Financial Toolbox

fints

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Construct financial time series object

Syntax

tsobj = fints(dates_and_data)
tsobj = fints(dates, data)
tsobj = fints(dates, data, datanames)
tsobj = fints(dates, data, datanames, freq)
tsobj = fints(dates, data, datanames, freq, desc)

Arguments

`dates_and_data`	Column-oriented matrix containing one column of dates and a single column for each series of data. In this format, dates must be entered in serial date number format. If the input serial date numbers encode time-of-day information, the output object contains a column labeled `'dates'` containing the date information and another labeled `'times'` containing the time information. You can use the function `today` to enter date information or the function `now` to enter date with time information.
`dates`	Column vector of dates. Dates can be date strings or serial date numbers and can include time of day information. When entering time-of-day information as serial date numbers, the entry must be a column-oriented matrix when multiple entries are present. If the time-of-day information is in string format, the entry must be a column-oriented cell array of dates and times when multiple entries are present. Valid date and time string formats are: `'ddmmmyy hh:mm'` or `'ddmmmyyyy hh:mm'` `'mm/dd/yy hh:mm'` or `'mm/dd/yyyy hh:mm'` `'dd-mmm-yy hh:mm'` or `'dd-mmm-yyyy hh:mm'` `'mmm.dd,yy hh:mm'` or `'mmm.dd,yyyy hh:mm'` Dates and times can initially be separate column-oriented vectors, but they must be concatenated into a single column-oriented matrix before being passed to `fints`. You can use the MATLAB functions `today` and `now` to assist in entering date and time information.
`data`	Column-oriented matrix containing a column for each series of data. The number of values in each data series must match the number of dates. If a mismatch occurs, MATLAB does not generate the financial time series object, and you receive an error message.
`datanames`	Cell array of data series names. Overrides the default data series names. Default data series names are `series1`, `series2`, ... .
`freq`	Frequency indicator. Allowed values are: `UNKNOWN`, `Unknown`, `unknown`, `U`, `u,0` `DAILY`, `Daily`, `daily`, `D`, `d,1` `WEEKLY`, `Weekly`, `weekly`, `W`, `w,2` `MONTHLY`, `Monthly`, `monthly`, `M`, `m`, `3` `QUARTERLY`, `Quarterly`, `quarterly`, `Q`, `q,4` `SEMIANNUAL`, `Semiannual`, `semiannual`, `S`, `s,5` `ANNUAL`, `Annual`, `annual`, `A`, `a`, `6` Default = `Unknown`.
`desc`	String providing descriptive name for financial time series object. Default = `''`.

Note The toolbox supports only hourly and minute time series. Seconds are disregarded when the object is created (for example, 01-jan-2001 12:00:01 is considered to be 01-jan-2001 12:00). If there are duplicate dates and times, fints sorts the dates and times and chooses the first instance of the duplicate dates and times. The other duplicate dates and times are removed from the object along with their corresponding data.

Description

fints constructs a financial time series object. A financial time series object is a MATLAB object that contains a series of dates and one or more series of data. Before you perform an operation on the data, you must set the frequency indicator (freq). You can optionally provide a description (desc) for the time series.

tsobj = fints(dates_and_data) creates a financial time series object containing the dates and data from the matrix dates_and_data. If the dates contain time-of-day information, the object contains an additional series of times. The date series and each data series must each be a column in the input matrix. The names of the data series default to series1, ..., seriesn. The desc and freq fields are set to their defaults.

tsobj = fints(dates, data) generates a financial time series object containing dates from the dates column vector of dates and data from the matrix data. If the dates contain time-of-day information, the object contains an additional series of times. The data matrix must be column-oriented, that is, each column in the matrix is a data series. The names of the series default to series1, ..., seriesn, where n is the total number of columns in data. The desc and freq fields are set to their defaults.

tsobj = fints(dates, data, datanames) additionally allows you to rename the data series. The names are specified in the datanames cell array. The number of strings in datanames must correspond to the number of columns in data. The desc and freq fields are set to their defaults.

tsobj = fints(dates, data, datanames, freq) additionally sets the frequency when you create the object. The desc field is set to its default ''.

tsobj = fints(dates, data, datanames, freq, desc) provides a description string for the financial time series object.

Examples

Example 1. Create a financial time series containing days and data only.

data = [1:6]'

data =

     1
     2
     3
     4
     5
     6

dates = [today:today+5]'

dates =

      731132
      731133
      731134
      731135
      731136
      731137

tsobjkt = fints(dates, data)
 
tsobjkt = 
 
    desc:  (none)
    freq:  Unknown (0)

    'dates:  (6)'    'series1:  (6)'
    '08-Oct-2001'    [            1]
    '09-Oct-2001'    [            2]
    '10-Oct-2001'    [            3]
    '11-Oct-2001'    [            4]
    '12-Oct-2001'    [            5]
    '13-Oct-2001'    [            6]

Example 2. Expand Example 1 to include time-of-day information:

dates = [now:now+5]';

tsobjkt = fints(dates, data)
 
tsobjkt = 
 
    desc:  (none)
    freq:  Unknown (0)

    'dates:  (6)'    'times:  (6)'    'series1:  (6)'
    '08-Oct-2001'    '14:51'          [            1]
    '09-Oct-2001'    '14:51'          [            2]
    '10-Oct-2001'    '14:51'          [            3]
    '11-Oct-2001'    '14:51'          [            4]
    '12-Oct-2001'    '14:51'          [            5]
    '13-Oct-2001'    '14:51'          [            6]

Example 3. Create a financial time series object when dates and times are located in separate vectors.

Step 1. Create a column vector of times in date number format:

times = datenum(datestr(now:1/24+1/24/60:now+6/24+1/24/60,15))

times = 

   0.43750000000000
   0.47986111111111
   0.52222222222222
   0.56458333333333
   0.60694444444444
   0.64930555555556

Step 2. Create a column vector of dates:

dates = [today:today+5]'

dates =

      731133
      731134
      731135
      731136
      731137
      731138

Step 3. Concatenate dates and times into a single matrix:

dates_times = [dates, times]

dates_times =

  1.0e+005 *

   7.31133000000000   0.00000437500000
   7.31134000000000   0.00000479861111
   7.31135000000000   0.00000522222222
   7.31136000000000   0.00000564583333
   7.31137000000000   0.00000606944444
   7.31138000000000   0.00000649305556

Step 4. Create column vector of data:

data = [1:6]'

Step 5. Create the financial time series object:

tsobj = fints(dates_times, data)

tsobj = 
 
    desc:  (none)
    freq:  Unknown (0)

    'dates:  (6)'    'times:  (6)'    'series1:  (6)'
    '09-Oct-2001'    '10:30'          [            1]
    '10-Oct-2001'    '11:31'          [            2]
    '11-Oct-2001'    '12:32'          [            3]
    '12-Oct-2001'    '13:33'          [            4]
    '13-Oct-2001'    '14:34'          [            5]
    '14-Oct-2001'    '15:35'          [            6]

fints

Syntax

Arguments

Description

Examples

See Also