IQ Trend Beams [TradingIQ]🔹 OVERVIEW
IQ Trend Beams is a trend assistant that draws your trendlines the way a disciplined chartist would - and then holds them accountable. It maintains two channels, support and resistance , each always showing one working line. A line is born forming : it moves and re-shapes freely, polished every bar by a perceptual score toward the line a skilled trader would actually draw. When its geometry settles and it has earned enough tangency credit, it locks - and from that moment the ink is frozen forever; it never moves again. Locked ink extends until break evidence fires, then it is broken : restyled but never relocated, holding the screen as history until its successor locks.
Riding each live beam is its own forecast ; a calibration band, a reach profile, and ghost levels, all built from the volume that has actually traded around that line.
This is an honest visualization and modeling tool , not a signal service. It draws structure clearly and states its own confidence out loud; it is not a validated edge or a promise of profit. Read the limitations section - it is not window dressing.
🔹 THE TWO CHANNELS - AN AUDITED PROMISE
Most trendline tools quietly redraw the past so the line always looks right in hindsight. Trend Beams refuses to. A line lives through three visible states:
• Forming (dotted) - the assistant sketching. It is free to move and re-fit while it hunts for the right geometry. This is the only state in which a support/resistance line moves, and it is dotted precisely so you can tell a guess from a commitment.
• Locked (solid) - the geometry has stilled and earned its tangency credit, so the line is frozen . It will never move again. A locked beam is a promise the tool has to keep in public.
• Broken (restyled) - break evidence fired. The ink is re-styled to show it failed, but it is never relocated ; it holds its original slope as an honest record and, if you keep history on, dims into the background once its successor locks.
Because a locked line cannot move, what you saw at lock time is what you keep. This is the core design commitment of the tool.
Two rails, either direction by design. Support is the lower rail, fit to the swing lows on the underside of price; resistance is the upper rail, fit to the swing highs above it. Neither is locked to a single slope: in a falling market the support rail angles down with the lows (the floor of the down-channel), and in a rally the resistance rail angles up with the highs (the ceiling of the up-channel). That is deliberate. A tool that forces support to only ever point up would go blind to the lower boundary of a downtrend - and miss exactly the moves that matter. Trend Beams instead always draws both boundaries of the channel price is actually in , so a strong move is framed on both sides rather than half-missed. If you prefer to read it the classical way, follow the rail that agrees with the trend and treat the other as the opposite wall of the same channel.
🔸 HOW A LINE EARNS ITS LOCK
While forming, each line is scored every bar by a perceptual fit , a running measure of how well its geometry matches what a careful trader would draw against the recent swing structure, blended with a one-pole toward its fitted slope so it settles rather than twitches. A lock is granted only when the geometry has gone still for long enough, the line has accumulated real tangency credit (genuine touches, not a single graze), and it spans a minimum bar count - and it is refused outright if it would invert the channel. The Mode dial sets how much evidence this takes.
🔹 THE AUDIT BADGE
Locked ink can carry a small measurement badge that reports, in plain terms, how the line is actually holding up:
• Wick-through - recent piercing of the line, exponentially weighted, measured against the tool's 10% design target . A well-behaved line lets price kiss it, not knife through it.
• Survival probability - the current modeled odds that the line is still valid.
• Maturity - how far through its estimated total run the move is, so a young trend reads differently from an exhausted one.
The badge is the tool grading its own work on the chart, not a trade instruction.
🔸 THE FORECAST - EACH BEAM READS ITS OWN VOLUME
Every live beam carries its own forecast, built entirely from the volume that has traded around that line. Trend Beams bins the intrabar volume by its distance from the beam, smooths it into a continuous density (a kernel-density estimate), and renders three things that ride the line:
• Calibration band - translucent ribbons hugging the beam, one per density bin, showing where the trend has held its volume. Strength is encoded as colour vibrancy at a constant perceptual lightness (the Oklab principle - a dense core reads vivid, the thin tails fade), so nothing is made brighter or darker than its weight warrants.
• Reach profile - a smooth filled contour fanning into the future margin, where each level's forward extent is its density times the trend's estimated remaining length . It answers, at a glance: if this trend keeps going, how far - and around which prices - does its own volume say it reaches?
• Ghost levels - dashed lines at the distribution's densest peaks, riding parallel to the beam, marking the prices this trend keeps returning to.
The forecast attaches only to a beam's currently-visible live element - its forming sketch, or its locked ink - and keeps no history . It is a read of the present trend, refreshed at the live edge, not a replay of the past.
🔸 THE ENGINE DIALS
• Mode - the tempo. Fast locks, breaks and re-forms sooner (short swings); Slow demands more evidence and holds through more noise (long moves); Medium is the balanced reference.
• Precision - how much data the engine reads: the perceptual fit window and the intrabar sample rate. Higher tiers resolve finer structure at more load. Sampling is timeframe-aware and never drops below one minute.
🔹 LAYERS, COLOUR & LEGIBILITY
Every layer is a toggle - forming lines, broken history, audit badges, and the forecast - so you can run it as a bare two-line channel or a fully dressed read. Colours come from three clean anchors: Support , Resistance , and Chrome (badges and neutral furniture). The whole translucent forecast - band, profile, and ghost levels - is coloured in the Oklab perceptual space, so strength shows up as vibrancy at a constant lightness rather than as glare, and a single Contrast dial scales the entire forecast from a whisper to bold.
🔸 HOW TO READ IT
• Treat a forming (dotted) line as a hypothesis and a locked (solid) line as a committed level - the tool is telling you which is which on purpose.
• Watch the audit badge : rising wick-through and falling survival probability say a locked line is wearing out.
• Read a broken line as a failed level that still marks where the structure gave way.
• Use each beam's band to see where its trend has held its volume, its reach profile for how far the trend's own volume says it can run, and its ghost levels for the prices it keeps returning to.
🔹 INPUTS
• Trend Engine - Mode (tempo) and Precision (data depth).
• Layers - show forming lines, broken history, audit badges, and the forecast.
• Colors - Support, Resistance, and Chrome anchors, plus a Contrast control for the translucent forecast.
• Channels - enable the support and/or resistance side independently.
🔸 LIMITATIONS AND HONEST NOTES
• This is a drawing and modeling assistant , not a validated strategy. It makes no performance claim and no edge claim . Nothing here is financial, investment or trading advice.
• Locked and broken lines do not repaint - once a line locks, its geometry is frozen. Forming lines move by design (they are the live sketch, and are dotted to say so), and each beam's forecast (band, profile, ghost levels) refreshes at the live edge as new volume arrives and attaches only to the current live element. These are live reads, on purpose; none of them rewrites confirmed history.
• Survival probability, maturity, remaining length and the reach profile are model estimates from the trend's own statistics - projections, not guarantees, and not forecasts of price.
• Intrabar sampling is subject to your plan's intrabar data limits ; higher Precision tiers read more intrabar data.
• Drawing budgets are finite. The tool caps its lines, labels and polylines internally, but very long histories with everything enabled push against TradingView's per-script drawing limits - trim the layers you don't need.
Indicatore
Indicatore
Chart Patterns [FEELS]Classical chart patterns, drawn only after price confirms them, each one carrying a running count of how often that pattern has reached its measured target on this chart.
No pattern appears until its neckline breaks. Once drawn, it never moves.
FEATURES
- Four classical reversal patterns: Double Top, Double Bottom, Head & Shoulders, Inverse Head & Shoulders
- Confirmed-only: a pattern is drawn after its neckline breaks, not while it is still forming
- Non-repaint: once drawn, the geometry never changes
- Measured target and neckline plotted for every pattern
- Live per-pattern hit-rate table: how often each type reached its target on the current chart
- Target-reached and invalidated outcomes marked on the chart
- ATR-based tolerances that adapt to each symbol
- Close or wick neckline confirmation, optional weaker-second-peak filter
- Four alerts, fully adjustable colors, labels and text
WHAT IT DETECTS
Four of the most widely taught reversal patterns: Double Top, Double Bottom, Head & Shoulders, and Inverse Head & Shoulders. Each is built from confirmed swing pivots, so the shape on the chart is the same shape a trader would draw by hand.
HOW IT WORKS
The engine keeps a zigzag of confirmed swing highs and lows and checks the most recent pivots against each pattern template: two equal tops over a shared low for a Double Top, a higher head between two level shoulders for Head & Shoulders, and so on. A candidate is not shown yet. It is only drawn once price breaks through the neckline, which is the point at which the pattern is considered complete. From that bar the geometry is locked.
- Neckline: the line the pattern breaks. Horizontal for double tops and bottoms, sloped through the two inner pivots between the shoulders and the head for Head & Shoulders and its inverse.
- Measured target: the pattern height projected from the break, drawn as a dotted line. This is the standard textbook objective, not a forecast.
- Outcome tracking: after a pattern confirms, the script follows it for a set number of bars to see whether price reached the measured target, closed back past the pattern, or did neither in time. All three outcomes feed the table.
- Hit-rate table: for every pattern type it shows how many confirmed patterns reached their target, out of every pattern that has finished tracking, as a running count on the current symbol and timeframe. Head & Shoulders reaching target less often than a Double Bottom is information, not a defect.
HOW TO READ IT
1. Wait for the break. A shape only appears after the neckline gives way, so what you see is a completed pattern, not a guess about one still forming.
2. Use the table as context. A pattern type that has historically reached its target often on this chart carries more weight than one that rarely has. The sample size is shown next to the percentage so you can judge how much to trust it.
3. The measured target is the reference objective. A pattern is only marked invalidated when price closes back past its own extreme, the high of a double top or the right shoulder of a head and shoulders, so the invalidation mark sits at that level rather than at the neckline. How you act on either is your decision.
ORIGINALITY
This script waits for the neckline break before drawing anything, locks the geometry once a pattern is drawn, and keeps a live per-pattern tally of how each one resolved on the chart you are looking at. The idea is to combine the shape a trader would draw by hand with a running record of what happened after that shape completed, on this exact symbol and timeframe. The zigzag, the pattern templates, the neckline construction and the outcome tracking are written from scratch for this script.
HONESTY
- A swing pivot confirms only after the Swing size number of bars, so a pattern appears on the chart once its break is confirmed, and its earlier points are drawn back to where they occurred. On a bar replay this looks like a shape appearing into the past. That is the cost of the no-repaint rule, not a glitch. After a pattern is drawn its position never changes, and the break is evaluated on bar close.
- The hit-rate table is a historical count on the current symbol and timeframe. Reaching target means price hit the measured objective within the tracking window; a pattern that neither reached target nor closed back past its extreme within that window counts against the rate, not as a skipped sample. Only patterns that reached target or invalidated print a mark on the chart, so a timed-out pattern is counted in the table but not tagged, and the visible marks are fewer than the table total. It describes what happened after past patterns, it does not predict future ones, and a small sample can move a lot. It is not a performance claim.
- Tolerances are ATR-based, so the definition of equal tops or a clean break adapts to each symbol's volatility instead of a fixed percentage.
- The tool is most useful on liquid symbols and on intraday-to-daily timeframes, where enough clean swings form. On very long histories only the most recent patterns stay drawn to keep the chart readable.
ALERTS
Bearish pattern confirmed · Bullish pattern confirmed · Target reached · Pattern invalidated.
SETTINGS
Every input has a tooltip. The main ones: "Swing size" sets how many bars on each side define a swing, "Neckline break" chooses close or wick confirmation, "Second peak / bottom" can require the classic weaker-second-peak form, "Patterns kept" caps how many stay on the chart, and the table, colors, outcome text and both text sizes are all adjustable.
This is a descriptive tool for reading classical chart patterns. It is not financial advice and does not predict price. Indicatore
Day Trade Setup - CRT Session Range ModelDay Trade Setup - CRT Session Range Model
Day Trade Setup - CRT Session Range Model is a session-based market framework designed to identify important intraday reference ranges and combine them with liquidity sweeps, M15 imbalance gaps, market structure levels, and supply or demand zones.
The script is designed to help traders organize intraday price action around selected H1 session ranges. Instead of displaying isolated signals, it creates a structured map of the current setup, including the range high, range low, 50% midpoint, nearby liquidity events, and relevant M15 reference areas.
Core Concept
The indicator analyses predefined H1 trading periods and selects the most significant candle within each session window using a weighted candle score.
The score considers:
Candle body size
Upper and lower wick size
User-defined body weighting
User-defined wick weighting
The selected candle becomes the active session range. Its high, low, and 50% midpoint are then projected across the chart as reference levels.
The most recent valid session setup automatically becomes the active model.
Session Range Models
The indicator supports three session groups:
Dawn Range
The Dawn Range evaluates the H1 candles formed between 1:00 AM and 5:00 AM.
The script compares the five candles and selects the candle with the highest weighted body-and-wick score as the active range.
Morning Range
The Morning Range compares the 8:00 AM and 9:00 AM H1 candles.
The candle with the stronger weighted score becomes the active range.
Evening Range
The Evening Range compares the 8:00 PM and 9:00 PM H1 candles.
The stronger candle is selected as the active range.
Users can display one session model individually or enable all available sessions.
Active Range Display
When a new setup is selected, the indicator displays:
Session Range High
Session Range Low
50% midpoint
Session and hour label
Continuously extending reference lines
The 50% level helps divide the selected range into upper and lower halves, providing a visual reference for premium and discount areas within the setup.
The script replaces the previous active range when a newer valid session setup is confirmed.
Liquidity Sweep Detection
The indicator includes an optional liquidity sweep module that monitors price interaction with the active range high and low.
A potential bearish liquidity sweep may be identified when price:
Trades above the active range high
Returns and closes below the range high
Meets the selected volatility, body, and upper-wick requirements
A potential bullish liquidity sweep may be identified when price:
Trades below the active range low
Returns and closes above the range low
Meets the selected volatility, body, and lower-wick requirements
The liquidity sweep filter also includes a cooldown period to reduce repeated labels appearing within a short number of bars.
These markers represent potential liquidity-rejection events and are not automatic entry signals.
M15 Imbalance Gap
The script can locate a recent bullish or bearish M15 imbalance gap that formed before the active session setup.
The imbalance module:
Searches the latest M15 gaps
Considers only gaps formed before the active setup
Supports bullish, bearish, or both gap types
Filters gaps using ATR-based minimum size
Can restrict results to gaps near the session range
Locks the selected gap when a new setup appears
Displays the gap boundaries and midpoint
Only a qualifying gap whose midpoint is outside the active session range is displayed.
This helps traders identify nearby price imbalances that may act as reaction areas or potential liquidity objectives.
M15 Structure Levels
The indicator identifies previously confirmed M15 swing highs and swing lows using pivot-based market structure.
For each new session setup, the script searches for:
A confirmed structure high above the session range
A confirmed structure low below the session range
Only structure points that formed before the active setup are considered.
The selected levels are extended across the chart and labelled as:
STRUCT-HIGH
STRUCT-LOW
These levels may be used as external liquidity references, breakout levels, or potential price objectives.
M15 Supply and Demand Zones
The indicator also includes a simplified M15 supply and demand zone module.
A potential demand zone is identified from a bearish candle followed by a bullish displacement above that candle’s high.
A potential supply zone is identified from a bullish candle followed by a bearish displacement below that candle’s low.
The script applies body-strength and optional ATR range filters before accepting a zone.
For a bullish session setup, the script searches for a qualifying demand zone positioned above the session range.
For a bearish session setup, the script searches for a qualifying supply zone positioned below the session range.
Only zones formed before the active setup are considered.
The selected zone is displayed with:
Zone boundaries
50% midpoint
M15 zone label
Automatic right-side extension
Multi-Timeframe Structure
The model combines information from multiple timeframes:
H1 for session-range selection
M15 for imbalance gaps
M15 for structure highs and lows
M15 for supply and demand zones
Current chart timeframe for liquidity-sweep confirmation and display
The M15 modules are intended for charts between 1 minute and 15 minutes. Their drawings are hidden automatically on timeframes above 15 minutes.
Alerts
The indicator includes alerts for:
A newly selected session setup
A qualifying M15 structure high
A qualifying M15 structure low
A selected demand zone
A selected supply zone
The new setup alert identifies the symbol, selected model, and setup hour.
Suggested Workflow
A possible workflow is:
Identify the active H1 session range.
Observe whether price is trading above or below the 50% midpoint.
Wait for price to interact with the session high or low.
Look for a qualifying liquidity sweep.
Review nearby M15 imbalance gaps.
Check external M15 structure levels.
Use the selected supply or demand zone as additional context.
Apply independent entry confirmation and risk management.
The script is intended to organize market context. It does not automatically calculate an entry price, Stop Loss, Take Profit, position size, or trade outcome.
Customization
Users can adjust:
Light or dark visual theme
Active session model
Candle body and wick weighting
Line width and label size
Range projection length
Liquidity-sweep quality filters
Sweep cooldown period
Gap direction and ATR filter
Gap proximity to the setup
Structure pivot length
Supply and demand zone strength
Zone distance from the setup
These settings allow the model to be adapted to different symbols, volatility conditions, and trading styles.
Limitations
The session model uses fixed H1 time windows based on the symbol’s exchange or chart time context. Users should verify that the displayed hours match their intended trading session.
Pivot-based structure levels require candles on both sides of the pivot before confirmation. As a result, structure levels appear after the turning point has already formed.
Liquidity sweeps, imbalance gaps, and supply or demand zones do not guarantee a price reversal or continuation.
The script displays selected technical reference areas only. It does not account for spread, commission, slippage, economic news, liquidity conditions, or broker execution.
Because the script uses multiple timeframe calculations, some elements may update only after the relevant H1 or M15 candle has completed.
Disclaimer
Day Trade Setup - CRT Session Range Model is provided for technical analysis and educational purposes only.
It does not constitute financial advice, investment advice, trade recommendations, or guaranteed trading results. The displayed ranges, sweeps, gaps, structure levels, and zones are technical reference areas and should not be used as standalone entry signals.
Users are responsible for independently evaluating market conditions and applying appropriate risk management before trading with real funds. Indicatore
Indicatore
Day Trade Setup - FVG FinderDay Trade Setup - FVG Finder
Day Trade Setup - FVG Finder is a Fair Value Gap detection tool designed to identify bullish and bearish price imbalances directly on the chart.
The indicator scans both the current chart timeframe and a user-selected higher timeframe, then displays active FVG zones as colored boxes with optional price labels. Zones remain visible until they are mitigated or, for chart-timeframe zones, expire after the selected lookback period.
How It Works
A bullish Fair Value Gap is detected when the low of the current candle is above the high from two candles earlier, creating an untraded price area between them.
A bearish Fair Value Gap is detected when the high of the current candle is below the low from two candles earlier.
The script measures the size of each gap in points and displays only the zones that meet the minimum gap-distance setting selected by the user.
All chart-timeframe FVG calculations are confirmed after the candle closes.
Main Features
Detects bullish and bearish Fair Value Gaps
Displays FVG zones directly on the chart
Adjustable minimum FVG gap size
Customizable bullish and bearish zone colors
Adjustable zone transparency
Automatic extension of active zones
Automatic removal when a zone is mitigated
Optional expiration of older chart-timeframe zones
Higher-timeframe FVG detection
Adjustable higher-timeframe gap threshold
Optional price labels for the upper and lower edges of each zone
Light and dark chart-theme support
Alerts for new and mitigated FVG zones
Current Timeframe FVG Zones
The indicator scans the active chart timeframe for three-candle price imbalances.
When a valid bullish or bearish FVG is detected, the zone is drawn from the originating candle area and extended to the right.
Chart-timeframe zones remain active until:
Price closes beyond the opposite boundary of the zone, or
The zone exceeds the selected historical bar limit
For a bullish FVG, the zone is considered mitigated when price closes below its lower boundary.
For a bearish FVG, the zone is considered mitigated when price closes above its upper boundary.
Higher-Timeframe FVG Zones
Users can enable Multi-Timeframe FVG detection and select a separate higher timeframe.
Higher-timeframe zones are calculated using completed higher-timeframe candles to reduce changes caused by an unfinished candle.
HTF zones are displayed on the current chart and continue extending until price closes beyond their mitigation boundary.
This allows traders to monitor broader price imbalances without switching between multiple charts.
FVG Gap Filter
The FVG GAP (Point) setting controls the minimum size required for a chart-timeframe imbalance to be displayed.
The HTF FVG GAP (Point) setting applies the same type of filter to higher-timeframe zones.
Increasing these values reduces the number of smaller gaps shown on the chart, while lowering them allows the indicator to display more zones.
The correct point value may vary depending on the symbol, broker, and minimum tick size.
Price Tags
Optional price tags can be displayed at the upper and lower boundaries of every FVG zone.
Users can choose to:
Match the tag color with the bullish or bearish zone
Automatically adjust the tag color for light or dark charts
Select custom background and text colors
Change the tag-text size
These labels help users read the exact zone boundaries without manually checking the price scale.
Alerts
The indicator provides alert conditions for:
New Bullish FVG
New Bearish FVG
Bullish FVG Mitigated
Bearish FVG Mitigated
New Bullish Higher-Timeframe FVG
New Bearish Higher-Timeframe FVG
Bullish Higher-Timeframe FVG Mitigated
Bearish Higher-Timeframe FVG Mitigated
After adding the indicator to the chart, users can create TradingView alerts for any of these conditions.
Suggested Use
FVG zones may be used as areas of interest for:
Pullbacks
Rebalancing of price imbalances
Support and resistance context
Trend-continuation setups
Liquidity and market-structure analysis
Multi-timeframe confluence
The indicator does not generate direct Buy or Sell entries. Traders should evaluate each zone together with market structure, trend direction, liquidity, volatility, trading session, and personal risk-management rules.
Limitations
Fair Value Gaps do not guarantee that price will return to a zone or react from it.
During volatile market conditions, multiple zones may form within a short period. Some zones may be mitigated immediately, while others may remain active for an extended time.
Mitigation is determined using candle closes beyond the selected zone boundary. Intrabar price movement alone does not remove a zone.
Higher-timeframe zones are based on completed higher-timeframe candles, so they appear only after the relevant candle has closed.
Historical zones may also be limited by TradingView drawing-object limits and the selected lookback settings.
Disclaimer
Day Trade Setup - FVG Finder is provided for technical analysis and educational purposes only.
It does not provide financial advice, investment advice, trade recommendations, or guaranteed trading results. Fair Value Gap zones are reference areas only and should not be used as standalone entry signals.
Users are responsible for independently evaluating market conditions and applying appropriate risk management before trading with real funds. Indicatore
XAUUSD Scalper Pro by QUANTRADZGold Scalping Direction & Pullback Signals is a trend-following indicator designed to identify potential BUY and SELL opportunities on XAU/USD. It is intended primarily for 1-minute, 3-minute and 5-minute charts.
The indicator combines trend direction, momentum, volatility and candle confirmation into a configurable scoring system. Signals are designed to appear only after a candle has closed, helping traders avoid acting on incomplete candles.
HOW IT WORKS
The indicator analyzes:
• EMA 20 and EMA 50 for short-term trend direction• Optional EMA 200 for the broader market trend• RSI for momentum confirmation• ADX and DMI for trend strength and directional pressure• ATR for volatility filtering and risk-level calculations• Pullbacks toward the moving averages• Candle-body strength for entry confirmation• Optional higher-timeframe trend alignment
BUY SIGNAL
A BUY signal may appear when the short-term trend is bullish, price completes a valid pullback, momentum supports further upside and a strong bullish candle closes.
SELL SIGNAL
A SELL signal may appear when the short-term trend is bearish, price completes a valid pullback, momentum supports further downside and a strong bearish candle closes.
SIGNAL SCORING
Each bullish or bearish condition contributes to a directional score. A signal appears only when the score reaches the selected minimum threshold.
A higher threshold generally produces fewer but more selective signals. A lower threshold produces more signals but may also increase false entries.
CHART FEATURES
• Confirmed BUY and SELL markers• EMA 20, EMA 50 and optional EMA 200• Bullish and bearish condition scores• Trend and momentum dashboard• Optional higher-timeframe confirmation• ATR-based stop-loss and target guides• Configurable signal cooldown• Optional session and volatility filters• Confirmed BUY and SELL alerts
SUGGESTED USE
This indicator is designed for trend-pullback trading. It should not be used to enter every signal automatically.
Before considering an entry:
Confirm that the market is trending.
Avoid flat or frequently crossing moving averages.
Wait for the signal candle to close.
Check nearby support and resistance.
Avoid major economic announcements and abnormal volatility.
Use appropriate risk management.
For normal spot, CFD or futures trading, ATR levels can help estimate possible stop-loss and profit-target locations.
For fixed-payout trades, the ATR stop and target lines do not represent expiry rules. Each expiry duration should be tested separately using historical and demo results.
NON-REPAINTING BEHAVIOR
Signals are designed to use confirmed candle data and appear after the signal candle closes. Higher-timeframe calculations are designed to avoid lookahead.
Users should independently verify this behavior with TradingView’s Bar Replay feature before using the indicator.
IMPORTANT LIMITATIONS
This indicator does not predict the market and does not guarantee profitable trades. Signals can fail during ranging conditions, sudden news events, low liquidity or rapid reversals.
TradingView prices may differ from prices displayed by a broker or fixed-payout platform. Small differences can significantly affect short-duration trades.
Always test the indicator on historical data and a demo account before considering real-money trading. Past performance does not guarantee future results. Never risk money you cannot afford to lose. Indicatore
Backtest and Beyond? CT CPCV Research Lab v1.2 [Pine v6]CT CPCV Research Lab v1.2
One profitable backtest does not prove you've found a profitable trading strategy.
It proves only one thing: Your strategy worked once...on one version of history.
The real question is: Would it still work if history had unfolded differently?
Professional quantitative researchers have been asking that question for decades.
This framework brings that same question—and one possible way of answering it—to individual traders.
What this description covers
By the time you finish reading this description, you'll understand:
• Why a profitable backtest can be dangerously misleading
• Why professional quantitative researchers demand stronger evidence before trusting a strategy.
• Why Combinatorial Purged Cross-Validation (CPCV) has become one of the most respected validation techniques in quantitative finance.
• What this framework does.
• What it doesn't do.
• Why those differences matter.
So, if that sounds interesting...keep reading.
******
What Is CT CPCV Research Lab?
CT CPCV Research Lab is an open-source quantitative research framework built for TradingView.
It allows complete trading strategies, not just individual indicators, to be evaluated using Combinatorial Purged Cross-Validation (CPCV) under consistent research conditions.
Rather than asking: "Which strategy produced the highest historical return?"
it asks: "Which strategy demonstrated the greatest robustness across many independent historical tests?"
The goal isn't to predict the future. The goal is to help you place more appropriate confidence in what the past may, or may not, be telling you.
If you've ever developed a trading strategy, you've probably followed a familiar process.
• Build some trading rules.
• Run a historical backtest.
• See a profitable equity curve.
• Assume you've found a trading edge.
Unfortunately, that's exactly how thousands of strategies fool their creators every day.
A traditional backtest answers only one question: "What would have happened if I had traded this one sequence of historical events?"
That's a useful question. It just isn't the only question that matters. The uncomfortable truth is that one backtest proves far less than most traders believe.
Built to Teach, Not Just Calculate
Most TradingView scripts give you signals. Some give you statistics. Very few explain why those signals or statistics matter.
CT CPCV Research Lab was designed differently.
Throughout the framework you'll find:
• Plain-English explanations of the underlying research methodology.
• Educational comments describing the purpose of each major section.
• Input tooltips explaining not only what each setting does, but why you might want to change it.
• Built-in guidance that helps interpret CPCV results instead of simply displaying numbers.
Whether you're completely new to quantitative research or already familiar with CPCV, the goal is the same:
Every major part of this framework should either perform the research...or teach the research.
If understanding the research process is just as important to you as obtaining the results, this framework was built with that philosophy in mind.
Why great backtests often fail
Markets only give us one history. One sequence of bull markets, one sequence of bear markets, one sequence of crashes, recoveries, trends and sideways markets. When a strategy performs well on that single history, we don't automatically know why.
Did it discover a genuine market behaviour?
Or...
Did it simply get lucky?
Was it accidentally tailored to one particular period of history?
This is one of the biggest problems in quantitative finance. It is known as overfitting, and it is one of the main reasons strategies that look exceptional in historical testing often disappoint in live trading. The better a strategy becomes at explaining the past, the greater the risk that it has simply memorized the past rather than discovered something that persists into the future.
"I'll just use Out-of-Sample testing."
Good. That's already a major improvement. Out-of-Sample (OOS) testing separates historical data into two sections. One section is used to develop the strategy and the other section is hidden until the strategy is complete. Only then is the strategy evaluated on data it has never seen before.
This helps answer an important question: "Does my strategy still work on genuinely unseen data?"
That's far more honest than testing on everything, but it still has one important weakness.
You only get one Out-of-Sample test, one unseen historical period...and one result.
"I'll use Walk-Forward Analysis."
Even better. Walk-Forward Analysis repeats the process. The strategy is trained on earlier data, tested on the next unseen period, then the window moves forward and the process repeats.
Professional quantitative researchers have used Walk-Forward Analysis for many years because it is a significant improvement over a single backtest. But even Walk-Forward follows one continuous timeline.
History always unfolds in the same order, “Beginning...Middle...End.”
It creates many tests…but they're all built from the same historical journey. Walk-Forward Analysis remains one of the most respected validation techniques used by professional researchers today. CPCV should not be viewed as replacing Walk-Forward, but as answering a different and often more demanding research question.
Enter Combinatorial Purged Cross-Validation (CPCV)
Professional quantitative researchers wanted something even more demanding. Instead of relying on one backtest...or one Out-of-Sample period...or one Walk-Forward schedule...,they wanted to repeatedly evaluate a strategy across many different combinations of historical data. One of the best-known methods for doing this is called:
Combinatorial Purged Cross-Validation (CPCV)
Combinatorial Purged Cross-Validation was introduced by Marcos López de Prado in Advances in Financial Machine Learning (2018), where it was developed for validating machine-learning models in finance. This framework adapts its core principles, combinatorial train/test splits, purging, embargoing, and reconstructed out-of-sample paths, to the practical constraints of Pine Script.
Although the name sounds intimidating, the idea is surprisingly simple. Imagine interviewing someone for an important job. Would you hire them because they answered one interview question correctly?
Of course not. You'd ask many questions, test different skills, look for consistency.
Trading strategies deserve exactly the same treatment. A traditional backtest gives a strategy one interview. CPCV gives it dozens of different interviews.
If the strategy performs consistently across many independent historical tests instead of one lucky backtest, it earns greater confidence. Not certainty. Nothing in financial markets offers certainty.
Just stronger evidence.
What does "Combinatorial Purged Cross-Validation" actually mean?
The name sounds complicated, but each word simply describes part of the process.
Combinatorial: Instead of creating one train/test split, CPCV creates many different combinations of training and testing periods. This allows the strategy to be evaluated across many historical scenarios rather than relying on one convenient sequence.
Purged: Financial observations that occur close together often contain overlapping information.
Imagine two students sitting the same exam. If one student quietly glances at the other's answers before writing their own, the exam is no longer fair.
Purging removes nearby training observations that could accidentally leak information into the test period.
Cross-Validation: Rather than asking "Did this strategy work once?", Cross-Validation repeatedly asks
"Does this strategy continue working when tested on different unseen historical data?"
The goal isn't to find one impressive result. The goal is to see whether good performance remains consistent.
Why this framework exists
For many years, advanced quantitative validation techniques were used primarily by institutional researchers, hedge funds and quantitative investment firms. Retail traders rarely had access to these ideas, not because they were secret, but because they were often buried in academic research or implemented in specialist software.
This framework was built to present those same research principles in plain English so individual traders can understand them, question them, and apply them for themselves. Good research shouldn't depend on where you work. It should depend on how carefully you test your ideas.
A note about the Pine implementation
This implementation is designed to bring the core principles of institutional Combinatorial Purged Cross-Validation (CPCV) research into Pine Script while respecting the practical execution limits of the TradingView environment.
Professional quantitative research platforms often have access to dedicated computing resources with relatively few practical limits on memory, processing time, data sources or dataset size.
TradingView's Pine Script is designed for interactive chart analysis and therefore operates within execution-time, memory and resource limits so scripts remain responsive for all users. To make CPCV practical within those limits, this implementation makes several engineering choices, including limiting the number of chronological groups, reference strategies and stored observations. These are implementation constraints, not changes to the underlying CPCV methodology.
A note on purging and embargo in this implementation. These techniques exist to prevent information from a training observation's forward-looking label leaking into a nearby test period. The built-in candidate strategies use one-bar returns, so their natural leakage window is very short and the purge/embargo settings have limited effect on them. Their value grows substantially if you replace a candidate with a strategy that uses multi-bar holding periods or forward-horizon labels, where boundary leakage is a real risk. They are included so the framework remains methodologically complete and correct for the strategies you may add, not only the ones shipped by default.
The objective has always been to preserve the essential research principles of CPCV while delivering an educational framework that runs efficiently inside TradingView. If you're learning quantitative strategy validation, understanding why CPCV works is far more valuable than simply increasing the number of groups from 8 to 20. Sound methodology will improve your research far more than simply making the computation larger.
How to Read the Tables
This framework displays its results in four tables rather than on the price chart, because CPCV evaluates research quality, not price action. Here's what each table shows and how to act on it.
Split Diagnostics
Each row is one training/test experiment. The engine holds out two chronological groups as unseen test data, selects the best candidate using the training data only, then measures how that choice performed on the held-out test data.
Read the columns left to right: which groups were held out, which candidate was selected, its score on training data, its score on test data, its test return, and its worst drawdown during the test period.
The single most important thing to look for is a candidate that scored well in training but poorly in testing. That gap is the fingerprint of overfitting. A strategy that looks brilliant in training and then collapses out-of-sample has told you something valuable, it just wasn't what you were hoping to hear.
Do not judge the framework by the best split. One good row is not evidence. Consistency across many rows is.
Path Diagnostics
Each row is one fully reconstructed out-of-sample history, assembled from test segments that the strategy never trained on. Instead of one backtest, you are looking at several independent reconstructions of history.
Four things deserve your attention, and the Results Guide lists them in order:
The median path tells you the typical outcome, not the luckiest one. The worst path tells you how bad an unlucky reconstruction looked, this is your pessimistic case, and a strategy that stays tolerable even here is showing real resilience. The positive-path rate tells you how many reconstructions finished profitable; a strategy profitable on one path and negative on the rest has not earned confidence. And return versus drawdown reminds you that a good return purchased with a brutal drawdown is not the same as a good return earned smoothly.
If the paths all look nearly identical, that usually means one candidate dominated selection across every split. That is normal and informative, it simply means CPCV is validating that one strategy.
Research Integrity
This panel does not measure whether your strategy is profitable. It measures how much confidence you should place in the research configuration itself, whether the sample was large enough, the coverage valid, the paths consistent, the worst case survivable, and the typical drawdown manageable.
Treat it as a credibility check on the test, not a prediction of the result. A high score means the validation has few obvious weaknesses. A low score means any attractive-looking performance should be treated with extra caution, because the setup itself may not support strong conclusions. The panel's own final row says it plainly: research confidence, not expected profit.
Results Guide
A permanent on-chart cheat sheet summarizing the reading order above and explaining the color coding, green when the median and worst case are both positive, yellow when the median holds up but the worst case is fragile, red when the median or most paths failed. If you remember nothing else, the guide is there to remind you: focus on the median and the worst case, not the single best split.
Configuring the Candidates
The most common first experience with this framework is to enable all ten candidates, run it on a favorite chart, and find every split selecting the same strategy and every path failing. That is not a malfunction and understanding why explains how to configure the framework properly.
CPCV can only reveal something interesting when the selection is contested, i.e., when different candidates genuinely compete to be chosen, and different ones win in different periods. If every candidate you enable behaves the same way, the framework isn't choosing between ideas. It's choosing the least-bad member of one idea.
Diversify the families, not just the parameters
Five EMA crossovers at different lengths are not five different strategies. They are one strategy at five speeds, and they are highly correlated…they mostly agree, so selection barely changes and the reconstructed paths become near-identical copies.
The candidates ship in two behavioral families:
Trend-following (the EMA crossovers, MACD, Donchian, Supertrend) profits when moves persist. Mean-reversion (RSI, Bollinger) profits when price snaps back toward an average.
These families tend to be opposites: when one struggles, the other often works, because trending and ranging are opposite market conditions. A balanced set, a few trend models alongside both reversion models, lets different candidates win in different periods, which is exactly what makes the paths diverge.
Test where regimes actually change
The framework can only display path dispersion if the data contains different conditions for different candidates to win in. A market in one long, clean trend will let a single slow trend-follower dominate every split, producing results that are consistent but undifferentiated. A market stuck in pure chop will punish every trend model at once, which is how an all-red board appears. The most revealing samples contain both trending and ranging periods, so widen the date range until it spans at least one full cycle of each, and consider instruments that move through both rather than sitting in a single prolonged trend.
Change the metric to change the winner
The selector ranks candidates using one training metric, and different metrics crown different winners. Sharpe rewards smoothness, Calmar rewards drawdown avoidance, Sortino favors directional trend-following, Omega favors skewed reversion payoffs. Running the same enabled set under different Optimization Metrics is a fast way to see selection shift, and watching which candidate wins under which metric is itself a lesson in how sensitive strategy selection really is.
What a good configuration looks like
Success here is not a green board. It is a contested one. In Split Diagnostics you want the MODEL column to show several different names rather than one name repeated down every row. In Path Diagnostics you want P1, P2, P3 and the rest to be visibly different numbers rather than clones, a genuine median sitting between a positive best case and a negative worst case. That spread is the CPCV signal. A board where one model wins everything is almost as uninformative as one where everything fails; both mean the selection was never truly contested.
One honest warning. Do not hunt through instruments and metrics until you find a green result and then treat that as proof. That is simply overfitting one level higher, cherry-picking the demonstration instead of the strategy. The purpose of a contested run is to watch the method work, red parts included. A result that mixes success and failure across its paths is not a disappointing outcome. It is the framework telling the truth.
Using Your Own Strategies
The ten built-in candidates are examples, not the point. The framework is designed so you can delete any of them and drop in your own logic, that is its intended use, not a hack.
To replace a candidate, keep to three rules:
First, produce a persistent desired-position series with exactly three possible values: +1 for long, 0 for flat, −1 for short. The framework evaluates this series, not your entry/exit orders, so your logic must hold a position until it decides to change it, rather than firing a one-bar signal.
Second, stay causal. Use only information available up to the current bar. Do not use future data, negative historical offsets, or lookahead on. The framework already lags exposure by one bar when simulating returns, so your job is simply to avoid look-ahead in the signal itself.
Third, wrap your output through the direction filter (f_direction) exactly as the existing candidates do, so the Long Only / Short Only / Long & Short control keeps working.
That's it. Anything that respects it, a moving-average system, an oscillator, a breakout rule, or something entirely your own, will be validated under the same CPCV conditions as the built-in examples. If your strategy uses multi-bar holding periods or forward-looking labels, this is also where purging and embargo begin to do real work, so set those values to match your strategy's actual horizon.
An important limitation
If you've read this far and concluded that CPCV is the ultimate solution... then this description has failed.
CPCV is one of the most rigorous historical validation techniques available, but it is not a crystal ball.
No historical validation method can predict the future.
Markets evolve
One of the biggest misconceptions in technical analysis is that indicators suddenly "stop working."
Most of the time, they don't. The mathematics haven't changed. A 50/200 EMA crossover calculates exactly the same way today as it did ten years ago.
RSI hasn't changed.
MACD hasn't changed.
Bollinger Bands haven't changed.
…the market changed.
Financial markets constantly move through different environments. Sometimes they trend strongly.
sometimes they move sideways for months, other times volatility explodes…and then it disappears. Periodically, liquidity is abundant…and inexplicably, it evaporates.
These and other changing environments are commonly called market regimes. Within every regime there are often shorter-lived shifts or states in market behavior that further influence strategy performance. The same trading strategy can perform exceptionally well in one regime and struggle in another, even if the strategy itself never changes. That's one of the most important lessons in quantitative research.
No technical indicator can know which market regime it is operating within. It simply continues performing the same calculation while the market itself changes around it.
What this framework can, and cannot, tell you
This framework is designed to answer one question: "How robust did this strategy appear across many independent historical tests?"
It is not designed to answer another: "Will this strategy continue working as markets evolve?" That requires continued observation, adaptation and research.
Do not be surprised if the same candidate is selected on every split. When one strategy scores highest across all training folds, CPCV effectively becomes a validation of that single strategy, and if it then fails out-of-sample on every path, that is not a malfunction. It is the framework doing its job: telling you the best-looking in-sample choice did not survive honest testing.
Good quantitative research is not about finding certainty. It is about reducing the chances that we fool ourselves before risking real capital.
One important clarification about what is being validated. This framework does not cross-validate each candidate strategy in isolation. It cross-validates a selection procedure: on every training split it picks the best-scoring candidate, then judges that choice on unseen test data. This matters because strategy selection is one of the most common places overfitting hides. A candidate that consistently looks best in training but fails in testing is exactly what CPCV is designed to expose.
The philosophy behind this project
Good quantitative research doesn't ask: "How can I prove this strategy works?"
It asks: "How hard can I try to prove that it doesn't?"
Every independent test that a strategy survives earns it a little more credibility. Not because it made more money, but because it had more opportunities to fail, and didn't.
That's the philosophy behind CT CPCV Research Lab.
A personal perspective
In my experience, market structure, liquidity, positioning, capital flows, and changing market regimes often explain market behavior more consistently than any individual technical indicator alone. This is where my own work has focused for many years — and, increasingly, on the fragility that builds inside a market before it shows up in price.
That does not mean technical analysis has no value. Millions of traders around the world continue to make decisions using technical analysis every day. Whether those decisions rest on enduring market truths or widely shared behavioral patterns is a separate question. Either way, when millions of participants respond to similar signals, those behaviors become part of the market itself.
For that reason alone, understanding how technical strategies behave — and how rigorously they should be tested — remains a worthwhile pursuit. If you're one of those traders, my hope is that this framework helps you evaluate technical strategies more honestly than a single backtest ever could.
Whether your strategy uses moving averages, RSI, MACD, Bollinger Bands, Donchian channels, or something entirely your own, it deserves to be tested honestly. And if this framework leaves you curious about why the same strategy thrives in one regime and dies in another — about the structural conditions that shift beneath price before price ever moves — then it has done something a backtest never could. That question is where my own work goes next.
If this project encourages even a few traders to question impressive-looking backtests, demand stronger evidence, and approach strategy development with greater intellectual honesty, then it has achieved exactly what it was created to do.
Good research doesn't eliminate uncertainty. It simply reduces the chances that we mistake luck for skill. If this framework helps even a handful of traders make that distinction, then it has served its purpose.
Disclaimer
CT CPCV Research Lab is provided for educational, informational, and analytical purposes only.
Nothing within this script, its outputs, tables, scores, grades, metrics, documentation, or associated materials constitutes financial advice, investment advice, trading advice, legal advice, or a recommendation to buy, sell, hold, or otherwise transact in any financial instrument.
Trading and investing involve substantial risk. Past performance is not indicative of future results, and no historical validation method, including Combinatorial Purged Cross-Validation, can predict future performance. Markets are inherently uncertain, and losses may occur.
Users are solely responsible for all trading and investment decisions made using information derived from this script. The developer makes no representations or warranties regarding accuracy, completeness, profitability, suitability, reliability, or fitness for any particular purpose.
CT CPCV Research Lab is a research and validation tool. It does not generate trade signals, is not an automated trading system, and must not be relied upon as the sole basis for any trading or investment decision. A high Research Integrity score reflects the credibility of a research configuration, not the likelihood of future profit.
By accessing or using this script, the user acknowledges and accepts all risks associated with its use and agrees that the developer shall not be liable for any direct, indirect, incidental, consequential, or special losses or damages arising from the use of the script or any information it provides.
Indicatore
crypto signals -Breakout Targets# 🚀 Crypto Signals (Breakout Targets)
**Crypto Signals (Breakout Targets)** is an enhanced breakout trading indicator designed to identify high-probability breakout opportunities while providing automatic trade management with multiple profit targets and a dynamic stop loss.
This version is based on the original open-source **Breakout Targets** indicator by **AlgoAlpha**, with numerous enhancements focused on customization, usability, performance tracking, and professional alert automation.
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## ✨ Features
✅ Automatic detection of bullish and bearish breakout opportunities.
✅ Up to **3 configurable Take Profit levels (TP1, TP2, TP3).**
✅ Dynamic Stop Loss calculated using **ATR** or **Percentage (%).**
✅ **Auto Symbol Profiles** for storing different settings across multiple trading pairs.
✅ Advanced Statistics Dashboard displaying:
* Win Rate
* Total Winning Trades
* Total Losing Trades
* Net Performance
* TP1 / TP2 / TP3 Statistics
✅ Fully customizable colors and display settings.
✅ Clean and intuitive chart visualization suitable for all timeframes.
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## 🔔 Smart Alert System
The indicator includes a professional built-in alert system fully compatible with **TradingView Alerts**, making it easy to integrate with Telegram bots, Discord, webhooks, or automated trading systems.
Available alert events:
* 🟢 Buy Signal
* 🔴 Sell Signal
* 🎯 TP1 Hit
* 🚀 TP2 Hit
* 🏆 TP3 Hit
* 🛑 Stop Loss Hit
Each alert is delivered in a clean, mobile-friendly format and includes essential trade information such as the trading pair, timeframe, entry price, target levels, and stop loss, allowing traders to monitor positions efficiently in real time.
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## 📈 How It Works
The indicator continuously analyzes price action to identify potential breakout opportunities.
Once a breakout is confirmed, it automatically plots:
* Entry Price
* Stop Loss
* Take Profit 1 (TP1)
* Take Profit 2 (TP2)
* Take Profit 3 (TP3)
The trade is then monitored automatically while the statistics dashboard keeps track of overall performance and target achievements.
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## 🎯 Best For
* Cryptocurrency
* Forex
* Stocks
* Indices
The indicator works on all timeframes and delivers the best results when combined with proper market structure analysis, confirmation tools, and sound risk management.
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## 🙏 Credits
This project is based on the open-source **Breakout Targets** indicator created by **AlgoAlpha**.
The original concept has been extended with additional features, profile management, enhanced dashboards, professional alerts, customization options, and various usability improvements while respecting the original open-source license and giving full credit to the original author.
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# ⚠️ Disclaimer
This indicator is provided for **educational and informational purposes only**.
It does **not** constitute financial or investment advice and should not be interpreted as a recommendation to buy or sell any financial instrument.
Trading financial markets involves substantial risk and may result in the partial or total loss of your capital. Always perform your own analysis, use proper risk management, and never rely solely on any indicator when making trading decisions.
Past performance does **not** guarantee future results.
Indicatore
Order Block Stop Survival StudyCredit
The order block detection and the retest condition used as the trigger of this study are adapted from "Power Order Blocks " by ChartPrime, published open source under the Mozilla Public License 2.0. Full credit to ChartPrime for that detection method. This script is published open source under the same licence.
What it adds to the original
The original draws order blocks and marks the moment price comes back to them. It never answers the question that actually decides whether you can trade them: when price taps an order block, does a stop of a given size survive long enough for the trade to work, and does that beat entering at a random moment on the same chart?
This script answers exactly that, and it puts the two numbers side by side.
How to read the table
Each row is a stop distance, expressed in ATR multiples or in absolute price.
On OB retest: out of every first touch of a fresh order block, how often the target was reached before the stop.
Random entry: the same measurement made at arbitrary moments on the same chart, both directions.
Edge: the difference in percentage points. Green when the setup beats chance, red when it does not.
The highlighted row is the stop distance you actually use, so you can place your own habit among the others.
The break-even line
A percentage means nothing without a reference. The line under the table gives the success rate that merely breaks even for your chosen target: 50 percent at 1R, 33.3 at 2R, 25 at 3R. Above it you are ahead, below it you are behind, whatever the raw number looks like.
First touch only
By default only the first return to a fresh block is counted, because that is the setup a trader takes. Turn the option off to include later touches of an already used zone. Comparing the two is informative in itself: on most instruments the edge is visibly thinner once worn out zones are included.
Long and short counts are shown
The footer reports how many setups were long and how many were short. If one side dominates heavily on a strongly trending sample, part of any measured edge is the trend rather than the order block. Showing the split lets you judge that instead of taking the result on faith.
How it works
At each sampled bar the script steps back so the entire outcome of the setup already sits in the past, then walks forward bar by bar and records which level was reached first. There is no forward-looking data and no repainting by construction.
When a single bar touches both the stop and the target, the script counts the stop. Inside a bar there is no way to know which came first, and overstating survival would be dishonest.
Settings
Max bars to resolve, target as an R multiple of the stop, and the sampling step of the random baseline.
Displacement multiplier, number of active blocks and minimum spacing between retests, all inherited from the original detection.
Five stop distances plus your own, ATR based or absolute.
Pip size: gold 0.1, forex majors 0.0001, JPY pairs 0.01, 0 to hide pips on crypto.
Colours, text size, border width and table position are configurable.
Limitations
Spread, slippage and commissions are ignored, so a real edge is thinner than the one displayed, and a small edge may not survive costs at all.
The statistics describe the history loaded on your chart. They do not predict anything.
This is a study. It produces no entry signal and no performance claim.
Below the minimum number of setups the table warns instead of showing percentages built on too little data. Indicatore
Regime Quadrant Map [XWiseTrade]Regime Quadrant Map
Part of the XWiseTrade Quant Suite. Follow so you don't miss the next one.
Most "regime" indicators sort the market into two boxes: trending or ranging. But that single axis hides the variable that actually decides whether a trend is tradeable — volatility. A market drifting up in dead-calm conditions and a market ripping up in violent conditions are both "trending," yet they demand opposite tactics. Collapsing them into one label is why so many trend filters fail exactly when you lean on them. This indicator separates the two questions that a one-dimensional filter fuses together, and maps the result onto four regimes instead of two.
Why volatility is measured as an ATR Z-score, not raw ATR
Raw ATR tells you nothing on its own — an ATR of 15 is enormous on one instrument and trivial on another, and huge in one era and small in the next. What matters is whether volatility is unusually high or low relative to this market's own recent behaviour. So ATR here is ranked against its own distribution over a lookback window and expressed as a Z-score: how many standard deviations above or below its own norm current volatility sits. That makes the reading self-referential and comparable across any symbol or timeframe, instead of an absolute number you'd have to re-learn for every chart.
Why trend is measured with Efficiency Ratio, not a moving-average slope
A rising moving average tells you price is higher than it was — it does not tell you how price got there. Efficiency Ratio does: it divides the net directional move by the total distance price actually travelled to make it. A value near 1 means a clean, purposeful move; near 0 means price thrashed back and forth to end up in nearly the same place. Two charts with an identical slope can have completely different efficiency, and that difference — not the slope — is what separates a trend you can ride from a trap. Slope measures result; Efficiency Ratio measures quality.
The four quadrants
Crossing the two axes gives four regimes, each with a distinct character:
GRIND (trending + low volatility) — a steady, efficient directional move; the kind you can lean into.
EXPANSION (trending + high volatility) — a violent directional move; momentum conditions, wider risk.
COIL (ranging + low volatility) — compression; energy building, often ahead of a breakout.
CHOP (ranging + high volatility) — whipsaw with no follow-through; the regime most accounts quietly bleed in.
How to use it
Watch the regime label and background tint for the current quadrant, or read the two plotted lines directly against their dashed thresholds — the ATR Z-score line for the volatility axis, the Efficiency Ratio line for the trend axis. Both thresholds and both lookbacks are adjustable, so you can set what counts as "high volatility" or "trending" for your own instrument and timeframe. An alert fires whenever the market crosses into a new quadrant, so you don't have to watch it to know the regime shifted.
What makes it different
Standard regime tools reduce the market to a single trend-versus-range line and treat volatility as an afterthought. This one builds regime from two independent axes, measures volatility as a self-referential Z-score rather than an absolute number, measures trend by path efficiency rather than slope, and resolves the market into four actionable states instead of two — because "trending" alone was never enough to decide how to trade it.
If this framework is useful, follow to get the rest of the Quant Suite as it drops — each script extends this model into entries, risk, and prop-firm workflows. More tools and write-ups: xwisetrade.com
These are descriptive regime classifications for discretionary use, not buy/sell signals. Indicatore
Indicatore
FULCRUM: Rates & Vol Adjusted Ratio VWAPWHAT IT DOES
The fulcrum of the index complex: a rates-and-volatility-adjusted VWAP for the relationship between two markets. It rebuilds the NQ/ES ratio bar by bar — 2500·NQ/ES, normalized by VXN×US10Y — then anchors a volume-weighted mean with ±1σ and ±2σ bands on that relative-value series. One line that says whether tech is rich or cheap against the broad market, and how stretched the move is. It lives in its own pane, works on any chart, and configures itself.
HOW IT WORKS
Both legs are requested at chart resolution, and the bar's ratio high/low come from the cross-extremes (NQ high over ES low, and the reverse) — the VWAP sees the bar's true range, not just closes.
A spread has no volume of its own, so weighting borrows the geometric mean of both legs' volume.
The rates/vol divisor uses the PRIOR session's confirmed VXN and US10Y closes — identical live and on reload. No repaint.
The anchor is automatic: session on charts up to 20m, week up to 4h, month above. Override it if you disagree.
Bands come from cumulative volume-weighted variance, not a rolling stdev, and stay hidden for the first bars after each reset while they cook.
The ratio line holds its color until the move clears ±0.15σ — color changes are regime, not noise. A faint tint marks ±2σ extension.
A live table reads VWAP, ratio, Δ%, σ-distance, zone, and the divisor's status — if a feed is missing it says so instead of guessing silently.
HOW TO USE IT
Read the relationship against its anchored mean: +2σ on a ratio behaves like +2σ on price — stretched, and usually walked back. Cross alerts on VWAP, ±1σ, and ±2σ are included. Swap the symbols and multiplier and it generalizes to any pair you trade.
WHAT IT CAN'T DO
It describes the relationship, not direction — the ratio falling doesn't say whether NQ is weak or ES is strong. If the VXN or US10Y feed is unavailable, the divisor falls back to sane defaults and the table flags it; it will not pretend.
SETTINGS
Numerator, denominator, and multiplier; VXN×US10Y normalization; auto or manual anchor (session, week, month); band multipliers; warm-up hiding; colors, fill, labels, table.
Open source. Free. Where the balance sits. Indicatore
Supertrend + Apex HUD Master Pro - Farthaze### Overview
**Supertrend + Apex HUD Master Pro** is an all-in-one trading dashboard designed to combine clean price action trailing stops with a high-density, real-time Heads-Up Display (HUD).
Instead of cluttering your chart with dozens of individual indicators, this script consolidates market trend, momentum, intraday volume dynamics, key daily pivot levels, and target projections into a single, compact interface.
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### Key Features
#### 1. Adaptive Supertrend Engine
* **Trailing Stop Overlay:** Uses Average True Range (ATR) to trail stops dynamically based on volatility.
* **Visual Trend Fill:** Highlights the active trend direction with transparent, non-intrusive color shading between price and the Supertrend line.
* **Signal Labels:** Displays clean `BUY` and `SELL` tags on valid trend flip transitions.
#### 2. Apex HUD Master Table
A real-time data table pinned to your chart providing quick market analysis:
* **Trend Bias & Momentum:** Instant visual status of trend direction alongside 14-period RSI momentum.
* **Volume Analysis (RVOL):** Tracks current bar volume relative to a 20-period SMA to spot unusual volume spikes instantly.
* **Shares Traded & Split Volume:** Calculates total session volume alongside intra-bar estimated **Buy Volume (Green)** and **Sell Volume (Red)** to gauge institutional buying vs. selling pressure.
* **Key Levels (PDH/PDL & TDH/TDL):** Consolidated tracking of Previous Day High/Low and Today's High/Low for quick support/resistance reference.
* **Dynamic Take-Profit Targets (TP1 / TP2 / TP3):** Calculates volatility-adjusted target levels using ATR multipliers to help plan trade exits.
* **Risk-to-Reward Ratio:** Displays a real-time Risk:Reward ratio based on the distance between current price, the Supertrend stop-loss, and target levels.
#### 3. Volatility Spike Monitor
* A standalone auxiliary table tracking recent high-volatility expansion bars (bars exceeding your defined ATR spike threshold).
* Keeps track of the last bullish and bearish volatility spikes along with their percentage move size and breakout prices.
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### How to Use
1. **Identify Trend Bias:** Check the Supertrend overlay and the HUD's **Trend Bias** indicator to align with the primary direction.
2. **Confirm Volume & Momentum:** Ensure RSI momentum aligns with your bias and check if RVOL indicates elevated volume participation.
3. **Gauge Institutional Pressure:** Compare the green **Buy Vol** and red **Sell Vol** numbers in the HUD to confirm who is controlling the intraday order flow.
4. **Manage Trade Exits:** Use the auto-calculated **TP1, TP2, and TP3** target levels alongside the Risk:Reward readout to plan your entries and exits.
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### Indicator Settings & Customization
* **Supertrend Settings:** Adjust ATR Period and Multiplier to fit scalping, swing trading, or position trading timeframes.
* **Apex HUD Options:** Customize table position (Top Right, Top Left, Bottom Right, Bottom Left) and text scaling size.
* **Session Filter:** Filter shares traded calculation between *All Sessions*, *Regular Hours Only*, *Premarket Only*, or *Postmarket Only*.
* **Volatility Spike Table:** Set custom ATR thresholds to trigger volume/range expansion tracking.
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*Disclaimer: This indicator is designed for educational and analytical purposes only and does not constitute financial advice. Always practice proper risk management.*
I created this to surpass time to see today highest and lows and volume etc. Hope you like it. Happy trading Indicatore
NeuPortal - Forecast: sealed distributions, not pathsDraws a forecast as a DISTRIBUTION at a stated horizon, never as a path.
What it plots, from values you enter yourself:
— median for the horizon
— core 50% zone (25th–75th percentile of the asset's own historical moves over the same horizon)
— wide 80% band (10th–90th percentile)
— the seal: a vertical line at the bar the forecast was fixed on, so left of it is observed and right of it was unknown
— an explicit invalidation level
— a computed daily read (ADX, DI, RSI, MACD, %B, EMA structure, ATR) taken from the chart itself, so the table cannot drift from the price it sits on
There is deliberately no diagonal anywhere. A line drawn from today's price to a future price is read as a claimed route, and a distribution at a horizon is not a route. The size of the expected move is stated as a vertical dimension bracket instead.
Free, open source, no gating, no signals, no DMs.
Educational content — not financial advice. Indicatore
Ribbon Concordance [RC Tools]RC Tools — Ribbon Concordance
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█ OVERVIEW
Most ribbon-of-moving-averages tools either average the ribbon or rely on simple crossovers. This one asks a different question: is the ribbon consistently ORDERED? A cleanly stacked ribbon signals real trend conviction; a tangled, crossing one signals chop — often before any single moving average has crossed another.
█ WHAT IT DOES
Plots a live moving-average ribbon directly on the price chart (choice of 7 MA types, up to 10 MAs), plus a rank-concordance score (-100 to +100) in its own pane. Classifies the ribbon into four bands — Strong Bullish, Weak Bullish, Weak Bearish, Strong Bearish — colours the chart background accordingly, and shows a table with the current band, how long price has been in it, and historical base rates (average forward return and win rate) for each band.
█ THE THEORY BEHIND IT
Ribbon tools usually throw away information about HOW consistently the ribbon is stacked, collapsing it to an average or a single crossover event. This tool instead measures rank concordance — a public, long-established statistical concept (related to Kendall's tau) that quantifies how well two orderings agree with each other. Applied to a moving-average ribbon: compare every pair of MAs, shorter-period against longer-period, and score whether their relative ordering is consistent with a clean trend. A ribbon where every shorter MA sits above every longer one (or below, for a downtrend) scores near the extreme; a tangled, crossing ribbon averages out near zero. This is a different statistical question than "is price above its moving average" or "how efficient was the recent price path" (see the Regime Classifier for that approach) — it is specifically about internal agreement across the whole ribbon at once.
█ HOW IT IS CALCULATED
1. Build a ribbon of N moving averages (configurable type and count), with periods increasing linearly from a base period by a fixed spacing.
2. For every pair of MAs (i, j) where i has a shorter period than j: score +1 if MA > MA (bullish-consistent ordering), -1 if reversed, 0 if tied.
3. Sum all pair scores and normalise by the number of pairs compared, scaled to -100..+100.
4. Optionally EMA-smooth the raw score, which is otherwise a somewhat steppy pairwise count, for a cleaner read.
Classification occurs ONLY on confirmed bar close — the band never flips mid-bar and reverses. The MA ribbon itself plots live, exactly like any moving average on any chart; that is normal behaviour, not repainting. Only the concordance score and its band classification are held to confirmed bars.
█ SETTINGS & CONFIGURATION
• Source, MA Type (SMA / EMA / WMA / RMA / HMA / DEMA / TEMA)
• Base Period and Period Spacing — set the shortest MA and the gap between each successive one
• Ribbon Size (3-10 MAs) — more MAs smooth the read but add lag from the longest one; fewer react faster but are noisier
• Score Smoothing Length — EMA smoothing on the raw concordance score (set to 1 for none)
• Strong Threshold — the score above which (or below its negative) a band counts as "Strong" rather than "Weak"
• Forward Return Window — the horizon used for the base-rate table
• Show MA Ribbon on Chart — toggle the ribbon overlay off if you only want the concordance pane
• Ribbon gradient colours (short end / long end) and band colours are fully configurable
█ HOW TO USE IT
Use it as a trend-conviction filter alongside your existing process. Strong Bullish/Bearish bands indicate a cleanly stacked ribbon — a higher-conviction environment for trend-following approaches. Weak bands, or frequent flips between Weak Bullish and Weak Bearish, indicate the ribbon is loosely ordered — more caution warranted for trend-following, and potentially a more favourable environment for mean-reversion approaches instead. Check the base-rate table's sample count before assuming any one band is systematically favourable.
Works on any asset and timeframe; ribbon size and spacing should be tuned to the timeframe you trade (a wide, long-spaced ribbon on a low timeframe will lag heavily).
█ LIMITATIONS
• This is a ribbon of moving averages — inherently lagging by construction. It confirms alignment after price has already moved, and this cannot be removed without curve-fitting.
• Near-zero or Weak readings are common in choppy, range-bound conditions and do NOT predict a breakout direction — they only describe the ribbon's current state of (dis)agreement.
• Ribbon size is a real trade-off: more MAs smooth the read but add lag from the longest included MA; fewer MAs react faster but are noisier.
• The concordance score and band update on confirmed bar close only. The ribbon MA lines themselves plot live, like any moving average — that is normal behaviour, not repainting.
• Historical base-rate stats need a meaningful sample count (check N) before being trusted, especially for less common bands.
• Four bands are a deliberate simplification of a continuous reality. Markets do not actually occupy discrete states.
█ DISCLAIMER
For educational and informational purposes only. Nothing here is financial advice. Past behaviour of any band does not indicate future results. Trade at your own risk.
Indicatore
NeuPortal - Forecast: sealed distributions, not pathsDraws a forecast as a DISTRIBUTION at a stated horizon, never as a path.
What it plots, from values you enter yourself:
- median for the horizon
- core 50% zone (25th to 75th percentile of the asset's own historical moves over the same horizon)
- wide 80% band (10th to 90th percentile)
- the seal: a vertical line at the bar the forecast was fixed on, so left of it is observed and right of it was unknown
- an explicit invalidation level
- a computed daily read (ADX, DI, RSI, MACD, %B, EMA structure, ATR) taken from the chart itself, so the table cannot drift from the price it sits on
There is deliberately no diagonal anywhere. A line drawn from today's price to a future price is read as a claimed route, and a distribution at a horizon is not a route. The size of the expected move is stated as a vertical dimension bracket instead.
Two ways to feed it. Fill the inputs by hand, or paste a single line into "Today's line" in the first settings group, in the form key=value;key=value - useful if you generate forecasts programmatically and do not want to retype twenty fields daily. Pasted values win, missing ones fall back to the manual inputs.
Free, open source, no gating, no signals, no DMs.
Educational content - not financial advice. Indicatore
NeuPortal Empirical Range - measured bands, honest sample sizeMost volatility bands are drawn the same way: per-bar sigma times the square root of the horizon. That rule assumes returns are independent draws from one fixed distribution. Crypto returns are neither — volatility clusters, tails are fat at short horizons, and the shape of the distribution changes as the horizon grows.
This script measures instead, and draws the assumption next to the measurement so you can see the gap on your own symbol.
An example of why that matters. On BTCUSDT 4h with a 24-bar horizon, the empirical band comes out 0.95x the textbook one — slightly narrower. But at 48 bars the measured width is 1.70x the 24-bar width where root-t predicts 1.41x, and at 72 bars it is 2.03x against a predicted 1.73x. The formula is roughly right at one horizon and badly wrong at another, on the same symbol. On ETHUSDT the pattern is the opposite. You cannot know which case you are in without measuring.
WHAT IT PLOTS
- core 50% zone: the interquartile range of how this market has actually moved over your horizon
- wide 80% band: the 10th to 90th percentile, as risk context
- median of the measured distribution
- the textbook sigma x root-t band, for contrast
The band is drawn FLAT on purpose. It describes one moment in the future, not a path to it. A diagonal would be a claim about the route, and this makes no claim about the route.
WHAT IT DOES THAT OTHER BANDS DO NOT
Conditional bands. An unconditional band averages today's market with every regime the symbol has ever been in. Switch conditioning on and only windows whose starting volatility resembled today's are counted. The table shows how many windows survived, because a conditional band on 20 windows is worse than an unconditional one on 500.
Touch versus close probability. Type a price and get two numbers: the share of historical windows that FINISHED beyond it, and the share that TOUCHED it at any point on the way. These differ a lot. If you are asking whether a stop gets hit, the second number is the answer and the first is misleading. Both come from actual highs and lows of real windows, not from a closed-form approximation.
The honest sample size. Overlapping windows flatter a sample: 3,000 rolling 24-bar returns come from 125 genuinely independent windows, and quantile standard errors scale with the second number. Both are printed, and the small one is flagged when it gets thin.
Out-of-sample coverage. The band is fitted on the older part of the chart and tested on the newer part it never saw. Target 50% for the core, 80% for the wide. Both directions are marked as failures: a band that contains everything is not skill, and that is the failure mode that flatters the author. On some symbols this script will tell you its own band is too wide. That is the point.
Multi-horizon widths at 1x, 2x and 3x your horizon with the observed ratio against root-t's prediction, plus skew and excess kurtosis so you can see how far from Gaussian this symbol is at this horizon.
Alerts fire when price leaves the zone that was supposed to hold it half the time.
HOW TO USE IT
Set the horizon in bars — it means whatever your timeframe means. 24 bars on 1H is a day, 30 bars on 1D is a month. Give it as much history as the chart has. Then read the independent window count before you read anything else.
Works on any symbol and any timeframe. Nothing is hard-coded to a particular market.
WHAT IT DOES NOT DO
It says nothing about direction. There is no signal here and no entry. It is a description of uncertainty, measured rather than assumed.
Educational content - not financial advice. Indicatore
NeuPortal Forecast - sealed distributions not pathsDraws a forecast as a DISTRIBUTION at a stated horizon, never as a path.
What it plots, from values you enter yourself:
- median for the horizon
- core 50% zone (25th to 75th percentile of the asset's own historical moves over the same horizon)
- wide 80% band (10th to 90th percentile)
- the seal: a vertical line at the bar the forecast was fixed on, so left of it is observed and right of it was unknown
- an explicit invalidation level
- a computed daily read (ADX, DI, RSI, MACD, %B, EMA structure, ATR) taken from the chart itself, so the table cannot drift from the price it sits on
There is deliberately no diagonal anywhere. A line drawn from today's price to a future price is read as a claimed route, and a distribution at a horizon is not a route. The size of the expected move is stated as a vertical dimension bracket instead.
Two ways to feed it. Fill the inputs by hand, or paste a single line into "Today's line" in the first settings group, in the form key=value;key=value - useful if you generate forecasts programmatically and do not want to retype twenty fields daily. Pasted values win, missing ones fall back to the manual inputs.
Free, open source, no gating, no signals, no DMs.
Educational content - not financial advice. Indicatore
Indicatore
Position Arrow (P/L %)Visualize your open positions' gain/loss at a glance.
This indicator draws a vertical arrow from your purchase price to the current price, to the right of the last candle, with a label showing your profit/loss as a percentage — and in USD if you enter a quantity.
HOW IT WORKS
Enter up to 8 positions in the settings (symbol, purchase price, and optional quantity). The indicator only displays on a chart whose symbol matches one of your slots, so you can add it once to your layout and it follows you across your portfolio's charts.
FEATURES
- Arrow from entry price to current price, pointing up (gain) or down (loss)
- Label shows P/L % and total gain/loss in USD when quantity is set
- Auto-contrast label text (black/white chosen by arrow color brightness)
- Customizable arrow color, line width, label size, and distance from the last candle
HOW TO USE
1. Add the indicator to your chart
2. Open Settings and fill in a symbol (e.g. AAPL), your purchase price, and optionally quantity
3. The arrow and P/L label appear to the right of the latest candle whenever that symbol's chart is open
Written in Pine Script v6. Open source — feel free to reuse and adapt. Indicatore
Adjustable Monthly OpEx & Triple Witching - Spectre TradesThe Adjustable Monthly OpEx & Triple Witching indicator is designed to help traders quickly identify important equity-index expiration dates directly on their chart.
The indicator automatically marks the third Friday of each month, which is the traditional expiration date for many monthly stock and index options. It also separately identifies the quarterly expiration dates that occur in March, June, September, and December. These quarterly dates are commonly associated with triple witching and can involve increased trading volume, contract rollover activity, institutional rebalancing, option hedging, and sudden changes in volatility.
Rather than predicting market direction, this indicator provides visual context. Expiration sessions can produce price pinning near major option strikes, sharp reversals, compressed price action, stop runs, or late-session volatility. Traders should continue to rely on their normal market structure, liquidity, volume, and price-action confirmation before entering a trade.
The indicator is highly customizable. Users can independently adjust the appearance of regular monthly OpEx sessions and quarterly triple-witching sessions. Background colors, transparency, labels, label wording, text size, marker position, vertical lines, session highlighting, time zone, alerts, and individual month visibility can all be modified through the indicator settings.
For futures traders, the indicator uses the trading session’s closing date so that an overnight session beginning Thursday evening can still be associated with the correct Friday expiration date. This makes it especially useful for ES, MES, NQ, and MNQ charts.
The indicator is best used as a market-awareness tool. On expiration days, traders may consider reducing position size, waiting for stronger confirmation, avoiding assumptions about directional bias, and being more selective around major liquidity levels and round-number prices.
This indicator does not provide buy or sell signals and should not be used as a standalone trading system. It is intended to highlight dates when expiration-related positioning may influence normal price behavior.
Indicatore
TargetExcursionQueueLibLibrary "TargetExcursionQueueLib"
helper lib for targetExcursionLib
f_queue_new(horizon)
Construct a fixed ring. Horizon is clamped to the supported 1..198 range.
Parameters:
horizon (int)
method advance(queue, pathHigh, pathLow, pathClose, pathValid, currentBar)
Update every unresolved path with this confirmed chart bar and
resolve the oldest origin exactly H chart bars after it was accepted.
Invalid path bars invalidate the affected target instead of hiding a gap.
Namespace types: PendingQueue
Parameters:
queue (PendingQueue)
pathHigh (float)
pathLow (float)
pathClose (float)
pathValid (bool)
currentBar (int)
method enqueue(queue, direction, origin, scale, currentBar)
Freeze one valid, non-neutral origin after older origins have advanced.
Namespace types: PendingQueue
Parameters:
queue (PendingQueue)
direction (int)
origin (float)
scale (float)
currentBar (int)
PendingOrigin
Fields:
originBar (series int)
resolutionBar (series int)
direction (series int)
origin (series float)
scale (series float)
maxHigh (series float)
minLow (series float)
pathComplete (series bool)
ResolvedExcursion
Fields:
resolved (series bool)
valid (series bool)
timingExact (series bool)
originBar (series int)
resolutionBar (series int)
direction (series int)
origin (series float)
scale (series float)
mae (series float)
mfe (series float)
closeReturn (series float)
directionalCloseReturn (series float)
PendingQueue
Fields:
slots (array)
capacity (series int)
horizon (series int)
readHead (series int)
writeHead (series int)
count (series int)
acceptedCount (series int)
resolvedCount (series int)
invalidResolvedCount (series int)
lastResolvedBar (series int) Libreria
