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我在用R中rugarch包uargchfit拟合garch模型后得到结果如下：
*---------------------------------* * GARCH Model Fit * *---------------------------------* Conditional Variance Dynamics ----------------------------------- GARCH Model : sGARCH(1,1) Mean Model : ARFIMA(1,0,1) Distribution : std Optimal Parameters ------------------------------------ EstimateStd. Errort value Pr(>|t|) mu -0.065186 0.025870-2.5197 0.011744 ar1 -0.533832 0.222276-2.4017 0.016321 ma1 0.587081 0.213037 2.7558 0.005855 omega 0.037920 0.012231 3.1003 0.001933 alpha10.093063 0.013322 6.9858 0.000000 beta1 0.900442 0.01327267.8431 0.000000 shape 5.977548 0.658367 9.0793 0.000000 Robust Standard Errors: EstimateStd. Errort value Pr(>|t|) mu -0.065186 0.032485-2.0066 0.044790 ar1 -0.533832 0.204255-2.6136 0.008960 ma1 0.587081 0.197354 2.9748 0.002932 omega 0.037920 0.014528 2.6101 0.009052 alpha10.093063 0.014831 6.2749 0.000000 beta1 0.900442 0.01520359.2268 0.000000 shape 5.977548 0.604537 9.8878 0.000000 LogLikelihood : -5512.035 Information Criteria ------------------------------------ Akaike 3.7493 Bayes 3.7636 Shibata 3.7493 Hannan-Quinn 3.7545 Q-Statistics on Standardized Residuals ------------------------------------ statisticp-value Lag[1] 1.719 0.189776 Lag[p+q+1][3] 7.575 0.005919 Lag[p+q+5][7] 16.102 0.006558 d.o.f=2 H0 : No serial correlation Q-Statistics on Standardized Squared Residuals ------------------------------------ statistic p-value Lag[1] 0.014070.9056 Lag[p+q+1][3] 0.695550.4043 Lag[p+q+5][7] 2.800580.7307 d.o.f=2 ARCH LM Tests ------------------------------------ Statistic DoF P-Value ARCH Lag[2] 0.684 20.7103 ARCH Lag[5] 1.290 50.9360 ARCH Lag[10] 3.871100.9530 Nyblom stability test ------------------------------------ Joint Statistic:3.6585 Individual Statistics: mu 0.9690 ar1 0.0941 ma1 0.1040 omega1.2244 alpha1 0.8088 beta11.3281 shape0.9257 Asymptotic Critical Values (10% 5% 1%) Joint Statistic: 1.69 1.9 2.35 Individual Statistic: 0.35 0.47 0.75 Sign Bias Test ------------------------------------ t-value prob sig Sign Bias 2.8083 0.005013 *** Negative Sign Bias0.0212 0.983085 Positive Sign Bias0.6948 0.487216 Joint Effect 12.9290 0.004793 *** Adjusted Pearson Goodness-of-Fit Test: ------------------------------------ group statistic p-value(g-1) 1 20 53501 0 2 30 82661 0 3 40 111908 0 4 50 141043 0 Elapsed time : 0.752043 想问一下输出结果最后面的Adjusted Pearson Goodness-of-Fit Test检验结果p值小 是说模型拟合不好吗？其检验原理是什么？ 希望得到大神指点！！！ |
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