I have seen posts about issues with BatchGetSymblols having issues on 4/27 and that some patches have been implemented. I installed the newest version of quantmod per recommendation but i still do not get any price data for 4/28 or 4/29. Anyone else having this issue or found work arounds?
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Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. – Community May 03 '22 at 05:01
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No issues. Both via quantmod, BatchGetSymbols and yfR everything returns the same data.
library(quantmod)
tickers <- c("AAPL", "MSFT")
start <- Sys.Date() - 7
# returns AAPL and MSFT in the environment
getSymbols(tickers, from = start)
AAPL
AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume AAPL.Adjusted
2022-04-25 161.12 163.17 158.46 162.88 96046400 162.88
2022-04-26 162.25 162.34 156.72 156.80 95623200 156.80
2022-04-27 155.91 159.79 155.38 156.57 88063200 156.57
2022-04-28 159.25 164.52 158.93 163.64 130216800 163.64
2022-04-29 161.84 166.20 157.25 157.65 131587100 157.65
MSFT
MSFT.Open MSFT.High MSFT.Low MSFT.Close MSFT.Volume MSFT.Adjusted
2022-04-25 273.29 281.11 270.77 280.72 35678900 280.72
2022-04-26 277.50 278.36 270.00 270.22 46518400 270.22
2022-04-27 282.10 290.97 279.16 283.22 63477700 283.22
2022-04-28 285.19 290.98 281.46 289.63 33646600 289.63
2022-04-29 288.61 289.88 276.50 277.52 37025000 277.52
library(BatchGetSymbols)
out <- BatchGetSymbols(tickers = tickers, first.date = start)
out
$df.control
# A tibble: 2 × 6
ticker src download.status total.obs perc.benchmark.dates threshold.decision
<chr> <chr> <chr> <int> <dbl> <chr>
1 AAPL yahoo OK 5 1 KEEP
2 MSFT yahoo OK 5 1 KEEP
$df.tickers
price.open price.high price.low price.close volume price.adjusted ref.date ticker ret.adjusted.prices
1 161.12 163.17 158.46 162.88 96046400 162.88 2022-04-25 AAPL NA
2 162.25 162.34 156.72 156.80 95623200 156.80 2022-04-26 AAPL -0.037328105
3 155.91 159.79 155.38 156.57 88063200 156.57 2022-04-27 AAPL -0.001466811
4 159.25 164.52 158.93 163.64 130216800 163.64 2022-04-28 AAPL 0.045155468
5 161.84 166.20 157.25 157.65 131587100 157.65 2022-04-29 AAPL -0.036604773
6 273.29 281.11 270.77 280.72 35678900 280.72 2022-04-25 MSFT NA
7 277.50 278.36 270.00 270.22 46518400 270.22 2022-04-26 MSFT -0.037403819
8 282.10 290.97 279.16 283.22 63477700 283.22 2022-04-27 MSFT 0.048108948
9 285.19 290.98 281.46 289.63 33646600 289.63 2022-04-28 MSFT 0.022632596
10 288.61 289.88 276.50 277.52 37025000 277.52 2022-04-29 MSFT -0.041812022
library(yfR)
yfr_out <- yf_get(tickers = tickers,
first_date = start)
yfr_out
# A tibble: 10 × 10
ticker ref_date price_open price_high price_low price_close volume price_adjusted ret_adjusted_prices
* <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AAPL 2022-04-25 161. 163. 158. 163. 96046400 163. NA
2 AAPL 2022-04-26 162. 162. 157. 157. 95623200 157. -0.0373
3 AAPL 2022-04-27 156. 160. 155. 157. 88063200 157. -0.00147
4 AAPL 2022-04-28 159. 165. 159. 164. 130216800 164. 0.0452
5 AAPL 2022-04-29 162. 166. 157. 158. 131587100 158. -0.0366
6 MSFT 2022-04-25 273. 281. 271. 281. 35678900 281. NA
7 MSFT 2022-04-26 278. 278. 270 270. 46518400 270. -0.0374
8 MSFT 2022-04-27 282. 291. 279. 283. 63477700 283. 0.0481
9 MSFT 2022-04-28 285. 291. 281. 290. 33646600 290. 0.0226
10 MSFT 2022-04-29 289. 290. 276. 278. 37025000 278. -0.0418
# … with 1 more variable: ret_closing_prices <dbl>
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