BT AstroBT Astro Indicator — Quick Summary
BT Astro is a market context overlay that plots major astronomical timing cycles (planetary conjunctions + key time harmonics) directly on your chart to help you identify when markets are more likely to transition, accelerate, or stall .
This is not a buy/sell signal tool —it’s a timing + regime awareness layer designed to complement price/volume structure.
Key Features & Visuals
• Major Cycle Markers: clean vertical markers for high-impact events (ex: major conjunctions, eclipses)
• Toggle Controls: enable/disable event groups (ex: “Major Conjunctions”) to keep charts uncluttered
• Minimal Overlay: stays in the background—no forecasting lines, just time-based context
• Designed for Confluence: built to pair with regime/volatility/flow tools (not replace them)
How Traders Use It (Context, Not Entries)
• Timing Awareness: highlight windows where breakouts may follow through or fail more often
• Risk Adjustment: reduce size / tighten risk / stand down near major cycle windows; press only with confluence
• Regime Confirmation: use astro timing as a secondary “permission” layer when structure + flow already agree
• Discipline Filter: helps avoid forcing trades when time is misaligned, even if setups look good
Bottom Line
BT Astro does not predict direction. It adds a time-based caution/permission layer so you can trade your existing models with better context and cleaner decision-making.
Волатильность
EMA Spread Exhaustion DetectorEMA Spread Exhaustion – Reversal Scalper's Tool
Identifies trend exhaustion for high-probability counter-trend entries. Triggers when EMA(4/9/20) stack is fully aligned and spread stretches beyond ±ATR threshold. Ideal confluence for TDI hooks + strong rejection candles on 15s charts. Visual markers, fills, and alerts for quick scalps.
Hard Asset Regime + StrongestHard Asset Strongest Momentum
Simple tool to show which hard asset (gold, silver, or Bitcoin) has the strongest 21-day momentum right now.
Green background = RISK ON regime (growth environment)
Red background = RISK OFF regime (defensive environment)
Black = NEUTRAL
Label shows the current regime and the strongest asset on momentum.
Use it to:
• Identify the current leader among gold, silver, and BTC
• Hold the strongest — consider trimming it if you need fiat for a purchase (it’s spiking)
Works well alongside my original "Best Metal to Sell → More BTC" indicator for rotation decisions.
No forced rotation — just clarity for long-term hard-asset holders.
2020–2025 backtest (holding strongest on signals): strong outperformance vs HODL metals, smoother than pure BTC.
Not financial advice.
BiasFlow Long System🔹 Short summary
“BiasFlow Long System” is an invite-only, long-only strategy designed to participate in bullish trends using a combination of:
• a directional “bias” filter based on price behaviour over time, and
• candle-structure conditions that confirm short-term strength before entering,
plus a simple risk-management layer (stop loss and optional take profit).
The system is intentionally selective: it aims to enter only when a clear upward bias and a cluster of bullish price action align, and then to exit on opposite conditions or risk-based levels. It is NOT a holy grail and NOT financial advice.
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0. Legal / risk disclaimer
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• This script is invite-only and for EDUCATIONAL and RESEARCH purposes only.
• It is NOT financial advice and does NOT guarantee profits.
• Backtest results can differ significantly from live trading results.
• Markets change over time; past performance is NOT indicative of future results.
• You are fully responsible for your own trading decisions and risk.
Do not trade with money you cannot afford to lose. Always start with demo / paper trading and make sure you understand how the strategy behaves on your own market and timeframe before risking real capital.
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1. About default settings and risk (very important)
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The internal `strategy()` call uses:
• `initial_capital = 100`
→ This is only a simple example account size for testing.
• `default_qty_type = strategy.percent_of_equity`
• `default_qty_value = 100`
→ This means 100% of equity per trade in the default properties.
→ This is EXTREMELY AGGRESSIVE and should be treated purely as a STRESS TEST of the logic, **not** as a realistic way to trade.
To align with TradingView’s Strategy Results guidelines and more realistic risk management, you should:
1. Open **Strategy Settings → Properties**.
2. Change:
• Order size type → **Percent of equity** (if not already).
• Order size (percent) → e.g. **1–2%** per trade (or any small risk that fits your plan).
3. Check that **commission & slippage** are realistic for your broker and market.
• The script uses a 0.1% example commission and a small slippage value as a starting point, but you must adapt them to your conditions.
If you decide to run 100% of equity per trade, treat it only as a stress scenario for backtesting the behaviour of the system, **never** as a recommended risk profile for live trading.
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2. What this strategy tries to do (conceptual overview)
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BiasFlow Long System is a **long-only, bias-based trend participation strategy**.
Conceptually, it tries to:
1. Detect when the market has a **sustained upward directional bias** using an internal bias filter applied directly to price behaviour over time.
2. Wait for a **short-term cluster of bullish candles** in that favourable environment before entering a long position.
3. Use **risk-based exits** (stop loss and optional take profit) together with a bearish candle-structure condition to close trades when the upward bias fails or local conditions deteriorate.
In other words, it is not trying to catch every small fluctuation. Instead, it waits for the market to **lean upward** and then demands a clear, short-term confirmation from the candles before committing capital, exiting either on a controlled risk level or on a structured bearish pattern.
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3. Components and how they work together
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BiasFlow Long System consists of three main building blocks:
(1) Time / backtest window control
• You can select a continuous start/end date range.
• You can also use a **year-selector** (checkboxes per year) to include or exclude specific calendar years.
• This allows you to:
- test the strategy across long histories,
- compare behaviour in different regimes (e.g. 2018 vs 2021),
- avoid accidentally cherry-picking a tiny, overly-optimistic window.
(2) Bias engine
• Internally, the strategy computes a **directional bias** from price.
• It classifies the environment into broad states like “up”, “down” (and internally handles flat conditions).
• Long entries are only allowed when the bias engine deems the environment favourable (an “up” state).
• This prevents the strategy from buying blindly into obvious downtrends.
(3) Candle-structure and risk module
• Entry signals require a **cluster of bullish candles** that meet strict internal conditions.
- Exact rules are deliberately not disclosed, but the idea is to demand multiple aligned bullish bars to confirm local strength before entering.
• Exits can be triggered by:
- a **cluster of bearish candles** under suitable conditions, signalling local weakness, and/or
- the risk module (stop loss / take profit) if those levels are hit first.
These components are designed to work together so that the strategy only participates when:
• the broader environment supports longs (bias engine), and
• the immediate price action confirms that bullish pressure is actually present (candle structure),
while exits are handled in a rule-based way either by candle structure or by pre-defined risk thresholds.
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4. Entry & Exit logic (high level)
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At a high conceptual level:
A) Time filter
• Only bars inside your chosen backtest window (date range or selected years) are considered for entries and exits.
• This helps you analyse specific periods (e.g. only post-2020 data) without changing the code.
B) Entry (long-only)
A long trade is considered only when all of the following conceptual conditions are met:
1. The bar is inside the allowed backtest window.
2. The **bias engine** classifies the environment as favourable for longs (up-bias).
3. The most recent candles form a **bullish sequence** according to internal rules (e.g. price closing strongly vs. open on several consecutive bars).
If these conditions align, the strategy opens a **single long position** with the sizing defined in your Strategy Properties (for example 1–2% of equity per trade).
C) Risk-based exit
Once in a position, the strategy maintains a basic risk framework:
• **Stop Loss (SL)**:
- Defined as a percentage distance below the average entry price.
- Enabled by default in the Inputs, but you can adjust the percentage or disable it if you want to test raw logic.
• **Take Profit (TP)**:
- Also defined as a percentage distance above the average entry price.
- By default, the TP module is optional and configured as a very wide level so it does not interfere unless you intentionally enable and tune it.
- You should set a realistic TP (for example a multiple of your risk) if you want to use it.
The SL/TP orders are managed as OCO exits by TradingView, so if one is hit first, the other is cancelled automatically.
D) Candle-based exit
In addition to risk exits:
• The strategy watches for a **structured bearish sequence** of candles while the bias is still acceptable for exits.
• When that bearish structure appears, the strategy closes the open long position.
• This allows the system to respond to a change in short-term price behaviour even if the stop loss or take profit have not been reached yet.
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5. Recommended backtest configuration (to avoid misleading results)
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To keep your results in line with TradingView’s Strategy Results guidelines and avoid misleading curves:
1. **Initial capital**
- You can keep 100 as in the code or choose any other realistic account size.
2. **Order size (RISK PER TRADE)**
- Type: **Percent of equity**.
- Recommended: **1–2% per trade** as a starting point.
- Avoid using more than 5–10% risk per trade if you want something that could be sustainable in real trading.
3. **Commission & slippage**
- Commission: for example 0.1% if that approximates your broker’s fee.
- Slippage: a few ticks (e.g. 3) to represent real fills.
- Always adjust these to your instrument and broker conditions.
4. **Timeframe & markets**
- The system is designed to work on trending instruments (for example major crypto pairs or indices).
- Typical timeframes: 1D is reasonable starting points but you can try with 1H / 4H.
- On higher timeframes, trades will be rarer but may aim at larger swings.
5. **Avoid “caution warning” backtests**
- If TradingView shows warnings like “too few trades” or “insufficient data” in your chosen configuration, consider:
- expanding the backtest period,
- switching to a more liquid / volatile instrument, or
- changing timeframe to produce a more meaningful sample.
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5a. About low trade count and selective signals
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BiasFlow Long System is **not** a high-frequency scalping algorithm. It is deliberately selective:
• It is long-only.
• It requires a favourable bias environment AND a specific pattern of bullish candles before entering.
• On higher timeframes (e.g. Daily) or very strict filter settings, the strategy can produce a **relatively low number of trades** over many years of data.
TradingView often recommends having 100+ trades for stronger statistics. In this particular system:
• A lower trade count is a **conscious design choice**, reflecting the goal of focusing on a smaller set of higher-conviction long setups rather than constant trading.
• Because of this, backtest metrics (profit factor, win rate, etc.) should NOT be interpreted as statistically “proven” – they are just one sample of how this logic would have behaved on past data.
Always use caution when drawing conclusions from a small number of trades.
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6. How to use this strategy (step-by-step)
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1. **Add the script to your chart**
- Choose your instrument and timeframe (e.g. BTCUSDT 1D, or any trending symbol you want to study).
2. **Configure the backtest window**
- In the Inputs, set either:
- a specific Start Date (e.g. 2018-01-01), or
- use the year checkboxes to include/exclude calendar years.
- This allows you to test different regimes (pre-/post-halving, bull vs. bear, etc.).
3. **Adjust risk settings**
- Open Inputs → Risk Management:
- Choose whether to use the Stop Loss and/or Take Profit.
- Set realistic percentages for your market and volatility.
- Open Strategy Properties:
- Set order size to a realistic % of equity (e.g. 1–2%).
- Verify commission and slippage.
4. **Run the backtest**
- Inspect:
- Net Profit, Max Drawdown, Profit Factor
- Number of trades and average trade duration
- Equity curve shape (smooth vs. choppy).
5. **Experiment carefully**
- Try different symbols, timeframes, and risk settings.
- Observe how the system behaves in different market regimes and how sensitive it is to your parameter choices.
6. **Forward-test in demo**
- Before even considering live usage, run the system on a paper account and watch how signals appear in real time.
- Make sure the behaviour matches your expectations from the backtest.
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7. Originality and usefulness (why this is more than a mashup)
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BiasFlow Long System is not just a visual mashup of common indicators on a chart. It is a **coherent, bias-driven framework** with:
• A dedicated **time / regime control** (year and date filters) to study behaviour across multiple cycles.
• An internal **bias engine** that only allows trades when the market structure supports longs.
• A **candle-structure layer** that requires a sequence of aligned bullish or bearish bars, rather than isolated single-bar signals.
• A simple but practical **risk module** that integrates percentage-based SL/TP exits.
The core logic is intentionally abstracted and not publicly disclosed, but the conceptual design is:
• to combine directional bias,
• with short-term confirmation,
• under explicit risk-management constraints,
in a way that is testable, repeatable, and suitable as a base for further private research and improvement.
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8. Limitations and good practices
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• No strategy performs well in all markets and all conditions.
• This system is **long-only**, so in prolonged bear markets it may spend long periods out of the market or perform poorly.
• Performance is sensitive to:
- timeframe,
- instrument volatility,
- risk settings (SL/TP, position size).
Good practices:
• Test on multiple instruments and timeframes.
• Focus on drawdowns, stability, and robustness, not just on maximum profit.
• Avoid overfitting by constantly re-optimising parameters to your last backtest window.
• Treat this as a **framework and research tool**, not a plug-and-play money printer.
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9. Licensing and credits
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• Code and logic:
- “BiasFlow Long System” created by Jokiniemi Marcin Arcisz.
• This script is invite-only.
• If you reuse or extend ideas from this system, please do so in a way that respects TradingView’s House Rules and the author’s intent.
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10. Invite-only / vendor information
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• This strategy is distributed on an **invite-only** basis.
• There is **no guarantee of profit** and no claim that this strategy will outperform the market.
• The description focuses on the conceptual design and risk considerations so that TradingView users and moderators can understand what it tries to do and how to use it responsibly.
• Any access, subscription, or collaboration outside TradingView, if it exists, should always comply with TradingView’s Vendor Requirements and general House Rules.
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11. Example backtest settings used in screenshots
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To avoid confusion about how example results were produced, here is one concrete configuration you can use as a starting point:
• Symbol: BTCUSDT (or another major, liquid trending pair)
• Timeframe: 1D
• Backtest period: from 2018-01-01 to the most recent available data
• Initial capital: 100
• Order size type: Percent of equity
• Order size: 2% per trade
• Commission: 0.1%
• Slippage: 3 ticks
• Risk settings:
- Stop Loss enabled with a moderate % distance from entry
- Take Profit disabled or set to a realistic multiple of the risk
• Filters:
- Backtest window: multiple years selected
- Bias engine and candle-structure logic enabled (as they are part of the core system)
If you change any of these parameters (symbol, timeframe, risk per trade, commission, slippage, backtest window, etc.), your results will look different. Always adapt the configuration to your own risk tolerance, market, and trading style.
STOC Trend Analysis for F&O
For Long Term trend Analysis.
I have added three STs for long term investments. This indicator absorbs the short term volatility.
//Follow me on Twitter @STOC_Master//
This indicator is provided for educational and informational purposes only.
It does not constitute financial advice, investment recommendations, or trade signals.
The creator and Systematic Traders Club are not responsible for any financial losses resulting from the use of this indicator.
Trading and investing involve risk. Always do your own analysis and use proper risk management.
Pro Minimalist ATR (Black)The script I provided is a tool that automatically calculates and displays volatility "zones" around the average price. Here is the plain English explanation of what it is doing and why:
1. The Anchor: 20 DMA (The "Fair Value")
The script starts by calculating the 20-Day Moving Average (20 DMA).
What it represents: Think of this as the "fair price" or the "center of gravity" for the market over the last month.
In the script: It looks at the closing price of the last 20 candles, adds them up, and divides by 20. This is your baseline.
2. The Ruler: ATR (The "Volatility")
Next, it measures the Average True Range (ATR) over the last 14 days.
What it represents: This measures the "energy" or "noise" of the market. If candles are huge, the ATR is high. If candles are tiny, the ATR is low.
Why we use it: Using a fixed number (like $50) doesn't work because stocks move differently. ATR adapts to the current market mood.
3. The Zones: +1, +2, -1, -2
The script then takes that "center" (20 DMA) and adds/subtracts the "ruler" (ATR) to create four distinct levels:
+1 ATR: This is the "Upper Normal" limit. Price hanging here is bullish but normal.
+2 ATR: This is the "Extreme" limit. Statistically, price rarely stays above this line for long without snapping back. This is often an overbought signal.
-1 ATR: This is the "Lower Normal" limit.
-2 ATR: This is the "Extreme" discount. If price hits this, it is statistically stretched far below its average.
4. The Visuals: "Clean" Labeling
Finally, the script focuses on presentation:
No Lines: It specifically avoids drawing lines all over your history to keep your chart clean.
Dynamic Labels: It creates text labels only on the very last bar (the current moment). It constantly deletes the old label and draws a new one as the price moves, so it looks like the text is "floating" next to the current price.
Axis Marking: It forces marks onto the right-hand price scale (display=display.price_scale) so you can see the exact price levels (e.g., 154.20) without having to guess.
S&P 500 Momentum Coiling Tracker [20/200 MA]This indicator measures the absolute point distance between the 20-period SMA and the 200-period SMA, specifically optimized for the S&P 500 (ES/MES) index.
In the style of institutional trend following, it identifies the "Narrow State"—a period of low volatility where a major breakout is imminent.
How to read the Histogram:
🟢 GREEN (< 8 pts): Ultra-Narrow/Coiled State. Stored energy is high. Watch for an explosive breakout.
🟡 YELLOW (8-15 pts): Narrow/Transition. The averages are converging or just starting to fan out.
⚪ GRAY (15-30 pts): Neutral trending zone.
🔴 RED (> 30 pts): Extended State. Price is stretched far from the long-term mean; avoid chasing the move.
D2E + Bands (Distance to EMA)D2E (Distance to Daily EMA)
Concept and Underlying Calculation This indicator is built on the theory of Mean Reversion. It operates on the premise that price acts like a rubber band; while it can stretch away from its average value, it rarely stays at extreme extensions for long periods without snapping back (retracement) or pausing to let the average catch up (consolidation).
Unlike standard deviations (Bollinger Bands) or ATR channels, this script uses Fixed Percentage Thresholds relative to a Multi-Timeframe Daily EMA.
How it Works (The Math)
Multi-Timeframe Data: The script specifically requests the Daily (1D) Exponential Moving Average (default length 20) regardless of the timeframe you are currently viewing. This allows day traders on a 5-minute or 15-minute chart to see their position relative to the macro Daily trend.
Distance Calculation: It calculates the variance between the current Close price and the Daily EMA using the formula: 100 * (Close - DailyEMA) / DailyEMA.
Projected Zones: It plots theoretical bands at user-defined percentage distances (e.g., 3% and 6%) above and below the Daily EMA.
How to Use
Trend Extension: When price interacts with the "Threshold %" (Yellow), it indicates the asset is becoming overextended relative to its daily mean. This often serves as a take-profit target for trend followers.
Reversal Signals: Interaction with the "Extreme Threshold %" (Red) suggests a statistically significant deviation, often signaling an exhaustion point where a mean-reversion trade (returning to the EMA) becomes probable.
The Dashboard: A dynamic table is included to provide real-time data on the exact dollar amount and percentage distance from the EMA, color-coded to match the severity of the extension.
Features and Settings
EMA Length: Customizable lookback period for the Daily EMA (Default: 20).
Thresholds: Adjustable percentage settings for standard and extreme deviations.
Visuals: Toggleable threshold lines and a customizable on-screen dashboard (position and size).
Alerts: Pre-configured alert conditions for crossing both standard and extreme thresholds.
Disclaimer This tool is for informational purposes only and does not constitute financial advice. Past performance of mean reversion strategies does not guarantee future results.
Bollinger Aurora Velocity [Pineify]Pineify - Bollinger Aurora Velocity
The Bollinger Aurora Velocity is an enhanced volatility and trend analysis indicator that transforms the classic Bollinger Bands into a visually stunning, multi-dimensional trading tool. By combining standard deviation bands with historical extreme tracking and dynamic momentum coloring, this indicator provides traders with deeper insights into volatility cycles, squeeze conditions, and trend strength all in one overlay.
Key Features
Classic Bollinger Bands with customizable period and standard deviation multiplier
Nebula Memory Cloud tracking historical band extremes for volatility context
Volatility Squeeze Detection with visual dot indicators on the basis line
Gradient-based candle coloring reflecting normalized price position
Multi-layer aurora gradient fills for intuitive visual analysis
How It Works
The indicator begins with a standard Bollinger Bands calculation using a simple moving average as the basis line, with upper and lower bands placed at a user-defined multiple of standard deviation. This core structure measures price volatility and identifies overbought/oversold conditions.
The Nebula Memory Cloud extends beyond traditional bands by tracking the highest point of the upper band and lowest point of the lower band over a configurable lookback period. This creates an outer envelope showing the maximum volatility expansion in recent history.
Trading Ideas and Insights
The Volatility Squeeze is a powerful concept where contracting Bollinger Bands often precede significant price breakouts. This indicator detects squeezes by comparing the current band width to its 100-period simple moving average. When the current range falls below this average, yellow dots appear on the basis line, alerting traders to potential explosive moves ahead.
When squeeze dots appear and the outer nebula cloud shows significant distance from the current bands, it suggests volatility is at a historical low relative to recent extremes—a setup often followed by strong directional moves.
How Multiple Indicators Work Together
Bollinger Bands establish the primary volatility envelope and mean-reversion zones
The Nebula Cloud provides historical context, showing how current volatility compares to recent extremes
Squeeze Detection identifies compression phases using relative bandwidth analysis
Normalized Scoring translates price position into a 0-100 scale for gradient coloring
Unique Aspects
Unlike standard Bollinger Bands indicators, the Aurora Velocity creates a heat-map effect on price bars. The normalized score calculates where price sits within the bands as a percentage, then applies a smooth gradient from bearish to bullish colors. This allows traders to instantly perceive momentum strength—saturated bullish colors near the upper band indicate strong upward pressure, while saturated bearish colors near the lower band signal selling dominance.
The aurora-style gradient fills between band layers create visual depth, making it easy to distinguish the core volatility zone from the historical extreme boundaries.
How to Use
Monitor candle colors for momentum direction—bright green indicates bullish positioning, bright red signals bearish pressure
Watch for yellow squeeze dots on the basis line as early warning for potential breakouts
Use the outer nebula cloud to assess if current volatility is testing historical extremes
Set alerts for price breakouts above the upper band or below the lower band
Combine squeeze conditions with the nebula cloud width to gauge breakout potential
Customization
Base Period - Controls Bollinger Bands calculation length (default: 20)
Standard Deviation Multiplier - Adjusts band width from the basis (default: 2.0)
Price Source - Select the price input for calculations (default: close)
Nebula Memory Length - Lookback period for tracking historical extremes (default: 50)
Color Settings - Customize bullish and bearish gradient colors
Conclusion
The Bollinger Aurora Velocity elevates traditional Bollinger Bands analysis by adding historical volatility context through the Nebula Cloud, precise squeeze detection for breakout anticipation, and intuitive momentum visualization through gradient candle coloring. This combination helps traders identify not just where price is relative to volatility bands, but how that volatility compares to recent history and when compression may lead to expansion.
Lakshmi - Low Volatility Range Breakout (LVRB)⚡️ Overview
The Low Volatility Range Breakout (LVRB) indicator is designed to identify consolidation phases characterized by suppressed volatility and generate actionable signals when price breaks out of these ranges. The underlying premise is rooted in the market principle that periods of low volatility often precede significant directional moves—volatility contraction leads to expansion.
Important Note on Optimization: The default parameter settings of this indicator have been specifically optimized for BTCUSDT on the 2-hour (2H) timeframe. While the indicator can be applied to other instruments and timeframes, users are encouraged to adjust the parameters accordingly to suit different trading conditions and asset characteristics.
This indicator automates the detection of "quiet" accumulation/distribution zones and provides clear visual cues and alerts when a breakout occurs.
⚡️ How to Use
1. Add the indicator to your chart. Default settings are optimized for BTCUSDT 2H.
2. Wait for a gray box to appear—this indicates a qualified low-volatility range is forming.
3. Monitor for breakout signals:
• LONG (green triangle below bar): Price broke above the range. Consider entering a long position.
• SHORT (red triangle above bar): Price broke below the range. Consider entering a short position.
4. Set alerts using "LVRB LONG" or "LVRB SHORT" to receive notifications on confirmed breakouts.
5. Adjust parameters as needed for different instruments or timeframes.
Tip: Combine with volume analysis or trend filters for higher-probability setups.
⚡️ How It Works
1. Low Volatility Bar Detection
A bar is classified as "low volatility" when it meets the following criteria:
• True Range (TR) is at or below the average TR (Simple Moving Average) multiplied by a user-defined threshold.
• (Optional) Candle Body is at or below the average body size multiplied by a separate threshold.
This dual-filter approach helps isolate bars that exhibit genuine compression in both range and directional commitment.
2. Range Box Formation
When consecutive low-volatility bars are detected, the indicator begins constructing a consolidation box:
• The box expands to encompass the high and low of qualifying bars.
• A minimum number of bars and a minimum fraction of low-volatility bars are required for the box to become "qualified" (active).
• A configurable tolerance allows for a limited number of consecutive non-low-vol bars within the sequence, accommodating minor noise without invalidating the range.
• If the box height exceeds a maximum threshold (defined as a multiple of the base ATR at sequence start), the range is invalidated.
3. Breakout Detection
Once a qualified range is established, the indicator monitors for breakouts:
• Wick Mode: Requires both a wick pierce beyond the range boundary AND a close outside the range.
• Close Mode: Requires only a close beyond the range boundary.
• (Optional) Breakout Body Filter: The breakout candle's body must exceed a multiple of the average body size at range formation.
• (Optional) Candle Direction Filter: Bullish breakouts require a green candle; bearish breakouts require a red candle.
Signals are displayed in real-time and confirmed upon bar close.
⚡️ Inputs & Parameters
• Volatility Window: Lookback period for calculating average TR and average body size.
• TR Multiplier: A bar's TR must be ≤ avgTR × this value to qualify as low-vol.
• Body Multiplier: A bar's body must be ≤ avgBody × this value (if body filter is enabled).
• Use Body Filter: Toggle the body size filter on/off.
• Min Bars in Box: Minimum number of bars required for a range to become qualified.
• Min Low-Vol Fraction: Minimum proportion of bars in the sequence that must be low-vol.
• Allowed Consecutive Non-Low-Vol Bars: Tolerance for consecutive bars that do not meet low-vol criteria.
• Max Box Height: Maximum allowed range height as a multiple of the base ATR.
• Breakout Mode: Choose between "Wick" (pierce + close) or "Close" (close only).
• Breakout Body Multiplier: Require breakout candle body ≥ avgBody × this value (1.0 = OFF).
• Require Candle Direction: Enforce green candle for LONG, red candle for SHORT.
⚡️ Visual Features
• Consolidation Boxes: Displayed in neutral (gray) color during formation. Upon a confirmed breakout, the box is colored green for bullish breakouts or red for bearish breakouts.
• Breakout Signals:
• LONG: Green upward triangle displayed below the price bar with "LONG" label.
• SHORT: Red downward triangle displayed above the price bar with "SHORT" label.
• Range Levels: Optional horizontal plots for the active range's high and low.
• Invalidated Boxes: Optionally retained in neutral (gray) color or deleted from the chart.
• Full Customization: Colors, transparency, and border width are all adjustable.
⚡️ Alerts
Two alert conditions are available:
• LVRB LONG: Triggered on a confirmed bullish breakout (bar close).
• LVRB SHORT: Triggered on a confirmed bearish breakout (bar close).
⚡️ Use Cases
• Breakout Trading: Enter positions when price escapes a well-defined low-volatility range.
• Volatility Expansion Plays: Anticipate increased volatility following periods of compression.
• Filtering Choppy Markets: Avoid trading during extended consolidation; wait for confirmed breakouts.
• Multi-Timeframe Analysis: Use on higher timeframes to identify major consolidation zones.
⚡️ Notes
• Best used in conjunction with volume analysis, trend context, or support/resistance levels for confirmation.
• Performance varies across instruments and timeframes; backtesting and parameter optimization are recommended.
⚡️ Credits
Developed by Lakshmi. Inspired by volatility contraction principles and range breakout methodologies.
⚡️ Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a guarantee of profits. Trading financial instruments involves substantial risk, and you may lose more than your initial investment. Past performance, whether indicated by backtesting or historical analysis, does not guarantee future results. The use of this indicator does not ensure or promise any profits or protection against losses. Users are solely responsible for their own trading decisions and should conduct their own research and/or consult with a qualified financial advisor before making any investment decisions. By using this indicator, you acknowledge and accept that you bear full responsibility for any trading outcomes.
Not only a Supertrend [by Oberlunar]Oberlunar’s Not only Supertrend is designed for traders who need something that stays reactive in fast regimes without collapsing when the tape turns discontinuous—volume gaps, microstructure noise, sudden volatility shocks.
The design goal is to approximate market regime dynamics by combining a probability-like regime score (a bounded Bayesian-style posterior from multiple evidence) with a measure of regime impulse (the Kalman-filtered step/change in evidence).
For ETF-like tapes, it models second-order behaviour: volatility expansion vs contraction, persistence of the expansion, and participation/flow confirmation proxies (via multi-broker OHLCV pressure dominance), to reduce sensitivity to transient spikes.
There is no type of lookahead bias or repaint:
More or less 2 R in a 10-minute chart...
The core signal is built around two regime proxies that are intentionally different, so they don’t fail in the same way when the tape gets stressed.
The first proxy looks at realised volatility computed from log-returns, then maps it into a rolling percentile range. Framing volatility this way keeps it scale-free and easier to compare across instruments and across very different volatility states, and it also helps avoid the typical warping you can get from raw ATR-like measures when the market produces abrupt jumps.
The second proxy focuses on Bollinger Band width, but not in absolute terms: it measures the width relative to its own EMA baseline, and then compresses that ratio through a logistic mapping. This keeps the regime evidence continuous, smoothly saturating, and far less prone to “threshold artefacts” where a tiny change flips the state.
Put together, these two pieces produce an “ expansion base ” and a “ contraction base ” that stay bounded and well-behaved, even when price action prints discontinuities.
Then, directional bias is handled as a soft prior that can lean the model without overpowering it. In practice, a weighted multi-timeframe RSI builds a probability-like prior over long versus short bias, so the engine can express partial conviction and gracefully reconcile conflicts across timeframes instead of forcing a single, binary view.
That separation matters in situations where directional edge and volatility regime edge are related but not the same thing. The design keeps them coupled—so strong direction can reinforce regime confidence—but it does not collapse them into one signal.
For that reason, the system works with four parallel channels— expansion-long, expansion-short, contraction-long, contraction-short —as continuous evidence streams. And when price breaks the Bollinger bands, it’s treated as a conditional boost to the relevant evidence instead of an absolute trigger, which helps reduce false positives during noisy, stop-run style breakouts.
You can use a not only Supertrend line style with signals...
...or just follow its planes and their breakout, such in the following example:
To keep the system resilient to gaps and one-bar anomalies, the raw evidence doesn’t go straight into decisions: it is first passed through an alpha–beta Kalman update. In practical terms, this acts as a lightweight state-space tracker that follows both the level of the evidence and its drift .
The level is your smoothed, probability-like regime proxy. The drift is the key ingredient for options, because it captures how quickly the regime is changing—what you can reasonably describe as the acceleration of the transition.
Crucially, the script doesn’t just compute that internally and forget it: it explicitly takes the step of the filtered state, normalises it, and uses it as a feature. That lets the engine distinguish between a regime that is high but basically flat, and a regime that is actively ramping. And because one-bar spikes can still happen, the step feature is bounded, so it can react to real transitions without overreacting to a single print.
The final confidence layer is produced with a Bayesian-style update that treats both the prior and the incoming evidence as **pseudo-counts in a Beta distribution**, and then uses the **posterior mean** as the final probability-like score. The prior is derived from the weighted multi-timeframe RSI: the script maps the weighted RSI into a smooth probability via a sigmoid (`rsiPriorLong`), and uses its complement for short bias (`rsiPriorShort`).
The likelihood is built per channel, and it is deliberately simple and bounded. For expansion, the likelihood combines the Bollinger expansion signal with the normalised Kalman step , using user-controlled weights. Contraction does the same with the corresponding contraction signals. Small conditional boosts are then applied when the price breaks the bands (or stays inside them), but these boosts remain incremental rather than flipping the state.
The two strength parameters, `kPrior` and `kLike`, control how “ sticky ” this posterior is. A higher `kPrior` makes the posterior lean more strongly on the RSI-based belief and therefore move more smoothly. A higher `kLike` gives more authority to the incoming evidence (BB regime + Kalman step), so the posterior adapts faster when conditions change.
In effect, this is a practical calibration layer: instead of stacking indicators and hoping they agree, the script converts each component into bounded evidence, fuses them into a single posterior mean, and exposes explicit controls for stability versus responsiveness—exactly the trade-off you typically care about when dealing with convex instruments, where you want confidence to be reactive, but not fragile.
Bands filled by expansion Bayesian posterior:
Because regime detection alone isn’t enough to avoid whipsaws, the script adds an adaptive “lane supertrend” layer. This supertrend layer is not built upon a classic ATR. Instead of operating on price distance, it operates on posterior imbalance : the engine computes a net score as the difference between bullish and bearish posteriors (`netE = postEL - postES` for expansion and `netC = postCL - postCS` for contraction), and that net is what drives direction.
Direction changes are then gated by an adaptive deadband .
In turn, the deadband is not fixed: it expands or contracts based on two things that already exist in the model— posterior confidence (e.g., `confE = max(postEL, postES)`) and regime intensity (e.g., `regE = volPct01`, and the complementary contraction regime). Those are mixed to produce `dbE` and `dbC`, which act like a hysteresis zone around neutrality.
When the posterior is indecisive and the regime is noisy, the deadband effectively widens, so small oscillations around zero don’t cause constant flips. When the posterior becomes decisive, the deadband tightens, and the direction logic becomes more responsive.
On top of that, flips are not allowed instantly: the script uses a flip-confirm counter that requires the net score to stay beyond the deadband for multiple bars before a direction switch is accepted. This prevents the engine from toggling on micro-oscillations and single-bar disturbances.
Visually, the “lane” is explicitly mapped into price space .
In detail, the script builds a lane geometry using ATR as a vertical scale, then projects the net posterior into the expansion and contraction band. With optional trailing enabled, the lane value is further “supertrend-like”, so what you see on the chart reads as a probabilistic supertrend line —a line whose position and persistence reflect posterior imbalance—rather than a raw volatility expression.
Finally, to address real-world tape issues (discontinuities, fragmented liquidity, venue noise), the script integrates a multi-broker Volumetric Dominance filter as an additional gate. It aggregates multi-broker OHLCV, derives a pressure-like proxy, and only allows certain triggers when cross-broker dominance is sufficiently aligned—so the system is less likely to react to isolated prints that aren’t supported by broader participation.
Once dominance is both directional and concentrated, the filter becomes a hard regime-consistency gate. If dominance is meaningfully bearish, the script blocks bullish expansion triggers and symmetrically blocks bearish expansion triggers when dominance is bullish. In other words, it’s not trying to “confirm” signals after the fact; it enforces a consistency constraint between volatility-expansion regime and cross-venue participation direction, specifically to reduce the exact kind of false positives that can wreck options entries: apparent volatility expansion occurring into opposing flow.
Thus, this is not only a Supertrend. It’s a bounded, smooth regime engine with an outlier-resistant “acceleration” step, a Bayesian-style posterior with tunable inertia, and a dominance gate that blocks expansion signals when multi-venue pressure points the other way.
It can still fail—no proxy fully captures the tape, and any filter can lag or miss abrupt turns—but I think it’s a framework worth exploring for more informed entries across assets: responsive in fast regimes, yet less fragile around gaps and volatility shocks.
Enjoy!
by Oberlunar 👁★
Stoch X vs Stoch Y (RSI-based)This script plots two RSI-based Stochastic oscillators in the same panel:
X (fast) is a classic Stoch RSI “trigger” line pair (K and D) using one RSI length and one Stoch length. It reacts quickly and is meant for timing.
Y (slow) is a structure Stoch RSI pair (K and D) built by averaging 28 Stoch-RSI calculations across multiple lookback lengths, then smoothing the result. It’s meant to show broader, higher-order momentum rather than the latest swing.
For Y’s lookback set, you can choose:
Fib: a predefined “fib-like” 28-length ladder,
14 + (i * 10): a linear ladder of 28 lengths,
Custom: 28 user slots with individual on/off toggles.
In Style, you can independently control each line’s color, thickness, and plot style (line/step/line break) for X-K, X-D, Y-K, and Y-D. It also adds five optional horizontal reference levels at 0, 20, 50, 80, 100 (0/100 solid, 20/50/80 dotted).
Simple RSI Strategy - Rule Based Higher Timeframe Trading
HOW IT WORKS
With the default settings, the strategy buys when RSI reaches 30 and closes when RSI reaches 40 .
That’s it.
A simple, rule-based mean reversion strategy designed for higher timeframes , where market noise is lower and trading becomes easier to manage.
Core logic:
Long when RSI moves into oversold territory
Exit when RSI mean-reverts upward
Optional short trades from overbought levels
One position at a time (no pyramiding)
No filters.
No discretion.
Just clear, testable rules.
MARKETS & TIMEFRAMES
This strategy is intended for:
Indices (Nasdaq, S&P 500, DAX, etc.)
Liquid futures and CFDs
Higher timeframes: 2H, 4H and Daily
The published example is Nasdaq (NDX) on the 2-hour timeframe .
Higher timeframes are strongly recommended.
HOW TO USE IT
Apply the strategy on a higher timeframe
Adjust RSI levels per market if needed
Use TradingView alerts to avoid constant screen-watching
Focus on execution, risk control, and consistency
This strategy is meant to be a building block , not a complete trading business on its own.
For long-term consistency, it works best when combined with other uncorrelated, rule-based systems.
IMPORTANT
This is not financial advice
All results are historical and not indicative of future performance
Always forward-test and apply proper risk management
For additional notes, setups and related systems, visit my TradingView profile page .
VSA Simple VolumeThe VSA Volume Indicator is especially useful for understanding institutional activity and improving decision-making by confirming trends or spotting early signs of market manipulation.
Asset Volatility Heatmap [SeerQuant]Asset Volatility Heatmap (AVH)
AVH is a cross-sectional volatility dashboard that ranks up to 30 assets and visualizes regime shifts as a time-series heatmap.
It computes annualized historical volatility (%) on a fixed 1D basis, then maps each asset’s volatility into a configurable color spectrum for fast, intuitive scanning of risk conditions across cryptocurrencies.
⚙️ How It Works
1. Daily, Annualized Historical Volatility
Each asset is measured on a fixed 1D timeframe (independent of your chart timeframe). Volatility is annualized and expressed in percentage terms. The user can choose between 1 of 4 volatility estimators: Close-Close (log returns stdev), Parkinson (H/L), Garman-Klass or Rogers-Satchell.
2. Heatmap
A heatmap is plotted on the lower window (sorting is turned on by default). Each row represents a rank position. (Rank #1 highest vol ... Rank #30 lowest vol). This means that tokens will move between rows over time as their volatility changes. The asset labels show the current token sitting in each rank bucket. This setting can be turned off for more of a "random" look.
3. Color Scaling
The user can select how the color range is normalized for visualization.
n = (v - scaleMin) / (scaleMax - scaleMin)
Cross-Section: Scales colors using the current bar’s cross-sectional min/max across the asset list.
Rolling: Scales colors using a lookback window of cross-sectional ranges, so today’s values are judged relative to recent volatility history.
Fixed: Uses your chosen Fixed Scale Min / Max for consistent benchmarking across time.
4. Contrast Control
The Color Contrast control option changes how aggressively the palette emphasizes extremes (useful for making “risk spikes” pop vs keeping gradients smooth).
5. Summary Table + Composite Read
The table highlights the highest vol / lowest vol token, along with average / median volatility, and a simple regime read (low / medium / high cross-sectional volatility).
✨ How to Use (Practical Reads)
Spot risk-on / risk-off transitions: When the heatmap “heats up” broadly (more hot colors across ranks), cross-sectional volatility is expanding (higher dispersion / risk).
Identify which names are driving the narrative: With sorting ON, the top ranks show which assets are currently the volatility leaders — often where attention, liquidity, and positioning stress is concentrated.
Use it as a regime overlay: Low/steady colors across most ranks tends to align with calmer conditions; sharp bright bursts signal volatility events.
✨ Customizable Settings
1. Assets
30 symbol inputs (defaults to crypto, but works across markets)
2. Calculation Settings
Length (lookback)
Volatility Estimator (Close-Close / Parkinson / GK / RS)
3. Style Settings
Color Scheme (SeerQuant / Viridis / Plasma / Magma / Turbo / Red-Blue)
Color Scaling (Cross-Section / Rolling / Fixed)
Scaling Lookback (for Rolling)
Fixed Scale Min / Max (for Fixed)
Color Contrast (emphasize extremes vs smooth gradients)
Sort Heatmap (High → Low)
Gradient Legend toggle
Focus Mode (highlights the chart symbol if included)
Ticker Label Right Padding
🚀 Features & Benefits
Cross-sectional volatility at a glance (dispersion/risk conditions)
Sortable rank heatmap for tracking “who’s hot” in volatility
Multiple estimators for different volatility philosophies
Flexible normalization (current cross-section, rolling context, or fixed benchmarks)
Clean legend + summary stats for quick context
📌 Notes
Sorting changes which token appears in each row over time (rows are rank buckets).
Volatility is computed on 1D even if your chart is lower/higher timeframe.
📜 Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always consult a licensed financial advisor before making trading decisions. Use at your own risk.
Dynamic ATR-based Renko Overlay - Non repaintingDaily ATR-Based Renko Overlay
Overview
This Pine Script v5 indicator creates a dynamic Renko overlay on your time-based charts (optimized for 1-minute timeframes), using the previous period's ATR from a user-specified higher timeframe (default: 1-hour) to determine brick sizes. Unlike traditional Renko charts, this is an overlay that draws Renko bricks directly on top of your existing candles, allowing you to combine the noise-filtering power of Renko with the full features of time-based charts.
It's designed for traders who want Renko's trend-clarity benefits without switching chart types, especially useful for intraday trading in volatile markets like forex, stocks, or crypto.
Key Features
- Adaptive Brick Sizing: Brick size is calculated as a percentage (default 40%) of the previous period's ATR (Average True Range, default length 14) from the selected higher timeframe (default: 1-hour). This makes bricks volatility-adjusted—larger in high-vol periods to reduce noise, smaller in low-vol for more detail.
- Periodic Recalculation: Resets brick size at the start of each new period based on the user-specified reset timeframe (default: daily), using the prior period's ATR from the chosen timeframe. This ensures relevance without unwanted disruptions.
- Traditional Renko Logic: Uses 1-box reversal (a full brick against the trend to reverse). Bricks form based on closing prices, ignoring time and minor fluctuations.
- Visual Style: Stepped lines with green (up) and red (down) fills for a box-like appearance. Semi-transparent for easy overlay on candles.
- Customizable Inputs:
- ATR Length: Adjust the ATR period (default: 14).
- Percentage of ATR: Fine-tune brick sensitivity (default: 0.4 or 40%; range 0-1).
- ATR Timeframe: Specify the timeframe for ATR calculation (default: "60" for 1-hour; enter as a string like "240" for 4-hour, "D" for daily, etc.).
- Reset Timeframe: Specify the period for recalculating the brick size (default: "D" for daily; enter as a string like "W" for weekly, "M" for monthly, etc.).
How It Works
1. Fetches ATR from the user-specified timeframe via `request.security` for higher-timeframe volatility data.
2. On new periods based on the reset timeframe (or first load), sets brick size to `percent * ATR_HTF`.
3. Tracks Renko "close" and "previous close" to calculate bricks:
- Upward moves add green bricks in multiples of the size.
- Downward moves add red bricks.
- Reversals require a full brick against the direction.
4. Plots and fills create the overlay, updating on each 1-min bar close.
Add it to a 1-minute chart for best results—bricks will adapt periodically while you retain full candle visibility.
Why This Indicator is Helpful
TradingView's native Renko charts are powerful but come with limitations that can frustrate serious traders:
- No Bar Replay: Native Renko doesn't support TradingView's bar replay feature, making it hard to simulate historical trading sessions.
- Inaccurate/Repainting Strategy Testing: Strategies on native Renko can repaint or lack precision due to the non-time-based nature, leading to unreliable backtests.
- Limited Data History: Fast Renko timeframes (e.g., small bricks) often load very little historical data, restricting long-term analysis.
This overlay solves these by building Renko on a time-based chart:
- Full Bar Replay Support: Replay sessions as usual on your 1-min chart—the Renko follows along.
- Accurate, Non-Repainting Testing: Test strategies on the underlying time chart without repainting issues, as Renko is derived from closes.
- Unlimited Data Depth: Access TradingView's full historical data for 1-min charts (up to years of bars), not limited by Renko's data constraints.
- Hybrid Analysis: Overlay Renko on candles to spot trends while using volume, indicators (e.g., RSI, MAs), or drawing tools that don't work well on native Renko.
It's a game-changer for trend-following, breakout strategies, or filtering noise in short-term trades. No more switching charts—get the best of both worlds!
Usage Tips
- Best on 1-min charts for intraday precision, but experiment with others.
- Tune the percentage lower (e.g., 0.3) for more bricks/sensitivity, higher (e.g., 0.5) for fewer/false-signal reduction.
- Adjust the ATR timeframe to match your strategy—e.g., "240" for longer-term volatility or "15" for shorter.
- Customize the reset timeframe for different recalculation frequencies—e.g., "W" for weekly resets to capture broader market shifts, or "240" for every 4 hours.
- Combine with alerts: right now I am experimenting with 90 period EMA and the Renko brick pullbacks to find some EDGE
If you find this useful, give it a thumbs up or share your tweaks in the comments. Feedback welcome—happy trading! 🚀
Daily ATR (Shown on All Timeframes)Daily ATR (Shown on All Timeframes) displays the Daily timeframe ATR on any chart you’re viewing, so you always know the current day’s average range without switching timeframes.
True Daily ATR (not chart ATR): The script pulls ATR from the Daily chart using request.security() and shows that value on every timeframe.
On-chart table (top-right): A clean 2-row table shows:
The label: Daily ATR (Length)
The ATR value, with an optional ATR-as-% of price readout.
Custom display controls:
ATR Length input (default 14)
Toggle to show ATR % of current price
Toggle to show/hide the table
Choose table text color
Choose table text size (Tiny → Huge)
Data Window output: The Daily ATR value is also plotted invisibly so it appears in TradingView’s Data Window for quick reference.
This is useful for gauging daily volatility, setting risk/position sizing, and comparing intraday movement to the stock’s typical daily range.
Daily ATR (Shown on All Timeframes)Daily ATR (Shown on All Timeframes) displays the Daily timeframe ATR on any chart you’re viewing, so you always know the current day’s average range without switching timeframes.
True Daily ATR (not chart ATR): The script pulls ATR from the Daily chart using request.security() and shows that value on every timeframe.
On-chart table (top-right): A clean 2-row table shows:
The label: Daily ATR (Length)
The ATR value, with an optional ATR-as-% of price readout.
Custom display controls:
ATR Length input (default 14)
Toggle to show ATR % of current price
Toggle to show/hide the table
Choose table text color
Choose table text size (Tiny → Huge)
Data Window output: The Daily ATR value is also plotted invisibly so it appears in TradingView’s Data Window for quick reference.
This is useful for gauging daily volatility, setting risk/position sizing, and comparing intraday movement to the stock’s typical daily range.
Intermarket Divergence (Futures vs Equity)Intermarket Divergence (Futures vs Equity)
This indicator detects intermarket divergence between a traded instrument (futures, CFD, or spot) and a related equity or ETF.
It highlights moments where price and its underlying market drivers disagree, often appearing before reversals or expansions.
🎯 What It Shows
Bullish divergence:
Price makes a lower low while the equity makes a higher low
Bearish divergence:
Price makes a higher high while the equity makes a lower high
Based on swing pivots, not candle noise
Designed for intraday context, not mechanical entries
✅ Recommended Use
XAUUSD (Gold) → GDX (default)
XAGUSD (Silver) → SIL
USOIL / WTI → XLE
(These guidelines are included directly in the indicator settings.)
🧭 How to Use
Apply on 15m–30m
Look for signals near key levels (PDH/PDL, Asia high/low, HTF structure)
Use price action for entries
Divergence is context, not a signal.
⚠️ Notes
Non-repainting
Signals are selective by design
Best during London & New York sessions
Volatility RadarVolatility Radar: Script Summary
The **Volatility Radar** is a real-time TradingView dashboard designed to decode dealer positioning by fusing structural VIX analysis with options flow. Instead of treating volatility as a static number, it categorizes the market into distinct regimes—supportive "Green Rooms," noisy "Grey Channels," or dangerous "Red Rooms"—to determine whether options flow represents genuine momentum or a dealer hedging trap.
Recent upgrades have transformed the script from a passive monitor into an active threat detection system. It now features a **Velocity Check** that instantly overrides standard confirmation timers during sudden VIX spikes, **Gatekeeper Logic** to identify regime breakout events, and a **Dealer Reality Check** that flags "Trap Risks" when call buying occurs directly into high-velocity resistance.
### Detailed Mechanics: Velocity & Gatekeeper Logic
**The Velocity Check (The "Speed Trap")**
Standard indicators often lag because they wait for candle closes or fixed time intervals (e.g., a 10-minute confirmation rule). The Velocity Check bypasses this by monitoring the *rate of change* in the VIX over a rolling 5-bar window. If the VIX moves more than **0.40 points** in this short timeframe, the script triggers an "Immediate Override." This acknowledges that high-velocity moves—whether spikes or crushes—force dealers to re-hedge instantly, making the standard wait times dangerous. If the velocity threshold is breached, the script flashes a lightning bolt icon (`⚡`) and treats the move as confirmed immediately.
**The Gatekeeper Check (The "Zone Logic")**
Rather than viewing volatility as a simple high/low binary, the Gatekeeper logic defines a "Neutral Zone" (Grey Channel) bounded by specific "Gates" (e.g., 14.78 and 15.26).
* **Inside the Gates:** The market is considered to be in "Chop/Noise," where directional signals are unreliable and often result in whipsaws.
* **Crossing the Gates:** The logic specifically watches for *breakout events*. A move from the Grey Channel into the "Red Room" (>Bear Chop) signals a **Bearish Breakout**, immediately flipping the script's interpretation of "Buying Pressure" from bullish momentum to a "Trap Risk" (dealers selling into resistance). Conversely, a breakdown into the "Green Room" (
Rumiancev Reaction ZonesRumiancev Reaction Zones
Rumiancev Reaction Zones (RRZ) is a clean, non-signal overlay that highlights potential reaction areas — places where price often slows down, bounces, or becomes stretched relative to the current market range.
RRZ is NOT a trading bot. It does not provide guaranteed entries/exits. Use it as a context tool alongside your own confirmation (structure, trend bias, momentum/volume, etc.).
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WHAT IS DRAWN ON THE CHART
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🔵 Blue Zone • Buy Area (Filled Band)
A lower reaction band (“discount / downside stretch”).
• Upper edge: Blue Zone • Buy Area (blue line)
• Lower edge: Blue Zone • Lower Band (hidden band edge)
When price enters this band, reactions become more likely (bounces, stabilization, reclaim moves).
🟠 Orange Zone • Sell Area (Filled Band)
An upper reaction band (“stretch / upside extension”).
• Lower edge: Orange Zone • Sell Area (orange line)
• Upper edge: Orange Zone • Upper Band (hidden band edge)
When price reaches this band, pauses, pullbacks, or distribution can appear.
⚪ Guide Line (Gray)
A neutral reference line inside the structure. Helps to judge whether price is closer to “discount” (Blue side) or “stretch” (Orange side).
🟢 Deep Line (Green) — Aggressive Context (NOT a zone)
A deeper downside reference line (green), not a filled band.
If price reaches it, conditions are typically more volatile and risk is higher. Treat it as a high-risk context line, not an automatic entry.
🔴 Orange Extreme (Red) — High Extension (NOT a zone)
A high-extension reference line above the Orange Zone. Often used as a strong risk-reduction context after extended upside moves.
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HOW TO USE RRZ (PRACTICAL FRAMEWORK)
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1) Blue Zone approach (potential entries)
• When price enters the Blue Zone , wait for confirmation first (rejection wick, reclaim back above the zone edge, local structure holding).
• Consider scaling in gradually rather than entering full size at once.
• If price continues deeper toward the green Deep Line , treat it as higher risk and act only if your plan and risk limits allow it.
2) Orange Zone approach (potential exits)
• When price reaches the Orange Zone , many traders consider partial risk reduction (scale out, protect profit, tighten stops).
• Near the red Orange Extreme line, many traders consider stronger risk reduction (up to closing most/all), especially after impulsive runs.
IMPORTANT: RRZ marks areas , not entries. Always define invalidation (stop/idea failure point) and position size before acting.
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CONFIRMATION IDEAS (SIMPLE)
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• Rejection wicks / reclaim back above a zone edge
• Break & retest of local structure
• Momentum/volume shift you personally trust
• Alignment with higher-timeframe direction
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SETTINGS
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• Depth → sensitivity (lower = more reactive, higher = steadier)
• Smoothness → adaptation speed (lower = faster, higher = smoother)
• Zone Width → thickness of the Blue/Orange fills (visual width)
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EXAMPLES (CHART IMAGES)
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Example 1 — Orange Zone reaction (Daily)
Price pushes into the Orange Zone (stretch area), then cools off and rotates lower. RRZ helps visualize this as a place to watch for rejection or profit-taking context.
Example 2 — Repeated cycles (Daily)
Multiple cycles where touches into the Orange Zone often coincide with pauses/pullbacks, while dips into the Blue Zone tend to act as reaction areas during corrections.
Example 3 — Blue Zone reaction after a sell-off (4H)
A sharp move pushes price into the Blue Zone , followed by stabilization and reaction. The Orange Zone remains overhead as the next upside stretch region to monitor.
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NOTES
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• Zones are dynamic and update as new market data forms.
• No future-looking data (“lookahead”) is used.
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DISCLAIMER
────────────────────────────────────────
This script is for educational and informational purposes only and is not financial advice. Trading involves risk. No indicator can guarantee results.
LiquidityPulse MTF Intrabar Micro-Structure Absorption DetectorLiquidityPulse MTF Intrabar Micro-Structure Absorption Detector
Non-repainting: Markers appear on bar close and do not change.
Important (if you can’t see any markers)
This indicator measures intrabar micro-structure and it can use seconds-based micro data on lower timeframes.
If you load it and don’t see anything:
Go to 15m or higher, or
In settings, change Micro feed (inside HTF bar) from Auto to 1m / 5m / 15m.
Auto will often choose a “micro” feed that’s very small when your HTF is small, which can affect what you see.
What this indicator does
This script is designed to highlight absorption-like conditions by analysing what happens inside each higher-timeframe (HTF) candle — not just the candle’s OHLC.
It looks for candles where:
price moves a lot internally (high intrabar activity),
the candle structure shows churn / rejection (wick dominates body),
and participation is elevated (relative high volume).
When those conditions align, the indicator prints a marker line at the wick extreme:
LW (Lower-wick marker) = printed at the candle’s low
UW (Upper-wick marker) = printed at the candle’s high
Each marker is then extended to the right (so it can be treated like a potential level).
Image shows a wick-dominant candle with an absorption marker: Markers appear when price shows strong intrabar movement, a wick-dominant candle structure, and elevated participation — a combination often associated with absorption-like behaviour.
How it works
A marker is created only when all three filters pass on a confirmed candle close:
1) Intrabar micro-speed (internal activity)
The script pulls intrabar closes from a lower timeframe (“micro feed”) and sums the absolute internal price changes inside the HTF candle.
It then converts this to a Z-score and checks it against the Speed-z threshold.
Higher threshold = fewer, stronger events.
2) Wick vs body (churn / rejection structure)
This measures how the HTF candle’s internal range compares to its net close-to-open movement using:
Churn ratio = (HTF range) / (HTF body)
If the candle has a large range but a relatively small body, it indicates that price moved extensively during the candle but made limited net progress by the close — a structure often associated with active two-sided participation and absorption-like behaviour.
3) Relative HTF volume (participation filter)
The script also Z-scores HTF volume and requires it to exceed the Volume z-score threshold.
This helps filter out candles that show apparent activity but occur on relatively low participation.
Multi-timeframe + micro-structure analysis: Image shows a 15 minute chart marker on the 1 minute timeframe. The indicator can analyse higher-timeframe candles (15 minute) while using lower-timeframe micro data inside each bar (1 minute). This allows absorption-style markers to be plotted with higher-timeframe context and intrabar detail.
Composite Intensity
When a marker triggers, the script calculates a Composite Intensity number (CI):
It’s a combined score based on how strongly each of the three conditions exceeded its threshold.
Higher CI = stronger absorption-style event
Higher CI = brighter chart marker
The table shows:
HTF and Micro timeframes being used
the last marker type (LW or UW)
the last CI value
Micro feed & multi-timeframe behaviour
This indicator always works as a two-layer system:
HTF candle (context) → the candle you’re analysing
Micro feed (inside HTF bar) → the intrabar data used to measure micro-speed
Higher-TF source
Chart timeframe = uses your chart timeframe as HTF
Manual = choose any HTF (example: chart = 1m, HTF = 15m → prints 15m absorption markers onto a 1m chart)
Micro feed options
Auto (recommended) picks a sensible micro feed based on HTF
Or choose 1s / 1m / 5m / 15m manually for performance/clarity
HTF direction filter (optional)
When enabled:
LW markers only print when the HTF candle closes bullish
UW markers only print when the HTF candle closes bearish
This is optional and is designed to reduce noise by aligning markers with the directional bias of the higher-timeframe candle.
Traders can use the absorption markers to:
Identify potential areas of interest where price showed unusually high intrabar activity but limited net progress by the close.
Mark reference levels where price may react again later, reflecting prior elevated participation and extensive intrabar movement areas.
Add structural context to existing analysis such as trend structure, support/resistance, session highs/lows, or other volume-based tools.
Compare behaviour across timeframes, by observing how absorption-style events on a higher timeframe align with lower-timeframe price action.
Image shows price reacting to a previous absorption markers level (Lines/ levels can be extended in the settings): Extended LW / UW markers can be observed as areas of prior absorption-like activity. Traders may watch how price behaves around these levels (reaction, acceptance, or rejection) alongside their own structure, liquidity, or risk management tools.
Key settings (what they change)
Higher-TF source / Higher-TF bar (manual): which candle timeframe is analysed
Micro feed (inside HTF bar): what intrabar resolution is used to calculate micro-speed
Speed-z threshold: how unusual intrabar activity must be
Wick/Body threshold: how large the candle’s total range must be compared to its body
Volume z-score threshold: how elevated HTF volume must be
Z-score look-back: how far back the indicator normalises speed/volume
Line extension (bars): raise if you want markers to behave more like extended levels
Max markers: how many markers remain on the chart at once
Alerts
Alerts trigger on candle close when an absorption marker is detected.
Disclaimer
This indicator does not measure true order flow or the full limit order book. It uses intrabar price activity, candle structure, and relative participation as interpretive tools to highlight absorption-like behaviour. It is not a buy/sell system, and all signals should be used with traders own confirmation and risk management.
Breakout Open Range (ORB) v3.3This is an advanced version of the classic Open Range Breakout (ORB) strategy, designed for precision and ease of use. It automatically identifies the initial volatility range of a trading session (e.g., London or New York Open) and projects clear Breakout and Take Profit levels.
v3.3 Update: Optimized for a cleaner chart and easier configuration.
KEY FEATURES:
1. User-Friendly Time Input:
No more typing complicated session strings! Now you can simply select the Start Hour/Minute and End Hour/Minute using easy number fields in the settings.
2. Clean Chart Logic (New):
The indicator now automatically resets all lines at the start of a new day. The chart remains completely empty until your defined start time (e.g., 15:30), preventing old levels from cluttering the pre-market view.
3. 1:1 Take Profit:
Automatically calculates and plots a Take Profit level based on a 1:1 Risk/Reward ratio relative to the range size.
*Note:* TP lines appear only AFTER the range formation is complete to maintain visual clarity.
4. Dynamic Price Labels:
Displays exact price levels on the right side of the chart for:
- Entry (Long/Short)
- Stop Loss positions
- Take Profit targets
- Total Range Size
HOW IT WORKS:
1. Define your Open Range time in the settings (e.g., 15:30 to 16:15).
2. The script draws the High and Low of this period.
3. Wait for a candle to close outside the range:
- Breakout Above = Long Signal (Target: Blue Upper Line)
- Breakout Below = Short Signal (Target: Blue Lower Line)
SETTINGS:
- Timezone & Session Hours (simple number inputs)
- Toggle visibility for Lines, Background, TP, and Labels
- Fully customizable colors
Perfect for day traders looking for an objective, automated way to trade the opening bell volatility.
