OPEN-SOURCE SCRIPT
ROC [CHE] with Kernel Selection

Introduction:
The script titled "ROC [CHE] with Kernel Selection" utilizes Rate of Change (ROC) to analyze price momentum in financial markets. It incorporates a kernel selection mechanism to smooth ROC values, enhancing clarity in trend identification.
Middle Part:
The script begins by calculating ROC over a specified period using the formula:
roc = (close - close[lengthPeriod]) / close[lengthPeriod] * 100
The period length determined by the user. The result is plotted alongside a zero line for reference.
The kernel selection aspect allows users to choose from various smoothing techniques:
Linear
Exponential
Epanechnikov
Triangular
Cosine
Each kernel applies a different weighting function to ROC values, influencing the sensitivity and smoothness of the plotted line. Users can customize parameters such as bandwidth and color preferences for up and down movements, facilitating visual interpretation.
The main logic of the script involves iterating through historical data to compute weighted averages of ROC values based on the selected kernel. It adjusts graphical elements dynamically, highlighting changes in momentum direction with color-coded lines and directional symbols (▲ or ▼).
Conclusion:
In conclusion, "ROC [CHE] with Kernel Selection" offers a flexible toolset for traders and analysts to assess price momentum robustly. By integrating kernel-based smoothing techniques, it enhances the clarity of ROC signals, aiding in the identification of trends and potential reversals in financial markets.
The script titled "ROC [CHE] with Kernel Selection" utilizes Rate of Change (ROC) to analyze price momentum in financial markets. It incorporates a kernel selection mechanism to smooth ROC values, enhancing clarity in trend identification.
Middle Part:
The script begins by calculating ROC over a specified period using the formula:
roc = (close - close[lengthPeriod]) / close[lengthPeriod] * 100
The period length determined by the user. The result is plotted alongside a zero line for reference.
The kernel selection aspect allows users to choose from various smoothing techniques:
Linear
Exponential
Epanechnikov
Triangular
Cosine
Each kernel applies a different weighting function to ROC values, influencing the sensitivity and smoothness of the plotted line. Users can customize parameters such as bandwidth and color preferences for up and down movements, facilitating visual interpretation.
The main logic of the script involves iterating through historical data to compute weighted averages of ROC values based on the selected kernel. It adjusts graphical elements dynamically, highlighting changes in momentum direction with color-coded lines and directional symbols (▲ or ▼).
Conclusion:
In conclusion, "ROC [CHE] with Kernel Selection" offers a flexible toolset for traders and analysts to assess price momentum robustly. By integrating kernel-based smoothing techniques, it enhances the clarity of ROC signals, aiding in the identification of trends and potential reversals in financial markets.
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.