How to tell Matlab to ignore NaNs in calculations/loops

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Hi, I am trying to make some operations with Matlab but I need to ignore the generatedmissing Values / NaNs Matlab gives out after reading in the data from excel. Since now the code is only taking the empty cells and copy them to the new spreadsheet. Instead the NaNs should be ignored. (I am replicating a Finance paper which makes use of the momentum strategy described in Jegadeesh/Titman(1993).) The code is posted below
The code is taken to some part from paper which is about quite the same topic. I have made only some few channges. I Can't delete all the columns which have some NaNs in it.
Thank you for any helpful comments
The code as used is
% [stockdata] = xlsread('Argentina.xlsm',-1);
% [stockid] = xlsread('Argentina.xlsm',-1);
s=-1+(1-(-1)).*rand(715,215);
stockdata=transpose(s);
stockdata(stockdata > 0.5) = NaN;
stockid=[1:715];
[totalmonths,totalstocks] = size(stockdata);% Number of months, number of stocks
period1 = 6; %order period
period2 = 6; % holding period
startmonth=14;
for i=1:totalmonths
nbrstocks(i) = totalstocks - sum(isnan(stockdata(i,:)));
end
for i = 1:length(period1)
for j = 1:length(period2)
p1 = period1(i);
p2 = period2(j);
Rwinner = zeros(totalmonths,1);
Rloser = zeros(totalmonths,1);
idwinner = zeros(totalmonths,round(max(nbrstocks)*0.33));% empty matrix for winners
idloser = zeros(totalmonths,round(max(nbrstocks)*0.33));% empty matrix for losers
for k = startmonth:totalmonths+1-p1-p2 % loop from start till end
start1 = k;
stop1 = start1+p1-1;
ordermonths = start1:stop1;
start2 = stop1+1;
stop2 = start2+p2-1;
holdmonths = start2:stop2;
nstocks = nbrstocks(k);
% order R for the ordering weeks
data1 = stockdata(ordermonths, 1:nstocks);
R1 = ones(1,nstocks);
for m = 1:length(ordermonths)
R1 = R1.*data1(m,:);
end
R1 = R1-1;
% select for the winners and losers
[B,idx] = sort(R1,'descend');
ncandidates = round(nstocks*0.33);
idwinner(k,1:ncandidates) = stockid(idx(1:ncandidates));
idloser(k,1:ncandidates) = stockid(idx(end-ncandidates+1:end));
% caculate the R for winners and losers in holding months
data2winner = stockdata(holdmonths, idx(1:ncandidates));
data2loser = stockdata(holdmonths, idx(end-ncandidates+1:end));
R2w = ones(1,ncandidates);
R2l = ones(1,ncandidates);
for m = 1:length(holdmonths)
R2w = R2w.*data2winner(m,:);
R2l = R2l.*data2loser(m,:);
end
R2w = R2w-1;
R2l = R2l - 1;
Rwinner(k) = mean(R2w);
Rloser(k) = mean(R2l);
end
xlswrite(fullfile(['strategy_' num2str(p1) '_' num2str(p2) '_''.xlsx']),Rwinner,'Rwinner');
xlswrite(fullfile(['strategy_' num2str(p1) '_' num2str(p2) '_''.xlsx']),Rloser,'Rloser');
xlswrite(fullfile(['strategy_' num2str(p1) '_' num2str(p2) '_''.xlsx']),idwinner,'idwinner');
xlswrite(fullfile(['strategy_' num2str(p1) '_' num2str(p2) '_''.xlsx']),idloser,'idloser');
end
end

Answers (4)

Oleg Komarov
Oleg Komarov on 8 Aug 2012
Edited: Oleg Komarov on 9 Aug 2012
If you have the Statistics or the Financial toolbox, use nanmean().
EDIT
What are you trying to do with:
% order R for the ordering weeks
data1 = stockdata(ordermonths, 1:nstocks);
R1 = ones(1,nstocks);
for m = 1:length(ordermonths)
R1 = R1.*data1(m,:);
end
R1 = R1-1;
the cumulative return? Then set the NaNs to 1.
idx = isnan(data1);
data1(idx) = 1;
R1 = prod(data1) - 1;
no need to loop, since prod() is vectorized.
Apply same concept here:
% caculate the R for winners and losers in holding months
data2winner = stockdata(holdmonths, idx(1:ncandidates));
data2loser = stockdata(holdmonths, idx(end-ncandidates+1:end));
R2w = ones(1,ncandidates);
R2l = ones(1,ncandidates);
for m = 1:length(holdmonths)
R2w = R2w.*data2winner(m,:);
R2l = R2l.*data2loser(m,:);
end
R2w = R2w-1;
R2l = R2l - 1;
AND then use nanmean().
  6 Comments

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Albert Yam
Albert Yam on 8 Aug 2012
How about just going low level. At the start of the loop (or where applicable),
if any(isnan(VARIABLE))
continue
end
  4 Comments
Tobi83
Tobi83 on 9 Aug 2012
Thanks for your help again. I tried it like this
if any(isnan(R1))
continue
[B,idx] = sort(R1,'descend');
end
but this gave me an RWinner of zeros. I used this as data in combination with the code above
s=-1+(1-(-1)).*rand(715,215);
stockdata=transpose(s);
stockdata(stockdata > 0.5) = NaN;
stockid=[1:715];

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Sebastian Holmqvist
Sebastian Holmqvist on 9 Aug 2012
data_vec = [1 2 3 4 5 NaN 7 8 NaN 10 12];
data_vec(~isnan(data_vec))
ans =
1 2 3 4 5 7 8 10 12
  3 Comments
Tobi83
Tobi83 on 9 Aug 2012
Thanks again. This doesnt't work because the number of elements must agree in
R1 = R1.*data1(m,:);
You simulate data which looks like the one I am using by copying the following and using it instead of the xlsread commands:
s=-1+(1-(-1)).*rand(715,215);
stockdata=transpose(s);
stockdata(stockdata > 0.5) = NaN;
stockid=[1:715];

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borge
borge on 6 Dec 2012
Hi Tobi83,
I am attempting to do a similar analysis andI have attempted to a compile a code similar to yours, but ran into the same problem, so I was wondering how your code ended up looking like?
Many thanks in advance!
Best, borge

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