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題名：臺股現貨與期貨之異常現象實證
作者：劉映興
作者(外文)：Ying-Sing Liu
校院名稱：雲林科技大學
系所名稱：管理研究所博士班
指導教授：楊踐為
學位類別：博士
出版日期：2009
主題關鍵詞：時間變動的資產定價；異常現象；交易稅；股票市場；股價指數期貨；效率市場假說；混合分配假說；彈性傅立葉形式；stock market；stock index futures；EMH；MDH；FFF；transaction tax；anomalies；time-varying asset pricing
原始連結：連回原系統網址new window
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本論文之研製共分為五個議題，其中包含：時間趨勢及季節性、降稅、週轉率、公司規模及帳面價值/市場價值比等效應的相關研究。以台灣期貨市場中的台指期(TX)、電子期(TE)和金融期(TF)近月契約之日與日內5分鐘的交易資料；及股票集中市場的普通股之月交易資料與加權股價指數(TAIEX)之日和月的交易資料為研究對象。同時，期貨市場的研究期間為2002.2.1.至2007.6.31.止，而股票市場則是從1982.6.到2006.2.為止。
在期貨市場驗證部分，係以混合分配假說(mixture of distributions hypothesis; MDH)作為探討價量關係的理論依據，同時運用彈性傅立葉形式(Flexible Fourier Form; FFF)檢定交易量的時間趨勢及季節性，並利用TGARCH-cum-volume模型探討價量關係。其次，又以VAR-cum-FFF模型探討報酬波動與交易量的因果關係，藉此證明報酬波動也會存在時間趨勢及季節性。最後再以FFF，以及報酬波動與交易活動所組成的兩結構方程式，檢定調降期貨交易稅對於報酬波動與交易活動間的影響。結果發現降稅會使期貨的投機性交易活動上升，而期貨的交易活動明顯地與時間趨勢或季節性因素有關。
在股票市場驗證部分，我們分別以傳統的市場模型、時間變動的市場模型及雙元時間變動貝它值之市場模型，檢定週轉率投資組合的系統風險之時間變動性與多空市場月的差異。此外，也以Fama and French (1993)的三因子模型和雙元時間變動的三因子之GARCH模型來探討三因子的貝它值，以檢證其在多頭或空頭月中對於條件市場波動變動的靈敏度(sensitivity)。經實證後發現台股具有週轉率現象、反公司規模及反帳面價值/市場價值比效應等異象(anomailies)。同時，較高週轉率之投資組合的時間變動係數在空頭月中是顯著存在的；而最高週轉率之投資組合的市場貝它值，其在多、空市場月中是存有不對稱性的。最後，也支持三因子的時間變動貝它值是存在的。
This study emphasizes on the effect correlation of five issues: time trend and seasonal effect, transaction tax reduction, turnover rate, firm-size, and book-to-market equity ratio. We will adopt the empirical data of Taiwan futures market covering the recently entered contracts of Taiwan Stock Index futures (TX), Electronic Sector Index futures (TE) and Finance Sector Index futures (TF) from February 1, 2002 to June 31, 2007 by observing the daily and intraday 5-minute interval trading data. Meanwhile, the common stock monthly trading data, TAIEX daily and monthly trading data from Taiwan Stock Exchange Market listed companies, during the period from June of 1982 to February of 2006 are also used.
The mixture of distributions hypothesis (MDH), an important theory in the futures market, was proposed in discussion of the relationship between the futures return volatility and the trading volume. First, we employ the Flexible Fourier Form (FFF) to examine the time trend and seasonal effect of trading volume, and adopts TGARCH-cum-volume model to test the volatility-volume relation. Second, we prove that the return volatility also contains the time trend and seasonal factors. We employ the VAR-cum-FFF model to discuss Granger causality of daily return volatility and trading volume of the index futures at Taiwan futures market. Furthermore, we also apply FFF to the return volatility and volume activity in a bivariate equation structural framework to test the effect of transaction tax reduction for the return volatility and trading activity. Major empirical results indicate that tax reduction has a boosting effect on speculative trading activity, while futures return volatility has a significant correlation to time trend and seasonal factors.
In the stock market, we employ Schwert and Sequin''s (1990) market model and dual time-varying beta market model to test the fact that the systematic risks of long-term turnover-sorted portfolios are non-stationary. We also adopts the Fama and French’s (1993) three-factor model and the dual time-varying beta’s three-factor- GARCH(1,1) model to examine the sensitivity and response orientation of three- factor betas of style portfolios to the sum of intra-monthly conditional market volatility in the bull and bear market months. Major empirical results indicate that there are positive turnover-size effect, reverse firm-size effect and reverse book-to- market effect in Taiwan Stock Market. Furthermore, only the constant market beta of the highest turnover-sorted portfolio appears to be asymmetric in bull and bear market months. The time-varying coefficient of higher turnover-sorted portfolios is significant in bear market months. Further, three-factor’s betas are sensitive to the sum of intra-monthly conditional market volatility, and the time-varying betas can explain part of the average return for most style portfolios, and finally the conditional heteroscedasticity does exist in the residual returns of the model.
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