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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

期貨的當沖交易者是否為資訊交易者-臺灣期貨市場實證分析 / Are daytraders tend to be informed? Evidence from Taiwan

張家齊, Chang, Chia Chi Unknown Date (has links)
本論文分析臺灣期貨市場當沖交易的交易概況,探討不同類別投資人的獲利能力,以及影響當沖報酬的因素。研究結果顯示,台灣期貨市場的當沖交易非常活絡,平均當沖交易占總交易量的74.71%,而個別投資人為主要的參與者,占了當沖交易的66.68%。而先賣當沖可獲得比先買當沖更多的報酬,40.16%的先賣當沖,其當沖報酬可以超越當日的市場報酬。在交易獲利方面,整體而言,平均每筆當沖交易投資人會有-111.55的虧損,以投資人類別分類後可以發現,和股票市場有很大的不同,有52.23%的個別投資人可以在當沖交易中獲利,而投信只有21.04%。整體投資人績效方面,在考慮交易成本後,只有外資可以獲得正報酬,相較其他投資人具有資訊優勢,而自營商和投信的績效則比個別投資人差,並不具有資訊優勢。 交易量分析方面,平均而言,在研究期間內交易量小於10筆的投資人可以獲得較高的報酬,而交易量大於10000的投資人則有小幅度的虧損。在單獨分析波動度較大的交易日中,發現投資人在這些交易日中可以獲得比平常更多的報酬。我們進一步去分析在研究期間內績效表現較好的投資人,發現他們平均的交易量只有12.65筆,這類投資人並不傾向先買和先賣當沖,但是傾向一天只從事一種當沖交易,但先賣當沖的報酬仍然會多於先買當沖。這些投資人的報酬有集中於波動度大的交易日的趨勢,而交易時間比般人的交易時間要來的長,平均一筆交易為91到96分鐘,而整體投資人的交易時間約為48到50分鐘。 在迴歸模型中,我們發現市場報酬、交易量、時間、投資人過去績效對於當沖報酬都有顯著的解釋能力,然而,交易時間對於報酬卻是負向的關係。在解釋力方面,先賣當沖的解釋力較先買當沖好,而超額報酬模型的解釋力較當沖報酬模型好。 / When an investor buys and sells the future on the same day, he was made a day trade. This thesis studies the performance of day trades in the Taiwan Furtures Exchange(TAIEX) for the period between July 2006 and December 2006. Day trading accounts for 74.71% of total trading activities, of which individual investors account for 66.68% of the day trading volume. The results showed that sell and then buy day trading can earn more profits than buy then sell day trading, about 40.16% of the sell and then buy day trading can earn more profits than market return. In aggregate, day traders earn mean gross profits(before transaction costs) of $NT 199 per transaction, but net losses(after a reasonable accounting for transaction costs) of $NT 111 per transaction. After we categorize day traders, we find that about 52.23% of the indiviual investers can profit by day trading activities, and only foreign investors can earn sufficient profits to cover transaction costs. To analyze the performed better investers, we find that their average trading volume only have 12.65 within half year, they don’t tend to sell and then buy day trading or buy then sell day trading, but they tend to engage one kind of trading in one day, and sell and then buy day trading can earn more profits than buy then sell day trading. Their trading time is longer the others, about 91 to 96 minutes, other traders’ trading time only about 48-50 minute. Overall, the evidence suggests that market returns、trading volume、trading time and past profitablilty have a strong relation with subsequent returns, day traders who historically earned profits continue to earn profits. The statistical power of sell and then buy regression model is stronger than buy then sell regression model.
2

台灣股市波動與成交量關係的分量迴歸分析 / Quantile regression analysis of volatility-volume relation of Taiwan stock index

陳威愷, Chen, Wei-Kai Unknown Date (has links)
本文採用1989年10月2日至2017年4月12日的台灣股市加權指數日資料,並分為漲跌幅限制為7%的區間一,以及放寬為10%的區間二。接著使用〔(最高價-最低價)/昨日收盤價〕以及〔(收盤價-開盤價)/昨日收盤價〕兩個不同變數來衡量台灣股市單日的波動與報酬,然後也運用了週轉率、成交金額、5日均值比三種方法來估算股市成交量。藉此探討台灣股市波動與成交量的關係。使用的方法是分量迴歸模型,更細部的研究股市上漲或下跌時,每個分量之下不同的價量關係。 實證結果顯示,台灣股市普遍存在「價漲量增」與「價跌量增」的現象,且在波動越大的時候也就是分量尾端的部分,其關係更加的明顯。另外,使用三種變數來衡量成交量,在區間二大致得出相同的結論,但是區間一因為週轉率與成交金額的歷史走勢具有差異,所以結果也不盡相同。但是使用週轉率在歷史樣本中更具有相同的比較基礎,因此得出的結論也較一致,所以認為台灣股市仍是以「價漲量增」與「價跌量增」為普遍現象。 / This paper used the Taiwan stock market index daily data from October 2, 1989 to April 12, 2017, which divided into a range of 7% of the price limit, and a range of 10%. There are two different variables to measure the volatility and return: [(the highest price - the lowest price) / yesterday's closing price] and [(closing price - opening price) / yesterday's closing price], and three different variables: turnover, dealing amount, 5-day average ratio to estimate the stock market volume. The method used is quantile regression model, and that allows us to observe different relationship between volatility and volume under every single quantile. Empirical results show that there are two phenomena exist in the stock market of Taiwan: "rising values increase in volume" and "falling values increase in volume." In addition, the use of three variables to measure the volume, in the interval 2 roughly come to the same conclusion, but in the interval 1 because the historical trend of turnover rate and dealing amount are different, so the results are not the same. But the use of turnover in the history sample has the same comparison basis, so the conclusions are more consistent, so that the Taiwan stock market is still the " rising values increase in volume " falling values increase in volume" as a common phenomenon.

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