For loop with moving window
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Hi
I want to create a for-loop that calculates the weights of portfolios using a moving window for the period I am investigating. The moving window should move one day at a time and there are 1000 days in the window.
For example, compute the optimal weights on day1001 based on observations for period 1-1000days. Then you move on to day 1002, and re-calculate the weights, based on observations for period 2-1001days, etc.
I have a matrix of returns (Rets) that is 3740x6. The first column has the dates and the rest of the columns have daily returns for five different asset classes.
Thanks!
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Answers (4)
Image Analyst
on 31 Jul 2014
Simply use conv()
kernel = [zeros(1,999), ones(1,1000)]; % Look backward 1000 elements.
output = conv(observations, kernel, 'valid'); % Get sliding means
5 Comments
Evan
on 31 Jul 2014
Edited: Evan
on 31 Jul 2014
Googling "convolution" may help you to get an overall idea of the operation before getting into the MATLAB implementation of it. You might find the wikipedia entry helpful, although I often find that I drown in notation when trying to read through mathematics wiki articles.
Basically, conv() will slide the kernel over the vector, progressing one element at a time, and multiply then sum corresponding values that fall within the window. It "pads" the array with zeros in order to start with the first element. Here's an example:
A = [1 2 3 4 5];
B = [1 1];
conv(A,B)
ans =
1 3 5 7 9 5
So here's the progression:
[ 0 1 2 3 4 5 0]
[ 1 1 ]
1*0 + 1*1 = 1;
__________________
[ 0 1 2 3 4 5 0 ]
[ 1 1 ]
1*1 + 1*2 = 3
__________________
[ 0 1 2 3 4 5 0 ]
[ 1 1 ]
1*2 + 1*3 = 5
__________________
[ 0 1 2 3 4 5 0]
[ 1 1 ]
1*3 + 1*4 = 7
__________________
[ 0 1 2 3 4 5 0]
[ 1 1 ]
1*4 + 1*5 = 9
__________________
[ 0 1 2 3 4 5 0]
[ 1 1 ]
1*5 + 1*0 = 5
Image Analyst
on 31 Jul 2014
Edited: Image Analyst
on 31 Jul 2014
Convolution basically gives you a weighted sum in a sliding window. It would give you the average value (price?) of your signal over the past 1000 days. I'm a scientist, not a financial person, so perhaps you don't want that - I don't know. If you do want a weighted sum in a sliding window (like the 20 day or 50 day moving stock price average) then convolution is for you, though there may be some functions in the Financial Toolbox that are better suited, like with more options and using the terminology financial people are familiar with.
There is also a conv2() function that deals with 2D arrays. If you just wanted to sum up going down columns, then the kernel would be a column vector. If you wanted to average across columns, then the kernel would be a row vector.
Ahmet Cecen
on 30 Jul 2014
Edited: Ahmet Cecen
on 30 Jul 2014
If I understand you correctly, you have an indexing problem. Try an indexing scheme like this:
for i=1:N
Weights(i)=function(Rets(i:(i+1000),2));
end
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Arijit Ghosh
on 9 Mar 2017
Hello I need to design a sliding window of time t=5 sec. to slide all over the signal without overlap and thereby perform CWT from each window. Can anyone help please..
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Alejandra Pena-Ordieres
on 29 Jul 2024 at 14:59
Hello,
You might want to consider using the backtesting workflow available in the Financial Toolbox, Backtest Investment Strategies Using Financial Toolbox. In your case, you'd need to convert your data into a timetable and define your optimization strategy as a backtestStrategy with RebalanceFrequency=1 and a LookbackWindow = [1000 1000].
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