OPEN-SOURCE SCRIPT
Standardized ROC Engine (EMA Version)

The purpose of this script is to create a standardized rate‑of‑change engine that compares the momentum of multiple structural anchors, specifically several EMAs, VWAP, price and volume. By converting each ROC stream into a z‑score, the indicator places all components on a common scale, allowing the trader to see when any anchor is accelerating or decelerating relative to its own long‑term distribution. This transforms raw ROC, which is naturally unstable and scale‑dependent, into a normalized momentum map that highlights extremes, clustering and regime shifts with far greater clarity.
The script works by first computing four EMAs of different lengths, along with VWAP, then calculating the percentage rate of change for each series over a user‑defined ROC window. Each ROC stream is then passed through a standardization function that subtracts its rolling mean and divides by its rolling standard deviation, producing a z‑score that expresses how unusual the current momentum is compared to the past. These standardized curves are plotted together, using consistent colors, while horizontal reference lines at one, two and three standard deviations provide visual thresholds for identifying statistically significant momentum events.
The rationale behind this architecture is that raw ROC values are not comparable across different structures because each anchor has its own volatility profile, amplitude and noise characteristics. Standardization solves this by converting every ROC stream into a dimensionless measure of deviation, enabling cross‑anchor comparison without distortion. This approach reveals when short‑term EMAs are accelerating faster than long‑term EMAs, when VWAP momentum diverges from trend momentum, and when volume expansion aligns with or contradicts price acceleration, all expressed in a unified statistical language that is robust across assets and timeframes.
The script works by first computing four EMAs of different lengths, along with VWAP, then calculating the percentage rate of change for each series over a user‑defined ROC window. Each ROC stream is then passed through a standardization function that subtracts its rolling mean and divides by its rolling standard deviation, producing a z‑score that expresses how unusual the current momentum is compared to the past. These standardized curves are plotted together, using consistent colors, while horizontal reference lines at one, two and three standard deviations provide visual thresholds for identifying statistically significant momentum events.
The rationale behind this architecture is that raw ROC values are not comparable across different structures because each anchor has its own volatility profile, amplitude and noise characteristics. Standardization solves this by converting every ROC stream into a dimensionless measure of deviation, enabling cross‑anchor comparison without distortion. This approach reveals when short‑term EMAs are accelerating faster than long‑term EMAs, when VWAP momentum diverges from trend momentum, and when volume expansion aligns with or contradicts price acceleration, all expressed in a unified statistical language that is robust across assets and timeframes.
开源脚本
秉承TradingView的精神,该脚本的作者将其开源,以便交易者可以查看和验证其功能。向作者致敬!您可以免费使用该脚本,但请记住,重新发布代码须遵守我们的网站规则。
免责声明
这些信息和出版物并非旨在提供,也不构成TradingView提供或认可的任何形式的财务、投资、交易或其他类型的建议或推荐。请阅读使用条款了解更多信息。
开源脚本
秉承TradingView的精神,该脚本的作者将其开源,以便交易者可以查看和验证其功能。向作者致敬!您可以免费使用该脚本,但请记住,重新发布代码须遵守我们的网站规则。
免责声明
这些信息和出版物并非旨在提供,也不构成TradingView提供或认可的任何形式的财务、投资、交易或其他类型的建议或推荐。请阅读使用条款了解更多信息。