Combining financial time series

Hello!

I'm struggling somewhat with the capability of the inbuilt financial time series object. I have two financial time series, covering the same start/end date range, however it is likely data may be missing from one, or both series. Is there any sensible way I can rebaseline the two series against the union of the date range?

e.g.

fts1 has values for 01/01, 02/01, 03/01, 04/01, 06/01... but has no data for 05/01

fts2 has values for 01/01, 02/01, 04/01, 05/01, 06/01... but has no data for 03/01

I want to rebase the two series, so they both cover the entire date sequence, i.e. 01/01, to 06/01 inclusive

I'm current doing some messy manipulations along the lines of:

• merge the two series - gives me the dates I want, but the data is rubbish, as missing data in one series will be filled with data from the other - not good!
• create a NaN fints object, using an appropriately sized NaN matrix, with the extracted dates and column names from the merged matrix
• remerge one series with the NaN series - now I get the data I want in there, against the full date range
• use fillts(..., 'zero') - fills in blanks in the data with previous value

repeat the last 2 steps, with the other series.

... but I'm sure there must be a cleaner way to do this!

Here's the code:

columnNames = fieldnames(fts1, 1)';

      tempFts = merge(fts1, fts2, 'SortColumns', '0');
      tempData = nan(length(tempFts), length(columnNames));
      datetimes = getfield(tempFts, 'dates') + getfield(tempFts, 'times');

      tempFts = fints(datetimes, tempData, columnNames);
      i1 = fillts(merge(tempFts, fts1, 'SortColumns', '0'), 'zero');   
      i2 = fillts(merge(tempFts, fts2, 'SortColumns', '0'), 'zero');