How to convert dataframe into time series?

Neil picture Neil · Mar 14, 2015 · Viewed 117k times · Source

I have one csv file in which I have 2 closing prices of stock(on daily basis)

Dates   Bajaj_close Hero_close
3/14/2013   1854.8  1669.1
3/15/2013   1850.3  1684.45
3/18/2013   1812.1  1690.5
3/19/2013   1835.9  1645.6
3/20/2013   1840    1651.15
3/21/2013   1755.3  1623.3
3/22/2013   1820.65 1659.6
3/25/2013   1802.5  1617.7
3/26/2013   1801.25 1571.85
3/28/2013   1799.55 1542

I want to convert above data into time series format. (start date is 3/14/2013 and end date is 3/13/2015) I have tried this but its giving me some weird output

values <- bajaj_hero[, -1]  (excluded first column i.e date in real dataset)
bajaj_hero_timeseries <- ts(values,start=c(2013,1),end=c(2015,3),frequency=365)

Output is:

           Bajaj_close Hero_close
2013.000     1854.80    1669.10
2013.003     1850.30    1684.45
2013.005     1812.10    1690.50
2013.008     1835.90    1645.60
2013.011     1840.00    1651.15
2013.014     1755.30    1623.30
2013.016     1820.65    1659.60
2013.019     1802.50    1617.70
2013.022     1801.25    1571.85

Answer

WaltS picture WaltS · Mar 15, 2015

R has multiple ways of represeting time series. Since you're working with daily prices of stocks, you may wish to consider that financial markets are closed on weekends and business holidays so that trading days and calendar days are not the same. However, you may need to work with your times series in terms of both trading days and calendar days. For example, daily returns are calculated from sequential daily closing prices regardless of whether a weekend intervenes. But you may also want to do calendar-based reporting such as weekly price summaries. For these reasons the xts package, an extension of zoo, is commonly used with financial data in R. An example of how it could be used with your data follows.

Assuming the data shown in your example is in the dataframe df

  library(xts)
  stocks <- xts(df[,-1], order.by=as.Date(df[,1], "%m/%d/%Y"))
#
#  daily returns
#
   returns <- diff(stocks, arithmetic=FALSE ) - 1
#
#  weekly open, high, low, close reports
#
   to.weekly(stocks$Hero_close, name="Hero")

which gives the output

           Hero.Open Hero.High Hero.Low Hero.Close
2013-03-15    1669.1   1684.45   1669.1    1684.45
2013-03-22    1690.5   1690.50   1623.3    1659.60
2013-03-28    1617.7   1617.70   1542.0    1542.00