K.-H. CHOI ET AL.

588

Table 5. Estimation results of GJR-GARCH and EGARCH

models with lagged trading volume.

GJR-GARCH (1,1) EGARCH (1,1)

0.037***

(0.008)

–0.107***

(0.014)

0.023***

(0.011)

0.158***

(0.019)

0.912***

(0.011)

0.980***

(0.004)

0.097***

(0.017)

–0.087***

(0.013)

–0.005

(0.003)

–0.001

(0.002)

12

s

Q 10.255

(0.594)

14.190***

[0.289]

ARCH (5) 1.032

(0.397)

1.529

[0.177]

Note: See Table 3.

uring the effects of information arrival to the market, when

trading volume is included.

6. Conclusions

We examined the persistence of return volatility on the

Korean Stock Market (KSM), both including and excluding

trading volume as a proxy for information flow, and con-

sidering lagged volume.

The main conclusions of this study are as follows. First,

the KSM index exhibits strong volatility persistence and

asymmetry. Second, the inclusion of contemporaneous trad-

ing volume in the GJR-GARCH and EGARCH models

results in a positive relationship between trading volume

and volatility. Third, when contemporaneous and lagged

trading volumes are included in the conditional variance

equation, the former is positively correlated with volatil-

ity but the latter is not. Thus, trading volume affects the

flow of information, supporting the validity of MDH.

Finally, the asymmetric effect of bad news on volatility is

higher when contemporaneous trading volume is included,

although market shocks, whether positive or negative, have

similar effects on conditional volatility. Thus, we conclude

that trading volume is a useful tool for predicting the

volatility dynamics of the KSM.

7. Acknowledgements

This work was supported by the National Research Foun-

dation of Korea Grant, funded by the Korean Govern-

ment (NRF-2011-330-B00044).

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