Hands-On Time Series Analysis
Introduction
1.
Everything Up-to-Date
2.
Quandl
2.1.
Access Quandl Databases
2.2.
Installation and Authentication
2.3.
Downloading Historical Data
2.3.1.
Using Additional Arguments of Quandl() Function
2.4.
Querying Quandl Databases from R Console
3.
Basic Visualization of Time Series
3.1.
plot()
3.2.
lines()
3.3.
legend()
4.
Random Walk and White Noise
4.1.
rnorm()
4.2.
set.seed()
4.3.
cumsum()
4.4.
Exercises
4.5.
Solutions
5.
Decomposing Time Series
5.1.
stl()
5.2.
Exercises
5.3.
Solutions
6.
ARMA Models
6.1.
fArma Package
6.2.
Exercises
6.3.
Solutions
7.
GARCH Models
7.1.
fGarch Package
7.2.
Exercises
7.3.
Solutions
8.
Advanced Time Series Visualization
8.1.
Static Graphics
8.1.1.
quantmod Package
8.1.2.
ggplot2 Package
8.2.
Interactive Graphics
8.2.1.
plotly Package
8.2.2.
shiny and rcharts Packages
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Hands-On Time Series Analysis
GARCH Models
For fitting a GARCH model to empirical data we use the
R
package
fGarch
.