Package 'cryptoQuotes'

Title:	Open Access to Cryptocurrency Market Data, Sentiment Indicators and Interactive Charts
Description:	This high-level API client provides open access to cryptocurrency market data, sentiment indicators, and interactive charting tools. The data is sourced from major cryptocurrency exchanges via 'curl' and returned in 'xts'-format. The data comes in open, high, low, and close (OHLC) format with flexible granularity, ranging from seconds to months. This flexibility makes it ideal for developing and backtesting trading strategies or conducting detailed market analysis.
Authors:	Serkan Korkmaz [cre, aut, ctb, cph] , Jonas Cuzulan Hirani [ctb]
Maintainer:	Serkan Korkmaz <[email protected]>
License:	GPL (>= 2)
Version:	1.3.2
Built:	2024-11-07 13:56:02 UTC
Source:	https://github.com/serkor1/cryptoquotes

Help Index

Add Arnaud Legoux Moving Average (ALMA) to the chart
USDT Denominated ATOM (ATOMUSDT) 15-Minute Intervals
Get available exchanges
Get available intervals
Get actively traded cryptocurrency pairs
Add Bollinger Bands to the chart
USDT Denominated Bitcoin (BTCUSDT) Weekly Intervals
calibrate the time window of a list of xts objects
Build an interactive financial chart
Add Double Exponential Moving Average (DEMA) to the chart
USDT Denominated DOGECOIN (DOGEUSDT) 1-Minute Intervals
Add Donchian Channels to the chart
Add Exponentially-Weighted Moving Average (EMA) to the chart
Add Elastic Volume-Weighted Moving Average (EVWMA) to the chart
Chart the Fear and Greed Index
Fear and Greed Index (FGI) values for the cryptocurrency market in daily intervals
Get the daily Fear and Greed Index in the cryptocurrency market
Get the funding rate on futures contracts
Get the long to short ratio of a cryptocurrency pair
Get the open interest on perpetual futures contracts
Get the Open, High, Low, Close and Volume data on a cryptocurrency pair
Add Hull Moving Average (HMA) to the chart
Candlestick Chart
Chart the long-short ratio
Chart the Moving Average Convergence Divergence (MACD) indicator
OHLC Barchart
Line Chart
remove upper and lower bounds from an XTS object
Chart the Relative Strength Index (RSI)
Add Simple Moving Average (SMA) indicators to the chart
Chart the Stochastic Momentum Index (SMI)
split xts object iteratively in lists of desired intervals
Chart the trading volume
Add Volume-Weighted Moving Average (VWAP) to the chart
Add Weighted Moving Average (WMA) to the chart
Read and Write xts-objects
Add Zero Lag Exponential Moving Average (ZLEMA) to the chart

Add Arnaud Legoux Moving Average (ALMA) to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with {TTR}'s moving average family of functions. The function adds moving average indicators to the main chart().

Usage

alma(
 price  = "close",
 n      = 9,
 offset = 0.85,
 sigma  = 6,
 ...
)
alma(
 price  = "close",
 n      = 9,
 offset = 0.85,
 sigma  = 6,
 ...
)

Arguments

`price`	A character-vector of length 1. "close" by default The name of the vector to passed into `TTR::ALMA()`.
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`offset`	Percentile at which the center of the distribution should occur.
`sigma`	Standard deviation of the distribution.
`...`	For internal use. Please ignore.

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

Examples

# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;
# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;

USDT Denominated ATOM (ATOMUSDT) 15-Minute Intervals

Description

This dataset contains time-series data for the ATOM (ATOM) denominated in USDT (Tether), captured in 15-minute intervals. The data spans from December 30 to December 31, 2023.

Usage

ATOM
ATOM

Format

An xts::xts()-object with 97 rows and 5 columns,

index: <POSIXct> The time-index
open: <numeric> Opening price
high: <numeric> Highest price
low: <numeric> Lowest price
close: <numeric> Closing price
volume: <numeric> Trading volume

Examples

# Load the dataset
data("ATOM")

# chart
chart(
  ticker = ATOM,
  main = kline(),
  sub = list(volume())
)
# Load the dataset
data("ATOM")

# chart
chart(
  ticker = ATOM,
  main = kline(),
  sub = list(volume())
)

Get available exchanges

Description

Get a vector of all available exchanges passed into the source argument of the get-functions.

Usage

available_exchanges(
   type = "ohlc"
)
available_exchanges(
   type = "ohlc"
)

Arguments

type

character-vector of length 1. One of,

"ohlc" - Available exchanges for Open, High, Low, Close and Volume market data. See the get_quote()-function.
"lsratio" - Available exchanges for Long-Short ratios. See the get_lsratio()-function.
"fundingrate" - Available exchanges for Funding rates. See the get_fundingrate()-function.
"interest" - Available exchanges for Open interest on perpetual contracts on both sides. See the get_openinterest()-function.

Details

The endpoints supported by the available_exchanges() are not uniform, so exchanges available for, say, get_lsratio() is not necessarily the same as those available for get_quote()

Value

An invisible() character-vector containing available exchanges

Author(s)

Serkan Korkmaz

Examples

# script start;

# 1) available exchanges
# on ohlc-v endpoint
cryptoQuotes::available_exchanges(
  type = "ohlc"
  )

# 2) available exchanges
# on long-short ratios
cryptoQuotes::available_exchanges(
  type = "lsratio"
)

# script end;
# script start;

# 1) available exchanges
# on ohlc-v endpoint
cryptoQuotes::available_exchanges(
  type = "ohlc"
  )

# 2) available exchanges
# on long-short ratios
cryptoQuotes::available_exchanges(
  type = "lsratio"
)

# script end;

Get available intervals

Description

Get available intervals for the available_tickers() on the available_exchanges().

Usage

available_intervals(
   source = "binance",
   type   = "ohlc",
   futures = TRUE
)
available_intervals(
   source = "binance",
   type   = "ohlc",
   futures = TRUE
)

Arguments

source

A character-vector of length 1. binance by default. See available_exchanges() for available exchanges.

type

character-vector of length 1. One of,

"ohlc" - Available exchanges for Open, High, Low, Close and Volume market data. See the get_quote()-function.
"lsratio" - Available exchanges for Long-Short ratios. See the get_lsratio()-function.
"fundingrate" - Available exchanges for Funding rates. See the get_fundingrate()-function.
"interest" - Available exchanges for Open interest on perpetual contracts on both sides. See the get_openinterest()-function.

futures

A logical-vector of length 1. TRUE by default. Returns futures market if TRUE, spot market otherwise.

Details

The endpoints supported by the available_exchanges() are not uniform, so exchanges available for, say, get_lsratio() is not necessarily the same as those available for get_quote()

Value

An invisible() character-vector containing the available intervals on the exchange, market and endpoint.

Sample output

#> i Available Intervals at "bybit" (futures):
#> v 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d, 1M, 1w
#> [1] "1m"  "3m"  "5m"  "15m" "30m" "1h"

Author(s)

Serkan Korkmaz

Examples

## Not run: 
  # script start;

  # available intervals
  # at kucoin futures market
  cryptoQuotes::available_intervals(
    source  = 'kucoin',
    futures = TRUE,
    type    = "ohlc"
  )

  # available intervals
  # at kraken spot market
  cryptoQuotes::available_intervals(
    source  = 'kraken',
    futures = FALSE,
    type    = "ohlc"
  )

  # script end;

## End(Not run)
## Not run: 
  # script start;

  # available intervals
  # at kucoin futures market
  cryptoQuotes::available_intervals(
    source  = 'kucoin',
    futures = TRUE,
    type    = "ohlc"
  )

  # available intervals
  # at kraken spot market
  cryptoQuotes::available_intervals(
    source  = 'kraken',
    futures = FALSE,
    type    = "ohlc"
  )

  # script end;

## End(Not run)

Get actively traded cryptocurrency pairs

Description

Get actively traded cryptocurrency pairs on the available_exchanges().

Usage

available_tickers(source = "binance", futures = TRUE)
available_tickers(source = "binance", futures = TRUE)

Arguments

`source`	A character-vector of length 1. `binance` by default. See `available_exchanges()` for available exchanges.
`futures`	A logical-vector of length 1. TRUE by default. Returns futures market if TRUE, spot market otherwise.

Details

The naming-conventions across, and within, available_exchanges() are not necessarily the same. This function lists all actively traded tickers.

Value

A character-vector of actively traded cryptocurrency pairs on the exchange, and the specified market.

Sample output

#> [1] "10000000AIDOGEUSDT"  "1000000BABYDOGEUSDT" "1000000MOGUSDT"     
#> [4] "1000000PEIPEIUSDT"   "10000COQUSDT"        "10000LADYSUSDT"

Author(s)

Serkan Korkmaz

Examples

## Not run: 
  # 1) available tickers
  # in Binance spot market
  head(
    cryptoQuotes::available_tickers(
      source  = 'binance',
      futures = FALSE
    )
  )

  # 2) available tickers
  # on Kraken futures market
  head(
    cryptoQuotes::available_tickers(
      source  = 'kraken',
      futures = TRUE
    )
  )

## End(Not run)



## Not run: 
  # 1) available tickers
  # in Binance spot market
  head(
    cryptoQuotes::available_tickers(
      source  = 'binance',
      futures = FALSE
    )
  )

  # 2) available tickers
  # on Kraken futures market
  head(
    cryptoQuotes::available_tickers(
      source  = 'kraken',
      futures = TRUE
    )
  )

## End(Not run)

Add Bollinger Bands to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with the TTR::BBands()-function. The function adds bollinger bands to the main chart().

Usage

bollinger_bands(
   n = 20,
   sd = 2,
   maType = "SMA",
   color  = '#4682b4',
   ...
)
bollinger_bands(
   n = 20,
   sd = 2,
   maType = "SMA",
   color  = '#4682b4',
   ...
)

Arguments

`n`	Number of periods for moving average.
`sd`	The number of standard deviations to use.
`maType`	A function or a string naming the function to be called.
`color`	A character-vector of length 1. "#4682b4" by default.
`...`	Other arguments to be passed to the `maType` function.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

# script start;

# Charting BTC using
# candlesticks as main
# chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::kline(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;
# script start;

# Charting BTC using
# candlesticks as main
# chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::kline(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;

USDT Denominated Bitcoin (BTCUSDT) Weekly Intervals

Description

This dataset contains time-series data for Bitcoin (BTC) denominated in USDT (Tether), captured in weekly intervals. The data spans from January 1, 2023, to December 31, 2023.

Usage

BTC
BTC

Format

An xts::xts()-object with 52 rows and 5 columns,

index: <POSIXct> The time-index
open: <numeric> Opening price
high: <numeric> Highest price
low: <numeric> Lowest price
close: <numeric> Closing price
volume: <numeric> Trading volume

Examples

# Load the dataset
data("BTC")

# chart
chart(
  ticker = BTC,
  main = kline(),
  sub = list(volume())
)
# Load the dataset
data("BTC")

# chart
chart(
  ticker = BTC,
  main = kline(),
  sub = list(volume())
)

calibrate the time window of a list of xts objects

Description

This function is a high-level wrapper of do.call and lapply which modifies each xts object stored in a list().

Usage

calibrate_window(list, FUN, ...)
calibrate_window(list, FUN, ...)

Arguments

`list`	A list of xts objects.
`FUN`	A function applied to each element of the list
`...`	optional arguments passed to `FUN`.

Value

Returns a xts object.

Examples

# script start;

# 1) check index of BTCUSDT and
# the Fear and Greed Index
setequal(
  zoo::index(BTC),
  zoo::index(FGIndex)
)

# 2) to align the indices,
# we use the convincience functions
# by splitting the FGI by the BTC index.
FGIndex <- cryptoQuotes::split_window(
  xts = cryptoQuotes::FGIndex,
  by  = zoo::index(BTC),

  # Remove upper bounds of the
  # index to avoid overlap between
  # the dates.
  #
  # This ensures that the FGI is split
  # according to start of each weekly
  # BTC candle
  bounds = 'upper'
)

# 3) as splitWindow returns a list
# it needs to passed into calibrateWindow
# to ensure comparability
FGIndex <- cryptoQuotes::calibrate_window(
  list = FGIndex,

  # As each element in the list can include
  # more than one row, each element needs to be aggregated
  # or summarised.
  #
  # using xts::first gives the first element
  # of each list, along with its values
  FUN  = xts::first
)


# 3) check if candles aligns
# accordingly
stopifnot(
  setequal(
    zoo::index(BTC),
    zoo::index(FGIndex)
  )
)


# script end;
# script start;

# 1) check index of BTCUSDT and
# the Fear and Greed Index
setequal(
  zoo::index(BTC),
  zoo::index(FGIndex)
)

# 2) to align the indices,
# we use the convincience functions
# by splitting the FGI by the BTC index.
FGIndex <- cryptoQuotes::split_window(
  xts = cryptoQuotes::FGIndex,
  by  = zoo::index(BTC),

  # Remove upper bounds of the
  # index to avoid overlap between
  # the dates.
  #
  # This ensures that the FGI is split
  # according to start of each weekly
  # BTC candle
  bounds = 'upper'
)

# 3) as splitWindow returns a list
# it needs to passed into calibrateWindow
# to ensure comparability
FGIndex <- cryptoQuotes::calibrate_window(
  list = FGIndex,

  # As each element in the list can include
  # more than one row, each element needs to be aggregated
  # or summarised.
  #
  # using xts::first gives the first element
  # of each list, along with its values
  FUN  = xts::first
)


# 3) check if candles aligns
# accordingly
stopifnot(
  setequal(
    zoo::index(BTC),
    zoo::index(FGIndex)
  )
)


# script end;

Build an interactive financial chart

Description

A high-level plotly::plot_ly()- and plotly::subplot()-wrapper function for building interactive financial charts using the affiliated chart-functions. The chart consists of a main chart, and an optional subchart. The main chart supports overlaying various trading indicators like sma and bollinger_bands.

Usage

chart(
  ticker,
  main = kline(),
  sub = list(),
  indicator = list(),
  event_data = NULL,
  options = list()
)
chart(
  ticker,
  main = kline(),
  sub = list(),
  indicator = list(),
  event_data = NULL,
  options = list()
)

Arguments

`ticker`	An object with Open, High, Low, Close and Volume columns that can be coerced to a `xts::xts()`-object.
`main`	A `plotly::plot_ly()`-function. `kline()` by default.
`sub`	An optional list of `plotly::plot_ly()`-function(s).
`indicator`	An optional list of `plotly::add_lines()`-function(s).
`event_data`	An optional data.frame with event line(s) to be added to the `chart()`. See `add_event()` for more details.
`options`	An optional list of `chart()`-options. See details below.

Details

Options

dark A <logical>-value of length 1. TRUE by default. Sets the overall theme of the chart()
slider A <logical>-value of length 1. FALSE by default. If TRUE, a plotly::rangeslider() is added.
deficiency A <logical>-value of length 1. FALSE by default. If TRUE, all chart()-elements are colorblind friendly
size A <numeric>-value of length 1. The relative size of the main chart. 0.6 by default. Must be between 0 and 1, non-inclusive.
scale A <numeric>-value of length 1. 1 by default. Scales all fonts on the chart.
width A <numeric>-value of length 1. 0.9 by default. Sets the width of all line elements on the chart.
static A <logical>-value of length 1. FALSE by default. If FALSE the chart can be edited, annotated and explored interactively.
palette A <character>-vector of length 1. "hawaii" by default. See hcl.pals() for all possible color palettes.

Charting Events

If event_data is passed, vertical eventlines with appropriate labels and coloring are added to the chart(). This function is rigid, as it will fail if event, label and index columns are not passed.

For more details please see add_event().

Value

A plotly::plot_ly() object.

Sample Output

Author(s)

Serkan Korkmaz

Examples

# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;
# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;

Add Double Exponential Moving Average (DEMA) to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with {TTR}'s moving average family of functions. The function adds moving average indicators to the main chart().

Usage

dema(
 price  = "close",
 n      = 10,
 v      = 1,
 wilder = FALSE,
 ratio  = NULL,
 ...
)
dema(
 price  = "close",
 n      = 10,
 v      = 1,
 wilder = FALSE,
 ratio  = NULL,
 ...
)

Arguments

`price`	A character-vector of length 1. "close" by default. The name of the vector to passed into `TTR::DEMA()`.
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`v`	The 'volume factor' (a number in [0,1]). See Notes.
`wilder`	logical; if `TRUE`, a Welles Wilder type EMA will be calculated; see notes.
`ratio`	A smoothing/decay ratio. `ratio` overrides `wilder` in `EMA`.
`...`	For internal use. Please ignore.

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

Examples

# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;
# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;

USDT Denominated DOGECOIN (DOGEUSDT) 1-Minute Intervals

Description

This dataset contains time-series data for the DOGECOIN (DOGE) denominated in USDT (Tether), captured in 1-minute intervals. The data spans 2022-01-14 07:00:00 CET to 2022-01-14 08:00:00 CET.

Usage

DOGE
DOGE

Format

An xts::xts()-object with 61 rows and 5 columns,

index: <POSIXct> The time-index
open: <numeric> Opening price
high: <numeric> Highest price
low: <numeric> Lowest price
close: <numeric> Closing price
volume: <numeric> Trading volume

Examples

# Load the dataset
data("DOGE")

# chart
chart(
  ticker = DOGE,
  main = kline(),
  sub = list(volume())
)
# Load the dataset
data("DOGE")

# chart
chart(
  ticker = DOGE,
  main = kline(),
  sub = list(volume())
)

Add Donchian Channels to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with the TTR::DonchianChannel()-function. The function adds Donchian Channels to the main chart().

Usage

donchian_channel(
 n = 10,
 include.lag = FALSE,
 color = '#4682b4',
 ...
)
donchian_channel(
 n = 10,
 include.lag = FALSE,
 color = '#4682b4',
 ...
)

Arguments

`n`	Number of periods for moving average.
`include.lag`	Should values be lagged so that today's prices are not included in the calculation? See Note.
`color`	A character-vector of length 1. "#4682b4" by default.
`...`	For internal use. Please ignore.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

# script start;

# Charting BTC using
# candlesticks as main
# chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::kline(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;
# script start;

# Charting BTC using
# candlesticks as main
# chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::kline(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;

Add Exponentially-Weighted Moving Average (EMA) to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with {TTR}'s moving average family of functions. The function adds moving average indicators to the main chart().

Usage

ema(
 price  = "close",
 n      = 10,
 wilder = FALSE,
 ratio  = NULL,
 ...
)
ema(
 price  = "close",
 n      = 10,
 wilder = FALSE,
 ratio  = NULL,
 ...
)

Arguments

`price`	A character-vector of length 1. "close" by default. The name of the vector to passed into `TTR::EMA()`.
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`wilder`	logical; if `TRUE`, a Welles Wilder type EMA will be calculated; see notes.
`ratio`	A smoothing/decay ratio. `ratio` overrides `wilder` in `EMA`.
`...`	For internal use. Please ignore.

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

Examples

# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;
# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;

Add Elastic Volume-Weighted Moving Average (EVWMA) to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with {TTR}'s moving average family of functions. The function adds moving average indicators to the main chart().

Usage

evwma(
 price  = "close",
 n      = 10,
 ...
)
evwma(
 price  = "close",
 n      = 10,
 ...
)

Arguments

`price`	A character-vector of length 1. "close" by default. The name of the vector to passed into `TTR::EVWMA()`
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`...`	For internal use. Please ignore.

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

Examples

# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;
# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;

Chart the Fear and Greed Index

Description

A high-level plotly::plot_ly()-wrapper function. The function adds a subchart with the ⁠fear and greed⁠-index.

Usage

fgi(index, ...)
fgi(index, ...)

Arguments

`index`	A `xts::xts()`-object. See `get_fgindex()` for more details.
`...`	For internal use. Please ignore.

Details

Classification

The Fear and Greed Index goes from 0-100, and can be classified as follows,

0-24, Extreme Fear
25-44, Fear
45-55, Neutral
56-75, Greed
76-100, Extreme Greed

About the Fear and Greed Index

The fear and greed index is a market sentiment indicator that measures investor emotions to gauge whether they are generally fearful (indicating potential selling pressure) or greedy (indicating potential buying enthusiasm).

Source

This index is fetched from alternative.me, and can be different from the one provided by coinmarketcap.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

## Not run: 
  # script start;

  # 1) get the fear and greed index
  # for the last 14 days
  FGIndex <- cryptoQuotes::get_fgindex(
    from = Sys.Date() - 14
  )

  # 2) get the BTC price
  # for the last 14 days
  BTC <- cryptoQuotes::get_quote(
    ticker  = "BTCUSDT",
    source  = "bybit",
    futures = FALSE,
    from    = Sys.Date() - 14
  )

  # 3) chart the daily BTC
  # along side the Fear and
  # Greed Index
  cryptoQuotes::chart(
    ticker = BTC,
    main   = kline(),
    sub    = list(
      fgi(
        FGIndex
      )
    )
  )

  # script end;

## End(Not run)

## Not run: 
  # script start;

  # 1) get the fear and greed index
  # for the last 14 days
  FGIndex <- cryptoQuotes::get_fgindex(
    from = Sys.Date() - 14
  )

  # 2) get the BTC price
  # for the last 14 days
  BTC <- cryptoQuotes::get_quote(
    ticker  = "BTCUSDT",
    source  = "bybit",
    futures = FALSE,
    from    = Sys.Date() - 14
  )

  # 3) chart the daily BTC
  # along side the Fear and
  # Greed Index
  cryptoQuotes::chart(
    ticker = BTC,
    main   = kline(),
    sub    = list(
      fgi(
        FGIndex
      )
    )
  )

  # script end;

## End(Not run)

Fear and Greed Index (FGI) values for the cryptocurrency market in daily intervals

Description

This dataset contains daily values of the Fear and Greed Index for the year 2023, which is used to measure the sentiments of investors in the market. The data spans from January 1, 2023, to December 31, 2023.

Usage

FGIndex
FGIndex

Format

An xts::xts()-object with 364 rows and 1 columns,

index: <POSIXct> The time-index
fgi: <numeric< The daily fear and greed index value

Details

The Fear and Greed Index goes from 0-100, and can be classified as follows,

0-24, Extreme Fear
25-44, Fear
45-55, Neutral
56-75, Greed
76-100, Extreme Greed

Examples

# Load the dataset
data("FGIndex")

# Get a summary of index values
summary(FGIndex)
# Load the dataset
data("FGIndex")

# Get a summary of index values
summary(FGIndex)

Get the daily Fear and Greed Index in the cryptocurrency market

Description

Get the daily fear and greed index.

Usage

get_fgindex(
 from = NULL,
 to   = NULL
)
get_fgindex(
 from = NULL,
 to   = NULL
)

Arguments

`from`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.
`to`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.

Details

Classification

The Fear and Greed Index goes from 0-100, and can be classified as follows,

0-24, Extreme Fear
25-44, Fear
45-55, Neutral
56-75, Greed
76-100, Extreme Greed

About the Fear and Greed Index

Source

This index is fetched from alternative.me, and can be different from the one provided by coinmarketcap.

Value

An <[xts]>-object containing,

`index`	<POSIXct> the time-index
`fgi`	<numeric> the daily fear and greed index value

Sample output

#>                     fgi
#> 2024-05-12 02:00:00  56
#> 2024-05-13 02:00:00  57
#> 2024-05-14 02:00:00  66
#> 2024-05-15 02:00:00  64
#> 2024-05-16 02:00:00  70
#> 2024-05-17 02:00:00  74

Author(s)

Serkan Korkmaz

Examples

## Not run: 
  # script start;

  # 1) get the fear and greed index
  # for the last 7 days
  tail(
    fgi <- cryptoQuotes::get_fgindex(
      from = Sys.Date() - 7
    )
  )

  # script end;

## End(Not run)

## Not run: 
  # script start;

  # 1) get the fear and greed index
  # for the last 7 days
  tail(
    fgi <- cryptoQuotes::get_fgindex(
      from = Sys.Date() - 7
    )
  )

  # script end;

## End(Not run)

Get the funding rate on futures contracts

Description

Get the funding rate on a cryptocurrency pair from the available_exchanges() in any actively traded available_tickers() on the futures markets.

Usage

get_fundingrate(
 ticker,
 source   = 'binance',
 from     = NULL,
 to       = NULL
)
get_fundingrate(
 ticker,
 source   = 'binance',
 from     = NULL,
 to       = NULL
)

Arguments

`ticker`	A character-vector of length 1. See `available_tickers()` for available tickers.
`source`	A character-vector of length 1. `binance` by default. See `available_exchanges()` for available exchanges.
`from`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.
`to`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.

Value

An <[xts]>-object containing,

`index`	<POSIXct> the time-index
`funding_rate`	<numeric> the current funding rate

Sample output

#>                     funding_rate
#> 2024-03-09 17:00:00   0.00026407
#> 2024-03-10 01:00:00   0.00031010
#> 2024-03-10 09:00:00   0.00063451
#> 2024-03-10 17:00:00   0.00054479
#> 2024-03-11 01:00:00   0.00035489
#> 2024-03-11 09:00:00   0.00078428

Author(s)

Serkan Korkmaz

Examples

## Not run: 
# script start;

# 1) check available
# exchanges for funding rates
cryptoQuotes::available_exchanges(
  type = "fundingrate"
  )

# 2) get BTC funding rate
# for the last 7 days
tail(
  BTC <- cryptoQuotes::get_fundingrate(
    ticker = "BTCUSDT",
    source = "binance",
    from   = Sys.Date() - 7
  )
)

# script end;

## End(Not run)
## Not run: 
# script start;

# 1) check available
# exchanges for funding rates
cryptoQuotes::available_exchanges(
  type = "fundingrate"
  )

# 2) get BTC funding rate
# for the last 7 days
tail(
  BTC <- cryptoQuotes::get_fundingrate(
    ticker = "BTCUSDT",
    source = "binance",
    from   = Sys.Date() - 7
  )
)

# script end;

## End(Not run)

Get the long to short ratio of a cryptocurrency pair

Description

Get the long-short ratio for any available_tickers() from the available_exchanges()

Usage

get_lsratio(
   ticker,
   interval = '1d',
   source   = 'binance',
   from     = NULL,
   to       = NULL,
   top      = FALSE
)
get_lsratio(
   ticker,
   interval = '1d',
   source   = 'binance',
   from     = NULL,
   to       = NULL,
   top      = FALSE
)

Arguments

`ticker`	A character-vector of length 1. See `available_tickers()` for available tickers.
`interval`	A character-vector of length 1. `⁠1d⁠` by default. See `available_intervals()` for available intervals.
`source`	A character-vector of length 1. `binance` by default. See `available_exchanges()` for available exchanges.
`from`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.
`to`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.
`top`	A logical vector. FALSE by default. If TRUE it returns the top traders Long-Short ratios.

Details

On time-zones and dates

Values passed to from or to must be coercible by as.Date(), or as.POSIXct(), with a format of either "%Y-%m-%d" or "%Y-%m-%d %H:%M:%S". By default all dates are passed and returned with Sys.timezone().

On returns

If only from is provided 200 pips are returned up to Sys.time(). If only to is provided 200 pips up to the specified date is returned.

Value

An xts::xts-object containing,

`index`	<POSIXct> the time-index
`long`	<numeric> the share of longs
`short`	<numeric> the share of shorts
`ls_ratio`	<numeric> the ratio of longs to shorts

Sample output

#>                       long  short  ls_ratio
#> 2024-05-12 02:00:00 0.6930 0.3070 2.2573290
#> 2024-05-13 02:00:00 0.6637 0.3363 1.9735355
#> 2024-05-14 02:00:00 0.5555 0.4445 1.2497188
#> 2024-05-15 02:00:00 0.6580 0.3420 1.9239766
#> 2024-05-16 02:00:00 0.4868 0.5132 0.9485581
#> 2024-05-17 02:00:00 0.5102 0.4898 1.0416497

Author(s)

Jonas Cuzulan Hirani

Examples

## Not run: 
  # script start;

  LS_BTC <- cryptoQuotes::get_lsratio(
    ticker   = 'BTCUSDT',
    interval = '15m',
    from     = Sys.Date() - 1,
    to       = Sys.Date()
  )

  # end of scrtipt;

## End(Not run)

## Not run: 
  # script start;

  LS_BTC <- cryptoQuotes::get_lsratio(
    ticker   = 'BTCUSDT',
    interval = '15m',
    from     = Sys.Date() - 1,
    to       = Sys.Date()
  )

  # end of scrtipt;

## End(Not run)

Get the open interest on perpetual futures contracts

Description

Get the open interest on a cryptocurrency pair from the available_exchanges() in any actively traded available_tickers() on the FUTURES markets.

Usage

get_openinterest(
 ticker,
 interval = '1d',
 source   = 'binance',
 from     = NULL,
 to       = NULL
)
get_openinterest(
 ticker,
 interval = '1d',
 source   = 'binance',
 from     = NULL,
 to       = NULL
)

Arguments

`ticker`	A character-vector of length 1. See `available_tickers()` for available tickers.
`interval`	A character-vector of length 1. `⁠1d⁠` by default. See `available_intervals()` for available intervals.
`source`	A character-vector of length 1. `binance` by default. See `available_exchanges()` for available exchanges.
`from`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.
`to`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.

Details

On time-zones and dates

On returns

If only from is provided 200 pips are returned up to Sys.time(). If only to is provided 200 pips up to the specified date is returned.

Value

An <[xts]>-object containing,

`index`	<POSIXct> the time-index
`open_interest`	<numeric> open perpetual contracts on both both sides

Sample output

#>                     open_interest
#> 2024-05-12 02:00:00      70961.07
#> 2024-05-13 02:00:00      69740.49
#> 2024-05-14 02:00:00      71110.33
#> 2024-05-15 02:00:00      67758.06
#> 2024-05-16 02:00:00      73614.70
#> 2024-05-17 02:00:00      72377.85

Author(s)

Serkan Korkmaz

Examples

## Not run: 
  # script start;

  # 1) check available
  # exchanges for open interest
  cryptoQuotes::available_exchanges(
    type = 'interest'
    )

  # 2) get BTC funding rate
  # for the last 7 days
  tail(
    BTC <- cryptoQuotes::get_openinterest(
      ticker = "BTCUSDT",
      source = "binance",
      from   = Sys.Date() - 7
    )
  )

  # script end;

## End(Not run)

## Not run: 
  # script start;

  # 1) check available
  # exchanges for open interest
  cryptoQuotes::available_exchanges(
    type = 'interest'
    )

  # 2) get BTC funding rate
  # for the last 7 days
  tail(
    BTC <- cryptoQuotes::get_openinterest(
      ticker = "BTCUSDT",
      source = "binance",
      from   = Sys.Date() - 7
    )
  )

  # script end;

## End(Not run)

Get the Open, High, Low, Close and Volume data on a cryptocurrency pair

Description

Get a quote on a cryptocurrency pair from the available_exchanges() in various available_intervals() for any actively traded available_tickers().

Usage

get_quote(
 ticker,
 source   = 'binance',
 futures  = TRUE,
 interval = '1d',
 from     = NULL,
 to       = NULL
)
get_quote(
 ticker,
 source   = 'binance',
 futures  = TRUE,
 interval = '1d',
 from     = NULL,
 to       = NULL
)

Arguments

`ticker`	A character-vector of length 1. See `available_tickers()` for available tickers.
`source`	A character-vector of length 1. `binance` by default. See `available_exchanges()` for available exchanges.
`futures`	A logical-vector of length 1. TRUE by default. Returns futures market if TRUE, spot market otherwise.
`interval`	A character-vector of length 1. `⁠1d⁠` by default. See `available_intervals()` for available intervals.
`from`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.
`to`	An optional character-, date- or POSIXct-vector of length 1. NULL by default.

Details

On time-zones and dates

On returns

If only from is provided 200 pips are returned up to Sys.time(). If only to is provided 200 pips up to the specified date is returned.

Value

An <[xts]>-object containing,

`index`	<POSIXct> The time-index
`open`	<numeric> Opening price
`high`	<numeric> Highest price
`low`	<numeric> Lowest price
`close`	<numeric> Closing price
`volume`	<numeric> Trading volume

Sample output

#>                        open    high     low   close   volume
#> 2024-05-12 02:00:00 60809.2 61849.4 60557.3 61455.8 104043.9
#> 2024-05-13 02:00:00 61455.7 63440.0 60750.0 62912.1 261927.1
#> 2024-05-14 02:00:00 62912.2 63099.6 60950.0 61550.5 244345.3
#> 2024-05-15 02:00:00 61550.5 66440.0 61316.1 66175.4 365031.7
#> 2024-05-16 02:00:00 66175.4 66800.0 64567.0 65217.7 242455.3
#> 2024-05-17 02:00:00 65217.7 66478.5 65061.2 66218.8  66139.1

Author(s)

Serkan Korkmaz

Examples

## Not run: 
  # script start;

  # get quote on
  # BTCUSDT pair from
  # Binance in 30m
  # intervals from the
  # last 24 hours
  tail(
    BTC <- cryptoQuotes::get_quote(
      ticker   = 'BTCUSDT',
      source   = 'binance',
      interval = '30m',
      futures  = FALSE,
      from     = Sys.Date() - 1
    )
  )

  # script end;

## End(Not run)
## Not run: 
  # script start;

  # get quote on
  # BTCUSDT pair from
  # Binance in 30m
  # intervals from the
  # last 24 hours
  tail(
    BTC <- cryptoQuotes::get_quote(
      ticker   = 'BTCUSDT',
      source   = 'binance',
      interval = '30m',
      futures  = FALSE,
      from     = Sys.Date() - 1
    )
  )

  # script end;

## End(Not run)

Add Hull Moving Average (HMA) to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with {TTR}'s moving average family of functions. The function adds moving average indicators to the main chart().

Usage

hma(
 price  = "close",
 n      = 20,
 ...
)
hma(
 price  = "close",
 n      = 20,
 ...
)

Arguments

`price`	A character-vector of length 1. "close" by default. The name of the vector to passed into `TTR::HMA()`.
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`...`	For internal use. Please ignore.

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

Examples

# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;
# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;

Candlestick Chart

Description

A high-level plotly::plot_ly()-function for charting Open, High, Low and Close prices.

Usage

kline(...)
kline(...)

Arguments

...

For internal use. Please ignore.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

# script start;

# Charting BTC using
# candlesticks as main
# chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::kline(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;
# script start;

# Charting BTC using
# candlesticks as main
# chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::kline(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;

Chart the long-short ratio

Description

A high-level plotly::plot_ly()-wrapper function. The function adds a subchart to the chart with ⁠long-short ratio⁠.

Usage

lsr(ratio, ...)
lsr(ratio, ...)

Arguments

`ratio`	A `xts::xts()`-object. See `get_lsratio()` for more details.
`...`	For internal use. Please ignore.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

## Not run: 
  # script start;

  # 1) long-short ratio
  # on BTCUSDT pair
  LS_BTC <- cryptoQuotes::get_lsratio(
    ticker   = 'BTCUSDT',
    interval = '15m',
    from     = Sys.Date() - 1,
    to       = Sys.Date()
  )

  # 2) BTCSDT in same period
  # as the long-short ratio;
  BTC <- cryptoQuotes::get_quote(
    ticker   = 'BTCUSDT',
    futures  = TRUE,
    interval = '15m',
    from     = Sys.Date() - 1,
    to       = Sys.Date()
  )

  # 3) plot BTCUSDT-pair
  # with long-short ratio
  cryptoQuotes::chart(
    ticker = BTC,
    main   = cryptoQuotes::kline(),
    sub    = list(
      cryptoQuotes::lsr(
        ratio = LS_BTC
      )
    )
  )

  # end of scrtipt;

## End(Not run)

## Not run: 
  # script start;

  # 1) long-short ratio
  # on BTCUSDT pair
  LS_BTC <- cryptoQuotes::get_lsratio(
    ticker   = 'BTCUSDT',
    interval = '15m',
    from     = Sys.Date() - 1,
    to       = Sys.Date()
  )

  # 2) BTCSDT in same period
  # as the long-short ratio;
  BTC <- cryptoQuotes::get_quote(
    ticker   = 'BTCUSDT',
    futures  = TRUE,
    interval = '15m',
    from     = Sys.Date() - 1,
    to       = Sys.Date()
  )

  # 3) plot BTCUSDT-pair
  # with long-short ratio
  cryptoQuotes::chart(
    ticker = BTC,
    main   = cryptoQuotes::kline(),
    sub    = list(
      cryptoQuotes::lsr(
        ratio = LS_BTC
      )
    )
  )

  # end of scrtipt;

## End(Not run)

Chart the Moving Average Convergence Divergence (MACD) indicator

Description

A high-level plotly::plot_ly()- and plotly::add_lines()-function that interacts with the TTR::MACD()-function. The function adds subchart with a TTR::MACD()-indicator.

Usage

macd(
 nFast   = 12,
 nSlow   = 26,
 nSig    = 9,
 maType  = "SMA",
 percent = TRUE,
 ...
)
macd(
 nFast   = 12,
 nSlow   = 26,
 nSig    = 9,
 maType  = "SMA",
 percent = TRUE,
 ...
)

Arguments

`nFast`	Number of periods for fast moving average.
`nSlow`	Number of periods for slow moving average.
`nSig`	Number of periods for signal moving average.
`maType`	Either: A function or a string naming the function to be called. A list with the first component like (1) above, and additional parameters specified as named components. See Examples.
`percent`	logical; if `TRUE`, the percentage difference between the fast and slow moving averages is returned, otherwise the difference between the respective averages is returned.
`...`	For internal use. Please ignore.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;
# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;

OHLC Barchart

Description

A high-level plotly::plot_ly()-function for charting Open, High, Low and Close prices.

Usage

ohlc(...)
ohlc(...)

Arguments

...

For internal use. Please ignore.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

# script start;

# Charting BTC using
# OHLC-bars as main
# chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::ohlc(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;
# script start;

# Charting BTC using
# OHLC-bars as main
# chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::ohlc(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;

Line Chart

Description

A high-level plotly::plot_ly()-function for charting Open, High, Low and Close prices.

Usage

pline(price = "close", ...)
pline(price = "close", ...)

Arguments

`price`	A character-vector of length 1. "close" by default.
`...`	For internal use. Please ignore.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

# script start;

# Charting BTC using
# line charts with closing price
# as main chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::pline(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;
# script start;

# Charting BTC using
# line charts with closing price
# as main chart
cryptoQuotes::chart(
  ticker = BTC,
  main   = cryptoQuotes::pline(),
  sub    = list(
    cryptoQuotes::volume()
  )
)

# script end;

remove upper and lower bounds from an XTS object

Description

The stats::window()-function has inclusive upper and lower bounds, which in some cases is an undesirable feature. This high level function removes the bounds if desired

Usage

remove_bound(xts, bounds = c("upper"))
remove_bound(xts, bounds = c("upper"))

Arguments

`xts`	A xts-object that needs its bounds modified.
`bounds`	A character vector of length 1. Has to be one of `c('upper','lower','both')`. Defaults to Upper.

Value

Returns an xts-class object with its bounds removed.

Examples

# script start;

# 1) check index of BTCUSDT and
# the Fear and Greed Index
setequal(
  zoo::index(BTC),
  zoo::index(FGIndex)
)

# 2) to align the indices,
# we use the convincience functions
# by splitting the FGI by the BTC index.
FGIndex <- cryptoQuotes::split_window(
  xts = cryptoQuotes::FGIndex,
  by  = zoo::index(BTC),

  # Remove upper bounds of the
  # index to avoid overlap between
  # the dates.
  #
  # This ensures that the FGI is split
  # according to start of each weekly
  # BTC candle
  bounds = 'upper'
)

# 3) as splitWindow returns a list
# it needs to passed into calibrateWindow
# to ensure comparability
FGIndex <- cryptoQuotes::calibrate_window(
  list = FGIndex,

  # As each element in the list can include
  # more than one row, each element needs to be aggregated
  # or summarised.
  #
  # using xts::first gives the first element
  # of each list, along with its values
  FUN  = xts::first
)


# 3) check if candles aligns
# accordingly
stopifnot(
  setequal(
    zoo::index(BTC),
    zoo::index(FGIndex)
  )
)


# script end;
# script start;

# 1) check index of BTCUSDT and
# the Fear and Greed Index
setequal(
  zoo::index(BTC),
  zoo::index(FGIndex)
)

# 2) to align the indices,
# we use the convincience functions
# by splitting the FGI by the BTC index.
FGIndex <- cryptoQuotes::split_window(
  xts = cryptoQuotes::FGIndex,
  by  = zoo::index(BTC),

  # Remove upper bounds of the
  # index to avoid overlap between
  # the dates.
  #
  # This ensures that the FGI is split
  # according to start of each weekly
  # BTC candle
  bounds = 'upper'
)

# 3) as splitWindow returns a list
# it needs to passed into calibrateWindow
# to ensure comparability
FGIndex <- cryptoQuotes::calibrate_window(
  list = FGIndex,

  # As each element in the list can include
  # more than one row, each element needs to be aggregated
  # or summarised.
  #
  # using xts::first gives the first element
  # of each list, along with its values
  FUN  = xts::first
)


# 3) check if candles aligns
# accordingly
stopifnot(
  setequal(
    zoo::index(BTC),
    zoo::index(FGIndex)
  )
)


# script end;

Chart the Relative Strength Index (RSI)

Description

A high-level plotly::plot_ly()- and plotly::add_lines()-function that interacts with the TTR::RSI()-function. The function adds a subchart with a TTR::RSI()-indicator.

Usage

rsi(
 price       = "close",
 n           = 14,
 maType      = "SMA",
 upper_limit = 80,
 lower_limit = 20,
 color       = '#4682b4',
 ...
)
rsi(
 price       = "close",
 n           = 14,
 maType      = "SMA",
 upper_limit = 80,
 lower_limit = 20,
 color       = '#4682b4',
 ...
)

Arguments

`price`	Price series that is coercible to xts or matrix.
`n`	Number of periods for moving averages.
`maType`	Either: A function or a string naming the function to be called. A list with the first component like (1) above, and additional parameters specified as named components. See Examples.
`upper_limit`	A numeric-vector of length 1. 80 by default. Sets the upper limit of the TTR::RSI.
`lower_limit`	A numeric-vector of length 1. 20 by default. Sets the lower limit of the TTR::RSI.
`color`	A character-vector of length 1. "#4682b4" by default.
`...`	For internal use. Please ignore.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;
# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;

Add Simple Moving Average (SMA) indicators to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with {TTR}'s moving average family of functions. The function adds moving average indicators to the main chart().

Usage

sma(
 price  = "close",
 n      = 10,
 ...
)
sma(
 price  = "close",
 n      = 10,
 ...
)

Arguments

`price`	A character-vector of length 1. "close" by default. The name of the vector to passed into `TTR::SMA()`.
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`...`	For internal use. Please ignore.

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

Examples

# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;
# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;

Chart the Stochastic Momentum Index (SMI)

Description

A high-level plotly::plot_ly()- and plotly::add_lines()-function that interacts with the TTR::SMI()-function. The function adds a subchart with a TTR::SMI()-indicator.

Usage

smi(
 nFastK = 14,
 nFastD = 3,
 nSlowD = 3,
 maType,
 bounded = TRUE,
 smooth = 1,
 upper_limit = 40,
 lower_limit = -40,
 color = "#4682b4",
 ...
)
smi(
 nFastK = 14,
 nFastD = 3,
 nSlowD = 3,
 maType,
 bounded = TRUE,
 smooth = 1,
 upper_limit = 40,
 lower_limit = -40,
 color = "#4682b4",
 ...
)

Arguments

`nFastK`	Number of periods for fast %K (i.e. the number of past periods to use).
`nFastD`	Number of periods for fast %D (i.e. the number smoothing periods to apply to fast %K).
`nSlowD`	Number of periods for slow %D (i.e. the number smoothing periods to apply to fast %D).
`maType`	Either: A function or a string naming the function to be called. A list with the first component like (1) above, and additional parameters specified as named components. See Examples.
`bounded`	Logical, should current period's values be used in the calculation?
`smooth`	Number of internal smoothing periods to be applied before calculating FastK. See Details.
`upper_limit`	A numeric-vector of length 1. 40 by default. Sets the upper limit of the TTR::SMI.
`lower_limit`	A numeric-vector of length 1. -40 by default. Sets the lower limit of the TTR::SMI.
`color`	A character-vector of length 1. "#4682b4" by default.
`...`	For internal use. Please ignore.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;
# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;

split xts object iteratively in lists of desired intervals

Description

The split_window()-function is a high level wrapper of the stats::window()-function which restricts the intervals between the first and second index value iteratively

Usage

split_window(xts, by, bounds = "upper")
split_window(xts, by, bounds = "upper")

Arguments

`xts`	A xts-object that needs needs to be split.
`by`	A reference `zoo::index()`-object, to be split by.
`bounds`	A character vector of length 1. Has to be one of `c('upper','lower','both')`. Defaults to Upper.

Value

Returns a list of iteratively restricted xts objects

Examples

# script start;

# 1) check index of BTCUSDT and
# the Fear and Greed Index
setequal(
  zoo::index(BTC),
  zoo::index(FGIndex)
)

# 2) to align the indices,
# we use the convincience functions
# by splitting the FGI by the BTC index.
FGIndex <- cryptoQuotes::split_window(
  xts = cryptoQuotes::FGIndex,
  by  = zoo::index(BTC),

  # Remove upper bounds of the
  # index to avoid overlap between
  # the dates.
  #
  # This ensures that the FGI is split
  # according to start of each weekly
  # BTC candle
  bounds = 'upper'
)

# 3) as splitWindow returns a list
# it needs to passed into calibrateWindow
# to ensure comparability
FGIndex <- cryptoQuotes::calibrate_window(
  list = FGIndex,

  # As each element in the list can include
  # more than one row, each element needs to be aggregated
  # or summarised.
  #
  # using xts::first gives the first element
  # of each list, along with its values
  FUN  = xts::first
)


# 3) check if candles aligns
# accordingly
stopifnot(
  setequal(
    zoo::index(BTC),
    zoo::index(FGIndex)
  )
)


# script end;
# script start;

# 1) check index of BTCUSDT and
# the Fear and Greed Index
setequal(
  zoo::index(BTC),
  zoo::index(FGIndex)
)

# 2) to align the indices,
# we use the convincience functions
# by splitting the FGI by the BTC index.
FGIndex <- cryptoQuotes::split_window(
  xts = cryptoQuotes::FGIndex,
  by  = zoo::index(BTC),

  # Remove upper bounds of the
  # index to avoid overlap between
  # the dates.
  #
  # This ensures that the FGI is split
  # according to start of each weekly
  # BTC candle
  bounds = 'upper'
)

# 3) as splitWindow returns a list
# it needs to passed into calibrateWindow
# to ensure comparability
FGIndex <- cryptoQuotes::calibrate_window(
  list = FGIndex,

  # As each element in the list can include
  # more than one row, each element needs to be aggregated
  # or summarised.
  #
  # using xts::first gives the first element
  # of each list, along with its values
  FUN  = xts::first
)


# 3) check if candles aligns
# accordingly
stopifnot(
  setequal(
    zoo::index(BTC),
    zoo::index(FGIndex)
  )
)


# script end;

Chart the trading volume

Description

A high-level plotly::plot_ly()-function. The function adds a subchart with the trading trading.

Usage

volume(...)
volume(...)

Arguments

...

For internal use. Please ignore.

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

Examples

# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;
# script start;

# 1) charting weekly
# BTC using candlesticks
# and indicators
cryptoQuotes::chart(
  ticker     = BTC,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume(),
    cryptoQuotes::macd()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands(),
    cryptoQuotes::sma(),
    cryptoQuotes::alma()
  ),
  options = list(
    dark       = TRUE,
    deficiency = FALSE
  )
)

# script end;

Add Volume-Weighted Moving Average (VWAP) to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with {TTR}'s moving average family of functions. The function adds moving average indicators to the main chart().

Usage

vwap(
 price  = "close",
 n      = 10,
 ratio = NULL,
 ...
)
vwap(
 price  = "close",
 n      = 10,
 ratio = NULL,
 ...
)

Arguments

`price`	A character-vector of length 1. "close" by default. The name of the vector to passed into `TTR::VWAP()`
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`ratio`	A smoothing/decay ratio. `ratio` overrides `wilder` in `EMA`.
`...`	For internal use. Please ignore.

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

Examples

# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;
# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;

Add Weighted Moving Average (WMA) to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with {TTR}'s moving average family of functions. The function adds moving average indicators to the main chart().

Usage

wma(
 price  = "close",
 n      = 10,
 wts    = 1:n,
 ...
)
wma(
 price  = "close",
 n      = 10,
 wts    = 1:n,
 ...
)

Arguments

`price`	A character-vector of length 1. "close" by default. The name of the vector to passed into `TTR::WMA()`.
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`wts`	Vector of weights. Length of `wts` vector must equal the length of `x`, or `n` (the default).
`...`	For internal use. Please ignore.

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

Examples

# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;
# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;

Read and Write `xts`-objects

Description

The write_xts()- and read_xts()-functions are zoo::write.zoo()- and zoo::read.zoo()-wrapper functions.

Usage

# write XTS-object
write_xts(
 x,
 file,
 ...
)

# read XTS-object
read_xts(
file
)
# write XTS-object
write_xts(
 x,
 file,
 ...
)

# read XTS-object
read_xts(
file
)

Arguments

`x`	An <[xts]>-object.
`file`	character string or strings giving the name of the file(s) which the data are to be read from/written to. See `read.table` and `write.table` for more information. Alternatively, in `read.zoo`, `file` can be a `connection` or a `data.frame` (e.g., resulting from a previous `read.table` call) that is subsequently processed to a `"zoo"` series.
`...`	further arguments passed to other functions. In the `read.*.zoo` the arguments are passed to the function specified in `read` (unless `file` is a `data.frame` already). In `write.zoo` the arguments are passed to `write.table`.

Details

When reading and writing <[xts]>-objects the attributes does not follow the object.

Author(s)

Serkan Korkmaz

Add Zero Lag Exponential Moving Average (ZLEMA) to the chart

Description

A high-level plotly::add_lines()-wrapper function that interacts with {TTR}'s moving average family of functions. The function adds moving average indicators to the main chart().

Usage

zlema(
 price  = "close",
 n      = 10,
 ratio = NULL,
 ...
)
zlema(
 price  = "close",
 n      = 10,
 ratio = NULL,
 ...
)

Arguments

`price`	A character-vector of length 1. "close" by default. The name of the vector to passed into `TTR::ZLEMA()`.
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`ratio`	A smoothing/decay ratio. `ratio` overrides `wilder` in `EMA`.
`...`	For internal use. Please ignore.

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

Examples

# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;
# script start;

cryptoQuotes::chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    cryptoQuotes::ema(n = 7),
    cryptoQuotes::sma(n = 14),
    cryptoQuotes::wma(n = 21)
  )
)

# script end;

Package 'cryptoQuotes'

Help Index

Add Arnaud Legoux Moving Average (ALMA) to the chart

Description

Usage

Arguments

Value

Author(s)

See Also

Examples

USDT Denominated ATOM (ATOMUSDT) 15-Minute Intervals

Description

Usage

Format

Examples

Get available exchanges

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

Get available intervals

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

Get actively traded cryptocurrency pairs

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

Add Bollinger Bands to the chart

Description

Usage

Arguments

Value

Author(s)

See Also

Examples

USDT Denominated Bitcoin (BTCUSDT) Weekly Intervals

Description

Usage

Format

Examples

calibrate the time window of a list of xts objects

Description

Usage

Arguments

Value

See Also

Examples

Build an interactive financial chart

Description

Usage

Arguments

Details

Options

Charting Events

Value

Author(s)

See Also

Examples

Add Double Exponential Moving Average (DEMA) to the chart

Description

Usage

Arguments

Value

Author(s)

See Also