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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

成交量是否可以預測報酬負偏態?─以Horn and Stein模型對臺灣上市公司實證為例

謝文凱, Hsieh,Wen Kai Unknown Date (has links)
市場上通常存在著跌幅大過漲幅的現象,更強烈的說法是,市場會在一夕之間崩盤,但卻不會在一夕之間漲上天,這造成了報酬負偏態的現象,而Horn and Stein的理論模型認為市場存在著兩群堅持己見、對股價有不同看法的投資人,再加上這群投資人面對放空的限制,是造成報酬負偏態的主要因素,若投資人之間看法差異愈大,則負偏態現象愈明顯。Chen, Horn and Stein根據他們的理論模型,他們將成交量定義週轉率,提出利用股票的週轉率來預測負偏態的概念,而本研究利用他們所提出的實證模型,應用在台灣股市上,並與美國實證結果相對照,實證結果顯示: 1. 在台灣,6個月期間週轉率愈高於平均的個股或大盤,下6個月報酬負偏態的情況會愈顯著,但其影響力和美國實證結果相對照小很多。 2. 市值愈大的股票,其報酬正偏態的情況愈顯著,這與美國的實證結果是相反的。 3. 依隨機泡沫模型理論,過去報酬率愈大的資產,愈有可能產生報酬負偏態的情況,而台灣的實證顯示,過去的報酬率無法有效的預測報酬負偏態,但美國的實證結果是成功的 / In stock market history, the very large movement are always decrease rather than increase. In other words, stock market tends to melt down, not melt up. This kind of return asymmetry causes the negative skewness of the stock return (either market portfolio or single stock). There are mainly three schools to explain mechanism behind the negative skewness of the return. They are leverage effect, assymmetry volatility, and stochastic bubble model. Chen, Horn and Stein states that stocks come through high turnover will later on go through the negative skewness of return. We use the empirical model proposed by Horn and Stein to inpsect if turnover can predict negative skewness of return in Taiwan stock market. we have three conclusions: 1. Negative skewness is greater in stocks and market portfolio that have experienced an increase in turnover rate relative to trend over the prior six month. This effect is smaller than that in America. 2. Negative skewness is greater in stocks that are larger in terms of market capitalization. This empirical evidence is contrary to those in America. 3. In view of stochastic bubble model, stocks that have high positive returns in the past are more likely to experience greater negative skewness in return. Empirical evidence in Taiwan shows that stochastic bubble does not apply to Taiwan stocks market, that is, past return in stocks can not predict the negative skewness in return.

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