2.6 KiB
VIDYA: Variable Index Dynamic Average
"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.
Historical Context
Developed by Tushar Chande and introduced in Technical Analysis of Stocks & Commodities (March 1992). It was one of the first "intelligent" moving averages, using Chande's own Momentum Oscillator (CMO) as the volatility index.
Architecture & Physics
VIDYA is essentially an EMA where the alpha (\alpha) is not constant.
\alpha_{dynamic} = \alpha_{static} \times |CMO|
Since |CMO| ranges from 0 to 1:
- CMO = 0 (No Trend):
\alpha = 0. VIDYA becomes a flat line. - CMO = 1 (Strong Trend):
\alpha = \alpha_{static}. VIDYA acts like a standard EMA.
Mathematical Foundation
1. Chande Momentum Oscillator (CMO)
CMO = \frac{\sum Up - \sum Down}{\sum Up + \sum Down}
2. Dynamic Alpha
\alpha_{static} = \frac{2}{N+1}
\alpha_{dynamic} = \alpha_{static} \times |CMO|
3. The Update
VIDYA_t = (\alpha_{dynamic} \times Price_t) + ((1 - \alpha_{dynamic}) \times VIDYA_{t-1})
Performance Profile
Zero-Allocation Design
The implementation uses two RingBuffers to track the sum of up-moves and down-moves for the CMO calculation. This allows O(1) updates of the volatility index without re-iterating history.
| Metric | Score | Notes |
|---|---|---|
| Throughput | High | CMO + EMA |
| Complexity | O(1) | Constant time update |
| Accuracy | 8/10 | Adapts to volatility, tracking trends |
| Timeliness | 8/10 | Speeds up in volatile markets |
| Overshoot | 7/10 | Can overshoot if volatility spikes |
| Smoothness | 7/10 | Smoother than EMA in quiet markets |
Validation
Validated against the original formula and reference implementations.
Common Pitfalls
- Flatlining: In extremely choppy, sideways markets, CMO can approach 0, causing VIDYA to flatline completely. This is a feature, not a bug.
- Sensitivity: VIDYA is highly sensitive to the period chosen for the CMO. A short period makes it jittery; a long period makes it sluggish.
- Comparison: Often compared to KAMA (Kaufman). KAMA uses Efficiency Ratio (ER); VIDYA uses CMO. They are conceptually similar but mathematically distinct.