From MATLAB to Python

Hi, Im new to coding and matlab but i have some basics in Python. I'm trying to learn MATLAB using resources i found online. there is this code that i found but am not sure some of it. below is the code and the understanding i have:

%create indicator and return lead & lag values
[lead,lag] = movavg(fitting30mAUDCAD.close,5,20,"e");

%create a variable the size of close and put all "0"
s = zeros(size(fitting30mAUDCAD.close));

%criteria to sell
s (lead<=lag) = -1;

%criteria to buy
s (lead>lag) = 1;

%what does this mean? 
r = [0;s(1:end-1).*diff(fitting30mAUDCAD.close)];
w = cumsum(r);

[Rik]

What part don't you understand? How the subindexing works? What the diff function does? What the .* syntax means?

[andy quek]

Hi Rik, so my understanding of return is: sell price - buy price = return which is same as return = earnings - costs.

from what i understand

s(1:end-1) = the array of "1" and "-1"

diff(fitting30mAUDCAD.close) = difference in closing price

Below is a illustration of what i think this code means

Therefore i cant really process how return is derived

Example:

time	      price	signal	differce in closing	code return
00:00:00	1	-1	  0	                    0
01:00:00	1.2	0	-0.2	                    0
02:00:00	1.4	0	-0.2	                    0
03:00:00	1.6	0	-0.2	                    0
04:00:00	1.8	0	-0.2	                    0
05:00:00	2	0	-0.2	                    0
06:00:00	2.2	0	-0.2	                    0
07:00:00	2.4	0	-0.2	                    0
08:00:00	2.6	1	-0.2	                  -0.2
return				                          -0.2

Return is actually -1.6 instead of -0.2.

Reference Video link: https://www.youtube.com/watch?v=SJ_I4NtQ-_8&t=701s

Part i mention is from 11 mins - 11.40 mins

Answer 1

[Matt J]

Below is a illustration of what i think this code means

It's not clear which column corresponds to which variable in your code. However, if I assume 3rd column is r,

>> r(1:9,1)=-0.2; r(1)=0

r =

         0
   -0.2000
   -0.2000
   -0.2000
   -0.2000
   -0.2000
   -0.2000
   -0.2000
   -0.2000

then the w that gets computed should be,

>> w=cumsum(r)

w =

         0
   -0.2000
   -0.4000
   -0.6000
   -0.8000
   -1.0000
   -1.2000
   -1.4000
   -1.6000