淡江大學機構典藏:Item 987654321/99549
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62797/95867 (66%)
造访人次 : 3750814      在线人数 : 469
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/99549


    题名: The predictive power of volatility models: evidence from the ETF market
    作者: Duan Chang-Wen;Lin, Jung-Chu
    关键词: volatility model;implied volatility;volatility index;incremental information.
    日期: 2014-06-17
    上传时间: 2014-11-25 15:25:31 (UTC+8)
    摘要: This study uses exchange-traded fund (ETF) data to investigate the ability of the time-series volatility model, the implied volatility model, and the intraday return volatility model to forecast return volatility. Among various ETFs, we adopt NASDAQ 100 Index Tracking Stock (QQQ) as the sample because it has corresponding volatility index (VIX) issued which is necessary. The results show that all volatility models applied in this study can reliably forecast volatility. The Glosten-Jagannathan-Runkle GARCH model is superior to the GARCH model, implying that the return volatility of QQQ is asymmetric. Among the added incremental information, QQQ Volatility Index (QQV) of the American Stock Exchange has better ability in forecasting the return volatility of QQQ, followed by the NASDAQ Volatility Index (VXN) of the Chicago Board Options Exchange, and then by the intraday return volatility. The probable reason is that the turnover of QQQ options is higher than that of the NASDAQ 100 Index Options (NDX) and causes QQV to contain substantially more information than VXN and to predict volatility better. We also find the predictive power of the time-series GARCH model is weaker than that of the volatility model with QQV embedded as incremental information. Since QQQ, as an ETF, has diversified its non-systematic risks, the GARCH model using non-systematic risk information to predict volatility is inevitably worse than that using implied volatility. Identical results are achieved when examining out-of-sample forecasting performance.
    關聯: Investment Management and Financial Innovations 11(2), p.100-110
    显示于类别:[財務金融學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    IMFI_2_2014_Jung-Chu Lin_201411.pdfpaper307KbAdobe PDF643检视/开启
    index.html0KbHTML114检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

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