How to Add Moving Averages in TradingView
A step-by-step guide to adding and configuring moving averages in TradingView for better technical analysis.
Last Updated: March 19, 2025
The Arnaud Legoux Moving Average (ALMA) uses Gaussian distribution to filter market noise, providing a smoother trend line than traditional moving averages
Three key ALMA settings—Window Size (50 recommended), Offset (0.85 default), and Sigma (6 default)—allow for customization based on trading style and market conditions
Compared to HMA (Hull Moving Average), ALMA provides smoother signals with less sensitivity to price changes, making it ideal for trend confirmation
ALMA can be effectively used for trend following (price above/below ALMA) and as dynamic support/resistance levels in different market conditions
For optimal results, adjust ALMA settings based on asset volatility—reduce Window Size for cryptocurrencies and volatile assets, and maintain default or higher settings for stable assets like major forex pairs
The Arnaud Legoux Moving Average (ALMA) offers traders a powerful advantage: exceptional trend clarity with minimal lag. Unlike standard moving averages, ALMA's unique Gaussian approach filters market noise while maintaining responsiveness. In this guide, we'll show you how to optimize ALMA settings for any market, from cryptocurrencies to stocks, and develop strategies that enhance your trading precision.
This blog post can be watched in video format on the Mind Math Money YouTube channel!
The Arnaud Legoux Moving Average (ALMA) is a type of moving average that aims to filter out market noise and enhance the trend detection capabilities of traditional moving averages. Unlike the Simple Moving Average (SMA) or the Exponential Moving Average (EMA), ALMA employs Gaussian distribution in its calculation, providing a smoother and more responsive trend line.
Smoothness: ALMA provides a smooth curve that reduces the impact of short-term fluctuations.
Responsiveness: Adjusting the settings can enhance the indicator's ability to react to price changes.
To get started with ALMA, you need to add the indicator to your charting platform. Here’s a step-by-step guide:
Open the Indicators Tab: Go to the indicators tab on your charting software.
Search for ALMA: Type "ALMA" in the search bar.
Select the Indicator: Choose the "Arnaud Legoux Moving Average" from the list.
ALMA Indicator in TradingView (Arnaud Legoux Moving Average)
The ALMA indicator comes with three primary settings: Window Size, Offset, and Sigma.
Window Size: Similar to the length setting in other moving averages, this determines the number of periods the indicator considers. Set this to 50 to match the Hull Moving Average (HMA) for comparison.
Offset: This parameter shifts the window, influencing the smoothness and lag. The default setting is 0.85.
Sigma: Controls the Gaussian distribution, affecting the curve’s smoothness. The default value is 6.
For optimal performance, it’s recommended to start with the default settings and adjust based on your trading strategy.
ALMA Settings
Unlike SMA and EMA, which use simple arithmetic and exponential calculations, ALMA’s Gaussian distribution offers a unique blend of smoothness and responsiveness. This makes ALMA particularly useful for traders looking to minimize noise and focus on the underlying trend.
When compared to HMA, ALMA shows a smoother curve with less sensitivity to price changes. While HMA might react faster to market movements, ALMA’s smoother line can provide better trend confirmation and support/resistance levels.
To visualize the differences, overlay the ALMA and HMA on a price chart. You’ll notice:
Smoothness: ALMA is smoother than HMA, providing clearer trend signals.
Responsiveness: HMA reacts quicker to price changes, which can be advantageous for short-term trading but may lead to false signals.
For trend-following strategies, ALMA’s smooth curve can help identify the primary trend. When the price is above the ALMA line, it indicates an uptrend, and when it’s below, a downtrend.
ALMA can act as a dynamic support and resistance level. During an uptrend, the price often finds support at the ALMA line, while in a downtrend, it acts as resistance.
For enhanced trading signals, combine ALMA with other indicators like Relative Strength Index (RSI) or Moving Average Convergence Divergence (MACD). This multi-indicator approach can confirm trends and reduce false signals.
For highly volatile assets like cryptocurrencies, consider reducing the Window Size for a more responsive ALMA line. This helps in capturing quick price movements.
For more stable assets like major Forex pairs or blue-chip stocks, stick to the default settings or increase the Window Size for a smoother curve, focusing on long-term trends.
The Arnaud Legoux Moving Average (ALMA) stands apart from other moving averages through its use of Gaussian distribution in calculations. Unlike SMA (Simple Moving Average) or EMA (Exponential Moving Average), ALMA applies a Gaussian filter to price data, creating a unique balance between smoothness and responsiveness. This distribution-based approach effectively reduces market noise while maintaining sensitivity to significant price movements, making it particularly valuable for identifying clearer trend signals with fewer false alarms.
For day trading, optimal ALMA settings typically include a shorter Window Size between 9-21 periods to capture intraday movements, an Offset of 0.75-0.85 (slightly lower than default to increase responsiveness), and a Sigma of 4-6. These adjustments create a more responsive indicator suitable for shorter timeframes while maintaining enough smoothness to filter out market noise. However, the ideal settings may vary depending on the specific asset being traded and market volatility, so it's recommended to test and fine-tune these parameters on historical data first.
Yes, ALMA works exceptionally well for swing trading. For this trading style, use a Window Size of 50-100 periods to capture the intermediate trend, keep the Offset at the default 0.85 or slightly higher (0.85-0.9) for smoothness, and maintain Sigma at 6. These settings help identify the underlying trend direction while filtering out short-term fluctuations that aren't relevant to swing traders. ALMA can serve as both a trend indicator and a dynamic support/resistance level for determining potential entry and exit points during multi-day or multi-week positions.
ALMA works well in combination with momentum indicators like RSI or MACD to confirm trends and identify potential reversal points. For example, you can use ALMA to determine the overall trend direction, then use RSI to identify overbought or oversold conditions within that trend. Another effective approach is using two ALMA lines with different periods (e.g., 21 and 50) to create a moving average crossover system. Additionally, combining ALMA with volume indicators like On-Balance Volume (OBV) can provide insights into the strength behind price movements, further validating trend signals.
For cryptocurrency trading, which typically involves higher volatility, adjust ALMA settings to be more responsive while still filtering out excessive noise. A Window Size of 21-34 periods works well for most timeframes, with an Offset of 0.75-0.8 (lower than default to increase responsiveness) and a Sigma of 4-5. These settings create a more reactive ALMA that can better adapt to crypto's rapid price movements. During extremely volatile periods, you might further reduce the Window Size to 14-21 to capture shorter-term trends, while during consolidation phases, increasing it to 50 can help identify the broader trend direction.
The ALMA indicator is a powerful tool for traders seeking a balance between smoothness and responsiveness. By understanding and optimizing its settings, you can enhance your trading strategy and make more informed decisions. Whether you’re trading volatile altcoins or stable stocks, ALMA provides valuable insights into market trends and potential support/resistance levels.
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I bought my first stock at 16, and since then, financial markets have fascinated me. Understanding how human behavior shapes market structure and price action is both intellectually and financially rewarding.
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