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업데이트됨 Lanczos Candles

This indicator reconstructs price action using Lanczos resampling, incorporating lower timeframe data to create a more detailed representation of market movements. Traditional candle aggregation on higher timeframes tends to lose some price action detail - this indicator attempts to preserve more of that information through mathematical resampling.
The indicator samples price data from a lower timeframe and uses the Lanczos algorithm, a mathematical method commonly used in signal processing and image resampling, to reconstruct the price series at the chart's timeframe. The process helps maintain price movements that might otherwise be smoothed out in regular candle aggregation.
The main settings allow you to select the source timeframe for sampling, adjust the Lanczos filter width to balance smoothness versus detail preservation, and optionally enable Heikin Ashi calculation. The filter width parameter (default: 3) affects how aggressive the smoothing is - higher values produce smoother results while lower values retain more of the original variation.
This approach can be useful for technical analysis when you want to work with higher timeframes while maintaining awareness of significant price movements that occurred within those candles. The optional Heikin Ashi mode can help visualize trends in the resampled data.
The indicator works best when there's a clear ratio between your chart timeframe and the source timeframe (for example, using 1-minute data to build 5-minute candles).
The indicator samples price data from a lower timeframe and uses the Lanczos algorithm, a mathematical method commonly used in signal processing and image resampling, to reconstruct the price series at the chart's timeframe. The process helps maintain price movements that might otherwise be smoothed out in regular candle aggregation.
The main settings allow you to select the source timeframe for sampling, adjust the Lanczos filter width to balance smoothness versus detail preservation, and optionally enable Heikin Ashi calculation. The filter width parameter (default: 3) affects how aggressive the smoothing is - higher values produce smoother results while lower values retain more of the original variation.
This approach can be useful for technical analysis when you want to work with higher timeframes while maintaining awareness of significant price movements that occurred within those candles. The optional Heikin Ashi mode can help visualize trends in the resampled data.
The indicator works best when there's a clear ratio between your chart timeframe and the source timeframe (for example, using 1-minute data to build 5-minute candles).
릴리즈 노트
Updated to allow you to pick from only processing the current candles data or to blead in the previous candles data to keep a fixed window size (original behavior). Added price tracking and the option to use the real price as your price track.Description update:
The idea behind this method is to use a form of upscaling to try to take into account all of the ltf data points as a close to maybe reduce aliasing. Also the trackprice should help with adding other indicators to the output source if you want to run them on that signal instead of the real close.
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.