基于真伪跳跃的~HAR~类波动预测模型研究
Research on the Forecasting Performance of the HAR-Type Model Based on True and False Jumps
-
摘要: 资产价格跳跃作为波动估计和预测的一大影响因素,得到了广泛关注. Andersen等将跳跃引入到HAR波动预测模型中,构建了HAR-CJ模型. 此后, 大量文献对跳跃进行了研究,但尚未研究真伪跳跃对波动预测的影响. 本文利用阈值技术, 对真伪跳跃进行区分,并将其引入到HAR波动建模框架中, 建立了HAR-CTFJ类模型及LHAR-CTFJ类模型,进一步研究了真伪跳跃对波动预测的影响. 结果表明:真实跳跃对波动预测具有显著影响, 而伪跳跃的影响并不显著.而且SPA检验结果表明, 与HAR-CJ模型相比,HAR-CTJ、LHAR-CTJ模型具有更好的波动预测能力.Abstract: Since the jump of an asset price has a strong effect on the estimate and forecast volatility, it has received widespread attention. Following HAR-CJ model introduced by Andersen et al, lots of works focus on this problem. In this paper, through a threshold technique, we distinguish the true and false jumps. Then we introduce two models, HAR-CTFJ model and LHAR-CTFJ model. Our result shows that the effect from the true jumps is significant while that from the false jumps is not. Moreover, the SPA test shows that our models (i.e. HAR-CTJ and LHAR-CTJ) are better than the classical HAR-CJ model in the prediction of volatility.