacific Conference 2005",

publisher = "University of Western Sydney",

note = "Financial Markets Asia-Pacific Conference ; Conference date: 01-01-2005",

}

TY - GEN

T1 - The empirical relationship between intraday volatility and trading volume : evidence from Chinese Stocks

AU - Tian, Gary G.

AU - Guo, Mingyuan

AU - Daly, Kevin James

AU - Valentine, Tom J.

AU - Ellis, Craig

PY - 2005

Y1 - 2005

N2 - ![CDATA[This paper investigates the empirical relationship between intraday volatility and trading volume. Our primary data set consists of 5-minute returns and trading volumes for the period between January 1, 2000 and December 31, 2002, for a subset of thirty-nine stocks from the Shanghai Stock Exchange 180 Index. Taking in consideration the excess kurtosis in high-frequency data, this study, unlike previous studies, estimated GARCH with generalized error distribution (GED) residuals. Similar to Rahman et al (2002), our results indicated that the GARCH (1,1) model best describes the volatility of intraday returns. Current volatility can be explained by past volatility that persists over time. Our results also show that the persistence in volatility remains in the intraday return series even after the lagged log-volume is included in the model as an explanatory variable.]]

AB - ![CDATA[This paper investigates the empirical relationship between intraday volatility and trading volume. Our primary data set consists of 5-minute returns and trading volumes for the period between January 1, 2000 and December 31, 2002, for a subset of thirty-nine stocks from the Shanghai Stock Exchange 180 Index. Taking in consideration the excess kurtosis in high-frequency data, this study, unlike previous studies, estimated GARCH with generalized error distribution (GED) residuals. Similar to Rahman et al (2002), our results indicated that the GARCH (1,1) model best describes the volatility of intraday returns. Current volatility can be explained by past volatility that persists over time. Our results also show that the persistence in volatility remains in the intraday return series even after the lagged log-volume is included in the model as an explanatory variable.]]

KW - stocks

KW - intraday returns

KW - trading volume

KW - volatility

KW - stock exchanges

KW - China

UR - http://handle.uws.edu.au:8081/1959.7/44881

M3 - Conference Paper

SN - 1741080967

BT - Proceedings of the 3rd Financial Markets Asia-Pacific Conference 2005

PB - University of Western Sydney

T2 - Financial Markets Asia-Pacific Conference

Y2 - 1 January 2005

ER -

The empirical relationship between intraday volatility and trading volume : evidence from Chinese Stocks

Abstract

Conference

Keywords

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