標題: 考慮交易量時高頻率股市報酬率波動性之研究
Volatility models for high frequency data in Taiwan stock market after considering trading volume
作者: 李騰正
Teng-Cheng Lee
王克陸
包曉天
Kenluh Wang
Hsiao-Tien Pao
經營管理研究所
關鍵字: 高頻率資料;波動性;成交量;不對稱效應;效應;high frequency data;Volatility;trading volume;asymmetric property;effect
公開日期: 2000
摘要: 本研究之目的在探討台灣加權股價指數高頻率資料之波動性模型,尤其是成交量對波動性的影響。使用1999年11月、12月之每分鐘加權指數資料,採取GARCH相關模型並考量成交量變數,結果發現GARCH相關模型在加入成交量後確實能對台灣加權指數的波動性行為有較佳的解釋。成交量增加時會增加股市的波動性,而加入成交量變數後並不會對於GARCH效應有所抵銷。此外在對於非對稱性模型的探討中,發現台灣股市高頻率資料其正向的衝擊較負向的衝擊對於股市波動性的影響較大,此和一般認為負向的衝擊較大的結果不同。 當進一步將波動性模型同時考量成交量、成交量及報酬率的正負向對於波動性非對稱的性質時,發現正向的衝擊或相對成交量擴大時,均會造成台股指數的波動性叢聚現象的波動性增大,而當二情況同時存在時波動性叢聚的波動性增大的現象會更明顯。
The purpose of this research is to study the volatility model of high frequency stock index in Taiwan, especially with consideration of trading volume. We found that the GARCH model with trading volume had better explanation for high frequency data in Taiwan stock market. The trading volume increases the stock volatility and does not offset the GARCH effect. For the asymmetric property, we found the positive side has more influence on the volatility than the negative side. Further investigation indicates that the positive impulse or relative trading volume will make the clustering effect more significant.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT890457044
http://hdl.handle.net/11536/67431
Appears in Collections:Thesis