Showing posts with label stock price of google. Show all posts
Showing posts with label stock price of google. Show all posts

## The stock price of google

The google stock price has been taken from yahoo.com since 2004 to 15oct20019
[1] "GOOG"
> chartSeries(ClCl(GOOG))
> chartSeries(Cl(GOOG))

> goog <- dailyReturn(Cl(GOOG), type='log')
> par(mfrow=c(2,2))> acf(ret, main="Return ACF");Error in as.ts(x) : object 'ret' not found
> pacf(goog, main="Return PACF");
> acf(goog^2, main="Squared return ACF");
> pacf(goog^2, main="Squared return PACF")
> acf(goog, main="Return ACF");

> par(mfrow=c(1,1))
> par(mfrow=c(1,1))
> m=mean(goog);s=sd(goog);
> par(mfrow=c(1,2))
> hist(goog, nclass=40, freq=FALSE, main='Return histogram');curve(dnorm(x,
+ mean=m,sd=s), from = -0.3, to = 0.2, add=TRUE, col="red")

> plot(density(goog), main='Return empirical distribution');curve(dnorm(x,mean=m,sd=s), from = -0.3, to = 0.2, add=TRUE, col="red")

> par(mfrow=c(1,1))
> kurtosis(goog)
daily.returns
12.66967
> plot(density(goog), main='Return EDF - upper tail', xlim = c(0.1, 0.2),
+      ylim=c(0,2));
> curve(dnorm(x, mean=m,sd=s), from = -0.3, to = 0.2, add=TRUE, col="red")
> plot(density(goog), xlim=c(-5*s,5*s),log='y', main='Density on log-scale')
> curve(dnorm(x, mean=m,sd=s), from=-5*s, to=5*s, log="y", add=TRUE,
+       col="red")

> qqnorm(goog);qqline(goog);

> garch11.spec = ugarchspec(variance.model = list(model="sGARCH",
+ garchOrder=c(1,1)), mean.model = list(armaOrder=c(0,0)))
> goog.garch11.fit = ugarchfit(spec=garch11.spec, data=goog)
> coef(goog.garch11.fit)
mu        omega       alpha1        beta1
9.274865e-04 1.069049e-05 6.712059e-02 9.035678e-01
> vcov(goog.garch11.fit)
[,1]          [,2]          [,3]
[1,]  6.658647e-08 -6.669035e-12  1.122512e-07
[2,] -6.669035e-12 -1.010435e-13  2.144569e-09
[3,]  1.122512e-07  2.144569e-09  1.135151e-05
[4,] -4.875341e-08 -1.045142e-09 -2.144153e-05
[,4]
[1,] -4.875341e-08
[2,] -1.045142e-09
[3,] -2.144153e-05

[4,]  2.694538e-05

### > infocriteria(goog.garch11.fit) Akaike       -5.274825Bayes        -5.268276Shibata      -5.274828Hannan-Quinn -5.272498

> newsimpact(goog.garch11.fit)
\$zy
[1] 0.0063810911 0.0061394817 0.0059028030 0.0056710552
[5] 0.0054442381 0.0052223519 0.0050053964 0.0047933718
[9] 0.0045862780 0.0043841150 0.0041868827 0.0039945813
[13] 0.0038072107 0.0036247709 0.0034472619 0.0032746838
[17] 0.0031070364 0.0029443198 0.0027865340 0.0026336791
[21] 0.0024857549 0.0023427615 0.0022046990 0.0020715672
[25] 0.0019433663 0.0018200962 0.0017017568 0.0015883483
[29] 0.0014798706 0.0013763237 0.0012777076 0.0011840223
[33] 0.0010952678 0.0010114441 0.0009325512 0.0008585891
[37] 0.0007895579 0.0007254574 0.0006662877 0.0006120489
[41] 0.0005627408 0.0005183636 0.0004789171 0.0004444015
[45] 0.0004148166 0.0003901626 0.0003704394 0.0003556470
[49] 0.0003457854 0.0003408546 0.0003408546 0.0003457854
[53] 0.0003556470 0.0003704394 0.0003901626 0.0004148166
[57] 0.0004444015 0.0004789171 0.0005183636 0.0005627408
[61] 0.0006120489 0.0006662877 0.0007254574 0.0007895579
[65] 0.0008585891 0.0009325512 0.0010114441 0.0010952678
[69] 0.0011840223 0.0012777076 0.0013763237 0.0014798706
[73] 0.0015883483 0.0017017568 0.0018200962 0.0019433663
[77] 0.0020715672 0.0022046990 0.0023427615 0.0024857549
[81] 0.0026336791 0.0027865340 0.0029443198 0.0031070364
[85] 0.0032746838 0.0034472619 0.0036247709 0.0038072107
[89] 0.0039945813 0.0041868827 0.0043841150 0.0045862780
[93] 0.0047933718 0.0050053964 0.0052223519 0.0054442381
[97] 0.0056710552 0.0059028030 0.0061394817 0.0063810911

\$zx
[1] -0.300000000 -0.293939394 -0.287878788 -0.281818182
[5] -0.275757576 -0.269696970 -0.263636364 -0.257575758
[9] -0.251515152 -0.245454545 -0.239393939 -0.233333333
[13] -0.227272727 -0.221212121 -0.215151515 -0.209090909
[17] -0.203030303 -0.196969697 -0.190909091 -0.184848485
[21] -0.178787879 -0.172727273 -0.166666667 -0.160606061
[25] -0.154545455 -0.148484848 -0.142424242 -0.136363636
[29] -0.130303030 -0.124242424 -0.118181818 -0.112121212
[33] -0.106060606 -0.100000000 -0.093939394 -0.087878788
[37] -0.081818182 -0.075757576 -0.069696970 -0.063636364
[41] -0.057575758 -0.051515152 -0.045454545 -0.039393939
[45] -0.033333333 -0.027272727 -0.021212121 -0.015151515
[49] -0.009090909 -0.003030303  0.003030303  0.009090909
[53]  0.015151515  0.021212121  0.027272727  0.033333333
[57]  0.039393939  0.045454545  0.051515152  0.057575758
[61]  0.063636364  0.069696970  0.075757576  0.081818182
[65]  0.087878788  0.093939394  0.100000000  0.106060606
[69]  0.112121212  0.118181818  0.124242424  0.130303030
[73]  0.136363636  0.142424242  0.148484848  0.154545455
[77]  0.160606061  0.166666667  0.172727273  0.178787879
[81]  0.184848485  0.190909091  0.196969697  0.203030303
[85]  0.209090909  0.215151515  0.221212121  0.227272727
[89]  0.233333333  0.239393939  0.245454545  0.251515152
[93]  0.257575758  0.263636364  0.269696970  0.275757576
[97]  0.281818182  0.287878788  0.293939394  0.300000000

\$yexpr
expression(sigma[t]^2)

\$xexpr
expression(epsilon[t - 1])
conclusion
signbias(goog.garch11.fit)
t-value                             prob sig
Sign Bias          1.0768888                  0.2815981
Negative Sign Bias 0.6681522           0.5040769
Positive Sign Bias 0.7067928            0.4797385
Joint Effect       3.0046371                0.3909108
> uncvariance(goog.garch11.fit)
[1] 0.0003647183
> uncmean(goog.garch11.fit)
[1] 0.0009274865

### Black-Scholes formula-R

Black-Scholes formula-R > BlackScholes <- function(TypeFlag = c("c", "p"), S, X, Time, r, b, sigma) { TypeFla...