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86fe32a682
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com> Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat> Co-authored-by: Warp <agent@warp.dev>
48 lines
1.7 KiB
Plaintext
48 lines
1.7 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("Regularized EMA (REMA)", "REMA", overlay=true)
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//@function Calculates REMA using exponential smoothing with regularization term
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//@param source Series to calculate REMA from
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//@param period Lookback period used to determine alpha value
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//@param lambda Regularization parameter (0-1) controlling smoothness
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//@returns REMA value, calculates from first bar using available data
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//@optimized Uses regularization term to reduce noise for O(1) complexity
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rema(series float source, simple int period, simple float lambda=0.5) =>
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if period <= 0
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runtime.error("Period must be greater than 0")
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if lambda < 0.0 or lambda > 1.0
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runtime.error("Lambda must be between 0 and 1")
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float alpha = 2.0 / (period + 1.0)
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var float rema_val = na
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var float prev_rema = na
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float result = na
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if not na(source)
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if na(rema_val)
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rema_val := source
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prev_rema := source
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result := rema_val
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else
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prev_rema := rema_val
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float ema_component = alpha * (source - rema_val) + rema_val
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float reg_component = rema_val + (rema_val - prev_rema)
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rema_val := lambda * (ema_component - reg_component) + reg_component
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result := rema_val
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else
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result := rema_val
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result
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// ---------- Main loop ----------
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// Inputs
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i_period = input.int(10, "Period", minval=1)
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i_lambda = input.float(0.5, "Lambda", minval=0.0, maxval=1.0, step=0.1, tooltip="Regularization parameter: 0 = maximum regularization, 1 = standard EMA")
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i_source = input.source(close, "Source")
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// Calculation
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rema_value = rema(i_source, i_period, i_lambda)
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// Plot
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plot(rema_value, "REMA", color=color.yellow, linewidth=2)
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