执行
ibm=read.table(file="m-ibm2697.txt")
ibmln=as.matrix(log(ibm+1)) #净收益率转化为对数收益率
egarch=garchOxFit(formula.mean=~arma(1,0),formula.var=~egarch(1,1),series=ibmln)
语句后估计结果最后提示如下错误:
————“错误于scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, :
scan()需要'a real', 而不是'.NaN'”
而且估计出来的参数值(如下)和您课堂视频的结果也有很大差异,还请方老师释疑
Maximum Likelihood Estimation (Std.Errors based on Second derivatives)
Coefficient Std.Error t-value t-prob
Cst(M) 0.011524 0.0021052 5.474 0.0000
AR(1) 0.089023 0.036581 2.434 0.0152
Cst(V) 0.000000 .NaN .NaN .NaN
ARCH(Alpha1) -0.024868 0.21767 -0.1142 0.9091
GARCH(Beta1) 0.997120 0.0013578 734.3 0.0000
EGARCH(Theta1) -0.031396 0.024237 -1.295 0.1955
EGARCH(Theta2) 0.336492 0.072134 4.665 0.0000
No. Observations : 864 No. Parameters : 7
Mean (Y) : 0.01189 Variance (Y) : 0.00439
Skewness (Y) : -0.22062 Kurtosis (Y) : 5.05333
Log Likelihood : 1122.293
Warning : To avoid numerical problems, the estimated parameter
Cst(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 :
0.011524; 0.089023; 0.000000;-0.024868; 0.997120;-0.031396; 0.336492
最近比较忙,所以没有听课,学习进程慢了很多。顺便问一下方老师,金融时间序列的高级课程什么时候能推出呢?


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