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LOWESS Channel & Extrapolation [LuxAlgo]
The LOWESS Channel & Extrapolation indicator calculates a Locally Weighted Scatterplot Smoothing (LOWESS) curve to define a non-linear trend and projects it into future bars using local regression slopes. It provides a dynamic channel based on the standard deviation of residuals, helping traders identify overextended price levels and potential mean-reversion points.
🔶 USAGE
This tool is primarily designed for trend analysis and identifying exhaustion points. Because the LOWESS algorithm recalculates based on the most recent data window, the entire historical curve can adjust, making it a powerful tool for backtesting and analyzing past market structures rather than for real-time signal generation without confirmation.
🔹 Trend Identification
The central fit line represents the smoothed local trend. When the curve is sloping upward, the local market sentiment is considered bullish; conversely, a downward slope indicates bearish sentiment.
🔹 Overbought/Oversold Conditions
The dashed outer channels represent a volatility-adjusted boundary. When price moves outside these boundaries, it is statistically overextended relative to the local trend, often preceding a move back toward the mid-line.
🔹 Extrapolation
The indicator extends the most recent local regression slope into the future. This provides a "path of least resistance" projection based on the current momentum of the smoothed curve.
🔶 DETAILS
The LOWESS (Locally Weighted Scatterplot Smoothing) algorithm works by performing a separate weighted linear regression for every data point in the window.
It uses a "tricube" weighting function, which ensures that data points closer to the focal point have a higher influence on the fit than points further away. This results in a curve that is much more flexible than a simple moving average and can adapt to complex price cycles without the lag associated with traditional filters.
The channel width is determined by calculating the Standard Deviation of the residuals (the difference between the actual price and the LOWESS fit). This ensures the channel expands during high volatility and contracts during consolidation.
🔶 SETTINGS
The LOWESS Channel & Extrapolation indicator is subject to repainting and displayed retrospectively.
🔶 USAGE
This tool is primarily designed for trend analysis and identifying exhaustion points. Because the LOWESS algorithm recalculates based on the most recent data window, the entire historical curve can adjust, making it a powerful tool for backtesting and analyzing past market structures rather than for real-time signal generation without confirmation.
🔹 Trend Identification
The central fit line represents the smoothed local trend. When the curve is sloping upward, the local market sentiment is considered bullish; conversely, a downward slope indicates bearish sentiment.
🔹 Overbought/Oversold Conditions
The dashed outer channels represent a volatility-adjusted boundary. When price moves outside these boundaries, it is statistically overextended relative to the local trend, often preceding a move back toward the mid-line.
🔹 Extrapolation
The indicator extends the most recent local regression slope into the future. This provides a "path of least resistance" projection based on the current momentum of the smoothed curve.
🔶 DETAILS
The LOWESS (Locally Weighted Scatterplot Smoothing) algorithm works by performing a separate weighted linear regression for every data point in the window.
It uses a "tricube" weighting function, which ensures that data points closer to the focal point have a higher influence on the fit than points further away. This results in a curve that is much more flexible than a simple moving average and can adapt to complex price cycles without the lag associated with traditional filters.
The channel width is determined by calculating the Standard Deviation of the residuals (the difference between the actual price and the LOWESS fit). This ensures the channel expands during high volatility and contracts during consolidation.
🔶 SETTINGS
- Length: Determines the number of historical observations used to fit the LOWESS curve. Larger values result in a smoother, more macro trend.
- Span: The fraction of data points used for each local regression. A higher span (closer to 1.0) creates a smoother line, while a lower span allows the curve to follow price more tightly.
- Channel Multiplier: Multiplier applied to the standard deviation of residuals to define the distance of the upper and lower bands from the mid-line.
- Extrapolation Bars: The number of bars to project the current trend into the future.
- Fit Color: Sets the color and transparency of the central LOWESS line.
- Channel Color: Sets the color of the dashed outer bands and the background fill.
- Line Width: Adjusts the thickness of the central fit line.
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.
Build your own edge with AI: luxalgo.com
All content provided by LuxAlgo is for informational & educational purposes only. Past performance does not guarantee future results.
All content provided by LuxAlgo is for informational & educational purposes only. Past performance does not guarantee future results.
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.
Build your own edge with AI: luxalgo.com
All content provided by LuxAlgo is for informational & educational purposes only. Past performance does not guarantee future results.
All content provided by LuxAlgo is for informational & educational purposes only. Past performance does not guarantee future results.
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.