XAUUSD Macro Anomaly Pulses (Chart XAU) - sudoXAUUSD Macro Anomaly Pulses
A simple pulse indicator that highlights when XAUUSD moves in a way that macro conditions cannot fully explain
Overview
This indicator marks candles on XAUUSD that behave differently than what the broader market suggests should happen.
Instead of looking at XAUUSD alone, this tool compares gold’s actual movement to an expected movement based on:
Other gold cross pairs (XAUJPY, XAUAUD, XAUCHF)
The U.S. Dollar Index (DXY), inverted
The US30 index (Dow Jones)
When XAUUSD moves much stronger or weaker than this macro-based expectation, the indicator plots a small pulse (a circle) directly on the candle.
Purpose
This indicator helps you quickly see when a candle on XAUUSD is acting “out of character” compared to normal macro flow. In other words:
“Did XAUUSD move in a way that makes sense with the rest of the market, or did something weird happen?”
These unusual moves often signal:
Liquidity grabs
Stop hunts
News-driven spikes
False breakouts
Front-running of macro shifts
How It Works
It reads the XAUUSD candles directly from the chart.
This ensures pulses stick to your candles correctly.
It pulls data from basket legs (XAUJPY, XAUAUD, XAUCHF) and macro symbols (DXY, US30) using security calls.
It converts each symbol into a simple % return per candle.
It builds an “expected” gold move using weighted inputs:
Average return of gold crosses
Inverse return of DXY
Return of US30
It calculates the “residual,” which means:
actual XAU return - expected macro return
It turns that into a Z-score to measure how extreme the deviation is.
If the Z-score is too high or too low, the script marks the candle:
Aqua pulse below bar = unusually strong move
Fuchsia pulse above bar = unusually weak move
How to Interpret the Pulses
Aqua Pulse (below candle) – Bullish anomaly
XAUUSD moved stronger than the macro environment suggests.
Meaning:
-Possible liquidity grab upward
-Possible early trend move
-Possible false breakout
-Price may be overreacting
Fuchsia Pulse (above candle) – Bearish anomaly
XAUUSD moved weaker than expected.
Meaning:
-Possible liquidity sweep downward
-Possible aggressive sell-side event
-Possible exhaustion
-Price may be taking liquidity before reversing
Typical Use Cases
-Spot moments when gold acts independently of macro
-Identify candles that might signal a reversal or a trap
-Confirm whether a breakout is real or suspicious
-Filter trades by macro alignment
-Help understand when XAUUSD is reacting to news or liquidity instead of fundamentals
Inputs Explained
- Z-score Lookback – How many candles are considered normal behavior
- Z-threshold – How extreme a move must be before it is marked
- Basket / DXY / US30 weights – How much influence each macro component has
Indicadores y estrategias
BTC Mon 8am Buy / Wed 2pm Sell (NY Time, Daily + Intraday)This strategy implements a fixed weekly time-based trading schedule for Bitcoin, using New York market hours as the reference clock. It is designed to test whether a consistent pattern exists between early-week accumulation and mid-week distribution in BTC price behavior.
Entry Rule — Monday 8:00 AM (NY Time)
The strategy enters a long position every Monday at exactly 08:00 AM Eastern Time, one hour after the U.S. equities market pre-open activity begins influencing global liquidity.
This timing attempts to capture early-week directional moves in Bitcoin, which sometimes occur as traditional markets come online.
Exit Rule — Wednesday 2:00 PM (NY Time)
The strategy closes the position every Wednesday at 2:00 PM Eastern Time, a point in the week where:
U.S. equity markets are still open
BTC often experiences mid-week volatility rotations
Liquidity is generally high
This exit removes exposure before later-week uncertainty and gives a consistent, measurable time window for each trade.
Timeframe Compatibility
Works on intraday charts (recommended 1h or lower) using precise time-based triggers.
Also runs on daily charts, where entries and exits occur on the Monday and Wednesday bars respectively (daily charts cannot show intraday timestamps).
All timestamps are synced to America/New_York regardless of the exchange’s native timezone.
Trading Frequency
Exactly one trade per week, preventing overtrading and allowing comparison of weekly performance across years of historical BTC price data.
Purpose of the Strategy
This is not a value-based or trend-following system, but a behavioral/time-cycle analysis tool.
It helps evaluate whether a repeating short-term edge exists based solely on:
Weekday timing
Liquidity cycles
Institutional market influence
BTC’s habitual early-week momentum patterns
It is ideal for:
Backtesting weekly BTC behavior
Studying time-based edges
Comparing alternative weekday/time combinations
Visualizing weekly P&L structure
Risk Notes
This strategy does not attempt to predict price direction and should not be assumed profitable without robust backtesting.
Time-based edges can appear, disappear, or invert depending on macro conditions.
There is no stop loss or risk management included by default, so the strategy reflects raw timing-based performance.
RSI Analytic Volume Matrix [RAVM] Overview
RSI Analytic Volume Matrix is an overlay indicator that turns classic RSI into a multi-layered market-reading engine. Instead of treating RSI 30 and 70 as simple buy/sell lines, RAVM combines RSI geometry (angle and acceleration), statistical volume analysis, and a 5×5 VSA-inspired matrix to describe what is really happening inside each candle.
The script is designed as an educational and analytical tool. It does not generate trading signals. Instead, it helps you read the market context, understand where the pressure is coming from (buyers vs. sellers), and see how price, momentum, and volume interact in real time.
Concept & Philosophy
RAVM is built around a hierarchical logic and a few core ideas:
• Hierarchical State Machine: First, RSI defines a context (where we are in the 0–100 range). Then the geometric engine evaluates the angle-of-turn of RSI using a Z-Score. Only after a meaningful geometric event is detected does the system promote a bar to a potential setup (warning vs. confirmed).
• Geometric Primacy: The angle and acceleration of RSI (RSI geometry) are more important than the raw RSI level itself. RAVM uses a geometric veto: if the geometric trigger is not confirmed, the confidence score is capped below 50%, even if volume looks interesting.
• RSI Beyond 30 and 70: Being above 70 or below 30 is not treated as an automatic overbought/oversold signal. RAVM treats those zones as contextual factors that contribute only a partial portion of the final score, alongside geometry, total volume expansion, buy/sell balance, and delta power.
• Volume Decomposition: Volume is decomposed into total, buy-side, sell-side, and delta components. Each of these is normalized with a Z-Score over a shared statistical window, so RSI geometry and volume live in the same statistical context.
• Educational Scoring Pipeline: RAVM builds a 0–100 "Quantum Score" for each detected setup. The score expresses how strong the story is across four dimensions: geometry (RSI angle-of-turn), total volume expansion, which side is driving that volume (buyers vs. sellers), and the power of delta. The score is designed for learning and weighting, not for mechanical trade entries.
• VSA Matrix Engine: A 5×5 matrix combines momentum states and volume dynamics. Each cell corresponds to an interpreted VSA-style scenario (Absorption, Distribution, No Demand, Stopping Volume, Strong Reversal, etc.), shown both as text and as a heatmap dashboard on the chart.
How RAVM Works
1. RSI Context & Geometry
RAVM starts with a classic RSI, but it does not stop at simple level checks. It computes the velocity and acceleration of RSI and normalizes them via a Z-Score to produce an Angle-of-Turn metric (Z-AoT). This Z-AoT is then mapped into a 0–1 intensity value called MSI (Momentum Shift Intensity).
The script monitors both classic RSI zones (around 30 and 70) and geometric triggers. Entering the lower or upper zone is treated as a contextual event only. A setup becomes "confirmed" when a significant geometric turn is detected (based on Z-AoT thresholds). Otherwise, the bar is at most a warning.
2. Volume & Statistical Engine
The volume engine can work in two modes: a geometric approximation (based on candle structure) or a more precise intrabar mode using up/down volume requests. In both cases, RAVM builds a volume packet consisting of:
• Total volume
• Buy-side volume
• Sell-side volume
• Delta (buy – sell)
Each of these series is normalized using a Z-Score over the same statistical window that is used for RSI geometry. This allows RAVM to answer questions such as: Is total volume exceptional on this bar? Is the expansion mostly coming from buyers or from sellers? Is delta unusually strong or weak compared to recent history?
3. Scoring System (Quantum Score)
For each bar where a setup is active, RAVM computes a 0–100 score intended as an educational confidence measure. The scoring pipeline follows this sequence:
A. RSI Geometry (MSI): Measures the strength of the RSI angle-of-turn via Z-AoT. This has geometric primacy over simple level checks.
B. RSI Zone Context: Being below 30 or above 70 contributes only a partial bonus to the score, reflecting the idea that these zones are context, not automatic signals. Mildly supportive zones (e.g., RSI below 50 for bullish contexts) can also contribute with lower weight.
C. Total Volume Expansion: A normalized Volume Power term expresses how exceptional the total volume is relative to its recent distribution. If there is no meaningful volume expansion, the score remains modest even if RSI geometry looks interesting.
D. Which Side Is Driving the Volume: RAVM then checks whether the expansion is primarily on the buy side or the sell side, using Z-Score statistics for buy and sell volume separately. This stage does not yet rely on delta as a power metric; it simply answers the question: "Is this expansion mostly driven by buyers, sellers, or both?"
E. Delta as Final Power: Only at the final stage does the script bring in delta and its Z-Score as a measure of how one-sided the pressure really is. A strong negative delta during a bullish context, for example, can highlight absorption, while a strong positive delta against a bearish context can highlight distribution or a buying climax.
If a setup is not geometrically confirmed (for example, a simple entry into RSI 30/70 without a strong geometric turn), RAVM caps the final score below 50%. This "Geometric Veto" enforces the idea that RSI geometry must confirm before a scenario can be considered high-confidence.
4. Overlay UI & Smart Labels
RAVM is an overlay indicator: all information is drawn directly on the price chart, not in a separate pane. When a setup is active, a smart label is attached to the bar, together with a vertical connector line. Each label shows:
• Direction of the setup (bullish or bearish)
• Trigger type (classic OS/OB vs. geometric/hidden)
• Status (warning vs. confirmed)
• Quantum Score as a percentage
Confirmed setups use stronger colors and solid connectors, while warnings use softer colors and dotted connectors. The script also manages label placement to avoid overlap, keeping the chart clean and readable.
In addition to labels, a dashboard table is drawn on the chart. It displays the currently active matrix scenario, the dominant bias, a short textual interpretation, the full 5×5 heatmap, and summary metrics such as RSI, MSI, and Volume Power.
RSI Is Not Just 30 and 70
One of the central design decisions in RAVM is to treat RSI 30 and 70 as context, not as fixed buy/sell buttons. Many traders mechanically assume that RSI below 30 means "buy" and RSI above 70 means "sell". RAVM explicitly rejects this simplification.
Instead, the script asks a series of deeper questions: How sharp is the angle-of-turn of RSI right now? Is total volume expanding or contracting? Is that expansion dominated by buyers or sellers? Is delta confirming the move, or is there a hidden absorption or distribution taking place?
In the scoring logic, being in a lower or upper RSI zone contributes only part of the final score. Geometry, volume expansion, the buy/sell split, and delta power all have to align before a high-confidence scenario emerges. This makes RAVM much closer to a structured market-reading tool than a classic overbought/oversold indicator.
Matrix User Manual – Reading the 5×5 Grid
The heart of RAVM is its 5×5 matrix, where the vertical axis represents momentum states (M1–M5) and the horizontal axis represents volume dynamics (V1–V5). Each cell in this grid corresponds to a VSA-style scenario. The dashboard highlights the currently active cell and prints a textual description so you can read the story at a glance.
1. Confirmation Scenarios
These scenarios occur when momentum direction and volume expansion are aligned:
• Bullish Confirmation / Strong Reversal: Momentum is shifting strongly upward (often from a depressed RSI context), and expanded volume is driven mainly by buyers. Often seen as a strong bullish reversal or continuation signal from a VSA perspective.
• Bearish Confirmation / Strong Drop: Momentum is turning decisively downward, and expanded volume is driven mainly by sellers. This maps to strong bearish continuation or sharp reversal patterns.
2. Absorption & Stopping Volume
• Absorption: Total volume expands, but the dominant flow is opposite to the recent price move or the geometric bias. For example, heavy selling volume while the geometric context is bullish. This can indicate smart money quietly absorbing orders from the crowd.
• Stopping Volume: Exceptionally high volume appears near the end of an extended move, while momentum begins to decelerate. Price may still print new extremes, but the effort vs. result relationship signals potential exhaustion and the possibility of a turn.
3. Distribution & Buying Climax
• Distribution: Heavy buying volume appears within a bearish or topping context. Rather than healthy accumulation, this often represents larger players offloading inventory to late buyers. The matrix will typically flag this as a bearish-leaning scenario despite strong upside prints.
• Buying Climax: A surge of buy-side volume near the end of a strong uptrend, with momentum starting to weaken. From a VSA point of view, this is often the last push where retail aggressively buys what smart money is selling.
4. No Demand & No Supply
• No Demand: Price attempts to rise but does so on low, non-expansive volume. The market is not interested in following the move, and the lack of participation often precedes weakness or sideways action.
• No Supply: Price tries to push lower on thin volume. Selling pressure is limited, and the lack of supply can precede stabilization or recovery if buyers step back in.
5. Trend Exhaustion
• Uptrend Exhaustion: Momentum remains nominally bullish, but the quality of volume deteriorates (e.g., more effort, less net result). The matrix marks this as an uptrend losing internal strength, often after a series of aggressive moves.
• Downtrend Exhaustion: Similar logic in the opposite direction: strong prior downtrend, but increasingly inefficient downside progress relative to the volume invested. This can precede accumulation or a relief rally.
6. Effort vs. Result Scenarios
• Bullish Effort, Little Result: Buyers invest notable volume, but price progress is limited. This may reveal hidden selling into strength or a lack of follow-through from the broader market.
• Bearish Effort, Little Result: Sellers push volume, but price does not decline proportionally. This can indicate absorption of selling pressure and potential underlying demand.
7. Neutral, Churn & Thin Markets
• Neutral / Thin Market: Momentum and volume both remain muted. RAVM marks these as neutral cells where aggressive decision-making is usually less attractive and observing the broader structure is more important.
• High Volume Churn / Volatility: Both sides are active with high volume but limited directional progress. This can correspond to battle zones, local ranges, or high volatility rotations where the main message is conflict rather than clear trend.
Inputs & Options
RAVM includes several input groups to adapt the tool to your preferences:
• Localization: Multiple language options for all labels and dashboard text (e.g., English, Farsi, Turkish, Russian).
• RSI Core Settings: RSI length, source, and upper/lower contextual zones (typically around 30 and 70).
• Geometric Engine: Z-AoT sigma thresholds, confirmation ratios, and normalization window multiplier. These control how sensitive the script is to RSI angle-of-turn events.
• Volume Engine: Choice between geometric approximation and intrabar up/down volume, Z-Score thresholds for volume expansion, and related parameters.
• Visual Interface: Toggles for smart labels, dashboard table, font sizes, dashboard position, and color themes for bullish, bearish, and warning states.
Disclaimer
RSI Analytic Volume Matrix is provided for educational and research purposes only. It does not constitute financial advice and is not a signal generator. Any trading decisions you make based on this tool, or any other, are entirely your own responsibility. Always consider your own risk management rules and conduct your own analysis.
MSSM – Multi-Session Structural Map (Precision Sweeps)MSSM – Multi-Session Structural Map (Precision Sweeps)
This indicator provides a structured view of the market based on four key components:
1). Previous session levels
2). Confirmed fractal swing points
3). Volume pocket highlights
4). Non-repainting precision liquidity sweep markers
It is designed to help analyze how price interacts with important reference areas and structural points. This tool does not generate signals or predictions. All information is visual and educational only.
HOW THE INDICATOR WORKS
PREVIOUS SESSION LEVELS
The script plots the previous session’s High, Low, and Mid. These levels help observe how the current session behaves around the prior day’s range. They act as reference areas only.
FRACTAL SWING MAP (NON-REPAINTING)
Confirmed fractals are used to mark historical swing highs and swing lows. Since fractals confirm after a certain number of bars, the swings do not repaint once formed. These swings provide a clearer view of market structure.
VOLUME POCKETS
The indicator highlights areas where volume expands relative to a rolling volume average. These regions show increased participation or activity. The highlights are informational and do not imply direction.
PRECISION LIQUIDITY SWEEPS (NON-REPAINTING)
A sweep is tagged only when:
• Price trades beyond a confirmed swing high or swing low
• Price closes back inside the previous swing level
• A wick rejection occurs
• Volume expands relative to a recent rolling average
These markers simply show where price interacted with liquidity around prior structural levels. They do not indicate a trading signal or bias.
HOW TO ADD THE INDICATOR
Open the Pine Editor in TradingView
Search the indicator name and add to favorites.
Click “Add to chart”
Adjust settings as needed (fractals, sweeps, volume pockets, or session levels)
HOW TO READ AND USE THE INDICATOR
SESSION LEVELS
Observe whether price respects, rejects, compresses around, or expands beyond the previous session high, low, or midpoint. These are observational reference levels only.
FRACTALS
Fractal highs and lows help visualize structural turning points. They provide a clearer picture of where liquidity may rest above or below past swing levels.
VOLUME POCKETS
When volume expands compared to the recent average, the candle is shaded. These areas may show increased participation, but no directional meaning is implied.
PRECISION SWEEPS
Sweeps highlight when price reaches beyond a prior confirmed swing level and then rejects that area with displacement. These markers identify interactions with liquidity, but they are not signals and do not forecast future outcomes.
CUSTOMIZATION OPTIONS
Users can adjust:
• Session level visibility
• Fractal sensitivity
• Volume pocket threshold
• Sweep sensitivity and visibility
• Transparency and styling
This makes the tool flexible across different symbols and timeframes.
IMPORTANT NOTES AND POLICY COMPLIANCE
• The indicator does not provide buy or sell signals
• The indicator does not predict price or direction
• All plotted elements are based on past price behavior
• All components are informational only
• Users should perform their own analysis and risk evaluation
• Past behavior does not guarantee future performance
SUMMARY
MSSM provides a structured view of price by combining previous session levels, confirmed swing structure, volume expansion zones, and non-repainting sweep identification. Its purpose is to assist traders in visually analyzing market structure while staying fully aligned with TradingView’s House Rules and content policies.
Kalman Ema Crosses - [JTCAPITAL]Kalman EMA Crosses - is a modified way to use Kalman Filters applied on Exponential Moving Averages (EMA Crosses) for Trend-Following.
Credits for the kalman function itself goes to @BackQuant
The Kalman filter is a recursive smoothing algorithm that reduces noise from raw price or indicator data, and in this script it is applied both directly to price and on top of EMA calculations. The goal is to create cleaner, more reliable crossover signals between two EMAs that are less prone to false triggers caused by volatility or market noise.
The indicator works by calculating in the following steps:
Source Selection
The script starts by selecting the price input (default is Close, but can be adjusted). This chosen source is the foundation for all further smoothing and EMA calculations.
Kalman Filtering on Price
Depending on user settings, the selected source is passed through one of two independent Kalman filters. The filter takes into account process noise (representing expected market randomness) and measurement noise (representing uncertainty in the price data). The Kalman filter outputs a smoothed version of price that minimizes noise and preserves underlying trend structure.
EMA Calculation
Two exponential moving averages (EMA 1 and EMA 2) are then computed on the Kalman-smoothed price. The lengths of these EMAs are fully customizable (default 15 and 25).
Kalman Filtering on EMA Values
Instead of directly using raw EMA curves, the script applies a second layer of Kalman filtering to the EMA values themselves. This step significantly reduces whipsaw behavior, creating smoother crossovers that emphasize real momentum shifts rather than temporary volatility spikes.
Trend Detection via EMA Crossovers
-A bullish trend is detected when EMA 1 (fast) crosses above EMA 2 (slow).
-A bearish trend is detected when EMA 1 crosses below EMA 2.
The detected trend state is stored and used to dynamically color the plots.
Visual Representation
Both EMAs are plotted on the chart. Their colors shift to blue during bullish phases and purple during bearish phases. The area between the two EMAs is filled with a shaded region to clearly highlight trending conditions.
Buy and Sell Conditions:
-Buy Condition: When the Kalman-smoothed EMA 1 crosses above the Kalman-smoothed EMA 2, a bullish crossover is confirmed.
-Sell Condition: When EMA 1 crosses below EMA 2, a bearish crossover is confirmed.
Users may enhance the robustness of these signals by adjusting process noise, measurement noise, or EMA lengths. Lower measurement noise values make the filter react faster (but potentially noisier), while higher values make it smoother (but slower).
Features and Parameters:
-Source: Selectable price input (Close, Open, High, Low, etc.).
-EMA 1 Length: Defines the fast EMA period.
-EMA 2 Length: Defines the slow EMA period.
-Process Noise: Controls how much randomness the Kalman filter assumes in price dynamics.
-Measurement Noise: Controls how much uncertainty is assumed in raw input data.
-Kalman Usage: Option to apply Kalman filtering either before EMA calculation (on price) or after (on EMA values).
Specifications:
Kalman Filter
The Kalman filter is an optimal recursive algorithm that estimates the state of a system from noisy measurements. In trading, it is used to smooth prices or indicator values. By balancing process noise (expected volatility) with measurement noise (data uncertainty), it generates a smoothed signal that reacts adaptively to market conditions.
Exponential Moving Average (EMA)
An EMA is a weighted moving average that emphasizes recent data more heavily than older data. This makes it more responsive than a simple moving average (SMA). EMAs are widely used to identify trends and momentum shifts.
EMA Crossovers
The crossing of a fast EMA above a slow EMA suggests bullish momentum, while the opposite suggests bearish momentum. This is a cornerstone technique in trend-following systems.
Dual Kalman Filtering
Applying Kalman both to raw price and to the EMAs themselves reduces whipsaws further. It creates crossover signals that are not only smoothed but also validated across two levels of noise reduction. This significantly enhances signal reliability compared to traditional EMA crossovers.
Process Noise
Represents the filter’s assumption about how much the underlying market can randomly change between steps. Higher values make the filter adapt faster to sudden changes, while lower values make it more stable.
Measurement Noise
Represents uncertainty in price data. A higher measurement noise value means the filter trusts the model more than the observed data, leading to smoother results. A lower value makes the filter more reactive to observed price fluctuations.
Trend Coloring & Fill
The use of dynamic colors and filled regions provides immediate visual recognition of trend states, helping traders act faster and with greater clarity.
Enjoy!
PDH/PDL Sweep & Rejection - sudoPDH/PDL Sweep + Rejection
This indicator identifies classic liquidity sweeps of the previous day's high or low, then confirms whether price rejected that level with force. It is built to highlight moments when the market takes liquidity and immediately snaps back in the opposite direction, a behavior often linked to failed breakouts, engineered stops, or clean reversals. The tool marks these events directly on the chart so you can see them without manually watching the daily levels.
What it detects
The indicator focuses on two events:
PDH sweep and rejection
Price breaks above the previous day's high, overshoots the level by a meaningful amount, and then closes back below the high.
PDL sweep and rejection
Price breaks below the previous day's low, overshoots, and then closes back above the low.
These are structural liquidity events, not random wicks. The script checks for enough overshoot and strong bar range to confirm it was a genuine stop grab rather than noise.
How it works
The indicator evaluates each bar using the following logic:
1. Previous day levels
It pulls yesterday's high and low directly from the daily timeframe. These act as the PDH and PDL reference points for intraday trading.
2. Overshoot measurement
After breaking the level, price must push far enough beyond it to qualify as a sweep. Instead of using arbitrary pips, the required overshoot is scaled relative to ATR. This keeps the logic stable across different assets and volatility conditions.
3. Range confirmation
The bar must be larger than normal compared to ATR. This ensures the sweep happened with momentum and not because of small, choppy price movement.
4. Rejection close
A valid signal only prints if price closes back inside the previous day's range.
For a PDH sweep, the bar must close below PDH.
For a PDL sweep, the bar must close above PDL.
This confirms a failed breakout and a rejection.
What gets placed on the chart
Red downward triangle above the bar: Previous Day High sweep and rejection
Lime upward triangle below the bar: Previous Day Low sweep and rejection
The markers appear exactly on the bar where the sweep and rejection occurred.
How traders can use this
Identify potential reversals
Sweeps often occur when algorithms target liquidity pools. When followed by a strong rejection, the market may be preparing for a reversal or rotation.
Avoid chasing breakouts
A clear sweep warns that a breakout attempt failed. This can prevent traders from entering at the worst possible location.
Time entries at extremes
The markers help you see where the market grabbed stops and immediately turned. These areas can become high quality entry zones in both trend continuation and countertrend setups.
Support liquidity based models
The indicator aligns naturally with trading frameworks that consider liquidity, displacement, failed breaks, and microstructure shifts.
Add confidence to confluence-based setups
Combine sweeps with displacement, FVGs, or higher timeframe levels to refine entry timing.
Why this indicator is helpful
It automates a pattern that traders often identify manually. Sweeps are easy to miss in fast markets, and this tool eliminates the need to constantly monitor daily levels. By marking only the events that show overshoot plus rejection plus significant range, it filters out the weak or false signals and leaves only meaningful liquidity events.
Displacement Pulse Markers - sudoThis indicator is designed to highlight sudden and meaningful bursts of price movement. These bursts are called displacement pulses. A pulse appears when price expands with force, closes near the extreme of its own bar, and breaks through a recent structural level. The indicator places small circles above or below the candle to signal these moments so that traders can quickly spot abnormal movement and potential shifts in market intent.
How it works
The indicator evaluates each bar for three conditions:
Range expansion relative to volatility
The bar must be larger than normal. It compares the bar range to ATR and requires that range to exceed a multiple of ATR. When this condition is met, the bar is considered a large or forceful bar.
Close location within the bar
The bar has to close near its own high or low. A close near the top suggests strong buying force. A close near the bottom suggests strong selling force. The user can adjust what percentage qualifies as near the top or bottom.
Break of recent structure
The bar must break a recent pivot level. For bullish pulses, the high of the bar must exceed the highest high of the past N bars. For bearish pulses, the low must break the lowest low of the past N bars. This confirms that the move did not merely expand but actually displaced prior structure.
When all conditions align
A bullish displacement pulse is marked with a small aqua circle below the bar.
A bearish displacement pulse is marked with a fuchsia circle above the bar.
The result is a clean on chart visualization of where price produced meaningful displacement.
How traders can use this
Spot abnormal momentum
Pulses can highlight areas where price behaves with more force than usual. These events often appear around news, liquidity sweeps, or algorithmic shifts.
Identify possible regime changes
A pulse that breaks structure while closing near the extreme may signal a transition from a ranging environment to a trending one. It does not predict direction but flags where displacement actually occurred.
Support narrative building
When combined with levels, zones, or other frameworks, pulses can confirm whether the market had enough strength to break through an area with conviction.
Filter trades or refine entries
Some traders may choose to trade in the direction of recent pulses during trending conditions. Others may only enter a trade after a pulse confirms that the market has shifted away from compression.
Track where the market is imbalanced
A pulse visually marks whether buyers or sellers were able to generate strong initiative movement. These points often become useful reference zones for continuation or rejection analysis.
Why this indicator is useful
It reduces complex logic into simple visual markers. Instead of scanning bar by bar for structural breaks, volatility expansions, and close strength, the indicator does this automatically and highlights only the bars that meet all criteria. This keeps the chart clean while still providing precision about where displacement actually occurred.
Hash Pivot DetectorHash Pivot Detector
Professional Support & Resistance Detection with Multi-Timeframe Zone Analysis
Developed by Hash Capital Research, the Hash Pivot Detector is a sophisticated indicator designed for identifying key support and resistance levels using pivot-based detection with institutional-grade zone analysis.
Key Features
Zone-Based Detection
Unlike traditional single-line S/R indicators, Hash Pivot Detector uses configurable zones around pivot levels to represent realistic institutional order areas. Adjustable zone width accommodates different asset volatilities.
Multi-Timeframe Analysis
Displays higher timeframe support/resistance levels alongside current timeframe pivots, providing crucial context for institutional positioning and stronger price barriers.
Clean Visual Design
Features Hash Capital's signature fluorescent color scheme (pink resistance, cyan support) optimized for dark charts with high contrast and instant visual recognition. Semi-transparent zones keep your chart clean and readable.
How It Works
The indicator uses pivot high/low detection with configurable left and right bar parameters. When a pivot is confirmed, it plots:
Primary support/resistance lines at pivot levels
Semi-transparent zones representing realistic order areas
Higher timeframe S/R levels as crosses for additional context
Recommended Settings
For Swing Trading:
Pivot Bars: 10-20 left/right
Zone Width: 0.5-1.0%
HTF: Daily (on 1H-4H charts)
For Intraday Trading:
Pivot Bars: 5-10 left/right
Zone Width: 0.3-0.5%
HTF: 1H or 4H (on 5min-15min charts)
Asset-Specific Zone Width:
Forex/Crypto: 0.3-0.5%
Stocks: 0.5-1.0%
Volatile Assets: 1.0-2.0%
What Makes It Different
✓ Zone-based approach (more realistic than lines)
✓ Multi-timeframe confluence detection
✓ Minimal visual clutter with maximum information
✓ Professional institutional aesthetic
✓ Comprehensive tooltips for easy optimization
✓ No repainting - all pivots are confirmed
Best Used For
Identifying high-probability entry/exit zones
Setting stop-loss and take-profit levels
Recognizing breakout/breakdown areas
Multi-timeframe confluence analysis
Swing trading and position trading
Intraday scalping with adjusted parameters
Notes
Works on all timeframes and markets
Fully customizable colors and parameters
All settings include detailed optimization guidance
Clean code, efficient performance
No alerts or notifications (visual analysis only)
Linear Trajectory & Volume StructureThe Linear Trajectory & Volume Structure indicator is a comprehensive trend-following system designed to identify market direction, volatility-adjusted channels, and high-probability entry points. Unlike standard Moving Averages, this tool utilizes Linear Regression logic to calculate the "best fit" trajectory of price, encased within volatility bands (ATR) to filter out market noise.
It integrates three core analytical components into a single interface:
Trend Engine: A Linear Regression Curve to determine the mean trajectory.
Volume Verification: Filters signals to ensure price movement is backed by market participation.
Market Structure: Identifies previous high-volume supply and demand zones for support and resistance analysis.
2. Core Components and Logic
The Trajectory Engine
The backbone of the system is a Linear Regression calculation. This statistical method fits a straight line through recent price data points to determine the current slope and direction.
The Baseline: Represents the "fair value" or mean trajectory of the asset.
The Cloud: Calculated using Average True Range (ATR). It expands during high volatility and contracts during consolidation.
Trend Definition:
Bullish: Price breaks above the Upper Deviation Band.
Bearish: Price breaks below the Lower Deviation Band.
Neutral/Chop: Price remains inside the cloud.
Smart Volume Filter
The indicator includes a toggleable volume filter. When enabled, the script calculates a Simple Moving Average (SMA) of the volume.
High Volume: Current volume is greater than the Volume SMA.
Signal Validation: Reversal signals and structure zones are only generated if High Volume is present, reducing the likelihood of trading false breakouts on low liquidity.
Volume Structure (Smart Liquidity)
The script automatically plots Support (Demand) and Resistance (Supply) boxes based on pivot points.
Creation: A box is drawn only if a pivot high or low is formed with High Volume (if the volume filter is active).
Mitigation: The boxes extend to the right. If price breaks through a zone, the box turns gray to indicate the level has been breached.
3. Signal Guide
Trend Reversals (Buy/Sell Labels)
These are the primary signals indicating a potential change in the macro trend.
BUY Signal: Appears when price closes above the upper volatility band after previously being in a downtrend.
SELL Signal: Appears when price closes below the lower volatility band after previously being in an uptrend.
Pullbacks (Small Circles)
These are continuation signals, useful for adding to positions or entering an existing trend.
Long Pullback: The trend is Bullish, but price dips momentarily below the baseline (into the "discount" area) and closes back above it.
Short Pullback: The trend is Bearish, but price rallies momentarily above the baseline (into the "premium" area) and closes back below it.
4. Configuration and Settings
Trend Engine Settings
Trajectory Length: The lookback period for the Linear Regression. This is the most critical setting for tuning sensitivity.
Channel Multiplier: Controls the width of the cloud.
1.0: Aggressive. Results in narrower bands and earlier signals, but more false positives.
1.5: Balanced (Default).
2.0+: Conservative. Creates a wide channel, filtering out significant noise but delaying entry signals.
Signal Logic
Show Trend Reversals: Toggles the main Buy/Sell labels.
Show Pullbacks: Toggles the re-entry circle signals.
Smart Volume Filter: If checked, signals require above-average volume. Unchecking this yields more signals but removes the volume confirmation requirement.
Volume Structure
Show Smart Liquidity: Toggles the Support/Resistance boxes.
Structure Lookback: Defines how many bars constitute a pivot. Higher numbers identify only major market structures.
Max Active Zones: Limits the number of boxes on the chart to prevent clutter.
5. Timeframe Optimization Guide
To maximize the effectiveness of the Linear Trajectory, you must adjust the Trajectory Length input based on your trading style and timeframe.
Scalping (1-Minute to 5-Minute Charts)
Recommended Length: 20 to 30
Multiplier: 1.2 to 1.5
Logic: Fast-moving markets require a shorter lookback to react quickly to micro-trend changes.
Day Trading (15-Minute to 1-Hour Charts)
Recommended Length: 55 (Default)
Multiplier: 1.5
Logic: A balance between responsiveness and noise filtering. The default setting of 55 is standard for identifying intraday sessions.
Swing Trading (4-Hour to Daily Charts)
Recommended Length: 89 to 100
Multiplier: 1.8 to 2.0
Logic: Swing trading requires filtering out intraday noise. A longer length ensures you stay in the trade during minor retracements.
6. Dashboard (HUD) Interpretation
The Head-Up Display (HUD) provides a summary of the current market state without needing to analyze the chart visually.
Bias: Displays the current trend direction (BULLISH or BEARISH).
Momentum:
ACCELERATING: Price is moving away from the baseline (strong trend).
WEAKENING: Price is compressing toward the baseline (potential consolidation or reversal).
Volume: Indicates if the current candle's volume is HIGH or LOW relative to the average.
Disclaimer
*Trading cryptocurrencies, stocks, forex, and other financial instruments involves a high level of risk and may not be suitable for all investors. This indicator is a technical analysis tool provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a guarantee of profit. Past performance of any trading system or methodology is not necessarily indicative of future results.
Correlation Scanner📊 CORRELATION SCANNER - Financial Instruments Correlation Analyzer
🎯 ORIGINALITY AND PURPOSE
Correlation Scanner is a professional tool for analyzing correlation relationships between different financial instruments. Unlike standard correlation indicators that show the relationship between only two instruments, this script allows you to simultaneously track the correlation of up to 10 customizable instruments with a selected base asset.
The indicator is designed for traders working with cross-market analysis, portfolio diversification, and searching for related assets for arbitrage strategies.
🔧 HOW IT WORKS
The indicator uses the built-in ta.correlation() function to calculate the Pearson correlation coefficient between instrument closing prices over a specified period. Mathematical foundation:
1. Correlation Calculation: for each instrument, the correlation coefficient with the base asset is calculated over N bars (default 60)
2. Results Sorting: instruments are automatically ranked by absolute correlation value (from strongest to weakest)
3. Visualization: results are displayed in a table with color coding:
- Green: positive correlation (instruments move in the same direction)
- Red: negative correlation (instruments move in opposite directions)
- Color intensity depends on correlation strength
4. Correlation Strength Classification:
- Very Strong (💪💪💪): |r| > 0.8 — very strong relationship
- Strong (💪💪): |r| > 0.6 — strong relationship
- Medium (💪): |r| > 0.4 — medium relationship
- Weak: |r| > 0.2 — weak relationship
- Very Weak: |r| ≤ 0.2 — very weak relationship
📋 SETTINGS AND USAGE
MAIN PARAMETERS:
• Main Instrument — base instrument for comparison (default TVC:DXY - US Dollar Index)
• Correlation Period — calculation period in bars (10-500, default 60)
• Number of Instruments to Display — number of instruments to show (1-10)
• Table Position — table location on the chart
INSTRUMENT CONFIGURATION:
The indicator allows configuring up to 10 instruments for analysis. For each, you can specify:
• Instrument — instrument ticker (e.g., FX_IDC:EURUSD)
• Name — display name (emojis supported)
VISUAL SETTINGS:
• Show Chart Label with Correlation — display current chart's correlation with base instrument
• Table Header Color — table header color
• Table Row Background — table row background color
💡 USAGE EXAMPLES
1. DOLLAR IMPACT ANALYSIS: set DXY as the base instrument and track how dollar index changes affect currency pairs, gold, and cryptocurrencies
2. HEDGING ASSETS SEARCH: find instruments with strong negative correlation for risk diversification
3. PAIRS TRADING: identify assets with high positive correlation to find divergences and arbitrage opportunities
4. CROSS-MARKET ANALYSIS: track relationships between stocks, bonds, commodities, and currencies
5. SYSTEMIC RISK ASSESSMENT: identify periods of increased correlation between assets, which may indicate systemic risks
⚠️ IMPORTANT NOTES
• Correlation does NOT imply causation
• Correlation can change over time — regularly review the analysis period
• High past correlation doesn't guarantee the relationship will persist in the future
• Recommended to use the indicator in combination with fundamental analysis
🔔 ALERTS
The indicator includes a built-in alert condition: triggers when strong correlation (|r| > 0.8) is detected between the current chart and the base instrument.
Matt's Multi-Timeframe MACD Direction AlertThe indicator monitors the direction of the Moving Average Convergence Divergence (MACD) lines on four specific timeframes: 1-hour, 15-minute, 5-minute, and 1-minute.
It only generates a signal when the MACD in all four timeframes is trending in the same direction (either all are bullish, or all are bearish). This alignment suggests a strong, synchronized market momentum from short-term scalping views up to immediate-term swing views.
Key Features:
Multi-Timeframe Confirmation: Uses TradingView's request.security() function to fetch data from different timeframes (1h, 15m, 5m, 1m), preventing the need to manually switch charts.
Visual Dashboard: A dashboard table is displayed on your chart, providing an immediate visual status (Bullish/Bearish/Neutral) for each of the four timeframes.
On-Chart Signals: The indicator plots visual shapes (green triangles for bullish alignment, red triangles for bearish alignment) directly on the sub-chart when the condition is met.
Custom Alert Integration: It includes a built-in alertcondition() function, allowing traders to set up real-time, hands-free notifications whenever a synchronized trading opportunity arises.
This tool helps filter out noise and potential false signals that might appear on a single timeframe, focusing instead on robust signals confirmed by a consensus of time perspectives.
Momentum Structural AnalysisMomentum Structural Analysis (MSA‑style Oscillator)
This indicator implements a simple, MSA‑style momentum oscillator that measures how far price has moved above or below its own long‑term trend on the active timeframe, expressed in percentage terms. Instead of looking at raw price, it "oscillates" price around a timeframe‑appropriate simple moving average (SMA) and plots the percentage distance from that SMA as an orange line around a zero baseline. Zero means price is exactly at its structural trend; positive values mean price is extended above trend; negative values mean it is trading below trend.
The script automatically selects the SMA length based on the chart timeframe:
On daily charts it uses the configurable Daily SMA Length (default 252 trading days, roughly 1 year).
On weekly charts it uses Weekly SMA Length (default 208 weeks).
On monthly charts it uses Monthly SMA Length (default 120 months).
This approach is inspired by the ideas behind Momentum Structural Analysis (MSA), which studies where a market trades relative to long‑term moving averages and then treats the momentum line (the oscillator) as the primary object of analysis. The goal is to highlight structural overbought/oversold conditions and regime changes that are often clearer on momentum than on the raw price chart.
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What the script computes and how it works
For each bar, the indicator:
Chooses an SMA length based on the current timeframe (daily/weekly/monthly).
Calculates the SMA of the close.
Computes the percentage distance:
\text{Diff %} = \frac{\text{Close} - \text{SMA}}{\text{SMA}} \times 100
Plots this Diff % as an orange line, with a dashed horizontal zero line as the base.
This produces a momentum oscillator that oscillates around zero and reflects the "structural" position of price versus its own long‑term mean.
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How to use it on index charts (e.g., NIFTY50)
On indices like NIFTY50, use the indicator to see how stretched the index is versus its structural trend.
Typical uses:
Identify extremes: a). Historically high positive readings can signal euphoric, late‑stage conditions where risk is elevated. b). Deep negative readings can highlight panic/capitulation zones where downside may be exhausted.
Draw structural levels: a). Mark horizontal bands on the oscillator where past turns have occurred (e.g., +15%, −10%, etc. specific to NIFTY50). b). Watch how price behaves when the oscillator revisits these zones: repeated rejections can validate them as structural bounds; clean breaks can indicate a change of regime.
This is not a buy/sell signal generator by itself; it is a framework to understand where the index sits within its long‑term momentum structure and to support risk‑management decisions.
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How to use it on ratio charts
Apply the same indicator to ratio symbols such as NIFTY50/GOLD, BANKNIFTY/NIFTY50, sector vs index, or any spread you plot as a ratio.
On a ratio chart:
The oscillator now measures relative momentum: how far that ratio is above or below its own long‑term mean.
High positive readings = strong outperformance of the numerator vs the denominator (e.g., equities strongly outperforming gold).
Deep negative readings = strong underperformance (e.g., equities structurally lagging gold).
This is very much in the spirit of MSA’s work on spreads between asset classes: it helps visualize major rotations (equities → gold, financials → commodities, etc.) and whether a relative‑performance trend is stretched, reverting, or breaking into a new phase.
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Using multiple timeframes for better decisions
You can stack information across timeframes to get a more robust view:
Monthly : a). Use monthly charts to see secular/structural phases. b). Long multi‑year stretches above or below zero, and large bases or trendline breaks on the monthly oscillator, can mark major bull or bear cycles and big rotations between asset classes.
Weekly : a). Use weekly charts for the primary trend. b). Weekly structures (multi‑month highs/lows, channels, or trendlines on the oscillator) are useful for medium‑term positioning and for confirming or rejecting signals seen on the monthly view.
Daily : a). Use daily charts mainly for timing entries/exits once the higher‑timeframe direction is clear. b). Short‑term extremes on the daily oscillator that align with the larger weekly/monthly structure can offer better‑timed opportunities, while signals that contradict higher‑timeframe momentum are more likely to be noise.
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RVol based Support & Resistance ZonesDescription:
This indicator is designed to help traders identify significant price levels based on institutional volume. It monitors two higher timeframes (defined by the user) simultaneously. When a candle on these higher timeframes exhibits unusually high volume—known as high Relative Volume (RVol)—the indicator automatically draws a "Zone of Interest" box on your current chart.
These zones are defined by:
Up candle : from candle open to low of candle
Down candle : from candle open to high of candle
Key Features:
Multi-Timeframe Monitoring: You can trade on a lower timeframe (e.g., 5-minute) while the indicator monitors the 30-minute and 1-hour charts for volume spikes.
RVol Boxes: Automatically draws boxes extending from high-volume candles.
Up Candles: Box covers Low to Open.
Down Candles: Box covers High to Open.
Live Dashboard: A neat, color-coded table displays the current Volume, Average Volume, and RVol percentage for your watched timeframes.
Real-Time vs. Confirmed: Choose whether to see boxes appear immediately as volume spikes (Live) or only after the candle has closed and confirmed the volume (Candle Close).
Settings Guide:
1. General Settings
Relative Volume Length: The number of past candles used to calculate the "Average Volume." (Default is 20).
Max Days Back to Draw: To keep your chart clean, this limits how far back in history the script looks for high-volume zones. (e.g., set to 5 to only see zones created in the last 5 days).
Draw Mode:
- Live (Real-time): Draws the box immediately if the current developing candle hits the volume threshold. (Note: The box may disappear if the volume average shifts before the candle closes).
- Candle Close: The box only appears once the candle has finished and permanently confirmed the volume spike.
2. Table Settings
Show Info Table: Toggles the dashboard on or off.
Text Size & Position: Customise where the table appears on your screen and how large the text is.
Colours: Fully customisable colours for the Table Header (Top row) and Data Rows (Bottom rows).
3. Timeframe 1 & 2 Settings
You have two identical sections to configure two different timeframes (e.g., 30m and 1H).
Timeframe: The chart interval to monitor (e.g., "30" for 30 minutes, "60" for 1 Hour, "240" for 4 Hours).
Threshold %: The "Trigger" for drawing a box based on relative candle volume in that timeframe.
Example:
100% = Candle Volume is equal to the average volume for the specified timeframe.
200% = Candle Volume is 2x the average volume for the specified timeframe.
300% = Candle Volume is 3x the average volume for the specified timeframe.
Box & Edge Colour: Distinct colours for each timeframe so you can easily tell which timeframe created the zone.
90% Buying Power Position Size Helper90% Buying Power Position Size Helper — Script Description
This tool calculates a recommended share size based on your available buying power and the current market price. TradingView does not provide access to live broker balances, so this script allows you to manually enter your current buying power and instantly see how many shares you can buy using a chosen percentage of it (default: 90%).
How It Works
• Enter your Buying Power ($)
• Choose the Percent to Use (e.g., 90%).
• The script divides the selected portion of your buying power by the current price of the symbol.
• A small display in the chart corner shows the recommended number of shares to buy.
Formula
shares = floor((buying_power * percent_to_use / 100) / price)
What It’s For
• Day traders who size positions based on account buying power
• Traders who want a quick way to calculate share size per trade
• Anyone who sizes entries using a fixed percentage of their account
What It Doesn’t Do
Due to TradingView limitations, the script cannot:
• Read your live buying power or broker balance
• Auto-fill orders or submit trades
• Retrieve real account data from your broker
You simply update the buying power input whenever your account changes, and the script does the rest.
Why It’s Useful
• Keeps you consistent with position sizing
• Reduces manual math during fast trading
• Prevents oversizing or undersizing trades
• Helps maintain discipline and risk control
IDWM Master StructureExecutive Summary
The IDWM Master Structure is a Multi-Timeframe (MTF) trading tool designed to force discipline by aligning traders with the "Parent" trend. It functions by locking onto the "Completed Auction" of a higher timeframe candle (like a Daily or Weekly bar) and projecting that structure onto your lower timeframe chart. Its primary goal is to define the "Dealing Range"—the hard boundaries where value was previously established—so you don't get lost in the noise of smaller price movements.
1. The Principle of Completed Auctions (Hierarchy)
Most technical indicators curve dynamically with every price tick. This script acts differently because it relies on "Settled Arguments." A closed Daily candle represents a finished battle between buyers and sellers; the High and Low are the historical results of that battle.
To enforce this, the script automatically selects a "Parent" timeframe based on your view:
Scalping (charts below 15 minutes) uses the 4-Hour Auction.
Intraday trading (15 minutes to 4 Hours) uses the Daily Auction.
Swing trading (Daily chart) uses the Weekly Auction.
2. Liquidity Pools & The Sticky Range
The High and Low lines drawn by the indicator are not just support and resistance; they represent Liquidity Pools. In market theory, stop-losses (Sell Stops below Lows, Buy Stops above Highs) accumulate at these edges.
Smart money often pushes price just past these lines to grab this liquidity (a "Stop Hunt") before reversing direction. To account for this, the script uses a "Sticky Range" mechanism. It refuses to redraw the box simply because price touched the line. Instead, it uses an Average True Range (ATR) Buffer. A new structure is only formed if the candle closes decisively outside the range plus this volatility buffer. This ensures you are trading real breakouts, not liquidity sweeps.
3. Internal Range Mechanics (Premium vs. Discount)
Inside the Master Box, the script applies Equilibrium Theory to help with trade location.
The most important internal line is the Equilibrium (EQ), which marks the exact 50% point of the range.
Premium Zone (Above EQ): Price is mathematically "expensive" relative to the recent range. Algorithms generally look to establish Short positions here.
Discount Zone (Below EQ): Price is considered "cheap." Algorithms generally look to establish Long positions here.
It also plots the Master Open, which acts as a "Line in the Sand." If price is currently trading above the Master Open, the higher timeframe candle is Green (Bullish), suggesting longs have a higher probability. If below, the candle is Red (Bearish).
4. Wick Theory (Failed Auctions)
The script places special emphasis on the wicks of the Master Candle because a wick represents a "Failed Auction"—a price level the market tried to explore but ultimately rejected.
The indicator highlights the background of the wick area (from the High to the Body). On a retest, these zones often act as supply or demand blocks because the market remembers the previous failure.
It also calculates the "Consequent Encroachment," which is the 50% midpoint of the wick. The rule of thumb here is that if a candle body can close past 50% of a wick, the rejection is nullified, and price will likely travel to fill the entire wick.
5. Energy Expansion (Breakout Targets)
Market energy transfers from Consolidation (inside the box) to Expansion (the breakout). When the price finally breaks the "Sticky Range" (confirming via the ATR buffer), the script projects where that energy will go.
It uses the height of the previous range to calculate Fibonacci extensions. Specifically, it targets the 1.618 Extension, often called the "Golden Ratio." This is a statistically significant level where expansion moves tend to exhaust themselves and reverse.
6. Safety Protocol: Live Detection
A dashboard monitors the state of the parent candle. If the text turns Magenta with a warning symbol, it means the Higher Timeframe candle is "Live" (still forming).
Trading off a live structure is considered higher risk because the "Auction" isn't finished—the High or Low can still shift. The safest approach is to trade when the dashboard indicates a standard, locked, historical structure.
RS Rating Multi-TimeframeRS Rating Multi-Timeframe (IBD-Style Relative Strength)
Short Description:
IBD-style Relative Strength Rating (1-99) comparing any stock's performance vs the S&P 500 across multiple timeframes.
Full Description:
Overview
This indicator calculates an IBD-style Relative Strength (RS) Rating that measures a stock's price performance relative to the S&P 500 over the past 12 months. The rating scale ranges from 1 (weakest) to 99 (strongest), telling you how a stock ranks against all other stocks in terms of relative performance.
How It Works
The RS Rating uses a weighted formula based on quarterly performance:
Last 63 days (1 quarter): 40% weight
Last 126 days (2 quarters): 20% weight
Last 189 days (3 quarters): 20% weight
Last 252 days (4 quarters): 20% weight
This weighting emphasizes recent performance while still accounting for longer-term strength.
Rating Interpretation
90-99 (Elite): Top 10% of all stocks - exceptional relative strength
80-89 (Excellent): Top 20% - strong leadership candidates
50-79 (Average): Middle of the pack
30-49 (Below Average): Underperforming the market
1-29 (Weak): Bottom 30% - avoid or consider shorting
Features
Multi-Timeframe: Works on any timeframe from 1-hour to weekly (always uses daily data for calculation)
Moving Average: Optional EMA or SMA of the RS Rating to smooth signals
Visual Zones: Color-coded zones for quick identification of strength/weakness
Signal Markers: Triangles appear when RS crosses key levels (80 and 30)
Info Table: Displays current RS Rating, change, MA value, and raw score
Alerts: Built-in alerts for key crossover events
Settings
Show Moving Average: Toggle MA line on/off
MA Length: Period for the moving average (default: 10)
MA Type: Choose between EMA or SMA
Benchmark Index: Change the comparison index (default: SP:SPX)
Show Rating Table: Toggle the info table on/off
How To Use
Buy candidates: Look for stocks with RS Rating above 80, ideally rising
Avoid: Stocks with RS Rating below 30 or falling rapidly
Confirmation: Use RS above its moving average as additional confirmation
Divergence: Watch for RS making new highs before price (bullish) or new lows before price (bearish)
Credits
RS Rating calculation methodology inspired by Investor's Business Daily (IBD) and adapted from Fred6724's RS Rating script. Percentile calibration based on analysis of ~6,600 US stocks.
Tags: relative strength, RS rating, IBD, momentum, CAN SLIM, benchmark, SPX, market leaders, stock ranking
Category: Relative Strength
Wick Size Percentage (%) IndicatorA lightweight utility script that measures the wick size of every bar in percentages. It helps identify significant rejection blocks and volatility spikes by displaying the exact % value above and below each candle. Perfect for ICT concepts and precise risk management.
This indicator is designed for price action traders who need precise measurements of market volatility and rejection. It automatically calculates and displays the size of both the upper and lower wicks of a candle as a percentage relative to the open price.
Key Features:
Dual Measurement: Separately calculates the upper wick (high to body) and lower wick (body to low).
Percentage Based: Values are shown in percentages (%) rather than price points, making it easier to compare volatility across different assets (Crypto, Forex, Stocks).
Dynamic Labels: Visual labels appear above and below the candles for quick reading.
Fully Customizable: Users can adjust the decimal precision (e.g., for low timeframe scalping), change text size, and toggle visibility to keep the chart clean.
Data Window Support: Values are also visible in the side Data Window for detailed analysis without clutter.
ZScore SemiConductoresZ-Score of Semiconductor Sector Volume
This custom Pine Script indicator applies a Z-Score calculation to the aggregated trading volume of leading semiconductor companies. The goal is to highlight statistical extremes in sector activity that may signal unusual market behavior.
🔧 How it works
- Fixed ticker list: NVDA, AVGO, TSM, AMD, ASML, MU, ARM, ON, TXN, QCOM, INTC.
- Aggregate volume: The script sums the trading volume of all tickers in the list for the selected timeframe.
- Z-Score calculation:
- Moving average and standard deviation are computed over a configurable window (default = 50 bars).
- Formula:
Z= (Current Volume - Mean) / Standard Deviation
Visualization:
- Z-Score plotted in green.
- Reference lines at 0, ±1σ, ±2σ.
- Labels (triangles) mark critical signals when Z > +2 or Z < -2.
📈 Why it matters
- Detects abnormal surges or drops in sector-wide volume.
- Highlights potential euphoria (+2σ) or panic (-2σ) moments.
- Useful as a filter for trading strategies or as a sector-level alert system.
⚠️ Disclaimer: This script is for educational purposes only and not financial advice
PoC Migration Map [BackQuant]PoC Migration Map
A volume structure tool that builds a side volume profile, extracts rolling Points of Control (PoCs), and maps how those PoCs migrate through time so you can see where value is moving, how volume clusters shift, and how that aligns with trend regime.
What this is
This indicator combines a classic volume profile with a segmented PoC trail. It looks back over a configurable window, splits that window into bins by price, and shows you where volume has concentrated. On top of that, it slices the lookback into fixed bar segments, finds the local PoC in each segment, and plots those PoCs as a chain of nodes across the chart.
The result is a "migration map" of value:
A side volume profile that shows how volume is distributed over the recent price range.
A sequence of PoC nodes that show where local value has been accepted over time.
Lines that connect those PoCs to reveal the path of value migration.
Optional trend coloring based on EMA 12 and EMA 21, so each PoC also encodes trend regime.
Used together, this gives you a structural read on where the market has actually traded size, how "value" is moving, and whether that movement is aligned or fighting the current trend.
Core components
Lookback volume profile - a side histogram built from all closes and volumes in the chosen lookback window.
Segmented PoC trail - rolling PoCs computed over fixed bar segments, plotted as nodes in time.
Trend heatmap - optional color mapping of PoC nodes using EMA 12 versus EMA 21.
PoC labels - optional labels on every Nth PoC for easier reading and referencing.
How it works
1) Global lookback and binning
You choose:
Lookback Bars - how far back to collect data.
Number of Bins - how finely to split the price range.
The script:
Finds the highest high and lowest low in the lookback.
Computes the total price range and divides it into equal binCount slices.
Assigns each bar's close and volume into the appropriate price bin.
This creates a discretized volume distribution across the entire lookback.
2) Side volume profile
If "Show Side Profile" is enabled, a right-hand volume profile is drawn:
Each bin becomes a horizontal bar anchored at a configurable "Right Offset" from the current bar.
The horizontal width of each bar is proportional to that bin's volume relative to the maximum volume bin.
Optionally, volume values and percentages are printed inside the profile bars.
Color and transparency are controlled by:
Base Profile Color and its transparency.
A gradient that uses relative volume to modulate opacity between lower volume and higher volume bins.
Profile Width (%) - how wide the maximum bin can extend in bars.
This gives you an at-a-glance view of the volume landscape for the chosen lookback window.
3) Segmenting for PoC migration
To build the PoC trail, the lookback is divided into segments:
Bars per Segment - bars in each local cluster.
Number of Segments - how many segments you want to see back in time.
For each segment:
The script uses the same price bins and accumulates volume only from bars in that segment.
It finds the bin with the highest volume in that segment, which is the local PoC for that segment.
It sets the PoC price to the center of that bin.
It finds the "mid bar" of the segment and places the PoC node at that time on the chart.
This is repeated for each segment from older to newer, so you get a chain of PoCs that shows how local value has migrated over time.
4) Trend regime and color coding
The indicator precomputes:
EMA 12 (Fast).
EMA 21 (Slow).
For each PoC:
It samples EMA 12 and EMA 21 at the mid bar of that segment.
It computes a simple trend score as fast EMA minus slow EMA.
If trend heatmap is enabled, PoC nodes (and the lines between them) are colored by:
Trend Up Color if EMA 12 is above EMA 21.
Trend Down Color if EMA 12 is below EMA 21.
Trend Flat Color if they are roughly equal.
If the trend heatmap is disabled, PoC color is instead based on PoC migration:
If the current PoC is above the previous PoC, use the Up PoC Color.
If the current PoC is below the previous PoC, use the Down PoC Color.
If unchanged, use the Flat PoC Color.
5) Connecting PoCs and labels
Once PoC prices and times are known:
Each PoC is connected to the previous one with a dotted line, using the PoC's color.
Optional labels are placed next to every Nth PoC:
Label text uses a simple "PoC N" scheme.
Label background uses a configurable label background color.
Label border is colored by the PoC's own color for visual consistency.
This turns the PoCs into a visual path that can be read like a "value trajectory" across the chart.
What it plots
When fully enabled, you will see:
A right-sided volume profile for the chosen lookback window, built from volume by price.
Colored horizontal bars representing each price bin's relative volume.
Optional volume text showing each bin's volume and its percentage of the profile maximum.
A series of PoC nodes spaced across the chart at the mid point of each segment.
Dotted lines connecting those PoCs to show the migration path of value.
Optional PoC labels at each Nth node for easier reference.
Color-coding of PoCs and lines either by EMA 12 / 21 trend regime or by up/down PoC drift.
Reading PoC migration and market pressure
Side profile as a pressure map
The side profile shows where trading has been most active:
Thick, opaque bars represent high volume zones and possible high interest or acceptance areas.
Thin, faint bars represent low volume zones, potential rejection or transition areas.
When price trades near a high volume bin, the market is sitting on an area of prior acceptance and size.
When price moves quickly through low volume bins, it often does so with less friction.
This gives you a static map of where the market has been willing to do business within your lookback.
PoC trail as a value migration map
The PoC chain represents "where value has lived" over time:
An upward sloping PoC trail indicates value migrating higher. Buyers have been willing to transact at increasingly higher prices.
A downward sloping trail indicates value migrating lower and sellers pushing the center of mass down.
A flat or oscillating trail indicates balance or rotational behaviour, with no clear directional acceptance.
Taken together, you can interpret:
Side profile as "where the volume mass sits", a static pressure field.
PoC trail as "how that mass has moved", the dynamic path of value.
Trend heatmap as a regime overlay
When PoCs are colored by the EMA 12 / 21 spread:
Green PoCs mark segments where the faster EMA is above the slower EMA, that is, a local uptrend regime.
Red PoCs mark segments where the faster EMA is below the slower EMA, that is, a local downtrend regime.
Gray PoCs mark flat or ambiguous trend segments.
This lets you answer questions like:
"Is value migrating higher while the trend regime is also up?" (trend confirming value).
"Is value migrating higher but most PoCs are red?" (value against the prevailing trend).
"Has value started to roll over just as PoCs flip from green to red?" (early regime transition).
Key settings
General Settings
Lookback Bars - how many bars back to use for both the global volume profile and segment profiles.
Number of Bins - how many price bins to split the high to low range into.
Profile Settings
Show Side Profile - toggle the right-hand volume profile on or off.
Profile Width (%) - how wide the largest volume bar is allowed to be in terms of bars.
Base Profile Color - the starting color for profile bars, with transparency.
Show Volume Values - if enabled, print volume and percent for each non-zero bin.
Profile Text Color - color for volume text inside the profile.
PoC Migration Settings
Show PoC Migration - toggle the PoC trail plotting.
Bars per Segment - the number of bars contained in each segment.
Number of Segments - how many segments to build backwards from the current bar.
Horizontal Spacing (bars) - spacing between PoC nodes when drawn. (Used to separate PoCs horizontally.)
Label Every Nth PoC - draw labels at every Nth PoC (0 or 1 to suppress labels).
Right Offset (bars) - horizontal offset to anchor the side profile on the right.
Up PoC Color - color used when a PoC is higher than the previous one, if trend heatmap is off.
Down PoC Color - color used when a PoC is lower than the previous one, if trend heatmap is off.
Flat PoC Color - color used when the PoC is unchanged, if trend heatmap is off.
PoC Label Background - background color for PoC labels.
Trend Heatmap Settings
Color PoCs By Trend (EMA 12 / 21) - when enabled, overrides simple up/down coloring and uses EMA-based trend colors.
Fast EMA - length for the fast EMA.
Slow EMA - length for the slow EMA.
Trend Up Color - color for PoCs in a bullish EMA regime.
Trend Down Color - color for PoCs in a bearish EMA regime.
Trend Flat Color - color for neutral or flat EMA regimes.
Trading applications
1) Value migration and trend confirmation
Use the PoC path to see if value is following price or lagging it:
In a healthy uptrend, price, PoCs, and trend regime should all lean higher.
In a weakening trend, price may still move up, but PoCs flatten or start drifting lower, suggesting fewer participants are accepting the new highs.
In a downtrend, persistent downward PoC migration confirms that sellers are winning the value battle.
2) Identifying acceptance and rejection zones
Combine the side profile with PoC locations:
High volume bins near clustered PoCs mark strong acceptance zones, good areas to watch for re-tests and decision points.
PoCs that quickly jump across low volume areas can indicate rejection and fast repricing between value zones.
High volume zones with mixed PoC colors may signal balance or prolonged negotiation.
3) Structuring entries and exits
Use the map to refine trade location:
Fade trades against value migration are higher risk unless you see clear signs of exhaustion or regime change.
Pullbacks into prior PoC zones in the direction of the current PoC slope can offer higher quality entries.
Stops placed beyond major accepted zones (clusters of PoCs and high volume bins) are less likely to be hit by random noise.
4) Regime transitions
Watch how PoCs behave as the EMA regime changes:
A flip in EMA 12 versus EMA 21, coupled with a turn in PoC slope, is a strong signal that value is beginning to move with the new trend.
If EMAs flip but PoC migration does not follow, the trend signal may be early or false.
A weakening PoC path (lower highs in PoCs) while trend colors are still green can warn of a late-stage trend.
Best practices
Start with a moderate lookback such as 200 to 300 bars and a moderate bin count such as 20 to 40. Too many bins can make the profile overly granular and sparse.
Align "Bars per Segment" with your trading horizon. For example, 5 to 10 bars for intraday, 10 to 20 bars for swing.
Use the profile and PoC trail as structural context rather than as a direct buy or sell signal. Combine with your existing setups for timing.
Pay attention to clusters of PoCs at similar prices. Those are areas where the market has repeatedly accepted value, and they often matter on future tests.
Notes
This is a structural volume tool, not a complete trading system. It does not manage execution, position sizing or risk management. Use it to understand:
Where the bulk of trading has occurred in your chosen window.
How the center of volume has migrated over time.
Whether that migration is aligned with or fighting the current trend regime.
By turning PoC evolution into a visible path and adding a trend-aware heatmap, the PoC Migration Map makes it easier to see how value has been moving, where the market is likely to feel "heavy" or "light", and how that structure fits into your trading decisions.
V2 BUY LOW, BUY MORE, SELL HIGH Strategy w Buffett Meter-LITE__________________________________________________________________________
V2 Buy Low, Buy More, Sell High With Buffett Meter (LITE – JTMarketAI)
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Category: Quantitative Momentum & Liquidity Flow
Author: JTMarketAI
Architecture: Non-Repainting
This strategy accumulates into validated pullbacks during fear cycles, scales intelligently as price declines into liquidity support, and exits when momentum weakens after meaningful run-ups. It uses synthetic higher-timeframe OHLC data (non-repainting), liquidity imbalance confirmation, adaptive KAMA trend logic, RSI validation, and a live Buffett macro valuation gauge.
This is a patient, conviction-based accumulation engine designed for equities.
It is not a scalp bot.
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Core Features
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Non-repainting (confirmed bars only)
Synthetic HTF OHLC (no lookahead)
Dynamic trailing exit preserves ~80–87% of peak profit
Bull vs Bear liquidity dominance and flow imbalance
Rolling lowest-low tracking (LLL)
NY-session alignment (default)
Buffett Macro Meter integration
Technical Highlights
Flow-confidence derived from volume-order pressure
Adaptive KAMA smoothing for lower-lag confirmation
Daily > Weekly > Monthly synthetic aggregation
LLL progression display for trend exhaustion
Fully profiler-optimized
Supports averaging down when pyramiding enabled
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Why It Does Not Repaint
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All state updates occur only on confirmed bars
All trades are recorded and remembered to not disappear
Synthetic HTFs built without lookahead
Persistent arrays freeze historical values
Trailing highs updated only after confirmation
No forward-reference to future bars
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Lite Edition Notes
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Manual trading focused
Live trades (Dark Blue) Preview period trades (aqua entries)
On strategy start date, if preview trades are profitable, live trades begin.
Buffett Meter enabled. Nice for monitoring volume bar-by-bar for day trading.
Visual dashboard included
No alerts, automation, or webhooks (PRO unlocks TradersPost.io auto-trading)
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Limitations
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Best on intraday equities (1m–4h) V2 uses virtual volume to enable Daily Charts.
Designed for stock market tickers only.
High-resource if full visuals enabled
Avoid extremely low-volume tickers. Nice cyclical wave tickers like TSLA are best.
Does not guard against after-hours gaps or major news moves
Does not prevent tickers from racing towards 0.
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Warnings
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Contrarian scaling requires discipline and patience
Expect longer-duration trades, not rapid scalps
Use on quality tickers unlikely to permanently collapse
Confirm price behavior outside cash session
Test manually before automating anything
Not suitable for every market environment or asset
Notes on Philosophy
This strategy attempts to accumulate when markets overshoot lower, and distribute after recovery momentum fades. It reflects a patient, value-driven approach built on the principle of buying fear and reducing exposure into strength.
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Disclaimer
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For research and educational use only. Not financial advice. Past performance does not guarantee future results. Test thoroughly and use appropriate risk management.
Markov ProjectionThe idea here is to provide mobile S/R through Markov chaining. Definitely not a reversion to the mean trading system, or a trading system of any sort. More like an error bounded future price envelope that dramatically overshoots projected price in the direction it's moving in while just barely failing price bounding in the opposite direction. So in an uptrend, it'll overshoot the top while the bottom pokes out a bit and vice versa. Looks rather pretty. You'll have to adjust transparency settings. Happy hunting.
5 SMA Set + Bollinger Bands follow this especially 5 day average5 SMA Set + Bollinger Bands follow this especially 5 day average is important
//@version=5
indicator("5'li SMA Seti + Bollinger Bands", overlay=true, max_lines_count=10)
// === ORİJİNAL 5'Lİ SMA SETİ (HİÇ DOKUNMADIM) ===
len1 = 1
len5 = 5
sma1_low = ta.sma(low, len1)
sma1_high = ta.sma(high, len1)
sma5_low = ta.sma(low, len5)
sma5_high = ta.sma(high, len5)
sma5_close = ta.sma(close, len5)
plot(sma1_low, title="1 Periyot Düşük SMA", color=#8B0000, linewidth=4, style=plot.style_circles)
plot(sma1_high, title="1 Periyot Yüksek SMA", color=#006400, linewidth=4, style=plot.style_circles)
plot(sma5_low, title="5 Periyot Düşük SMA", color=#FF4040, linewidth=2, style=plot.style_line)
plot(sma5_high, title="5 Periyot Yüksek SMA", color=#90EE90, linewidth=2, style=plot.style_line)
plot(sma5_close, title="5 Periyot Kapanış SMA", color=#DA70D6, linewidth=3, style=plot.style_line)
// === KLASİK BOLLINGER BANDS (20-2) - ORİJİNAL HALİYLE ===
length_bb = 20
mult = 2.0
basis = ta.sma(close, length_bb)
dev = mult * ta.stdev(close, length_bb)
upper = basis + dev
lower = basis - dev
plot(basis, title="BB Orta (SMA 20)", color=#787B86, linewidth=2)
p1 = plot(upper, title="BB Üst Bant", color=#2962FF, linewidth=1)
p2 = plot(lower, title="BB Alt Bant", color=#2962FF, linewidth=1)
fill(p1, p2, color=color.new(#2962FF, 94), title="BB Arka Plan")
Optionsmith Daily SPX Direction ModelThis indicator, published by Optionsmith LLC, is used on the DAILY chart only, to gauge whether there is an edge to the bullish side or bearish side for the day. It uses multiple factors, such as where the price closed the previous day compared to the range for that day, as well as whether there is a large gap on open, and factoring in the general upward drift of SPX over time.
This indicator is published as is for educational use and with no guarantees on its reliability.
