gavindiaz/QuanTAlib
1
0
Fork 0
mirror of https://github.com/mihakralj/QuanTAlib.git synced 2026-08-22 12:38:06 +00:00
Code Issues Packages Projects Releases Wiki Activity

v0.8.6: update indicator docs, ndepend tooling, ALMA refactor, gitignore cleanup

Browse Source
This commit is contained in:
Miha Kralj
2026-03-13 13:46:52 -07:00
parent e3e9555fc1
commit c75135ab14
402 changed files with 2222 additions and 1779 deletions
Download Patch File Download Diff File Expand all files Collapse all files
lib/dynamics/pfe/Pfe.md
+2 -4
View File
@@ -13,9 +13,7 @@
| **PineScript** | [pfe.pine](pfe.pine) |
- Polarized Fractal Efficiency (PFE) quantifies trend strength by comparing the Euclidean distance a price series actually travels bar-to-bar against...
- Parameterized by `period` (default 10), `smoothperiod` (default 5).
- Output range: Varies (see docs).
- Requires `period + 1` bars of warmup before first valid output (IsHot = true).
- **Similar:** [ADX](../adx/Adx.md), [VHF](../vhf/Vhf.md) | **Complementary:** Moving average for trend direction | **Trading note:** Polarized Fractal Efficiency; measures how efficiently price travels. ±100 scale.
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
Polarized Fractal Efficiency (PFE) quantifies trend strength by comparing the Euclidean distance a price series actually travels bar-to-bar against the straight-line distance between the endpoints over the same window. The ratio, scaled to [-100, +100] and smoothed with an EMA, distinguishes efficient trending motion (values near ±100) from fractal, self-similar noise (values near 0). Created by Hans Hannula and published in *Technical Analysis of Stocks & Commodities* (January 1994), PFE applies fractal geometry to price action without requiring Hurst exponent estimation or rescaled-range analysis. With default parameters (period=10, smooth=5), the indicator needs 11 close values for the first raw reading plus 5 bars of EMA convergence, totaling ~16 bars of warmup. The core loop executes $N$ square roots per bar, making it $O(N)$ per update in streaming mode.
@@ -251,4 +249,4 @@ Key validation points:
- Mandelbrot, Benoit. "The Variation of Certain Speculative Prices." *The Journal of Business*, Vol. 36, No. 4, October 1963.
- Kaufman, Perry. *Trading Systems and Methods*, 5th Edition. Wiley, 2013. (Efficiency Ratio comparison)
- Hannula, Hans. "Chaos and the Stock Market." *Cycles Magazine*, 1993.
- PineScript reference: `pfe.pine` in indicator directory.
- PineScript reference: `pfe.pine` in indicator directory.