Rmetrics - Autoregressive Conditional Heteroskedastic Modelling
Diethelm Wuertz and Yohan Chalabi with contribution from Michal
Miklovic, Chris Boudt, Pierre Chausse and others
R (>= 2.6.0), stats, graphics, methods, timeDate, timeSeries,
fBasics (>= 2100.78)
Environment for teaching "Financial Engineering and
Computational Finance"
SEVERAL PARTS ARE STILL PRELIMINARY AND MAY BE CHANGED IN THE
FUTURE. THIS TYPICALLY INCLUDES FUNCTION AND ARGUMENT NAMES, AS
WELL AS DEFAULTS FOR ARGUMENTS AND RETURN VALUES.