2013-07-18_GARCH_example

6 02 04 acf 04 02 00 00 acf 06 08 08 10 series

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 0.2 0.4 ACF 0.4 0.2 0.0 0.0 ACF 0.6 0.8 0.8 1.0 Series diff(log(DAX))^2 1.0 Series diff(log(DAX)) 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.00 0.02 0.04 0.06 0.08 0.10 0.12 Lag Lag GARCH model for DAX time series Fitting GARCH(1,1) model... > garch11 <- garch(diff(log(DAX)), order = c(1, 1)) > summary(garch11) Call: garch(x = diff(log(DAX)), order = c(1, 1)) Model: GARCH(1,1) Residuals: Min 1Q -12.18398 -0.47968 Median 0.04949 3Q 0.65746 Max 4.48048 Coefficient(s): Estimate Std. Error t value Pr(>|t|) a0 4.639e-06 7.560e-07 6.137 8.42e-10 *** a1 6.833e-02 1.125e-02 6.073 1.25e-09 *** b1 8.891e-01 1.652e-02 53.817 < 2e-16 *** --Signif. codes: 0 ‘***‘ 0.001 ‘**‘ 0.01 ‘*‘ 0.05 ‘.‘ 0.1 ‘ ‘ 1 GARCH model for DAX time series ...fitting GARCH(1,1) model Diagnostic Tests: Jarque Bera Test data: Residuals X-squared = 12946.6, df = 2, p-value < 2.2e-16 Box-Ljung test data: Squared.Residuals X-squared = 0.1357, df = 1, p-value = 0.7126 GARCH model for DAX time series All GARCH model outputs > ls(garch11...
View Full Document

This note was uploaded on 08/04/2013 for the course ECON 201 taught by Professor Vandewaal during the Spring '09 term at Waterloo.

Ask a homework question - tutors are online