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Exponential Moving Average (EMA)

Exponentially weighted moving average is a rolling moving average that puts more weight on current price. [Discuss] 💬

// Go usage syntax (with Close price)
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Parameters

lookbackPeriods int - Number of periods (N) in the moving average. Must be greater than 0.

Historical quotes requirements

You must have at least 2×N or N+100 periods of quotes, whichever is more, to cover the convergence periods. Since this uses a smoothing technique, we recommend you use at least N+250 data points prior to the intended usage date for better precision.

quotes is a collection of generic TQuote historical price quotes. It should have a consistent frequency (day, hour, minute, etc). See the Guide for more information.

Response

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• This method returns a time series of all available indicator values for the quotes provided.
• It always returns the same number of elements as there are in the historical quotes.
• It does not return a single incremental indicator value.
• The first N-1 periods will have null values since there’s not enough data to calculate.

⚞ Convergence warning: The first N+100 periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.

EmaResult

Timestamp DateTime - date from evaluated TQuote

Ema double - Exponential moving average

Utilities

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See Utilities and helpers for more information.

Chaining

This indicator may be generated from any chain-enabled indicator or method.

// example
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Results can be further processed on Ema with additional chain-enabled indicators.

// example
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