Revisiting the puzzle of jumps in volatility forecasting: The new insights of high-frequency jump intensity
JOURNAL OF FUTURES MARKETS(2024)
摘要
Motivated by the puzzling null impact of high-frequency-based jumps on future volatility, this paper exploits the rich information content in high-frequency jump intensity with a mark structure under the heterogeneous autoregressive framework. Our proposed model shows that harnessing jump intensity information from the marked Hawkes process leads to significantly superior in-sample fit and out-of-sample forecasting accuracy. In addition to statistical significance evidence, we also illustrate the economic significance in terms of trading efficiency. Our findings hold for a variety of competing models and under different market conditions, underlying the robustness of our results.
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关键词
HAR model,high-frequency data,jump intensity,marked Hawkes process,volatility forecasting
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