OPEN-SOURCE SCRIPT
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
진정한 트레이딩뷰 정신에 따라 이 스크립트 작성자는 트레이더가 기능을 검토하고 검증할 수 있도록 오픈소스로 공개했습니다. 작성자에게 찬사를 보냅니다! 무료로 사용할 수 있지만 코드를 다시 게시할 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.
오픈 소스 스크립트
진정한 트레이딩뷰 정신에 따라 이 스크립트 작성자는 트레이더가 기능을 검토하고 검증할 수 있도록 오픈소스로 공개했습니다. 작성자에게 찬사를 보냅니다! 무료로 사용할 수 있지만 코드를 다시 게시할 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.