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为提高波动估计的准确性,针对修正因子的不足,改进了多重分形波动率测度,建立了反映多重分形波动特征的ARFIMA模型和HAR模型.样本内拟合实证表明:考虑杠杆效应的多重分形波动建模明显提高模型拟合程度.样本外预测实证表明:基于多重分形的波动模型是比GARCH类模型更有效的预测模型.两方面实证表明考虑杠杆效应的多重分形波动建模更能有效地刻画金融市场波动复杂性.
In order to improve the accuracy of the volatility estimation, aiming at the deficiency of the correction factor, the multifractal volatility measure is improved and an ARFIMA model and a HAR model reflecting the characteristics of multifractal fluctuation are established. The sample fitting shows that the multifractal fluctuation Modeling significantly improves the fitting degree of the model.The empirical results show that the volatility model based on multifractal is a more effective prediction model than the GARCH model.It is empirically proved that the multifractal fluctuation model considering the leverage effect can be more effectively described Financial market volatility complexity.