Daily NYSE Composite Index
NYSESW.RdA daily time series from 1990 to 2005 of the New York Stock Exchange composite index.
Usage
data("NYSESW")Format
A daily univariate time series from 1990-01-02 to 2005-11-11 (of class
"zoo" with "Date" index).
References
Stock, J.H. and Watson, M.W. (2007). Introduction to Econometrics, 2nd ed. Boston: Addison Wesley.
Examples
## returns
data("NYSESW")
ret <- 100 * diff(log(NYSESW))
plot(ret)
## Stock and Watson (2007), p. 667, GARCH(1,1) model
library("tseries")
fm <- garch(coredata(ret))
#>
#> ***** ESTIMATION WITH ANALYTICAL GRADIENT *****
#>
#>
#> I INITIAL X(I) D(I)
#>
#> 1 7.247660e-01 1.000e+00
#> 2 5.000000e-02 1.000e+00
#> 3 5.000000e-02 1.000e+00
#>
#> IT NF F RELDF PRELDF RELDX STPPAR D*STEP NPRELDF
#> 0 1 1.503e+03
#> 1 3 1.487e+03 1.08e-02 2.29e-01 3.2e-01 1.7e+03 4.5e-01 1.96e+02
#> 2 4 1.481e+03 3.49e-03 6.05e-02 1.8e-01 2.7e+00 2.2e-01 6.80e+01
#> 3 5 1.406e+03 5.06e-02 6.85e-02 1.1e-01 2.3e+00 1.1e-01 8.55e+01
#> 4 7 1.374e+03 2.31e-02 2.63e-02 9.2e-02 1.2e+01 1.1e-01 6.91e+01
#> 5 9 1.356e+03 1.30e-02 2.07e-02 1.2e-01 4.0e+00 1.0e-01 1.06e+01
#> 6 10 1.330e+03 1.91e-02 2.08e-02 1.4e-01 2.0e+00 1.0e-01 1.47e+01
#> 7 11 1.297e+03 2.52e-02 3.20e-02 1.7e-01 2.0e+00 2.0e-01 1.11e+01
#> 8 13 1.290e+03 5.19e-03 1.02e-02 3.4e-02 2.9e+00 4.0e-02 1.85e+00
#> 9 14 1.278e+03 9.38e-03 1.03e-02 2.9e-02 2.0e+00 4.0e-02 2.39e+00
#> 10 15 1.261e+03 1.29e-02 1.58e-02 7.6e-02 2.0e+00 8.0e-02 1.92e+00
#> 11 16 1.227e+03 2.73e-02 3.26e-02 1.2e-01 2.0e+00 1.6e-01 2.11e+00
#> 12 18 1.223e+03 3.24e-03 9.12e-03 1.3e-02 1.8e+02 2.5e-02 4.47e+00
#> 13 19 1.212e+03 9.29e-03 9.02e-03 1.4e-02 2.0e+00 2.5e-02 1.59e+00
#> 14 22 1.168e+03 3.63e-02 3.40e-02 7.2e-02 1.8e+00 1.3e-01 1.70e+00
#> 15 24 1.162e+03 4.48e-03 7.20e-03 1.5e-02 2.0e+00 2.6e-02 5.64e+00
#> 16 25 1.150e+03 1.06e-02 1.12e-02 1.5e-02 2.0e+00 2.6e-02 3.37e+00
#> 17 27 1.135e+03 1.34e-02 1.43e-02 2.4e-02 2.0e+00 5.3e-02 3.34e+00
#> 18 28 1.118e+03 1.50e-02 3.01e-02 4.8e-02 1.9e+00 1.1e-01 9.31e-01
#> 19 31 1.111e+03 5.86e-03 8.61e-03 1.3e-03 4.0e+00 3.4e-03 9.54e-01
#> 20 33 1.102e+03 7.77e-03 1.33e-02 5.4e-03 1.6e+01 1.3e-02 1.18e+00
#> 21 37 1.102e+03 5.75e-04 9.10e-04 5.0e-04 3.8e+00 1.2e-03 3.59e-01
#> 22 39 1.101e+03 4.98e-04 5.37e-04 1.6e-03 2.1e+00 3.4e-03 2.75e-01
#> 23 40 1.100e+03 1.37e-03 1.55e-03 2.9e-03 2.0e+00 6.7e-03 2.23e-01
#> 24 43 1.096e+03 3.56e-03 6.62e-03 1.6e-02 1.8e+00 3.9e-02 9.44e-02
#> 25 45 1.095e+03 6.89e-04 8.79e-04 3.2e-03 1.0e+00 7.0e-03 1.17e-03
#> 26 47 1.095e+03 1.16e-04 1.90e-04 4.8e-04 1.0e+00 1.2e-03 3.08e-04
#> 27 48 1.095e+03 7.85e-07 9.55e-07 1.2e-04 0.0e+00 2.9e-04 9.55e-07
#> 28 49 1.095e+03 3.91e-08 9.27e-08 5.4e-05 0.0e+00 1.2e-04 9.27e-08
#> 29 50 1.095e+03 3.73e-09 1.07e-09 8.4e-06 0.0e+00 2.1e-05 1.07e-09
#> 30 51 1.095e+03 -1.54e-10 8.11e-11 1.6e-06 0.0e+00 4.0e-06 8.11e-11
#>
#> ***** RELATIVE FUNCTION CONVERGENCE *****
#>
#> FUNCTION 1.094921e+03 RELDX 1.590e-06
#> FUNC. EVALS 51 GRAD. EVALS 30
#> PRELDF 8.114e-11 NPRELDF 8.114e-11
#>
#> I FINAL X(I) D(I) G(I)
#>
#> 1 7.620546e-03 1.000e+00 3.522e-01
#> 2 7.019513e-02 1.000e+00 8.588e-02
#> 3 9.216098e-01 1.000e+00 1.571e-01
#>
summary(fm)
#>
#> Call:
#> garch(x = coredata(ret))
#>
#> Model:
#> GARCH(1,1)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -7.21895 -0.51459 0.06401 0.63914 4.31975
#>
#> Coefficient(s):
#> Estimate Std. Error t value Pr(>|t|)
#> a0 0.007621 0.001364 5.585 2.34e-08 ***
#> a1 0.070195 0.005063 13.863 < 2e-16 ***
#> b1 0.921610 0.005948 154.934 < 2e-16 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Diagnostic Tests:
#> Jarque Bera Test
#>
#> data: Residuals
#> X-squared = 805.62, df = 2, p-value < 2.2e-16
#>
#>
#> Box-Ljung test
#>
#> data: Squared.Residuals
#> X-squared = 0.032173, df = 1, p-value = 0.8576
#>