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Forecasting Long-Memory Volatility Of The Australian Futures Market

Author

Listed:
  • Seong-Min Yoon

    (Pusan National University)

  • Sang Hoon Kang

    (Gyeongsang National University)

  • Sung-Jin Cho

    (Pukyong National University)

  • Gyun Woo

    (Pusan National University)

  • Jeong-Hoon Ji

    (Pusan National University)

Abstract

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.

Suggested Citation

  • Seong-Min Yoon & Sang Hoon Kang & Sung-Jin Cho & Gyun Woo & Jeong-Hoon Ji, 2009. "Forecasting Long-Memory Volatility Of The Australian Futures Market," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 12(12(541)(s), pages 763-770, December.
    • Handle: RePEc:agr:journl:v:12(541)(supplement):y:2009:i:12(541)(supplement):p:763-770
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