MTF Round Level Reversal [RunRox]🧲 MTF Round Level Reversal is an indicator designed to highlight price levels on the chart where the market encountered significant resistance or support at round numbers, failing to break through large clusters of orders.
In many cases, price revisits these round-number levels to absorb the remaining liquidity, offering potential reversal or continuation trade opportunities.
✏️ EXAMPLE
Here’s an example demonstrating how this indicator works and how its logic is structured:
As shown in the screenshot above, price encountered resistance at round-number levels, clearly reacting off these areas.
Afterward, the market pulled back, presenting opportunities to enter trades targeting these previously established open levels.
This logic is based on the observation that price often seeks to revisit these open round-number levels due to the residual liquidity resting there.
While effective across various markets, this indicator performs particularly well with stocks or assets priced at higher values.
For a level to appear on the chart, price must first encounter a round-number value and clearly reverse from it, leaving a visible reaction on the chart. After this occurs, the indicator will mark this level as fully formed and display it as an active reversal area.
⚙️ SETTINGS
🔷 Timeframe – Choose any timeframe from which you’d like the indicator to source level data.
🔷 Period – Defines the number of candles required on both sides (left and right) to confirm and fully form a level.
🔷 Rounding Level – Adjusts price rounding precision when detecting levels (from 0.0001 up to 5000).
🔷 Color – Customize the color and transparency of displayed levels.
🔷 Line Style – Select the desired line style for level visualization.
🔷 Label Size – Set the font size for the level labels displayed on the chart.
🔷 Move Label to the Right – Move level labels to the right side of the screen for better visibility.
🔷 Label Offset – Specifies how many bars labels should be offset from the chart’s right edge.
🔷 Delete Filled Level – Automatically removes levels from the chart after they’ve been revisited or filled.
🔷 Calculation Bars – Determines the number of recent bars considered when calculating and identifying levels.
🔶 There are numerous ways to apply this indicator in your trading strategy. You can look for trades targeting these round-number levels or identify reversal setups forming at these high-liquidity zones. The key insight is understanding that these levels represent significant liquidity areas, which price frequently revisits and retests.
We greatly appreciate your feedback and suggestions to further improve and enhance this indicator!
Komut dosyalarını "liquidity" için ara
Quarterly Theory ICT 01 [TradingFinder] XAMD + Q1-Q4 Sessions🔵 Introduction
The Quarterly Theory ICT indicator is an advanced analytical system based on the concepts of ICT (Inner Circle Trader) and fractal time. It divides time into quarterly periods and accurately determines entry and exit points for trades by using the True Open as the starting point of each cycle. This system is applicable across various time frames including annual, monthly, weekly, daily, and even 90-minute sessions.
Time is divided into four quarters: in the first quarter (Q1), which is dedicated to the Accumulation phase, the market is in a consolidation state, laying the groundwork for a new trend; in the second quarter (Q2), allocated to the Manipulation phase (also known as Judas Swing), sudden price changes and false moves occur, marking the true starting point of a trend change; the third quarter (Q3) is dedicated to the Distribution phase, during which prices are broadly distributed and price volatility peaks; and the fourth quarter (Q4), corresponding to the Continuation/Reversal phase, either continues or reverses the previous trend.
By leveraging smart algorithms and technical analysis, this system identifies optimal price patterns and trading positions through the precise detection of stop-run and liquidity zones.
With the division of time into Q1 through Q4 and by incorporating key terms such as Quarterly Theory ICT, True Open, Accumulation, Manipulation (Judas Swing), Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, this system enables traders to identify market trends and make informed trading decisions using real data and precise analysis.
♦ Important Note :
This indicator and the "Quarterly Theory ICT" concept have been developed based on material published in primary sources, notably the articles on Daye( traderdaye ) and Joshuuu . All copyright rights are reserved.
🔵 How to Use
The Quarterly Theory ICT strategy is built on dividing time into four distinct periods across various time frames such as annual, monthly, weekly, daily, and even 90-minute sessions. In this approach, time is segmented into four quarters, during which the phases of Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal appear in a systematic and recurring manner.
The first segment (Q1) functions as the Accumulation phase, where the market consolidates and lays the foundation for future movement; the second segment (Q2) represents the Manipulation phase, during which prices experience sudden initial changes, and with the aid of the True Open concept, the real starting point of the market’s movement is determined; in the third segment (Q3), the Distribution phase takes place, where prices are widely dispersed and price volatility reaches its peak; and finally, the fourth segment (Q4) is recognized as the Continuation/Reversal phase, in which the previous trend either continues or reverses.
This strategy, by harnessing the concepts of fractal time and smart algorithms, enables precise analysis of price patterns across multiple time frames and, through the identification of key points such as stop-run and liquidity zones, assists traders in optimizing their trading positions. Utilizing real market data and dividing time into Q1 through Q4 allows for a comprehensive and multi-level technical analysis in which optimal entry and exit points are identified by comparing prices to the True Open.
Thus, by focusing on keywords like Quarterly Theory ICT, True Open, Accumulation, Manipulation, Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, the Quarterly Theory ICT strategy acts as a coherent framework for predicting market trends and developing trading strategies.
🔵b]Settings
Cycle Display Mode: Determines whether the cycle is displayed on the chart or on the indicator panel.
Show Cycle: Enables or disables the display of the ranges corresponding to each quarter within the micro cycles (e.g., Q1/1, Q1/2, Q1/3, Q1/4, etc.).
Show Cycle Label: Toggles the display of textual labels for identifying the micro cycle phases (for example, Q1/1 or Q2/2).
Table Display Mode: Enables or disables the ability to display cycle information in a tabular format.
Show Table: Determines whether the table—which summarizes the phases (Q1 to Q4)—is displayed.
Show More Info: Adds additional details to the table, such as the name of the phase (Accumulation, Manipulation, Distribution, or Continuation/Reversal) or further specifics about each cycle.
🔵 Conclusion
Quarterly Theory ICT provides a fractal and recurring approach to analyzing price behavior by dividing time into four quarters (Q1, Q2, Q3, and Q4) and defining the True Open at the beginning of the second phase.
The Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal phases repeat in each cycle, allowing traders to identify price patterns with greater precision across annual, monthly, weekly, daily, and even micro-level time frames.
Focusing on the True Open as the primary reference point enables faster recognition of potential trend changes and facilitates optimal management of trading positions. In summary, this strategy, based on ICT principles and fractal time concepts, offers a powerful framework for predicting future market movements, identifying optimal entry and exit points, and managing risk in various trading conditions.
MT-Turnover.IndicatorMT-Turnover Indicator – Market Liquidity & Activity Gauge
Overview
The MT-Turnover Indicator is a TradingView tool designed to measure market liquidity and trading activity by tracking the turnover rate of a stock. It calculates the turnover percentage by comparing the trading volume to the number of outstanding shares, providing traders with insights into how actively a stock is being traded.
By incorporating a moving average (MA) of turnover and a customizable high turnover threshold, this indicator helps identify periods of increased market participation, potential breakouts, or distribution phases.
Key Features
✔ Turnover Rate Calculation – Expresses turnover as a percentage of outstanding shares
✔ Customizable Moving Average (MA) for Trend Analysis – Smoothens turnover fluctuations for better trend identification
✔ High Turnover Level Alert – Marks periods when turnover exceeds a predefined threshold
✔ Histogram Visualization – Shows turnover dynamics with clear green (above MA) and red (below MA) bars
✔ High Turnover Signal Markers – Flags exceptionally high turnover events for quick identification
How It Works
1. Turnover Rate Calculation
• Formula:

• Configurable Outstanding Shares (in millions) to match the stock being analyzed
2. Turnover Moving Average (MA) for Trend Analysis
• A simple moving average (SMA) of turnover is calculated over a user-defined period (default: 20 days)
• Green bars indicate turnover above MA, suggesting increased activity
• Red bars indicate turnover below MA, signaling lower participation
3. High Turnover Threshold
• Users can set a high turnover level (%) to mark exceptionally active trading periods
• When turnover exceeds this level, a red triangle marker appears above the bar
4. Reference Line & Informative Table
• A dashed red reference line marks the high turnover threshold
• A floating table in the top-right corner provides a quick summary
How to Use This Indicator
📈 For Breakout Traders – High turnover can indicate strong buying interest, often preceding breakouts
📉 For Risk Management – Spikes in turnover may signal distribution phases or panic selling
🔎 For Liquidity Analysis – Helps gauge how liquid a stock is, which can impact price stability
Conclusion
The MT-Turnover Indicator is a powerful tool for identifying periods of high market activity, helping traders detect potential breakouts, reversals, or strong accumulation/distribution phases. By visualizing turnover with a moving average and customizable threshold, it provides valuable insights into market participation trends.
➡ Add this indicator to your TradingView chart and improve your liquidity-based trading decisions today! 🚀
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.
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.
XAUUSD BOS + Retest Looser Bot//@version=5
indicator("SMC Map — BOS/CHoCH + PD + Liquidity + Killzones", overlay=true)
// === CONFIG ===
pd_tf = input.timeframe("240", "HTF for PD array")
show_killzone = input.bool(true, "Show Killzones")
// === HTF SWINGS ===
htf_high = request.security(syminfo.tickerid, pd_tf, high)
htf_low = request.security(syminfo.tickerid, pd_tf, low)
pd_mid = (htf_high + htf_low) / 2
// Plot PD midline
plot(pd_mid, title="PD 50%", color=color.gray, linewidth=2)
// === SWING STRUCTURE ===
var float swing_high = na
var float swing_low = na
is_swing_high = ta.highest(high, 3) == high and close < high
is_swing_low = ta.lowest(low, 3) == low and close > low
if (is_swing_high)
swing_high := high
if (is_swing_low)
swing_low := low
// === BOS / CHoCH ===
bos_up = not na(swing_high) and close > swing_high
bos_down = not na(swing_low) and close < swing_low
var int structure_dir = 0 // 0=neutral, 1=up, -1=down
choch_up = false
choch_down = false
if (bos_up)
choch_up := structure_dir == -1
structure_dir := 1
if (bos_down)
choch_down := structure_dir == 1
structure_dir := -1
// === PLOTS ===
plotshape(bos_up, title="BOS UP", style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small)
plotshape(bos_down, title="BOS DOWN", style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small)
plotshape(choch_up, title="CHOCH UP", style=shape.labelup, location=location.belowbar, color=color.lime, size=size.tiny, text="CHOCH")
plotshape(choch_down, title="CHOCH DOWN", style=shape.labeldown, location=location.abovebar, color=color.maroon, size=size.tiny, text="CHOCH")
plot(swing_high, title="Swing High Liquidity", color=color.new(color.green, 50), style=plot.style_cross, linewidth=1)
plot(swing_low, title="Swing Low Liquidity", color=color.new(color.red, 50), style=plot.style_cross, linewidth=1)
// === KILLZONE ===
in_london = (hour >= 6 and hour < 11)
in_ny = (hour >= 12 and hour < 18)
bgcolor(show_killzone and in_london ? color.new(color.green, 90) : na)
bgcolor(show_killzone and in_ny ? color.new(color.blue, 90) : na)
Smart Money Trap SignalSmart Money Trap Signal – Indicator Description
The Smart Money Trap Signal is a precision-based trading tool designed to identify areas where institutional traders (smart money) are likely to trap retail traders through false breakouts and liquidity grabs. These traps often occur near key highs and lows, where retail traders are lured into trades just before price reverses sharply.
🔍 Key Features:
Liquidity Sweep Detection
Identifies false breakouts of recent swing highs or lows, signaling potential liquidity grabs by large players.
Reversal Confirmation
Confirms the trap using a classic price action reversal pattern (bullish or bearish engulfing), helping filter out weak signals.
Optional Volume Spike Filter
Allows additional confirmation based on a significant spike in volume, indicating potential institutional involvement.
Buy and Sell Trap Signals
🔴 Smart Money Short (SMT↓) – Triggered when price sweeps a high and reverses down.
🟢 Smart Money Long (SMT↑) – Triggered when price sweeps a low and reverses up.
Alerts & Labels
Real-time alert conditions and on-chart labels to help you catch setups without missing opportunities.
📈 How to Use:
Apply on Higher Timeframes (1H, 4H, Daily) for cleaner signals.
Look for SMT signals at key supply/demand zones or market structure points.
Combine with your existing trading strategy, such as order blocks or break of structure (BoS), for higher accuracy.
Use volume filter only if you're analyzing markets where volume data is reliable.
⚠️ Disclaimer:
This tool is meant to assist with trade identification, not trade execution. Always use proper risk management and validate setups with your trading plan.
CLMM Vault策略回测 (专业版) v5Explanation of the CLMM (Concentrated Liquidity - Market Maker) Strategy Backtesting Model Developed for the Sui Chain Vaults Protocol
Why Are We Doing This?
Conducting strategy backtesting is a crucial step for us to make data-driven decisions, validate the feasibility of strategies, and manage potential risks before committing real funds and significant development resources. A strategy that appears to have a high APY may perform entirely differently once real-world frictional costs (such as rebalancing fees and slippage) are deducted. The goal of this backtesting model is to quickly and cost-effectively identify which strategy parameter combinations have the potential to be profitable and which ones pose risks before formal development, thereby avoiding significant losses and providing data support for the project's direction.
Core Features of the Backtesting Model
We have built a "pro version" (v5) strategy simulator using TradingView's Pine Script. It can quickly simulate the core performance of our auto-compounding and rebalancing Vaults on historical price data, with the following main features:
Auto-Compounding: Continuously adds the generated fee income to the principal based on the set profit range (e.g., 0.01%).
Auto-Rebalancing: Simulates automatic rebalancing actions when the price exceeds the preset profit range and deducts the corresponding costs.
Smart Filtering Mechanism: To make the simulation closer to our ideal "smart" decision-making, it integrates three freely combinable filtering mechanisms:
Buffer Zone: Tolerates minor and temporary breaches of the profit range to avoid unnecessary rebalancing.
Breakout Confirmation: Requires the price to be in the trigger zone for N consecutive candles to confirm a breakout, filtering out market noise from "false breakouts."
Time Cooldown: Enforces a minimum time interval between two rebalances to prevent value-destroying high-frequency trading in extreme market conditions.
Important: Simplifications and Assumptions of the Model
To quickly prototype and iterate on the TradingView platform, we have made some key simplifications to the model.
A fully accurate backtest would require a deep simulation of on-chain liquidity pools (Pool Pair), calculating the price impact (Slippage) and impermanent loss (IL) caused by each rebalance on the pool. Since TradingView cannot access real-time on-chain liquidity data, we have made the following simplifications:
Simplified Rebalancing Costs: Instead of simulating real transaction slippage, we use a unified input parameter of single rebalance cost (%) to "bundle" and approximate the total of Gas fees, slippage, and realized impermanent loss.
Simplified Fee Income: Instead of calculating fees based on real-time trading volume, we directly input an average fee annualized return (%) as the core income assumption for our strategy.
How to Use and Test
Team members can load this script and test different strategies by adjusting the input parameters on the panel. The most critical parameters include: position profit range, average fee annualized return, single rebalance cost, and the switches and corresponding values of the above three smart filters.
