Root Mean Square (RMS)

22 thg 12, 2022

The Root Mean Square (RMS) is a statistical measure of the magnitude of a set of numbers. It is a type of mean, or average, that is calculated by taking the square root of the sum of the squares of a set of numbers, divided by the number of items in the set. The RMS is often used to measure the magnitude of a time-varying signal, such as a waveform or a time series data.

The indicator takes in two input parameters: the source data and the length of the RMS window. The source data can be any time series data, such as the closing price of a security, and the length parameter determines the number of data points used in the RMS calculation.

The script begins by declaring the RMS indicator function and specifying that it should be plotted as an overlay on the chart. The function takes in two parameters: source and length. The source parameter is the time series data that will be used in the RMS calculation, and the length parameter determines the number of data points to include in the calculation.

Next, the script defines the RMS function using a single line of code. The function calculates the RMS by taking the square root of the sum of the squares of the source data, divided by the length. This is done using the built-in math.sqrt, math.sum, and math.pow functions, which respectively calculate the square root, sum, and power of a set of numbers.

Finally, the script defines the source and length input parameters using the input.source and input.int functions. The source parameter is defined as the closing price of the security, and the length parameter is defined as an integer with a default value of 20.

The RMS indicator implemented in this script can be used to measure the magnitude of a time-varying signal. By adjusting the length parameter, users can control the number of data points included in the RMS calculation and fine-tune the indicator to their specific needs.