A composite index answers questions like:

• What is the overall momentum of a group of assets?

• How strong is a market when multiple indicators agree?

• How does a basket of assets behave as a whole?

Composite formulas are ideal for creating custom indices, health scores, and multi-signal summaries.

What a composite index represents

A composite index merges several time series into one normalized output. Each component contributes to the final result, allowing you to express a broader market view than any single metric could provide.

Depending on the inputs, a composite index can represent:

• Aggregate momentum

• Market strength

• Asset group performance

• Indicator agreement

• System-wide health

Composites do not predict direction on their own. They summarize state.

Why composite index formulas matter

Composite formulas are useful because they:

• Reduce complexity into a single signal

• Combine multiple assets or indicators

• Capture consensus rather than noise

• Enable custom index creation

• Scale naturally from simple to advanced systems

They are especially powerful when you want one chart instead of many, without losing informational depth.

How composite formulas work

Composite formulas accept two or more time series as inputs and blend them into a single output.

The general structure is:

composite(series_1, series_2, series_3, ...)

Each input can be:

• A price series

• A volume series

• An indicator

• A derived formula

All inputs are aligned in time before being combined.

Weighted composites

In addition to simple composites, you can build weighted composites where each component contributes a specific proportion to the final index.

The general structure is:

weighted(weight_1:series_1, weight_2:series_2, ...)

Weights must sum to 1.0, making the contribution of each component explicit.

Common composite use cases

Composite index formulas are commonly used to:

• Build market-wide indices

• Aggregate multi-asset momentum

• Create indicator consensus scores

• Rank asset strength

• Design health and risk scores

They are often used as inputs to signals, filters, or dashboards.

Sample composite index formulas

Below are example prompts paired with their generated formulas.

Momentum composite index

"Create a crypto momentum index from BTC, ETH, and SOL RSI"

composite(BTCUSD.rsi, ETHUSD.rsi, SOLUSD.rsi)

This produces a single momentum index reflecting RSI behavior across the three assets.

Multi-asset composite index

"Give me a forex composite index from the top 10 currencies monthly"

composite(
  EURUSD.close,
  GBPUSD.close,
  USDJPY.close,
  AUDUSD.close,
  USDCAD.close,
  NZDUSD.close,
  EURJPY.close,
  GBPJPY.close,
  AUDJPY.close,
  EURCAD.close
)

This creates a broad forex index representing combined price behavior across major currency pairs.

Multi-indicator composite

"Build a multi-indicator score for Bitcoin using RSI, MACD, and ADX"

composite(X:BTCUSD.rsi, BTCUSD.macd, BTCUSD.adx)

This blends momentum, trend, and strength into a single Bitcoin score.

Price index composite

"Show me a top 5 crypto price index"

composite(
  BTCUSD.close,
  ETHUSD.close,
  SOLUSD.close,
  DOGEUSD.close,
  XRPUSD.close
)

This behaves like a custom crypto index tracking overall price movement across major assets.

Weighted composite index

"Create a weighted BTC health score: 60% RSI, 40% volume"

weighted(
  0.6:BTCUSD.rsi,
  0.4:normalize(BTCUSD.volume)
)

This creates a health score where momentum has more influence than volume, with normalization ensuring comparability.

Normalization in composites

When combining values with different scales (for example RSI and volume), normalization is often required.

Normalization:

• Aligns ranges

• Prevents domination by large values

• Ensures fair contribution

This is especially important in weighted composites.

Best practices

When building composite indices:

• Combine conceptually related inputs

• Normalize values when scales differ

• Use weights to express conviction

• Keep composites interpretable

• Avoid overloading with too many components

A good composite tells a clear story.

Summary

Composite index formulas allow you to transform multiple signals into a single, meaningful index. They are ideal for summarizing market state, combining indicators, and building custom benchmarks.

By reducing complexity without sacrificing structure, composites act as a powerful bridge between raw data and decision-ready signals.