请教 R语言做的arima-garch结果的解读！

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ARIMA-GARCH模型

> arimagarch.fit=garchFit(~arma(1, 2)+garch(1,1), data=capm.model$residuals, algorithm="nlminb+nm", trace=F, include.mean=F) > summary(arimagarch.fit)Title: GARCH Modelling Call: garchFit(formula = ~arma(1, 2) + garch(1, 1), data = capm.model$residuals,     include.mean = F, trace = F, algorithm = "nlminb+nm") Mean and Variance Equation: data ~ arma(1, 2) + garch(1, 1)<environment: 0x0000000016430098> [data = capm.model$residuals] Conditional Distribution: norm Coefficient(s):       ar1         ma1         ma2       omega      alpha1       beta1   0.7056438  -0.6594565  -0.0576294   0.0015822   0.0235457   0.9700100   Std. Errors: based on Hessian Error Analysis:         Estimate  Std. Error  t value Pr(>|t|)    ar1     0.7056438   0.2662349    2.650 0.008038 ** ma1    -0.6594565   0.2674443   -2.466 0.013672 *  ma2    -0.0576294   0.0292255   -1.972 0.048622 *  omega   0.0015822   0.0008641    1.831 0.067094 .  alpha1  0.0235457   0.0060596    3.886 0.000102 ***beta1   0.9700100   0.0078065  124.256  < 2e-16 ***---Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Log Likelihood: -901.7432    normalized:  -0.7055894 Description: Sat Jan 28 01:00:06 2017 by user: hp Standardised Residuals Tests:                                Statistic p-Value      Jarque-Bera Test   R    Chi^2  278.4188  0            Shapiro-Wilk Test  R    W      0.9833757 6.135388e-11 Ljung-Box Test     R    Q(10)  8.44004   0.5859366    Ljung-Box Test     R    Q(15)  11.05071  0.7489917    Ljung-Box Test     R    Q(20)  21.79654  0.3516525    Ljung-Box Test     R^2  Q(10)  5.231958  0.875154    Ljung-Box Test     R^2  Q(15)  8.541135  0.9002633    Ljung-Box Test     R^2  Q(20)  9.225074  0.9801507    LM Arch Test       R    TR^2   7.184211  0.8452038    Information Criterion Statistics:     AIC      BIC      SIC     HQIC 1.420568 1.444761 1.420525 1.429653 请按照结果做个详细的解释，谢谢！

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