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This high-level API
-client provides open access to
cryptocurrency market data without relying on low-level coding and
API
-keys. Currently all actively traded cryptocurrencies on
either binance
, bybit
, bitmart
,
kucoin
and kraken
are available.
In this vignette we will explore a case study to showcase the
capabilities of the cryptoQuotes
-package; how did the
Dogecoin
-market react to Elon Musks following tweet,
Elon Musk tweeted (Well, now he X’ed) about Dogecoin
January 14, 06.18 AM (UTC) - and Dogecoin
rallied. To
determine how fast the markets reacted to his tweets, we could get the
market data for Dogecoin in 1 minute intervals the day he tweeeted using
the getQuotes()
,
## DOGEUSDT the day
## of the tweet on the
## 1m chart
DOGE <- cryptoQuotes::get_quote(
ticker = 'DOGE-USDT',
interval = '1m',
source = 'kucoin',
futures = FALSE,
from = '2022-01-14 07:00:00',
to = '2022-01-14 08:00:00'
)
This returns an object of class xts and zoo with 61 rows. To
calculate the rally within the first minute of the tweet, we can use
xts
-syntax to determine the how much it rallied,
## extrat the
## tweet moment
tweet_moment <- DOGE["2022-01-14 07:18:00"]
## calculate
## rally
cat(
"Doge closed:", round((tweet_moment$close/tweet_moment$open - 1),4) * 100, "%"
)
#> Doge closed: 8.71 %
Dogecoin
rallied 8.71% within the minute Elon Musk
tweeted.
We can illustrate this with candlestick charts using the
chart()
- and kline()
-function,
## chart the
## price action
## using klines
cryptoQuotes::chart(
ticker = DOGE,
main = cryptoQuotes::kline(),
indicator = list(
cryptoQuotes::bollinger_bands()
),
sub = list(
cryptoQuotes::volume()
),
options = list(
dark = FALSE
)
)
#> Warning in call_stack == calling_function: longer object length is not a
#> multiple of shorter object length
To create a, presumably, better visual overview we can add event
lines using the event_data
-argument, which takes a
data.frame
of any kind as argument,
## 1) create event data.frame
## by subsetting the data
event_data <- as.data.frame(
zoo::coredata(
DOGE["2022-01-14 07:18:00"]
)
)
## 1.1) add the index
## to the event_data
event_data$index <- zoo::index(
DOGE["2022-01-14 07:18:00"]
)
# 1.2) add event label
# to the data
event_data$event <- 'Elon Musk Tweets'
# 1.3) add color to the
# event label
event_data$color <- 'steelblue'
This event data, can be passed into the chart as follows,
## 1) chart the
## price action
## using klines
cryptoQuotes::chart(
ticker = DOGE,
event_data = event_data,
main = cryptoQuotes::kline(),
indicator = list(
cryptoQuotes::bollinger_bands()
),
sub = list(
cryptoQuotes::volume()
),
options = list(
dark = FALSE
)
)
#> Warning in call_stack == calling_function: longer object length is not a
#> multiple of shorter object length
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.