Review of Quantitative Finance and Accounting, 19: 155–180, 2002
2002 Kluwer Academic Publishers. Manufactured in The Netherlands.
Intraday Return Volatility Process: Evidence
from NASDAQ Stocks
School of Business Administration, Portland State University
School of Business, Rutgers University
KIAN PING ANG
Treasury Derivatives Trading, Overseas Union Bank, Singapore
Abstract. This paper presents a comprehensive analysis of the distributional and time-series properties of in-
traday returns. The purpose is to determine whether a GARCH model that allows for time varying variance in
a process can adequately represent intraday return volatility. Our primary data set consists of 5-minute returns,
trading volumes, and bid-ask spreads during the period January 1, 1999 through March 31, 1999, for a subset
of thirty stocks from the NASDAQ 100 Index. Our results indicate that the GARCH(1,1) model best describes
the volatility of intraday returns. Current volatility can be explained by past volatility that tends to persist over
time. These results are consistent with those of Akgiray (1989) who estimates volatility using the various ARCH
and GARCH speciﬁcations and ﬁnds the GARCH(1,1) model performs the best. We add volume as an additional
explanatory variable in the GARCH model to examine if volume can capture the GARCH effects. Consistent with
results of Najand and Yung (1991) and Foster (1995) and contrary to those of Lamoureux and Lastrapes (1990),
our results show that the persistence in volatility remains in intraday return series even after volume is included
in the model as an explanatory variable. We then substitute bid-ask spread for volume in the conditional volatility
equation to examine if the latter can capture the GARCH effects. The results show that the GARCH effects remain
strongly signiﬁcant for many of the securities after the introduction of bid-ask spread. Consistent with results of
Antoniou, Homes and Priestley (1998), intraday returns also exhibit signiﬁcant asymmetric responses of volatility
to ﬂow of information into the market.
Key words: trading volume, return volatility, GARCH, assymetric
JEL Classiﬁcation: G12, G14
The dynamics of the intraday return volatility process has important implication for market
microstructure research. This is because news arrivals and the resolution of their infor-
mational impact are directly related to the dynamics of the return volatility process. More
The opinions and conclusions offered in this study do not necessarily represent those of Overseas Union Bank.
Nanyang Business School at Nanyang Tech University, Singapore, provided partial funding for this research.
Address correspondence to: School of Business Administration, Portland State University, P. O. Box 751, Portland,
OR 97207-0751. (503) 725-3715 (Voice), (503) 725-5850 (Fax).