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lib/cycles/eacp/eacp.md
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# EACP: Ehlers Autocorrelation Periodogram
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Cycle |
| **Inputs** | Source (close) |
| **Parameters** | `minPeriod` (default 8), `maxPeriod` (default 48), `avgLength` (default 3), `enhance` (default true) |
| **Outputs** | Single series (Eacp) |
| **Output range** | Varies (see docs) |
| **Warmup** | `maxPeriod * 2` bars |
### TL;DR
- EACP estimates the dominant cycle period of a financial time series by computing autocorrelation across multiple lags and transforming the result i...
- Parameterized by `minperiod` (default 8), `maxperiod` (default 48), `avglength` (default 3), `enhance` (default true).
- Output range: Varies (see docs).
- Requires `maxPeriod * 2` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
EACP estimates the dominant cycle period of a financial time series by computing autocorrelation across multiple lags and transforming the result into a power spectrum via the Wiener-Khinchin theorem. The output is a continuously updating cycle period measurement (in bars) that can adaptively tune other indicators to the market's current rhythm, making fixed-period assumptions unnecessary.
## Historical Context