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Beyond the HAR: A New Benchmark for Volatility Forecasting

Author

Listed:
  • Shuping Shi

    (Macquarie University)

  • Jun Yu

    (University of Macau)

  • Chen Zhang

    (Sun Yat-sen University)

Abstract

Continuous time models provide a stronger benchmark for realized volatility forecasting than the discrete time models standard in empirical finance. Using 111 U.S. equities and ETFs, we compare continuous time fractional processes, ARFIMA, and HAR models on a common footing. Three families perform similarly at the daily horizon but separate at longer horizons, where continuous time models lead statistically and economically. The ranking reflects how each model balances recent volatility against its long run level. The continuous time advantage grows with volatility persistence and diminishes as jumps account for more variation.

Suggested Citation

  • Shuping Shi & Jun Yu & Chen Zhang, 2026. "Beyond the HAR: A New Benchmark for Volatility Forecasting," Working Papers 202648, University of Macau, Faculty of Business Administration.
    • Handle: RePEc:boa:wpaper:202648
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