Stock Price ITC.NS
> addMomentum()
> addMACD()
> addPoints()
> retitc <- dailyReturn(Cl(ITC.NS), type='log')
> par(mfrow=c(2,2))
> acf(retitc, main="ITC Return ACF");
> pacf(retitc, main="ITC Return PACF");
> acf(retitc^2, main="Squared ITC return ACF");
> pacf(retitc^2, main="Squared ITC return PACF")
> par(mfrow=c(1,1))
> plot(density(retitc), main='ITC Return empirical distribution');curve(dnorm(x,mean=m,sd=s), from = -0.3, to = 0.2, add=TRUE, col="red")
> hist(retitc, nclass=40, freq=FALSE, main='Return histogram');curve(dnorm(x,
+ mean=m,sd=s), from = -0.3, to = 0.2, add=TRUE, col="red")
kurtosis(retitc)
[1] 81.70154
attr(,"method")
[1] "excess"
> curve(dnorm(x, mean=m,sd=s), from=-5*s, to=5*s, log="y", add=TRUE,
+ col="red")
> qqnorm(retitc);qqline(retitc);
> chartSeries(retitc)
> garch11.spec = ugarchspec(variance.model = list(model="sGARCH",garchOrder=c(1,1)), mean.model = list(armaOrder=c(0,0)))
> itc.garch11.fit = ugarchfit(spec=garch11.spec, data=retitc)
> coef(itc.garch11.fit)
mu omega alpha1
7.572865e-04 7.054504e-06 6.574492e-02
beta1
9.199215e-01
> vcov(itc.garch11.fit)
[,1] [,2] [,3]
[1,] 6.837256e-08 1.707724e-11 -4.076436e-08
[2,] 1.707724e-11 -1.467594e-12 5.285928e-09
[3,] -4.076436e-08 5.285928e-09 2.924242e-05
[4,] -2.586683e-08 6.830059e-10 -3.873864e-05
[,4]
[1,] -2.586683e-08
[2,] 6.830059e-10
[3,] -3.873864e-05
[4,] 2.972086e-05
> uncmean(itc.garch11.fit)
[1] 0.0007572865
> uncvariance(itc.garch11.fit)
[1] 0.0004921646
(itc.garch11.fit)
Akaike -5.207977
Bayes -5.201582
Shibata -5.207980
Hannan-Quinn -5.205708
> newsimpact(itc.garch11.fit)
$zy
[1] 0.0063768498 0.0061401923 0.0059083645
[4] 0.0056813664 0.0054591981 0.0052418595
[7] 0.0050293507 0.0048216716 0.0046188223
[10] 0.0044208027 0.0042276129 0.0040392528
[13] 0.0038557224 0.0036770218 0.0035031510
[16] 0.0033341099 0.0031698985 0.0030105169
[19] 0.0028559650 0.0027062429 0.0025613505
[22] 0.0024212879 0.0022860550 0.0021556518
[25] 0.0020300784 0.0019093348 0.0017934209
[28] 0.0016823367 0.0015760823 0.0014746577
[31] 0.0013780627 0.0012862976 0.0011993621
[34] 0.0011172564 0.0010399805 0.0009675343
[37] 0.0008999179 0.0008371312 0.0007791742
[40] 0.0007260470 0.0006777496 0.0006342818
[43] 0.0005956439 0.0005618357 0.0005328572
[46] 0.0005087085 0.0004893895 0.0004749002
[49] 0.0004652407 0.0004604110 0.0004604110
[52] 0.0004652407 0.0004749002 0.0004893895
[55] 0.0005087085 0.0005328572 0.0005618357
[58] 0.0005956439 0.0006342818 0.0006777496
[61] 0.0007260470 0.0007791742 0.0008371312
[64] 0.0008999179 0.0009675343 0.0010399805
[67] 0.0011172564 0.0011993621 0.0012862976
[70] 0.0013780627 0.0014746577 0.0015760823
[73] 0.0016823367 0.0017934209 0.0019093348
[76] 0.0020300784 0.0021556518 0.0022860550
[79] 0.0024212879 0.0025613505 0.0027062429
[82] 0.0028559650 0.0030105169 0.0031698985
[85] 0.0033341099 0.0035031510 0.0036770218
[88] 0.0038557224 0.0040392528 0.0042276129
[91] 0.0044208027 0.0046188223 0.0048216716
[94] 0.0050293507 0.0052418595 0.0054591981
[97] 0.0056813664 0.0059083645 0.0061401923
[100] 0.0063768498
$zx
[1] -0.300000000 -0.293939394 -0.287878788
[4] -0.281818182 -0.275757576 -0.269696970
[7] -0.263636364 -0.257575758 -0.251515152
[10] -0.245454545 -0.239393939 -0.233333333
[13] -0.227272727 -0.221212121 -0.215151515
[16] -0.209090909 -0.203030303 -0.196969697
[19] -0.190909091 -0.184848485 -0.178787879
[22] -0.172727273 -0.166666667 -0.160606061
[25] -0.154545455 -0.148484848 -0.142424242
[28] -0.136363636 -0.130303030 -0.124242424
[31] -0.118181818 -0.112121212 -0.106060606
[34] -0.100000000 -0.093939394 -0.087878788
[37] -0.081818182 -0.075757576 -0.069696970
[40] -0.063636364 -0.057575758 -0.051515152
[43] -0.045454545 -0.039393939 -0.033333333
[46] -0.027272727 -0.021212121 -0.015151515
[49] -0.009090909 -0.003030303 0.003030303
[52] 0.009090909 0.015151515 0.021212121
[55] 0.027272727 0.033333333 0.039393939
[58] 0.045454545 0.051515152 0.057575758
[61] 0.063636364 0.069696970 0.075757576
[64] 0.081818182 0.087878788 0.093939394
[67] 0.100000000 0.106060606 0.112121212
[70] 0.118181818 0.124242424 0.130303030
[73] 0.136363636 0.142424242 0.148484848
[76] 0.154545455 0.160606061 0.166666667
[79] 0.172727273 0.178787879 0.184848485
[82] 0.190909091 0.196969697 0.203030303
[85] 0.209090909 0.215151515 0.221212121
[88] 0.227272727 0.233333333 0.239393939
[91] 0.245454545 0.251515152 0.257575758
[94] 0.263636364 0.269696970 0.275757576
[97] 0.281818182 0.287878788 0.293939394
[100] 0.300000000
$yexpr
expression(sigma[t]^2)
$xexpr
expression(epsilon[t - 1])
signbias(itc.garch11.fit)
t-value prob sig
Sign Bias 1.0290102 0.303538366
Negative Sign Bias 0.5976512 0.550107217
Positive Sign Bias 2.6295677 0.008582753 ***
Joint Effect 7.2815860 0.063444166 *
egarch11.spec = ugarchspec(variance.model = list(model="eGARCH",garchOrder=c(1,1)), mean.model = list(armaOrder=c(0,0)))
> itc.egarch11.fit = ugarchfit(spec=egarch11.spec, data=retitc)
> coef(itc.egarch11.fit)
mu omega alpha1
0.0007458757 -0.1284922189 -0.0070553000
beta1 gamma1
0.9824002414 0.1562207989
> ni.egarch11 <- newsimpact(itc.egarch11.fit)
> plot(ni.egarch11$zx, ni.egarch11$zy, type="l", lwd=2, col="blue",
+ main="EGARCH(1,1) - News Impact",
+ ylab=ni.egarch11$yexpr, xlab=ni.egarch11$xexpr)
> tgarch11.spec = ugarchspec(variance.model = list(model="fGARCH",submodel="TGARCH", garchOrder=c(1,1)),mean.model = list(armaOrder=c(0,0)))
> itc.tgarch11.fit = ugarchfit(spec=tgarch11.spec, data=retitc)
coef(itc.egarch11.fit)
mu omega alpha1
0.0007458757 -0.1284922189 -0.0070553000
beta1 gamma1
0.9824002414 0.1562207989
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