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    Advanced MACD

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    shanmugam
    This study defines an advanced version of the moving average convergence divergence (MACD) indicator. It allows the user to customize the type of moving averages used (simple, exponential, weighted, etc.) and choose whether to volume weight the indicator. Volume weighting turns it into a volume-weighted MACD, while weighting against true range can also be selected. The indicator is more customizable than the standard MACD.

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    © All Rights Reserved
    Download as TXT, PDF, TXT or read online from Scribd

    Advanced MACD

    Uploaded by

    shanmugam
    268 views2 pages
    This study defines an advanced version of the moving average convergence divergence (MACD) indicator. It allows the user to customize the type of moving averages used (simple, exponential, weighted, etc.) and choose whether to volume weight the indicator. Volume weighting turns it into a volume-weighted MACD, while weighting against true range can also be selected. The indicator is more customizable than the standard MACD.

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    This study defines an advanced version of the moving average convergence divergence (MACD) indicator. It allows the user to customize the type of moving averages used (simple, exponential, weighted, etc.) and choose whether to volume weight the indicator. Volume weighting turns it into a volume-weighted MACD, while weighting against true range can also be selected. The indicator is more customizable than the standard MACD.

    Copyright:

    © All Rights Reserved
    Download as TXT, PDF, TXT or read online from Scribd
    Download as txt, pdf, or txt
    268 views2 pages

    Advanced MACD

    Uploaded by

    shanmugam
    This study defines an advanced version of the moving average convergence divergence (MACD) indicator. It allows the user to customize the type of moving averages used (simple, exponential, weighted, etc.) and choose whether to volume weight the indicator. Volume weighting turns it into a volume-weighted MACD, while weighting against true range can also be selected. The indicator is more customizable than the standard MACD.

    Copyright:

    © All Rights Reserved
    Download as TXT, PDF, TXT or read online from Scribd
    Download as txt, pdf, or txt
    of 2

    //@version=4

    study(title="Advanced MACD", shorttitle="MACD", resolution="")


    tema(s, p) =>
    3 * ema(s, p) - 3 * ema(ema(s, p), p) + ema(ema(ema(s, p), p), p)
    ma(t, s, p) =>
    ema_1 = ema(s, p)
    rma_1 = rma(s, p)
    vwma_1 = vwma(s, p)
    wma_1 = wma(s, p)
    tema_1 = tema(s, p)
    sma_1 = sma(s, p)
    t == "ema" ? ema_1 : t == "rma" ? rma_1 :
    t == "vwma" ? vwma_1 : t == "wma" ? wma_1 : t == "tema" ? tema_1 : sma_1
    src = input(close, title="Source")
    fastLength = input(12, title="Fast Length", type=input.integer, minval=1)
    slowLength = input(26, title="Slow Length", type=input.integer, minval=1)
    signalLength = input(9, title="Signal Length", type=input.integer, minval=1)
    volumeWeighted = input(true, title="Volume Weighted", type=input.bool)
    volumeLength = input(3, title="Volume Length", type=input.integer, minval=1)
    volumePower = input(1, title="Volume Power", type=input.integer, minval=1)
    ppo = input(false, title="Percentage Price Oscillator", type=input.bool)
    fastType = input(defval="ema", options=["ema", "sma", "rma", "vwma", "wma",
    "tema"], title="Fast Moving Average Type")
    slowType = input(defval="ema", options=["ema", "sma", "rma", "vwma", "wma",
    "tema"], title="Slow Moving Average Type")
    signalType = input(defval="sma", options=["ema", "sma", "rma", "vwma", "wma",
    "tema"], title="Signal Moving Average Type")
    vwType = input(defval="ema", options=["ema", "sma", "rma", "vwma", "wma", "tema"],
    title="Volume Weighted Moving Average Type")
    useTrueRange = input(defval="Auto", options=["Always", "Auto", "Never"], title="Use
    True Range instead of Volume")
    isSMACD = input(false, title="Stochastic MACD", type=input.bool)
    stochLength = input(45, title="Stochastic Length", type=input.integer, minval=1)
    stochType = input(defval="ema", options=["ema", "sma", "rma", "vwma", "wma",
    "tema"], title="Stochastic Moving Average Type")
    vol = useTrueRange == "Always" or useTrueRange == "Auto" and na(volume) ? tr :
    volume
    slowMA = float(na)
    fastMA = float(na)
    if volumeWeighted
    volMA = ma(vwType, pow(vol, volumePower), volumeLength)
    fastMA := ma(fastType, volMA * src, fastLength) / ma(fastType, volMA,
    fastLength)
    slowMA := ma(slowType, volMA * src, slowLength) / ma(slowType, volMA,
    slowLength)
    else
    fastMA := ma(fastType, src, fastLength)
    slowMA := ma(slowType, src, slowLength)

    macd = ppo ? (fastMA - slowMA) / slowMA * 100 : fastMA - slowMA

    if isSMACD
    fastStoch = (fastMA - lowest(low, stochLength)) /
    (highest(high, stochLength) - lowest(low, stochLength))
    slowStoch = (slowMA - lowest(low, stochLength)) /
    (highest(high, stochLength) - lowest(low, stochLength))
    macd := (fastStoch - slowStoch) * 100
    macd := ma(stochType, macd, signalLength)
    signal = ma(signalType, macd, signalLength)
    hist = macd - signal
    plot(macd, title='MACD', color=#000099, linewidth=1)
    plot(signal, title='Signal', color=#990000, linewidth=1)
    plot(hist, title='Histogram', color=#009900, linewidth=3, transp=70,
    style=plot.style_histogram)
    hline(0, title="Zero", color=color.gray, linestyle=hline.style_dashed)

    //This is a more advanced version of the standard moving average


    convergence/divergence indicator ( MACD ). It allows you to change the type of all
    moving averages (Simple, Exponential, Weighted, Volume-weighted, Triple EMA or a
    moving average that uses RSI ). By for example setting the period to 3/10/16 and
    use simple moving averages instead of exponential moving averages you can turn it
    into the modified version of the MACD oscillator (mMACD) described in detail in
    Appendix B in the book "The Art and Science of Technical Analysis: Market
    Structure, Price Action and Trading Strategies" by Adam Grimes.

    The indicator also allows you to volume weight the indicator (turned on by
    default), which will turn it into a Volume-Weighted Moving Average Convergence
    Divergence (VW-MACD) first used by Buff Pelz Dormeier in 2002 and described in
    detail in his book "Investing with Volume Analysis: Identify, Follow, and Profit
    from Trends". If you want to weight the oscillator against the true range instead
    of volume this is also possible. By default, this will be done automatically for
    assets that do not support volume .

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