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  2. Zero lag exponential moving average - Wikipedia

    en.wikipedia.org/wiki/Zero_lag_exponential...

    The idea is do a regular exponential moving average (EMA) calculation but on a de-lagged data instead of doing it on the regular data. Data is de-lagged by removing the data from "lag" days ago thus removing (or attempting to) the cumulative effect of the moving average.

  3. Detrended price oscillator - Wikipedia

    en.wikipedia.org/wiki/Detrended_price_oscillator

    The DPO is calculated by subtracting the simple moving average over an n day period and shifted (n / 2 + 1) days back from the price. To calculate the detrended price oscillator: [5] Decide on the time frame that you wish to analyze. Set n as half of that cycle period. Calculate a simple moving average for n periods. Calculate (n / 2 + 1).

  4. Moving Average Crossover Alert: The Middleby (MIDD) - AOL

    www.aol.com/news/moving-average-crossover-alert...

    The Middleby Corporation (MIDD) could be a stock to avoid from a technical perspective, as the firm is seeing unfavorable trends on the moving average crossover front

  5. Moving Average Crossover Alert: Bank of New York Mellon - AOL

    www.aol.com/news/moving-average-crossover-alert...

    For premium support please call: 800-290-4726 more ways to reach us

  6. Moving Average Crossover Alert: Sunrun - AOL

    www.aol.com/news/moving-average-crossover-alert...

    For premium support please call: 800-290-4726 more ways to reach us

  7. MACD - Wikipedia

    en.wikipedia.org/wiki/MACD

    Exponential moving averages highlight recent changes in a stock's price. By comparing EMAs of different lengths, the MACD series gauges changes in the trend of a stock. The difference between the MACD series and its average is claimed to reveal subtle shifts in the strength and direction of a stock's trend.

  8. Moving Average Crossover Alert: Arconic Inc. (ARNC) - AOL

    www.aol.com/news/moving-average-crossover-alert...

    For premium support please call: 800-290-4726 more ways to reach us

  9. Kernel smoother - Wikipedia

    en.wikipedia.org/wiki/Kernel_smoother

    Kernel average smoother example. The idea of the kernel average smoother is the following. For each data point X 0, choose a constant distance size λ (kernel radius, or window width for p = 1 dimension), and compute a weighted average for all data points that are closer than to X 0 (the closer to X 0 points get higher weights).