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>
>
> # I merged the common dates with this python script
> # http://www-stat.stanford.edu/~jtaylo/courses/stats202/R/chap2_data/merge.py
>
> merged = read.table("http://www-stat.stanford.edu/~jtaylo/courses/stats202/data/merged_indices.csv", sep=',', header=T)
>
> # this will be a scatter plot because I didn't specify type='l'
>
> plot(merged$dow, merged$sp500)
>
>
>
>
> # I merged the common dates with this python script
> # http://www-stat.stanford.edu/~jtaylo/courses/stats202/R/chap2_data/merge.py
> # and added the Yahoo stock price
>
> merged = read.table("http://www-stat.stanford.edu/~jtaylo/courses/stats202/data/merged_indices.csv", sep=',', header=T)
>
> # this will be a scatter plot because I didn't specify type='l'
>
> plot(merged$dow, merged$sp500, pch=23, col='orange')
>
>
>
> # often the log-returns are used rather than the raw score
> # note: there are 850 rows in the merged data
>
> dow_r = log(merged$dow[2:850] / merged$dow[1:849])
> sp_r = log(merged$sp500[2:850] / merged$sp500[1:849])
>
> plot(dow_r, sp_r, pch=23, col='orange')
>
>
>
> # What if we want to see how the DJI influences Yahoo?
>
> yahoo_r = log(merged$yahoo[2:850] / merged$yahoo[1:849])
> plot(dow_r, yahoo_r, pch=23, col='blue')
>
>
>
>
> # Yahoo had a really great day while the rest of the market
> # was sort of flat -- what day was it?
>
> print(merged$date[which.max(yahoo_r)+1])
[1] 2008-02-01
850 Levels: 2006-01-03 2006-01-04 2006-01-05 2006-01-06 ... 2009-05-19
>
> # Take a look: http://www.microsoft.com/presspass/press/2008/feb08/02-01corpnewspr.mspx
>
>
>
> proc.time()
user system elapsed
0.652 0.028 0.775
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