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toquarterly

Convert to quarterly

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toquarterly is not recommended. Use convert2quarterly instead.

Syntax

newfts = toquarterly(oldfts)
newfts = toquarterly(oldfts,'ParameterName',ParameterValue, ...)

Arguments

oldfts

Financial time series object

Description

newfts = toquarterly(oldfts) converts a financial time series of any frequency to a quarterly frequency. The default quarterly days are the last business day of March, June, September, and December. toquarterly uses holidays.m to determine valid trading days.

Note

If oldfts contains time-of-day information, newfts displays the time-of-day as 00:00 for those days that did not previously exist in oldfts.

Empty ([ ]) passed as inputs for parameter pair values for toquarterly triggers the use of the defaults.

newfts = toquarterly(oldfts,'ParameterName',ParameterValue, ...) accepts parameter name/parameter value pairs as input, as specified in the following table.

Parameter Name

Parameter Value

Description

CalcMethod

CumSum

Returns the cumulative sum of the values between each quarter. Data for missing dates are given the value 0.

 

Exact

Returns the exact value at the end-of-quarter date. No data manipulation occurs.

 

Nearest

(Default) Returns the values located at the end-of-quarter date. If there is missing data, Nearest returns the nearest data point preceding the end-of-quarter date.

 

SimpAvg

Returns an averaged quarterly value that only takes into account dates with data (non-NaN) within each quarter.

 

v21x

This mode is compatible with previous versions of this function (Version 2.1.x and earlier). It returns an averaged end-of-quarter value using a previous toquarterly algorithm. This algorithm takes into account all dates and data. For dates that do not contain any data, the data is assumed to be 0.

Note

If you set CalcMethod to v21x, settings for all the following parameter name/parameter value pairs are not supported.

BusDays

0

Generates a financial time series that ranges from (or between) the first date to the last date in oldfts (includes NYSE nonbusiness days and holidays).

 

1

(Default) Generates a financial time series that ranges from the first date to the last date in oldfts (excludes NYSE nonbusiness days and holidays and weekends based on AltHolidays and Weekend). If an end-of-quarter date falls on a nonbusiness day or NYSE holiday, returns the last business day of the quarter.

NYSE market closures, holidays, and weekends are observed if AltHolidays and Weekend are not supplied or empty ([]).

DateFilter

Absolute

(Default) Returns all quarterly dates between the start and end dates of oldfts. Some dates may be disregarded if BusDays = 1.

Note

The default is to create a time series with every date at the specified periodicity, which is with DateFilter = Absolute. If you use DateFilter = Relative, the endpoint effects do not apply since only your data defines which dates appear in the output time series object.

 

Relative

Returns only quarterly dates that exist in oldfts. Some dates may be disregarded if BusDays = 1.

ED

0

(Default) The end-of-quarter date is the last day (or last business day) of the quarter.

 

1 - 31

Specifies a particular end-of-quarter day. Months that do not contain the specified end-of-quarter day return the last day of the quarter instead (for example, ED = 31 does not exist for February).

EM

1 - 12

Last month of the first quarter. All subsequent quarterly dates are based on this month. The default end-of-first-quarter month is March (3).

EndPtTol

[Begin, End]

Denotes the minimum number of days that constitute an odd quarter at the endpoints of the time series (before the first whole period and after the last whole period).

Begin and End must be -1 or any positive integer greater than or equal to 0.

A single value input for EndPtTol is the same as specifying that single value for Begin and End.

-1   Do not include odd quarter dates and data in calculations.

0    (Default) Include all odd quarter dates and data in calculations.

n   Number of days (any positive integer) that constitute an odd quarter. If there are insufficient days for a complete quarter, the odd quarter dates and data are ignored.

The following diagram is a general depiction of the factors involved in the determination of endpoints for this function.

TimeSpec

First

Returns only the observation that occurs at the first (earliest) time for a specific date.

 

Last

(Default) Returns only the observation that occurs at the last (latest) time for a specific date.

AltHolidays

 

Vector of dates specifying an alternate set of market closure dates.

 

-1

Excludes all holidays.

Weekend

 

Vector of length 7 containing 0's and 1's. The value 1 indicates a weekend day. The first element of this vector corresponds to Sunday. For example, when Saturday and Sunday are weekend days (default) then Weekend = [1 0 0 0 0 0 1].

Examples

collapse all

Open Live Script

This example shows how to transform a time series object from weekly to quarterly values.

Load the data from the file predict_ret_data.mat and use the fints function to create a time series object with a weekly frequency. 

load predict_ret_data.mat
x0 = fints(expdates, expdata, {'Metric'}, 'w', 'Index')
Warning: FINTS is not recommended. Use TIMETABLE instead. For more information, see <a href="matlab:web(fullfile(docroot, 'finance/convert-from-fints-to-timetables.html'))">Convert Financial Time Series Objects (fints) to Timetables</a>.

 
x0 = 
 
    desc:  Index
    freq:  Weekly (2)

    {'dates:  (53)'}    {'Metric:  (53)'}
    {'01-Jan-1999' }    {[      97.8872]}
    {'08-Jan-1999' }    {[      97.0847]}
    {'15-Jan-1999' }    {[     109.6312]}
    {'22-Jan-1999' }    {[     105.5743]}
    {'29-Jan-1999' }    {[     108.4028]}
    {'05-Feb-1999' }    {[     134.4882]}
    {'12-Feb-1999' }    {[     117.5581]}
    {'19-Feb-1999' }    {[     106.6683]}
    {'26-Feb-1999' }    {[     118.2912]}
    {'05-Mar-1999' }    {[     105.6835]}
    {'12-Mar-1999' }    {[     128.5836]}
    {'19-Mar-1999' }    {[     115.1746]}
    {'26-Mar-1999' }    {[     131.2854]}
    {'02-Apr-1999' }    {[     130.7116]}
    {'09-Apr-1999' }    {[     123.1684]}
    {'16-Apr-1999' }    {[     107.2975]}
    {'23-Apr-1999' }    {[      91.5625]}
    {'30-Apr-1999' }    {[      78.5738]}
    {'07-May-1999' }    {[      65.2904]}
    {'14-May-1999' }    {[      70.8581]}
    {'21-May-1999' }    {[      72.4807]}
    {'28-May-1999' }    {[      72.9190]}
    {'04-Jun-1999' }    {[      64.3460]}
    {'11-Jun-1999' }    {[      59.8743]}
    {'18-Jun-1999' }    {[      55.0026]}
    {'25-Jun-1999' }    {[      49.4032]}
    {'02-Jul-1999' }    {[      49.9485]}
    {'09-Jul-1999' }    {[      47.8061]}
    {'16-Jul-1999' }    {[      61.0517]}
    {'23-Jul-1999' }    {[      58.9313]}
    {'30-Jul-1999' }    {[      53.9584]}
    {'06-Aug-1999' }    {[      44.8472]}
    {'13-Aug-1999' }    {[      45.0463]}
    {'20-Aug-1999' }    {[      45.1088]}
    {'27-Aug-1999' }    {[      56.4897]}
    {'03-Sep-1999' }    {[      61.2449]}
    {'10-Sep-1999' }    {[      58.1012]}
    {'17-Sep-1999' }    {[      50.8974]}
    {'24-Sep-1999' }    {[      46.5143]}
    {'01-Oct-1999' }    {[      38.0806]}
    {'08-Oct-1999' }    {[      33.6664]}
    {'15-Oct-1999' }    {[      34.2992]}
    {'22-Oct-1999' }    {[      33.4202]}
    {'29-Oct-1999' }    {[      36.9287]}
    {'05-Nov-1999' }    {[      35.1278]}
    {'12-Nov-1999' }    {[      41.8128]}
    {'19-Nov-1999' }    {[      35.8199]}
    {'26-Nov-1999' }    {[      36.9495]}
    {'03-Dec-1999' }    {[      36.2880]}
    {'10-Dec-1999' }    {[      33.8457]}
    {'17-Dec-1999' }    {[      33.3868]}
    {'24-Dec-1999' }    {[      32.7737]}
    {'31-Dec-1999' }    {[      28.5665]}

Use toquarterly to obtain the quarterly aggregate for the x0 times series. 

x1 = toquarterly(x0)
Warning: FINTS is not recommended. Use convert2quarterly instead.

 
x1 = 
 
    desc:  TOQUARTERLY: Index
    freq:  Quarterly (4)

    {'dates:  (4)'}    {'Metric:  (4)'}
    {'31-Mar-1999'}    {[    131.2854]}
    {'30-Jun-1999'}    {[     49.4032]}
    {'30-Sep-1999'}    {[     46.5143]}
    {'31-Dec-1999'}    {[     28.5665]}
Open Live Script

Load the data from the file predict_ret_data.mat and use the fints function to create a time series object with a weekly frequency. 

load predict_ret_data.mat
x0 = fints(expdates, expdata, {'Metric'}, 'w', 'Index')
Warning: FINTS is not recommended. Use TIMETABLE instead. For more information, see <a href="matlab:web(fullfile(docroot, 'finance/convert-from-fints-to-timetables.html'))">Convert Financial Time Series Objects (fints) to Timetables</a>.

 
x0 = 
 
    desc:  Index
    freq:  Weekly (2)

    {'dates:  (53)'}    {'Metric:  (53)'}
    {'01-Jan-1999' }    {[      97.8872]}
    {'08-Jan-1999' }    {[      97.0847]}
    {'15-Jan-1999' }    {[     109.6312]}
    {'22-Jan-1999' }    {[     105.5743]}
    {'29-Jan-1999' }    {[     108.4028]}
    {'05-Feb-1999' }    {[     134.4882]}
    {'12-Feb-1999' }    {[     117.5581]}
    {'19-Feb-1999' }    {[     106.6683]}
    {'26-Feb-1999' }    {[     118.2912]}
    {'05-Mar-1999' }    {[     105.6835]}
    {'12-Mar-1999' }    {[     128.5836]}
    {'19-Mar-1999' }    {[     115.1746]}
    {'26-Mar-1999' }    {[     131.2854]}
    {'02-Apr-1999' }    {[     130.7116]}
    {'09-Apr-1999' }    {[     123.1684]}
    {'16-Apr-1999' }    {[     107.2975]}
    {'23-Apr-1999' }    {[      91.5625]}
    {'30-Apr-1999' }    {[      78.5738]}
    {'07-May-1999' }    {[      65.2904]}
    {'14-May-1999' }    {[      70.8581]}
    {'21-May-1999' }    {[      72.4807]}
    {'28-May-1999' }    {[      72.9190]}
    {'04-Jun-1999' }    {[      64.3460]}
    {'11-Jun-1999' }    {[      59.8743]}
    {'18-Jun-1999' }    {[      55.0026]}
    {'25-Jun-1999' }    {[      49.4032]}
    {'02-Jul-1999' }    {[      49.9485]}
    {'09-Jul-1999' }    {[      47.8061]}
    {'16-Jul-1999' }    {[      61.0517]}
    {'23-Jul-1999' }    {[      58.9313]}
    {'30-Jul-1999' }    {[      53.9584]}
    {'06-Aug-1999' }    {[      44.8472]}
    {'13-Aug-1999' }    {[      45.0463]}
    {'20-Aug-1999' }    {[      45.1088]}
    {'27-Aug-1999' }    {[      56.4897]}
    {'03-Sep-1999' }    {[      61.2449]}
    {'10-Sep-1999' }    {[      58.1012]}
    {'17-Sep-1999' }    {[      50.8974]}
    {'24-Sep-1999' }    {[      46.5143]}
    {'01-Oct-1999' }    {[      38.0806]}
    {'08-Oct-1999' }    {[      33.6664]}
    {'15-Oct-1999' }    {[      34.2992]}
    {'22-Oct-1999' }    {[      33.4202]}
    {'29-Oct-1999' }    {[      36.9287]}
    {'05-Nov-1999' }    {[      35.1278]}
    {'12-Nov-1999' }    {[      41.8128]}
    {'19-Nov-1999' }    {[      35.8199]}
    {'26-Nov-1999' }    {[      36.9495]}
    {'03-Dec-1999' }    {[      36.2880]}
    {'10-Dec-1999' }    {[      33.8457]}
    {'17-Dec-1999' }    {[      33.3868]}
    {'24-Dec-1999' }    {[      32.7737]}
    {'31-Dec-1999' }    {[      28.5665]}

Use toquarterly with the optional BusDays argument set to 0 to obtain the quarterly cumulative sums for the x0 times series that includes NYSE nonbusiness days and holidays. 

x1 = toquarterly(x0,'CalcMethod','CumSum','Busdays',0)
Warning: FINTS is not recommended. Use convert2quarterly instead.

 
x1 = 
 
    desc:  TOQUARTERLY: Index
    freq:  Quarterly (4)

    {'dates:  (4)'}    {'Metric:  (4)'}
    {'31-Mar-1999'}    {[  1.4763e+03]}
    {'30-Jun-1999'}    {[  1.0415e+03]}
    {'30-Sep-1999'}    {[    679.9459]}
    {'31-Dec-1999'}    {[    490.9659]}

Version History

Introduced before R2006a

See Also

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