What is a KPI Indicator?

Indicators vs. KPIs: Understanding the Distinction

In the field of technical analysis, the term “indicator” is widely used. However, within this system, a technical distinction is made between a Standard Indicator and a KPI (Key Performance Indicator). This article explains how these data types differ and how they function within the software architecture.

1. What is a KPI in this Script?

In the context of this tool, a KPI is distinguished from standard oscillators like the RSI or MACD by its computational complexity.

While a standard indicator typically calculates a single data point based on past price action (e.g., “Is current price > average price?”), the KPIs in this script utilize complex algorithms. They aim to provide aggregated insight by processing data from multiple sources simultaneously—such as volume deltas, open interest changes, and market structure—to output a single data visualization.

The Core Characteristics of Our KPIs:

• Context: The algorithms are designed to analyze not just price movement, but also the volume and order flow data often associated with different market participants (Institutional vs. Retail).
• Confluence: The KPI merges multiple data points (e.g., combining Spot market volume with Perpetual futures data) to form a composite metric.
• Information Density: A KPI is designed to summarize broader market conditions rather than just a single asset’s price history.

2. KPI vs. Standard Indicator: The Comparison

A key difference lies in the data responsiveness. Standard indicators are mathematically “lagging” as they rely solely on historical price. The KPIs in this suite are engineered to analyze real-time flow data to reduce latency.

Feature	Standard Indicator (e.g., RSI)	KPI in this Script (e.g., ETF or LPI)
Data Source	Price action only (Historical)	Price, Volume, Open Interest, Flow Data
Calculation	Standard mathematical formula	Multi-variable algorithmic processing
Output Type	Oscillator (e.g., “Overbought/Oversold”)	Flow Analysis (e.g., “Divergence detected”)
Focus	Historical Price Trends	Volume & Liquidity Analysis
Function	Reacts to completed candle closes	Tracks real-time capital flow

3. Advanced Capabilities of a KPI

A. Identifying Divergences (vs. “False Signals”)

Standard indicators can generate signals based on price alone, which may not be supported by volume. For example, an RSI may indicate an “overbought” condition during a strong trend. The KPIs in this script cross-reference price with volume and open interest.

• Scenario: If price is rising, but the KPI detects a decrease in capital flow (divergence), the system highlights this data point. This helps the user assess the strength or weakness of a trend beyond price action alone.

B. Multi-Dimensional Analysis

Standard indicators are often one-dimensional (Price vs. Time). The KPIs, such as the Squeeze Radar or Correlation & Lag, analyze the relationships between assets, volatility pressure, and market velocity. This offers a multi-variate view of the market structure.

C. Enhanced Market Visibility

Modern crypto markets are increasingly influenced by large-volume participants. Standard price indicators do not account for volume types. KPIs like the SMC Overview and ETF Dashboard are designed to visualize money flow data. This allows users to base their analysis on volume dynamics rather than price history alone.

Conclusion

If a standard indicator functions like a rearview mirror showing where price has been, the KPIs in this script function as a radar system detecting current environmental conditions.

While standard analysis reacts to price movements that have already occurred, these KPIs allow users to analyze the underlying market structure and capital flow. The system is not designed to predict the price, but to provide a comprehensive dataset, enabling users to make informed, data-driven decisions.