Rate of Change

rate_of_change() is a generic S3 function that preserves the input class: data.frame in, data.frame out; matrix in, matrix out.

rate_of_change() also accepts a double vector, in which case the indicator is calculated directly without column selection. When the result has a single column it is simplified to a double vector; otherwise the full n by k matrix is returned.

Handling of -values

Leading NAs are always produced for the initial lookback period where insufficient data is available. If the input itself contains NAs they are passed through to the underlying C routine, which can cause the entire output to be filled with NAs. Set na.ignore = TRUE to strip NAs before calculation and re-insert them at their original positions in the output.

Usage

rate_of_change(x, cols, n = 10, na.ignore = FALSE, ...)

Arguments

x

An OHLC-V series coercible to data.frame. Alternatively, x may also be supplied as a double vector.

cols

(formula). An optional 1-variable formula selecting columns from x via model.frame. Defaults to ~close.

n

(integer). Lookback period (window size). A positive integer of length 1.

na.ignore

(logical). A logical of length 1. FALSE by default. If TRUE, NAs in the input are stripped before calculation and re-inserted at their original positions in the output.

...

Additional parameters passed into model.frame

Value

An object of same class and length of x:

ROC

double

See also

Other Momentum Indicator: absolute_price_oscillator(), aroon(), aroon_oscillator(), average_directional_movement_index(), average_directional_movement_index_rating(), balance_of_power(), chande_momentum_oscillator(), commodity_channel_index(), directional_movement_index(), extended_moving_average_convergence_divergence(), fast_stochastic(), fixed_moving_average_convergence_divergence(), intraday_movement_index(), minus_directional_indicator(), minus_directional_movement(), momentum(), money_flow_index(), moving_average_convergence_divergence(), percentage_price_oscillator(), plus_directional_indicator(), plus_directional_movement(), ratio_of_change(), relative_strength_index(), stochastic(), stochastic_relative_strength_index(), triple_exponential_average(), ultimate_oscillator(), williams_oscillator()

Author

Serkan Korkmaz

Examples

## load Bitcoin (BTC)
## series
data(BTC, package = "talib")

## calculate the indicator
## for Bitcoin (BTC)
output <- talib::rate_of_change(BTC)

## display the results
utils::tail(output)
#>                            ROC
#> 2024-12-26 01:00:00  -9.824191
#> 2024-12-27 01:00:00 -11.283855
#> 2024-12-28 01:00:00  -5.033286
#> 2024-12-29 01:00:00  -3.918679
#> 2024-12-30 01:00:00  -5.257295
#> 2024-12-31 01:00:00  -3.949353

## visualize the indicator
## with talib::chart()
##
## see ?talib::chart or ?talib::indicator
## for more details
{
 ## chart OHLC-V
 ## series with talib::chart()
 talib::chart(BTC)

 ## chart indicator
 ## with default values
 talib::indicator(
     talib::rate_of_change
 )
}