Enter Adaptive Moving Average Inputs
Example Data Table
| Time | Observed Value | Comment |
|---|---|---|
| 1 | 100 | Starting baseline observation |
| 2 | 102 | Initial rise appears |
| 3 | 101 | Small pullback adds noise |
| 4 | 105 | Momentum strengthens |
| 5 | 108 | Trend continues upward |
| 6 | 107 | Temporary dip tests stability |
Formula Used
Adaptive moving average reacts to directional efficiency instead of using one fixed smoothing speed.
Efficiency Ratio: ER = |Pricet − Pricet−n| ÷ Σ|Price change over n periods|
Fast Smoothing Constant: 2 ÷ (Fast Period + 1)
Slow Smoothing Constant: 2 ÷ (Slow Period + 1)
Adaptive Smoothing: SC = [ER × (Fast SC − Slow SC) + Slow SC]2
Adaptive Moving Average: AMAt = AMAt−1 + SC × (Pricet − AMAt−1)
How to Use This Calculator
- Paste a sequential numeric series into the data field.
- Set a short fast period for quick adaptation.
- Set a longer slow period for stable smoothing limits.
- Choose an efficiency ratio period matching your review window.
- Use the projection factor to extend the current AMA slope.
- Press submit to view summary metrics and row level calculations.
- Export the output as CSV or PDF for reporting.
Frequently Asked Questions
1. What does adaptive moving average measure?
It estimates the underlying trend while adjusting smoothing speed to market or data efficiency. Strong directional movement makes it respond faster than a standard moving average.
2. Why use fast and slow periods together?
The fast period defines the quickest allowed response. The slow period defines the smoothest allowed response. The efficiency ratio moves the average between those two limits.
3. What is a good efficiency ratio period?
A moderate lookback such as 10 is common because it balances sensitivity and stability. Shorter values react quickly, while longer values suppress more noise.
4. What does a high efficiency ratio mean?
A high ratio means recent movement was direct rather than choppy. The calculator then uses a larger smoothing constant, making the adaptive average react faster.
5. Can this calculator work for non financial data?
Yes. It works for sensor data, demand series, web traffic, production output, or any ordered numeric sequence where noise filtering and changing responsiveness matter.
6. What does the projected AMA show?
It extends the latest adaptive slope by the selected projection factor. This is a simple directional estimate, not a full predictive model.
7. How should I interpret value versus AMA?
If the latest value is above AMA, the current series is stronger than its adaptive baseline. If below, recent movement is weaker than that baseline.
8. Why does the first part of the series use slower updates?
Before enough history exists for the efficiency ratio, the calculator seeds the series conservatively. That prevents unstable early readings from distorting the output.