Title:	Open Access to Cryptocurrency Market Data, Sentiment Indicators and Interactive Charts
Version:	1.3.2
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.
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Encoding:	UTF-8
RoxygenNote:	7.3.2
Suggests:	data.table, knitr, quantmod, rmarkdown, testthat (≥ 3.0.0), tidyverse
Config/testthat/edition:	3
Imports:	cli (≥ 3.6.3), curl (≥ 5.2.1), jsonlite (≥ 1.8.8), lifecycle (≥ 1.0.4), plotly (≥ 4.10.4), TTR (≥ 0.24.4), utils, xts (≥ 0.14.0), zoo (≥ 1.8-12)
Depends:	R (≥ 4.0.0)
LazyData:	true
VignetteBuilder:	knitr
URL:	https://serkor1.github.io/cryptoQuotes/, https://github.com/serkor1/cryptoQuotes
BugReports:	https://github.com/serkor1/cryptoQuotes/issues
NeedsCompilation:	no
Packaged:	2024-11-07 12:08:12 UTC; serkan
Author:	Serkan Korkmaz [cre, aut, ctb, cph], Jonas Cuzulan Hirani [ctb]
Maintainer:	Serkan Korkmaz <serkor1@duck.com>
Repository:	CRAN
Date/Publication:	2024-11-07 12:30:11 UTC

cryptoQuotes: 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.

Author(s)

Maintainer: Serkan Korkmaz serkor1@duck.com (ORCID) [contributor, copyright holder]

Other contributors:

• Jonas Cuzulan Hirani jjh@vive.dk (ORCID) [contributor]

See Also

Useful links:

• https://serkor1.github.io/cryptoQuotes/

• https://github.com/serkor1/cryptoQuotes

• Report bugs at https://github.com/serkor1/cryptoQuotes/issues

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

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())
)

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

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())
)

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

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())
)

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

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)

GET-requests

Description

GET-requests

Usage

GET(url, endpoint = NULL, query = NULL, path = NULL)

Arguments

Value

A list crated by jsonlite::fromJSON()

See Also

Other development tools: chart_layout(), convert_date(), default_dates(), fetch(), flatten(), is.date()

Examples

## Not run: 
  # script start;

  exchange <- "bybit"
  futures  <- FALSE

  # 1) define baseurl
  base_url <- cryptoQuotes:::baseUrl(
    source  = exchange,
    futures = futures
  )

  # 2) define endpoint
  end_point <- cryptoQuotes:::endPoint(
    source  = "bybit",
    futures = futures,
    type    = "ohlc"
  )

  # 2) define actual
  # parameters based on
  # API docs
  queries <- list(
    symbol   = "BTCUSDT",
    category = "spot",
    limit    = 100,
    interval = "D"
  )

  # 3) perform GET request
  cryptoQuotes:::GET(
    url      = base_url,
    endpoint = end_point,
    query    = queries
  )

  # script end;

## End(Not run)

Add eventlines to the chart

Description

A high-level plotly::layout()-function. The function adds shapes and annotations to the main chart().

Usage

add_event(data, ...)

Arguments

Details

The data.frame must include the following columns,

• index integer or date: corresponding to the event timing.

• event character: the event label.

• color character: the color of the event

Value

A plotly::plot_ly()-object with shapes and annotations

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other subchart indicators: fgi(), lsr(), macd(), rsi(), smi(), volume()

Other main chart indicators: alma(), bollinger_bands(), dema(), donchian_channel(), ema(), evwma(), hma(), sma(), vwap(), wma(), zlema()

Examples

# script start;

# 1) Generate random events
# of buys and sells and convert
# to data.frame
#
# Note: tibbles, data.tables are also supported
# but only base R is shown here to avoid
# too many dependencies
set.seed(1903)
event_data <- cryptoQuotes::ATOM[
  sample(
    x = 1:nrow(cryptoQuotes::ATOM),
    size = 2
  )
]

# 1.1) Extract the index
# from the event data
index <- zoo::index(
  event_data
)

# 1.2) Convert the coredata
# into a data.frame
event_data <- as.data.frame(
  zoo::coredata(
    event_data
  )
)

# 1.3) Add the index into the data.frame
# case insensitive
event_data$index <- index

# 1.4) add events to the data.
# here we use Buys and Sells.
event_data$event <- rep(
  x = c('Buy', 'Sell'),
  lenght.out = nrow(event_data)
)

# 1.5) add colors based
# on the event; here buy is colored
# darkgrey, and if the position is closed
# with profit the color is green
event_data$color <- ifelse(
  event_data$event == 'Buy',
  yes = 'darkgrey',
  no  = ifelse(
    test = subset(
        x = event_data,
        event == 'Buy')$close < subset(x = event_data, event == 'Sell')$close,
    yes  = 'green',
    no   = 'red'
  )
)

# 1.6) modify the event to add
# closing price at each event
event_data$event <- paste0(
  event_data$event, ' @', event_data$close
)

# 2) Chart the the klines
# and add the buy and sell events
cryptoQuotes::chart(
  ticker     = cryptoQuotes::ATOM,
  main       = cryptoQuotes::kline(),
  sub        = list(
    cryptoQuotes::volume()
  ),
  indicator = list(
    cryptoQuotes::bollinger_bands()
  ),
  event_data = event_data,
  options = list(
    dark = TRUE,
    deficiency = FALSE
  )
)

# script end;

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,
 ...
)

Arguments

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other moving average indicators: dema(), ema(), evwma(), hma(), sma(), vwap(), wma(), zlema()

Other main chart indicators: add_event(), bollinger_bands(), dema(), donchian_channel(), ema(), evwma(), hma(), sma(), vwap(), wma(), zlema()

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;

Assert truthfulness of conditions before evaluation

Description

This function is a wrapper of stopifnot(), tryCatch() and cli::cli_abort() and asserts the truthfulness of the passed expression(s).

Usage

assert(..., error_message = NULL)

Arguments

Value

NULL if all statements in ... are TRUE

See Also

stopifnot(), cli::cli_abort(), tryCatch()

Examples

## Not run: 
  # script start;

  # 1) unnamed assert
  # expressions
  foo <- function(
    a,
    b) {

    # assert without
    # named expressions
    cryptoQuotes:::assert(
      is.numeric(a),
      is.numeric(b)
    )

    a + b

  }

  # 1.1) returns
  # the regular R error
  # messages in cli-format
  foo(
    a = "1",
    b = "2"
  )

  # 2) named assert
  # expressions
  foo <- function(
    a,
    b) {

    cryptoQuotes:::assert(
      "{.arg a} is not {.cls numeric}" =  is.numeric(a),
      "{.arg a} is not {.cls numeric}" = is.numeric(b)
    )

    a + b

  }

  # 2.2) Returns
  # custom error-messages
  # in cli-format
  foo(
    a = "1",
    b = "2"
  )

  # 3) custom error
  # messages on
  foo <- function(
    a) {

    cryptoQuotes:::assert(
      is.numeric(a),
      error_message = sprintf(
        fmt = "{.val %s} is not a numeric value.",
        a
      )
    )

    a

  }

  # 2.2) Returns
  # custom error-messages with
  # passed values in cli-format
  foo(
    a = "1"
  )

  # script end;

## End(Not run)

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"
)

Arguments

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

See Also

Other supported calls: available_intervals(), available_tickers()

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;

Get available intervals

Description

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

Usage

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

Arguments

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

See Also

Other supported calls: available_exchanges(), available_tickers()

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)

Get actively traded cryptocurrency pairs

Description

Get actively traded cryptocurrency pairs on the available_exchanges().

Usage

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

Arguments

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

See Also

Other supported calls: available_exchanges(), available_intervals()

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)

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',
   ...
)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other main chart indicators: add_event(), alma(), dema(), donchian_channel(), ema(), evwma(), hma(), sma(), vwap(), wma(), zlema()

Examples

# script start;

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

# script end;

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, ...)

Arguments

Value

Returns a xts object.

See Also

Other utility: remove_bound(), split_window(), write_xts()

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;

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()
)

Arguments

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

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other price charts: kline(), ohlc(), pline()

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;

Create a list of layout elements on subcharts

Description

Create a list of layout elements on subcharts

Usage

chart_layout(x, layout_element, layout_attribute)

Arguments

Value

A list of layout elements.

See Also

Other development tools: GET(), convert_date(), default_dates(), fetch(), flatten(), is.date()

Examples

## Not run: 
chart_layout(
  x = 1:plot_list_length,
  layout_element = "yaxis",
  layout_attribute = list(
  gridcolor = if (dark) "#40454c" else  '#D3D3D3' # Was CCCCCC
    )
)

## End(Not run)

Convert dates passed to UNIX

Description

This function converts dates to UNIX time if passed to the API, and converts it to POSIXct from API

Usage

convert_date(x, multiplier)

Arguments

Details

If x is numeric, then the function assumes that its a return value

Value

A vector of same length as x.

See Also

Other development tools: GET(), chart_layout(), default_dates(), fetch(), flatten(), is.date()

Get the minimum and maximum date range

Description

All available_exchanges() have different limitations on the returned data this function is adaptive in nature so enforces compliance on the limits

Usage

default_dates(interval, from = NULL, to = NULL, length = 200, limit = NULL)

Arguments

Value

A vector of minimum and maximum dates.

Author(s)

Serkan Korkmaz

See Also

Other development tools: GET(), chart_layout(), convert_date(), fetch(), flatten(), is.date()

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,
 ...
)

Arguments

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other moving average indicators: alma(), ema(), evwma(), hma(), sma(), vwap(), wma(), zlema()

Other main chart indicators: add_event(), alma(), bollinger_bands(), donchian_channel(), ema(), evwma(), hma(), sma(), vwap(), wma(), zlema()

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;

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',
 ...
)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other main chart indicators: add_event(), alma(), bollinger_bands(), dema(), ema(), evwma(), hma(), sma(), vwap(), wma(), zlema()

Examples

# 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,
 ...
)

Arguments

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other moving average indicators: alma(), dema(), evwma(), hma(), sma(), vwap(), wma(), zlema()

Other main chart indicators: add_event(), alma(), bollinger_bands(), dema(), donchian_channel(), evwma(), hma(), sma(), vwap(), wma(), zlema()

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;

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,
 ...
)

Arguments

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other moving average indicators: alma(), dema(), ema(), hma(), sma(), vwap(), wma(), zlema()

Other main chart indicators: add_event(), alma(), bollinger_bands(), dema(), donchian_channel(), ema(), hma(), sma(), vwap(), wma(), zlema()

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;

Fetch time-based API-endpoint responses

Description

This function is a high-level wrapper around the development tools available and should reduce the amount of coding.

Usage

fetch(ticker, source, futures, interval, type, to, from, ...)

Arguments

Details

This function can only be used to fetch time-based objects, and can therefore not be used to get, for example, available_tickers().

Value

It returns an xts::xts-object from the desired endpoint.

Author(s)

Serkan Korkmaz

See Also

Other development tools: GET(), chart_layout(), convert_date(), default_dates(), flatten(), is.date()

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, ...)

Arguments

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

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other sentiment indicators: lsr()

Other subchart indicators: add_event(), lsr(), macd(), rsi(), smi(), volume()

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)

flatten nested lists

Description

Flatten a nested list, regardless of its level of nesting.

Usage

flatten(x)

Arguments

Value

An unnested list

See Also

Other development tools: GET(), chart_layout(), convert_date(), default_dates(), fetch(), is.date()

Examples

# script start;

# 1) create a nested list
nested_list <- list(
  a = 1,
  b = list(
    c = 2,
    d = 3
  )
)

# 2) flatten the
# nested list
cryptoQuotes:::flatten(
  nested_list
)

# script end;

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
)

Arguments

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 <[xts]>-object containing,

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

See Also

Other get-functions: get_fundingrate(), get_lsratio(), get_openinterest(), get_quote()

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)

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
)

Arguments

Value

An <[xts]>-object containing,

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

See Also

Other get-functions: get_fgindex(), get_lsratio(), get_openinterest(), get_quote()

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)

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
)

Arguments

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,

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

See Also

Other get-functions: get_fgindex(), get_fundingrate(), get_openinterest(), get_quote()

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)

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
)

Arguments

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]>-object containing,

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

See Also

Other get-functions: get_fgindex(), get_fundingrate(), get_lsratio(), get_quote()

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)

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
)

Arguments

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]>-object containing,

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

See Also

Other get-functions: get_fgindex(), get_fundingrate(), get_lsratio(), get_openinterest()

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)

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,
 ...
)

Arguments

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other moving average indicators: alma(), dema(), ema(), evwma(), sma(), vwap(), wma(), zlema()

Other main chart indicators: add_event(), alma(), bollinger_bands(), dema(), donchian_channel(), ema(), evwma(), sma(), vwap(), wma(), zlema()

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;

Check if values are valid dates

Description

This function check is equivalent to is.numeric(), is.logical(), and checks for the date type classes POSIXct, POSIXt and Date. And wether the character vector can be formatted to dates.

Usage

is.date(x)

Arguments

Value

TRUE if its either POSIXct, POSIXt or Date. FALSE otherwise.

See Also

Other development tools: GET(), chart_layout(), convert_date(), default_dates(), fetch(), flatten()

Candlestick Chart

Description

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

Usage

kline(...)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other price charts: chart(), ohlc(), pline()

Examples

# 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, ...)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other sentiment indicators: fgi()

Other subchart indicators: add_event(), fgi(), macd(), rsi(), smi(), volume()

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)

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,
 ...
)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), rsi(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other subchart indicators: add_event(), fgi(), lsr(), rsi(), smi(), volume()

Other momentum indicators: rsi(), smi()

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;

OHLC Barchart

Description

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

Usage

ohlc(...)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other price charts: chart(), kline(), pline()

Examples

# 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", ...)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other price charts: chart(), kline(), ohlc()

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;

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"))

Arguments

Value

Returns an xts-class object with its bounds removed.

See Also

Other utility: calibrate_window(), split_window(), write_xts()

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;

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',
 ...
)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), sma(), smi(), volume(), vwap(), wma(), zlema()

Other subchart indicators: add_event(), fgi(), lsr(), macd(), smi(), volume()

Other momentum indicators: macd(), smi()

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;

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,
 ...
)

Arguments

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), smi(), volume(), vwap(), wma(), zlema()

Other moving average indicators: alma(), dema(), ema(), evwma(), hma(), vwap(), wma(), zlema()

Other main chart indicators: add_event(), alma(), bollinger_bands(), dema(), donchian_channel(), ema(), evwma(), hma(), vwap(), wma(), zlema()

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;

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",
 ...
)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), volume(), vwap(), wma(), zlema()

Other subchart indicators: add_event(), fgi(), lsr(), macd(), rsi(), volume()

Other momentum indicators: macd(), rsi()

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;

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")

Arguments

Value

Returns a list of iteratively restricted xts objects

See Also

Other utility: calibrate_window(), remove_bound(), write_xts()

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;

Chart the trading volume

Description

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

Usage

volume(...)

Arguments

Value

An invisible plotly::plot_ly()-object.

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), vwap(), wma(), zlema()

Other subchart indicators: add_event(), fgi(), lsr(), macd(), rsi(), smi()

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;

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,
 ...
)

Arguments

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), wma(), zlema()

Other moving average indicators: alma(), dema(), ema(), evwma(), hma(), sma(), wma(), zlema()

Other main chart indicators: add_event(), alma(), bollinger_bands(), dema(), donchian_channel(), ema(), evwma(), hma(), sma(), wma(), zlema()

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;

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,
 ...
)

Arguments

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), zlema()

Other moving average indicators: alma(), dema(), ema(), evwma(), hma(), sma(), vwap(), zlema()

Other main chart indicators: add_event(), alma(), bollinger_bands(), dema(), donchian_channel(), ema(), evwma(), hma(), sma(), vwap(), zlema()

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;

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
)

Arguments

Details

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

Author(s)

Serkan Korkmaz

See Also

Other utility: calibrate_window(), remove_bound(), split_window()

Other utility: calibrate_window(), remove_bound(), split_window()

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,
 ...
)

Arguments

Value

A plotly::plot_ly()-object

Author(s)

Serkan Korkmaz

See Also

Other chart indicators: add_event(), alma(), bollinger_bands(), chart(), dema(), donchian_channel(), ema(), evwma(), fgi(), hma(), lsr(), macd(), rsi(), sma(), smi(), volume(), vwap(), wma()

Other moving average indicators: alma(), dema(), ema(), evwma(), hma(), sma(), vwap(), wma()

Other main chart indicators: add_event(), alma(), bollinger_bands(), dema(), donchian_channel(), ema(), evwma(), hma(), sma(), vwap(), wma()

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;