Usecase

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Usecase

What happens when Elon Musk Tweets about Dogecoin?

Introduction

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 1 major exchanges are available, see the wiki for more details.

In this vignette we will explore a case study to showcase the capabilities of {cryptoQuotes}; how did the Dogecoin-market react to Elon Musks following tweet,

Tweet by Elon Musk - the timezone is CET.

Cryptocurrency Market Analysis in R

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 get_quotes()-function,

## 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 its magnitude,

## 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.

Charting price action with candlesticks

We can visualize the rally 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
  )
)

Charting price action with event lines

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
  )
)

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.