Dear Sirs, is it possible to make an autoregressive conditional volatility, skewness and kurtosis model for matlab, winrats, c++ or any other software? The Specificaton is as follows: r(t) = a0 +a1*r(t-1) +e(t), e(t)~(0,s^2) e(t)=h^0.5*p(t), p(t)~(0,1) h(t)=b0 + b1*(e(t-1)+b2*h(t-1)^0.5)^2 +b3*h(t-1) s(t)= c0 + c1*p(t-1)^3 + c2*s(t-1) k(t)= d0 + d1*p(t-1)^3 + d2*k(t-1) where the residuals p(t) follow the Gram-Charlier series expansion: g(p(t))=f(p(t)*[1+(s(t)/3!)*(p(t)^3-3(p(t))+((k(t)-3/4!)*(p(t)^4-6p(t)^2+3]= f(p(t)*F(p(t) for simplicity with the log-likelihood function being: l(t)=-1/2ln(h(t))-1/2h(t)^2+ln(F(p(t))-ln(1+s(t)^2/3!+(k(t)-3)^2/4!) I am attaching the original article which contains the information, in a more analytic form. Kind Regards ## Deliverables 1) Complete a...
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