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dc.contributor.author郭念青en_US
dc.contributor.authorNien-Ching Kuoen_US
dc.contributor.author周雨田en_US
dc.contributor.authorRay Yeu-Tien Chouen_US
dc.date.accessioned2014-12-12T01:18:19Z-
dc.date.available2014-12-12T01:18:19Z-
dc.date.issued2007en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT009537521en_US
dc.identifier.urihttp://hdl.handle.net/11536/39303-
dc.description.abstract我們使用GJR-GARCH和七種情緒指標來檢驗De Long等(1990a)所提出雜訊交易者風險在條件波動和超額報酬上的影響。我們發現情緒是一個解釋股票超額報酬和條件波動很顯著的因子。情緒的變化量對於條件波動和超額報酬有很顯著的影響。PCO、AAII、II和IPON可以用來預測未來的報酬,而ARMS、PCO、PCV、AAII和IPON可以預測報酬波動。看漲的情緒會使得條件波動向下修正,而看跌的情緒則會使波動向上爬升。此外,我們使用Component GARCH檢測雜訊交易者風險在長期和短期的情形。我們發現情緒在短期波動的影響比長期波動來的大且顯著。zh_TW
dc.description.abstractUsing seven sentiment indices, we employ a GJR-GARCH specification to test the impact of noise trader risk on both the formation of conditional volatility and expected return as suggested by De Long et al. (1990a). Our main findings suggest that sentiment is a significant factor in explaining equity excess returns and conditional volatility. We find that the magnitude of shifts in sentiment has a significant impact on the formation of conditional volatility of returns and expected returns. PCO, AAII, II, and IPON can be used to forecast the future returns and ARMS, PCO, PCV, AAII, and IPON are good proxy to forecast the volatility of returns. Bullish (bearish) shifts in sentiment lead to downward (upward) revisions in the volatility of returns. In addition, we try to use the component GARCH to divide the noise trader risk into two components which are the transitory component and the permanent component. We find that effect of sentiment in the transitory component is larger and more significant than in the permanent component.en_US
dc.language.isoen_USen_US
dc.subject情緒zh_TW
dc.subject雜訊交易者風險zh_TW
dc.subjectGJR-GARCHzh_TW
dc.subjectComponent GARCHzh_TW
dc.subjectSentimenten_US
dc.subjectNoise trader risken_US
dc.subjectGJR-GARCHen_US
dc.subjectComponent GARCHen_US
dc.title波動成分情緒指標與雜訊交易者風險zh_TW
dc.titleVolatility components sentiment indices and noise trader risken_US
dc.typeThesisen_US
dc.contributor.department經營管理研究所zh_TW
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