中大機構典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/51717
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 80990/80990 (100%)
造訪人次 : 41777032      線上人數 : 2050
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU 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://ir.lib.ncu.edu.tw/handle/987654321/51717


    題名: Random Aggregation with Applications in High-Frequency Finance
    作者: Tsay,RS;Yeh,JH
    貢獻者: 財務金融學系
    關鍵詞: MARKET;RISK
    日期: 2011
    上傳時間: 2012-03-27 19:03:29 (UTC+8)
    出版者: 國立中央大學
    摘要: In this paper we consider properties of random aggregation in time series analysis. For application, we focus on the problem of estimating the high-frequency beta of an asset return when the returns are subject to the effects of market microstructure. Specifically, we study the correlation between intraday log returns of two assets. Our investigation starts with the effect of non-synchronous trading on intraday log returns when the underlying return series follows a stationary time series model. This is a random aggregation problem in time series analysis. We also study the effect of non-synchronous trading on the covariance of two asset returns. To overcome the impact of non-synchronous trading, we use Markov chain Monte Carlo methods to recover the underlying log return series based on the observed intraday data. We then define a high-frequency beta based on the recovered log return series and propose an efficient method to estimate the measure. We apply the proposed analysis to many mid- or small-cap stocks using the Trade and Quote Data of the New York Stock Exchange, and discuss implications of the results obtained. Copyright (C) 2010 John Wiley & Sons, Ltd.
    關聯: JOURNAL OF FORECASTING
    顯示於類別:[財務金融學系] 期刊論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML625檢視/開啟


    在NCUIR中所有的資料項目都受到原著作權保護.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明