having trouble optimizing a NPV

So I am trying to find the optimization for r, however i can never get yval to equal 0

rinit=0.05;


[npvmin,yval]=fminsearch(@tsk,rinit);

function [npv]=tsk(r)
outlay=1000;
t=[0.25;0.5;0.75;1;1.25;1.5];
cf=[250;100;150;200;250;200];
asx = cf./((1+r).^t);
npv=sum(asx);
end

Answer 1

[Sam Chak]

Hi @jxl

The function tsk(r) seems to be converging asymptotically to zero as .

r = linspace(0, 1000, 10001);
plot(r, tsk(r)), grid on, xlabel('r')

rinit = 0.05;
[npvmin, yval] = fminsearch(@tsk, rinit)

 
Exiting: Maximum number of function evaluations has been exceeded
         - increase MaxFunEvals option.
         Current function value: 0.000033 

npvmin = 3.1691e+27

yval = 3.3320e-05

function [npv] = tsk(r)
    outlay = 1000;
    t      = [0.25; 0.50; 0.75; 1.00; 1.25; 1.50];
    cf     = [250; 100; 150; 200; 250; 200];
    asx    = cf./((1 + r).^t);
    npv    = sum(asx);
end