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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

指數調整效應:以滬深300 為例 / The Comprehensive Analyze of Index Composition Change in CSI300 Index

温智恒, Wun, Chi Hang Unknown Date (has links)
本篇論文以滬深300 指數調整前後期的異常報酬、影子成本、流動性、資訊不稱性及套利風險的變動觀察中國投資者的行為。本研究發現在調整後的短期間中中國股票的報酬與國外文獻的變動方向一致,調入股將上漲而調出股則下跌,但於長期則有十分明顯的相反傾向。本文將影子成本等四個變數加入作前後期變動的觀察。發現調整期前後影子成本、流動性、套利風險和資訊不對稱性的變動都與與文獻變動方向假設一致。最後本文把異常報酬作應變數,其餘各項作自變數去觀察四個變數影響報酬的程度和方向。回歸後發現只有流動性的影響符合前人以S&P500 作指標的研究,其他則是有著不一致的影響。本文認為這個現象與文獻中不同的原因是滬 深300 指數偏向於納入高估的股票而剔除低估的股票。滬深300 指數是以股票前一年的交易量大小作標準,這使得81%交易量為個人投資者提供的滬深300 指數偏向納入高估股票。這可能使得中國市場的指數調整效應與文獻並不一致。 / This paper empirically examines the differences of abnormal return, shadow cost, liquidity effect, information asymmetry and arbitrage risk during the composition change of CSI300 index to observe the behavior of investors in China market. Although this paper examines the short term return of adjusted stock change in the same direction as recent studies, added stocks increase and deleted stocks decrease, the long term return reverse. This paper also computes those four variables to observe their changes during the adjustment. The results show that the movements of these four variables are similar to the previous studies. To observe how these variables affect the return of the stocks, this paper computes a regression analysis with the cumulative abnormal return as the dependent variable. The results show that only the affection of liquidity matches the recent studies of S&P 500, when the others are not. The reason of this phenomenon maybe because of the CSI 300 index intends to include the overestimated stocks and exclude the underestimated stocks. The adjustment is determined by the past one year trading volume, which means that the market, with individual investors provided 81 % of trading volume, may possibly overestimate the included stocks. That maybe the reason why the influence of composition change is not similar to recent studies.

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