How to download intraday stock market data with R

Question

All,

I'm looking to download stock data either from Yahoo or Google on 15 - 60 minute intervals for as much history as I can get. I've come up with a crude solution as follows:

library(RCurl)
tmp <- getURL('https://www.google.com/finance/getprices?i=900&p=1000d&f=d,o,h,l,c,v&df=cpct&q=AAPL')
tmp <- strsplit(tmp,'\n')
tmp <- tmp[[1]]
tmp <- tmp[-c(1:8)]
tmp <- strsplit(tmp,',')
tmp <- do.call('rbind',tmp)
tmp <- apply(tmp,2,as.numeric)
tmp <- tmp[-apply(tmp,1,function(x) any(is.na(x))),]

Given the amount of data I'm looking to import, I worry that this could be computationally expensive. I also don't for the life of me, understand how the time stamps are coded in Yahoo and Google.

So my question is twofold--what's a simple, elegant way to quickly ingest data for a series of stocks into R, and how do I interpret the time stamping on the Google/Yahoo files that I would be using?

Answer 1

I will try to answer timestamp question first. Please note this is my interpretation and I could be wrong.

Using the link in your example https://www.google.com/finance/getprices?i=900&p=1000d&f=d,o,h,l,c,v&df=cpct&q=AAPL I get following data :

EXCHANGE%3DNASDAQ
MARKET_OPEN_MINUTE=570
MARKET_CLOSE_MINUTE=960
INTERVAL=900
COLUMNS=DATE,CLOSE,HIGH,LOW,OPEN,VOLUME
DATA=
TIMEZONE_OFFSET=-300
a1357828200,528.5999,528.62,528.14,528.55,129259
1,522.63,528.72,522,528.6499,2054578
2,523.11,523.69,520.75,522.77,1422586
3,520.48,523.11,519.6501,523.09,1130409
4,518.28,520.579,517.86,520.34,1215466
5,518.8501,519.48,517.33,517.94,832100
6,518.685,520.22,518.63,518.85,565411
7,516.55,519.2,516.55,518.64,617281
...
...

Note the first value of first column a1357828200, my intuition was that this has something to do with POSIXct. Hence a quick check :

> as.POSIXct(1357828200, origin = '1970-01-01', tz='EST')
[1] "2013-01-10 14:30:00 EST"

So my intuition seems to be correct. But the time seems to be off. Now we have one more info in the data. TIMEZONE_OFFSET=-300. So if we offset our timestamps by this amount we should get :

as.POSIXct(1357828200-300*60, origin = '1970-01-01', tz='EST')
[1] "2013-01-10 09:30:00 EST"

Note that I didn't know which day data you had requested. But quick check on google finance reveals, those were indeed price levels on 10th Jan 2013.

Remaining values from first column seem to be some sort of offset from first row value.