Problem with missing data in a time series
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Hello, I need a hand on this problem: In an Excel workbook I reported 10 time series (with monthly frequency) of 10 titles that should cover the past 15 years. Unfortunately, not all titles can cover the 15-year time series. For example, a title only goes up to 2003; So in the column of that title, I have the first 5 years with a "Not Available" instead of a value. Once I’have imported the data into Matlab, obviously, in the column of the title with the shorter series appears NaN where there are no values.
Prices xlsread = ('PrezziTitoli.xls')
whos
% Name Size Bytes Class Attributes
%
Prices 182x10% 6360 double
My goal is to estimate the variance-covariance matrix, however, because of the lack of data, the calculation is not possible for me. I thought to an interpolation, before the calculation of the variance-covariance matrix, to cover the values that in Matlab return NaN, for example with a "fillts", but have difficulties in its use.
Can you help?
Thanks
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Shashank Prasanna
2013-1-29
0 个投票
You can use NONCOV to compute the covariance matrix for data with NaN:
3 个评论
Fabrizio Marinelli
2013-1-29
Shashank Prasanna
2013-1-29
Then interpolation is way to go. What is the problem with using fillts? It does require you to create a financial time series object first. If you prefer to just use interp1, check the doc of interp1:
http://www.mathworks.com/help/matlab/ref/interp1.html Unless you provide some code you tried, it will be hard to help.
Fabrizio Marinelli
2013-1-30
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Titus Edelhofer
2013-1-29
0 个投票
Hi,
this answer is more of a general advice rather than answering the question, sorry for that ;-).
I'm not sure that it will make sense to try to go from 2003 back 5 years "guessing" the data. I would assume it makes more sense to restrict yourself to the last 10 years, i.e., where you have all the data and compute the variance-covariance matrix for this time period only ...
Titus
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