Hello,
When computing Sxx, Syy and you are mistaking the square of the sum for
the sum of squares. The same goes for the crossed term Sxy, it's the sum
of the products, not the product of the sums Sx and Sy.
Hope this helps,
Rui Barradas
Em 20-07-2012 23:04, cesare orsini escreveu:
Dear friends
i am trying to fit an Ornstein-Uhlenbeck process by MAXIMUM LIKELYHOOD
method.
i found these formulas on
http://www.sitmo.com/article/calibrating-the-ornstein-uhlenbeck-model/
this is the mean-reverting process
http://r.789695.n4.nabble.com/file/n4637271/process.txt process.txt
and this is the script that i am using.......
ouFit.ML=function(spread) {
n=length(spread)
delta=n/n
Sx=sum(spread[1:n-1])
Sy=sum(spread[2:n])
Sxx=(Sx)^2
Syy=(Sy)^2
Sxy=Sx*Sy
mu = (Sy*Sxx - Sx*Sxy) / ( n*(Sxx - Sxy) - (Sx^2 - Sx*Sy) )
lambda = -log( (Sxy - mu*Sx - mu*Sy + n*mu^2) / (Sxx -2*mu*Sx + n*mu^2)
)/delta
a = exp(-lambda*delta)
sigmah2 = (Syy - 2*a*Sxy + a^2*Sxx - 2*mu*(1-a)*(Sy - a*Sx) +
n*mu^2*(1-a)^2)/n;
sigma = sqrt((sigmah2)*2*lambda/(1-a^2))
theta=list(lambda=lambda, mu=mu,sigma=sigma,sigmah2=sigmah2)
return(theta)
}
where is my error?
is there some other script to obtain a good result by the same method?
thank you!!! :-)
--
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