Updates from version 2.0:
1. The marginal GARCH models are estimated from the toolbox functions (without the use of the econometrics/GARCH toolbox of MATLAB).
2. Hansen's Skew t distribution for the margins is supported.
3. Asymptotic standard errors are computed (Godambe info. matrix)
I have a 3 x n matrix with the values of x-coordinate, y-coordinate and some value of the point. As I am new to Matlab, please help me how to run your code with these.
Thank you in advance.
For any information or help regarding the toolbox please contact me at email@example.com
In the description it says "without the use of the econometrics/GARCH toolbox of MATLAB" but in required products it says: "Econometrics Toolbox". I don't have this toolbox. Do I need it to run this code? Thank you
so helpful!thanks a lot!
I found out by myself ,sorry to disturb u.
Anyway, it is really a good and helpful toolbox!!!
Thanks for the Author!
When I ran this code , I met this problem. I tried to find out the reason, but failed. The data here is one stock return. I want to fit a GARCH(1,1)model.
>> spec = modelspec(data)
??? Operands to the || and && operators must be convertible to logical scalar
Error in ==> FromCons2Unc at 41
if max(max(x))> a || min(min(x))<-a
Error in ==> RescaleParameters at 116
[uncmparams, d1mp, d2mp] = FromCons2Unc(consmparams,.5,3);
Error in ==> fitModel at 86
theta0 = RescaleParameters(theta0, 2, spec);
Thanks for your work, now I meet a problem with FitModel.m as:
[parameters, LogL, evalmodel, GradHess, varargout] = fitModel(spec, out1, fminunc)
??? Error using ==> fminunc at 156
FMINUNC requires two input arguments.
I am still confusing with the data input way, because I already transformed the stock return into empirical CDF through empirical.m in out1 and just put out1 instead of data in the FitModel.m function, you see the error comes out as FMINUNC requires two input arguments. So could you show me how to input the data in a correct way?
nice work! this program help me a lot~~~
Just correcting my first comment above: I was not able to estimate a vine copula sequentially using “modelspec” (and the menu) and “fitModel” after that. I had to use “SeqFitCopVine.m” instead of “fitModel” and this is not specified in the Tutorial.
Excellent work! It has helped me a lot.
I just would like to mention two minor difficulties I had:
1) I was not able to estimate a vine copula sequentially using the menu. I had to use the function “SeqFitCopVine.m”.
2) I could not find “hfuncJC.m” in the third version of the toolbox. I think it’s missing. I had to copy this from version 2.0.
Thanks for your work.
Sorry for the inconvenience. I just forgot to add the hessian_2sided function to the toolbox. I will fix it tomorrow. Thanks for the rating and comments
Thanks for your nice work.
However, I find some problems when using this toolbox.
The wrong messages are follows:
??? Undefined function or method 'hessian_2sided' for input arguments of type 'struct'.
Error in ==> CalcStErrors at 39
Hnum = hessian_2sided(MyFunc,theta,data,spec,'fmincon'); % calculates the Hessian
Error in ==> fitModel at 185
[derivatives, RobVCV, VCV, hessian, RobStE]=CalcStErrors('CopulaGARCHLogL',
parameters, data, grad, hessian, spec, 'fmincon');
I truely hope you can deal with the above problem.
updates so it can be used as a toolbox
Remove any older versions, install the new version and open HotToUseTheToolbox.m, then follow the instructions therein
Just open the script HowToUseTheToolbox.m and follow the instructions therein.