BK AK-SILENCER (P8N)🚨Introducing BK AK-SILENCER (P8N) — Institutional Order Flow Tracking for Silent Precision🚨
After months of meticulous tuning and refinement, I'm proud to unleash the next weapon in my trading arsenal—BK AK-SILENCER (P8N).
🔥 Why "AK-SILENCER"? The True Meaning
Institutions don’t announce their moves—they move silently, hidden beneath the noise. The SILENCER is built specifically to detect and track these stealth institutional maneuvers, giving you the power to hunt quietly, execute decisively, and strike precisely before the market catches on.
🔹 "AK" continues the legacy, honoring my mentor, A.K., whose teachings on discipline, precision, and clarity form the cornerstone of my trading.
🔹 "SILENCER" symbolizes the stealth aspect of institutional trading—quiet but deadly moves. This indicator equips you to silently track, expose, and capitalize on their hidden footprints.
🧠 What Exactly is BK AK-SILENCER (P8N)?
It's a next-generation Cumulative Volume Delta (CVD) tool crafted specifically for traders who hunt institutional order flow, combining adaptive volatility bands, enhanced momentum gradients, and precise divergence detection into a single deadly-accurate weapon.
Built for silent execution—tracking moves quietly and trading with lethal precision.
⚙️ Core Weapon Systems
✅ Institutional CVD Engine
→ Dynamically measures hidden volume shifts (buying/selling pressure) to reveal institutional footprints that price alone won't show.
✅ Adaptive AK-9 Bollinger Bands
→ Bollinger Bands placed around a custom CVD signal line, pinpointing exactly when institutional accumulation or distribution reaches critical extremes.
✅ Gradient Momentum Intelligence
→ Color-coded momentum gradients reveal the strength, speed, and silent intent behind institutional order flow:
🟢 Strong Bullish (aggressive buying)
🟡 Moderate Bullish (steady accumulation)
🔵 Neutral (balance)
🟠 Moderate Bearish (quiet distribution)
🔴 Strong Bearish (aggressive selling)
✅ Silent Divergence Detection
→ Instantly spots divergence between price and hidden volume—your earliest indication that institutions are stealthily reversing direction.
✅ Background Flash Alerts
→ Visually highlights institutional extremes through subtle background flashes, alerting you quietly yet powerfully when market-moving players make their silent moves.
✅ Structural & Institutional Clarity
→ Optional structural pivots, standard deviation bands, volume profile anchors, and session lines clearly identify the exact levels institutions defend or attack silently.
🛡️ Why BK AK-SILENCER (P8N) is Your Edge
🔹 Tracks Institutional Footprints—Silently identifies hidden volume signals of institutional intentions before they’re obvious.
🔹 Precision Execution—Cuts through noise, allowing you to execute silently, confidently, and precisely.
🔹 Perfect for Traders Using:
Elliott Wave
Gann Methods (Angles, Squares)
Fibonacci Time & Price
Harmonic Patterns
Market Profile & Order Flow Analysis
🎯 How to Use BK AK-SILENCER (P8N)
🔸 Institutional Reversal Hunting (Stealth Mode)
Bearish divergence + CVD breaking below lower BB → stealth short signal.
Bullish divergence + CVD breaking above upper BB → quiet, early long entry.
🔸 Momentum Confirmation (Silent Strength)
Strong bullish gradient + CVD above upper BB → follow institutional buying quietly.
Strong bearish gradient + CVD below lower BB → confidently short institutional selling.
🔸 Noise Filtering (Patience & Precision)
Neutral gradient (blue) → remain quiet, wait patiently to strike precisely when institutional activity resumes.
🔸 Structural Precision (Institutional Levels)
Optional StdDev, POC, Value Areas, Session Anchors clearly identify exact institutional defense/offense zones.
🙏 Final Thoughts
Institutions move in silence, leaving subtle footprints. BK AK-SILENCER (P8N) is your specialized weapon for tracking and hunting their quiet, decisive actions before the market reacts.
🔹 Dedicated in deep gratitude to my mentor, A.K.—whose silent wisdom shapes every line of code.
🔹 Engineered for the disciplined, quiet hunter who knows when to wait patiently and when to strike decisively.
Above all, honor and gratitude to Gd—the ultimate source of wisdom, clarity, and disciplined execution. Without Him, markets are chaos. With Him, we move silently, purposefully, and precisely.
⚡ Stay Quiet. Stay Precise. Hunt Silently.
🔥 BK AK-SILENCER (P8N) — Track the Silent Moves. Strike with Precision. 🔥
May Gd bless every silent step you take. 🙏
Cerca negli script per "TAKE"
MC Geopolitical Tension Events📌 Script Title: Geopolitical Tension Events
📖 Description:
This script highlights key geopolitical and military tension events from 1914 to 2024 that have historically impacted global markets.
It automatically plots vertical dashed lines and labels on the chart at the time of each major event. This allows traders and analysts to visually assess how markets have responded to global crises, wars, and significant political instability over time.
🧠 Use Cases:
Historical backtesting: Understand how market responded to past geopolitical shocks.
Contextual analysis: Add macro context to technical setups.
🗓️ List of Geopolitical Tension Events in the Script
Date Event Title Description
1914-07-28 WWI Begins Outbreak of World War I following the assassination of Archduke Franz Ferdinand.
1929-10-24 Wall Street Crash Black Thursday, the start of the 1929 stock market crash.
1939-09-01 WWII Begins Germany invades Poland, starting World War II.
1941-12-07 Pearl Harbor Japanese attack on Pearl Harbor; U.S. enters WWII.
1945-08-06 Hiroshima Bombing First atomic bomb dropped on Hiroshima by the U.S.
1950-06-25 Korean War Begins North Korea invades South Korea.
1962-10-16 Cuban Missile Crisis 13-day standoff between the U.S. and USSR over missiles in Cuba.
1973-10-06 Yom Kippur War Egypt and Syria launch surprise attack on Israel.
1979-11-04 Iran Hostage Crisis U.S. Embassy in Tehran seized; 52 hostages taken.
1990-08-02 Gulf War Begins Iraq invades Kuwait, triggering U.S. intervention.
2001-09-11 9/11 Attacks Coordinated terrorist attacks on the U.S.
2003-03-20 Iraq War Begins U.S.-led invasion of Iraq to remove Saddam Hussein.
2008-09-15 Lehman Collapse Bankruptcy of Lehman Brothers; peak of global financial crisis.
2014-03-01 Crimea Crisis Russia annexes Crimea from Ukraine.
2020-01-03 Soleimani Strike U.S. drone strike kills Iranian General Qasem Soleimani.
2022-02-24 Ukraine Invasion Russia launches full-scale invasion of Ukraine.
2023-10-07 Hamas-Israel War Hamas launches attack on Israel, sparking war in Gaza.
2024-01-12 Red Sea Crisis Houthis attack ships in Red Sea, prompting Western naval response.
Robby DSS Bressert Colored DotsIntroduction
The Robby DSS Bressert Colored Dots is a technical analysis tool designed to measure momentum and identify potential overbought or oversold conditions in a market. It is a visually enhanced version of the Double Smoothed Stochastic (DSS) indicator, which was developed to be a smoother and more responsive version of the traditional Stochastic Oscillator.
This specific version provides at-a-glance information about momentum shifts through the use of colored dots, making it easy to interpret.
The Core Engine: DSS Bressert
The foundation of this indicator is the Double Smoothed Stochastic, a concept attributed to both William Blau and Walter Bressert, who introduced similar ideas. The goal of the DSS is to filter out the "noise" and false signals common in standard oscillators without introducing significant lag.
It achieves this through a two-step smoothing process:
First Smoothing: A standard Stochastic value is calculated based on the price. This value is then smoothed using an Exponential Moving Average (EMA). This creates a cleaner, less erratic line than the raw stochastic.
Second Smoothing: The indicator then takes this newly smoothed line and performs a second Stochastic calculation on it. This result is then smoothed one final time with another EMA.
This double-application of smoothing results in a very clean oscillator line that reacts quickly to price changes but is less prone to whipsaws.
The Visual Modification: "Robby" Colored Dots
The "Robby DSS Bressert Colored Dots" version takes the powerful DSS calculation and adds a unique visual layer for easier interpretation.
Colored Dots: Instead of plotting a continuous line, the indicator displays a dot for each candle. The color of this dot instantly tells you about the indicator's momentum:
Lime/Green dots appear when the DSS value is rising, indicating bullish or positive momentum.
Red dots appear when the DSS value is falling, indicating bearish or negative momentum.
If the value is unchanged, the dot retains the color of the previous one.
The "Robby" Name: In trading communities like Forex Factory and MQL5, it's common for programmers to modify popular indicators. These enhanced versions are often named after the member who created or popularized them. The "Robby" version specifically refers to this popular colored-dot modification of the DSS Bressert.
How to Interpret and Use It
Traders typically use the Robby DSS Bressert Colored Dots in a few key ways:
Momentum Shifts: The most straightforward signal is the change of dot color. A switch from red to lime can signal that downside momentum is waning and a potential move up is beginning. A switch from lime to red signals the opposite.
Overbought & Oversold Conditions: Like a standard stochastic, the indicator uses levels (typically 80 and 20).
When the dots are above 80, the market is considered overbought. A color change from lime to red in this zone can be a strong signal for a potential reversal down.
When the dots are below 20, the market is considered oversold. A color change from red to lime here can signal a potential reversal up.
Trend Confirmation: In a strong uptrend, traders might ignore red dots and use the appearance of lime dots in the oversold zone (or after a minor pullback) as a signal to join the trend. The opposite is true in a downtrend.
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This is just an indicator that can found publicly online for mt4, and just translated it to Pinescript.
DrawZigZag🟩 OVERVIEW
This library draws zigzag lines for existing pivots. It is designed to be simple to use. If your script creates pivots and you want to join them up while handling edge cases, this library does that quickly and efficiently. If you want your pivots created for you, choose one of the many other zigzag libraries that do that.
🟩 HOW TO USE
Pine Script libraries contain reusable code for importing into indicators. You do not need to copy any code out of here. Just import the library and call the function you want.
For example, for version 1 of this library, import it like this:
import SimpleCryptoLife/DrawZigZag/1
See the EXAMPLE USAGE sections within the library for examples of calling the functions.
For more information on libraries and incorporating them into your scripts, see the Libraries section of the Pine Script User Manual.
🟩 WHAT IT DOES
I looked at every zigzag library on TradingView, after finishing this one. They all seemed to fall into two groups in terms of functionality:
• Create the pivots themselves, using a combination of Williams-style pivots and sometimes price distance.
• Require an array of pivot information, often in a format that uses user-defined types.
My library takes a completely different approach.
Firstly, it only does the drawing. It doesn't calculate the pivots for you. This isn't laziness. There are so many ways to define pivots and that should be up to you. If you've followed my work on market structure you know what I think of Williams pivots.
Secondly, when you pass information about your pivots to the library function, you only need the minimum of pivot information -- whether it's a High or Low pivot, the price, and the bar index. Pass these as normal variables -- bools, ints, and floats -- on the fly as your pivots confirm. It is completely agnostic as to how you derive your pivots. If they are confirmed an arbitrary number of bars after they happen, that's fine.
So why even bother using it if all it does it draw some lines?
Turns out there is quite some logic needed in order to connect highs and lows in the right way, and to handle edge cases. This is the kind of thing one can happily outsource.
🟩 THE RULES
• Zigs and zags must alternate between Highs and Lows. We never connect a High to a High or a Low to a Low.
• If a candle has both a High and Low pivot confirmed on it, the first line is drawn to the end of the candle that is the opposite to the previous pivot. Then the next line goes vertically through the candle to the other end, and then after that continues normally.
• If we draw a line up from a Low to a High pivot, and another High pivot comes in higher, we *extend* the line up, and the same for lines down. Yes this is a form of repainting. It is in my opinion the only way to end up with a correct structure.
• We ignore lower highs on the way up and higher lows on the way down.
🟩 WHAT'S COOL ABOUT THIS LIBRARY
• It's simple and lightweight: no exported user-defined types, no helper methods, no matrices.
• It's really fast. In my profiling it runs at about ~50ms, and changing the options (e.g., trimming the array) doesn't make very much difference.
• You only need to call one function, which does all the calculations and draws all lines.
• There are two variations of this function though -- one simple function that just draws lines, and one slightly more advanced method that modifies an array containing the lines. If you don't know which one you want, use the simpler one.
🟩 GEEK STUFF
• There are no dependencies on other libraries.
• I tried to make the logic as clear as I could and comment it appropriately.
• In the `f_drawZigZags` function, the line variable is declared using the `var` keyword *inside* the function, for simplicity. For this reason, it persists between function calls *only* if the function is called from the global scope or a local if block. In general, if a function is called from inside a loop , or multiple times from different contexts, persistent variables inside that function are re-initialised on each call. In this case, this re-initialisation would mean that the function loses track of the previous line, resulting in incorrect drawings. This is why you cannot call the `f_drawZigZags` function from a loop (not that there's any reason to). The `m_drawZigZagsArray` does not use any internal `var` variables.
• The function itself takes a Boolean parameter `_showZigZag`, which turns the drawings on and off, so there is no need to call the function conditionally. In the examples, we do call the functions from an if block, purely as an illustration of how to increase performance by restricting the amount of code that needs to be run.
🟩 BRING ON THE FUNCTIONS
f_drawZigZags(_showZigZag, _isHighPivot, _isLowPivot, _highPivotPrice, _lowPivotPrice, _pivotIndex, _zigzagWidth, _lineStyle, _upZigColour, _downZagColour)
This function creates or extends the latest zigzag line. Takes real-time information about pivots and draws lines. It does not calculate the pivots. It must be called once per script and cannot be called from a loop.
Parameters:
_showZigZag (bool) : Whether to show the zigzag lines.
_isHighPivot (bool) : Whether the current bar confirms a high pivot. Note that pivots are confirmed after the bar in which they occur.
_isLowPivot (bool) : Whether the current bar confirms a low pivot.
_highPivotPrice (float) : The price of the high pivot that was confirmed this bar. It is NOT the high price of the current bar.
_lowPivotPrice (float) : The price of the low pivot that was confirmed this bar. It is NOT the low price of the current bar.
_pivotIndex (int) : The bar index of the pivot that was confirmed this bar. This is not an offset. It's the `bar_index` value of the pivot.
_zigzagWidth (int) : The width of the zigzag lines.
_lineStyle (string) : The style of the zigzag lines.
_upZigColour (color) : The colour of the up zigzag lines.
_downZagColour (color) : The colour of the down zigzag lines.
Returns: The function has no explicit returns. As a side effect, it draws or updates zigzag lines.
method m_drawZigZagsArray(_a_zigZagLines, _showZigZag, _isHighPivot, _isLowPivot, _highPivotPrice, _lowPivotPrice, _pivotIndex, _zigzagWidth, _lineStyle, _upZigColour, _downZagColour, _trimArray)
Namespace types: array
Parameters:
_a_zigZagLines (array)
_showZigZag (bool) : Whether to show the zigzag lines.
_isHighPivot (bool) : Whether the current bar confirms a high pivot. Note that pivots are usually confirmed after the bar in which they occur.
_isLowPivot (bool) : Whether the current bar confirms a low pivot.
_highPivotPrice (float) : The price of the high pivot that was confirmed this bar. It is NOT the high price of the current bar.
_lowPivotPrice (float) : The price of the low pivot that was confirmed this bar. It is NOT the low price of the current bar.
_pivotIndex (int) : The bar index of the pivot that was confirmed this bar. This is not an offset. It's the `bar_index` value of the pivot.
_zigzagWidth (int) : The width of the zigzag lines.
_lineStyle (string) : The style of the zigzag lines.
_upZigColour (color) : The colour of the up zigzag lines.
_downZagColour (color) : The colour of the down zigzag lines.
_trimArray (bool) : If true, the array of lines is kept to a maximum size of two lines (the line elements are not deleted). If false (the default), the array is kept to a maximum of 500 lines (the maximum number of line objects a single Pine script can display).
Returns: This function has no explicit returns but it modifies a global array of zigzag lines.
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
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14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
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Supply/Demand Zones + Engulfment-based ExecutionSupply/Demand Zones + Engulfment-Based Execution
Strategy Overview
This strategy combines institutional trading concepts—supply/demand zones and engulfing candle patterns—to generate high-probability long and short trade setups. The system uses aggregated price action to identify potential reversal zones and confirms entries with engulfing candle patterns, ensuring trades are only taken when market structure shows commitment in the direction of the trade.
Core Concepts
• Supply & Demand Zones: These are automatically detected by analyzing aggregated bullish and bearish candle structures over user-defined intervals. Supply zones are formed after bearish continuation patterns; demand zones appear after bullish continuation patterns.
• Engulfing Entries: Once price enters a zone, the strategy waits for a bullish engulfing pattern (in a demand zone) or a bearish engulfing pattern (in a supply zone) before executing a trade. This adds confirmation and reduces false signals.
• Risk Management: Stop-loss is placed at the low (for long trades) or high (for short trades) of the engulfed candle. Take-profit can be calculated using a fixed R-multiple (risk-to-reward ratio) or a user-defined target price.
Key Features
Fully customizable aggregation factor for zone detection
Visual zone boxes, entry/SL/TP boxes, and engulfing pattern labels
Optional removal of mitigated zones for cleaner charting
Configurable trade mode (Long only, Short only, or Both)
Support for trading sessions and date filtering
Alerts for price entering supply or demand zones
How to Use
Select Aggregation Factor: Choose how many candles to group together for identifying key zones (e.g., 4x timeframe).
Enable Zones: Turn on supply and/or demand zones as needed.
Set Execution Parameters:
– Choose R-multiple (e.g., 2:1 risk-reward)
– Or use a fixed take-profit price
Define Trade Time Window:
– Set the date and time ranges to restrict execution
– Use Start Hour and End Hour to limit trades to specific sessions (e.g., London/New York)
Run on Desired Timeframe: Typically used on 15m–4H charts, depending on your strategy and the asset’s volatility.
Ideal For
• Traders using Smart Money Concepts (SMC)
• Those who value high-confluence entries
• Intraday to swing traders looking for structure-based automation
⚠️ Important Notes
• The strategy requires engulfing confirmation within the zone to enter a position.
• This script does not repaint and executes trades on a bar close basis.
• Backtest results may vary based on session filters and aggregation factor.
© Attribution
This strategy was developed by The_Forex_Steward and is licensed under the Mozilla Public License 2.0.
You are free to use, modify, and distribute it under the terms of that license.
System 0530 - Stoch RSI Strategy with ATR filterStrategy Description: System 0530 - Multi-Timeframe Stochastic RSI with ATR Filter
Overview:
This strategy, "System 0530," is designed to identify trading opportunities by leveraging the Stochastic RSI indicator across two different timeframes: a shorter timeframe for initial signal triggers (assumed to be the chart's current timeframe, e.g., 5-minute) and a longer timeframe (15-minute) for signal confirmation. It incorporates an ATR (Average True Range) filter to help ensure trades are taken during periods of adequate market volatility and includes a cooldown mechanism to prevent rapid, successive signals in the same direction. Trade exits are primarily handled by reversing signals.
How It Works:
1. Signal Initiation (e.g., 5-Minute Timeframe):
Long Signal Wait: A potential long entry is considered when the 5-minute Stochastic RSI %K line crosses above its %D line, AND the %K value at the time of the cross is at or below a user-defined oversold level (default: 30).
Short Signal Wait: A potential short entry is considered when the 5-minute Stochastic RSI %K line crosses below its %D line, AND the %K value at the time of the cross is at or above a user-defined overbought level (default: 70). When these conditions are met, the strategy enters a "waiting state" for confirmation from the 15-minute timeframe.
2. Signal Confirmation (15-Minute Timeframe):
Once in a waiting state, the strategy looks for confirmation on the 15-minute Stochastic RSI within a user-defined number of 5-minute bars (wait_window_5min_bars, default: 5 bars).
Long Confirmation:
The 15-minute Stochastic RSI %K must be greater than or equal to its %D line.
The 15-minute Stochastic RSI %K value must be below a user-defined threshold (stoch_15min_long_entry_level, default: 40).
Short Confirmation:
The 15-minute Stochastic RSI %K must be less than or equal to its %D line.
The 15-minute Stochastic RSI %K value must be above a user-defined threshold (stoch_15min_short_entry_level, default: 60).
3. Filters:
ATR Volatility Filter: If enabled, trades are only confirmed if the current ATR value (converted to ticks) is above a user-defined minimum threshold (min_atr_value_ticks). This helps to avoid taking signals during periods of very low market volatility. If the ATR condition is not met, the strategy continues to wait for the condition to be met within the confirmation window, provided other conditions still hold.
Signal Cooldown Filter: If enabled, after a signal is generated, the strategy will wait for a minimum number of bars (min_bars_between_signals) before allowing another signal in the same direction. This aims to reduce overtrading.
4. Entry and Exit Logic:
Entry: A strategy.entry() order is placed when all trigger, confirmation, and filter conditions are met.
Exit: This strategy primarily uses reversing signals for exits. For example, if a long position is open, a confirmed short signal will close the long position and open a new short position. There are no explicit take profit or stop loss orders programmed into this version of the script.
Key User-Adjustable Parameters:
Stochastic RSI Parameters: RSI Length, Stochastic RSI Length, %K Smoothing, %D Smoothing.
Signal Trigger & Confirmation:
5-minute %K trigger levels for long and short.
15-minute %K confirmation thresholds for long and short.
Wait window (in 5-minute bars) for 15-minute confirmation.
Filters:
Enable/disable and configure the Signal Cooldown filter (minimum bars between signals).
Enable/disable and configure the ATR Volatility filter (ATR period, minimum ATR value in ticks).
Strategy Parameters:
Leverage Multiplier (Note: This primarily affects theoretical position sizing for backtesting calculations in TradingView and does not simulate actual leveraged trading risks).
Recommendations for Users:
Thorough Backtesting: Test this strategy extensively on historical data for the instruments and timeframes you intend to trade.
Parameter Optimization: Experiment with different parameter settings to find what works best for your trading style and chosen markets. The default values are starting points and may not be optimal for all conditions.
Understand the Logic: Ensure you understand how each component (Stochastic RSI on different timeframes, ATR filter, cooldown) interacts to generate signals.
Risk Management: Since this version does not include explicit stop-loss orders, ensure you have a clear risk management plan in place if trading this strategy live. You might consider manually adding stop-loss orders through your broker or using TradingView's separate strategy order settings for stop-loss if applicable.
Disclaimer:
This strategy description is for informational purposes only and does not constitute financial advice. Past performance is not indicative of future results. Trading involves significant risk of loss. Always do your own research and understand the risks before trading.
NUPL Z-ScoreThis indicator is derived from Market Value and Realized Value, which can be defined as:
Market Value: The current price of Bitcoin multiplied by the number of coins in circulation. This is like market cap in traditional markets i.e. share price multiplied by number of shares.
Realized Value: Rather than taking the current price of Bitcoin, Realized Value takes the price of each Bitcoin when it was last moved i.e. the last time it was sent from one wallet to another wallet. It then adds up all those individual prices and takes an average of them. It then multiplies that average price by the total number of coins in circulation.
By subtracting Realized Value from Market Value we calculate Unrealized Profit/Loss.
Unrealized Profit/Loss estimates the total paper profits/losses in Bitcoin held by investors. This is interesting to know but of greater value is identifying how this changes relatively over time.
To do this we can divide Unrealized Profit/Loss by Market Cap. This creates Net Unrealized Profit/Loss, sometimes referred to as NUPL, which is very useful to track investor sentiment over time for Bitcoin.
Relative Unrealised Profit/Loss is another name used for this analysis.
AsturRiskPanelIndicator Summary
ATR Engine
Length & Smoothing: Choose how many bars to use (default 14) and the smoothing method (RMA/SMA/EMA/WMA).
Median ATR: Computes a rolling median of ATR over a user-defined look-back (default 14) to derive a “scalp” target.
Scalp Target
Automatically set at ½ × median ATR, snapped to the nearest tick.
Optional rounding to whole points for simplicity.
Stop Calculation
ATR Multiplier: Scales current ATR by a user input (default 1.5) to produce your stop distance in points (and ticks when appropriate).
Distortion Handling: Switches between point-only and point + tick displays based on contract specifications.
Risk & Sizing
Risk % of account per trade (default 2 %).
Calculates dollar risk per contract and optimal contract count.
Displays all metrics (scalp, stop, risk/contract, max contracts, max risk, account size) in a customizable on-chart table.
ATR-Based Stop Placement Guidelines
Trade Context ATR Multiplier Notes
Tight Range Entry 1.0 × ATR High-conviction, precise entries. Expect more shake-outs.
Standard Trend Entry 1.5 × ATR Balanced for H2/L2, MTR, DT/DB entries.
Breakouts/Microchannels 2.0 × ATR Wide stops through chop—Brooks-style breathing room.
How to Use
Select ATR Settings
Pick an ATR length (e.g. 14) and smoothing (RMA for stability).
Adjust the median length if you want a faster/slower scalp line.
Align Multiplier with Your Setup
For tight-range entries, set ATR Multiplier ≈ 1.0.
For standard trend trades, leave at 1.5.
For breakout/pullback setups, increase to 2.0 or more.
Customize Risk Parameters
Enter your account size and desired risk % per trade (e.g. 2 %).
The table auto-calculates how many contracts you can take.
Read the On-Chart Table
Scalp shows your intraday target.
Stop gives Brooks-style stop distance in points (and ticks).
Risk/Contract is the dollar risk per contract.
Max Contracts tells you maximum position size.
Max Risk confirms total dollar exposure.
Visual Confirmation
Place your entry, then eyeball the scalp and stop levels against chart structure (e.g. swing highs/lows).
Adjust the ATR multiplier if market context shifts (e.g. volatility spikes).
By blending this sizing panel with contextual ATR multipliers, you’ll consistently give your trades the right amount of “breathing room” while keeping risk in check.
MTF Candle Direction Forecast + Breakdown🧭 MTF Candle Direction Forecast + Breakdown 🔥📈🔼
This script is a multi-timeframe (MTF) price action dashboard that helps traders assess real-time directional bias across five customizable timeframes — with a focus on candle behavior, trend alignment, and confidence strength.
📌 What It Does
For each timeframe, this dashboard summarizes:
Current direction → Bullish, Bearish, or Neutral
Confidence score (0–100) → How strongly price is likely to continue in that direction
Candle strength → 🔥 icon appears if the current candle has a large body relative to its range
Trend alignment:
📈 = EMA9 is above EMA20
🔼 = Price is above VWAP
Color-coded background to visually reinforce directional state
Each row gives you a visual “at-a-glance” readout of what price is doing right now — not in the past.
💡 Why It’s Useful
✅ Direction forecasting based on price action
Instead of lagging indicators, this script prioritizes:
Candle body-to-range ratio (momentum)
Real-time VWAP/EMA structure
Immediate price positioning
✅ Confidence is quantified
The score (0–100) helps you judge how reliable each directional signal is:
90+ → Strong conviction
50–70 → Mixed but potentially valid
<40 → Weak move or early signal
✅ Timeframe confluence at a glance
See whether multiple timeframes are aligning directionally — helpful for scalping, day trading, or waiting for multi-timeframe breakout setups.
✅ Visual & intuitive
Icons, colors, and layout make it easy to scan your dashboard instead of deciphering charts or code.
🛠️ Adjustable Settings
Setting Description
Timeframe 1–5 Choose any timeframes to monitor (e.g., 5m, 15m, 1h, 4h)
Candle Display Mode Show trend color via emoji (🟢/🔴) or background shading
Strong Candle Threshold Adjust the body-to-range % needed to trigger 🔥 strength
Bullish/Bearish Background Customize label color coding
Neutral Background (opacity) Set transparency or styling for flat/consolidating zones
Table Location Place the dashboard anywhere on the chart
🎯 Use Cases
Scalpers: Confirm trend across 1m/5m/15m before entering
Day Traders: Use confidence score to avoid low-momentum setups
Swing Traders: Monitor higher timeframes for trend shifts while tracking intraday noise
VWAP/EMA traders: Quickly see when price is reclaiming or losing critical trend levels
🧠 What Makes It Unique?
Unlike generic trend meters or mashups of standard indicators, this script:
Uses live candle dynamics (not just closes or lagging values)
Computes directional bias and confidence together
Visualizes strength and structure in a compact, readable interface
Let’s you filter by price action, not just indicator alignment
💥 Why Traders Love Will Love It
✅ Instant clarity on which timeframes agree
✅ No more guessing candle strength or trend health
✅ Confidence score keeps you out of weak trades
✅ Works with any strategy — trend following, VWAP reclaim, EMA scalps, even breakouts
✅ Keeps your chart clean — all the context, none of the clutter
⚠️ Transparency🧬 Under the Hood
Powered by live candle body analysis, trend structure (EMA9 vs EMA20), and VWAP placement.
All scores are generated in real-time — No repainting or lookahead bias: all values are computed with lookahead=barmerge.lookahead_on
Confidence scores reflect the current candle only — they do not predict future moves but measure momentum and alignment in real-time
Labels update per bar and respond to subtle shifts in candle structure and trend indicators
✅ MTF Trend Snapshot (Live Output Example Shown in Chart Above)
This dashboard gives you a fast, visual summary of market trend and momentum across 5 timeframes. Here's what it's telling you right now:
🕔 5 Minute (5m)
📉 EMA Trend: Down
🔼 Price: Above VWAP
Direction: Bearish (42)
🟥 Weak bearish bias. Short-term pullback against a stronger trend. Use caution — lower confidence and mixed structure.
⏱️ 15 Minute (15m)
📈 EMA Trend: Up
🔼 Price: Above VWAP
Direction: Bullish (73)
🟩 Clean bullish structure with growing momentum. Solid for intraday confirmation.
🕧 30 Minute (30m)
📈 EMA Trend: Up
🔼 Price: Above VWAP
Direction: Bullish (77)
🟩 Stronger trend forming. Above VWAP and EMAs — building conviction.
🕐 1 Hour (1h)
📈 EMA Trend: Up
🔼 Price: Above VWAP
Direction: Bullish (70)
🟩 Confident, clean trend. Good alignment across indicators. Ideal timeframe for swing entries.
🕓 4 Hour (4h)
🔥 Strong Candle
📈 EMA Trend: Up
🔼 Price: Above VWAP
Direction: Bullish (100)
🟩 Full trend alignment with max momentum. Strong body candle + structure — high confidence continuation.
🧠 Quick Takeaway
🔻 5m is pulling back short term
✅ 15m through 4h are fully aligned Bullish
🔥 4h has max confidence — big-picture trend is intact
📈 Ideal setup for momentum traders looking to ride trend with multi-timeframe confirmation
Try pinning this dashboard to your chart during live trading to read price like a story across timeframes, and filter out weak setups with low-confidence noise.
SOXL Trend Surge v3.0.2 – Profit-Only RunnerSOXL Trend Surge v3.0.2 – Profit-Only Runner
This is a trend-following strategy built for leveraged ETFs like SOXL, designed to ride high-momentum waves with minimal interference. Unlike most short-term scalping scripts, this model allows trades to develop over multiple days to even several months, capitalizing on the full power of extended directional moves — all without using a stop-loss.
🔍 How It Works
Entry Logic:
Price is above the 200 EMA (long-term trend confirmation)
Supertrend is bullish (momentum confirmation)
ATR is rising (volatility expansion)
Volume is above its 20-bar average (liquidity filter)
Price is outside a small buffer zone from the 200 EMA (to avoid whipsaws)
Trades are restricted to market hours only (9 AM to 2 PM EST)
Cooldown of 15 bars after each exit to prevent overtrading
Exit Strategy:
Takes partial profit at +2× ATR if held for at least 2 bars
Rides the remaining position with a trailing stop at 1.5× ATR
No hard stop-loss — giving space for volatile pullbacks
⚙️ Strategy Settings
Initial Capital: $500
Risk per Trade: 100% of equity (fully allocated per entry)
Commission: 0.1%
Slippage: 1 tick
Recalculate after order is filled
Fill orders on bar close
Timeframe Optimized For: 45-minute chart
These parameters simulate an aggressive, high-volatility trading model meant for forward-testing compounding potential under realistic trading costs.
✅ What Makes This Unique
No stop-loss = fewer premature exits
Partial profit-taking helps lock in early wins
Trailing logic gives room to ride large multi-week moves
Uses strict filters (volume, ATR, EMA bias) to enter only during high-probability windows
Ideal for leveraged ETF swing or position traders looking to hold longer than the typical intraday or 2–3 day strategies
⚠️ Important Note
This is a high-risk, high-reward strategy meant for educational and testing purposes. Without a stop-loss, trades can experience deep drawdowns that may take weeks or even months to recover. Always test thoroughly and adjust position sizing to suit your risk tolerance. Past results do not guarantee future returns. Backtest range: May 8, 2020 – May 23, 2025
Decimal EMAImagine you want a moving average line, but you want its "length" or "period" to be super precise, like 2.7 days instead of just 2 days or 3 days.
This script lets you do that. Here's the simple idea:
You Pick a Decimal Number: In the settings, you can type in a period with a decimal, say, 2.7.
The Script Does a Smart Blend:
It first calculates two regular EMAs: one for the whole number below your choice (EMA for 2 days) and one for the whole number above (EMA for 3 days).
Then, it cleverly mixes these two EMA lines. Since 2.7 is closer to 3 than to 2, it takes more from the "3-day EMA" and a bit less from the "2-day EMA." (Specifically, it takes 70% from the 3-day EMA and 30% from the 2-day EMA).
You Get a Decimal EMA Line: The result is a new EMA line that acts as if its period was exactly 2.7. This line is drawn on your chart.
Why do this?
It allows for very fine-tuned adjustments to how responsive your moving average is, giving a smoother change if you're testing slightly different period lengths.
In Short:
This script calculates an EMA for a period like "2.7" by intelligently blending the results of an EMA for "2" and an EMA for "3".
Order Blocks📈 Order Blocks Only (With Mitigation Alerts)
This indicator identifies bullish and bearish order blocks on your chart and alerts you when they are formed or mitigated . Order blocks are key institutional price levels where strong buying or selling has previously occurred, often leading to significant future price reactions.
🔍 How It Works:
-Bullish Order Block: Formed when price closes above the high of a recent bearish candle. This suggests buyers have taken control.
-Bearish Order Block: Formed when price closes below the low of a recent bullish candle. This signals seller dominance.
-Once an order block is formed, a box is drawn on the chart to highlight the zone.
-These boxes last for a user-defined number of bars (default is 20) and can be automatically removed when price mitigates (retests and closes beyond) the zone.
🛠 User Settings:
-Show Bullish Order Blocks – Toggle green zones on/off.
-Show Bearish Order Blocks – Toggle red zones on/off.
-Order Block Duration – How many bars the boxes should remain on the chart.
-Delete Mitigated Boxes – If enabled, mitigated zones are automatically removed.
-Custom Colors – Personalize the fill and border colors of bullish and bearish blocks.
🔔 Alerts:
This tool supports four built-in alert types:
-Bullish Order Block Formed
-Bearish Order Block Formed
-Bullish Order Block Mitigated
-Bearish Order Block Mitigated
Set these alerts to stay on top of key price reactions.
✅ How to Use It:
1. Apply the indicator to any chart and timeframe.
2. Watch for new order blocks to form after strong price breaks.
3. Use these zones as potential entry points, stop placement areas, or take profit zones.
4. Enable alerts to catch key institutional levels as they form or are retested.
Zero Lag MTF Moving Average by CoffeeshopCryptoBased on Moving Average Types supplied by @TradingView www.tradingview.com
Ideas and code enhanced to show higher timeframe by @CoffeeShopCrypto
It’s time to take the guesswork out of moving averages and multiple timeframes when day trading. Moving averages are a cornerstone of many trading strategies, often viewed as dynamic support and resistance levels. Traders rely on these levels to anticipate price reactions, whether it’s a bounce in a trending market or a reversal in a ranging one. Additionally, the direction and alignment of multi timeframe moving averages—whether they’re moving in the same direction or diverging—provide critical clues about market momentum and potential reversals. However, the traditional higher timeframe moving average indicators force traders to wait for higher timeframe candles to close, creating lag and missed opportunities.
The Old Way
For example: If you are on a 5 minute chart and you want to observe the location and direction of a 30 minute chart Moving Average, you'll need to wait for a total of 6 candles to close, and again every 6 candles after that. This only creates more lag.
The New Way
Now there is no waiting for high timeframe session candles to close. No matter what timeframe Moving Average you want to know about, this indicator will show you its location on your current chart at any time in real time.
For those who prefer Bollinger Bands, this indicator adds a whole new dimension to your strategy. Traders often wait for price action to break outside the lower time frame Bollinger bands before considering a trade, while still seeking key support or resistance levels beyond them. But if you don't know the position of your higher time frame Bollinger, you could be trading into a trap. With Zero Lag Multi Timeframe Moving Average, you can view both your current and higher timeframe Bollinger Bands simultaneously with zero waiting. This lets you instantly see when price action is traveling between the bands of either timeframe or breaking through both—indicating a strong trend in that direction. Additionally, when both sets of Bollinger Bands overlap at the same price levels, it highlights areas of strong consolidation and ranging conditions, giving you a clear picture of market dynamics. This is a key element in price action that tells you there is currently no direction to the market and both the current and higher time frames are flat.
Enter Zero Lag Multi Timeframe Moving Average—the ultimate tool for real-time higher timeframe moving averages and Bollinger Bands. This innovative indicator eliminates the delay, delivering instant, precise values for higher timeframe averages and bands, even on open candles. Seamlessly combining current and higher timeframe data, it allows traders to identify key moments where moving averages or Bollinger Bands align or diverge, signaling market conditions. Whether you’re gauging the strength of a trend, pinpointing potential reversals, or identifying consolidation zones, Zero Lag Multi Timeframe Moving Average gives you the clarity needed to make better trading decisions according to market conditions.
Why is this "Mashup" of moving averages different and important?
Honestly its really about the calculation thats imported through the "import library" function.
Heres what it does:
The ZLMTF-MA is designed to help traders easily see where higher timeframe moving averages and Bollinger Bands are—without needing to switch chart timeframes or wait for those larger candles to close. It works by adjusting common moving average types like SMA, EMA, and VWMA to show what they would look like if they were based on a higher timeframe, right on your current chart. This helps users stay focused on their main timeframe while still having a clear view of the bigger picture, making it easier to spot trend direction, key support and resistance levels, and overall market structure. The goal is to keep things simple, fast, and more visually informative for everyday traders.
Bollinger Bands
When working with Bollinger Bands, a common strategy is to take the trades once price action has escaped through the top or bottom of your current Bollinger Band.
A false breakout occurs when both Bollinger Bands are not moving in the same direction as eachother or when they are overlapping.
Moving Averages as Support and Resistance:
Traders who use Moving Averages as support or resistance, looking for rejections or failures of these areas can now see multiple timeframe price action instantly and simultaneously.
Trading Setup Examples:
Price Action Scenario 1:
Higher Timeframe Ranging-
When price action breaks through a current moving average headed toward a higher timeframe moving average, trades are taken with caution if the moving averages are converging.
Price Action Scenario 2:
Strong Trending Market -
If the moving averages are in the same direction, and your price action is now leading the low timeframe moving average, you have re-entered a strong trend.
Price Action Scenario 3:
High Timeframe Rejections -
If you have a rejection of a higher timeframe moving average, and your both averages are still diverging, this is the end of a pullback as you re-enter a strong trend in the original direction
Price Action Scenario 4:
Trend Reversals -
If you close beyond both the low and high timeframe moving averages, you can consider that price action is strong enough to change direction here and you should prepare for trade setups in the opposite direction of the previous.
HTF MA Label Information:
Even if your high timeframe moving average is turned off, you can still see this label.
It gives you a quick reminder of what high timeframe settings you have used to see MA values.
ETI IndicatorThe Ensemble Technical Indicator (ETI) is a script that combines multiple established indicators into one single powerful indicator. Specifically, it takes a number of technical indicators and then converts them into +1 to represent a bullish trend, or a -1 to represent a bearish trend. It then adds these values together and takes the running sum over the past 20 days.
The ETI is composed of the following indicators and converted to +1 or -1 using the following criteria:
Simple Moving Average (10 days) : When the price is above the 10-day simple moving averaging, +1, when below -1
Weighted Moving Average (10 days) : Similar to the SMA 10, when the the price is above the 10-day weighted moving average, +1, when below -1
Stochastic K% : If the current Stochastic K% is greater than the previous value, then +1, else -1.
Stochastic D% : Similar to the Stochastic K%, when the current Stochastic D% is greater than the previous value, +1, else -1.
MACD Difference : First subtract the MACD signal (i.e. the moving average) from the MACD value and if the current value is higher than the previous value, then +1, else -1.
William's R% : If the current William's R% is greater than the previous one, then +1, else -1.
William's Accumulation/Distribution : If the current William's AD value is greater than the previous value, then +1, else -1.
Commodity Channel Index : If the Commodity Channel Index is greater than 200 (overbought), then -1, if it is less than -200 (oversold) then +1. When it is between those values, if the current value is greater than the previous value then +1, else -1.
Relative Strength Index : If the Relative Strength Index is over 70 (overbought) then -1 and if under 30 (oversold) then +1. If the Relative Strength Indicator is between those values then if the current value is higher than the previous value +1, else -1.
Momentum (9 days) : If the momentum value is greater than 0, then +1, else -1.
Again, once these values have been calculated and converted, they are added up to produce a single value. This single value is then summed across the previous 20 candles to produce a running sum.
By coalescing multiple technical indicators into a single value across time, traders can better understand how multiple inter-related indicators are behaving at once; high scores indicate that numerous indicators are showing bullish signals indicating a potential or ongoing uptrend (and vice-versa with low scores).
Additional Features
Numerous smoothing transformations have also been added (e.g. gaussian smoothing) to remove some of the noise might exist.
Suggested Use
It is recommended that stocks are shorted when the cross below 0, and are bought when the ETI crosses above -40. Arrows can be shown on the indicator to show these points. However feel free to use levels that work best for you.
Traditionally, I have treated values above +50 as overbought and below -40 as undersold (with -80 indicating extremely oversold); however these levels could also indicate either upwards and downwards momentum so taking a position based on where the ETI is (rather than crossing levels) should be done with caution.
DDDDD: ATR & ADR Table + Suggested Time-based Exit📈 DDDDD: ATR & ADR Table + Suggested Time-based Exit
This indicator provides a simple yet powerful table displaying key volatility metrics for any timeframe you apply it to. It is designed for traders who want to assess the volatility of an asset, estimate the average time required for a potential move, and define a time-based exit strategy.
🔍 Features:
Displays ATR (Average True Range) for the selected length
Shows Average Range (High-Low) and Maximum Range over a configurable number of bars
Calculates Avg Bars/Move → average number of bars needed to achieve the maximum range
Calculates Recommended Exit Bars → suggested maximum holding period (in bars) before considering an exit if price hasn’t moved as expected
All values dynamically adjust based on the chart’s current timeframe
Outputs values directly in a table overlay on your main chart for quick reference
📝 How to interpret the table:
Field Meaning
ATR (14) Average True Range over the last 14 bars (volatility indicator)
Avg Range (20) Average High-Low range over the last 20 bars
Max Range Maximum High-Low range observed in the last 20 bars
Avg Bars/Move Average number of bars it takes to achieve a Max Range move
Rec. Exit Bars Suggested max holding period (bars) → consider exit if move hasn’t occurred
✅ How to use:
Apply this indicator to any chart (works on minutes, hourly, daily, weekly…)
It will automatically calculate based on the chart’s current timeframe
Use ATR & Avg Range to gauge volatility
Use Avg Bars/Move to estimate how long the market usually takes to achieve a big move
Use Rec. Exit Bars as a soft stop — if price hasn’t moved by this time, consider exiting due to declining probability of a breakout
⚠️ Notes:
All values are relative to your current chart timeframe. For example:
→ On a daily chart, ATR represents daily volatility
→ On a 1H chart, ATR represents hourly volatility
“Bars” refers to the bars of the current timeframe. Always interpret time accordingly.
Perfect for traders who want to:
Time their trades based on average volatility
Avoid overholding losing positions
Set time-based exit rules to complement price-based stoplosses
6 Dynamic EMAs by Koenigsegg🚀 6 Dynamic EMAs by Koenigsegg
Take control of your chart with ultimate flexibility. This tool gives you 6 customizable EMAs across any timeframe, helping you read the market like a pro — whether you're scalping seconds or swinging days. Built for precision, designed for dominance.
The combinations? Endless. Mix and match any EMA lengths and timeframes for tailored confluence — exactly how elite traders operate.
🔑 Key Features
✅ 6 Fully Customizable EMAs
⏳ Multi-Timeframe Support (from seconds to months)
🎨 Custom Colors & Thickness for each EMA
🚨 Built-in Cross Alerts for instant trade signals
🧠 Clean, efficient logic using request.security()
🔁 Dynamically toggle EMAs on/off
⚙️ Lightweight for smooth chart performance
🧩 Endless combo potential — confluence on your terms
📈 What Is an EMA?
The EMA is a type of moving average that adjusts more quickly to recent price changes than a Simple Moving Average (SMA). It does this by giving exponentially more weight to the most recent candles.
⚙️ How Does It Function?
Smoothing Price Data:
It takes the average of closing prices over a chosen period (like 20 or 50 candles), but gives more influence to the latest prices.
Reacts Quickly to Price Shifts:
Since recent data is weighted more heavily, the EMA adjusts faster to sudden price changes — helping you spot trend reversals or momentum shifts earlier.
Dynamic Support & Resistance:
Traders often use EMAs as moving support/resistance levels. Price often "respects" EMAs in trending markets — bouncing off them during pullbacks.
Trend Confirmation:
- If price is above the EMA, the market is likely in an uptrend.
- If price is below the EMA, the market is likely in a downtrend.
- Multiple EMAs (like 12/21 or 50/200) crossing each other are used for entry/exit signals.
💡 Example:
If you use a 21 EMA on a chart, it shows you the average price of the last 21 candles, but the most recent ones weigh heavier. This makes the EMA more responsive than an SMA, and better for short-term or active trading.
📊 Why EMAs Matter — and How Multi-Timeframe EMAs Give You the Edge
Exponential Moving Averages (EMAs) are essential tools for identifying trend direction, momentum shifts, and dynamic support/resistance. Because they weight recent price data more heavily, EMAs adapt quickly to changing market conditions, giving traders early insight into reversals or continuations.
Where this script shines is in its multi-timeframe (MTF) capability. For example, plotting a daily EMA on a 4H chart gives you high-level directional guidance while still allowing precision entries. This enables confluence between LTF (low timeframe) signals and HTF (high timeframe) momentum — a crucial edge used by institutional-level traders.
You can configure the tool to run classic combos like the 12/21 crossover on your current chart, while layering in a 50 or 200 EMA from a higher timeframe for macro confirmation. The 6th EMA, colored light blue by default, is perfect for adding one final level of structure insight — often used as a long-term anchor or trend bias marker.
Whether you're riding the wave or catching the reversal, these EMAs serve as your adaptable compass in every environment.
🎯 Purpose
This indicator was built to give traders a clear, responsive, and multi-timeframe edge using dynamic Exponential Moving Averages. Whether you're trend-following, identifying momentum shifts, or building a confluence system — these 6 EMAs are here to align with your strategy and style.
💡 Pro Tip
Instead of cluttering your chart with multiple EMA indicators, this script consolidates all into one sleek tool. You can toggle off bands you don't currently need, like running only the 12/21 EMAs on your active chart timeframe, while adding the 12/21 EMAs from a higher timeframe to guide trade decisions.
With this setup, you're not just reacting — you're orchestrating your trades with intention.
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice. Always do your own research and trade responsibly. Past performance does not guarantee future results.
Dskyz (DAFE) Adaptive Regime - Quant Machine ProDskyz (DAFE) Adaptive Regime - Quant Machine Pro:
Buckle up for the Dskyz (DAFE) Adaptive Regime - Quant Machine Pro, is a strategy that’s your ultimate edge for conquering futures markets like ES, MES, NQ, and MNQ. This isn’t just another script—it’s a quant-grade powerhouse, crafted with precision to adapt to market regimes, deliver multi-factor signals, and protect your capital with futures-tuned risk management. With its shimmering DAFE visuals, dual dashboards, and glowing watermark, it turns your charts into a cyberpunk command center, making trading as thrilling as it is profitable.
Unlike generic scripts clogging up the space, the Adaptive Regime is a DAFE original, built from the ground up to tackle the chaos of futures trading. It identifies market regimes (Trending, Range, Volatile, Quiet) using ADX, Bollinger Bands, and HTF indicators, then fires trades based on a weighted scoring system that blends candlestick patterns, RSI, MACD, and more. Add in dynamic stops, trailing exits, and a 5% drawdown circuit breaker, and you’ve got a system that’s as safe as it is aggressive. Whether you’re a newbie or a prop desk pro, this strat’s your ticket to outsmarting the markets. Let’s break down every detail and see why it’s a must-have.
Why Traders Need This Strategy
Futures markets are a gauntlet—fast moves, volatility spikes (like the April 28, 2025 NQ 1k-point drop), and institutional traps that punish the unprepared. Meanwhile, platforms are flooded with low-effort scripts that recycle old ideas with zero innovation. The Adaptive Regime stands tall, offering:
Adaptive Intelligence: Detects market regimes (Trending, Range, Volatile, Quiet) to optimize signals, unlike one-size-fits-all scripts.
Multi-Factor Precision: Combines candlestick patterns, MA trends, RSI, MACD, volume, and HTF confirmation for high-probability trades.
Futures-Optimized Risk: Calculates position sizes based on $ risk (default: $300), with ATR or fixed stops/TPs tailored for ES/MES.
Bulletproof Safety: 5% daily drawdown circuit breaker and trailing stops keep your account intact, even in chaos.
DAFE Visual Mastery: Pulsing Bollinger Band fills, dynamic SL/TP lines, and dual dashboards (metrics + position) make signals crystal-clear and charts a work of art.
Original Craftsmanship: A DAFE creation, built with community passion, not a rehashed clone of generic code.
Traders need this because it’s a complete, adaptive system that blends quant smarts, user-friendly design, and DAFE flair. It’s your edge to trade with confidence, cut through market noise, and leave the copycats in the dust.
Strategy Components
1. Market Regime Detection
The strategy’s brain is its ability to classify market conditions into five regimes, ensuring signals match the environment.
How It Works:
Trending (Regime 1): ADX > 20, fast/slow EMA spread > 0.3x ATR, HTF RSI > 50 or MACD bullish (htf_trend_bull/bear).
Range (Regime 2): ADX < 25, price range < 3% of close, no HTF trend.
Volatile (Regime 3): BB width > 1.5x avg, ATR > 1.2x avg, HTF RSI overbought/oversold.
Quiet (Regime 4): BB width < 0.8x avg, ATR < 0.9x avg.
Other (Regime 5): Default for unclear conditions.
Indicators: ADX (14), BB width (20), ATR (14, 50-bar SMA), HTF RSI (14, daily default), HTF MACD (12,26,9).
Why It’s Brilliant:
Regime detection adapts signals to market context, boosting win rates in trending or volatile conditions.
HTF RSI/MACD add a big-picture filter, rare in basic scripts.
Visualized via gradient background (green for Trending, orange for Range, red for Volatile, gray for Quiet, navy for Other).
2. Multi-Factor Signal Scoring
Entries are driven by a weighted scoring system that combines candlestick patterns, trend, momentum, and volume for robust signals.
Candlestick Patterns:
Bullish: Engulfing (0.5), hammer (0.4 in Range, 0.2 else), morning star (0.2), piercing (0.2), double bottom (0.3 in Volatile, 0.15 else). Must be near support (low ≤ 1.01x 20-bar low) with volume spike (>1.5x 20-bar avg).
Bearish: Engulfing (0.5), shooting star (0.4 in Range, 0.2 else), evening star (0.2), dark cloud (0.2), double top (0.3 in Volatile, 0.15 else). Must be near resistance (high ≥ 0.99x 20-bar high) with volume spike.
Logic: Patterns are weighted higher in specific regimes (e.g., hammer in Range, double bottom in Volatile).
Additional Factors:
Trend: Fast EMA (20) > slow EMA (50) + 0.5x ATR (trend_bull, +0.2); opposite for trend_bear.
RSI: RSI (14) < 30 (rsi_bull, +0.15); > 70 (rsi_bear, +0.15).
MACD: MACD line > signal (12,26,9, macd_bull, +0.15); opposite for macd_bear.
Volume: ATR > 1.2x 50-bar avg (vol_expansion, +0.1).
HTF Confirmation: HTF RSI < 70 and MACD bullish (htf_bull_confirm, +0.2); RSI > 30 and MACD bearish (htf_bear_confirm, +0.2).
Scoring:
bull_score = sum of bullish factors; bear_score = sum of bearish. Entry requires score ≥ 1.0.
Example: Bullish engulfing (0.5) + trend_bull (0.2) + rsi_bull (0.15) + htf_bull_confirm (0.2) = 1.05, triggers long.
Why It’s Brilliant:
Multi-factor scoring ensures signals are confirmed by multiple market dynamics, reducing false positives.
Regime-specific weights make patterns more relevant (e.g., hammers shine in Range markets).
HTF confirmation aligns with the big picture, a quant edge over simplistic scripts.
3. Futures-Tuned Risk Management
The risk system is built for futures, calculating position sizes based on $ risk and offering flexible stops/TPs.
Position Sizing:
Logic: Risk per trade (default: $300) ÷ (stop distance in points * point value) = contracts, capped at max_contracts (default: 5). Point value = tick value (e.g., $12.5 for ES) * ticks per point (4) * contract multiplier (1 for ES, 0.1 for MES).
Example: $300 risk, 8-point stop, ES ($50/point) → 0.75 contracts, rounded to 1.
Impact: Precise sizing prevents over-leverage, critical for micro contracts like MES.
Stops and Take-Profits:
Fixed: Default stop = 8 points, TP = 16 points (2:1 reward/risk).
ATR-Based: Stop = 1.5x ATR (default), TP = 3x ATR, enabled via use_atr_for_stops.
Logic: Stops set at swing low/high ± stop distance; TPs at 2x stop distance from entry.
Impact: ATR stops adapt to volatility, while fixed stops suit stable markets.
Trailing Stops:
Logic: Activates at 50% of TP distance. Trails at close ± 1.5x ATR (atr_multiplier). Longs: max(trail_stop_long, close - ATR * 1.5); shorts: min(trail_stop_short, close + ATR * 1.5).
Impact: Locks in profits during trends, a game-changer in volatile sessions.
Circuit Breaker:
Logic: Pauses trading if daily drawdown > 5% (daily_drawdown = (max_equity - equity) / max_equity).
Impact: Protects capital during black swan events (e.g., April 27, 2025 ES slippage).
Why It’s Brilliant:
Futures-specific inputs (tick value, multiplier) make it plug-and-play for ES/MES.
Trailing stops and circuit breaker add pro-level safety, rare in off-the-shelf scripts.
Flexible stops (ATR or fixed) suit different trading styles.
4. Trade Entry and Exit Logic
Entries and exits are precise, driven by bull_score/bear_score and protected by drawdown checks.
Entry Conditions:
Long: bull_score ≥ 1.0, no position (position_size <= 0), drawdown < 5% (not pause_trading). Calculates contracts, sets stop at swing low - stop points, TP at 2x stop distance.
Short: bear_score ≥ 1.0, position_size >= 0, drawdown < 5%. Stop at swing high + stop points, TP at 2x stop distance.
Logic: Tracks entry_regime for PNL arrays. Closes opposite positions before entering.
Exit Conditions:
Stop-Loss/Take-Profit: Hits stop or TP (strategy.exit).
Trailing Stop: Activates at 50% TP, trails by ATR * 1.5.
Emergency Exit: Closes if price breaches stop (close < long_stop_price or close > short_stop_price).
Reset: Clears stop/TP prices when flat (position_size = 0).
Why It’s Brilliant:
Score-based entries ensure multi-factor confirmation, filtering out weak signals.
Trailing stops maximize profits in trends, unlike static exits in basic scripts.
Emergency exits add an extra safety layer, critical for futures volatility.
5. DAFE Visuals
The visuals are pure DAFE magic, blending function with cyberpunk flair to make signals intuitive and charts stunning.
Shimmering Bollinger Band Fill:
Display: BB basis (20, white), upper/lower (green/red, 45% transparent). Fill pulses (30–50 alpha) by regime, with glow (60–95 alpha) near bands (close ≥ 0.995x upper or ≤ 1.005x lower).
Purpose: Highlights volatility and key levels with a futuristic glow.
Visuals make complex regimes and signals instantly clear, even for newbies.
Pulsing effects and regime-specific colors add a DAFE signature, setting it apart from generic scripts.
BB glow emphasizes tradeable levels, enhancing decision-making.
Chart Background (Regime Heatmap):
Green — Trending Market: Strong, sustained price movement in one direction. The market is in a trend phase—momentum follows through.
Orange — Range-Bound: Market is consolidating or moving sideways, with no clear up/down trend. Great for mean reversion setups.
Red — Volatile Regime: High volatility, heightened risk, and larger/faster price swings—trade with caution.
Gray — Quiet/Low Volatility: Market is calm and inactive, with small moves—often poor conditions for most strategies.
Navy — Other/Neutral: Regime is uncertain or mixed; signals may be less reliable.
Bollinger Bands Glow (Dynamic Fill):
Neon Red Glow — Warning!: Price is near or breaking above the upper band; momentum is overstretched, watch for overbought conditions or reversals.
Bright Green Glow — Opportunity!: Price is near or breaking below the lower band; market could be oversold, prime for bounce or reversal.
Trend Green Fill — Trending Regime: Fills between bands with green when the market is trending, showing clear momentum.
Gold/Yellow Fill — Range Regime: Fills with gold/aqua in range conditions, showing the market is sideways/oscillating.
Magenta/Red Fill — Volatility Spike: Fills with vivid magenta/red during highly volatile regimes.
Blue Fill — Neutral/Quiet: A soft blue glow for other or uncertain market states.
Moving Averages:
Display: Blue fast EMA (20), red slow EMA (50), 2px.
Purpose: Shows trend direction, with trend_dir requiring ATR-scaled spread.
Dynamic SL/TP Lines:
Display: Pulsing colors (red SL, green TP for Trending; yellow/orange for Range, etc.), 3px, with pulse_alpha for shimmer.
Purpose: Tracks stops/TPs in real-time, color-coded by regime.
6. Dual Dashboards
Two dashboards deliver real-time insights, making the strat a quant command center.
Bottom-Left Metrics Dashboard (2x13):
Metrics: Mode (Active/Paused), trend (Bullish/Bearish/Neutral), ATR, ATR avg, volume spike (YES/NO), RSI (value + Oversold/Overbought/Neutral), HTF RSI, HTF trend, last signal (Buy/Sell/None), regime, bull score.
Display: Black (29% transparent), purple title, color-coded (green for bullish, red for bearish).
Purpose: Consolidates market context and signal strength.
Top-Right Position Dashboard (2x7):
Metrics: Regime, position side (Long/Short/None), position PNL ($), SL, TP, daily PNL ($).
Display: Black (29% transparent), purple title, color-coded (lime for Long, red for Short).
Purpose: Tracks live trades and profitability.
Why It’s Brilliant:
Dual dashboards cover market context and trade status, a rare feature.
Color-coding and concise metrics guide beginners (e.g., green “Buy” = go).
Real-time PNL and SL/TP visibility empower disciplined trading.
7. Performance Tracking
Logic: Arrays (regime_pnl_long/short, regime_win/loss_long/short) track PNL and win/loss by regime (1–5). Updated on trade close (barstate.isconfirmed).
Purpose: Prepares for future adaptive thresholds (e.g., adjust bull_score min based on regime performance).
Why It’s Brilliant: Lays the groundwork for self-optimizing logic, a quant edge over static scripts.
Key Features
Regime-Adaptive: Optimizes signals for Trending, Range, Volatile, Quiet markets.
Futures-Optimized: Precise sizing for ES/MES with tick-based risk inputs.
Multi-Factor Signals: Candlestick patterns, RSI, MACD, and HTF confirmation for robust entries.
Dynamic Exits: ATR/fixed stops, 2:1 TPs, and trailing stops maximize profits.
Safe and Smart: 5% drawdown breaker and emergency exits protect capital.
DAFE Visuals: Shimmering BB fill, pulsing SL/TP, and dual dashboards.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
How to Use
Add to Chart: Load on a 5min ES/MES chart in TradingView.
Configure Inputs: Set instrument (ES/MES), tick value ($12.5/$1.25), multiplier (1/0.1), risk ($300 default). Enable ATR stops for volatility.
Monitor Dashboards: Bottom-left for regime/signals, top-right for position/PNL.
Backtest: Run in strategy tester to compare regimes.
Live Trade: Connect to Tradovate or similar. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Try April 28, 2025 NQ drop to see regime shifts and stops.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance does not guarantee future results. Backtest results may differ from live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Slippage: 3
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Adaptive Regime - Quant Machine Pro is more than a strategy—it’s a revolution. Crafted with DAFE’s signature precision, it rises above generic scripts with adaptive regimes, quant-grade signals, and visuals that make trading a thrill. Whether you’re scalping MES or swinging ES, this system empowers you to navigate markets with confidence and style. Join the DAFE crew, light up your charts, and let’s dominate the futures game!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
Dskyz (DAFE) Aurora Divergence – Quant Master Dskyz (DAFE) Aurora Divergence – Quant Master
Introducing the Dskyz (DAFE) Aurora Divergence – Quant Master , a strategy that’s your secret weapon for mastering futures markets like MNQ, NQ, MES, and ES. Born from the legendary Aurora Divergence indicator, this fully automated system transforms raw divergence signals into a quant-grade trading machine, blending precision, risk management, and cyberpunk DAFE visuals that make your charts glow like a neon skyline. Crafted with care and driven by community passion, this strategy stands out in a sea of generic scripts, offering traders a unique edge to outsmart institutional traps and navigate volatile markets.
The Aurora Divergence indicator was a cult favorite for spotting price-OBV divergences with its aqua and fuchsia orbs, but traders craved a system to act on those signals with discipline and automation. This strategy delivers, layering advanced filters (z-score, ATR, multi-timeframe, session), dynamic risk controls (kill switches, adaptive stops/TPs), and a real-time dashboard to turn insights into profits. Whether you’re a newbie dipping into futures or a pro hunting reversals, this strat’s got your back with a beginner guide, alerts, and visuals that make trading feel like a sci-fi mission. Let’s dive into every detail and see why this original DAFE creation is a must-have.
Why Traders Need This Strategy
Futures markets are a battlefield—fast-paced, volatile, and riddled with institutional games that can wipe out undisciplined traders. From the April 28, 2025 NQ 1k-point drop to sneaky ES slippage, the stakes are high. Meanwhile, platforms are flooded with unoriginal, low-effort scripts that promise the moon but deliver noise. The Aurora Divergence – Quant Master rises above, offering:
Unmatched Originality: A bespoke system built from the ground up, with custom divergence logic, DAFE visuals, and quant filters that set it apart from copycat clutter.
Automation with Precision: Executes trades on divergence signals, eliminating emotional slip-ups and ensuring consistency, even in chaotic sessions.
Quant-Grade Filters: Z-score, ATR, multi-timeframe, and session checks filter out noise, targeting high-probability reversals.
Robust Risk Management: Daily loss and rolling drawdown kill switches, plus ATR-based stops/TPs, protect your capital like a fortress.
Stunning DAFE Visuals: Aqua/fuchsia orbs, aurora bands, and a glowing dashboard make signals intuitive and charts a work of art.
Community-Driven: Evolved from trader feedback, this strat’s a labor of love, not a recycled knockoff.
Traders need this because it’s a complete, original system that blends accessibility, sophistication, and style. It’s your edge to trade smarter, not harder, in a market full of traps and imitators.
1. Divergence Detection (Core Signal Logic)
The strategy’s core is its ability to detect bullish and bearish divergences between price and On-Balance Volume (OBV), pinpointing reversals with surgical accuracy.
How It Works:
Price Slope: Uses linear regression over a lookback (default: 9 bars) to measure price momentum (priceSlope).
OBV Slope: OBV tracks volume flow (+volume if price rises, -volume if falls), with its slope calculated similarly (obvSlope).
Bullish Divergence: Price slope negative (falling), OBV slope positive (rising), and price above 50-bar SMA (trend_ma).
Bearish Divergence: Price slope positive (rising), OBV slope negative (falling), and price below 50-bar SMA.
Smoothing: Requires two consecutive divergence bars (bullDiv2, bearDiv2) to confirm signals, reducing false positives.
Strength: Divergence intensity (divStrength = |priceSlope * obvSlope| * sensitivity) is normalized (0–1, divStrengthNorm) for visuals.
Why It’s Brilliant:
- Divergences catch hidden momentum shifts, often exploited by institutions, giving you an edge on reversals.
- The 50-bar SMA filter aligns signals with the broader trend, avoiding choppy markets.
- Adjustable lookback (min: 3) and sensitivity (default: 1.0) let you tune for different instruments or timeframes.
2. Filters for Precision
Four advanced filters ensure signals are high-probability and market-aligned, cutting through the noise of volatile futures.
Z-Score Filter:
Logic: Calculates z-score ((close - SMA) / stdev) over a lookback (default: 50 bars). Blocks entries if |z-score| > threshold (default: 1.5) unless disabled (useZFilter = false).
Impact: Avoids trades during extreme price moves (e.g., blow-off tops), keeping you in statistically safe zones.
ATR Percentile Volatility Filter:
Logic: Tracks 14-bar ATR in a 100-bar window (default). Requires current ATR > 80th percentile (percATR) to trade (tradeOk).
Impact: Ensures sufficient volatility for meaningful moves, filtering out low-volume chop.
Multi-Timeframe (HTF) Trend Filter:
Logic: Uses a 50-bar SMA on a higher timeframe (default: 60min). Longs require price > HTF MA (bullTrendOK), shorts < HTF MA (bearTrendOK).
Impact: Aligns trades with the bigger trend, reducing counter-trend losses.
US Session Filter:
Logic: Restricts trading to 9:30am–4:00pm ET (default: enabled, useSession = true) using America/New_York timezone.
Impact: Focuses on high-liquidity hours, avoiding overnight spreads and erratic moves.
Evolution:
- These filters create a robust signal pipeline, ensuring trades are timed for optimal conditions.
- Customizable inputs (e.g., zThreshold, atrPercentile) let traders adapt to their style without compromising quality.
3. Risk Management
The strategy’s risk controls are a masterclass in balancing aggression and safety, protecting capital in volatile markets.
Daily Loss Kill Switch:
Logic: Tracks daily loss (dayStartEquity - strategy.equity). Halts trading if loss ≥ $300 (default) and enabled (killSwitch = true, killSwitchActive).
Impact: Caps daily downside, crucial during events like April 27, 2025 ES slippage.
Rolling Drawdown Kill Switch:
Logic: Monitors drawdown (rollingPeak - strategy.equity) over 100 bars (default). Stops trading if > $1000 (rollingKill).
Impact: Prevents prolonged losing streaks, preserving capital for better setups.
Dynamic Stop-Loss and Take-Profit:
Logic: Stops = entry ± ATR * multiplier (default: 1.0x, stopDist). TPs = entry ± ATR * 1.5x (profitDist). Longs: stop below, TP above; shorts: vice versa.
Impact: Adapts to volatility, keeping stops tight but realistic, with TPs targeting 1.5:1 reward/risk.
Max Bars in Trade:
Logic: Closes trades after 8 bars (default) if not already exited.
Impact: Frees capital from stagnant trades, maintaining efficiency.
Kill Switch Buffer Dashboard:
Logic: Shows smallest buffer ($300 - daily loss or $1000 - rolling DD). Displays 0 (red) if kill switch active, else buffer (green).
Impact: Real-time risk visibility, letting traders adjust dynamically.
Why It’s Brilliant:
- Kill switches and ATR-based exits create a safety net, rare in generic scripts.
- Customizable risk inputs (maxDailyLoss, dynamicStopMult) suit different account sizes.
- Buffer metric empowers disciplined trading, a DAFE signature.
4. Trade Entry and Exit Logic
The entry/exit rules are precise, filtered, and adaptive, ensuring trades are deliberate and profitable.
Entry Conditions:
Long Entry: bullDiv2, cooldown passed (canSignal), ATR filter passed (tradeOk), in US session (inSession), no kill switches (not killSwitchActive, not rollingKill), z-score OK (zOk), HTF trend bullish (bullTrendOK), no existing long (lastDirection != 1, position_size <= 0). Closes shorts first.
Short Entry: Same, but for bearDiv2, bearTrendOK, no long (lastDirection != -1, position_size >= 0). Closes longs first.
Adaptive Cooldown: Default 2 bars (cooldownBars). Doubles (up to 10) after a losing trade, resets after wins (dynamicCooldown).
Exit Conditions:
Stop-Loss/Take-Profit: Set per trade (ATR-based). Exits on stop/TP hits.
Other Exits: Closes if maxBarsInTrade reached, ATR filter fails, or kill switch activates.
Position Management: Ensures no conflicting positions, closing opposites before new entries.
Built To Be Reliable and Consistent:
- Multi-filtered entries minimize false signals, a stark contrast to basic scripts.
- Adaptive cooldown prevents overtrading, especially after losses.
- Clean position handling ensures smooth execution, even in fast markets.
5. DAFE Visuals
The visuals are a DAFE hallmark, blending function with clean flair to make signals intuitive and charts stunning.
Aurora Bands:
Display: Bands around price during divergences (bullish: below low, bearish: above high), sized by ATR * bandwidth (default: 0.5).
Colors: Aqua (bullish), fuchsia (bearish), with transparency tied to divStrengthNorm.
Purpose: Highlights divergence zones with a glowing, futuristic vibe.
Divergence Orbs:
Display: Large/small circles (aqua below for bullish, fuchsia above for bearish) when bullDiv2/bearDiv2 and canSignal. Labels show strength (0–1).
Purpose: Pinpoints entries with eye-catching clarity.
Gradient Background:
Display: Green (bullish), red (bearish), or gray (neutral), 90–95% transparent.
Purpose: Sets the market mood without clutter.
Strategy Plots:
- Stop/TP Lines: Red (stops), green (TPs) for active trades.
- HTF MA: Yellow line for trend context.
- Z-Score: Blue step-line (if enabled).
- Kill Switch Warning: Red background flash when active.
What Makes This Next-Level?:
- Visuals make complex signals (divergences, filters) instantly clear, even for beginners.
- DAFE’s unique aesthetic (orbs, bands) sets it apart from generic scripts, reinforcing originality.
- Functional plots (stops, TPs) enhance trade management.
6. Metrics Dashboard
The top-right dashboard (2x8 table) is your command center, delivering real-time insights.
Metrics:
Daily Loss ($): Current loss vs. day’s start, red if > $300.
Rolling DD ($): Drawdown vs. 100-bar peak, red if > $1000.
ATR Threshold: Current percATR, green if ATR exceeds, red if not.
Z-Score: Current value, green if within threshold, red if not.
Signal: “Bullish Div” (aqua), “Bearish Div” (fuchsia), or “None” (gray).
Action: “Consider Buying”/“Consider Selling” (signal color) or “Wait” (gray).
Kill Switch Buffer ($): Smallest buffer to kill switch, green if > 0, red if 0.
Why This Is Important?:
- Consolidates critical data, making decisions effortless.
- Color-coded metrics guide beginners (e.g., green action = go).
- Buffer metric adds transparency, rare in off-the-shelf scripts.
7. Beginner Guide
Beginner Guide: Middle-right table (shown once on chart load), explains aqua orbs (bullish, buy) and fuchsia orbs (bearish, sell).
Key Features:
Futures-Optimized: Tailored for MNQ, NQ, MES, ES with point-value adjustments.
Highly Customizable: Inputs for lookback, sensitivity, filters, and risk settings.
Real-Time Insights: Dashboard and visuals update every bar.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
User-Friendly: Guide, visuals, and dashboard make it accessible yet powerful.
Original Design: DAFE’s unique logic and visuals stand out from generic scripts.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Configure Inputs: Adjust instrument, filters, or risk (defaults optimized for MNQ).
Monitor Dashboard: Watch signals, actions, and risk metrics (top-right).
Backtest: Run in strategy tester to evaluate performance.
Live Trade: Connect to a broker (e.g., Tradovate) for automation. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Use bar replay (e.g., April 28, 2025 NQ drop) to test volatility handling.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Backtest results may not reflect live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Aurora Divergence – Quant Master isn’t just a strategy—it’s a movement. Crafted with originality and driven by community passion, it rises above the flood of generic scripts to deliver a system that’s as powerful as it is beautiful. With its quant-grade logic, DAFE visuals, and robust risk controls, it empowers traders to tackle futures with confidence and style. Join the DAFE crew, light up your charts, and let’s outsmart the markets together!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
Prop Firm Business SimulatorThe prop firm business simulator is exactly what it sounds like. It's a plug and play tool to test out any tradingview strategy and simulate hypothetical performance on CFD Prop Firms.
Now what is a modern day CFD Prop Firm?
These companies sell simulated trading challenges for a challenge fee. If you complete the challenge you get access to simulated capital and you get a portion of the profits you make on those accounts payed out.
I've included some popular firms in the code as presets so it's easy to simulate them. Take into account that this info will likely be out of date soon as these prices and challenge conditions change.
Also, this tool will never be able to 100% simulate prop firm conditions and all their rules. All I aim to do with this tool is provide estimations.
Now why is this tool helpful?
Most traders on here want to turn their passion into their full-time career, prop firms have lately been the buzz in the trading community and market themselves as a faster way to reach that goal.
While this all sounds great on paper, it is sometimes hard to estimate how much money you will have to burn on challenge fees and set realistic monthly payout expectations for yourself and your trading. This is where this tool comes in.
I've specifically developed this for traders that want to treat prop firms as a business. And as a business you want to know your monthly costs and income depending on the trading strategy and prop firm challenge you are using.
How to use this tool
It's quite simple you remove the top part of the script and replace it with your own strategy. Make sure it's written in same version of pinescript before you do that.
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
//--$$$$$--Strategy-- --$$$$$$--// ******************************************************************************************************************************
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
length = input.int(20, minval=1, group="Keltner Channel Breakout")
mult = input(2.0, "Multiplier", group="Keltner Channel Breakout")
src = input(close, title="Source", group="Keltner Channel Breakout")
exp = input(true, "Use Exponential MA", display = display.data_window, group="Keltner Channel Breakout")
BandsStyle = input.string("Average True Range", options = , title="Bands Style", display = display.data_window, group="Keltner Channel Breakout")
atrlength = input(10, "ATR Length", display = display.data_window, group="Keltner Channel Breakout")
esma(source, length)=>
s = ta.sma(source, length)
e = ta.ema(source, length)
exp ? e : s
ma = esma(src, length)
rangema = BandsStyle == "True Range" ? ta.tr(true) : BandsStyle == "Average True Range" ? ta.atr(atrlength) : ta.rma(high - low, length)
upper = ma + rangema * mult
lower = ma - rangema * mult
//--Graphical Display--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
u = plot(upper, color=#2962FF, title="Upper", force_overlay=true)
plot(ma, color=#2962FF, title="Basis", force_overlay=true)
l = plot(lower, color=#2962FF, title="Lower", force_overlay=true)
fill(u, l, color=color.rgb(33, 150, 243, 95), title="Background")
//--Risk Management--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
riskPerTradePerc = input.float(1, title="Risk per trade (%)", group="Keltner Channel Breakout")
le = high>upper ? false : true
se = lowlower
strategy.entry('PivRevLE', strategy.long, comment = 'PivRevLE', stop = upper, qty=riskToLots)
if se and upper>lower
strategy.entry('PivRevSE', strategy.short, comment = 'PivRevSE', stop = lower, qty=riskToLots)
The tool will then use the strategy equity of your own strategy and use this to simulat prop firms. Since these CFD prop firms work with different phases and payouts the indicator will simulate the gains until target or max drawdown / daily drawdown limit gets reached. If it reaches target it will go to the next phase and keep on doing that until it fails a challenge.
If in one of the phases there is a reward for completing, like a payout, refund, extra it will add this to the gains.
If you fail the challenge by reaching max drawdown or daily drawdown limit it will substract the challenge fee from the gains.
These gains are then visualised in the calendar so you can get an idea of yearly / monthly gains of the backtest. Remember, it is just a backtest so no guarantees of future income.
The bottom pane (non-overlay) is visualising the performance of the backtest during the phases. This way u can check if it is realistic. For instance if it only takes 1 bar on chart to reach target you are probably risking more than the firm wants you to risk. Also, it becomes much less clear if daily drawdown got hit in those high risk strategies, the results will be less accurate.
The daily drawdown limit get's reset every time there is a new dayofweek on chart.
If you set your prop firm preset setting to "'custom" the settings below that are applied as your prop firm settings. Otherwise it will use one of the template by default it's FTMO 100K.
The strategy I'm using as an example in this script is a simple Keltner Channel breakout strategy. I'm using a 0.05% commission per trade as that is what I found most common on crypto exchanges and it's close to the commissions+spread you get on a cfd prop firm. I'm targeting a 1% risk per trade in the backtest to try and stay within prop firm boundaries of max 1% risk per trade.
Lastly, the original yearly and monthly performance table was developed by Quantnomad and I've build ontop of that code. Here's a link to the original publication:
That's everything for now, hope this indicator helps people visualise the potential of prop firms better or to understand that they are not a good fit for their current financial situation.
Collatz Conjecture - DolphinTradeBot1️⃣ Overview
Every positive number follows its own unique path to reach 1 according to the Collatz rule.
Some numbers reach the end quickly and directly.
Others rise significantly before crashing down sharply.
Some get stuck within a certain range for a while before finally reaching 1.
Each number follows a different pattern — the number of steps it takes, how high it climbs, or which values it passes through cannot be predicted in advance.
This is a structure that appears chaotic but ultimately leads to order:
Every number reaches 1, but the way it gets there is entirely uncertain.
2️⃣ How Is It Work?
The rule is simple:
▪️ If the number is even → divide it by two.
▪️ If it’s odd → multiply it by three and add one.
Repeat this process at each step.
Example :
Let’s say the starting number is 7:
7 → 22 → 11 → 34 → 17 → 52 → 26 → 13 → 40 → 20 → 10 → 5 → 16 → 8 → 4 → 2 → 1
It reaches 1 in 17 steps.
And from there, it always enters the same cycle:
4 → 2 → 1 → 4 → 2 → 1...
3️⃣ Why Is It Worth Learning?
🎯 This indicator isn’t just mathematical fun—it’s a thought experiment for those who dare to question market behavior.
▪️ It’s fun.
Watching numbers behave in unpredictable ways from a simple rule set is surprisingly enjoyable.
▪️ It shows how hard it is to teach a computer what randomness really is .
The Collatz process can be used to simulate chaotic behavior and may even inspire creative ways to introduce complexity into your code.
▪️ It makes you think — especially in financial markets.
The patternless, yet rule-based structure of Collatz can help train your mind to recognize that not all unpredictability is random. It’s a great mental model for navigating complex systems like price action.
▪️ Just like price movements in financial markets, this ancient problem remains unsolved.
Despite its simplicity, the Collatz conjecture has resisted proof for decades — a reminder that even the most basic-looking systems can hide deep complexity.
4️⃣ How To Use?
Super easy — in the indicator’s settings, there’s just one input field.
Enter any positive number, and you’ll see the pattern it follows on its way to 1.
You can also observe how many steps it takes and which values it visits in the info box at the top center of the chart.
5️⃣ Some Examples
You Can Observe the Chaos in the Following Examples⤵️
For Input Number → 12
For Input Number → 13
For Input Number → 14
For Input Number → 32768
For Input Number → 47
DCA StrategyThis strategy makes it easy for you to backtest and automate the DCA strategy based on 2 triggers:
Day of the week
Every X candles
This way you can set up your DCA strategy the way you like and automate on any exchange or even a DEX, which offers an API.
The strategy is auto selling on the last candle, otherwise you won't see any performance numbers because all positions will still be open (non conclusive).
Settings
Start Date & End Date
Use those dates to help you with your backtest period. It also helps when automating, to start at a specific time to mimic what you have already done on your own portfolio and thus be in sync in TV as well.
Capital to invest per trade
Set how capital to use per DCA buy signal. Hover over the tooltip to understand, which currency is used.
Close All on last candle
When backtesting, you must close open positions, otherwise the Strategy Tester won't show you any numbers. This is why the strategy automatically closes all positions on the last candle for your convenience (ON per default).
BUT, when automating, you cannot have this checked because it would sell all of your asset on every candle open. So turn this OFF when automating.
Use Day of Week Mode
This checkbox switches between the "Day of Week" mode or the "Every X Candles" mode.
Day of Week
Opens a long position at the start of the weekday you have set it to.
Hover over the tooltip to understand, which number to use for the day of the week you need.
Every X Candles
Opens a long position after every x candles. Always at the start of every such candle.
On the daily chart, this number represents "1 day", on the 1h chart, it's "1 hour" and so on.
Properties
Initial Capital
DCA has a special quirk and that is that it invests more and more and more funds the longer it runs. But TradingView takes the Initial Capital number to calculate Net Profit, thus the Initial Capital number has to grow with every additional dollar (money) that is being invested over time, otherwise the Net Profit number will be wrong.
Sadly PineScript does not allow to set the Initial Capital number dynamically. So you have to set it manually.
To that end, this strategy shows a Label on the last candle, which shows the Invested Capital. You must take that number and put it into the Initial Capital input and click Ok .
If you don't do this, your Net Profit Number will be totally wrong!
The label must show green .
If it shows red it means you need to change the Initial Capital number before looking at the performance numbers.
After every timeframe or settings change, you must adapt the Initial Capital, otherwise you will get wrong numbers.
Follow Line Strategy Version 2.5 (React HTF)Follow Line Strategy v2.5 (React HTF) - TradingView Script Usage
This strategy utilizes a "Follow Line" concept based on Bollinger Bands and ATR to identify potential trading opportunities. It includes advanced features like optional working hours filtering, higher timeframe (HTF) trend confirmation, and improved trend-following entry/exit logic. Version 2.5 introduces reactivity to HTF trend changes for more adaptive trading.
Key Features:
Follow Line: The core of the strategy. It dynamically adjusts based on price breakouts beyond Bollinger Bands, using either the low/high or ATR-adjusted levels.
Bollinger Bands: Uses a standard Bollinger Bands setup to identify overbought/oversold conditions.
ATR Filter: Optionally uses the Average True Range (ATR) to adjust the Follow Line offset, providing a more dynamic and volatility-adjusted entry point.
Optional Trading Session Filter: Allows you to restrict trading to specific hours of the day.
Higher Timeframe (HTF) Confirmation: A significant feature that allows you to confirm trade signals with the trend on a higher timeframe. This can help to filter out false signals and improve the overall win rate.
HTF Selection Method: Choose between Auto and Manual HTF selection:
Auto: The script automatically determines the appropriate HTF based on the current chart timeframe (e.g., 1min -> 15min, 5min -> 4h, 1h -> 1D, Daily -> Monthly).
Manual: Allows you to select a specific HTF using the Manual Higher Timeframe input.
Trend-Following Entries/Exits: The strategy aims to enter trades in the direction of the established trend, using the Follow Line to define the trend.
Reactive HTF Trend Changes: v2.5 exits positions not only based on the trade timeframe (TTF) trend changing, but also when the higher timeframe trend reverses against the position. This makes the strategy more responsive to larger market movements.
Alerts: Provides buy and sell alerts for convenient trading signal notifications.
Visualizations: Plots the Follow Line for both the trade timeframe and the higher timeframe (optional), making it easy to understand the strategy's logic.
How to Use:
Add to Chart: Add the "Follow Line Strategy Version 2.5 (React HTF)" script to your TradingView chart.
Configure Settings: Customize the strategy's settings to match your trading style and preferences. Here's a breakdown of the key settings:
Indicator Settings:
ATR Period: The period used to calculate the ATR. A smaller period is more sensitive to recent price changes.
Bollinger Bands Period: The period used for the Bollinger Bands calculation. A longer period results in smoother bands.
Bollinger Bands Deviation: The number of standard deviations from the moving average that the Bollinger Bands are plotted. Higher deviations create wider bands.
Use ATR for Follow Line Offset?: Enable to use ATR to calculate the Follow Line offset. Disable to use the simple high/low.
Show Trade Signals on Chart?: Enable to show BUY/SELL labels on the chart.
Time Filter:
Use Trading Session Filter?: Enable to restrict trading to specific hours of the day.
Trading Session: The trading session to use (e.g., 0930-1600 for regular US stock market hours). Use 0000-2400 for all hours.
Higher Timeframe Confirmation:
Enable HTF Confirmation?: Enable to use the HTF trend to filter trade signals. If enabled, only trades in the direction of the HTF trend will be taken.
HTF Selection Method: Choose between "Auto" and "Manual" HTF selection.
Manual Higher Timeframe: If "Manual" is selected, choose the specific HTF (e.g., 240 for 4 hours, D for daily).
Show HTF Follow Line?: Enable to plot the HTF Follow Line on the chart.
Understanding the Signals:
Buy Signal: The price breaks above the upper Bollinger Band, and the HTF (if enabled) confirms the uptrend.
Sell Signal: The price breaks below the lower Bollinger Band, and the HTF (if enabled) confirms the downtrend.
Exit Long: The trade timeframe trend changes to downtrend or the higher timeframe trend changes to downtrend.
Exit Short: The trade timeframe trend changes to uptrend or the higher timeframe trend changes to uptrend.
Alerts:
The script includes alert conditions for buy and sell signals. To set up alerts, click the "Alerts" button in TradingView and select the desired alert condition from the script. The alert message provides the ticker and interval.
Backtesting and Optimization:
Use TradingView's Strategy Tester to backtest the strategy on different assets and timeframes.
Experiment with different settings to optimize the strategy for your specific trading style and risk tolerance. Pay close attention to the ATR Period, Bollinger Bands settings, and the HTF confirmation options.
Tips and Considerations:
HTF Confirmation: The HTF confirmation can significantly improve the strategy's performance by filtering out false signals. However, it can also reduce the number of trades.
Risk Management: Always use proper risk management techniques, such as stop-loss orders and position sizing, when trading any strategy.
Market Conditions: The strategy may perform differently in different market conditions. It's important to backtest and optimize the strategy for the specific markets you are trading.
Customization: Feel free to modify the script to suit your specific needs. For example, you could add additional filters or entry/exit conditions.
Pyramiding: The pyramiding = 0 setting prevents multiple entries in the same direction, ensuring the strategy doesn't compound losses. You can adjust this value if you prefer to pyramid into winning positions, but be cautious.
Lookahead: The lookahead = barmerge.lookahead_off setting ensures that the HTF data is calculated based on the current bar's closed data, preventing potential future peeking bias.
Trend Determination: The logic for determining the HTF trend and reacting to changes is critical. Carefully review the f_calculateHTFData function and the conditions for exiting positions to ensure you understand how the strategy responds to different market scenarios.
Disclaimer:
This script is for informational and educational purposes only. It is not financial advice, and you should not trade based solely on the signals generated by this script. Always do your own research and consult with a qualified financial advisor before making any trading decisions. The author is not responsible for any losses incurred as a result of using this script.
