IZAKI 0.618 TRADING ZONE
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Modjoy-Fractal Levels [BigBeluga]

Modjoy-Fractal Levels [BigBeluga]

Unlocking Trading Potential with Modjoy-Fractal Levels: A Comprehensive Guide

Technical analysis is a crucial aspect of trading, and one of the most effective tools in this realm is the Modjoy-Fractal Levels strategy, also known as BigBeluga. Developed by experienced traders, this approach has gained popularity due to its efficacy in identifying key price levels and predicting market movements. In this article, we will delve into the core logic and trading strategy of Modjoy-Fractal Levels, providing you with a deeper understanding of how to harness its potential in your trading endeavors.

Understanding Modjoy-Fractal Levels

Modjoy-Fractal Levels, or BigBeluga, is a trading strategy that utilizes fractal analysis to identify significant price levels. Fractals are geometric patterns that repeat at different scales, and in the context of trading, they represent self-similar price patterns that can be used to predict future price movements. The Modjoy-Fractal Levels strategy combines fractal analysis with other technical indicators to generate accurate trading signals.

Core Logic of Modjoy-Fractal Levels

The core logic of Modjoy-Fractal Levels revolves around the identification of fractal patterns in price charts. This is achieved through the use of specific algorithms that detect and analyze these patterns. The strategy focuses on the following key aspects:

  • Fractal Pattern Recognition: The strategy uses advanced algorithms to identify fractal patterns in price charts, which are then used to predict future price movements.
  • Price Level Identification: The Modjoy-Fractal Levels strategy identifies key price levels, including support and resistance levels, which are critical for making informed trading decisions.
  • Signal Generation: The strategy generates accurate trading signals based on the analysis of fractal patterns and price levels, providing traders with actionable insights.

Modjoy-Fractal Levels Trading Strategy

The Modjoy-Fractal Levels trading strategy involves the following steps:

  1. Chart Analysis: Conduct a thorough analysis of the price chart to identify fractal patterns and key price levels.
  2. Signal Generation: Use the Modjoy-Fractal Levels algorithm to generate trading signals based on the analysis of fractal patterns and price levels.
  3. Risk Management: Implement a robust risk management strategy to minimize potential losses and maximize gains.
  4. Trade Execution: Execute trades based on the generated signals, taking into account market conditions and other relevant factors.

Conclusion

In conclusion, the Modjoy-Fractal Levels strategy, also known as BigBeluga, is a powerful tool for traders seeking to improve their technical analysis skills and make more informed trading decisions. By understanding the core logic and trading strategy of Modjoy-Fractal Levels, traders can unlock the full potential of this approach and enhance their trading performance. Whether you are a seasoned trader or just starting out, the Modjoy-Fractal Levels strategy is definitely worth exploring.


Modjoy Exclusive Source Code:

MODJOY-FRACTAL LEVELS [BIGBELUGA] SOURCE CODE
//@version=5
indicator("Modjoy-Fractal Levels [BigBeluga]", 
         overlay            = true,
         max_labels_count   = 75,
         max_bars_back      = 1000, 
         max_lines_count    = 500, 
         max_boxes_count    = 100)

// USER INPUTS‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗{

// Inputs for fractal detection and filtering
int  length     = input(10, "Length")                         // Length for detecting pivot highs and lows
int  filter     = input(2)                                   // Filter to display only significant volume levels
bool zone       = input.string("Wide", "Level Detects Zones", ["Wide", "Tight"]) == "Tight"  // Detection zone type (Tight or Wide)

// Additional options for volume delta display and line styles
bool show_delta = input.bool(false, "Delta Volume Fractals")  // Show volume delta for fractals
bool show_broke = input.bool(false, "Broken Levels")         // Display broken levels

// Color inputs for bullish and bearish fractal lines
color up        = #14b477                              // Color for bullish fractals (up)
color dn        = color.rgb(204, 51, 71)              // Color for bearish fractals (down)

// }
// CALCULATIONS‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗{

// Detecting pivot highs and lows based on the input length
series float ph = ta.pivothigh(open, length, length)           // Detect pivot highs
series float pl = ta.pivotlow (close, length, length)         // Detect pivot lows

// Initialize label variables to store fractal markers
label lbl1      = label(na)                                   // Label for bullish fractals
label lbl2      = label(na)                                  // Label for bearish fractals

// Arrays to store volume data and fractal levels
array    vol1  = array.new()                    // Array for normalized volume values
array    vol2  = array.new()                   // Array for delta volume values
var array lines = array.new(50)                 // Array to store fractal lines
array      boxes = array.new()                   // Array to store fractal zones (boxes)

// Method to normalize values between 0 and 100
method normalize(float src)=>
    int   coef  = 100
    float value = ((src - ta.lowest(src, 200)) / (ta.highest(src, 200) - ta.lowest(src, 200))) * coef
    value

// Calculating normalized volume and volatility
series float volume_val = volume.normalize()                  // Normalize volume between 0 and 100
series float volatility = ta.sma(high - low, 200)            // Calculate volatility using the simple moving average of range
series float delta_vol  = close > open ? volume : -volume   // Delta volume calculation (positive for bullish candles, negative for bearish candles)

// }
// FRACTAL DETECTION AND VOLUME ZONES‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗{

if last_bar_index - bar_index < 1000   // Limiting the calculation within the lookback period
    // Detect Pivot High (Bearish Fractals)
    if not na(ph)
        lbl1 := label.new(na, na, color = color(na), style = label.style_label_down)

        // Calculate average volume and delta volume for the detected fractal
        for i = 0 to length * 2
            vol1.push(volume_val[i])
            vol2.push(delta_vol[i])

        series float volume_avg1 = math.round(vol1.avg())      // Average normalized volume
        series float volume_sum2 = vol2.sum()                 // Sum of delta volume

        // Creating labels and drawing lines and boxes for bearish fractals
        string txt = str.tostring(volume_avg1) + "\n🢃" 
        int    x1  = bar_index[length]
        int    x2  = bar_index[length]
        float  y1  = high[length] + volatility * (zone ? 1.5 : 2.5)
        float  y2  = high[length] - volatility * (zone ? 1.5 : 2.5)
        float  y   = high[length]

        color color = color.from_gradient(volume_avg1, 0, 20,  color.new(dn, 70), dn)

        // Drawing lines and boxes if volume exceeds filter
        if volume_avg1 > filter
            lines.push(line.new(x1, y, x2, y, color = color, width = 3))
            boxes.push(box.new(x1, y1, x2, y2, border_width = 0, bgcolor = color(na)))

            // Optionally display delta volume for fractals
            if show_delta
                box.new(
                         bar_index[length*2], high[length], bar_index, high[length] - volatility*2.5, 
                         border_width = 0, 
                         bgcolor      = color.from_gradient(vol1.avg(), 0, 205, 
                                         color.new(chart.fg_color, 98), color.new(chart.fg_color, 40)), 
                         text         = str.tostring(volume_sum2, format.volume), 
                         text_size    = size.small,
                         text_color   = chart.fg_color,
                         text_halign  = text.align_right, 
                         text_valign  = text.align_top
                         )

            lbl1.set_xy(bar_index[length], high[length])
            lbl1.set_text(txt)
            lbl1.set_textcolor(dn)

    // Detect Pivot Low (Bullish Fractals)
    if not na(pl)
        lbl2 := label.new(na, na, color = color(na), style = label.style_label_up)

        // Calculate average volume and delta volume for the detected fractal
        for i = 0 to length * 2
            vol1.push(volume_val[i])
            vol2.push(delta_vol[i])

        series float volume_avg1 = math.round(vol1.avg())      // Average normalized volume
        series float volume_sum2 = vol2.sum()                 // Sum of delta volume

        // Creating labels and drawing lines and boxes for bullish fractals
        string txt = "🢁\n" + str.tostring(volume_avg1)  
        int    x1  = bar_index[length]
        int    x2  = bar_index[length]
        float  y1  = low[length] + volatility * (zone ? 1 : 1.5)
        float  y2  = low[length] - volatility * (zone ? 1 : 1.5)
        float  y   = low[length]

        color color = color.from_gradient(volume_avg1, 0, 20, color.new(up, 70), up)
        
        // Drawing lines and boxes if volume exceeds filter
        if volume_avg1 > filter
            lines.push(line.new(x1, y, x2, y, color = color, width = 3))
            boxes.push(box.new(x1, y1, x2, y2, border_width = 0, bgcolor = color(na)))

            // Optionally display delta volume for fractals
            if show_delta
                box.new(
                         bar_index[length*2], low[length], bar_index, low[length] + volatility*2.5, 
                         border_width = 0, 
                         bgcolor      = color.new(chart.fg_color, 90), 
                         text         = str.tostring(volume_sum2, format.volume), 
                         text_size    = size.small,
                         text_color   = chart.fg_color,
                         text_halign  = text.align_left, 
                         text_valign  = text.align_bottom
                         )

            lbl2.set_xy(bar_index[length], low[length])
            lbl2.set_text(txt)
            lbl2.set_textcolor(up)


// }
// BROKEN LEVELS DETECTION ‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗‗{

// Handle logic for broken levels (levels that price crosses)
for line_id in lines
    float line_y  = line_id.get_y1()

    // If price crosses the fractal line, change its width or delete it
    if hl2 > line_y and hl2[1] <= line_y or hl2 < line_y and hl2[1] >= line_y and barstate.isconfirmed
        if show_broke
            line_id.set_width(3)
            line_id.set_color(color.new(chart.fg_color, 92))
        if not show_broke
            line.delete(line_id)

    // Extend the fractal lines as the bars move forward
    if  line_id.get_x1() < line_id.get_x2()
        line_id.set_x2(bar_index+15)

// Update boxes with fractal lines
for box_id in boxes
    float top    = box_id.get_top()
    float bottom = box_id.get_bottom()

    for line_id in lines
        float line_y = line_id.get_y2()

        // Adjust box dimensions when lines are broken
        if line_y > bottom and line_y < top
            line_id.set_x2(bar_index[length])

// A dummy line to ensure proper execution of the script
line.new(na, na, na, na)

// Warning if no volume
if ta.cum(volume) <= 0 and barstate.islast
    label.new(bar_index, hl2, "No Volume Data is provided\n Check other tickers",
                  style     = label.style_label_left, 
                  textcolor = chart.fg_color) 

// }


⚠️ High Risk Warning

Trading Forex and Futures involves a very high degree of risk and may not be suitable for all investors. The high degree of leverage can result in the complete loss of your funds. These indicators are educational tools and do not guarantee profits. Please trade responsibly with capital you can afford to lose.