Speed up a recursive loop

Hi,

I have to speed up a portion of my code as much as possible, since the associated computational time is way too high (especially because this part of the code belongs to a nested function, which is called in an optimization process). I 'd like to avoid using a for loop for my vector recursion since its pretty time consuming

I have heard about using the "filter" function or a Cmex file to accelerate the process in a similar discussion (<http://www.mathworks.com/matlabcentral/answers/28396-speed-up-recursive-loop)>, but I dont have a clue of how to apply them to my problem. Therefore, I would really appreciate any kind of help :)

 function f=charac_fun(phi)
            phi=phi'; % the input has to be a row vector

            % recursion for calculating A(t,T,Phi)=A_ and B(t,T,Phi)=B_ (see
            % p.592 in Heston and Nandi article)
            %A=zeros(phi.*r);
            row=size(phi,1);
            A=zeros(row,T-1);
            B=zeros(row,T-1);
            A(:,T-1)=phi.*r;
            B(:,T-1)=lam_.*phi+.5*phi.^2; 

            *for i=2:T-1
                A(:,T-i)=A(:,T-i+1)+phi.*r+B(:,T-i+1).*w-.5*log(1-2*a.*B(:,T-i+1));
                B(:,T-i)=phi.*(lam_+g_)-.5*g_^2+b.*B(:,T-i+1)+.5.*(phi-g_).^2./(1-2.*a.*B(:,T-i+...
                    1));
            end*
            A_=A(:,1)+phi.*r+B(:,1).*w-.5*log(1-2.*a.*B(:,1)); % A(t;T,phi)
            B_=phi.*(lam_+g_)-.5*g_^2+b.*B(:,1)+.5*(phi-g_).^2./(1-2.*a.*B(:,1)); % B(t;T,phi)
            f=S_0.^phi.*exp(A_+B_.*Sig_);
            f=f'; % the output is a row vector
        end

Thanks a lot!!!

Notes: r w a b lam_ g_ S_0 Sig_ are scalars, phi is a vector that might contain complex numbers

Basically the backward recursion is as described in the for loop, from final conditions A(T,T)=B(T,T)=0.