Financial Time Series Toolbox

fillts

Fill missing values in time series

Syntax

• newfts = fillts(oldfts, fill_method)
  newfts = fillts(oldfts, fill_method, newdates)
  newfts = fillts(oldfts, fill_method, newdates, {'T1','T2',...})
  newfts = fillts(oldfts, fill_method, newdates, 'SPAN', {'TS','TE'}, 
  delta)
  newfts = fillts(... sortmode)
  

Arguments

oldfts	Financial time series object
fill_method	(Optional) To fill using an interpolation menthod, enter 'linear '(default), 'cubic', 'spline', 'nearest', or 'pchip'. To fill with a constant, enter that constant.
newdates	(Optional) Column vector of serial dates, a date string, or a column cell array of date strings. If oldfts contains time of day information, newdates must be accompanied by a time vector (newtimes). Otherwise, newdates is assumed to have times of '00:00'.
T1, T2, TS, TE	First time, second time, start time, end time
delta	Time interval in minutes to span between the start time and end time
sortmode	(Optional) Default = 0 (unsorted). 1 = sorted.

Description

newfts = fillts(oldfts, fill_method) replaces missing values (represented by NaN) in the financial time series object oldfts with real values, using either a constant or the interpolation process indicated by fill_method.

newfts = fillts(oldfts, fill_method, newdates) replaces all the missing values on the specified dates newdates added to the financial time series oldfts with new values. The values may be a single constant or values obtained through the interpolation process designated by fill_method. If any of the dates in newdates exists in oldfts, the existing one has precedence.

newfts = fillts(oldfts, fill_method, newdates, {'T1','T2',...}) additionally allows the designation of specific times of day for addition or replacement of data.

newfts = fillts(oldfts, fill_method, newdates, 'SPAN', {'TS','TE'}, delta) is similar to the previous format except that you designate only a start time and an end time. You follow these times with a spanning time interval, delta.

If you specify only one date for newdates, specifying a start and end time generates only times for that specific date.

newfts = fillts(... sortmode) additionally denotes whether you want the order of the dates in the output object to stay the same as in the input object or to be sorted chronologically.

sortmode = 0 (unsorted) appends any new dates to the end. The interpolation process that calculates the values for the new dates works on a sorted object. Upon completion, the existing dates are reordered as they were originally, and the new dates are appended to the end.

sortmode = 1 sorts the output. After interpolation, no reordering of the date sequence occurs.

Examples

Create a financial time series object with missing data in the fourth and fifth rows.

• dates = ['01-Jan-2001';'01-Jan-2001'; '02-Jan-2001';...
           '02-Jan-2001'; '03-Jan-2001';'03-Jan-2001'];
  times = ['11:00';'12:00';'11:00';'12:00';'11:00';'12:00'];
  dates_times = cellstr([dates, repmat(' ',size(dates,1),1),... 
                         times]);
  OpenFts = fints(dates_times,[(1:3)'; nan; nan; 6],{'Data1'},1,... 
  'Open Financial Time Series');
  

OpenFts looks like

• OpenFts = 
   
      desc:  Open Financial Time Series
      freq:  Daily (1)
  
      'dates:  (6)'    'times:  (6)'    'Data1:  (6)'
      '01-Jan-2001'    '11:00'          [          1]
      '     "     '    '12:00'          [          2]
      '02-Jan-2001'    '11:00'          [          3]
      '     "     '    '12:00'          [        NaN]
      '03-Jan-2001'    '11:00'          [        NaN]
      '     "     '    '12:00'          [          6]
  

Example1. Fill the missing data in OpenFts using cubic interpolation.

• FilledFts = fillts(OpenFts,'cubic')
    
  FilledFts = 
    
         desc:  Filled Open Financial Time Series
         freq:  Unknown (0)
   
         'dates:  (6)'    'times:  (6)'    'Data1:  (6)'
         '01-Jan-2001'    '11:00'          [          1]
         '     "     '    '12:00'          [          2]
         '02-Jan-2001'    '11:00'          [          3]
         '     "     '    '12:00'          [     3.0663]
         '03-Jan-2001'    '11:00'          [     5.8411]
         '     "     '    '12:00'          [     6.0000]
  

Example 2. Fill the missing data in OpenFts with a constant value.

• FilledFts = fillts(OpenFts,0.3)
   
  FilledFts = 
   
      desc:  Filled Open Financial Time Series
      freq:  Unknown (0)
  
      'dates:  (6)'    'times:  (6)'    'Data1:  (6)'
      '01-Jan-2001'    '11:00'          [          1]
      '     "     '    '12:00'          [          2]
      '02-Jan-2001'    '11:00'          [          3]
      '     "     '    '12:00'          [     0.3000]
      '03-Jan-2001'    '11:00'          [     0.3000]
      '     "     '    '12:00'          [          6]
  

Example 3. You can use fillts to identify a specific time on a specific day for the replacement of missing data. This example shows how to replace missing data at 12:00 on January 2 and 11:00 on January 3.

• FilltimeFts = fillts(OpenFts,'c',... 
  {'02-Jan-2001';'03-Jan-2001'}, {'12:00';'11:00'},0)
    
  FilltimeFts = 
    
         desc:  Filled Open Financial Time Series
         freq:  Unknown (0)
   
         'dates:  (6)'    'times:  (6)'    'Data1:  (6)'
         '01-Jan-2001'    '11:00'          [          1]
         '     "     '    '12:00'          [          2]
         '02-Jan-2001'    '11:00'          [          3]
         '     "     '    '12:00'          [     3.0663]
         '03-Jan-2001'    '11:00'          [     5.8411]
         '     "     '    '12:00'          [     6.0000]
  

Example 4. Use a spanning time interval to add an additional day to OpenFts.

• SpanFts = fillts(OpenFts,'c','04-Jan-2001','span',... 
                 {'11:00';'12:00'},60,0)
    
  SpanFts = 
    
         desc:  Filled Open Financial Time Series
         freq:  Unknown (0)
   
         'dates:  (8)'    'times:  (8)'    'Data1:  (8)'
         '01-Jan-2001'    '11:00'          [          1]
         '     "     '    '12:00'          [          2]
         '02-Jan-2001'    '11:00'          [          3]
         '     "     '    '12:00'          [     3.0663]
         '03-Jan-2001'    '11:00'          [     5.8411]
         '     "     '    '12:00'          [     6.0000]
         '04-Jan-2001'    '11:00'          [     9.8404]
         '     "     '    '12:00'          [     9.9994]
  

See Also

interp1 in the MATLAB documentation

fieldnames

filter