Auto Wyckoff Schematic [by DanielM]This indicator is designed to automatically detect essential components of Wyckoff schematics. This tool aims to capture the critical phases of liquidity transfer from weak to strong hands, occurring before a trend reversal. While the Wyckoff method is a comprehensive and a very nuanced approach, every Wyckoff schematic is unique, making it impractical to implement all its components without undermining the detection of the pattern. Consequently, this script focuses on the essential elements critical to identifying these schematics effectively.
Key Features:
Swing Detection Sensitivity:
The sensitivity of swing detection is adjustable through the input parameter. This parameter controls the number of past bars analyzed to determine swing highs and lows, allowing users to fine-tune detection based on market volatility and timeframes.
Pattern Detection Logic:
Accumulation Schematic:
Detects consecutive lower swing lows, representing phases like Selling Climax (SC) and Spring, which often precede a trend reversal upward. After the final low is identified, a higher high is detected to confirm the upward trend initiation.
Labeled Key Points:
SC: Selling Climax, marking the beginning of the accumulation zone.
ST: Secondary Test during the schematic.
ST(b): Secondary Test in phase B.
Spring: The lowest point in the schematic, signaling a final liquidity grab.
SOS: Sign of Strength, confirming a bullish breakout.
The schematic is outlined visually with a rectangle to highlight the price range.
Distribution Schematic:
Detects consecutive higher swing highs, which indicate phases such as Buying Climax (BC) and UTAD, often leading to a bearish reversal. After the final high, a lower low is detected to confirm the downward trend initiation.
Labeled Key Points:
BC: Buying Climax, marking the beginning of the distribution zone.
ST: Secondary Test during the schematic.
UT: Upthrust.
UTAD: Upthrust After Distribution, signaling the final upward liquidity grab before a bearish trend.
SOW: Sign of Weakness, confirming a bearish breakout.
The schematic is visually outlined with a rectangle to highlight the price range.
Notes:
Simplification for Practicality: Due to the inherent complexity and variability of Wyckoff schematics, the indicator focuses only on the most essential features—liquidity transfer and key reversal signals.
Limitations: The tool does not account for all components of Wyckoff's method (e.g., minor phases or nuanced volume analysis) to maintain clarity and usability.
Unique Behavior: Every Wyckoff schematic is different, and this tool is designed to provide a simplified, generalized approach to detecting these unique patterns.
Cerca negli script per "liquidity"
CandelaCharts - Swing Failure Pattern (SFP)# SWING FAILURE PATTERN
📝 Overview
The Swing Failure Pattern (SFP) indicator is designed to identify and highlight Swing Failure Patterns on a user’s chart. This pattern typically emerges when significant market participants generate liquidity by driving price action to key levels. An SFP occurs when the price temporarily breaks above a resistance level or below a support level, only to quickly reverse and return within the previous range. These movements are often associated with stop-loss hunting or liquidity grabs, providing traders with potential opportunities to anticipate reversals or key market turning points.
A Bullish SFP occurs when the price dips below a key support level, triggering stop-loss orders, but then swiftly reverses upward, signaling a potential upward trend or reversal.
A Bearish SFP happens when the price spikes above a key resistance level, triggering stop-losses of short positions, but then quickly reverses downward, indicating a potential bearish trend or reversal.
The indicator is a powerful tool for traders, helping to identify liquidity grabs and potential reversal points in real-time. Marking bullish and bearish Swing Failure Patterns on the chart, it provides clear visual cues for spotting market traps set by major players, enabling more informed trading decisions and improved risk management.
📦 Features
Bullish/Bearish SFPs
Styling
⚙️ Settings
Length: Determines the detection length of each SFP
Bullish SFP: Displays the bullish SFPs
Bearish SFP: Displays the bearish SFPs
Label: Controls the size of the label
⚡️ Showcase
Bullish
Bearish
Both
📒 Usage
The best approach is to combine a few complementary indicators to gain a clearer market perspective. This doesn’t mean relying on the Golden Cross, RSI divergences, SFPs, and funding rates simultaneously, but rather focusing on one or two that align well in a given scenario.
The example above demonstrates the confluence of a Bearish Swing Failure Pattern (SFP) with an RSI divergence. This combination strengthens the signal, as the Bearish SFP indicates a potential reversal after a liquidity grab, while the RSI divergence confirms weakening momentum at the key level. Together, these indicators provide a more robust setup for identifying potential market reversals with greater confidence.
🚨 Alerts
This script provides alert options for all signals.
Bearish Signal
A bearish signal is triggered when a Bearish SFP is formed.
Bullish Signal
A bullish signal is triggered when a Bullish SFP is formed.
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
HMA w(LRLR)Description: This script combines a customizable Hull Moving Average (HMA) with a Low Resistance Liquidity Run (LRLR) detection system, ideal for identifying trend direction and potential breakout points in a single overlay.
Features:
Hull Moving Average (HMA):
Select separate calculation sources (open, high, low, close) for short and long periods.
Choose from SMA, EMA, and VWMA for length type on both short and long periods, offering flexible moving average calculations to suit different trading strategies.
Color-coded HMA line that visually changes based on crossover direction, providing an intuitive view of market trends.
Customizable options for line thickness, color transparency, and band fill between HMA short and long lines.
Low Resistance Liquidity Run (LRLR):
Detects breakout signals based on price and volume conditions, identifying potential liquidity run levels.
User-defined length and breakout multiplier control breakout sensitivity and adjust standard deviation-based thresholds.
Color-coded visual markers for bullish and bearish LRLR signals, customizable for user preference.
Alerts for both bullish and bearish LRLR events, keeping users informed of potential trading opportunities.
This script allows traders to visually track the HMA trend direction while also spotting low-resistance liquidity opportunities, all on one chart overlay.
Disclaimer: This tool is intended for educational purposes only and should not be used solely to make trading decisions. Adjust parameters as needed, and consider additional analysis for comprehensive decision-making.
Liquidations Zones [ChartPrime]The Liquidation Zones indicator is designed to detect potential liquidation zones based on common leverage levels such as 10x, 25x, 50x, and 100x. By calculating percentage distances from recent pivot points, the indicator shows where leveraged positions are most likely to get liquidated. It also tracks buy and sell volumes in these zones, helping traders assess market pressure and predict liquidation scenarios. Additionally, the indicator features a heat map mode to highlight areas where orders and stop-losses might be clustered.
⯁ KEY FEATURES AND HOW TO USE
⯌ Leverage Zones Detection :
The indicator identifies zones where positions with leverage ratios of 100x, 50x, 25x, and 10x are at risk of liquidation. These zones are based on percentage moves from recent pivots: a 1% move can liquidate 100x positions, a 4% move affects 25x positions, and so on.
⯌ Liquidated Zones and Volume Tracking :
The indicator displays liquidated zones by plotting gray areas where the price potentually liquidate positons. It calculates the volume needed to liquidate positions in these zones, showing volume from bullish candles if short positions were liquidated and volume from bearish candles for long positions. This feature helps traders assess the risk of liquidation as the price approaches these zones.
⯌ Buy/Sell Volume Calculation :
Buy and sell volumes are calculated from the most recent pivot high or low. For buy volume, only bullish candles are considered, while for sell volume, only bearish candles are summed. This data helps traders gauge the strength of potential liquidation in different zones.
Example of buy and sell volume tracking in active zones:
⯌ Liquidity Heat Map :
In heat map mode, the indicator visualizes potential liquidity areas where orders and stop-losses may be clustered. This map highlights zones that are likely to experience liquidations based on leverage ratios. Additionally, it tracks the highest and lowest price levels for the past 100 bars, while also displaying buy and sell volumes. This feature is useful for predicting market moves driven by liquidation events.
⯁ USER INPUTS
Length : Determines the number of bars used to calculate pivots for liquidation zones.
Extend : Controls how far the liquidation zones are extended on the chart.
Leverage Options : Toggle options to display zones for different leverage levels: 10x, 25x, 50x, and 100x.
Display Heat Map : Enables or disables the liquidity heat map feature.
⯁ CONCLUSION
The Liquidation Zones indicator provides a powerful tool for identifying potential liquidation zones, tracking volume pressure, and visualizing liquidity areas on the chart. With its real-time updates and multiple features, this indicator offers valuable insights for managing risk and anticipating market moves driven by leveraged positions.
[TTM] ICT Key Levels🌟 Overview 🌟
This tool highlights key price levels, such as highs, lows, and session opens, that can influence market moves. Based on ICT concepts, these levels help traders spot potential areas for market reversals or trend continuations.
🌟 Key Levels 🌟
🔹 Week Open (00:00 EST)
Marks the start of the trading week. This level helps track price direction and is useful for framing the Weekly candle formation using ICT’s Power of 3.
🔹 Midnight Open (00:00 EST)
The Midnight Open (MNOP) marks the start of the new trading day. Price often retraces to this level for liquidity grabs, setting up larger moves in the daily trend. It's also key for framing the Daily Power of 3 and spotting possible market manipulation.
🔹 New York Stock Exchange Open (09:30 EST)
The NYSE Open is a major liquidity event, where price seeks liquidity from earlier in the day, like stop hunts or retracements to the London or Midnight Open. This time often brings reversals or trend continuations as volatility increases.
🔹 Previous Day High/Low
These levels show where liquidity rests, often serving as targets for price revisits, ideal for reversals or continuation trades.
🔹 Previous Week High/Low
Similar to daily levels but on a larger scale. They help identify swing trades and track broader market trends.
🔹 Previous Month High/Low
These monthly levels are important for long-term traders, as price often aims to clear them before setting new trends or market cycles.
Happy Trading!
TheTickMagnet
TPS Short Strategy by Larry ConnersThe TPS Short strategy aims to capitalize on extreme overbought conditions in an ETF by employing a scaling-in approach when certain technical indicators signal potential reversals. The strategy is designed to short the ETF when it is deemed overextended, based on the Relative Strength Index (RSI) and moving averages.
Components:
200-Day Simple Moving Average (SMA):
Purpose: Acts as a long-term trend filter. The ETF must be below its 200-day SMA to be eligible for shorting.
Rationale: The 200-day SMA is widely used to gauge the long-term trend of a security. When the price is below this moving average, it is often considered to be in a downtrend (Tushar S. Chande & Stanley Kroll, "The New Technical Trader: Boost Your Profit by Plugging Into the Latest Indicators").
2-Period RSI:
Purpose: Measures the speed and change of price movements to identify overbought conditions.
Criteria: Short 10% of the position when the 2-period RSI is above 75 for two consecutive days.
Rationale: A high RSI value (above 75) indicates that the ETF may be overbought, which could precede a price reversal (J. Welles Wilder, "New Concepts in Technical Trading Systems").
Scaling-In Mechanism:
Purpose: Gradually increase the short position as the ETF price rises beyond previous entry points.
Scaling Strategy:
20% more when the price is higher than the first entry.
30% more when the price is higher than the second entry.
40% more when the price is higher than the third entry.
Rationale: This incremental approach allows for an increased position size in a worsening trend, potentially increasing profitability if the trend continues to align with the strategy’s premise (Marty Schwartz, "Pit Bull: Lessons from Wall Street's Champion Day Trader").
Exit Conditions:
Criteria: Close all positions when the 2-period RSI drops below 30 or the 10-day SMA crosses above the 30-day SMA.
Rationale: A low RSI value (below 30) suggests that the ETF may be oversold and could be poised for a rebound, while the SMA crossover indicates a potential change in the trend (Martin J. Pring, "Technical Analysis Explained").
Risks and Considerations:
Market Risk:
The strategy assumes that the ETF will continue to decline once shorted. However, markets can be unpredictable, and price movements might not align with the strategy's expectations, especially in a volatile market (Nassim Nicholas Taleb, "The Black Swan: The Impact of the Highly Improbable").
Scaling Risks:
Scaling into a position as the price increases may increase exposure to adverse price movements. This method can amplify losses if the market moves against the position significantly before any reversal occurs.
Liquidity Risk:
Depending on the ETF’s liquidity, executing large trades in increments might affect the price and increase trading costs. It is crucial to ensure that the ETF has sufficient liquidity to handle large trades without significant slippage (James Altucher, "Trade Like a Hedge Fund").
Execution Risk:
The strategy relies on timely execution of trades based on specific conditions. Delays or errors in order execution can impact performance, especially in fast-moving markets.
Technical Indicator Limitations:
Technical indicators like RSI and SMA are based on historical data and may not always predict future price movements accurately. They can sometimes produce false signals, leading to potential losses if used in isolation (John Murphy, "Technical Analysis of the Financial Markets").
Conclusion
The TPS Short strategy utilizes a combination of long-term trend filtering, overbought conditions, and incremental shorting to potentially profit from price reversals. While the strategy has a structured approach and leverages well-known technical indicators, it is essential to be aware of the inherent risks, including market volatility, liquidity issues, and potential limitations of technical indicators. As with any trading strategy, thorough backtesting and risk management are crucial to its successful implementation.
Spiral Levels [ChartPrime]SPIRAL LEVELS
⯁ OVERVIEW
The Spiral Levels [ ChartPrime ] indicator, designed for use on TradingView and developed with Pine Script™ , leveraging a combination of traditional pivot points and spiral geometry to visualize support and resistance levels on the chart. By plotting spirals from pivot points, the indicator provides a distinctive perspective on potential price movements.
It's an experiment inspired from spirals in the Pine documentation and the concept of using spirals to add padding/offsets to SR zones in a market (an idea we plan to expand on in the future).
◆ USAGE
● Identifying Pivot Points: The indicator identifies significant pivot highs and lows based on user-defined criteria.
● Filtered Pivot Points: Pivot points for spirals are filtered using volume and high/low thresholds to ensure they are significant.
● Spiral Visualization: Spirals are plotted from these pivots, indicating potential future support and resistance levels or as liquidity zones.
Additionally, the plotted levels can serve as liquidity zones where the price might attempt to grab liquidity, providing a deeper understanding of market behavior at significant volume levels.
● Volume-Based Coloring: Spirals are colored based on volume data, providing additional context about the strength of the price movement.
● Labeling and Line Extensions: Labels display volume information, and lines extend from the end of the spirals to the current bar for clarity.
● Spiral Rotation: By adjusting the "Number of spiral rotations" input, you can control the number of rotations each spiral makes around a pivot point, offering more detailed insights. This also allows you to control the distance of levels from a pivot. More rotations will extend the spiral further from the pivot point, potentially identifying support and resistance levels or liquidity zones at greater distances.
This modification emphasizes that the number of rotations not only provides more detailed insights but also affects the spatial distribution of the identified levels relative to the pivot point.
⯁ USER INPUTS
● Pivots
Left Bars: Determines the number of bars to the left of the pivot.
Right Bars: Determines the number of bars to the right of the pivot.
● Filter
Volume Filter: Sets the threshold for volume filtering.
High & Low Filter: Sets the threshold for filtering pivot highs and lows.
● Spiral
Spirals Shown: Specifies the number of spirals to be displayed on the chart.
Number of spiral rotations: Sets the number of rotations for each spiral.
X Scale: Adjusts the horizontal scale of the spirals.
Y Scale: Adjusts the vertical scale of the spirals, relative to the ATR(200).
Reverse Spirals: Option to reverse the direction of the spirals.
⯁ TECHNICAL NOTES
The indicator uses Pine Script's polyline feature for smooth spiral rendering.
It implements a custom cross detection function to manage line and label visibility.
The script is optimized to limit calculations to the last 1000 bars for performance.
It automatically manages the number of displayed elements to prevent clutter and ensure smooth performance.
The Spiral Levels ChartPrime indicator offers a unique and visually engaging method to identify potential support and resistance levels. By integrating volume data and pivot points with spiral geometry, traders can gain valuable insights into market dynamics and make more informed trading decisions.
BTC x M2 Divergence (Weekly)### Why the "M2 Money Supply vs BTC Divergence with Normalized RSI" Indicator Should Work
IMPORTANT
- Weekly only indicator
- Combine it with BTC Halving Cycle Profit for better results
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator leverages the relationship between macroeconomic factors (M2 money supply) and Bitcoin price movements, combined with technical analysis tools like RSI, to provide actionable trading signals. Here's a detailed rationale on why this indicator should be effective:
1. **Macroeconomic Influence**:
- **M2 Money Supply**: Represents the total money supply, including cash, checking deposits, and easily convertible near money. Changes in M2 reflect liquidity in the economy, which can influence asset prices, including Bitcoin.
- **Bitcoin Sensitivity to Liquidity**: Bitcoin, being a digital asset, often reacts to changes in liquidity conditions. An increase in money supply can lead to higher asset prices as more money chases fewer assets, while a decrease can signal tightening conditions and lower prices.
2. **Divergence Analysis**:
- **Economic Divergence**: The indicator calculates the divergence between the percentage changes in M2 and Bitcoin prices. This divergence can highlight discrepancies between Bitcoin's price movements and broader economic conditions.
- **Market Inefficiencies**: Large divergences may indicate inefficiencies or imbalances that could lead to price corrections or trends. For example, if M2 is increasing (indicating more liquidity) but Bitcoin is not rising proportionately, it might suggest a potential upward correction in Bitcoin's price.
3. **Normalization and Smoothing**:
- **Normalized Divergence**: Normalizing the divergence to a consistent scale (-100 to 100) allows for easier comparison and interpretation over time, making the signals more robust.
- **Smoothing with EMA**: Applying Exponential Moving Averages (EMAs) to the normalized divergence helps to reduce noise and identify the underlying trend more clearly. This double-smoothed divergence provides a clearer signal by filtering out short-term volatility.
4. **RSI Integration**:
- **RSI as a Momentum Indicator**: RSI measures the speed and change of price movements, indicating overbought or oversold conditions. Normalizing the RSI and incorporating it into the divergence analysis helps to confirm the strength of the signals.
- **Combining Divergence with RSI**: By using RSI in conjunction with divergence, the indicator gains an additional layer of confirmation. For instance, a bullish divergence combined with an oversold RSI can be a strong buy signal.
5. **Dynamic Zones and Sensitivity**:
- **Good DCA Zones**: Highlighting zones where the divergence is significantly positive (good DCA zones) indicates periods where Bitcoin might be undervalued relative to economic conditions, suggesting good buying opportunities.
- **Red Zones**: Marking zones with extremely negative divergence, combined with RSI confirmation, identifies potential market tops or bearish conditions. This helps traders avoid buying into overbought markets or consider selling.
- **Peak Detection**: The sensitivity setting for detecting upside down peaks allows for early identification of potential market bottoms, providing timely entry points for traders.
6. **Visual Cues and Alerts**:
- **Clear Visualization**: The plots and background colors provide immediate visual feedback, making it easier for traders to spot significant conditions without deep analysis.
- **Alerts**: Built-in alerts for key conditions (good DCA zones, red zones, sell signals) ensure traders can act promptly based on the indicator's signals, enhancing the practicality of the tool.
### Conclusion
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator integrates macroeconomic data with technical analysis to offer a comprehensive view of Bitcoin's market conditions. By analyzing the divergence between M2 money supply and Bitcoin prices, normalizing and smoothing the data, and incorporating RSI for momentum confirmation, the indicator provides robust signals for identifying potential buying and selling opportunities. This holistic approach increases the likelihood of capturing significant market movements and making informed trading decisions.
Reversal Pivot PointsThis indicator aims to identify price levels where price action has quickly reversed from. These "pivots" establish major levels where major liquidity is located. Unlike standard support and resistance levels, when price breaks below or above a pivot, these pivots disappear from the chart. Comes with various customization features built to fit all.
Features
Pivot Timeframe: Identify and plot pivots from one specific timeframe and see it from all lower timeframes
Pivot left/right bar limit: A feature aimed at preventing false pivots identification
Remove On Close (ROC): Feature to only remove pivots once price close under it
ROC Timeframe: The timeframe the script uses to determine if the candle closed under the level
Wait For Close: Will only remove the pivot after the current candle closes
Line Extension Type: The extension of the line. None - extends line to current time, left - only extends line to the left, right - only extends line to the right, both - extends line both directions
Line Offset: How much to offset (in bars) the line and label from the current candle
Line Type: The style of line when plotted. Solid (─), dotted (┈), dashed (╌), arrow left (←), arrow right (→), arrows both (↔)
Display Level: Whether to or not to display the price of the pivot
Display Perfect Level: Whether to or not to display levels where price perfectly rejected off of
Alerts: Creates an alert when a level has been crossed
How to trade
1. Pivots can be traded to or from. The stock market (market makers) will tend to "chase" liquidity in order to fill orders at better averages. This allows us retail traders to to participate alongside these moves to these pivots. Once price action hits a pivot, it can do two things: break the pivot and continue or bounce off it. We can participate alongside these bounces after confirmation of a reversal (doji, volume, etc). These bounce plays are high risk as it's generally 50-50, but the risk to reward is typically also very high, making them very valuable to take.
2. Typically, the market is a fluid environment and should be "natural," so perfect things (manmade and filled with liquidity) should not occur. With this knowledge, we can expect these perfect levels, "PDT/PDB," to break as they are not natural occurrence and have heavy liquidity on and above/below them. We can trade to these levels and expect them to break/sweep if price action comes near them again.
ICT Silver Bullet | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Silver Bullet Indicator! This indicator is built around the ICT's "Silver Bullet" strategy. The strategy has 5 steps for execution and works best in 1-5 min timeframes. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Silver Bullet Indicator :
Implementation of ICT's Silver Bullet Strategy
Customizable Execution Settings
2 NY Sessions & London Session
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
ICT's Silver Bullet strategy has 5 steps :
1. Mark your market sessions open (This indicator has 3 -> NY 10-11, NY 14-15, LDN 03-04)
2. Mark the swing liquidity points
3. Wait for market to take down one liquidity side
4. Look for a market structure-shift for reversals
5. Wait for a FVG for execution
This indicator follows these steps and inform you step by step by plotting them in your chart. You can switch execution types between FVG and MSS.
🚩UNIQUENESS
This indicator is an all-in-one suit for the ICT's Silver Bullet concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. It's designed for simplyfing a rather complex strategy, helping you to execute it with clean signals. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️SETTINGS
1. General Configuration
Execution Type -> FVG execution type will require a FVG to take an entry, while the MSS setting will take an entry as soon as it detects a market structure-shift.
MSS Swing Length -> The swing length when finding liquidity zones for market structure-shift detection.
Breakout Method -> If "Wick" is selected, a bar wick will be enough to confirm a market structure-shift. If "Close" is selected, the bar must close above / below the liquidity zone to confirm a market structure-shift.
FVG Detection -> "Same Type" means that all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). "All" means that bar types may vary between bullish / bearish.
FVG Detection Sensitivity -> You can turn this setting on and off. If it's off, any 3 consecutive bullish / bearish bars will be calculated as FVGs. If it's on, the size of FVGs will be filtered by the selected sensitivity. Lower settings mean less but larger FVGs.
2. TP / SL
TP / SL Method -> If "Fixed" is selected, you can adjust the TP / SL ratios from the settings below. If "Dynamic" is selected, the TP / SL zones will be auto-determined by the algorithm.
Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails.
Close Position @ Session End -> If this setting is enabled, the current position (if any) will be closed at the beginning of a new session, regardless if it hit the TP / SL zone. If it's off, the position will be open until it hits a TP / SL zone.
Data from dataThe "Data from Data" indicator, developed by OmegaTools, is a sophisticated and versatile tool designed to offer a nuanced analysis of various market dynamics, catering to traders and investors seeking a comprehensive understanding of price movements considering a large amount of data and variables.
The uses of this indicator are nonconventional. You can use the indicator as a stand-alone tool on the chart, hiding the current symbol price data, to be able to analyze the price action with the Semaphore visualization method, you can also hide the indicator and choose from your favorite indicators and oscillator one of the data output as a source to have additional insight on the asset.
The last use of this indicator, which depends on the X Value that you set in the settings, is to have a possible scenario for the future outcomes of the markets. Remember that there is no tool that can really predict what the market will do in the future, this tool applies a large amount of formulas to use past prices as an indication that aims to be as close as possible to the future prices. The X Value not only changes the lookback of the formulas but also changes the number of future scenarios that the indicator will plot on the chart.
Key Features:
1. Rate of Change Analysis:
The indicator evaluates the rate of change variations in closing prices, providing insights into the current rate of change and expected rate of change variation.
2. Momentum Analysis:
Momentum is analyzed through calculations involving simple moving averages, offering expected values derived from momentum and momentum variation.
3. High/Low Variation:
The expected market behavior is assessed based on the average variation between high and low prices, contributing to a more holistic analysis.
4. Liquidity Targets:
Liquidity targets can be found by analyzing the highs and lows in the direction of the current fair price.
5. Regression Sequence:
Linear regression analysis is applied to closing prices, assessing momentum and providing expected values based on regression sequences.
6. Volume Presence:
The indicator evaluates the Rate of Change (ROC) by volume presence, offering insights into price movements influenced by trading volume.
7. Liquidity Grabs:
Expected market behavior is determined based on liquidity grabs, considering both current and historical price levels.
8. Fair Value Analysis:
Expected values are derived from fair value closes and fair value highs and lows, contributing to a more nuanced analysis of market conditions.
9. STT (Sequential Trend Test):
The Sequential Trend Test is employed to analyze market trends, providing expected values for a more informed decision-making process.
Visualization:
The indicator shows a "Semaphore" on the chart, visually representing all of the data extrapolated from the script. The visualization can be more minimalistic or more complex, to let the user decide that, in the settings, it's possible to decide if to show all of the data or only the average.
Additionally, the user can choose to display bars on the chart, that visualize the standard high and low of the price data, with the difference between the expected forecasted value and the actual closing price.
My suggestion is to try to change the colors of the data to fit best your eye and the data that you find more useful, and also to try to change some parameters from circle to line as a visualization method to catch with more ease some price patterns.
Error Analysis:
The indicator provides a detailed error analysis, including historical error, average error, and present error. This information is presented in a user-friendly table for quick reference. This table can be used to analyze the margin of error of the expected future price.
LIT - TimingIntroduction
This Script displays the Asia Session Range, the London Open Inducement Window, the NY Open Inducement Window, the Previous Week's high and low, the Previous Day's highs and lows, and the Day Open price in the cleanest way possible.
Description
The Indicator is based on UTC -7 timing but displays the Session Boxes automatically correct at your chart so you do not have to adjust any timings based on your Time Zone and don't have to do any calculations based on your UTC. It is already perfect.
You will see on default settings the purple Asia Box and 2 grey boxes, the first one is for the London Open Inducement Window (1 hour) and the second grey box is for the NY Open Inducement Window (also 1 hour)
Asia Range comes with default settings with the Asia Range high, low, and midline, you can remove these 3 lines in the settings "style" and untick the "Lines" box, that way you only will have the boxes displayed.
Special Feature
Most Timing-based Indicators have "bugged" boxes or don't show clean boxes at all and don't adjust at daylight savings times, we made sure that everything automatically gets adjusted so you don't have to! So the timings will always display at the correct time regarding the daylight savings times.
Combining Timing with Liquidity Zones the right way and in a clear, clean, and simple format.
Different than others this script also shows the "true" Asia range as it respects the "day open gap" which affects the Asia range in other scripts and it also covers the full 8 hours of Asia Session.
Additions
You can add in the settings menu the last week's high and low, the previous day's high and low, and also the day's open price by ticking the boxes in the settings menu
All colors of the boxes are fully adjustable and customizable for your personal preferences. Same for the previous weeks and day highs and lows. Just go to "Style" and you can adjust the Line types or colors to your preferred choice.
Recommended Use
The most beautiful display is on the M5 Timeframe as you have a clear overview of all sessions without losing the intraday view. You can also use it on the M1 for more details or the M15 for the bigger picture. The Template can hide on higher time frames starting from the H1 to not flood your chart with boxes.
How to use the Asia Session Range Box
Use the Asia Range Box as your intraday Guide, keep in mind that a Breakout of Asia high or low induces Liquidity and a common price behavior is a reversal after the fake breakout of that range.
How to use the London Open and NY Open Inducement Windows
Both grey boxes highlight the Open of either London Open or NY Open and you should keep an eye out for potential Liquditiy Graps or Mitigations during that times as this is when they introduce major Liquidity for the regarding Session.
How to use the Asia high, low and midline and day open price
After Asia Range got taken out in one direction, often price comes back to those levels to mitigate or bounce off, so you can imagine those zones as support and resistance on some occasions, recommended in combination with Imbalances.
How to use the previous day and week's highs and lows
Once added in the settings, you can display those price levels, you can use them either as Liquidity Targets or as Inducement Levels once they are taken out.
Enjoy!
Support and Resistance Signals MTF [LuxAlgo]The Support and Resistance Signals MTF indicator aims to identify undoubtedly one of the key concepts of technical analysis Support and Resistance Levels and more importantly, the script aims to capture and highlight major price action movements, such as Breakouts , Tests of the Zones , Retests of the Zones , and Rejections .
The script supports Multi-TimeFrame (MTF) functionality allowing users to analyze and observe the Support and Resistance Levels/Zones and their associated Signals from a higher timeframe perspective.
This script is an extended version of our previously published Support-and-Resistance-Levels-with-Breaks script from 2020.
Identification of key support and resistance levels/zones is an essential ingredient to successful technical analysis.
🔶 USAGE
Support and resistance are key concepts that help traders understand, analyze and act on chart patterns in the financial markets. Support describes a price level where a downtrend pauses due to demand for an asset increasing, while resistance refers to a level where an uptrend reverses as a sell-off happens.
The creation of support and resistance levels comes as a result of an initial imbalance of supply/demand, which forms what we know as a swing high or swing low. This script starts its processing using the swing highs/lows. Swing Highs/Lows are levels that many of the market participants use as a historical reference to place their trading orders (buy, sell, stop loss), as a result, those price levels potentially become and serve as key support and resistance levels.
One of the important features of the script is the signals it provides. The script follows the major price movements and highlights them on the chart.
🔹 Breakouts (non-repaint)
A breakout is a price moving outside a defined support or resistance level, the significance of the breakout can be measured by examining the volume. This script is not filtering them based on volume but provides volume information for the bar where the breakout takes place.
🔹 Retests
Retest is a case where the price action breaches a zone and then revisits the level breached.
🔹 Tests
Test is a case where the price action touches the support or resistance zones.
🔹 Rejections
Rejections are pin bar patterns with high trading volume.
Finally, Multi TimeFrame (MTF) functionality allows users to analyze and observe the Support and Resistance Levels/Zones and their associated Signals from a higher timeframe perspective.
🔶 SETTINGS
The script takes into account user-defined parameters to detect and highlight the zones, levels, and signals.
🔹 Support & Resistance Settings
Detection Timeframe: Set the indicator resolution, the users may examine higher timeframe detection on their chart timeframe.
Detection Length: Swing levels detection length
Check Previous Historical S&R Level: enables the script to check the previous historical levels.
🔹 Signals
Breakouts: Toggles the visibility of the Breakouts, enables customization of the color and the size of the visuals
Tests: Toggles the visibility of the Tests, enables customization of the color and the size of the visuals
Retests: Toggles the visibility of the Retests, enables customization of the color and the size of the visuals
Rejections: Toggles the visibility of the Rejections, enables customization of the color and the size of the visuals
🔹 Others
Sentiment Profile: Toggles the visibility of the Sentiment Profiles
Bullish Nodes: Color option for Bullish Nodes
Bearish Nodes: Color option for Bearish Nodes
🔶 RELATED SCRIPTS
Support-and-Resistance-Levels-with-Breaks
Buyside-Sellside-Liquidity
Liquidity-Levels-Voids
Temporary imbalancesThis indicator is designed to identify imbalances in order flow and market liquidity, It highlights candles with significant imbalances and draws reference lines
The indicator calculates imbalance based on changes in closing prices and volume. It uses the standard deviation to determine the significant imbalance threshold. Candles with bullish imbalances are highlighted in green, while candles with bearish imbalances are highlighted in red.
Furthermore, the indicator includes features of latency arbitrage and liquidity analysis. Latency arbitrage looks for price differences between the anchored VWAP and bid/ask quotes, targeting trading opportunities based on these differences. The liquidity analysis verifies the liquidity imbalance and calculates the VWAP anchored on this value in total using 4 VWAP.
This indicator can be adjusted according to the preferences and characteristics of the specific asset or market. It provides clear visual information and can be used as a complementary tool for technical analysis in trading strategies.
Interesting Segment Length 20,50,80,200
and Interesting lookback period 20,50,80,200
Interesting imbalance threshold 1.5, 2.4, 3.3 ,4.2
Este indicador é projetado para identificar desequilíbrios no fluxo de ordens e na liquidez do mercado, Ele destaca velas com desequilíbrios significativos e traça linhas de referência
O indicador calcula o desequilíbrio com base nas mudanças nos preços de fechamento e no volume. Ele usa o desvio padrão para determinar o limiar de desequilíbrio significativo. As velas com desequilíbrios de alta são destacadas em verde, enquanto as velas com desequilíbrios de baixa são destacadas em vermelho.
Além disso, o indicador inclui recursos de arbitragem de latência e análise de liquidez. A arbitragem de latência procura diferenças de preços entre a VWAP ancorada e as cotações de compra/venda, visando oportunidades de negociação com base nessas diferenças. A análise de liquidez verifica o desequilíbrio de liquidez e calcula a VWAP ancorada nesse valor ao total utiliza 4 VWAP.
Este indicador pode ser ajustado de acordo com as preferências e características do ativo ou mercado específico. Ele fornece informações visuais claras e pode ser usado como uma ferramenta complementar para análise técnica em estratégias de negociação.
Comprimento do Segmento interessante para usa 20,50,80,200
e Período de lookback interessante para usa 20,50,80,200
Limiar de desequilíbrio interessante para usa 1.5 ,2.4, 3.3 ,4.2
MTF Market Structure Highs and LowsThe indicator marks the last fractal highs and lows (W,D,4H and 1H options) to help determine current market structure. The script was created to help with directional bias but also as a MTF visual aid for stop hunts/liquidity raids.
Liquidity areas are where we assume trader's stop losses would be when buying or selling. Liquidity lies above and below swing points and institutions need liquidity to fill large orders.
Monitor price action as it hits these areas for a potential reversal trade.
Volume Indicators PackageCONTAINS 3 OF MY BEST VOLUME INDICATORS ALL FOR THE PRICE OF ONE!
CONTAINS:
Average Dollar Volume in RED
Up/Down Volume Ratio in Green
Volume Buzz/Volume Run Rate in BLUE
If you would like to get these individually, I also have scripts for that too.
Below is information about all three of these indicators, what they do, and why they are important.
---------------------------------------------------------------------------------------------AVERAGE DOLLAR VOLUME----------------------------------------------------------------------------------------
Dollar volume is simply the volume traded multiplied times the cost of the stock.
Dollar volume is an extremely important metric for finding stocks with enough liquidity for market makers to position themselves in. Market Liquidity is defined as market's feature whereby an individual or firm can quickly purchase or sell an asset without causing a drastic change in the asset's price. The key concept you want to understand is that these big instructions with billions of dollars need liquidity in a stock in order to even think about buying it, and therefore these institutions will demand a large dollar volume . A good dollar volume amount, that represents a pretty liquid name, is typically above 100 million $ average. Why are institutions important? Simple because they are the ones who make stocks move, and I mean really move. If you want to see large growth from a stock in a short amount of time, you need institutions wielding billions of dollars to be fighting one another to buy more shares. Institutions are the ones who make or break a stock, this is why we call them market makers.
My script calculates average dollar volume using four averages: the 50, the 30, the 20, and the 10 period. I use multiple averages in order to provide the accurate and up to date information to you. It then selects the minimum of these averages and divides this value by 1 million and displays this number to you.
TL;DR? If you want monster moves from your stocks, you need to pick names with average high liquidity(dollar volume >= $100 million). The number presented to you is in millions of whatever currency the name is traded in.
---------------------------------------------------------------------------------------------UP/DOWN VOLUME RATIO-----------------------------------------------------------------------------------------
Up/Down Volume Ratio is calculated by summing volume on days when it closes up and divide that total by the volume on days when the stock closed down.
High volume up days are typically a sign of accumulation(buying) by big players, while down days are signs of distribution(selling) by big market players. The Up Down volume ratio takes this assumption and turns it into a tangible number that's easier for the trader to understand. My formula is calculated using the past 50 periods, be warned it will not display a value for stocks with under 50 periods of trading history. This indicator is great for identify accumulation of growth stocks early on in their moves, most of the time you would like a growth stocks U/D value to be above 2, showing institutional sponsorship of a stock.
Up/Down Volume value interpretation:
U/D < 1 -> Bearish outlook, as sellers are in control
U/D = 1 -> Sellers and Buyers are equal
U/D > 1 -> Bullish outlook, as buyers are in control
U/D > 2 -> Bullish outlook, significant accumulation underway by market makers
U/D >= 3 -> MONSTER STOCK ALERT, market makers can not get enough of this stock and are ravenous to buy more
U/D values greater than 2 are rare and typically do not last very long, and U/D >= 3 are extremely rare one example I kind find of a stock's U/D peaking above 3 was Google back in 2005.
-----------------------------------------------------------------------------------------------------VOLUME BUZZ-----------------------------------------------------------------------------------------------
Volume Buzz/ Volume Run Rate as seen on TC2000 and MarketSmith respectively.
Basically, the volume buzz tells you what percentage over average(100 time period moving average) the volume traded was. You can use this indicator to more readily identify above-average trading volume and accumulation days on charts. The percentage will show up in the top left corner, make sure to click the settings button and uncheck the second box(left of plot) in order to get rid of the chart line.
Average Dollar VolumeDollar volume is simply the volume traded multiplied times the cost of the stock.
Dollar volume is an extremely important metric for finding stocks with enough liquidity for market makers to position themselves in. Market Liquidity is defined as market's feature whereby an individual or firm can quickly purchase or sell an asset without causing a drastic change in the asset's price. The key concept you want to understand is that these big instructions with billions of dollars need liquidity in a stock in order to even think about buying it, and therefore these institutions will demand a large dollar volume. A good dollar volume amount, that represents a pretty liquid name, is typically above 100 million $ average. Why are institutions important? Simple because they are the ones who make stocks move, and I mean really move. If you want to see large growth from a stock in a short amount of time, you need institutions wielding billions of dollars to be fighting one another to buy more shares. Institutions are the ones who make or break a stock, this is why we call them market makers.
My script calculates average dollar volume using four averages: the 50, the 30, the 20, and the 10 period. I use multiple averages in order to provide the accurate and up to date information to you. It then selects the minimum of these averages and divides this value by 1 million and displays this number to you.
TL;DR? If you want monster moves from your stocks, you need to pick names with average high liquidity(dollar volume >= $100 million). The number presented to you is in millions of whatever currency the name is traded in.
Master's Info Panel (v2)🧭 Overview
The Master Info Panel (v2) is a compact analytics dashboard that shows essential trading metrics right on your chart. It fuses volatility, liquidity, and relative-strength data with real-time fundamentals pulled directly from TradingView’s database. Everything updates live—no switching tabs or doing math in your head.
⚙️ What It Calculates
Volatility & Range:
ATR (14) – short-term volatility in raw points.
ADR % (20) – the average daily range as a percentage of current price.
Day High / Low – intraday extremes tracked dynamically.
Liquidity & Participation:
Relative Volume – today’s volume vs. the 20-day average.
Avg $ Volume – rolling average of (volume × price), a fast liquidity gauge.
Market Context:
RS vs Benchmark – compares performance against your chosen index (e.g., SPX) using a 50-period normalized ratio.
Market Cap & Float – live from TradingView financials for context on size / supply.
Sector & Industry – automatically detected from syminfo metadata.
🧩 Display Features
Custom Panel Position (Top/Bottom Left/Right)
Adjustable Text Size and optional background shade
Smart formatting that converts big numbers to K/M/B/T
Automatically refreshes at each new daily session
💡 Use Case
Use the panel as your quick-glance fundamentals + context readout before each trade:
Verify RS > 0 and Rel Vol > 1.5× for momentum setups.
Cross-check ADR % to size stops intelligently.
Use Market Cap + Float to judge breakout potential (smaller floats = higher torque).
✅ Built for clarity, Master Info Panel (v2) turns the hidden stats behind every chart into an always-visible, no-nonsense control center for active traders.
Global Risk Terminal – Multi-Asset Macro Sentiment IndicatorDescription:
The Global Risk Terminal is a sophisticated macro sentiment indicator that synthesizes signals from three key cross-asset relationships to produce a single, actionable risk appetite score. It is designed to help traders and investors identify whether global markets are in a risk-on (growth-seeking) or risk-off (defensive) regime. The indicator analyzes the behavior of commodities, equities, bonds, and currencies to generate a comprehensive view of market conditions.
Indicator Output:
The Global Risk Terminal produces a normalized risk score ranging from -1 to +1:
Positive values indicate risk-on conditions (growth assets favored)
Negative values indicate risk-off conditions (safe-haven assets favored)
Core Components:
Growth Pulse (Copper to Gold Ratio, HG/GC)
Purpose: Measures investor preference for industrial growth versus safe-haven assets.
Interpretation:
Rising ratio → Copper outperforming gold → Risk-on environment
Falling ratio → Gold outperforming copper → Risk-off environment
Flat ratio → Transitional market phase
Technical Implementation: Dual moving average slope method (fast MA default 20, slow MA default 40). Positive slope = +1, negative slope = -1, flat slope = 0
Equity Rotation (Russell 2000 to S&P 500 Ratio, RTY/ES)
Purpose: Tracks rotation between small-cap and large-cap equities, revealing market risk appetite.
Interpretation:
Rising ratio → Small-caps outperforming → Strong risk-on
Falling ratio → Large-caps outperforming → Defensive positioning
Technical Implementation: Dual moving average slope method (same as Growth Pulse)
Flow Gauge (10-Year Treasury to US Dollar Index, ZN/DXY)
Purpose: Captures liquidity conditions and cross-asset capital flows.
Interpretation:
Rising ratio → Treasury prices rising or USD weakening → Liquidity expansion, risk-on environment
Falling ratio → Treasury prices falling or USD strengthening → Liquidity contraction, risk-off environment
Technical Implementation: Dual moving average slope method
Composite Risk Score Calculation:
Analyze each component for trend using dual moving averages
Assign signal values: +1 (risk-on), -1 (risk-off), 0 (neutral)
Average the three signals:
Risk Score = (Growth Pulse + Equity Rotation + Flow Gauge) / 3
Optional smoothing with exponential moving average (default 3 periods) to reduce noise
Interpreting the Risk Score:
+0.66 to +1.0: Full risk-on – favor cyclical sectors, small-caps, growth strategies
+0.33 to +0.66: Moderate risk-on – mostly bullish environment, watch for fading momentum
-0.33 to +0.33: Neutral/transition – markets in flux, signals mixed, exercise caution
-0.66 to -0.33: Cautious risk-off – favor defensive sectors, reduce high-beta exposure
-1.0 to -0.66: Full risk-off – strong defensive positioning, prioritize safe-haven assets
How to Use the Global Risk Terminal to Frame Trades:
Aligning Trades with Market Regime
Risk-On (+0.33 and above): Look for buying opportunities in cyclical stocks, high-beta equities, commodities, and emerging markets. Use long entries for swing trades or intraday positions, following confirmed price action.
Risk-Off (-0.33 and below): Shift focus to defensive sectors, large-cap quality stocks, U.S. Treasuries, and safe-haven currencies. Prefer short entries or reduced exposure in risky assets.
Entry and Exit Framing
Use the risk score as a macro filter before executing trades:
Example: The risk score is +0.7 (strong risk-on). Prefer long positions in equities or commodities that are showing bullish confirmation on your regular chart.
Conversely, if the risk score is -0.7 (strong risk-off), avoid aggressive longs and consider short or defensive trades.
Watch for threshold crossings (+/-0.33, +/-0.66) as potential inflection points for adjusting position size, stop-loss levels, or sector rotation.
Confirming Trade Decisions
Combine the Global Risk Terminal with price action, volume, and trend indicators:
If equities rally but the risk score is declining, this may indicate a fragile rally driven by few leaders—trade cautiously.
If equities fall but the risk score is rising, consider counter-trend entries or buying dips.
Risk Management and Position Sizing
Strong alignment across components → increase position size and hold with wider stops
Mixed or neutral signals → reduce exposure, tighten stops, or avoid new trades
Defensive regimes → rotate into stable, low-volatility assets and increase cash buffer
Framing Trades Across Timeframes
Use the indicator as a strategic guide rather than a precise timing tool. Even without the MTF table:
Daily trend alignment → Guide swing trade bias
Shorter timeframe price action → Refine entry points and stop placement
Example: Daily chart shows +0.6 risk score → identify high-probability long setups using intraday technical patterns (breakouts, trend continuation).
Sector and Asset Rotation
Risk-On: Focus on cyclical sectors (financials, industrials, materials, energy), small-caps, high-beta instruments
Risk-Off: Focus on defensive sectors (utilities, consumer staples, healthcare), large-caps, safe-haven instruments
Alert Integration
Set alerts on the risk score to notify you when markets move from neutral to risk-on or risk-off regimes. Use these alerts to plan entries, exits, or portfolio adjustments in advance.
Customization Options:
Moving Average Length (5–100): Adjust sensitivity of trend detection
Score Smoothing (1–10): Reduce noise or see raw risk score
Visual Themes: Six preset themes (Cyber, Ocean, Sunset, Monochrome, Matrix, Custom)
Display Options: Show or hide component dashboards, main header, risk level lines, gradient fill, and component signals
Label Size: Tiny, Small, Normal, Large
Alert Conditions:
Risk score crosses above +0.66 → Strong risk-on
Risk score crosses below -0.66 → Strong risk-off
Risk score crosses zero → Neutral line
Risk score crosses above +0.33 → Moderate risk-on
Risk score crosses below -0.33 → Moderate risk-off
Data Sources:
HG1! – Copper Futures (COMEX)
GC1! – Gold Futures (COMEX)
RTY1! – Russell 2000 E-mini Futures (CME)
ES1! – S&P 500 E-mini Futures (CME)
ZN1! – 10-Year U.S. Treasury Note Futures (CBOT)
DXY – U.S. Dollar Index (ICE)
Notes and Limitations:
Works best during clear macro regimes and aligned trends
Use with price action, volume, and other technical tools
Not a standalone trading system; serves as a macro context filter
Equal weighting assumes all three components are equally important, but market conditions may vary
Past performance does not guarantee future results
Conclusion:
The Global Risk Terminal consolidates complex cross-asset signals into a simple, actionable score that informs market regime, portfolio positioning, sector rotation, and trading decisions. Its user-friendly layout and extensive customization options make it suitable for traders of all experience levels seeking macro-driven insights. By framing trades around risk score thresholds and combining macro context with tactical execution, traders can identify higher-probability opportunities and optimize position sizing, entries, and exits across a wide range of market conditions.
Trend-Fib-Pivot Sweep [JopAlgo]Trend-Fib-Pivot Sweep — trend rails + Fib touch rules + sweep logic
Core idea
This tool blends two trend MAs, a rolling Fibonacci grid, and pivot sweep tags so you can do three things quickly:
Trend → MA1 vs MA2 stack and slope
Location → Fib touch/bounce/reject rules
Triggers → sweep → reclaim or trend pullback → continuation
Use the MAs for bias, the Fib levels for where price should react, and the sweeps to spot traps and entries after liquidity grabs.
What you’ll see
MA 1 (default 21, purple) and MA 2 (default 50, gray)
Fib lines from the highest/lowest of your lookback: 0.236 (light blue), 0.382 (green), 0.5 (white), 0.618 (orange), 0.786 (red)
Sweep markers: triangle above = high sweep; triangle below = low sweep
Background: soft green when MA1 > MA2, soft red when MA1 < MA2
Read it fast → Trend (background + MA stack)? Which Fib are we near? Any sweep and reclaim?
How the Fib levels work (and what to do at each)
0.236 → shallow pullback in a strong trend
→ Expect quick bounce continuation.
→ If price closes through 0.236 and stalls, momentum may be cooling; look to 0.382.
0.382 → standard trend pullback
→ In a bullish trend, tests here often bounce and continue.
→ Entry idea: touch/bounce at 0.382 with MA1 above MA2 and rising, then a higher-low and push back above 0.382 → enter.
0.5 → midline / fair value
→ Often the “decision” level.
→ Clean continuation if 0.5 holds; deeper rotation if we accept below (for longs).
0.618 (“golden”) → deep pullback / last line for trend
→ Best risk-defined continuation entries come from rejects/reclaims here.
→ For longs: wick below 0.618, then reclaim 0.618 → long with stop under the sweep low.
0.786 → exhaustive pullback / trap zone
→ If trend is truly alive, 0.786 rejects and snaps back.
→ If we accept beyond 0.786 (closes), expect a full range rotation or trend change.
Touch/bounce rule of thumb
You want to see price interact: touch → reject (wick) → reclaim the level.
A close back above the Fib after a downside probe (or below after an upside probe) is a stronger confirmation than intrabar wicks.
What the MAs do (and how to use them)
MA1 (fast) vs MA2 (slow) define bias and momentum.
MA1 above MA2 and both rising (↗) → bullish regime.
MA1 below MA2 and both falling (↘) → bearish regime.
Flat / crossing often → balance; lean on sweeps and the deeper Fibs (0.5/0.618/0.786).
Interaction with Fibs
Highest quality: Fib level + MA confluence (e.g., 0.382 near MA1).
When MA1 = dynamic trigger: reclaim MA1 at a Fib → continuation signal.
When MA2 = last defense: lose MA2 at 0.5/0.618 → expect deeper rotation.
Sweep logic (why it matters and how to execute)
High sweep = current bar’s high takes out the recent high then fails → liquidity grab above.
Low sweep = current bar’s low takes the recent low then fails → liquidity grab below.
Execution idea
Longs: low sweep into 0.5/0.618/0.786, then reclaim the Fib and, ideally, MA1 → enter; stop under sweep low.
Shorts: high sweep into 0.5/0.382/0.236, then reclaim below the Fib and MA1 → enter; stop above sweep high.
Repaint note
If you enable Lag-Confirmed Pivot Mode, sweep labels are stricter and may “finalize” later (can appear as repaint).
For signals/alerts, prefer non-repaint mode; for review/training, lag-confirmed is fine.
How to trade it (simple playbook)
Direction filter (use MAs first)
Bullish bias → MA1 > MA2 and not flat → look for longs at 0.236/0.382/0.5.
Bearish bias → MA1 < MA2 → look for shorts at 0.236/0.382/0.5 from above.
Entries (two clean templates)
Trend pullback → continuation
→ In bull regime: price pulls to 0.382 or 0.5, shows rejection wick, then reclaims level and MA1 → enter long.
→ In bear regime: mirror with short from above.
Sweep → reclaim
→ Downside sweep through 0.618/0.786, then close back above the Fib and through MA1 → enter long.
→ Upside sweep through 0.382/0.236, then close back below and under MA1 → enter short.
Risk & targets
Stops → beyond the sweep extreme or below/above the reclaimed Fib (structure-based).
Targets → next Fib ladder (e.g., long from 0.5 → target 0.382 → 0.236), or obvious POC/HVNs if you use Volume Profile.
Settings that matter (and how to tune)
MA Types/Lengths
EMA (default fast) = responsive trend read.
SMA/HMA = smoother backbone.
21/50 is a solid default; swing traders can run 34/89.
Fib Lookback
Shorter lookback = tighter range, more sensitive levels;
Longer = broader swing map, fewer interactions but stronger signals.
Sweeps
Sweep Detection Range controls how “recent” the pivot must be (default 10).
Lag-Confirmed mode reduces false sweeps but can finalize later.
Starter presets
Intraday (15m–1H) → MA1 21 EMA, MA2 50 SMA, Fib lookback 100–150, Sweeps 10
Swing (4H) → MA1 34 EMA, MA2 89 SMA, Fib lookback 150–250, Sweeps 10–14
Pattern cheat sheet
0.382 kiss & go (trend day) → quick tag and bounce in bull regime → continuation.
0.5 decision → hold = trend resumes; failure = rotate to 0.618.
0.618 sweep + reclaim → high-quality continuation with tight risk.
0.786 trap → deep flush then snapback; if acceptance persists, expect full rotation.
MA pinch → break → MA1 and MA2 compress, then price breaks and holds a Fib → expansion leg.
Best combos (kept simple)
Volume Profile v3.2 → use VAH/VAL/POC/LVNs as concrete targets; look for Fib + VP confluence.
Anchored VWAP → reclaims/rejections at anchored lines with Fib reaction and MA agreement improve timing.
Common mistakes this helps you avoid
Buying into 0.618/0.786 without a reclaim (catching falling knives).
Fading a 0.236 pullback when MAs are strongly ↗ (fighting trend).
Taking sweeps without a reclaim/confirmation.
Ignoring the MA stack when choosing direction.
Disclaimer
This indicator and write-up are for education only, not financial advice. Trading involves risk; results vary by market, venue, and settings. Test first, act at defined levels, and manage risk. No guarantees or warranties are provided.
Opening Range IndicatorComplete Trading Guide: Opening Range Breakout Strategy
What Are Opening Ranges?
Opening ranges capture the high and low prices during the first few minutes of market open. These levels often act as key support and resistance throughout the trading day because:
Heavy volume occurs at market open as overnight orders execute
Institutional activity is concentrated during opening minutes
Price discovery happens as market participants react to overnight news
Psychological levels are established that traders watch all day
Understanding the Three Timeframes
OR5 (5-Minute Range: 9:30-9:35 AM)
Most sensitive - captures immediate market reaction
Quick signals but higher false breakout rate
Best for scalping and momentum trading
Use for early entry when conviction is high
OR15 (15-Minute Range: 9:30-9:45 AM)
Balanced approach - most popular among day traders
Moderate sensitivity with better reliability
Good for swing trades lasting several hours
Primary timeframe for most strategies
OR30 (30-Minute Range: 9:30-10:00 AM)
Most reliable but slower signals
Lower false breakout rate
Best for position trades and trend following
Use when looking for major moves
Core Trading Strategies
Strategy 1: Basic Breakout
Setup:
Wait for price to break above OR15 high or below OR15 low
Enter on the breakout candle close
Stop loss: Opposite side of the range
Target: 2-3x the range size
Example:
OR15 range: $100.00 - $102.00 (Range = $2.00)
Long entry: Break above $102.00
Stop loss: $99.50 (below OR15 low)
Target: $104.00+ (2x range size)
Strategy 2: Multiple Confirmation
Setup:
Wait for OR5 break first (early signal)
Confirm with OR15 break in same direction
Enter on OR15 confirmation
Stop: Below OR30 if available, or OR15 opposite level
Why it works:
Multiple timeframe confirmation reduces false signals and increases probability of sustained moves.
Strategy 3: Failed Breakout Reversal
Setup:
Price breaks OR15 level but fails to hold
Wait for re-entry into the range
Enter reversal trade toward opposite OR level
Stop: Recent breakout high/low
Target: Opposite side of range + extension
Key insight: Failed breakouts often lead to strong moves in the opposite direction.
Advanced Techniques
Range Quality Assessment
High-Quality Ranges (Trade these):
Range size: 0.5% - 2% of stock price
Clean boundaries (not choppy)
Volume spike during range formation
Clear rejection at range levels
Low-Quality Ranges (Avoid these):
Very narrow ranges (<0.3% of stock price)
Extremely wide ranges (>3% of stock price)
Choppy, overlapping candles
Low volume during formation
Volume Confirmation
For Breakouts:
Look for volume spike (2x+ average) on breakout
Declining volume often signals false breakout
Rising volume during range formation shows interest
Market Context Filters
Best Conditions:
Trending market days (SPY/QQQ with clear direction)
Earnings reactions or news-driven moves
High-volume stocks with good liquidity
Volatility above average (VIX considerations)
Avoid Trading When:
Extremely low volume days
Major economic announcements pending
Holidays or half-days
Choppy, sideways market conditions
Risk Management Rules
Position Sizing
Conservative: Risk 0.5% of account per trade
Moderate: Risk 1% of account per trade
Aggressive: Risk 2% maximum per trade
Stop Loss Placement
Inside the range: Quick exit but higher stop-out rate
Outside opposite level: More room but larger risk
ATR-based: 1.5-2x Average True Range below entry
Profit Taking
Target 1: 1x range size (take 50% off)
Target 2: 2x range size (take 25% off)
Runner: Trail remaining 25% with moving stops
Specific Entry Techniques
Breakout Entry Methods
Method 1: Immediate Entry
Enter as soon as price closes above/below range
Fastest entry but highest false signal rate
Best for strong momentum situations
Method 2: Pullback Entry
Wait for breakout, then pullback to range level
Enter when price bounces off former resistance/support
Better risk/reward but may miss some moves
Method 3: Volume Confirmation
Wait for breakout + volume spike
Enter after volume confirmation candle
Reduces false signals significantly
Multiple Timeframe Entries
Aggressive: OR5 break → immediate entry
Conservative: OR5 + OR15 + OR30 all align → enter
Balanced: OR15 break with OR30 support → enter
Common Mistakes to Avoid
1. Trading Poor-Quality Ranges
❌ Don't trade ranges that are too narrow or too wide
✅ Focus on clean, well-defined ranges with good volume
2. Ignoring Volume
❌ Don't chase breakouts without volume confirmation
✅ Always check for volume spike on breakouts
3. Over-Trading
❌ Don't force trades when ranges are unclear
✅ Wait for high-probability setups only
4. Poor Risk Management
❌ Don't risk more than planned or use tight stops in volatile conditions
✅ Stick to predetermined risk levels
5. Fighting the Trend
❌ Don't fade breakouts in strongly trending markets
✅ Align trades with overall market direction
Daily Trading Routine
Pre-Market (8:00-9:30 AM)
Check overnight news and earnings
Review major indices (SPY, QQQ, IWM)
Identify potential opening range candidates
Set alerts for range breakouts
Market Open (9:30-10:00 AM)
Watch opening range formation
Note volume and price action quality
Mark key levels on charts
Prepare for breakout signals
Trading Session (10:00 AM - 4:00 PM)
Execute breakout strategies
Manage existing positions
Trail stops as profits develop
Look for additional setups
Post-Market Review
Analyze winning and losing trades
Review range quality vs. outcomes
Identify improvement areas
Prepare for next session
Best Stocks/ETFs for Opening Range Trading
Large Cap Stocks (Best for beginners):
AAPL, MSFT, GOOGL, AMZN, TSLA
High liquidity, predictable behavior
Good range formation most days
ETFs (Consistent patterns):
SPY, QQQ, IWM, XLF, XLE
Excellent liquidity
Clear range boundaries
Mid-Cap Growth (Advanced traders):
Stocks with good volume (1M+ shares daily)
Recent news catalysts
Clean technical patterns
Performance Optimization
Track These Metrics:
Win rate by range type (OR5 vs OR15 vs OR30)
Average R/R (risk vs reward ratio)
Best performing market conditions
Time of day performance
Continuous Improvement:
Keep detailed trade journal
Review failed breakouts for patterns
Adjust position sizing based on win rate
Refine entry timing based on backtesting
Final Tips for Success
Start small - Paper trade or use tiny positions initially
Focus on quality - Better to miss trades than take bad ones
Stay disciplined - Stick to your rules even during losing streaks
Adapt to conditions - What works in trending markets may fail in choppy conditions
Keep learning - Markets evolve, so should your approach
The opening range strategy is powerful because it captures natural market behavior, but like all strategies, it requires practice, discipline, and proper risk management to be profitable long-term.
Live Market - Performance MonitorLive Market — Performance Monitor
Study material (no code) — step-by-step training guide for learners
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1) What this tool is — short overview
This indicator is a live market performance monitor designed for learning. It scans price, volume and volatility, detects order blocks and trendline events, applies filters (volume & ATR), generates trade signals (BUY/SELL), creates simple TP/SL trade management, and renders a compact dashboard summarizing market state, risk and performance metrics.
Use it to learn how multi-factor signals are constructed, how Greeks-style sensitivity is replaced by volatility/ATR reasoning, and how a live dashboard helps monitor trade quality.
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2) Quick start — how a learner uses it (step-by-step)
1. Add the indicator to a chart (any ticker / timeframe).
2. Open inputs and review the main groups: Order Block, Trendline, Signal Filters, Display.
3. Start with defaults (OB periods ≈ 7, ATR multiplier 0.5, volume threshold 1.2) and observe the dashboard on the last bar.
4. Walk the chart back in time (use the last-bar update behavior) and watch how signals, order blocks, trendlines, and the performance counters change.
5. Run the hands-on labs below to build intuition.
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3) Main configurable inputs (what you can tweak)
• Order Block Relevant Periods (default ~7): number of consecutive candles used to define an order block.
• Min. Percent Move for Valid OB (threshold): minimum percent move required for a valid order block.
• Number of OB Channels: how many past order block lines to keep visible.
• Trendline Period (tl_period): pivot lookback for detecting highs/lows used to draw trendlines.
• Use Wicks for Trendlines: whether pivot uses wicks or body.
• Extension Bars: how far trendlines are projected forward.
• Use Volume Filter + Volume Threshold Multiplier (e.g., 1.2): requires volume to be greater than multiplier × average volume.
• Use ATR Filter + ATR Multiplier: require bar range > ATR × multiplier to filter noise.
• Show Targets / Table settings / Colors for visualization.
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4) Core building blocks — what the script computes (plain language)
Price & trend:
• Spot / LTP: current close price.
• EMA 9 / 21 / 50: fast, medium, slow moving averages to define short/medium trend.
o trend_bullish: EMA9 > EMA21 > EMA50
o trend_bearish: EMA9 < EMA21 < EMA50
o trend_neutral: otherwise
Volatility & noise:
• ATR (14): average true range used for dynamic target and filter sizing.
• dynamic_zone = ATR × atr_multiplier: minimum bar range required for meaningful move.
• Annualized volatility: stdev of price changes × sqrt(252) × 100 — used to classify volatility (HIGH/MEDIUM/LOW).
Momentum & oscillators:
• RSI 14: overbought/oversold indicator (thresholds 70/30).
• MACD: EMA(12)-EMA(26) and a 9-period signal line; histogram used for momentum direction and strength.
• Momentum (ta.mom 10): raw momentum over 10 bars.
Mean reversion / band context:
• Bollinger Bands (20, 2σ): upper, mid, lower.
o price_position measures where price sits inside the band range as 0–100.
Volume metrics:
• avg_volume = SMA(volume, 20) and volume_spike = volume > avg_volume × volume_threshold
o volume_ratio = volume / avg_volume
Support & Resistance:
• support_level = lowest low over 20 bars
• resistance_level = highest high over 20 bars
• current_position = percent of price between support & resistance (0–100)
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5) Order Block detection — concept & logic
What it tries to find: a bar (the base) followed by N candles in the opposite direction (a classical order block setup), with a minimum % move to qualify. The script records the high/low of the base candle, averages them, and plots those levels as OB channels.
How learners should think about it (conceptual):
1. An order block is a signature area where institutions (theory) left liquidity — often seen as a large bar followed by a sequence of directional candles.
2. This indicator uses a configurable number of subsequent candles to confirm that the pattern exists.
3. When found, it stores and displays the base candle’s high/low area so students can see how price later reacts to those zones.
Implementation note for learners: the tool keeps a limited history of OB lines (ob_channels). When new OBs exceed the count, the oldest lines are removed — good practice to avoid clutter.
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6) Trendline detection — idea & interpretation
• The script finds pivot highs and lows using a symmetric lookback (tl_period and half that as right/left).
• It then computes a trendline slope from successive pivots and projects the line forward (extension_bars).
• Break detection: Resistance break = close crosses above the projected resistance line; Support break = close crosses below projected support.
Learning tip: trendlines here are computed from pivot points and time. Watch how changing tl_period (bigger = smoother, fewer pivots) alters the trendlines and break signals.
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7) Signal generation & filters — step-by-step
1. Primary triggers:
o Bullish trigger: order block bullish OR resistance trendline break.
o Bearish trigger: bearish order block OR support trendline break.
2. Filters applied (both must pass unless disabled):
o Volume filter: volume must be > avg_volume × volume_threshold.
o ATR filter: bar range (high-low) must exceed ATR × atr_multiplier.
o Not in an existing trade: new trades only start if trade_active is false.
3. Trend confirmation:
o The primary trigger is only confirmed if trend is bullish/neutral for buys or bearish/neutral for sells (EMA alignment).
4. Result:
o When confirmed, a long or short trade is activated with TP/SL calculated from ATR multiples.
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8) Trade management — what the tool does after a signal
• Entry management: the script marks a trade as trade_active and sets long_trade or short_trade flags.
• TP & SL rules:
o Long: TP = high + 2×ATR ; SL = low − 1×ATR
o Short: TP = low − 2×ATR ; SL = high + 1×ATR
• Monitoring & exit:
o A trade closes when price reaches TP or SL.
o When TP/SL hit, the indicator updates win_count and total_pnl using a very simple calculation (difference between TP/SL and previous close).
o Visual lines/labels are drawn for TP and updated as the trade runs.
Important learner notes:
• The script does not store a true entry price (it uses close in its P&L math), so PnL is an approximation — treat this as a learning proxy, not a position accounting system.
• There’s no sizing, slippage, or fee accounted — students must manually factor these when translating to real trades.
• This indicator is not a backtesting strategy; strategy.* functions would be needed for rigorous backtest results.
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9) Signal strength & helper utilities
• Signal strength is a composite score (0–100) made up of four signals worth 25 points each:
1. RSI extreme (overbought/oversold) → 25
2. Volume spike → 25
3. MACD histogram magnitude increasing → 25
4. Trend existence (bull or bear) → 25
• Progress bars (text glyphs) are used to visually show RSI and signal strength on the table.
Learning point: composite scoring is a way to combine orthogonal signals — study how changing weights changes outcomes.
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10) Dashboard — how to read each section (walkthrough)
The dashboard is split into sections; here's how to interpret them:
1. Market Overview
o LTP / Change%: immediate price & daily % change.
2. RSI & MACD
o RSI value plus progress bar (overbought 70 / oversold 30).
o MACD histogram sign indicates bullish/bearish momentum.
3. Volume Analysis
o Volume ratio (current / average) and whether there’s a spike.
4. Order Block Status
o Buy OB / Sell OB: the average base price of detected order blocks or “No Signal.”
5. Signal Status
o 🔼 BUY or 🔽 SELL if confirmed, or ⚪ WAIT.
o No-trade vs Active indicator summarizing market readiness.
6. Trend Analysis
o Trend direction (from EMAs), market sentiment score (composite), volatility level and band/position metrics.
7. Performance
o Win Rate = wins / signals (percentage)
o Total PnL = cumulative PnL (approximate)
o Bull / Bear Volume = accumulated volumes attributable to signals
8. Support & Resistance
o 20-bar highest/lowest — use as nearby reference points.
9. Risk & R:R
o Risk Level from ATR/price as a percent.
o R:R Ratio computed from TP/SL if a trade is active.
10. Signal Strength & Active Trade Status
• Numeric strength + progress bar and whether a trade is currently active with TP/SL display.
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11) Alerts — what will notify you
The indicator includes pre-built alert triggers for:
• Bullish confirmed signal
• Bearish confirmed signal
• TP hit (long/short)
• SL hit (long/short)
• No-trade zone
• High signal strength (score > 75%)
Training use: enable alerts during a replay session to be notified when the indicator would have signalled.
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12) Labs — hands-on exercises for learners (step-by-step)
Lab A — Order Block recognition
1. Pick a 15–30 minute timeframe on a liquid ticker.
2. Use default OB periods (7). Mark each time the dashboard shows a Buy/Sell OB.
3. Manually inspect the chart at the base candle and the following sequence — draw the OB zone by hand and watch later price reactions to it.
4. Repeat with OB periods 5 and 10; note stability vs noise.
Lab B — Trendline break confirmation
1. Increase trendline period (e.g., 20), watch trendlines form from pivots.
2. When a resistance break is flagged, compare with MACD & volume: was momentum aligned?
3. Note false breaks vs confirmed moves — change extension_bars to see projection effects.
Lab C — Filter sensitivity
1. Toggle Use Volume Filter off, and record the number and quality of signals in a 2-day window.
2. Re-enable volume filter and change threshold from 1.2 → 1.6; note how many low-quality signals are filtered out.
Lab D — Trade management simulation
1. For each signalled trade, record the time, close entry approximation, TP, SL, and eventual hit/miss.
2. Compute actual PnL if you had entered at the open of the next bar to compare with the script’s PnL math.
3. Tabulate win rate and average R:R.
Lab E — Performance review & improvement
1. Build a spreadsheet of signals over 30–90 periods with columns: Date, Signal type, Entry price (real), TP, SL, Exit, PnL, Notes.
2. Analyze which filters or indicators contributed most to winners vs losers and adjust weights.
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13) Common pitfalls, assumptions & implementation notes (things to watch)
• P&L simplification: total_pnl uses close as a proxy entry price. Real entry/exit prices and slippage are not recorded — so PnL is approximate.
• No position sizing or money management: the script doesn’t compute position size from equity or risk percent.
• Signal confirmation logic: composite "signal_strength" is a simple 4×25 point scheme — explore different weights or additional signals.
• Order block detection nuance: the script defines the base candle and checks the subsequent sequence. Be sure to verify whether the intended candle direction (base being bullish vs bearish) aligns with academic/your trading definition — read the code carefully and test.
• Trendline slope over time: slope is computed using timestamps; small differences may make lines sensitive on very short timeframes — using bar_index differences is usually more stable.
• Not a true backtester: to evaluate performance statistically you must transform the logic into a strategy script that places hypothetical orders and records exact entry/exit prices.
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14) Suggested improvements for advanced learners
• Record true entry price & timestamp for accurate PnL.
• Add position sizing: risk % per trade using SL distance and account size.
• Convert to strategy. (Pine Strategy)* to run formal backtests with equity curves, drawdowns, and metrics (Sharpe, Sortino).
• Log trades to an external spreadsheet (via alerts + webhook) for offline analysis.
• Add statistics: average win/loss, expectancy, max drawdown.
• Add additional filters: news time blackout, market session filters, multi-timeframe confirmation.
• Improve OB detection: combine wick/body, volume spike at base bar, and liquidity sweep detection.
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15) Glossary — quick definitions
• ATR (Average True Range): measure of typical range; used to size targets and stops.
• EMA (Exponential Moving Average): trend smoothing giving more weight to recent prices.
• RSI (Relative Strength Index): momentum oscillator; >70 overbought, <30 oversold.
• MACD: momentum oscillator using difference of two EMAs.
• Bollinger Bands: volatility bands around SMA.
• Order Block: a base candle area with subsequent confirmation candles; a zone of institutional interest (learning model).
• Pivot High/Low: local turning point defined by candles on both sides.
• Signal Strength: combined score from multiple indicators.
• Win Rate: proportion of signals that hit TP vs total signals.
• R:R (Risk:Reward): ratio of potential reward (TP distance) to risk (entry to SL).
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16) Limitations & assumptions (be explicit)
• This is an indicator for learning — not a trading robot or broker connection.
• No slippage, fees, commissions or tie-in to real orders are considered.
• The logic is heuristic (rule-of-thumb), not a guarantee of performance.
• Results are sensitive to timeframe, market liquidity, and parameter choices.
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17) Practical classroom / study plan (4 sessions)
• Session 1 — Foundations: Understand EMAs, ATR, RSI, MACD, Bollinger Bands. Run the indicator and watch how these numbers change on a single day.
• Session 2 — Zones & Filters: Study order blocks and trendlines. Test volume & ATR filters and note changes in false signals.
• Session 3 — Simulated trading: Manually track 20 signals, compute real PnL and compare to the dashboard.
• Session 4 — Improvement plan: Propose changes (e.g., better PnL accounting, alternative OB rule) and test their impact.
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18) Quick reference checklist for each signal
1. Was an order block or trendline break detected? (primary trigger)
2. Did volume meet threshold? (filter)
3. Did ATR filter (bar size) show a real move? (filter)
4. Was trend aligned (EMA 9/21/50)? (confirmation)
5. Signal confirmed → mark entry approximation, TP, SL.
6. Monitor dashboard (Signal Strength, Volatility, No-trade zone, R:R).
7. After exit, log real entry/exit, compute actual PnL, update spreadsheet.
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19) Educational caveat & final note
This tool is built for training and analysis: it helps you see how common technical building blocks combine into trade ideas, but it is not a trading recommendation. Use it to develop judgment, to test hypotheses, and to design robust systems with proper backtesting and risk control before risking capital.
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20) Disclaimer (must include)
Training & Educational Only — This material and the indicator are provided for educational purposes only. Nothing here is investment advice or a solicitation to buy or sell financial instruments. Past simulated or historical performance does not predict future results. Always perform full backtesting and risk management, and consider seeking advice from a qualified financial professional before trading with real capital.
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Intrabar Volume Delta — RealTime + History (Stocks/Crypto/Forex)Intrabar Volume Delta Grid — RealTime + History (Stocks/Crypto/Forex)
# Short Description
Shows intrabar Up/Down volume, Delta (absolute/relative) and UpShare% in a compact grid for both real-time and historical bars. Includes an MTF (M1…D1) dashboard, contextual coloring, density controls, and alerts on Δ and UpShare%. Smart historical splitting (“History Mode”) for Crypto/Futures/FX.
---
# What it does (Quick)
* **UpVol / DownVol / Δ / UpShare%** — visualizes order-flow inside each candle.
* **Real-time** — accumulates intrabar volume live by tick-direction.
* **History Mode** — splits Up/Down on closed bars via simple or range-aware logic.
* **MTF Dashboard** — one table view across M1, M5, M15, M30, H1, H4, D1 (Vol, Up/Down, Δ%, Share, Trend).
* **Contextual opacity** — stronger signals appear bolder.
* **Label density** — draw every N-th bar and limit to last X bars for performance.
* **Alerts** — thresholds for |Δ|, Δ%, and UpShare%.
---
# How it works (Real-Time vs History)
* **Real-time (open bar):** volume increments into **UpVolRT** or **DownVolRT** depending on last price move (↑ goes to Up, ↓ to Down). This approximates live order-flow even when full tick history isn’t available.
* **History (closed bars):**
* **None** — no split (Up/Down = 0/0). Safest for equities/indices with unreliable tick history.
* **Approx (Close vs Open)** — all volume goes to candle direction (green → Up 100%, red → Down 100%). Fast but yields many 0/100% bars.
* **Price Action Based** — splits by Close position within High-Low range; strength = |Close−mid|/(High−Low). Above mid → more Up; below mid → more Down. Falls back to direction if High==Low.
* **Auto** — **Stocks/Index → None**, **Crypto/Futures/FX → Approx**. If you see too many 0/100 bars, switch to **Price Action Based**.
---
# Rows & Meaning
* **Volume** — total bar volume (no split).
* **UpVol / DownVol** — directional intrabar volume.
* **Delta (Δ)** — UpVol − DownVol.
* **Absolute**: raw units
* **Relative (Δ%)**: Δ / (Up+Down) × 100
* **Both**: shows both formats
* **UpShare%** — UpVol / (Up+Down) × 100. >50% bullish, <50% bearish.
* Helpful icons: ▲ (>65%), ▼ (<35%).
---
# MTF Dashboard (🔧 Enable Dashboard)
A single table with **Vol, Up, Down, Δ%, Share, Trend (🔼/🔽/⏭️)** for selected timeframes (M1…D1). Great for a fast “panorama” read of flow alignment across horizons.
---
# Inputs (Grouped)
## Display
* Toggle rows: **Volume / Up / Down / Delta / UpShare**
* **Delta Display**: Absolute / Relative / Both
## Realtime & History
* **History Mode**: Auto / None / Approx / Price Action Based
* **Compact Numbers**: 1.2k, 1.25M, 3.4B…
## Theme & UI
* **Theme Mode**: Auto / Light / Dark
* **Row Spacing**: vertical spacing between rows
* **Top Row Y**: moves the whole grid vertically
* **Draw Guide Lines**: faint dotted guides
* **Text Size**: Tiny / Small / Normal / Large
## 🔧 Dashboard Settings
* **Enable Dashboard**
* **📏 Table Text Size**: Tiny…Huge
* **🦓 Zebra Rows**
* **🔲 Table Border**
## ⏰ Timeframes (for Dashboard)
* **M1…D1** toggles
## Contextual Coloring
* **Enable Contextual Coloring**: opacity by signal strength
* **Δ% cap / Share offset cap**: saturation caps
* **Min/Max transparency**: solid vs faint extremes
## Label Density & Size
* **Show every N-th bar**: draw labels only every Nth bar
* **Limit to last X bars**: keep labels only in the most recent X bars
## Colors
* Up / Down / Text / Guide
## Alerts
* **Delta Threshold (abs)** — |Δ| in volume units
* **UpShare > / <** — bullish/bearish thresholds
* **Enable Δ% Alert**, **Δ% > +**, **Δ% < −** — relative delta levels
---
# How to use (Quick Start)
1. Add the indicator to your chart (overlay=false → separate pane).
2. **History Mode**:
* Crypto/Futures/FX → keep **Auto** or switch to **Price Action Based** for richer history.
* Stocks/Index → prefer **None** or **Price Action Based** for safer splits.
3. **Label Density**: start with **Limit to last X bars = 30–150** and **Show every N-th bar = 2–4**.
4. **Contextual Coloring**: keep on to emphasize strong Δ% / Share moves.
5. **Dashboard**: enable and pick only the TFs you actually use.
6. **Alerts**: set thresholds (ideas below).
---
# Alerts (in TradingView)
Add alert → pick this indicator → choose any of:
* **Delta exceeds threshold** (|Δ| > X)
* **UpShare above threshold** (UpShare% > X)
* **UpShare below threshold** (UpShare% < X)
* **Relative Delta above +X%**
* **Relative Delta below −X%**
**Starter thresholds (tune per symbol & TF):**
* **Crypto M1/M5**: Δ% > +25…35 (bullish), Δ% < −25…−35 (bearish)
* **FX (tick volume)**: UpShare > 60–65% or < 40–35%
* **Stocks (liquid)**: set **Absolute Δ** by typical volume scale (e.g., 50k / 100k / 500k)
---
# Notes by Market Type
* **Crypto/Futures**: 24/7 and high liquidity — **Price Action Based** often gives nicer history splits than Approx.
* **Forex (FX)**: TradingView volume is typically **tick volume** (not true exchange volume). Treat Δ/Share as tick-based flow, still very useful intraday.
* **Stocks/Index**: historical tick detail can be limited. **None** or **Price Action Based** is a safer default. If you see too many 0/100% shares, switch away from Approx.
---
# “All Timeframes” accuracy
* Works on **any TF** (M1 → D1/W1).
* **Real-time accuracy** is strong for the open bar (live accumulation).
* **Historical accuracy** depends on your **History Mode** (None = safest, Approx = fastest/simplest, Price Action Based = more nuanced).
* The MTF dashboard uses `request.security` and therefore follows the same logic per TF.
---
# Trade Ideas (Use-Cases)
* **Scalping (M1–M5)**: a spike in Δ% + UpShare>65% + rising total Vol → momentum entries.
* **Intraday (M5–M30–H1)**: when multiple TFs show aligned Δ%/Share (e.g., M5 & M15 bullish), join the trend.
* **Swing (H4–D1)**: persistent Δ% > 0 and UpShare > 55–60% → structural accumulation bias.
---
# Advantages
* **True-feeling live flow** on the open bar.
* **Adaptable history** (three modes) to match data quality.
* **Clean visual layout** with guides, compact numbers, contextual opacity.
* **MTF snapshot** for quick bias read.
* **Performance controls** (last X bars, every N-th bar).
---
# Limitations & Care
* **FX uses tick volume** — interpret Δ/Share accordingly.
* **History Mode is an approximation** — confirm with trend/structure/liquidity context.
* **Illiquid symbols** can produce noisy or contradictory signals.
* **Too many labels** can slow charts → raise N, lower X, or disable guides.
---
# Best Practices (Checklist)
* Crypto/Futures: prefer **Price Action Based** for history.
* Stocks: **None** or **Price Action Based**; be cautious with **Approx**.
* FX: pair Δ% & UpShare% with session context (London/NY) and volatility.
* If labels overlap: tweak **Row Spacing** and **Text Size**.
* In the dashboard, keep only the TFs you actually act on.
* Alerts: start around **Δ% 25–35** for “punchy” moves, then refine per asset.
---
# FAQ
**1) Why do some closed bars show 0%/100% UpShare?**
You’re on **Approx** history mode. Switch to **Price Action Based** for smoother splits.
**2) Δ% looks strong but price doesn’t move — why?**
Δ% is an **order-flow** measure. Price also depends on liquidity pockets, sessions, news, higher-timeframe structure. Use confirmations.
**3) Performance slowdown — what to do?**
Lower **Limit to last X bars** (e.g., 30–100), increase **Show every N-th bar** (2–6), or disable **Draw Guide Lines**.
**4) Dashboard values don’t “match” the grid exactly?**
Dashboard is multi-TF via `request.security` and follows the history logic per TF. Differences are normal.
---
# Short “Store” Marketing Blurb
Intrabar Volume Delta Grid reveals the order-flow inside every candle (Up/Down, Δ, UpShare%) — live and on history. With smart history splitting, an MTF dashboard, contextual emphasis, and flexible alerts, it helps you spot momentum and bias across Crypto, Forex (tick volume), and Stocks. Tidy labels and compact numbers keep the panel readable and fast.
