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lib/trends_IIR/vidya/Vidya.md
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# VIDYA: Variable Index Dynamic Average
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Trend (IIR MA) |
| **Inputs** | Source (close) |
| **Parameters** | `period` |
| **Outputs** | Single series (Vidya) |
| **Output range** | Tracks input |
| **Warmup** | `period` bars |
### TL;DR
- The Variable Index Dynamic Average (VIDYA) is an adaptive moving average that automatically adjusts its smoothing speed based on market volatility.
- Parameterized by `period`.
- Output range: Tracks input.
- Requires `period` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "Tushar Chande asked: 'Why should I trust a moving average that treats a market crash the same as a lunch break?' VIDYA is the answer."
The Variable Index Dynamic Average (VIDYA) is an adaptive moving average that automatically adjusts its smoothing speed based on market volatility. When the market is trending (high volatility), VIDYA speeds up to capture the move. When the market is ranging (low volatility), it slows down to filter out the noise.
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1. **Flatlining**: In extremely choppy, sideways markets, CMO can approach 0, causing VIDYA to flatline completely. This is a feature, not a bug.
2. **Sensitivity**: VIDYA is highly sensitive to the period chosen for the CMO. A short period makes it jittery; a long period makes it sluggish.
3. **Comparison**: Often compared to KAMA (Kaufman). KAMA uses Efficiency Ratio (ER); VIDYA uses CMO. They are conceptually similar but mathematically distinct.
3. **Comparison**: Often compared to KAMA (Kaufman). KAMA uses Efficiency Ratio (ER); VIDYA uses CMO. They are conceptually similar but mathematically distinct.