In the vast universe of technical indicators, Arnaud Legoux Moving Average, often known as ALMA, holds a unique place. Unlike conventional moving averages, ALMA uses Gaussian distribution as weights, offering an advantageous tradeoff between smoothness and responsiveness. This tutorial will offer an in-depth look at the ** ta.alma** function in Pine Script, showcasing how to use it effectively in your scripts.

**What is **`ta.alma`

?

`ta.alma`

?** ta.alma** is a built-in function in Pine Script that calculates the Arnaud Legoux Moving Average. This function has two overloads:

ta.alma(series, length, offset, sigma) → series float ta.alma(series, length, offset, sigma, floor) → series float

Where:

is the data you want to calculate ALMA for. This could be any series of integer or float values, such as close prices of a stock.`series`

is the number of bars to include in the calculation.`length`

is a value that controls the tradeoff between smoothness (values closer to 1) and responsiveness (values closer to 0).`offset`

influences the smoothness of ALMA; the larger the value, the smoother the ALMA.`sigma`

is an optional boolean parameter that determines whether the offset calculation is floored before ALMA is calculated. The default value is false.`floor`

**A Basic **`ta.alma`

Example

`ta.alma`

ExampleHere’s a simple example of how to use ** ta.alma**:

//@version=5 indicator("ta.alma", overlay=true) plot(ta.alma(close, 9, 0.85, 6))

In this script, ** ta.alma** is calculated using the closing price (

**), over 9 bars (**

`close`

**), with an offset of**

`9`

**and a sigma of**

`0.85`

**. The result is plotted on the chart overlay.**

`6`

**An Extended Example: Implementing ALMA without **`ta.alma`

`ta.alma`

While ** ta.alma** is an efficient way to calculate ALMA in Pine Script, it can be instructive to implement the calculation ourselves to better understand how it works. Here is a script that implements ALMA without using

**:**

`ta.alma`

//@version=5 indicator("ta.alma", overlay=true) plot(ta.alma(close, 9, 0.85, 6)) // same on pine, but much less efficient pine_alma(series, windowsize, offset, sigma) => m = offset * (windowsize - 1) //m = math.floor(offset * (windowsize - 1)) // Used as m when math.floor=true s = windowsize / sigma norm = 0.0 sum = 0.0 for i = 0 to windowsize - 1 weight = math.exp(-1 * math.pow(i - m, 2) / (2 * math.pow(s, 2))) norm := norm + weight sum := sum + series[windowsize - i - 1] * weight sum / norm plot(pine_alma(close, 9, 0.85, 6) , linewidth = 3)

Here, ** pine_alma** is a user-defined function that calculates ALMA. It takes four parameters:

**(the series to calculate ALMA for),**

`series`

**(equivalent to**

`windowsize`

**in**

`length`

**),**

`ta.alma`

**, and**

`offset`

**. The function calculates**

`sigma`

**and**

`m`

**based on these parameters, then computes a weight for each bar in the window. These weights are then used to calculate a weighted sum of the series values, which is finally divided by the total weight (**

`s`

**) to get ALMA.**

`norm`

**Key Takeaways**

The Arnaud Legoux Moving Average (ALMA) is a versatile and powerful tool that can help you make more informed decisions in trading. The use of ** ta.alma** in Pine Script provides a streamlined way to implement this complex calculation in your scripts. While understanding the underlying algorithm might not be necessary for all traders, it can certainly help you gain a deeper understanding of this tool and how it impacts your trading strategies.

**Conclusion**

In this tutorial, we’ve introduced you to the ** ta.alma** function in Pine Script, explained its parameters, and shown how to use it in a basic example. We’ve also provided an extended example where we implemented the ALMA calculation without using

**. Whether you’re a seasoned Pine Script developer or just getting started, understanding how to use tools like ALMA effectively can make a big difference in your trading strategies.**

`ta.alma`