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Miha Kralj
39 lines
1.0 KiB
Markdown
39 lines
1.0 KiB
Markdown
# EMA: Exponential Moving Average
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EMA needs very short history buffer and calculates the EMA value using just the previous EMA value. The weight of the new datapoint (k) is k = 2 / (period-1)
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## Calculation
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There is an adopted practice to calculate $SMA$ when $n < period$.
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$$
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EMA_n = \left\{ \begin{array}{cl}
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\frac{1}{p}\left( data_{n}-data_{n-p}\right)+SMA_{n-1} & : \ n \leq period \\
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{k}\times ({data_{n}} - EMA_{n-1}) + EMA_{n-1} & : \ x > period
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\end{array} \right.
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$$
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## Implementation
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``` csharp
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EMA_Series mean = new(source: data, period: p, useNaN: false);
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```
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- `TSeries source` - List of value tuples (DateTime, double)
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- `int period` - Integer representing the period of SMA
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- `bool useNaN` - if true, initial values from 1 to period-1 will be replaced with NaN. If false, the initial calculation will return values for SMA(length) instead of SMA(period)
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## Comparison & Validation
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Validation tests
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Performance tests
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## Visual analysis
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## References
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