in:

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  The time period parameter, usually a positive integer, indicates the length of the time window used to calculate the moving average. For example, N=5 means using the data of the past 5 time units for calculation. This parameter determines the sensitivity of the indicator to price changes. Smaller N values ​​are more sensitive to recent price changes, but may generate more noise; larger N values ​​have better smoothing effects, but the response to price changes is relatively lagging. The commonly used default value is 5, but it can be adjusted according to the trading strategy and asset volatility.

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  The input sequence value at time t is usually the price sequence of an asset (such as the closing price: CLOSE(t)), or other time series data (such as trading volume: VOL(t)). Here, time t can be understood as a trading time point, trading day, or other time unit, depending on the data frequency.

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  The first-level exponential moving average represents the value of the input sequence $REAL(t)$ after exponential smoothing at time t.

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  The second layer of exponential moving average represents the value after exponential smoothing of $EMA_1(t)$ at time t.

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  The third layer of exponential moving average represents the value after exponential smoothing of $EMA_2(t)$ at time t.

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  The exponential moving average function means that the time series x is exponentially smoothed using the time period N and the result sequence is returned. Its calculation formula is: $EMA(x,N)t = \alpha * x_t + (1 - \alpha) * EMA(x,N){t-1} $, where $ \alpha = \frac{2}{N + 1} $. The initial value $EMA(x,N)_0$ is usually the first value of x or the simple average of the first N values.