gavindiaz/QuanTAlib
1
0
Fork 0
mirror of https://github.com/mihakralj/QuanTAlib.git synced 2026-08-17 01:58:06 +00:00
Code Issues Packages Projects Releases Wiki Activity

doc headers

Browse Source
This commit is contained in:
Miha Kralj
2026-02-27 07:48:12 -08:00
parent 8a1ba95173
commit 4ab3a7fb53
389 changed files with 6682 additions and 468 deletions
Download Patch File Download Diff File Expand all files Collapse all files
lib/volatility/bbwn/Bbwn.md
+17
View File
@@ -1,5 +1,22 @@
# BBWN: Bollinger Band Width Normalized
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Volatility |
| **Inputs** | Source (close) |
| **Parameters** | `period`, `multiplier` (default 2.0), `lookback` (default 252) |
| **Outputs** | Single series (Bbwn) |
| **Output range** | $\geq 0$ |
| **Warmup** | `period + lookback` bars |
### TL;DR
- Bollinger Band Width Normalized (BBWN) extends the standard BBW by normalizing it to a [0,1] range based on historical minimum and maximum values o...
- Parameterized by `period`, `multiplier` (default 2.0), `lookback` (default 252).
- Output range: $\geq 0$.
- Requires `period + lookback` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "Normalization transforms volatility chaos into comparable signals."
Bollinger Band Width Normalized (BBWN) extends the standard BBW by normalizing it to a [0,1] range based on historical minimum and maximum values over a lookback period. This normalization enables better comparison across different timeframes, instruments, and market conditions, making it easier to identify relative volatility levels consistently.