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to.period

Convert time series data to an OHLC series


Description

Convert an OHLC or univariate object to a specified periodicity lower than the given data object. For example, convert a daily series to a monthly series, or a monthly series to a yearly one, or a one minute series to an hourly series.

The result will contain the open and close for the given period, as well as the maximum and minimum over the new period, reflected in the new high and low, respectively.

If volume for a period was available, the new volume will also be calculated.

Usage

to.minutes(x,k,name,...)
to.minutes3(x,name,...)
to.minutes5(x,name,...)
to.minutes10(x,name,...)
to.minutes15(x,name,...)
to.minutes30(x,name,...)
to.hourly(x,name,...)
to.daily(x,drop.time=TRUE,name,...)

to.weekly(x,drop.time=TRUE,name,...)
to.monthly(x,indexAt='yearmon',drop.time=TRUE,name,...)
to.quarterly(x,indexAt='yearqtr',drop.time=TRUE,name,...)
to.yearly(x,drop.time=TRUE,name,...)

to.period(x,
          period = 'months', 
          k = 1, 
          indexAt, 
          name=NULL,
          OHLC = TRUE,
          ...)

Arguments

x

a univariate or OHLC type time-series object

period

period to convert to. See details.

indexAt

convert final index to new class or date. See details

drop.time

remove time component of POSIX datestamp (if any)

k

number of sub periods to aggregate on (only for minutes and seconds)

name

override column names

OHLC

should an OHLC object be returned? (only OHLC=TRUE currently supported)

...

additional arguments

Details

Essentially an easy and reliable way to convert one periodicity of data into any new periodicity. It is important to note that all dates will be aligned to the end of each period by default - with the exception of to.monthly and to.quarterly, which index by ‘yearmon’ and ‘yearqtr’ from the zoo package, respectively.

Valid period character strings include: "seconds", "minutes", "hours", "days", "weeks", "months", "quarters", and "years". These are calculated internally via endpoints. See that function's help page for further details.

To adjust the final indexing style, it is possible to set indexAt to one of the following: ‘yearmon’, ‘yearqtr’, ‘firstof’, ‘lastof’, ‘startof’, or ‘endof’. The final index will then be yearmon, yearqtr, the first time of the period, the last time of the period, the starting time in the data for that period, or the ending time in the data for that period, respectively.

It is also possible to pass a single time series, such as a univariate exchange rate, and return an OHLC object of lower frequency - e.g. the weekly OHLC of the daily series.

Setting drop.time to TRUE (the default) will convert a series that includes a time component into one with just a date index, as the time index is often of little value in lower frequency series.

It is not possible to convert a series from a lower periodicity to a higher periodicity - e.g. weekly to daily or daily to 5 minute bars, as that would require magic.

Value

An object of the original type, with new periodicity.

Note

In order for this function to work properly on OHLC data, it is necessary that the Open, High, Low and Close columns be names as such; including the first letter capitalized and the full spelling found. Internally a call is made to reorder the data into the correct column order, and then a verification step to make sure that this ordering and naming has succeeded. All other data formats must be aggregated with functions such as aggregate and period.apply.

This method should work on almost all time-series-like objects. Including ‘timeSeries’, ‘zoo’, ‘ts’, and ‘irts’. It is even likely to work well for other data structures - including ‘data.frames’ and ‘matrix’ objects.

Internally a call to as.xts converts the original x into the universal xts format, and then re-converts back to the original type.

A special note with respect to ‘ts’ objects. As these are strictly regular they may include NA values. These are stripped for aggregation purposes, though replaced before returning. This inevitably leads to many, many additional ‘NA’ values in the data. It is more beneficial to consider using an ‘xts’ object originally, or converting to one in the function call by means of as.xts.

Author(s)

Jeffrey A. Ryan

Examples

data(sample_matrix)

samplexts <- as.xts(sample_matrix)

to.monthly(samplexts)
to.monthly(sample_matrix)

str(to.monthly(samplexts))
str(to.monthly(sample_matrix))

xts

eXtensible Time Series

v0.12.1
GPL (>= 2)
Authors
Jeffrey A. Ryan [aut, cph], Joshua M. Ulrich [cre, aut], Ross Bennett [ctb], Corwin Joy [ctb]
Initial release

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