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Miha Kralj
86fe32a682
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com> Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat> Co-authored-by: Warp <agent@warp.dev>
74 lines
3.3 KiB
Markdown
74 lines
3.3 KiB
Markdown
# Aroon
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> Price levels are irrelevant. The only thing that matters is *when* they happened. Aroon is a stopwatch for trends.
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The Aroon indicator measures the temporal freshness of price extremes. Unlike oscillators that obsess over *how much* price has moved, Aroon asks *how long* it has been since a new high or low. It quantifies the "staleness" of a trend, providing an early warning system for consolidation and reversals.
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## Historical Context
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Tushar Chande introduced Aroon in *Beyond Technical Analysis* (1995). The name comes from the Sanskrit word for "Dawn's Early Light." Chande's insight was that trends don't just stop; they age. By measuring the time elapsed since the last extreme, Aroon attempts to spot the "dawn" of a new trend rather than just confirming an existing one.
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## Architecture & Physics
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Aroon is purely time-based. It normalizes the "days since" metric into a 0-100 oscillator.
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1. **Time Tracking**: A sliding window of the last $N$ bars is maintained.
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2. **Extremum Search**: The index of the highest high and lowest low within that window is located.
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3. **Normalization**: The distance (in bars) is converted into a percentage.
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### The Logic of Freshness
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* **Aroon Up**: Quantifies the recency of the High.
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* 100: New high today.
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* 0: No new high for the entire period.
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* **Aroon Down**: Quantifies the recency of the Low.
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* 100: New low today.
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* 0: No new low for the entire period.
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* **Oscillator**: The net difference ($Up - Down$), showing the dominant temporal force.
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## Mathematical Foundation
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The math is a linear decay function based on time.
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$$ \text{Aroon Up} = \frac{Period - \text{Days Since High}}{Period} \times 100 $$
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$$ \text{Aroon Down} = \frac{Period - \text{Days Since Low}}{Period} \times 100 $$
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$$ \text{Oscillator} = \text{Aroon Up} - \text{Aroon Down} $$
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## Performance Profile
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While memory is O(P), computational complexity is linear with respect to the period due to the min/max search.
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### Zero-Allocation Design
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The implementation uses a circular buffer (`RingBuffer`) to store historical highs and lows, ensuring O(1) access and zero heap allocations during the update cycle. The min/max search is performed in-place on the buffer.
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| Metric | Score | Notes |
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| :--- | :--- | :--- |
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| **Throughput** | 10ns | 10ns / bar. |
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| **Allocations** | 0 | Hot path is allocation-free. |
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| **Complexity** | O(P) | Linear scan for extremes. |
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| **Accuracy** | 10/10 | Matches standard implementations. |
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| **Timeliness** | 10/10 | Reacts immediately to new extremes. |
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| **Overshoot** | 0/10 | Bounded 0-100. |
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| **Smoothness** | 2/10 | Step-function behavior. |
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## Validation
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Validation is performed against industry-standard libraries.
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| Library | Status | Notes |
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| :--- | :--- | :--- |
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| **QuanTAlib** | ✅ | Validated. |
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| **Skender** | ✅ | Matches `GetAroon`. |
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| **TA-Lib** | ✅ | Matches `TA_AROON` and `TA_AROONOSC`. |
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| **Tulip** | ✅ | Matches `ti.aroon` and `ti.aroonosc`. |
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| **Ooples** | N/A | Not implemented. |
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### Common Pitfalls
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* **Single Value Updates**: If you feed Aroon only `Close` prices (instead of High/Low), it degrades into a "Time Since Highest Close" metric. It works, but it loses the nuance of intraday extremes.
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* **The 70/30 Rule**: A common interpretation is that a trend is strong only if the primary line is > 70. Values between 30 and 70 often indicate noise or consolidation.
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