Publication: Impacts of news on stock's return volatility under different economic conditions: evidence from stock exchange of Thailand.
Issued Date
2006
Resource Type
Language
eng
Rights
Mahidol University
Rights Holder(s)
Chiang Mai University
Bibliographic Citation
Journal of Economics, Chiang Mai University. Vol. 1, (2006), 44-59
Suggested Citation
Jiranart Sutthirat Impacts of news on stock's return volatility under different economic conditions: evidence from stock exchange of Thailand.. Journal of Economics, Chiang Mai University. Vol. 1, (2006), 44-59. Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/9889
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Title
Impacts of news on stock's return volatility under different economic conditions: evidence from stock exchange of Thailand.
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Other Contributor(s)
Abstract
Not only is a well-specified model required in estimation of financial
market volatility, sample period used in such estimation is needed to
represent only one economic condition. This paper uses the ARCH-class
models to show that using symmetric model over sample period covering
more than one economic condition could mislead the volatility estimates.
This is because investors perceive differently between good and bad
news, which are factors determining volatility. During period full of
good news as Thai economic was stellar, another good-news would not
surprise investor as much as bad news. On the other hand, over period
market clouded by many bad news as in recession period, investors are
pessimistic and do not expect any good news. Using the day Thailand
floated the baht as change in economic condition, this paper finds
evidence suggesting that the impact of good and bad news are diverse
under different economic conditions. As a result, to predict market
volatility, practitioners and researchers need to be careful in selecting the
sample period by excluding sample under one economic condition from
another. Moreover, the volatility estimators used in such estimation
should be asymmetric in which difference between good and bad news is
captured. Otherwise, the volatility estimates could be misleading.