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  • 标题:FORECASTING LONG-MEMORY VOLATILITY OF THE AUSTRALIAN FUTURES MARKET
  • 本地全文:下载
  • 作者:Yoon, Seong-Min ; Kang, Sang Hoon ; Cho, Sung-Jin
  • 期刊名称:Theoretical and Applied Economics
  • 印刷版ISSN:1841-8678
  • 电子版ISSN:1844-0029
  • 出版年度:2009
  • 卷号:12(541)(supplement)
  • 期号:12(541)(supplement)
  • 页码:763-770
  • 出版社:Asociatia Generala a Economistilor din Romania - AGER
  • 摘要:Accurate forecasting of volatility is of considerable interest in financial volatility research, particularly in regard to portfolio allocation, option pricing, and risk management. This article investigates and compares the ability to conduct one-day-ahead volatility forecasts in the Australian index futures market by three volatility models: GARCH, IGARCH and FIGARCH. The FIGARCH model better captured the long-memory property than did the GARCH and IGARCH models. Additionally, the FIGARCH model provided superior performance in one-day-ahead volatility forecasts. As discussed in this paper, the FIGARCH model should prove useful in forecasting the long-memory property in the Australian index futures market.
  • 关键词:diebold-mariano test; forecasting ability; long memory; lo's modified R/S analysis; SPI futures.
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