CallPricingFFTi(model,n,S,K,T,r,d,imethod,varargin)

% This is material illustrating the methods from the book
% Financial Modelling  Theory, Implementation and Practice with Matlab
% source
% Wiley Finance Series
% ISBN 9780470744895
%
% Date: 02.05.2012
%
% Authors: Joerg Kienitz
% Daniel Wetterau
%
% Please send comments, suggestions, bugs, code etc. to
% kienitzwetterau_FinModelling@gmx.de
%
% (C) Joerg Kienitz, Daniel Wetterau
%
% Since this piece of code is distributed via the mathworks fileexchange
% it is covered by the BSD license
%
% This code is being provided solely for information and general
% illustrative purposes. The authors will not be responsible for the
% consequences of reliance upon using the code or for numbers produced
% from using the code.
function call_price_fft = CallPricingFFTi(model,n,S,K,T,r,d,imethod,varargin)
lnS = log(S);
lnK = log(K);
%optAlpha = optimalAlpha(model,lnS,lnK,T,r,d,varargin{:});
optAlpha = .75;
DiscountFactor = exp(r*T);
%
% FFT Option Pricing 
%
% from: Option Valuation Using the Fast Fourier Transform,
% Peter Carr, March 1999, pp 1011
%
% predefined parameters
FFT_N = 2^n; % must be a power of two (2^14)
FFT_eta = 0.05; % spacing of psi integrand
% effective upper limit for integration (18)
% uplim = FFT_N * FFT_eta;
FFT_lambda = (2 * pi) / (FFT_N * FFT_eta); %spacing for log strike output (23)
FFT_b = (FFT_N * FFT_lambda) / 2; % (20)
uvec = 1:FFT_N;
%log strike levels ranging from lnSb to lnS+b
ku =  FFT_b + FFT_lambda * (uvec  1); %(19)
jvec = 1:FFT_N;
vj = (jvec1) * FFT_eta;
% optimal alpha illustration (payoff independent)
% alpharange = 3:0.1:8;
% resultrangef = zeros(1,length(alpharange));
% resultrangef1 = zeros(1,length(alpharange));
% eps = 0.000001;
% for n = 1:length(alpharange)
% resultrangef(n)= (alpharange(n) * log(K) + log(psialpha(model,alpharange(n),lnS,T,r,d,varargin{:})));
% resultrangef1(n)= ((alpharange(n) + eps) * log(K) ...
% + log(psialpha(model,alpharange(n)+eps,lnS,T,r,d,varargin{:})));
% resultrangef1(n)= (resultrangef1(n)  resultrangef(n)) / eps;
% end
% plot(alpharange,resultrangef); hold on; plot(alpharange,resultrangef1, 'g'); hold off;
%applying FFT
tmp = DiscountFactor * psi(model,vj,optAlpha,lnS,T,r,d,varargin{:}) .* exp(1i * vj * (FFT_b)) * FFT_eta;
tmp = (tmp / 3) .* (3 + (1).^jvec  ((jvec  1) == 0) ); %applying simpson's rule
cpvec = real(exp(optAlpha .* ku) .* fft(tmp) / pi); %call price vector resulting in equation 24
indexOfStrike = floor((lnK + FFT_b)/FFT_lambda + 1);
iset = max(indexOfStrike)+1:1:min(indexOfStrike)1;
xp = ku(iset);
yp = cpvec(iset);
call_price_fft = real(interp1(xp,yp,lnK,imethod));
end
%analytical formula for zhi in equation ( 6 ) of Madan's paper
function ret = psi(model,v,alpha,varargin)
ret = exp(feval(@CharacteristicFunctionLib, model, v  (alpha + 1) * 1i,varargin{:})) ./ (alpha.^2 + alpha  v.^2 + 1i * (2 * alpha + 1) .* v);
end
% function ret = psialpha(model,alpha,varargin)
% ret = exp(feval(@CharacteristicFunctionLib, model,  (alpha + 1) * 1i,varargin{:}))./ (alpha.^2 + alpha);
% end

