CODEWITHSUNDEEP
rquantmod
Luis Rodriguez Fuentes
Luis Rodriguez Fuentes

Reputation: 15

How to download multiple Adjusted closing stock price in the same DataFrame with quantmod?

I would like to download historical Adjusted closing stock prices and save them in the same DataFrame

This was my attempt


library('quantmod')

start <- as.Date("2017-01-01")
end <- as.Date("2017-10-27")

tickers = c('AAPL','TSLA')


i=1

data <- getSymbols(tickers, src = "yahoo", from = start, to = end)
data

for (i in length(tickers)) {
  
  data <- getSymbols(tickers[i], src = "yahoo", from = start, to = end)
  
  Data <- as.data.frame(tickers[i])
  
  Data <- Data[6] #6 is the column of the adjusted price 
  
i=i+1
  
}

How can I make this possible ?

Thank you in advance

Upvotes: 0

Views: 1001

Answers (2)

hvollmeier
hvollmeier

Reputation: 2986

Another alternative:

getSymbols(tickers)    
tail(do.call(merge,lapply(tickers, function(x) Cl(get(x)))))
           AAPL.Close TSLA.Close
2020-11-30     119.05     567.60
2020-12-01     122.72     584.76
2020-12-02     123.08     568.82
2020-12-03     122.94     593.38
2020-12-04     122.25     599.04
2020-12-07     123.75     641.76

If you want a data frame object:

tail(fortify.zoo(do.call(merge,lapply(tickers, function(x) Cl(get(x))))))
          Index AAPL.Close TSLA.Close
3503 2020-11-30     119.05     567.60
3504 2020-12-01     122.72     584.76
3505 2020-12-02     123.08     568.82
3506 2020-12-03     122.94     593.38
3507 2020-12-04     122.25     599.04
3508 2020-12-07     123.75     641.76

If you want the adjusted close use Ad(get(x)) instead of Cl(get(x)).

Upvotes: 3

Blue050205
Blue050205

Reputation: 276

The code set forth below produces a data frame with the adjusted closing prices for Apple and Tesla.

library('quantmod')

start <- as.Date("2017-01-01")
end <- as.Date("2017-10-27")

tickers = c('AAPL','TSLA')
Data <- c()
for (i in 1:length(tickers)) {
  
  data <- getSymbols(tickers[i], src = "yahoo", from = start, to = end, auto.assign = FALSE)[,6]
  Data <- merge.xts(Data, data)
  
}
Data <- as.data.frame(Data)

Upvotes: 1

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