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Regularized EMA/RMA/FEMA Cross [Loxx]
Regularized EMA/RMA/FEMA Cross calculates two types of moving averages, Fast REMA and Slow REMA, and uses their crossovers and crossunders to generate buy (Long) and sell (Short) signals for a trading strategy. You have the option of choosing EMA, RMA, or FEMA (Fast Exponential Moving Average) for both the fast and slow REMA separately.
█ Understanding the Regularized Moving Average
The Regularized Moving Average, as conceptualized by Chris Satchwell, offers a more responsive interpretation compared to traditional moving averages. By incorporating a smoothing mechanism using "Lambda", this approach reduces lag without compromising the data's integrity.
In the realm of technical analysis, many regard it as a preferred alternative to the standard Moving Average and Exponential Moving Average.
█ How Does It Stand Out from Other Moving Averages?
While analysts traditionally shorten an indicator's length or period to minimize lag, the Regularized Moving Average uses a unique approach. By embedding "Regularization" within its computation, this method introduces Lambda (often symbolized as λ-calculus). This mathematical factor tames the moving average's undue fluctuations, offering more stability through its Lambda adjustments.
Pro Tip: For those analyzing smaller intraday timeframes, consider ramping up the Lambda setting to 6.0 or even higher. When tweaking these settings, always remember to backtest and observe how it impacts signal accuracy and noise filtering.
█ Extras
-Alerts
-Signals
█ Understanding the Regularized Moving Average
The Regularized Moving Average, as conceptualized by Chris Satchwell, offers a more responsive interpretation compared to traditional moving averages. By incorporating a smoothing mechanism using "Lambda", this approach reduces lag without compromising the data's integrity.
In the realm of technical analysis, many regard it as a preferred alternative to the standard Moving Average and Exponential Moving Average.
█ How Does It Stand Out from Other Moving Averages?
While analysts traditionally shorten an indicator's length or period to minimize lag, the Regularized Moving Average uses a unique approach. By embedding "Regularization" within its computation, this method introduces Lambda (often symbolized as λ-calculus). This mathematical factor tames the moving average's undue fluctuations, offering more stability through its Lambda adjustments.
Pro Tip: For those analyzing smaller intraday timeframes, consider ramping up the Lambda setting to 6.0 or even higher. When tweaking these settings, always remember to backtest and observe how it impacts signal accuracy and noise filtering.
█ Extras
-Alerts
-Signals
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