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I am trying to execute a parfor loop within a parent script for Matlab.
I want to calculate the implied volatility of an option price, and then create a new column within a preexisting dataset with the results.
load('/home/arreat/Casino/names.mat')
name = char(names(i))
%Loop over n rows to populate columns in dataset named using variable 'name(i)'
rows = eval(['length(',name,')'])
parfor n=[1:rows]
%Calculate implied volatility using blsimpv(Price, Strike, Rate, Time, Value, Limit,Yield, Tolerance, Class)
BidIV = blsimpv(eval([name,'.UnderlyingPrice(n)']),...
eval([name,'.Strike(n)']),...
RiskFree/100,...
eval([name,'.Lifespan(n)'])/252,...
eval([name,'.Bid(n)'])+.01,...
10,...
0,...
1e-15,...
eval([name,'.Type(n)'])...
eval([name,'.BidIV(n,1) = double(BidIV);']);
%Loop and add implied volatility (BidIV) to a column with n number of
%rows.
The problem arises with the 'eval()' calculation in the parfor loop. Mathworks suggested that I should turn the whole script into a function, and then call the function within the parfor loop.
While I work on this, any ideas?
Instead of calling eval
all the time, you can call it once outside the loop, e.g. data = eval(name)
, and then use data.Strike
etc inside the parfor
loop.
To avoid calling eval
at all, do the following:
%# load mat-file contents into structure allData, where
%# each variable becomes a field
allData = load('/home/arreat/Casino/names.mat');
data = allData.(name);
–
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