Description Usage Arguments Value Note Author(s) References
Off-diagonal parameter estimation in bivariate GARCH(1,1) when diagonal parameters are given.
1 |
y |
: [vector] (T x 1) data generated by a GARCH(1,1) process |
c1 |
: [scalar] diagonal parameter of the GARCH(1,1) process taken from matrix C |
a1 |
: [scalar] diagonal parameter of the GARCH(1,1) process taken from matrix A |
b1 |
: [scalar] diagonal parameter of the GARCH(1,1) process taken from matrix B |
y1 |
: [vector] (T x 1) data generated by a GARCH(1,1) process |
h1 |
: [vector] (T x 1) data generated by a GARCH(1,1) process |
c2 |
: [scalar] diagonal parameter of the GARCH(1,1) process taken from matrix C |
a2 |
: [scalar] diagonal parameter of the GARCH(1,1) process taken from matrix A |
b2 |
: [scalar] diagonal parameter of the GARCH(1,1) process taken from matrix B |
y2 |
: [vector] (T x 1) data generated by a GARCH(1,1) process |
h2 |
: [vector] (T x 1) generated by a GARCH(1,1) process |
df |
: [scalar] degree of freedom for the t-distribution; the default value is 500 to make it, basically, normal |
q : [vector] (4 x 1) parameters of the GARCH(1,1) process
qerr : [vector] (4 x 1) standard error of parameter estimates
hf : [scalar] current conditional heteroskedasticity estimate
hferr : [scalar] standard error on hf
MATLAB's code initially written by Olivier Ledoit, 4/28/1997
Uses a conditional t-distribution with fixed degrees of freedom
Steepest Ascent on boundary, Hessian off boundary, no grid search
Xavier Valls flamejat@gmail.com
A. Meucci - "Exercises in Advanced Risk and Portfolio Management" http://symmys.com/node/170.
See Meucci's script for "FitMultivariateGarch.m"
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