Super Trend Fisher Indicator

Super Trend Fisher Indicator

Discover the Super Trend Fisher Indicator: Analysis and Applications in ProRealTime

Introduction

The Super Trend Fisher indicator stands out as an advanced tool that combines several analytical methods to deliver clear and timely signals. This indicator is especially valued for its ability to adapt to different market conditions and its ease of integration into various trading strategies.

Description of the Super Trend Fisher Indicator

The Super Trend Fisher is a complex technical indicator that incorporates elements of the Detrended Price Oscillator, Fisher Transform, and the calculation of the Average True Range (ATR) to dynamically adjust trend levels. Its main goal is to identify the direction of the trend and signal possible reversals, using a methodology that adjusts its parameters in real-time to capture market volatility.

  • Detrended Price Oscillator (DPO): Measures the deviation of the price from its moving average, helping to identify short-term price cycles stripped of long-term trends.
  • Fisher Transform: Converts prices into a Gaussian distribution to produce clearer and timelier signals.
  • Average True Range (ATR): Used to calculate market volatility, the ATR helps adjust the SuperTrend thresholds to be more responsive during volatile market conditions.
  • SuperTrend: Combines direction of the trend and volatility, offering a clear visual summary of the current market situation.

Functioning of the Indicator

The Super Trend Fisher uses a combination of analytical techniques to provide an integrated and deeply contextual view of market behavior. Below is an explanation of how each component of the indicator is calculated:

  • Calculation of the Detrended Price Oscillator: The moving average is subtracted from the closing price, which helps eliminate long-term price variations and focus on short-term fluctuations.
  • Application of the Fisher Transform: This transform alters the distribution of price data to make overbought and oversold areas more identifiable and accessible for technical analysis.
  • Integration of the ATR: The ATR adjusts the limits of the SuperTrend according to market volatility, allowing the indicator to be effective under different market conditions.

Practical Applications

The Super Trend Fisher indicator is exceptionally useful for traders looking to quickly identify market trends and reversal points. Here are some ways to interpret the signals provided by this indicator:

  • Trend Identification: When the indicator moves above the zero level and changes color, it indicates a possible entry into an uptrend. Conversely, a movement below the zero level with a color change suggests a downtrend.
  • Buy and Sell Signals: A buy signal may be considered when the Super Trend Fisher changes from red to green and is above the zero line. Conversely, a sell signal is suggested when it changes from green to red and is located below the zero line.
  • Optimization of Entries and Exits: Combining the Super Trend Fisher with other momentum or volume indicators can help refine entries and exits, thereby improving risk management and the effectiveness of trading strategies.

Setup and Customization

Copy and paste the code provided in the programming section of the editor. Adjust the parameters period, length, len, stFactor, and stPeriod according to your specific needs to tailor the sensitivity and reactivity of the indicator.

  • Application and Analysis: Once the code is adjusted, apply the indicator to the chart. Observe how the indicator interacts with price movements and adjust settings if necessary to optimize signals.

Conclusions

The Super Trend Fisher indicator offers a robust combination of technical analysis and adaptability, making it a valuable tool for any trader. Its ability to integrate multiple analytical techniques into a single indicator allows for a richer and more nuanced interpretation of the markets. As with any trading tool, it is recommended to combine the Super Trend Fisher with proper risk management and a coherent trading strategy.

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Risk disclosure:

No information on this site is investment advice or a solicitation to buy or sell any financial instrument. Past performance is not indicative of future results. Trading may expose you to risk of loss greater than your deposits and is only suitable for experienced investors who have sufficient financial means to bear such risk.

ProRealTime ITF files and other attachments : How to import ITF files into ProRealTime platform?

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  1. Stenozar • 42 days ago #

    Scusa Ivan, ho trovato un’altra versione di supertrend, Kalmana Hull Supertrand, che mi pare interessante ma non mi fa creare un nuovo topic, non so per quale motivo. Provo a incollare il codice qui, se tu potessi tradurlo. Grazie
    /////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
    // This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
    // © BackQuant

    //@version=5
    indicator(
    title = “Kalman Hull Supertrend [BackQuant]”,
    shorttitle = “Kalman Hull ST [BackQuant]”,
    overlay=true,
    precision = 2,
    format = format.price,
    timeframe = “”,
    timeframe_gaps = true
    )

    // Define User Inputs
    series float pricesource = input.source(close, “Kalman Price Source”, group = “Calculation”)
    simple float measurementNoise = input.float(3.0, title=”Measurement Noise”, group = “Calculation”, tooltip = “Lookback Period/ Calculation Length”, step = 1.0)
    simple float processNoise = input.float(0.01, title=”Process Noise”, step = 0.01, group = “Calculation”)

    simple int atrPeriod = input.int(12, “ATR Period”, group = “Supertrend”, inline = “ST”)
    simple float factor = input.float(1.7, “Factor”, group = “Supertrend”, inline = “ST”, step = 0.01)

    simple bool showkalman = input.bool(true, “Show Supertrend on chart?”, group = “UI Settings”)
    simple bool paintCandles = input.bool(true, “Paint candles according to Trend?”, group = “UI Settings”)
    simple bool showlongshort = input.bool(true, “Show Long and Short Signals { + }”, group = “UI Settings”)

    color longColor = input.color(#33ff00, “Long Color”, group = “UI Settings”, inline = “Col”)
    color shortColor = input.color(#ff0000, “Short Color”, group = “UI Settings”, inline = “Col”)
    /////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
    // Kalman Price Filter Function
    N = 5
    var float[] stateEstimate = array.new_float(N, na)
    var float[] errorCovariance = array.new_float(N, 100.0)
    f_init(series float pricesource) =>
    if na(array.get(stateEstimate, 0))
    for i = 0 to N-1
    array.set(stateEstimate, i, pricesource)
    array.set(errorCovariance, i, 1.0)

    f_kalman(series float pricesource, float measurementNoise) =>
    // Prediction Step
    predictedStateEstimate = array.new_float(N)
    predictedErrorCovariance = array.new_float(N)
    for i = 0 to N-1
    array.set(predictedStateEstimate, i, array.get(stateEstimate, i)) // Simplified prediction
    array.set(predictedErrorCovariance, i, array.get(errorCovariance, i) + processNoise)

    kalmanGain = array.new_float(N)
    for i = 0 to N-1
    kg = array.get(predictedErrorCovariance, i) / (array.get(predictedErrorCovariance, i) + measurementNoise)
    array.set(kalmanGain, i, kg)
    array.set(stateEstimate, i, array.get(predictedStateEstimate, i) + kg * (pricesource – array.get(predictedStateEstimate, i)))
    array.set(errorCovariance, i, (1 – kg) * array.get(predictedErrorCovariance, i))

    array.get(stateEstimate, 0)

    f_init(pricesource)
    kalmanFilteredPrice = f_kalman(pricesource, measurementNoise)
    /////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
    // Hull Moving Average Function with Kalman instead of Weighted Moving Average
    KHMA(_src, _length) =>
    f_kalman(2 * f_kalman(_src, _length / 2) – f_kalman(_src, _length), math.round(math.sqrt(_length)))
    // Return
    kalmanHMA = KHMA(pricesource, measurementNoise)
    /////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
    // Supertrend Function
    supertrend(factor, atrPeriod, src) =>
    atr = ta.atr(atrPeriod)
    upperBand = src + factor * atr
    lowerBand = src – factor * atr
    prevLowerBand = nz(lowerBand[1])
    prevUpperBand = nz(upperBand[1])

    lowerBand := lowerBand > prevLowerBand or close[1] < prevLowerBand ? lowerBand : prevLowerBand
    upperBand := upperBand prevUpperBand ? upperBand : prevUpperBand
    int direction = na
    float superTrend = na
    prevSuperTrend = superTrend[1]
    if na(atr[1])
    direction := 1
    else if prevSuperTrend == prevUpperBand
    direction := close > upperBand ? -1 : 1
    else
    direction := close < lowerBand ? 1 : -1
    superTrend := direction == -1 ? lowerBand : upperBand
    [superTrend, direction]

    // Call Function with Inputs
    [superTrend, direction] = supertrend(factor, atrPeriod, kalmanHMA)
    /////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
    // Conditional Trend
    SupertrendLong = ta.crossunder(direction, 0)
    SupertrendShort = ta.crossover(direction, 0)
    var Trend = 0
    if SupertrendLong and not SupertrendShort
    Trend := 1

    if SupertrendShort
    Trend := -1

    // Colouring
    var barColour = #ffffff
    if Trend == 1
    barColour := longColor
    if Trend == -1
    barColour := shortColor

    // Plotting
    plot(
    showkalman ? superTrend : na,
    "Kalman Hull ST",
    color = color.new(barColour, 40),
    linewidth = 4
    )

    barcolor(paintCandles ? barColour : na)

    // Long and Short Signals ()
    plotshape(
    showlongshort ? SupertrendLong : na,
    offset=0,
    title="Long",
    text="",
    style=shape.triangleup,
    location=location.belowbar,
    color=barColour,
    textcolor=barColour,
    size = size.tiny
    )
    plotshape(
    showlongshort ? SupertrendShort: na,
    offset=0,
    title="Short",
    text="",
    style=shape.triangledown,
    location=location.abovebar,
    color=barColour,
    textcolor=barColour,
    size = size.tiny
    )

    // Alert Conditions
    alertcondition(SupertrendLong, title="Kalman Hull ST Long", message="Kalman Hull ST Long {{exchange}}:{{ticker}}")
    alertcondition(SupertrendShort, title="Kalman Hull ST Short", message="Kalman Hull ST Short {{exchange}}:{{ticker}}")

    • Iván • 40 days ago #

      Ciao
      Certo, posso analizzare il codice per tradurlo, ma devi lanciare la richiesta da qui:
      https://www.prorealcode.com/free-code-conversion/

  2. Stenozar • 39 days ago #

    Ciao Ivan, ho provato ma non mi lascia caricare il post, non so per quale strano motivo…

    • Iván • 39 days ago #

      Allora crei un nuovo post. Lo aspetterò.

    • Stenozar • 35 days ago #

      Ciao Ivan, ho inserito il post con la richiesta di traduzione. Se puoi vedere, grazie!

    • Iván • 32 days ago #

      perfect!

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