Research on the Influence of Volatility of International Energy Commodity Futures Market on CPI in China

Table 4

Exchange rate: the goodness of fit and in-sample and out-of-sample prediction accuracy at different lag orders.

Model	Index	Lag order
		15	20	25	30	35	40
Beta-MIDAS	R^2	0.8617	0.8621	0.8619	0.8619	0.8664	0.8668
	RMSE	0.4903	0.4863	0.4873	0.4877	0.5004	0.4938
	MSFE	0.2404	0.2364	0.2375	0.2378	0.2504	0.2439
	DMSFE	0.0770	0.0778	0.0779	0.0777	0.0797	0.0793
Beta-nonzero-MIDAS	R^2	0.8616	0.8617	0.8617	0.8617	0.8663	0.8664
	RMSE	0.4938	0.4916	0.4907	0.4896	0.5018	0.5007
	MSFE	0.2438	0.2417	0.2408	0.2397	0.2518	0.2507
	DMSFE	0.0781	0.0780	0.0779	0.0778	0.0798	0.0798
Exp Almon-MIDAS	R^2	0.8618	0.8620	0.8619	0.8620	0.8666	0.8668
	RMSE	0.4887	0.4875	0.4871	0.4837	0.4972	0.4929
	MSFE	0.2388	0.2377	0.2373	0.2340	0.2472	0.2430
	DMSFE	0.0770	0.0782	0.0780	0.0778	0.0803	0.0793
U-MIDAS	R^2	0.8810	0.8843	0.8918	0.9054	0.9230	0.9302
	RMSE	0.5246	0.4669	0.5415	0.7292	0.7439	0.8527
	MSFE	0.2752	0.2180	0.2932	0.5318	0.5534	0.7271
	DMSFE	0.1430	0.1210	0.1751	0.3701	0.3777	0.4827
Stepfun-MIDAS	R^2	0.8627	0.8641	0.8661	0.8700	0.8813	0.8829
	RMSE	0.4763	0.4839	0.4977	0.5728	0.6078	0.6080
	MSFE	0.2268	0.2342	0.2477	0.3281	0.3694	0.3696
	DMSFE	0.0736	0.0996	0.0990	0.1826	0.1980	0.1986
Almon-MIDAS	R^2	0.6872	0.6935	0.6976	0.7051	0.7103	0.7221
	RMSE	0.4906	0.4909	0.5023	0.5012	0.4973	0.4986
	MSFE	0.2407	0.2410	0.2523	0.2512	0.2473	0.2486
	DMSFE	0.0780	0.0780	0.0796	0.0794	0.0810	0.0796