MATLAB: Does the cumulative sum of the financial time series change when I covert it from a daily to a monthly series in Financial Toolbox 3.6 (R2009a)

changecumulativedailyfinancialFinancial Toolboxmonthlyseriestime

I created a daily time series and converted it to monthly using the TOMONTHLY function with the 'cumsum' cumulative sum calculation method as follows:

fts2mat(tomonthly(fints(dates,data),'calcmethod','cumsum'))

I noticed that the sum of the monthly data is not equal to the sum of the daily data.

Best Answer

By default, the TOMONTHLY function skips non-business days. Therefore, values associated with non-business days are not included in the cumulative sum.

To include all days, add the 'BusDays' flag and set it to 0.

For example:

fts2mat(tomonthly(fints(dates,data),'calcmethod','cumsum','BusDays',0))

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MATLAB: Do I receive NaN values when I use the TSMOVAVG function in the Financial Time Series Toolbox 2.1 (R14)

This change has been incorporated into the documentation in Release 14 Service Pack 3 (R14SP3). For previous releases, read below for any additional information:

The TSMOVAVG function computes the moving average using a moving window. If the length of the moving average is "n", then, when computing the first n-1 moving average values, the moving averages depend on data before the first available data sample. Therefore, TSMOVAVG treats these moving averages as undefined and assigns NaN values.

There is a bug in the Financial Time Series Toolbox 2.0 (R13SP1) or earlier versions when using the TSMOVAVG function that it does not return NaN values for the first n-1 moving average values.

There are no workarounds.

MATLAB: How to aggregate data on seasonal basis

You can do that by setting new time vector as the 2nd input variable of retime function, like:

t2 = [datetime(1980,12,1):calmonths(3):datetime(1983,2,1)]';
TT2 = retime(TT,t2,'mean');

The result looks like:

>> TT2
TT2 =
9×1 timetable
      t1                A         
  __________    __________________
  1980/12/01    0.55223     0.4327
  1981/03/01    0.46912    0.44696
  1981/06/01    0.47352    0.46669
  1981/09/01    0.51435    0.51787
  1981/12/01    0.47761    0.52672
  1982/03/01    0.51506    0.50781
  1982/06/01    0.51125    0.58926
  1982/09/01      0.491    0.52664
  1982/12/01    0.84221    0.70557

Best Answer

Related Solutions

MATLAB: Do I receive NaN values when I use the TSMOVAVG function in the Financial Time Series Toolbox 2.1 (R14)

MATLAB: How to aggregate data on seasonal basis

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