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Wavelet Smoothed Moving Average (TechnoBlooms)

Wavelet Smoothed Moving Average (WSMA) is a part of the Quantum Price Theory (QPT) Series of indicators.
Overview:
The Wavelet Smoothed Moving Average (WSMA) is a trend-following indicator inspired by multi-level Haar Wavelet decomposition. Rather than using traditional wavelet basis functions, it emulates the core wavelet concept of multi-resolution analysis using nested simple moving averages (SMA).
How It Works:
WSMA applies three levels of smoothing:
• Level 1: SMA on price (base smoothing)
• Level 2: SMA on Level 1 output (further denoising)
• Level 3: SMA on Level 2 output (final approximation)
Why Use WSMA:
• Multi-Level Smoothing: Captures price structure across multiple time scales, unlike single-length MAs.
• Noise Reduction: Filters out short-term volatility and focuses on the underlying trend.
• Low Lag, High Clarity: Unlike traditional moving averages that react slowly or miss subtle shifts, WSMA’s layered smoothing delivers cleaner and more adaptive trend detection.
Unique Value:
• Wavelet-Inspired Design: Mimics core wavelet decomposition logic without the complexity of downsampling or basis functions.
• Perfect for Trend Confirmation: The final line (a3) can act as a trend filter, while the detail levels can help identify momentum shifts and volatility bursts.
• Fits Into Quantum Price Theory: As part of the QPT framework, WSMA bridges scientific theory with trading application, giving traders a deeper understanding of market structure and signal compression.
Overview:
The Wavelet Smoothed Moving Average (WSMA) is a trend-following indicator inspired by multi-level Haar Wavelet decomposition. Rather than using traditional wavelet basis functions, it emulates the core wavelet concept of multi-resolution analysis using nested simple moving averages (SMA).
How It Works:
WSMA applies three levels of smoothing:
• Level 1: SMA on price (base smoothing)
• Level 2: SMA on Level 1 output (further denoising)
• Level 3: SMA on Level 2 output (final approximation)
Why Use WSMA:
• Multi-Level Smoothing: Captures price structure across multiple time scales, unlike single-length MAs.
• Noise Reduction: Filters out short-term volatility and focuses on the underlying trend.
• Low Lag, High Clarity: Unlike traditional moving averages that react slowly or miss subtle shifts, WSMA’s layered smoothing delivers cleaner and more adaptive trend detection.
Unique Value:
• Wavelet-Inspired Design: Mimics core wavelet decomposition logic without the complexity of downsampling or basis functions.
• Perfect for Trend Confirmation: The final line (a3) can act as a trend filter, while the detail levels can help identify momentum shifts and volatility bursts.
• Fits Into Quantum Price Theory: As part of the QPT framework, WSMA bridges scientific theory with trading application, giving traders a deeper understanding of market structure and signal compression.
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.