
when I run the following code:
#------------------------------------------------------------------
library(fImport)library(fGarch)query = "s=IBM&a=11&b=1&c=1999&d=0&q=31&f=2000&z=IBM&x=.csv"IBM = yahooImport(query)RetIBM = diff(log(IBM@data[, "Adj.Close"]))mod = garchOxFit(formula = ~egarch(1, 1), data = RetIBM)
#------------------------------------------------------------------
I get following result and stored these in "mod"
> mod
Title: GARCH Ox Modelling 
Mean Equation: ~arma(0, 0)
Conditional Variance Equation: ~egarch(1, 1)
Conditional Distribution: gaussian
Coefficient(s):                Value  Std.Error    t.valueCst(M)     0.00027697 2.7573e-04    1.00450Cst(V)     0.00000000 2.0974e+02    0.00000ARCH(1)    0.17620000 2.4579e-01    0.71689GARCH(1)   0.99798000 5.3373e-04 1869.80000EGARCH(1) -0.06414600 1.5700e-02   -4.08570EGARCH(2)  0.24758000 5.4078e-02    4.57820
 
 
but at the sametime , i lost the following useful messages which are trace messages:
 ******************** ** SPECIFICATIONS ** ********************Dependent variable : XMean Equation : ARMA (0, 0) model.No regressor in the meanVariance Equation : EGARCH (1, 1) model. No regressor in the varianceThe distribution is a Gauss distribution.
Strong convergence using numerical derivativesLog-likelihood = 5455.52Please wait : Computing the Std Errors ...
 Maximum Likelihood Estimation (Std.Errors based on Second derivatives)                  Coefficient  Std.Error  t-value  t-probCst(M)               0.000277 0.00027573    1.005  0.3153Cst(V)               0.000000     209.74     0.00  1.0000ARCH(Alpha1)         0.176204    0.24579   0.7169  0.4735GARCH(Beta1)         0.997976 0.00053373    1870.  0.0000EGARCH(Theta1)      -0.064146   0.015700   -4.086  0.0000EGARCH(Theta2)       0.247578   0.054078    4.578  0.0000
No. Observations :      1996  No. Parameters  :         6Mean (Y)         :   0.00005  Variance (Y)    :   0.00036Skewness (Y)     :  -0.07514  Kurtosis (Y)    :  10.60064Log Likelihood   :  5455.518
Warning : To avoid numerical problems, the estimated parameterCst(V), and its std.Error have been multiplied by 10^4.
The sample mean of squared residuals was used to start recursion.
Estimated Parameters Vector :  0.000277; 0.000000; 0.176204; 0.997976;-0.064146; 0.247578
 
  *************** ** FORECASTS *****************Number of Forecasts: 15
Horizon       Mean   Variance      1   0.000277   0.000539      2   0.000277  0.0006183      3   0.000277  0.0006276      4   0.000277  0.0006371      5   0.000277  0.0006466      6   0.000277  0.0006563      7   0.000277  0.0006661      8   0.000277   0.000676      9   0.000277  0.0006861     10   0.000277  0.0006963     11   0.000277  0.0007066     12   0.000277  0.0007171     13   0.000277  0.0007277     14   0.000277  0.0007384     15   0.000277  0.0007492---------------Forecasts errors measures cannot be computed because there are not enough out-of-sample observations).Elapsed Time : 12.64 seconds (or 0.210667 minutes).
  *********** ** TESTS *************                   Statistic       t-Test      P-ValueSkewness           -0.096485       1.7611     0.078216Excess Kurtosis       3.2361       29.548  6.8674e-192Jarque-Bera           874.03         .NaN  1.6094e-190---------------Information Criterium (to be minimized)Akaike         -5.460439  Shibata        -5.460457Schwarz         -5.443608  Hannan-Quinn    -5.454258---------------Q-Statistics on Standardized Residuals  Q( 10) =  8.56194   [0.5741183]  Q( 15) =  14.1404   [0.5149081]  Q( 20) =  17.6476   [0.6106090]H0 : No serial correlation ==> Accept H0 when prob. is High [Q < Chisq(lag)]--------------Q-Statistics on Squared Standardized Residuals  --> P-values adjusted by 2 degree(s) of freedom   Q( 10) =  8.28254   [0.4063687]  Q( 15) =  17.1193   [0.1939091]  Q( 20) =  20.4735   [0.3068045]H0 : No serial correlation ==> Accept H0 when prob. is High [Q < Chisq(lag)]--------------ARCH 1-2 test:    F(2,1989)=  0.44852 [0.6386]  ARCH 1-5 test:    F(5,1983)=  0.58328 [0.7129]  ARCH 1-10 test:   F(10,1973)=  0.87535 [0.5558]  --------------
Residual-Based Diagnostic for Conditional Heteroskedasticity of Tse (2001)
  RBD(10) =  9.10388   [0.5222740]  RBD(15) =  14.6812   [0.4746184]  RBD(20) =  19.7141   [0.4759394]------------------------------------------------P-values in brackets
Diagnostic test based on the news impact curve (EGARCH vs. GARCH)                                     Test  P-valueSign Bias t-Test                  0.28096  0.77874Negative Size Bias t-Test         0.90666  0.36459Positive Size Bias t-Test         0.89604  0.37023Joint Test for the Three Effects  1.77506  0.62038---------------
Joint Statistic of the Nyblom test of stability: 21.3842
Individual Nyblom Statistics: Cst(M)           0.11744Cst(V)           1.24579ARCH(Alpha1)     1.84550GARCH(Beta1)     0.23648EGARCH(Theta1)   0.12947EGARCH(Theta2)   2.21806
Rem: Asymptotic 1% critical value for individual statistics = 0.75.     Asymptotic 5% critical value for individual statistics = 0.47.---------------
Adjusted Pearson Chi-square Goodness-of-fit test
# Cells(g)  Statistic      P-Value(g-1)     P-Value(g-k-1)       40       93.3788         0.000002          0.000000    50      103.4489         0.000009          0.000001    60      116.2645         0.000013          0.000001Rem.: k = 6 = # estimated parameters---------------
Execution Time: Time difference of 13.609 secs
 the problem is how to store these?
 
thanks
 
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