convert2weekly
Description
Examples
Aggregate Timetable Daily Data to Weekly Periodicity
Apply separate aggregation methods to related variables in a timetable
while maintaining consistency between aggregated results when converting from a daily to a weekly periodicity. You can use convert2weekly
to aggregate both intra-daily data and aggregated daily data. These methods result in equivalent weekly aggregates.
Load a timetable (DataTimeTable
) of simulated stock price data and corresponding logarithmic returns. The data stored in DataTimeTable
is recorded at various times throughout the day on New York Stock Exchange (NYSE) business days from January 1, 2018, to December 31, 2020. The timetable DataTimeTable
also includes NYSE business calendar awareness. If your timetable does not account for nonbusiness days (weekends, holidays, and market closures), add business calendar awareness by using addBusinessCalendar
first.
load("SimulatedStockSeries.mat","DataTimeTable"); head(DataTimeTable)
Time Price Log_Return ____________________ ______ __________ 01-Jan-2018 11:52:48 100 -0.025375 01-Jan-2018 13:23:13 101.14 0.011336 01-Jan-2018 14:45:09 101.5 0.0035531 01-Jan-2018 15:30:30 100.15 -0.01339 02-Jan-2018 10:43:37 99.72 -0.0043028 03-Jan-2018 10:02:21 100.11 0.0039033 03-Jan-2018 11:22:37 103.96 0.037737 03-Jan-2018 13:42:27 107.05 0.02929
Use convert2daily
to aggregate intra-daily prices and returns to daily periodicity. To maintain consistency between prices and returns, for any given trading day, aggregate prices by reporting the last recorded price with "lastvalue"
and aggregate returns by summing all logarithmic returns with "sum"
.
DTTDaily = convert2daily(DataTimeTable,Aggregation=["lastvalue" "sum"]); head(DTTDaily)
Time Price Log_Return ___________ ______ __________ 01-Jan-2018 100.15 -0.023876 02-Jan-2018 99.72 -0.0043028 03-Jan-2018 105.57 0.057008 04-Jan-2018 109.01 0.032065 05-Jan-2018 110.69 0.015294 06-Jan-2018 110.48 -0.001899 07-Jan-2018 113.83 0.029872 08-Jan-2018 116.41 0.022412
Use convert2weekly
to aggregate the data to a weekly periodicity and compare the results of two different aggregation approaches. The first approach computes weekly results by aggregating the daily aggregates and the second approach computes weekly results by directly aggregating the original intra-daily data.
DTTWeekly1 = convert2weekly(DTTDaily,Aggregation=["lastvalue" "sum"]); % Daily to weekly DTTWeekly2 = convert2weekly(DataTimeTable,Aggregation=["lastvalue" "sum"]); % Intra-daily to weekly head(DTTWeekly1)
Time Price Log_Return ___________ ______ ___________ 05-Jan-2018 110.69 0.076188 12-Jan-2018 119.91 0.080008 19-Jan-2018 116.6 -0.027992 26-Jan-2018 118.51 0.016248 02-Feb-2018 120.03 0.012744 09-Feb-2018 117.07 -0.02497 16-Feb-2018 117.06 -8.5423e-05 23-Feb-2018 116.72 -0.0029087
head(DTTWeekly2)
Time Price Log_Return ___________ ______ ___________ 05-Jan-2018 110.69 0.076188 12-Jan-2018 119.91 0.080008 19-Jan-2018 116.6 -0.027992 26-Jan-2018 118.51 0.016248 02-Feb-2018 120.03 0.012744 09-Feb-2018 117.07 -0.02497 16-Feb-2018 117.06 -8.5423e-05 23-Feb-2018 116.72 -0.0029087
Notice that the results of the two approaches are the same and that convert2weekly
reports on Fridays by default. For weeks in which Friday is not an NYSE trading day, the function reports results on the previous business day. In addition, you can use the convert2weekly
optional name-value argument EndOfWeekDay
to specify a different day of the week that ends business weeks.
Input Arguments
TT1
— Data to aggregate to weekly periodicity
timetable
Data to aggregate to a weekly periodicity, specified as a timetable.
Each variable can be a numeric vector (univariate series) or numeric matrix (multivariate series).
Note
NaN
s indicate missing values.Timestamps must be in ascending or descending order.
By default, all days are business days. If your timetable does not account for nonbusiness
days (weekends, holidays, and market closures), add business calendar awareness by using
addBusinessCalendar
first. For example, the following command adds business calendar logic to include only NYSE
business
days.
TT = addBusinessCalendar(TT);
Data Types: timetable
Name-Value Arguments
Specify optional pairs of arguments as
Name1=Value1,...,NameN=ValueN
, where Name
is
the argument name and Value
is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.
Example: TT2 = convert2weekly(TT1,'Aggregation',["lastvalue"
"sum"])
Aggregation
— Aggregation method for TT1
data for intra-week or inter-day aggregation
"lastvalue"
(default) | "sum"
| "prod"
| "mean"
| "min"
| "max"
| "firstvalue"
| character vector | function handle | string vector | cell vector of character vectors or function handles
Aggregation method for TT1
defining how
data is aggregated over business days in an intra-week or
inter-day periodicity, specified as one of the following methods,
a string vector of methods, or a length
numVariables
cell vector of methods,
where numVariables
is the number of variables
in TT1
.
"sum"
— Sum the values in each year or day."mean"
— Calculate the mean of the values in each year or day."prod"
— Calculate the product of the values in each year or day."min"
— Calculate the minimum of the values in each year or day."max"
— Calculate the maximum of the values in each year or day."firstvalue"
— Use the first value in each year or day."lastvalue"
— Use the last value in each year or day.@customfcn
— A custom aggregation method that accepts a table variable and returns a numeric scalar (for univariate series) or row vector (for multivariate series). The function must accept empty inputs[]
.
If you specify a single method, convert2weekly
applies the specified method to all time series in TT1
. If you specify a string vector or cell vector aggregation
, convert2weekly
applies aggregation(
to j
)TT1(:,
; j
)convert2weekly
applies each aggregation method one at a time (for more details, see retime
). For example, consider a daily timetable
representing TT1
with three
variables.
Time AAA BBB CCC ___________ ______ ______ ________________ 01-Jan-2018 100.00 200.00 300.00 400.00 02-Jan-2018 100.03 200.06 300.09 400.12 03-Jan-2018 100.07 200.14 300.21 400.28 04-Jan-2018 100.08 200.16 300.24 400.32 05-Jan-2018 100.25 200.50 300.75 401.00 06-Jan-2018 100.19 200.38 300.57 400.76 07-Jan-2018 100.54 201.08 301.62 402.16 08-Jan-2018 100.59 201.18 301.77 402.36 09-Jan-2018 101.40 202.80 304.20 405.60 10-Jan-2018 101.94 203.88 305.82 407.76 11-Jan-2018 102.53 205.06 307.59 410.12 12-Jan-2018 103.35 206.70 310.05 413.40 13-Jan-2018 103.40 206.80 310.20 413.60 14-Jan-2018 103.91 207.82 311.73 415.64 15-Jan-2018 103.89 207.78 311.67 415.56 16-Jan-2018 104.44 208.88 313.32 417.76 17-Jan-2018 104.44 208.88 313.32 417.76 18-Jan-2018 104.04 208.08 312.12 416.16 19-Jan-2018 104.94 209.88 314.82 419.76
The corresponding default weekly results representing
TT2
(in which all days are business
days and the 'lastvalue'
is reported on
Fridays) are as
follows.
Time AAA BBB CCC ___________ ______ ______ ________________ 05-Jan-2018 100.25 200.50 300.75 401.00 12-Jan-2018 103.35 206.70 310.05 413.40 19-Jan-2018 104.94 209.88 314.82 419.76
The default 'lastvalue'
returns the latest
observed value in a given week for all variables in
TT1
.
All methods omit missing data (NaN
s) in direct aggregation calculations on each variable. However, for situations in which missing values appear in the first row of TT1
, missing values can also appear in the aggregated results TT2
. To address missing data, write and specify a custom aggregation method (function handle) that supports missing data.
Data Types: char
| string
| cell
| function_handle
Daily
— Intra-day aggregation method for TT1
"lastvalue"
(default) | "sum"
| "prod"
| "mean"
| "min"
| "max"
| "firstvalue"
| character vector | function handle | string vector | cell vector of character vectors or function handles
Intra-day aggregation method for TT1
, specified as an aggregation method, a
string vector of methods, or a length numVariables
cell vector of
methods. For more details on supported methods and behaviors, see the
'Aggregation'
name-value argument.
Data Types: char
| string
| cell
| function_handle
EndOfWeekDay
— Day of week that ends business weeks
"Friday"
(weeks end on
Friday) (default) | scalar integer with value 1
through
7
| "Sunday"
| "Monday"
| "Tuesday"
| "Wednesday"
| "Thursday"
| "Friday"
| "Saturday"
| character vector
Day of the week that ends business weeks, specified as a value in the table.
Value | Day Ending Each Week |
---|---|
"Sunday" or
1 | Sunday |
"Monday" or
2 | Monday |
"Tuesday" or
3 | Tuesday |
"Wednesday" or
4 | Wednesday |
"Thursday" or
5 | Thursday |
"Friday" or
6 | Friday |
"Saturday" or
7 | Saturday |
If the specified end-of-week day in a given week is not a business day, the preceding business day ends that week.
Data Types: double
| char
| string
Output Arguments
TT2
— Weekly data
timetable
Weekly data, returned as a timetable. The time arrangement of TT1
and TT2
are the same.
If a variable of TT1
has no business-day records
during an annual period within the sampling time span,
convert2weekly
returns a NaN
for that variable and annual period in TT2
.
If the first week (week1
) of
TT1
contains at least one business day, the
first date in TT2
is the last business date of
week1
. Otherwise, the first date in
TT2
is the next end-of-week business date of
TT1
.
If the last week (weekT
) of
TT1
contains at least one business day, the
last date in TT2
is the last business date of
weekT
. Otherwise, the last date in
TT2
is the previous end-of-week business date
of TT1
.
Version History
Introduced in R2021a
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