Gold as a vital hedging asset plays increasing critical roles in risk management during turmoil macroeconomic environments. For the massive and indistinct impactors of gold price volatility, this paper tries to investigate whether the short- and long-term asymmetry, extreme observations, and jump components in past gold volatility help to obtain higher forecasting accuracy in future volatility from both in-sample and out-of-sample perspectives. A variety of evaluation methods are utilized to compare the performances of GARCH-MIDAS models incorporating these volatility components and the standard ones without them. The results of in-sample estimation show first that all the short-term and long-term asymmetry, extreme observations, and jump components have significantly impact on gold volatility. The evaluation results of out-of-sample forecasts suggest that the forecasting accuracy of gold volatility can be significantly improved by most of the extended GARCH-MIDAS models including asymmetry, extreme observations, and jump components. The model including short-term jump intensity and the model with both long-term asymmetry and long-term leverage effects have better forecasting performances than other models for gold volatility, especially for regular volatility. Moreover, GARCH-MIDAS models incorporating long-term leverage and long-term jump have better performances in forecasting accuracy of extreme gold volatility.

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预测常规和极端金价波动：不对称、极端事件和跳跃的作用

在动荡的宏观经济环境中，黄金作为一种重要的对冲资产，在风险管理中发挥着越来越重要的作用。对于金价波动的巨大且模糊的影响因素，本文试图研究过去黄金波动中的短期和长期不对称性、极端观察和跳跃分量是否有助于从样本内获得更高的未来波动率预测精度。和样本外观点。各种评估方法被用来比较包含这些波动性成分的 GARCH-MIDAS 模型和没有它们的标准模型的性能。样本内估计的结果首先表明，所有短期和长期的不对称性、极端观察和跳跃分量对黄金波动率都有显着影响。样本外预测的评估结果表明，大多数扩展的 GARCH-MIDAS 模型包括不对称性、极端观测值和跳跃分量，都可以显着提高黄金波动率的预测精度。包含短期跳跃强度的模型以及同时具有长期不对称性和长期杠杆效应的模型对黄金波动率，尤其是常规波动率的预测性能优于其他模型。此外，结合长期杠杆和长期跳跃的GARCH-MIDAS模型在预测黄金极端波动的准确性方面有更好的表现。包含短期跳跃强度的模型以及同时具有长期不对称性和长期杠杆效应的模型对黄金波动率，尤其是常规波动率的预测性能优于其他模型。此外，结合长期杠杆和长期跳跃的 GARCH-MIDAS 模型在预测黄金极端波动的准确性方面有更好的表现。包含短期跳跃强度的模型以及同时具有长期不对称性和长期杠杆效应的模型对黄金波动率，尤其是常规波动率的预测性能优于其他模型。此外，结合长期杠杆和长期跳跃的GARCH-MIDAS模型在预测黄金极端波动的准确性方面有更好的表现。