function mpt_invest(investments,lb,ub,min,max);
addpath ("/usr/share/octave/site/api-v22/m/octave2.9-forge/io")

#Plot point styles
style = {'*','+','o','x','s'};
stylecount = 5;

# Count the total number of investmentss
count      = rows(investments);

# Set initial value 
x0 = (ub-lb)/2+lb;
x0 = x0*1/sum(x0);

# Calculate investments with smallest number of data points
points = inf;
for i =1:rows(investments)
  tmp = csvread(investments{i,:},1);
  if rows(tmp) < points
    points = rows(tmp);
  end
end

# Read in each investments, crop to min size and store column 9 (return)
in = zeros(points,rows(investments));
for i =1:rows(investments)
  tmp = csvread(investments{i,:},1);
  # Column 9 has adjusted return
  tmp = tmp(1:points,9);
  in(:,i) = tmp;
end;

# Calculate percentage return for each months close
points=rows(in);
py = zeros(points-1,count);
for a=1:count
  for b=1:points-1
    py(b,a) = (in(b,a)-in(b+1,a))/in(b+1,a)*100;
  end;
end;

# Calculate mean, sd, correlation, etc.
e = mean(py)';
sd = std(py)';
cc = corrcoef(py);
C = (sd*sd').*cc;

steps = 10;
axis = 1:steps;
axis = axis.*(max-min)/steps + min;

figure(1);
clearplot
hold on

y=[];
for i=1:steps
  rt = axis(i);
  [tmp, e_mix(i), sd_mix(i)] = gqp(rt,e,C,lb,ub,x0);
  y(i,:) = tmp';
end;

plot(sd_mix,e_mix,"-@;PORTFOLIO;");

for a=1:rows(sd)
  tmp = ["@",style{mod(a,stylecount)+1},dec2base(mod(floor(a/stylecount)+1,7),10),";", investments{a,:}, ";"];
  plot(sd(a),e(a),tmp)
end;
xlabel('Standard Deviation')
ylabel('Return')

figure(2);
clearplot
hold on
for a=1:columns(y)
#  tmp = ["@",dec2base(a+7,7),";", investments{a,:}, ";"];
  tmp = ["-@",style{mod(a,stylecount)+1},dec2base(mod(floor(a/stylecount)+1,7),10),";", investments{a,:}, ";"];
  plot(axis,y(:,a),tmp);
end;
xlabel('Risk')
ylabel('Portfolio Percentage')
hold off
for a=1:rows(sd)
  printf("%s %f\n",investments{a,:},y(steps/2,a));
end;
sd_expected = sd_mix(steps/2)
e_expected = e_mix(steps/2) 
end;