中国科学院数学与系统科学研究院期刊网

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高频数据环境下我国股票市场的波动率预测——基于机器学习和HAR模型的融合研究
杨科, 张洲深, 田凤平
计量经济学报, 2023, 3(3): 886-904.   DOI: 10.12012/CJoE2022-0067

MSE MAE $ R^2 $ EV
HAR 103 154 208 246
(0.000) (0.000) (0.001) (0.000)
HAR-J 335 392 371 287
(0.001) (0.001) (0.001) (0.001)
Lasso-HAR 796 874 857 904
(0.001) (0.001) (0.001) (0.002)
Lasso-HAR-J 1359 1281 1302 1115
(0.003) (0.008) (0.005) (0.005)
Lasso-NN 1024 1105 986 929
(0.001) (0.002) (0.002) (0.002)
Lasso-NN-J 4592 4124 4035 4033
(0.941) (0.934) (0.901) (0.900)
RF-HAR 788 892 905 893
(0.001) (0.001) (0.001) (0.002)
RF-HAR-J 957 1032 1237 1189
(0.003) (0.002) (0.003) (0.001)
RF-NN 2411 2856 2903 2844
(0.485) (0.405) (0.358) (0.372)
RF-NN-J 3281 3397 2679 3048
(0.794) (0.816) (0.727) (0.715)
HARQ-RV-SJ 2015 2189 2614 2149
(0.385) (0.326) (0.318) (0.283)
HARQF-RV-CJ 2024 2207 2960 2367
(0.396) (0.310) (0.289) (0.307)
TVS-HAR 3495 3102 3369 3206
(0.873) (0.815) (0.796) (0.810)
GARCH 0 0 0 0
(0.000) (0.000) (0.000) (0.000)
TARCH 0 0 0 0
(0.000) (0.000) (0.000) (0.000)
GJR 10 0 0 21
(0.000) (0.000) (0.000) (0.000)
EGARCH 0 0 0 0
(0.000) (0.000) (0.000) (0.000)
表7 随机抽样模拟检验结果
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