English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 56450/90276 (63%)
造訪人次 : 11706453      線上人數 : 56
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/73974


    題名: 股票與權證隱含價格發現關係
    其他題名: A study of price discovery between stocks and warrants
    作者: 戴育衡;Tai, Yu-Heng
    貢獻者: 淡江大學財務金融學系碩士班
    邱建良;Chiu, Chien-Liang
    關鍵詞: 權證;價格發現;VAR模型;warrants;price discovery;VAR Model
    日期: 2011
    上傳時間: 2011-12-28 17:42:30 (UTC+8)
    摘要: 本文使用高頻日內資料探討權證與現貨市場間的價格發現關係。利用樣本期間為2007年10月至2008年10月份的現貨與權證的交易資料。上述權證的標的資產與現貨相同。本文將在確定兩個市場間是否具有共整合(cointegration)關係之後來決定本次研究該採用向量誤差修正模型(vector error correction model, VECM)或者向量自我回歸模型(VAR),最後藉由衝擊反應函數以及變異數分解來探討市場間相互影響的程度。經由實證結果可發現,現貨的領導地位較強於權證。而且兩個市場對於對方幾乎沒有解釋能力。這可能與台股的權證市場尚未發展成熟有關。雖然低交易成本的價格發現能力越強,但交易量也是影響的重要因素之一。
    This thesis aims to investigate the price discovery between stocks and warrants by analyzing the high-frequency data from Oct. 2007 to Oct. 2008. The sample data were dated between Oct. 2007 and Oct. 2008. These warrants’ underlying assets are the same as stocks’. Through this thesis, the existence of the cointegration between both markets will be examined to decide rather VAR or VECM model should be applied. In the end we will use Impulse Response Function and Forecast Error Variance Decomposition to investigate how these two markets influence each other. The conclusion reveals that spots donate warrants and neither of both has explaining ability over the other. This might be related to the immaturity of warrant market in Taiwan. Although the securities with lower transaction cost have stronger price discovery, the volume is also one of the important factors.
    顯示於類別:[財務金融學系暨研究所] 學位論文

    文件中的檔案:

    檔案 大小格式瀏覽次數
    index.html0KbHTML122檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋