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Miha Kralj
2025-12-18 13:51:06 -08:00
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lib/trends/tema/Tema.md
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@@ -43,6 +43,48 @@ Our implementation uses three internal EMA instances.
|-----------|---------|---------|----------------------|
| Period | 14 | Lookback window | Short (5-10) for scalping; Medium (20-50) for swing trading. |
## Performance Profile
| Operation | Complexity | Description |
|-----------|------------|-------------------|
| Streaming update | O(1) | 3 EMA updates + scalar math |
| Bar correction | O(1) | Efficient state rollback |
| Batch processing | O(N) | Single pass through data |
| Memory footprint | O(1) | Stores state for 3 internal EMAs |
## Interpretation
### Trading Signals
#### Trend Direction
- **Fast Response:** TEMA turns much faster than SMA or EMA. A turn in TEMA often precedes a turn in price trend.
#### Crossovers
- **Price Crossover:** Because TEMA hugs price so closely, crossovers are frequent. They are best used for short-term entries in the direction of a larger trend.
### When It Works Best
- **Momentum Trading:** TEMA is excellent for capturing short-term bursts of momentum.
### When It Struggles
- **Overshoot:** In a sudden V-shaped reversal, TEMA can "overshoot" the price briefly due to the momentum of its internal calculation components.
## Architecture Notes
This implementation makes specific trade-offs:
### Choice: Composition
- **Implementation:** Composed of 3 `Ema` objects.
- **Rationale:** Reusing the robust `Ema` class ensures consistent behavior (like initialization and NaN handling) across the library.
## References
- Mulloy, Patrick G. "Smoothing Data with Faster Moving Averages." *Technical Analysis of Stocks & Commodities*, Jan 1994.
## C# Usage
### Streaming Updates (Single Instance)
@@ -86,46 +128,3 @@ tema.Update(new TValue(time, 100), isNew: true);
// Intra-bar update
tema.Update(new TValue(time, 101), isNew: false); // Replaces 100 with 101
```
## Performance Profile
| Operation | Complexity | Description |
|-----------|------------|-------------------|
| Streaming update | O(1) | 3 EMA updates + scalar math |
| Bar correction | O(1) | Efficient state rollback |
| Batch processing | O(N) | Single pass through data |
| Memory footprint | O(1) | Stores state for 3 internal EMAs |
## Interpretation
### Trading Signals
#### Trend Direction
- **Fast Response:** TEMA turns much faster than SMA or EMA. A turn in TEMA often precedes a turn in price trend.
#### Crossovers
- **Price Crossover:** Because TEMA hugs price so closely, crossovers are frequent. They are best used for short-term entries in the direction of a larger trend.
### When It Works Best
- **Momentum Trading:** TEMA is excellent for capturing short-term bursts of momentum.
### When It Struggles
- **Overshoot:** In a sudden V-shaped reversal, TEMA can "overshoot" the price briefly due to the momentum of its internal calculation components.
## Architecture Notes
This implementation makes specific trade-offs:
### Choice: Composition
- **Implementation:** Composed of 3 `Ema` objects.
- **Rationale:** Reusing the robust `Ema` class ensures consistent behavior (like initialization and NaN handling) across the library.
## References
- Mulloy, Patrick G. "Smoothing Data with Faster Moving Averages." *Technical Analysis of Stocks & Commodities*, Jan 1994.