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@@ -7,22 +7,13 @@ namespace QuanTAlib;
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/// TEMA: Triple Exponential Moving Average
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/// </summary>
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/// <remarks>
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/// TEMA uses triple smoothing to reduce lag even further than DEMA.
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/// Uses triple smoothing to further reduce lag beyond DEMA.
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/// Excellent for fast trend identification with minimal overshoot.
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///
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/// Calculation:
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/// EMA1 = EMA(input)
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/// EMA2 = EMA(EMA1)
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/// EMA3 = EMA(EMA2)
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/// TEMA = 3 * EMA1 - 3 * EMA2 + EMA3
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///
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/// O(1) update:
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/// Uses three EMA instances, each with O(1) update complexity.
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///
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/// IsHot:
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/// Becomes true when the TEMA step response converges to within 5% error.
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/// This happens when the third EMA's error factor drops below ~9% (approx 2.43/alpha steps),
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/// which is faster than the standard EMA convergence (3/alpha steps).
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/// Calculation: <c>TEMA = 3×EMA1 - 3×EMA2 + EMA3</c> (cascaded EMAs).
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/// </remarks>
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/// <seealso href="Tema.md">Detailed documentation</seealso>
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/// <seealso href="tema.pine">Reference Pine Script implementation</seealso>
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[SkipLocalsInit]
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public sealed class Tema : AbstractBase
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{
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