Moving Average Bands with Signals [UAlgo]

The "Moving Average Bands with Signals [UAlgo] combines various moving average types with ATR-based bands to help traders identify potential support and resistance levels.
It plots moving average bands with upper and lower support/resistance levels based on the Average True Range (ATR) and user-defined settings.Additionally, the script generates buy/sell signals based on price crossing above or below the bands.

🔶 Key Features

Multiple Moving Average Types:

Supports various moving average calculations including Arnaud Legoux Moving Average (ALMA), Exponential Moving Average (EMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Kaufman Adaptive Moving Average (KAMA), Hull Moving Average (HMA), Least Squares Moving Average (LSMA), Simple Moving Average (SMA), Triangular Moving Average (TMA), Volume-Weighted Moving Average (VWMA), Weighted Moving Average (WMA), and Zero-Lag Moving Average (ZLMA).

Customizable ATR Bands:

Integrates the Average True Range (ATR) to calculate dynamic support and resistance bands around the moving average. The multiplier for the bands is user-adjustable, allowing for finer control over the sensitivity and width of the bands.

Signal Generation:

Provides visual signals on the chart when the price interacts with the support or resistance bands. Users can choose between using the wick or the close price to generate these signals, adding an extra layer of customization based on their trading style.



Flexible Input Parameters:

Allows users to input parameters for moving average length, ATR length, band multiplier, and signal type. Additional settings are available for specific moving average types, such as ALMA's offset and sigma, KAMA's fast and slow periods, and LSMA's offset.

🔶 Disclaimer

This script is provided for educational purposes only and should not be considered financial advice.

Trading financial instruments involves substantial risk and can result in significant financial losses.

The script’s performance in the past is not indicative of future results, and no guarantees are made regarding its accuracy, reliability, or performance.