Liquidations Levels [RunRox]📈 Liquidation Levels is an indicator designed to visualize key price levels on the chart, highlighting potential reversal points where liquidity may trigger significant price movements.
Liquidity is essential in trading - price action consistently moves from one liquidity area to another. We’ve created this free indicator to help traders easily identify and visualize these liquidity zones on their charts.
📌 HOW IT WORKS
The indicator works by marking visible highs and lows, points widely recognized by traders. Because many traders commonly place their stop-loss orders beyond these visible extremes, significant liquidity accumulates behind these points. By analyzing trading volume and visible extremes, the indicator estimates areas where clusters of stop-loss orders (liquidity pools) are likely positioned, giving traders valuable insights into potential market moves.
As shown in the screenshot above, the price aggressively moved toward Sell-Side liquidity. After sweeping this liquidity level for the second time, it reversed and began targeting Buy-Side liquidity. This clearly demonstrates how price moves from one liquidity pool to another, continually seeking out liquidity to fuel its next directional move.
As shown in the screenshot, price levels with fewer anticipated trader stop-losses are indicated by less vibrant, faded colors. When the lines become more saturated and vivid, it signals that sufficient liquidity - in the form of clustered stop-losses has accumulated, potentially attracting price movement toward these areas.
⚙️ SETTINGS
🔹 Period – Increasing this setting makes the marked highs and lows more significant, filtering out minor price swings.
🔹 Low Volume – Select the color displayed for low-liquidity levels.
🔹 High Volume – Select the color displayed for high-liquidity levels.
🔹 Levels to Display – Choose between 1 and 15 nearest liquidity levels to be shown on the chart.
🔹 Volume Sensitivity – Adjust the sensitivity of the indicator to volume data on the chart.
🔹 Show Volume – Enable or disable the display of volume values next to each liquidity level.
🔹 Max Age – Limits displayed liquidity levels to those not older than the specified number of bars.
✅ HOW TO USE
One method of using this indicator is demonstrated in the screenshot above.
Price reached a high-liquidity level and showed an initial reaction. We then waited for a second confirmation - a liquidity sweep followed by a clear market structure break - to enter the trade.
Our target is set at the liquidity accumulated below, with the stop-loss placed behind the manipulation high responsible for the liquidity sweep.
By following this approach, you can effectively identify trading opportunities using this indicator.
🔶 We’ve made every effort to create an indicator that’s as simple and user-friendly as possible. We’ll continue to improve and enhance it based on your feedback and suggestions in the future.
Liquidity
Uptrick: Portfolio Allocation DiversificationIntro
The Uptrick: Portfolio Allocation Diversification script is designed to help traders and investors manage multiple assets simultaneously. It generates signals based on various trading systems, allocates capital using different diversification methods, and displays real-time metrics and performance tables on the chart. The indicator compares active trading strategies with a separate long-term holding (HODL) simulation, allowing you to see how a systematic trading approach stacks up against a simple buy-and-hold strategy.
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Trading System Selection
1. No signals (none)
In this mode, the script does not produce bullish or bearish indicators; every asset stays in a neutral stance. This setup is useful if you prefer to observe how capital might be distributed based solely on the chosen diversification method, with no influence from directional signals.
2. rsi – neutral
This mode uses an index-based measure of whether an asset appears overbought or oversold. It generates a bearish signal if market conditions point to overbought territory, and a bullish signal if they indicate oversold territory. If neither extreme surfaces, it remains neutral. Some traders apply this in sideways or range-bound conditions, where overbought and oversold levels often hint at possible turning points. It does not specifically account for divergence patterns.
3. rsi – long only
In this setting, the system watches for instances where momentum readings strengthen even if the asset’s price is still under pressure or setting new lows. It also considers oversold levels as potential signals for a bullish setup. When such conditions emerge, the script flags a possible move to the upside, ignoring indications that might otherwise suggest a bearish trend. This approach is generally favored by those who want to concentrate exclusively on identifying price recoveries.
4. rsi – short only
Here, the script focuses on spotting signs of deteriorating momentum while an asset’s price remains relatively high or attempts further gains. It also checks whether the market is drifting into overbought territory, suggesting a potential decline. Under such conditions, it issues a bearish signal. It provides no bullish alerts, making it particularly suitable for traders who look to take advantage of overvalued scenarios or protect themselves against sudden downward moves.
5. Deviation from fair value
Under this system, the script judges how far the current price may have strayed from what is considered typical, taking into account normal fluctuations. If the asset appears to be trading at an unusually low level compared to that reference, it is flagged as bullish. If it seems abnormally high, a bearish signal is issued. This can be applied in various market environments to seek opportunities that arise from perceived mispricing.
6. Percentile channel valuation
In this mode, the script determines where an asset's price stands within a historical distribution, highlighting whether it has reached unusually high or low territory compared to its recent past. When the price reaches what is deemed an extreme reading, it may indicate that a reversal is more likely. This approach is often used by traders who watch for statistical outliers and potential reversion to a more typical trading range.
7. ATH valuation
This technique involves comparing an asset's current price with its previously recorded peak values. The script then interprets whether the price is positioned so far below the all-time high that it looks discounted, or so close to that high that it could be overextended. Such perspective is favored by market participants who want to see if an asset still has ample room to climb before matching historic extremes, or if it is nearing a possible ceiling.
8. Z-score system
Here, the script measures how far above or below a standard reference average an asset's price may be, translated into standardized units. Substantial negative readings can suggest a price that might be unusually weak, prompting a bullish indication, while large positive readings could signal overextension and lead to a bearish call. This method is useful for traders watching for abrupt deviations from a norm that often invite a reversion to more balanced levels.
RSI Divergence Period
This input is particularly relevant for the RSI - Long Only and RSI - Short Only modes. The period determines how many bars in the past you compare RSI values to detect any divergences.
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Diversification Method
Once the script has determined a bullish, bearish, or neutral stance for each asset, it then calculates how to distribute capital among all included assets. The diversification method sets the weighting logic.
1. None
Gives each asset an equal weight. For example, if you have five included assets, each might get 20 percent. This is a simple baseline.
2. Risk-Adjusted Expected Return Using Volatility Clustering
Emphasizes each asset’s average returns relative to its observed risk or volatility tendencies. Assets that exhibit good risk-adjusted returns combined with moderate or lower volatility may receive higher weights than more volatile or less appealing assets. This helps steer capital toward assets that have historically provided a better ratio of return to risk.
3. Relative Strength
Allocates more capital to assets that show stronger price strength compared to a reference (for example, price above a long-term moving average plus a higher RSI). Assets in clear uptrends may be given higher allocations.
4. Trend-Following Indicators
Examines trend-based signals, like positive momentum measurements or upward-trending strength indicators, to assign more weight to assets demonstrating strong directional moves. This suits those who prefer to latch onto trending markets.
5. Volatility-Adjusted Momentum
Looks for assets that have strong price momentum but relatively subdued volatility. The script tends to reward assets that are trending well yet are not too volatile, aiming for stable upward performance rather than massive swings.
6. Correlation-Based Risk Parity
Attempts to weight assets in such a way that the overall portfolio risk is more balanced. Although it is not an advanced correlation matrix approach in a strict sense, it conceptually scales each asset’s weight so no single outlier heavily dominates.
7. Omega Ratio Maximization
Gives preference to assets with higher omega ratios. This ratio can be interpreted as the probability-weighted gains versus losses. Assets with a favorable skew are given more capital.
8. Liquidity-Weighted Valuation
Considers each asset’s average trading liquidity, such as the combination of volume and price. More liquid assets typically receive a higher allocation because they can be entered or exited with lower slippage. If the trading system signals bullishness, that can further boost the allocation, and if it signals bearishness, the allocation might be set to zero or reduced drastically.
9. Drawdown-Controlled Allocation (DCA)
Examines each asset’s maximum drawdown over a recent window. Assets experiencing lighter drawdowns (thus indicating somewhat less downside volatility) receive higher allocations, aiming for a smoother overall equity curve.
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Portfolio and Allocation Settings
Portfolio Value
Defines how much total capital is available for the strategy-based investment portion. For example, if set to 10,000, then each asset’s monetary allocation is determined by the percentage weighting times 10,000.
Use Fixed Allocation
When enabled, the script calculates the initial allocation percentages after 50 bars of data have passed. It then locks those percentages for the remainder of the backtest or real-time session. This feature allows traders to test a static weighting scenario to see how it differs from recalculating weights at each bar.
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HODL Simulator
The script has a separate simulation that accumulates positions in an asset whenever it appears to be recovering from an undervalued state. This parallel tracking is intended to contrast a simple buy-and-hold approach with the more adaptive allocation methods used elsewhere in the script.
HODL Buy Quantity
Each time an asset transitions from an undervalued state to a recovery phase, the simulator executes a purchase of a predefined quantity. For example, if set to 0.5 units, the system will accumulate this amount whenever conditions indicate a shift away from undervaluation.
HODL Buy Threshold
This parameter determines the level at which the simulation identifies an asset as transitioning out of an undervalued state. When the asset moves above this threshold after previously being classified as undervalued, a buy order is triggered. Over time, the performance of these accumulated positions is tracked, allowing for a comparison between this passive accumulation method and the more dynamic allocation strategy.
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Asset Table and Display Settings
The script displays data in multiple tables directly on your chart. You can toggle these tables on or off and position them in various corners of your TradingView screen.
Asset Info Table Position
This table provides key details for each included asset, displaying:
Symbol – Identifies the trading pair being monitored. This helps users keep track of which assets are included in the portfolio allocation process.
Current Trading Signal – Indicates whether the asset is in a bullish, bearish, or neutral state based on the selected trading system. This assists in quickly identifying which assets are showing potential trade opportunities.
Volatility Approximation – Represents the asset’s historical price fluctuations. Higher volatility suggests greater price swings, which can impact risk management and position sizing.
Liquidity Estimate – Reflects the asset’s market liquidity, often based on trading volume and price activity. More liquid assets tend to have lower transaction costs and reduced slippage, making them more favorable for active strategies.
Risk-Adjusted Return Value – Measures the asset’s returns relative to its risk level. This helps in determining whether an asset is generating efficient returns for the level of volatility it experiences, which is useful when making allocation decisions.
2. Strategy Allocation Table Position
Displays how your selected diversification method converts each asset into an allocation percentage. It also shows how much capital is being invested per asset, the cumulative return, standard performance metrics (for example, Sharpe ratio), and the separate HODL return percentage.
Symbol – Displays the asset being analyzed, ensuring clarity in allocation distribution.
Allocation Percentage – Represents the proportion of total capital assigned to each asset. This value is determined by the selected diversification method and helps traders understand how funds are distributed within the portfolio.
Investment Amount – Converts the allocation percentage into a dollar value based on the total portfolio size. This shows the exact amount being invested in each asset.
Cumulative Return – Tracks the total return of each asset over time, reflecting how well it has performed since the strategy began.
Sharpe Ratio – Evaluates the asset’s return in relation to its risk by comparing excess returns to volatility. A higher Sharpe ratio suggests a more favorable risk-adjusted performance.
Sortino Ratio – Similar to the Sharpe ratio, but focuses only on downside risk, making it more relevant for traders who prioritize minimizing losses.
Omega Ratio – Compares the probability of achieving gains versus losses, helping to assess whether an asset provides an attractive risk-reward balance.
Maximum Drawdown – Measures the largest percentage decline from an asset’s peak value to its lowest point. This metric helps traders understand the worst-case loss scenario.
HODL Return Percentage – Displays the hypothetical return if the asset had been bought and held instead of traded actively, offering a direct comparison between passive accumulation and the active strategy.
3. Profit Table
If the Profit Table is activated, it provides a summary of the actual dollar-based gains or losses for each asset and calculates the overall profit of the system. This table includes separate columns for profit excluding HODL and the combined total when HODL gains are included. As seen in the image below, this allows users to compare the performance of the active strategy against a passive buy-and-hold approach. The HODL profit percentage is derived from the Portfolio Value input, ensuring a clear comparison of accumulated returns.
4. Best Performing Asset Table
Focuses on the single highest-returning or highest-profit asset at that moment. It highlights the symbol, the asset’s cumulative returns, risk metrics, and other relevant stats. This helps identify which asset is currently outperforming the rest.
5. Most Profitable Asset
A simpler table that underscores the asset producing the highest absolute dollar profit across the portfolio.
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Multi Asset Selection
You can include up to ten different assets (such as BTCUSDT, ETHUSDT, ADAUSDT, and so on) in this script. Each asset has two inputs: one to enable or disable its inclusion, and another to select its trading pair symbol. Once you enable an asset, the script requests the relevant market data from TradingView.
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Uniqness and Features
1. Multiple Data Fetches
Each asset is pulled from the chart’s timeframe, along with various metrics such as RSI, volatility approximations, and trend indicators.
2. Various Risk and Performance Metrics
The script internally keeps track of different measures, like Sharpe ratio (a measure of average return adjusted for risk), Sortino ratio (which focuses on downside volatility), Omega ratio, and maximum drawdown. These metrics feed into the strategy allocation table, helping you quickly assess the risk-and-return profile of each asset.
3. Real-Time Tables
Instead of having to set up complex spreadsheets or external dashboards, the script updates all tables on every new bar. The color schemes in these tables are designed to draw attention to bullish or bearish signals, positive or negative returns, and so forth.
4. HODL Comparison
You can visually compare the active strategy’s results to a separate continuous buy-on-dips accumulation strategy. This allows for insight into whether your dynamic approach truly beats a simpler, more patient method.
5. Locking Allocations
The Use Fixed Allocation input is convenient for those who want to see how holding a fixed distribution of capital performs over time. It helps in distinguishing between constant rebalancing vs a fixed, set-and-forget style.
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How to use
1. Add the Script to Your Chart
Once added, open the settings panel to configure your asset list, choose a trading system, and select the diversification approach.
2. Select Assets
Pick up to ten symbols to monitor. Disable any you do not want included. Each included asset is then handled for signals, diversification, and performance metrics.
3. Choose Trading System
Decide if you prefer RSI-based signals, a fair-value approach, or a percentile-based method, among others. The script will then flag assets as bullish, bearish, or neutral according to that selection.
4. Pick a Diversification Method
For example, you might choose Trend-Following Indicators if you believe momentum stocks or cryptocurrencies will continue their trends. Or you could use the Omega Ratio approach if you want to reward assets that have had a favorable upside probability.
5. Set Portfolio Value and HODL Parameters
Enter how much capital you want to allocate in total (for the dynamic strategy) and adjust HODL buy quantities and thresholds as desired. (HODL Profit % is calculated from the Portfolio Value)
6. Inspect the Tables
On the chart, the script can display multiple tables showing your allocations, returns, risk metrics, and which assets are leading or lagging. Monitor these to make decisions about capital distribution or see how the strategy evolves.
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Additional Remarks
This script aims to simplify multi-asset portfolio management in a single tool. It emphasizes user-friendliness by color-coding the data in tables, so you do not need extra spreadsheets. The script is also flexible in letting you lock allocations or compare dynamic updates.
Always remember that no script can guarantee profitable outcomes. Real markets involve unpredictability, and real trading includes fees, slippage, and liquidity constraints not fully accounted for here. The script uses real-time and historical data for demonstration and educational purposes, providing a testing environment for various systematic strategies.
Performance Considerations
Due to the complexity of this script, users may experience longer loading times, especially when handling multiple assets or using advanced allocation methods. In some cases, calculations may time out if too many settings are adjusted simultaneously. If this occurs, removing and reapplying the indicator to the chart can help reset the process. Additionally, it is recommended to configure inputs gradually instead of adjusting all parameters at once, as excessive changes can extend the script’s loading duration beyond TradingView’s processing limits.
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Originality
This script stands out by integrating multiple asset management techniques within a single indicator, eliminating the need for multiple scripts or external portfolio tools. Unlike traditional single-asset strategies, it simultaneously evaluates multiple assets, applies systematic allocation logic, and tracks risk-adjusted performance in real time. The script is designed to function within TradingView’s script limitations while still allowing for complex portfolio simulations, making it an efficient tool for traders managing diverse holdings. Additionally, its combination of systematic trading signals with allocation-based diversification provides a structured approach to balancing exposure across different market conditions. The dynamic interplay between adaptive trading strategies and passive accumulation further differentiates it from conventional strategy indicators that focus solely on directional signals without considering capital allocation.
Conclusion
Uptrick: Portfolio Allocation Diversification pulls multiple assets into one efficient workflow, where each asset’s signal, volatility, and performance is measured, then assigned a share of capital according to your selected diversification method. The script accommodates both dynamic rebalancing and a locked allocation style, plus an ongoing HODL simulation for passive accumulation comparison. It neatly visualizes the entire process through on-chart tables that are updated every bar.
Traders and investors looking for ways to manage multiple assets under one unified framework can explore the different modules within this script to find what suits their style. Users can quickly switch among trading systems, vary the allocation approach, or review side-by-side performance metrics to see which method aligns best with their risk tolerance and market perspective.
Stablecoin Ratio with TPI ScoreThe script measures the stablecoin ratio (total stablecoin market cap divided by total crypto market cap, times 100) and its weekly change. Stablecoins (e.g., USDT, USDC) are a key gateway for capital entering or exiting the crypto ecosystem.
A rising ratio suggests more capital is parked in stablecoins (potential buying power), while a falling ratio indicates capital leaving (selling or withdrawal).
In a macro analysis, this is critical—it reflects the availability of liquid funds that could fuel price movements.
In macroeconomics, liquidity is a driver of asset prices.
In crypto, stablecoins represent sidelined capital ready to deploy.
How does it work?
Stablecoin Ratio:
Formula: (total_stablecoin_mcap / total_crypto_mcap) * 100.
Example: If stablecoins = $235B and total market cap = $2.5T, ratio = 9.4%.
Plotted as a red line in the oscillator pane, showing the percentage of the market held in stablecoins.
Weekly Change:
Calculates the percentage change in the ratio from the previous week:
(current_ratio - previous_ratio) / previous_ratio * 100.
Example: Ratio goes from 9% to 10% = +11.11% change.
TPI Score Assignment:
+1 (Bullish): If the ratio increases by more than 5% week-over-week.
-1 (Bearish): If the ratio decreases by more than 5% week-over-week.
0 (Neutral): If the change is between -5% and +5%.
Plotted as orange step line bars in the oscillator pane, snapping to +1, 0, or -1.
Engulfing Sweeps - Milana TradesEngulfing Sweeps
The Engulfing Sweeps Candle is a candlestick pattern that:
1)Takes liquidity from the previous candle’s high or low.
2)Fully engulfs previous candles upon closing.
3)Indicates strong buying or selling pressure.
4)Helps determine the bias of the next candle.
Logic Behind Engulfing Sweeps
If you analyze this candle on a lower timeframe, you’ll often see popular models like PO3 (Power of Three) or AMD (Accumulation – Manipulation – Distribution).
Once the candle closes, the goal is to enter a position on the retracement of the distribution phase.
How to Use Engulfing Sweeps?
Recommended Timeframes:
4H, Daily, Weekly – these levels hold significant liquidity.
Personally, I prefer 4H, as it provides a solid view of mid-term market moves.
Step1 - Identify Engulfing Sweep Candle
Step 2-Switch to a lower timeframe (15m or 5m).And you task identify optimal trade entry
Look for an entry pattern based on:
FVG (Fair Value Gap)
OB (Order Block)
FIB levels (0/0.25/0.5/ 0.75/ 1)
Wait for confirmation and take the trade.
Automating with TradingView Alerts
To avoid missing the pattern, you can set up alerts using a custom script. Once the pattern forms, TradingView will notify you so you can analyze the chart and take action. This approch helps me be more freedom
[TehThomas- Pro] - Liquidity SignalsOverview
This Pine Script indicator is designed to generate Buy and Sell signals based on liquidity sweeps and market structure shifts (MSS) or break of structure (BOS). The combination of liquidity sweeps and market structure changes provides a highly confluential signal that can be used to identify high-probability trade setups. This indicator is capable of working as a standalone tool or as part of a broader trading strategy.
Core Concepts
Liquidity Sweeps:
A liquidity sweep occurs when the price temporarily breaks a previous high or low, taking out stop losses or inducing breakout traders, only to reverse direction shortly after.
The indicator detects these liquidity sweeps at pivot points defined by a user-set pivotPeriod.
It plots Buyside Liquidity (resistance) or Sellside Liquidity (support) lines on the chart to indicate where liquidity pools are likely positioned.
Market Structure Shifts (MSS) and Break of Structure (BOS):
BOS: This occurs when the price closes above or below a previous swing high or low, indicating a potential shift in trend.
MSS: This is a more aggressive form of market structure change where the price action reverses after a liquidity sweep, signaling a potential reversal before a BOS confirmation.
The script tracks swing highs and swing lows using the pivot_strength setting to define how many bars are required on both sides of a pivot point.
Confluence of Signals:
The main signal is plotted when a Liquidity Sweep is followed by an MSS within a specified number of bars (25 by default).
This creates a high-probability trade signal because it combines both liquidity traps and market structure reversals.
Below, you can see the signals the indicator generates
There is one loss marked by the second circle.
Settings and Inputs
Liquidity Sweep Settings
pivotPeriod: Defines the left and right length of the pivot points to detect swing highs and lows.
maxLine: Maximum number of liquidity lines plotted on the chart.
resistanceColor & supportColor: Colors for Buyside and Sellside liquidity lines.
lineExtend: Number of bars to extend liquidity lines into the future.
hitAction: Determines what happens when liquidity lines are hit (dotted, dashed, or delete).
Market Structure Settings
show_mss: Toggle to display MSS signals on the chart.
show_bos: Toggle to display BOS signals on the chart.
Customizable line styles, colors, and labels for both MSS and BOS.
How to Use the Indicator
Signal Confirmation:
A Buy Signal is most effective when combined with a liquidity sweep of sellside liquidity followed by a bullish market structure shift.
A Sell Signal is most effective when combined with a liquidity sweep of buyside liquidity followed by a bearish market structure shift.
Always check confluence with other indicators such as moving averages or volume analysis.
Trade Management:
Place stop-loss orders below the liquidity sweep low for buys or above the liquidity sweep high for sells.
Use the previous swing high or low as a target or set custom risk-reward ratios.
Why This Indicator Works So Well
✅ Combines liquidity sweeps and market structure for highly accurate signals.
✅ Works across all timeframes and markets.
✅ Automatically plots support and resistance zones.
✅ Provides clear buy and sell signals with customizable alerts.
✅ Helps traders avoid false breakouts by waiting for market structure confirmation.
Conclusion
This indicator is a highly confluential trading tool that combines liquidity sweeps with market structure shifts to generate Buy and Sell signals. It provides a strong edge by confirming liquidity traps with market structure reversals. With customizable settings, it can be adapted to different timeframes and trading styles, making it suitable for both scalping and swing trading strategies.
By automating the detection of these advanced concepts, the indicator helps traders stay objective and disciplined in their decision-making process.
Whether you're a beginner or an advanced trader, this indicator will help you spot high-probability trade setups and improve your overall trading performance.
Disclaimer
This indicator is a powerful tool for identifying potential trading opportunities, but it is not a guarantee of future performance. Use this indicator at your own risk. Trading involves significant risk, and it is essential to have proper knowledge and experience before making any financial decisions. The signals provided by this indicator should be used as part of a comprehensive trading plan and combined with other forms of analysis. The creator is not responsible for any financial losses incurred while using this tool.
[TehThomas] - ICT Liquidity sweepsThe ICT Liquidity Sweeps Indicator is designed to track liquidity zones in the market areas where stop-losses and pending orders are typically clustered. This indicator marks buyside liquidity (resistance) and sellside liquidity (support), helping traders identify areas where price is likely to manipulate liquidity before making a significant move.
This tool is based on Inner Circle Trader (ICT) Smart Money Concepts, which emphasize how institutional traders, or “Smart Money,” manipulate liquidity to fuel price movements. By identifying these zones, traders can anticipate liquidity sweeps and position themselves accordingly.
⚙️ How It Works
1️⃣ Detects Key Liquidity Zones
The script automatically identifies significant swing highs and swing lows in price action using a pivot-based method.
A swing high (buyside liquidity) is a peak where price struggles to break higher, forming a resistance level.
A swing low (sellside liquidity) is a valley where price struggles to go lower, creating a support level.
These liquidity points are prime targets for liquidity sweeps before a true trend direction is confirmed.
2️⃣ Draws Liquidity Lines
Once a swing high or low is identified, a horizontal line is drawn at that level.
The lines extend to the right, serving as future liquidity targets until they are broken.
The indicator allows customization in terms of color, line width, and maximum number of liquidity lines displayed at once.
3️⃣ Handles Liquidity Sweeps
When price breaks a liquidity level, the indicator reacts based on the chosen action setting:
Dotted/Dashed: The line remains visible but changes style to indicate a sweep.
Delete: The line is completely removed once price has interacted with it.
This feature ensures that traders can easily spot where liquidity has been taken and determine whether a reversal or continuation is likely.
4️⃣ Prevents Chart Clutter
To maintain a clean chart, the script limits the number of liquidity lines displayed at any given time.
When new liquidity zones are formed, the oldest lines are automatically removed, keeping the focus on the most relevant liquidity zones.
🎯 How to Use the ICT Liquidity Sweeps Indicator
🔍 Identifying Liquidity Grabs
This indicator helps you identify areas where Smart Money is targeting liquidity before making a move.
Buyside Liquidity (BSL) Sweeps:
Occur when price spikes above a resistance level before reversing downward.
Indicate that Smart Money has hunted stop-losses and buy stops before driving price lower.
Sellside Liquidity (SSL) Sweeps:
Occur when price drops below a support level before reversing upward.
Indicate that Smart Money has collected liquidity from stop-losses and sell stops before pushing price higher.
📈 Combining with Market Structure Shifts (MSS)
One of the best ways to use this indicator is in conjunction with our Market Structure Shifts Indicator.
Liquidity sweeps + MSS Confirmation give strong high-probability trade setups:
Wait for a liquidity sweep (price takes out a liquidity level).
Look for an MSS in the opposite direction (e.g., price sweeps a high, then breaks a recent low).
Enter the trade in the new direction with stop-loss above/below the liquidity sweep.
📊 Entry & Exit Strategies
Long Trade Example:
Price sweeps a key sellside liquidity level (SSL) → creates a false breakdown.
MSS confirms a reversal (price breaks structure upwards).
Enter long position after confirmation.
Stop-loss below the liquidity grab to minimize risk.
Short Trade Example:
Price sweeps a key buyside liquidity level (BSL) → takes liquidity above resistance.
MSS confirms a bearish move (price breaks a key support level).
Enter short position after confirmation.
Stop-loss above the liquidity grab.
🚀 Why This Indicator is a Game-Changer
✅ Helps Identify Smart Money Manipulation – Understand where institutions are likely to grab liquidity before the real move happens.
✅ Enhances Market Structure Analysis – When paired with MSS, liquidity sweeps become powerful signals for trend reversals.
✅ Filters Out False Breakouts – Many traders get caught in liquidity grabs. This indicator helps avoid bad entries.
✅ Keeps Your Chart Clean – The auto-limiting feature ensures that only the most relevant liquidity levels remain visible.
✅ Works on Any Timeframe – Whether you’re a scalper, day trader, or swing trader, liquidity concepts apply universally.
📌 Final Thoughts
The ICT Liquidity Sweeps Indicator is a must-have tool for traders who follow Smart Money Concepts. By tracking liquidity levels and highlighting sweeps, it allows traders to enter trades with precision while avoiding false breakouts.
When combined with Market Structure Shifts (MSS), this strategy becomes even more powerful, offering traders an edge in spotting reversals and timing entries effectively.
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CandelaCharts - Liquidity Key Zones (LKZ)📝 Overview
The Liquidity Key Zones indicator displays the previous high and low levels for daily, weekly, monthly, quarterly, and yearly timeframes. These levels serve as crucial price zones for trading any market or instrument. They are also high-probability reaction zones, ideal for trading using straightforward confirmation patterns.
Each of these levels plays a significant role in determining whether the market continues its momentum or reverses its bias. I like to think of these levels as dual magnets—they simultaneously attract and repel price. You might wonder how having opposing views can be useful. The key is to remain neutral about direction and establish your own rules to identify when these zones are likely to attract or repel price. I have my own set of rules, and you can develop yours.
📦 Features
MTF
Styling
⚙️ Settings
Day: Shows previous day levels
Week: Shows previous week levels
Month: Shows previous month levels
Quarter: Shows previous quarter levels
Year: Shows previous year levels
Show Average: Shows previous level average price
Show Open: Shows previous level open price
⚡️ Showcase
Daily
Weekly
Monthly
Quarterly
Yearly
Average
Open
📒 Usage
When the price breaks through a significant level, such as a daily, weekly, or monthly high or low, it often signals a potential reversal in market direction. This occurs because these levels represent key areas of support or resistance, where traders anticipate heightened activity, including profit-taking, stop-loss orders, or new positions being initiated.
Once the price breaches these levels, it may trigger a sharp reaction as market participants adjust their strategies, leading to a reversal. Monitoring price action and volume around these levels can provide valuable confirmation of such reversals.
Another effective approach to utilizing these pivot points is by incorporating them into a structured trading strategy, such as the X Model, which leverages multiple timeframes and technical tools to refine trade entries and exits.
X Model conditions:
(D1) Previous Day High (ERL)
(H1) Bullish FVG/IFVG/OB (IRL)
(m15) MSS / SMT
Only Short Above 00:00
By combining these elements, the X Model offers a comprehensive framework for leveraging pivot levels effectively, emphasizing confluence between liquidity zones, time-based rules, and multi-timeframe analysis to enhance trading accuracy and consistency.
🚨 Alerts
This script provides alert options for all signals.
Bearish Signal
A bearish signal is generated when the price breaks below the previous low level.
Bullish Signal
A bullish signal is generated when the price breaks above the previous low level.
⚠️ 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.
2:30 [LuciTech]this is a technical analysis tool designed to highlight key price levels and patterns during a specific trading window, based on UK time (Europe/London). It overlays visual elements on the chart, including a 12 PM reference line, Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL) levels, a highlighted 2:30 PM candle, and Engulfing Fair Value Gaps (FVGs). This indicator is intended for traders who focus on intraday price action and liquidity zones.
Features
The 12 PM Line displays a vertical line at 12:00 PM (UK time) to mark the start of the session. It’s customizable, allowing you to enable or disable it and adjust its color.
BSL/SSL Lines track the highest high (BSL) and lowest low (SSL) from 12:00 PM to 2:00 PM (UK time). These lines extend horizontally until 3:30 PM, after which they remain static at their last recorded levels. You can customize them by enabling or disabling visibility, adjusting colors, choosing a line style (solid, dashed, or dotted), and setting the width.
The 2:30 PM Candle highlights the candle at 2:30 PM (UK time) with a distinct color. It’s customizable, with options to enable or disable it and change its color.
Engulfing FVG (Fair Value Gap) identifies bullish and bearish engulfing patterns with a gap from the prior candle’s range. It draws a shaded box over the FVG area, and you can customize it by enabling or disabling it and adjusting the box color.
How It Works
The indicator operates within a session starting at 12:00 PM (UK time). BSL/SSL levels update between 12:00 PM and 2:00 PM, with lines extending until 3:30 PM. After 3:30 PM, these lines freeze.
BSL/SSL lines show the highest price (BSL) and lowest price (SSL) reached during the 12:00 PM to 2:00 PM window. After 3:30 PM, they remain static, marking the final range boundaries.
The 2:30 PM candle emphasizes a key timestamp, often of interest to intraday traders.
Engulfing FVGs detect significant price gaps created by engulfing candles, which may indicate potential reversal or continuation zones.
Settings
12 PM Line Settings let you toggle visibility and set the line color.
BSL/SSL Line Settings allow you to toggle visibility, set BSL and SSL colors, choose a line style (Solid, Dashed, Dotted), and adjust width (1-4).
2:30 Candle Settings let you toggle visibility and set the candle color.
Engulfing FVG Settings allow you to toggle visibility and set the box color.
Interpretation
The 12 PM Line serves as a reference for the session start.
BSL/SSL Lines may act as potential support or resistance zones or highlight liquidity areas. After 3:30 PM, they remain static, showing the session’s final range.
The 2:30 PM Candle can be monitored for price action signals, such as reversals or breakouts.
Engulfing FVGs shaded areas may indicate imbalances in supply and demand, useful for identifying trade opportunities or stop-loss placement.
Notes
The timezone is set to Europe/London (UK time). Ensure your chart’s timezone aligns for accurate results.
This indicator is best used on intraday timeframes, such as 1-minute or 5-minute charts.
It provides visual aids for analysis and does not generate buy or sell signals on its own.
Liquidity Sweep Filter [AlgoAlpha]Unlock a deeper understanding of market liquidity with the Liquidity Sweep Filter by AlgoAlpha. This indicator identifies liquidity sweeps, highlighting key price levels where large liquidations have occurred. By visualizing major and minor liquidation events, traders can better anticipate potential reversals and market structure shifts, making this an essential tool for those trading in volatile conditions.
Key Features :
🔍 Liquidity Sweep Detection – Identifies and highlights areas where liquidity has been swept, distinguishing between major and minor liquidation events.
📊 Volume Profile Integration – Displays a volume profile overlay, helping traders spot high-activity price zones where the market is likely to react.
📈 Trend-Based Filtering – Utilizes an adaptive trend detection algorithm to refine liquidity sweeps based on market direction, reducing noise.
🎨 Customizable Visualization – Modify colors, thresholds, and display settings to tailor the indicator to your trading style.
🔔 Alerts for Liquidity Sweeps & Trend Changes – Stay ahead of the market by receiving alerts when significant liquidity events or trend shifts occur.
How to Use:
🛠 Add the Indicator : Add the Liquidity Sweep Filter to your chart and configure the settings based on your preferred sensitivity. Adjust the major sweep threshold to filter out smaller moves.
📊 Analyze Liquidity Zones and trend direction : Look for liquidation levels where large buy or sell stops have been triggered. Major sweeps indicate strong reactions, while minor sweeps show gradual liquidity absorption. You can also see which levels are high in liquidity by the transparency of the levels.
🔔 Set-Up Alerts : Use the in-built alerts so you don't miss a trading opportunity
How It Works :
The Liquidity Sweep Filter detects liquidity events by tracking swing highs and lows (defined as a pivot where neighboring candles are lower/higher than it) where traders are likely to have placed stop-loss orders. It evaluates volume and price action, marking areas where liquidity has been absorbed by the market. Additionally, the integrated trend filter ensures that only relevant liquidity sweeps are highlighted based on market direction, lows in an uptrend and highs in a downtrend. The trend filter works by calculating a basis, and defining trend shifts when the closing price crosses over the upper or lower bands.The included volume profile further enhances analysis by displaying key trading zones where price may react.
Dollar Cost Averaging (DCA) | FractalystWhat's the purpose of this strategy?
The purpose of dollar cost averaging (DCA) is to grow investments over time using a disciplined, methodical approach used by many top institutions like MicroStrategy and other institutions.
Here's how it functions:
Dollar Cost Averaging (DCA): This technique involves investing a set amount of money regularly, regardless of market conditions. It helps to mitigate the risk of investing a large sum at a peak price by spreading out your investment, thus potentially lowering your average cost per share over time.
Regular Contributions: By adding money to your investments on a pre-determined frequency and dollar amount defined by the user, you take advantage of compounding. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
Technical Analysis: The strategy employs a market trend ratio to gauge market sentiment. It calculates the ratio of bullish vs bearish breakouts across various timeframes, assigning this ratio a percentage-based score to determine the directional bias. Once this score exceeds a user-selected percentage, the strategy looks to take buy entries, signaling a favorable time for investment based on current market trends.
Fundamental Analysis: This aspect looks at the health of the economy and companies within it to determine bullish market conditions. Specifically, we consider:
Specifically, it considers:
Interest Rate: High interest rates can affect borrowing costs, potentially slowing down economic growth or making stocks less attractive compared to fixed income.
Inflation Rate: Inflation erodes purchasing power, but moderate inflation can be a sign of a healthy economy. We look for investments that might benefit from or withstand inflation.
GDP Rate: GDP growth indicates the overall health of the economy; we aim to invest in sectors poised to grow with the economy.
Unemployment Rate: Lower unemployment typically signals consumer confidence and spending power, which can boost certain sectors.
By integrating these elements, the strategy aims to:
Reduce Investment Volatility: By spreading out your investments, you're less impacted by short-term market swings.
Enhance Growth Potential: Using both technical and fundamental filters helps in choosing investments that are more likely to appreciate over time.
Manage Risk: The strategy aims to balance the risk of market timing by investing consistently and choosing assets wisely based on both economic data and market conditions.
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What are Regular Contributions in this strategy?
Regular Contributions involve adding money to your investments on a pre-determined frequency and dollar amount defined by the user. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
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How do regular contributions enhance compounding and reduce timing risk?
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
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How does the strategy integrate technical and fundamental analysis for investors?
A: The strategy combines technical and fundamental analysis in the following manner:
Technical Analysis: It uses a market trend ratio to determine the directional bias by calculating the ratio of bullish vs bearish breakouts. Once this ratio exceeds a user-selected percentage threshold, the strategy signals to take buy entries, optimizing the timing within the given timeframe(s).
Fundamental Analysis: This aspect assesses the broader economic environment to identify sectors or assets that are likely to benefit from current economic conditions. By understanding these fundamentals, the strategy ensures investments are made in assets with strong growth potential.
This integration allows the strategy to select investments that are both technically favorable for entry and fundamentally sound, providing a comprehensive approach to investment decisions in the crypto, stock, and commodities markets.
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How does the strategy identify market structure? What are the underlying calculations?
Q: How does the strategy identify market structure?
A: The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
What are the underlying calculations for identifying market structure?
A: The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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How does the script calculate trend score? What are the underlying calculations?
Market Trend Ratio: The script calculates the ratio of bullish to bearish breakouts. This involves:
Counting Bullish Breakouts: A bullish breakout is counted when the price breaks above a recent swing high (as identified in the strategy's market structure analysis).
Counting Bearish Breakouts: A bearish breakout is counted when the price breaks below a recent swing low.
Percentage-Based Score: This ratio is then converted into a percentage-based score:
For example, if there are 10 bullish breakouts and 5 bearish breakouts in a given timeframe, the ratio would be 10:5 or 2:1. This could be translated into a score where 66.67% (10/(10+5) * 100) represents the bullish trend strength.
The score might be calculated as (Number of Bullish Breakouts / Total Breakouts) * 100.
User-Defined Threshold: The strategy uses this score to determine when to take buy entries. If the trend score exceeds a user-defined percentage threshold, it indicates a strong enough bullish trend to justify a buy entry. For instance, if the user sets the threshold at 60%, the script would look for a buy entry when the trend score is above this level.
Timeframe Consideration: The calculations are performed across the timeframes specified by the user, ensuring the trend score reflects the market's behavior over different periods, which could be daily, weekly, or any other relevant timeframe.
This method provides a quantitative measure of market trend strength, helping to make informed decisions based on the balance between bullish and bearish market movements.
What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP
- You can choose to set a take profit level at which your position gets fully closed.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
Incorporation of Fundamental Analysis:
This strategy integrates fundamental analysis by considering key economic indicators such as interest rates, inflation, GDP growth, and unemployment rates. These fundamentals help in assessing the broader economic health, which in turn influences sector performance and market trends. By understanding these economic conditions, the strategy can identify sectors or assets that are likely to thrive, ensuring investments are made in environments conducive to growth. This approach allows for a more informed investment decision, aligning technical entries with fundamentally strong market conditions, thus potentially enhancing the strategy's effectiveness over time.
Technical Analysis Without Classical Methods:
The strategy's technical analysis diverges from traditional methods like moving averages by focusing on market structure through a trend score system.
Instead of using lagging indicators, it employs a real-time analysis of market trends by calculating the ratio of bullish to bearish breakouts. This provides several benefits:
Immediate Market Sentiment: The trend score system reacts more dynamically to current market conditions, offering insights into the market's immediate sentiment rather than historical trends, which can often lag behind real-time changes.
Reduced Overfitting: By not relying on moving averages or similar classical indicators, the strategy avoids the common pitfall of overfitting to historical data, which can lead to poor performance in new market conditions. The trend score provides a fresh perspective on market direction, potentially leading to more robust trading signals.
Clear Entry Signals: With the trend score, entry decisions are based on a clear percentage threshold, making the strategy's decision-making process straightforward and less subjective than interpreting moving average crossovers or similar signals.
Regular Contributions and Reminders:
The strategy encourages regular investments through a system of predefined frequency and amount, which could be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach:
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
Long-Term Wealth Building:
Focused on long-term wealth accumulation, this strategy:
Promotes Patience and Discipline: By emphasizing regular contributions and a disciplined approach to both entry and risk management, it aligns with the principles of long-term investing, discouraging impulsive decisions based on short-term market fluctuations.
Diversification Across Asset Classes: Operating across crypto, stocks, and commodities, the strategy provides diversification, which is a key component of long-term wealth building, reducing risk through varied exposure.
Growth Over Time: The strategy's design to work with the market's natural growth cycles, supported by fundamental analysis, aims for sustainable growth rather than quick profits, aligning with the goals of investors looking to build wealth over decades.
This comprehensive approach, combining fundamental insights, innovative technical analysis, disciplined investment habits, and a focus on long-term growth, offers a unique and potentially effective pathway for investors seeking to build wealth steadily over time.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Cluster Reversal Zones📌 Cluster Reversal Zones – Smart Market Turning Point Detector
📌 Category : Public (Restricted/Closed-Source) Indicator
📌 Designed for : Traders looking for high-accuracy reversal zones based on price clustering & liquidity shifts.
🔍 Overview
The Cluster Reversal Zones Indicator is an advanced market reversal detection tool that helps traders identify key turning points using a combination of price clustering, order flow analysis, and liquidity tracking. Instead of relying on static support and resistance levels, this tool dynamically adjusts to live market conditions, ensuring traders get the most accurate reversal signals possible.
📊 Core Features:
✅ Real-Time Reversal Zone Mapping – Detects high-probability market turning points using price clustering & order flow imbalance.
✅ Liquidity-Based Support/Resistance Detection – Identifies strong rejection zones based on real-time liquidity shifts.
✅ Order Flow Sensitivity for Smart Filtering – Filters out weak reversals by detecting real market participation behind price movements.
✅ Momentum Divergence for Confirmation – Aligns reversal zones with momentum divergences to increase accuracy.
✅ Adaptive Risk Management System – Adjusts risk parameters dynamically based on volatility and trend state.
🔒 Justification for Mashup
The Cluster Reversal Zones Indicator contains custom-built methodologies that extend beyond traditional support/resistance indicators:
✔ Smart Price Clustering Algorithm: Instead of plotting fixed support/resistance lines, this system analyzes historical price clustering to detect active reversal areas.
✔ Order Flow Delta & Liquidity Shift Sensitivity: The tool tracks real-time order flow data, identifying price zones with the highest accumulation or distribution levels.
✔ Momentum-Based Reversal Validation: Unlike traditional indicators, this tool requires a momentum shift confirmation before validating a potential reversal.
✔ Adaptive Reversal Filtering Mechanism: Uses a combination of historical confluence detection + live market validation to improve accuracy.
🛠️ How to Use:
• Works well for reversal traders, scalpers, and swing traders seeking precise turning points.
• Best combined with VWAP, Market Profile, and Delta Volume indicators for confirmation.
• Suitable for Forex, Indices, Commodities, Crypto, and Stock markets.
🚨 Important Note:
For educational & analytical purposes only.
Blockchain Fundamentals: Liquidity & BTC YoYLiquidity & BTC YoY Indicator
Overview:
This indicator calculates the Year-over-Year (YoY) percentage change for two critical metrics: a custom Liquidity Index and Bitcoin's price. The Liquidity Index is derived from a blend of economic and forex data representing the M2 money supply, while the BTC price is obtained from a reliable market source. A dedicated limit(length) function is implemented to handle limited historical data, ensuring that the YoY calculations are available immediately—even when the chart's history is short.
Features Breakdown:
1. Limited Historical Data Workaround
- Functionality: limit(length) The function dynamically adjusts the lookback period when there isn’t enough historical data. This prevents delays in displaying YoY metrics at the beginning of the chart.
2. Liquidity Calculation
- Data Sources: Combines multiple data streams:
USM2, ECONOMICS:CNM2, USDCNY, ECONOMICS:JPM2, USDJPY, ECONOMICS:EUM2, USDEUR
- Formula:
Liquidity Index = USM2 + (CNM2 / USDCNY) + (JPM2 / USDJPY) + (EUM2 / USDEUR)
[b3. Bitcoin Price Calculation
- Data Source: Retrieves Bitcoin's price from BITSTAMP:BTCUSD on the user-selected timeframe for its historical length.
4. Year-over-Year (YoY) Percent Change Calculation
- Methodology:
- The indicator uses a custom function, to autodetect the proper number of bars, based on the selected timeframe.
- It then compares the current value to that from one year ago for both the Liquidity Index and BTC price, calculating the YoY percentage change.
5. Visual Presentation
- Plotting:
- The YoY percentage changes for Liquidity (plotted in blue) and BTC price (plotted in orange) are clearly displayed.
- A horizontal zero line is added for visual alignment, making it easier to compare the two copies of the metric. You add one copy and only display the BTC YoY. Then you add another copy and only display the M2 YoY.
-The zero lines are then used to align the scripts to each other by interposing them. You scale each chart the way you like, then move each copy individually to align both zero lines on top of each other.
This indicator is ideal for analysts and investors looking to monitor macroeconomic liquidity trends alongside Bitcoin's performance, providing immediate insights.
Blockchain Fundamentals: Global LiquidityGlobal Liquidity Indicator Overview
This indicator provides a comprehensive technical analysis of liquidity trends by deriving a Global Liquidity metric from multiple data sources. It applies a suite of technical indicators directly on this liquidity measure, rather than on price data. When this metric is expanding Bitcoin and crypto tends to bullish conditions.
Features:
1. Global Liquidity Calculation
Data Integration: Combines multiple market data sources using a ratio-based formula to produce a unique liquidity measure.
Custom Metric: This liquidity metric serves as the foundational input for further technical analysis.
2. Timeframe Customization
User-Selected Period: Users can select the data timeframe (default is 2 months) to ensure consistency and flexibility in analysis.
3. Additional Technical Indicators
RSI, Momentum, ROC, MACD, and Stochastic:
Each indicator is computed using the Global Liquidity series rather than price.
User-selectable toggles allow for enabling or disabling each individual indicator as desired.
4. Enhanced MACD Visualization
Dynamic Histogram Coloring:
The MACD histogram color adjusts dynamically: brighter hues indicate rising histogram values while darker hues indicate falling values.
When the histogram is above zero, green is used; when below zero, red is applied, offering immediate visual insight into momentum shifts.
Conclusion
This indicator is an enlightening tool for understanding liquidity dynamics, aiding in macroeconomic analysis and investment decision-making by highlighting shifts in liquidity conditions and market momentum.
Excess Liquidity IndicatorExcess Liquidity Indicator
This script visualizes excess liquidity trends in relation to risk assets. It estimates excess liquidity by combining various macroeconomic factors such as WW M2 money supply, central bank balance sheets, and interest rates, oil, and the dollar index, and it substracts WW GDP. The tool helps traders analyze liquidity-driven market trends in a structured manner.
Note: This script is for research purposes only and does not provide financial advice.
I cannot point names cause I get banned but work is inspired by others...
Draw on Liquidity [PhenLabs]📊 Draw on Liquidity (DOL) Indicator
Version: PineScript™ v6
Description
The Draw on Liquidity (DOL) indicator is an advanced technical analysis tool designed to identify and visualize significant liquidity zones in the market. It combines volume analysis, pivot point detection, and real-time proximity alerts to help traders identify potential support and resistance levels where significant trading activity occurs. The indicator features dual display modes, adaptive volume thresholds, and a comprehensive real-time dashboard.
🔧 Components
• Liquidity Detection: Advanced pivot point analysis with volume validation
• Volume Analysis: Adaptive volume threshold system
• Display Modes: Historical and Current visualization options
• Proximity Detection: Real-time price-to-level distance monitoring
• Visual Dashboard: Dynamic status display with alert system
🚨 Important Dashboard Features 🚨
The dashboard provides real-time information about:
• High Draw Zones: Resistance levels with significant liquidity
• Low Draw Zones: Support levels with high trading activity
• Current Price: Real-time price monitoring
• Active Alerts: Proximity warnings when price approaches liquidity zones
📈 Visualization
• Historical Mode: Displays all past and present liquidity zones
• Current Mode: Shows only active, unhit liquidity levels
• Color-coded lines: Blue for high liquidity, Red for low liquidity
• Dynamic line extension: Updates with price movement
• Alert indicators: Visual signals when price approaches zones
Historical Visualization
Current Visualization
📌 Usage Guidelines
The indicator is highly customizable with several key parameters:
Pivot Settings:
• Shorter lengths (3-7): More frequent zones, suitable for scalping
• Longer lengths (7-15): Major zones, better for swing trading
Volume Analysis:
• Lower multiplier (1.5-2.0): More zones, higher sensitivity
• Higher multiplier (2.0-3.0): Major zones only, reduced noise
✅ Best Practices:
• Start with default settings and adjust based on timeframe
• Use Historical mode for analysis, Current mode for active trading
• Monitor dashboard alerts for potential trade setups
• Combine with trend analysis for better entry/exit points
⚠️ Limitations
• Requires sufficient volume data for accurate analysis
• Performance varies with market volatility
• Historical mode may become visually cluttered on longer timeframes
• Best performance during regular market hours
What Makes This Unique
• Dual Display System: Choose between historical analysis and current trading modes
• Volume-Validated Zones: Only marks levels with significant trading activity
• Real-time Proximity Alerts: Dynamic warnings when approaching liquidity zones
• Adaptive Threshold System: Automatically adjusts to market conditions
• Comprehensive Dashboard: All-in-one view of current market status
🔧 How It Works
The indicator processes market data through three main components:
1. Liquidity Detection (40% weight):
• Identifies pivot points using customizable lookback periods
• Validates levels with volume analysis
• Marks significant zones based on combined criteria
2. Volume Analysis (40% weight):
• Calculates dynamic volume thresholds
• Compares current volume to moving average
• Filters out low-volume noise
3. Proximity Analysis (20% weight):
• Monitors price distance to active zones
• Triggers alerts based on customizable thresholds
• Updates dashboard status in real-time
💡 Note: For optimal results, combine with price action analysis and consider using multiple timeframes for confirmation. The indicator performs best in markets with consistent volume and clear trend structure.
2022 Model ICT Entry Strategy [TradingFinder] One Setup For Life🔵 Introduction
The ICT 2022 model, introduced by Michael Huddleston, is an advanced trading strategy rooted in liquidity and price imbalance, where time and price serve as the core elements. This ICT 2022 trading strategy is an algorithmic approach designed to analyze liquidity and imbalances in the market. It incorporates concepts such as Fair Value Gap (FVG), Liquidity Sweep, and Market Structure Shift (MSS) to help traders identify liquidity movements and structural changes in the market, enabling them to determine optimal entry and exit points for their trades.
This Full ICT Day Trading Model empowers traders to pinpoint the Previous Day High/Low as well as the highs and lows of critical sessions like the London and New York sessions. These levels act as Liquidity Zones, which are frequently swept prior to a market structure shift (MSS) or a retracement to areas such as Optimal Trade Entry (OTE).
Bullish :
Bearish :
🔵 How to Use
The ICT 2022 model is a sophisticated trading strategy that focuses on identifying key liquidity levels and price movements. It operates based on two main principles. In the first phase, the price approaches liquidity zones and sweeps critical levels such as the previous day’s high or low and key session levels.
This movement is known as a Liquidity Sweep. In the second phase, following the sweep, the price retraces to areas like the FVG (Fair Value Gap), creating ideal entry points for trades. Below is a detailed explanation of how to apply this strategy in bullish and bearish setups.
🟣 Bullish ICT 2022 Model Setup
To use the ICT 2022 model in a bullish setup, start by identifying the Previous Day High/Low or key session levels, such as those of the London or New York sessions. In a bullish setup, the price usually moves downward first, sweeping the Liquidity Low. This move, known as a Liquidity Sweep, reflects the collection of buy orders by major market participants.
After the liquidity sweep, the price should shift market structure and start moving upward; this shift, referred to as Market Structure Shift (MSS), signals the beginning of an upward trend. Following MSS, areas like FVG, located within the Discount Zone, are identified. At this stage, the trader waits for the price to retrace to these zones. Once the price returns, a long trade is executed.
Finally, the stop-loss should be set below the liquidity low to manage risk, while the take-profit target is usually placed above the previous day’s high or other identified liquidity levels. This structure enables traders to take advantage of the upward price movement after the liquidity sweep.
🟣 Bearish ICT 2022 Model Setup
To identify a bearish setup in the ICT 2022 model, begin by marking the Previous Day High/Low or key session levels, such as the London or New York sessions. In this scenario, the price typically moves upward first, sweeping the Liquidity High. This move, known as a Liquidity Sweep, signifies the collection of sell orders by key market players.
After the liquidity sweep, the price should shift market structure downward. This movement, called the Market Structure Shift (MSS), indicates the start of a downtrend. Following MSS, areas such as FVG, found within the Premium Zone, are identified. At this stage, the trader waits for the price to retrace to these areas. Once the price revisits these zones, a short trade is executed.
In this setup, the stop-loss should be placed above the liquidity high to control risk, while the take-profit target is typically set below the previous day’s low or another defined liquidity level. This approach allows traders to capitalize on the downward price movement following the liquidity sweep.
🔵 Settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
FVG Length : Default is 120 Bar.
MSS Length : Default is 80 Bar.
FVG Filter : This refines the number of identified FVG areas based on a specified algorithm to focus on higher quality signals and reduce noise.
Types of FVG filters :
Very Aggressive Filter: Adds a condition where, for an upward FVG, the last candle's highest price must exceed the middle candle's highest price, and for a downward FVG, the last candle's lowest price must be lower than the middle candle's lowest price. This minimally filters out FVGs.
Aggressive Filter: Builds on the Very Aggressive mode by ensuring the middle candle is not too small, filtering out more FVGs.
Defensive Filter: Adds criteria regarding the size and structure of the middle candle, requiring it to have a substantial body and specific polarity conditions, filtering out a significant number of FVGs.
Very Defensive Filter: Further refines filtering by ensuring the first and third candles are not small-bodied doji candles, retaining only the highest quality signals.
🔵 Conclusion
The ICT 2022 model is a comprehensive and advanced trading strategy designed around key concepts such as liquidity, price imbalance, and market structure shifts (MSS). By focusing on the sweep of critical levels such as the previous day’s high/low and important trading sessions like London and New York, this strategy enables traders to predict market movements with greater precision.
The use of tools like FVG in this model helps traders fine-tune their entry and exit points and take advantage of bullish and bearish trends after liquidity sweeps. Moreover, combining this strategy with precise timing during key trading sessions allows traders to minimize risk and maximize returns.
In conclusion, the ICT 2022 model emphasizes the importance of time and liquidity, making it a powerful tool for both professional and novice traders. By applying the principles of this model, you can make more informed trading decisions and seize opportunities in financial markets more effectively.
Liquidity Trap Detector (LTD)The Liquidity Trap Detector is an advanced trading tool designed to identify liquidity zones and potential traps set by institutional players. It provides traders with a comprehensive framework to align with smart money movements, helping them avoid common retail pitfalls such as bull and bear traps.
The indicator focuses on detecting liquidity sweeps, breaker blocks, and areas of institutional accumulation/distribution. It integrates multiple technical analysis methods to offer high-probability signals and insights into how liquidity dynamics unfold in the market.
Note : This indicator is not designed for beginners; it is intended for traders who already have a solid understanding of trading fundamentals. It is tailored for individuals who are familiar with concepts like liquidity, order blocks, and traps. Traders with at least 6 months to 1 year of trading experience will fully appreciate the power and potential of this indicator, as they will have the necessary knowledge to leverage its features effectively. Beginners may find it challenging to grasp the advanced concepts embedded in this tool.
Why Combine These Elements?
The components of the Liquidity Trap Detector are carefully chosen to address the core challenges of identifying institutional activity and liquidity traps. Here’s why each element is included and how they work together:
1. Order Blocks:
• Purpose: Identify zones where large institutional players accumulate or distribute positions.
• Role in the Indicator: These zones act as primary liquidity areas, where price is likely to reverse or consolidate due to significant order flow.
2. Breaker Blocks:
• Purpose: Highlight areas where liquidity has been swept, leading to potential price reversals or continuations.
• Role in the Indicator: Confirms whether a liquidity trap has occurred and provides actionable levels for entry or exit.
3. ATR-Based Volatility Zones:
• Purpose: Filter signals based on market volatility to ensure trades align with statistically significant price movements.
• Role in the Indicator: Defines dynamic support and resistance zones, improving the accuracy of signal generation.
4. Volume Delta:
• Purpose: Measure the imbalance between aggressive buyers and sellers, often indicating institutional activity.
• Role in the Indicator: Validates whether a liquidity trap is backed by smart money absorption or retail-driven momentum.
5. Trend Confirmation (EMA):
• Purpose: Align liquidity trap signals with the broader market trend, reducing false positives.
• Role in the Indicator: Ensures trades are executed in the direction of the prevailing trend.
What Makes It Unique?
1. Gen 1 Liquidity Zones and Traps:
• The indicator identifies Gen 1 Liquidity Zones, which represent the first areas where liquidity is accumulated or swept. While these zones often lead to reversals, they can sometimes fail, resulting in continuation moves. The indicator highlights these scenarios, helping traders adapt.
• For example, a bull trap identified in a Gen 1 Zone may see price move higher after an initial red candle, completing a secondary liquidity sweep before reversing.
2. Multi-Layer Signal Validation:
• Signals are only generated when liquidity, volume, trend, and volatility align. This ensures high-probability setups and reduces noise in choppy markets.
3. Dynamic Adaptability:
• ATR-based zones and volume delta filtering allow the indicator to adapt to different market conditions, from trending to range-bound environments.
4. Institutional Insights:
• By focusing on liquidity sweeps, order blocks, and volume imbalances, the indicator helps traders align with institutional strategies rather than retail behavior.
How It Works
The Liquidity Trap Detector uses a step-by-step process to identify and validate liquidity traps:
1. Identifying Liquidity Zones:
• Order Blocks: Mark key zones of institutional activity where price is likely to reverse.
• Breaker Blocks: Highlight areas where liquidity sweeps have occurred, signaling potential traps.
2. Filtering with Volatility (ATR):
• ATR defines dynamic support and resistance zones, ensuring signals are only generated near significant price levels.
3. Validating Traps with Volume Delta:
• Volume delta shows whether liquidity sweeps are backed by aggressive buying/selling from institutions, confirming the trap’s validity.
4. Aligning with Market Trends:
• EMA ensures signals align with the broader trend to reduce false positives.
5. Monitoring Gen 1 Liquidity Zones:
• The indicator highlights Gen 1 Liquidity Zones where price may initially reverse or sweep further before a true reversal. Traders are alerted to potential continuation scenarios if volume or momentum suggests unmet liquidity above/below the zone.
How to Use It
Buy Signal:
• Triggered when:
• Price sweeps below an order block and forms a breaker block, indicating a liquidity trap.
• Volume delta confirms aggressive selling absorption.
• ATR volatility zone supports the reversal.
• EMA confirms a bullish trend.
• Action: Enter a Buy trade and set:
• Stop Loss (SL): Below the order block.
• Take Profit (TP): Near the next resistance or liquidity zone.
Sell Signal:
• Triggered when:
• Price sweeps above an order block and forms a breaker block, indicating a liquidity trap.
• Volume delta confirms aggressive buying absorption.
• ATR volatility zone supports the reversal.
• EMA confirms a bearish trend.
• Action: Enter a Sell trade and set:
• SL: Above the order block.
• TP: Near the next support or liquidity zone.
Timeframes:
• Best suited for scalping and intraday trading on lower timeframes (5m, 15m, 1H).
• Can also be applied to swing trading on higher timeframes.
Example Scenarios:
1. Bull Trap in a Gen 1 Zone:
• Price sweeps above a resistance order block, forms a breaker block, and reverses sharply. However, if momentum persists, price may continue higher after a minor pullback. The indicator helps traders anticipate this by monitoring volume and trend shifts.
2. Bear Trap with Secondary Sweep:
• Price sweeps below a support order block but fails to reverse immediately, instead forming a secondary liquidity sweep before turning bullish. The indicator highlights both scenarios, allowing for flexible trade management.
Why Use It?
The Liquidity Trap Detector offers:
1. Precision: Combines multiple filters to identify institutional liquidity traps with high accuracy.
2. Adaptability: Works across trending and range-bound markets.
3. Smart Money Alignment: Helps traders avoid retail traps by focusing on liquidity sweeps and institutional behavior.
Thin Liquidity Zones [PhenLabs]Thin Liquidity Zones with Volume Delta
Our advanced volume analysis tool identifies and visualizes significant liquidity zones using real-time volume delta analysis. This indicator helps traders pinpoint and monitor critical price levels where substantial trading activity occurs, providing precise volume flow measurement through lower timeframe analysis.
The tool works by leveraging the fact that hedge funds, institutions, and other large market participants strategically fill their orders in areas of thin liquidity to minimize slippage and market impact. By detecting these zones, traders gain valuable insights into potential areas of accumulation, distribution, and liquidity traps, allowing for more informed trading decisions.
🔍 Key Features
Real-time volume delta calculation using lower timeframe data
Dynamic zone creation based on volume spikes
Automatic timeframe optimization
Size-filtered zones to avoid noise
Custom delta timeframe scanning
Flexible analysis period selection
📊 Visual Demonstration
💡 How It Works
The indicator continuously scans for high-volume areas where trading activity exceeds the specified threshold (default 6.0x average volume). When detected, it creates zones that display the net volume delta, showing whether buying or selling pressure dominated that price level.
Key zone characteristics:
Size filtering prevents noise from large price swings
Volume delta shows actual buying/selling pressure
Zones automatically expire based on lookback period
Real-time updates as new volume data arrives
⚙️ Settings
Time Settings
Analysis Timeframe: 15M to 1W options
Custom Period: User-defined bar count
Delta Timeframe: Automatic or manual selection
Volume Analysis
Volume Threshold: Minimum spike multiple
Volume MA Length: Averaging period
Maximum Zone Size: Size filter percentage
Display Options
Zone Color: Customizable with transparency
Delta Display: On/Off toggle
Text Position: Left/Center/Right alignment
📌 Tips for Best Results
Adjust volume threshold based on instrument volatility
Monitor zone clusters for potential support/resistance
Consider reducing max zone size in volatile markets
Use in conjunction with price action and other indicators
⚠️ Important Notes
Requires volume data from your data provider
Lower timeframe scanning may impact performance
Maximum 500 zones maintained for optimization
Zone creation is filtered by both volume and size
🔧 Volume Delta Calculation
The indicator uses TradingView’s advanced volume delta calculation, which:
Scans lower timeframe data for precision
Measures actual buying vs selling pressure
Updates in real-time with new data
Provides clear positive/negative flow indication
This tool is ideal for traders focusing on volume analysis and order flow. It helps identify key levels where significant trading activity has occurred and provides insight into the nature of that activity through volume delta analysis.
Note: Performance may vary based on your chart’s timeframe. Adjust settings according to your trading style and the instrument’s characteristics. Past performance is not indicative of future results, DYOR.
Liquidity Trading Algorithm (LTA)
The Liquidity Trading Algorithm is an algorithm designed to provide trade signals based on
liquidity conditions in the market. The underlying algorithm is based on the Liquidity
Dependent Price Movement (LDPM) metric and the Liquidity Dependent Price Stability (LDPS)
algorithm.
Together, LDPM and LDPS demonstrate statistically significant forecasting capabilities for price-
action on equities, cryptocurrencies, and futures. LTA takes these liquidity measurements and
translates them into actionable insights by way of entering or exiting a position based
on the future outlooks, as measured by the current liquidity status.
The benefit of LTA is that it can incorporate these powerful liquidity measurements into
actionable insights with several features designed to help you tailor LTA's behavior and
measurements to your desired vantage point. These customizable features come by the way of determining LTA's assessment style, and additional monitoring systems for avoiding bear and bull traps, along with various other quality of life features, discussed in more detail below.
First, a few quick facts:
- LTA is compatible on a wide array of instruments, including Equities, Futures, Cryptocurrencies, and Forex.
- LTA is compatible on most intervals in so long as the data can be calculated appropriately,
(be sure to do a backtest on timescales less than 1-minue to ensure the data can be computed).
- LTA only measures liquidity at the end of the interval of the chart chosen, and does not respond to conditions during the candle interval, unless specified (such as with `Stops`).
- LTA is interval-dependent, this means it will measure and behave differently on different
intervals as the underlying algorithms are dependent on the interval chosen.
- LTA can utilize fractional share sizing for cryptocurrencies.
- LTA can be restricted to either bullish or bearish indications.
- Additional Monitoring Systems are available for additional risk mitigation.
In short, LTA is a widely applicable, unique algorithm designed to translate liquidity measurements into liquidity insights.
Before getting more into the details, here is a quick list of the main features and settings
available for customization:
- Backtesting Start Date: Manual selection of the start date for the algorithm during backtesting.
- Assessment Style: adjust how LDPM and LDPS measure and respond to changes in liquidity.
- Impose Wait: force LTA to wait before entering or exiting a position to ensure conditions have remained conducive.
- Trade Direction Allowance: Restrict LTA to only long or only short, if desired.
- Position Sizing Method: determine how LTA calculates position sizing.
- Fractional Share Sizing: allow LTA to calculate fractional share sizes for cryptocurrencies
- Max Size Limit: Impose a maximum size on LTA's positions.
- Initial Capital: Indicate how much capital LTA should stat with.
- Portfolio Allotment: Indicate to LTA how much (in percentages) of the available balance should be considered when calculating position size.
- Enact Additional Monitoring Systems: Indicate if LTA should impose additional safety criteria when monitoring liquidity.
- Configure Take Profit, Stop-Loss, Trailing Stop Loss
- Display Information tables on the current position, overall strategy performance, along
with a text output showing LTA's processes.
- Real-time text output and updates on LTA's inner workings.
Let's get into some more of the details.
LTA's Assessment Style
LTA's assessment style determines how LTA collects and responds to changing data. In traditional terms, this is akin to (but not quite exactly the same as) the sensitivity versus specificity spectrum, whereby on one end (the sensitive end), an algorithm responds to changes in data in a reactive manner (which tends to lower its specificity, or how often it is correct in its indications), and on the other end, the opposite one, the algorithm foresakes quick changes for longevity of outlook.
While this is in part true, it is not a full view of the underlying mechanisms that changing the assessment style augments. A better analogy would be that the sensitive end of the spectrum (`Aggressive`) is in a state such that the algorithm wants to changing its outlooks, and as such, with changes in data, the algorithm has to be convinced as to why that is not a good idea to change outlooks, whereas the the more specific states (`Conservative`, `Diamond`) must be convinced that their view is no longer valid and that it needs to be changed.
This means the `Aggressive` and the `Diamond` settings fundamentally differ not just in their
data collection, but also in the data processing such that the `Aggressive` decision tree has to
be convinced that the data is the same (as its defualt is that it has changed),
and the `Diamond` decision tree has to be convinced that the data is not the same, and as such, the outlook need changed.
From there, the algorithm cooks through the data and determines to what the outlook should be changed to, given the current state of liquidity.
`Balanced` lies in the middle of this balance, attempting to balance being open to new ideas while not removing the wisdom of the past, as it were.
On a scale of most `sensitive` to most `specific`, it is as follows: `Aggressive`, `Balanced`,
`Conservative`, `Diamond`.
Functionally, these different modes can help in different liquidity environments, as certain
environments are more conducive to an eager approach (such as found near `Aggressive`) or are more conducive to a more conservative approach, where sudden changes in liquidity are known to be short-lived and unremarkable (such as many previously identified bull or bear traps).
For instance, on low interval views, it can often-times be beneficial to keep the algorithm towards the `Sensitive` end, since on the lower-timeframes, the crosswinds can change quite dramatically; whereas on the longer intervals, it may be useful to maintain a more `Specific` algorithm (such as found near `Diamond` mode) setting since longer intervals typically lend themselves to longer time-horizons, which themselves typically lend themselves to "weathering the storm", as it were.
LTA's Assessment Style is also supported by the Additional Monitoring Systems which works
to add sensitivity without sacrificing specificity by enacting a separate monitoring system, as described below.
Additional Monitoring Systems
The Additional Monitoring System (AMS) attempts to add more context to any changes in liquidity conditions as measured, such that LTA as a whole will have an expanded view into any rapidly changing liquidity conditions before these changes manifest in the traditional data streams. The ideal is that this allows for early exits or early entrances to positions "a head of time".
The traditional use of this system is to indicate when liquidity is suggestive of the end of a particular run (be it a bear run or a bull run), so an early exit can be initiated (and thus,
downside averted) even before the data officially showcase such changes. In such cases (when AMS becomes activated), the algorithm will signal to exit any open positions, and will restrict the opening of any new positions.
When a position is exited because of AMS, it is denoted as an `Early Exit` and if a position is prevented from being entered, the text output will display `AM prevented entry...` to indicate that conditions are not meeting AMS' additional standards.
The algorithm will wait to make any actions while `AMS` is `active` and will only enter into a new position once `AMS` has been `deactivated` and overall liquidity conditions are appropriate.
Functionally, the benefits of AMS translate to:
- Toggeling AMS on will typically see a net reduction in overall profitability, but
- AMS will typically (almost always) reduce max drawdown,
an increases in max runup, and increase return-over-maxdrawdown, and
- AMS can provide benefit for equities that experience a lot of "traps" by navigating early
entrance and early exits.
So in short, AMS is way of adding an additional level of liquidity monitoring that attempts to
exit positions if conditions look to be deteriorating, and to enter conditions if they look to be
improving. The cost of this additional monitoring, however, is a greater number of trades indicated, and a lower overall profitability.
Impose Wait
Note: `Impose Wait` will not force Take Profit, Stop Loss, or Trailing Stop Loss to
wait.
LTA can be indicated to `wait` before entering or exiting a position if desired. This means that if conditions change, whereas without a `wait` imposed, the algorithm would immediately indicate this change via a signal to alter the strategy's position, with a `wait` imposed, the algorithm will `wait` the indicated number of bars, and then re-check conditions before proceeding.
If, while waiting, conditions change to a state that is no longer compatible with the "order-in-
waiting", then the order-in-waiting is removed, and the counts reset (i.e.: conditions must remain favorable to the intended positional change throughout the wait period).
Since LTA works at the end-of-intervals, there is an inherently "built-in" wait of 1 bar when
switching directly from long to short (i.e.: if a full switch is indicated, then it is indicated as
conditions change -> exit new position -> wait until -> check conditions ->
enter new position as indicated). Thus, to impose a wait of `1 bar` would be to effectively have a total of two candles' ends prior to the entrance of the new position).
There are two main styles of `Impose Wait` that you can utilize:
- `Wait` : this mode will cause LTA to `wait` when both entering and exiting a position (in so long as it is not an exit signaled via a Take Profit, Stop Loss or Trailing Stop Loss).
- `Exit-Wait` : This mode will >not< cause LTA to `wait` if conditions require the closing of a position, but will force LTA to wait before entering into a position.
Position:
In addition to the availability to restrict LTA to either a long-only or short-only strategy, LTA
also comprises additional flexibility when deciding on how it should navigate the markets with
regards to sizing. Notably, this flexibility benefits several aspects of LTA's existence, namely the ability to determine the `Sizing Method`, or if `Fractional Share Sizing` should be employed, and more, as discussed below.
Position Sizing Method
There are two main ways LTA can determine the size of a position. Either via the `Fixed-Share` choice, or the `Fixed-Percentage` choice.
- `Fixed-Share` will use the amount indicated in the `Max Sizing Limit` field as the position size, always.
Note: With `Fixed-Share` sizing, LTA will >not< check if the balance is sufficient
prior to signaling an entrance.
- `Fixed-Percentage` will use the percentage amount indicated in the `Portfolio Allotment` field as the percentage of available funds to use when calculating the position size. Additionally, with the `Fixed-Percentage` choice, you can set the `Max Sizing Limit` if desired, which will ensure that no position will be entered greater than the amount indicated in the field.
Fractional Share Sizing
If the underlying instrument supports it (typically only cryptocurrencies), share sizing can be
fractionalized. If this is done, the resulting positin size is rounded to `4 digits`. This means any
position with a size less than `0.00005` will be rounded to `0.0000`
Note: Ensure that the underlying instrument supports fractional share sizing prior
to initiating.
Max Sizing Limit
As discussed above, the `Max Sizing Limit` will determine:
- The position size for every position, if `Sizing Method : Fixed-Share` is utilized, or
- The maximum allowed size, regardless of available capital, if `Sizing Method : Fixed-Percentage` is utilized.
Note: There is an internal maximum of 100,000 units.
Initial Capital
Note: There are 2 `Initial Capital` settings; one in LTA's settings and one in the
`Properties` tab. Ensure these two are the same when doing backtesting.
The initial capital field will be used to determine the starting balanace of the strategy, and
is used to calculate the internal data reporting (the data tables).
Portfolio Allotment
You can specify how much of the total available balance should be used when calculating the share size. The default is 100%.
Stops
Note: Stops over-ride `AMS` and `Impose Wait`, and are not restricted to only the
end-of-candle and will occur instantaneously upon their activation. Neither `AMS` nor `Impose Wait` can over-ride a signal from a `Take-Profit`, `Stop-Loss`, or a `Trailing-Stop Loss`.
LTA enhouses three stops that can be configured, a `Take-Profit`, a `Stop-Loss` and a `Trailing-Stop Loss`. The configurations can be set in the settings in percent terms. These exit signals will always over-ride AMS or any other restrictions on position exit.
Their configuration is rather standard; set the percentages you want the signal to be sent at and so it will be done.
Some quick notes on the `Trailing-Stop Loss`:
- The activation percentage must be reached (in profits) prior to the `Traililng-Stop Loss`
from activating the downside protection. For example, if the `Activation Percentage` is 10%, then unless the position reaches (at any point) a 10% profit, then it will not signal any exits on the downside, should it occur.
- The downside price-point is continuously updated and is calculated from the maximum profit reached in the given position and the loss percentage placed in the appropriate field.
Data Tables and Data Output
LTA provides real-time data output through a variety of mechanisms:
- `Position Table`
The `Position Table` displays information about the current position, including:
> Position Duration : how long the position has been open for.
> Indicates if the side is Long or Short, depending on if it is long or short.
> Entry Price: the price the position was entered at.
> Current Price (% Dif): the current price of the underlying and the %-difference between the entry price and the current price.
> Max Profit ($/%): the maximum profit reached in $ and % terms.
> Current PnL ($/%) : the current PnL for the open position.
- `Performance Table`
The `Performance Table` displays information regarding the overall performance of the algorithm since its `Start Date`. These data include:
> Initial Equity ($): The initial equity the algorithm started with.
> Current Equity ($): The current total equity of the account (including open positions)
> Net Profits ($|%) : The overall net profit in $ and % terms.
> Long / Short Trade Counts: The respective trade counts for the positions entered.
> Total Closed Trades: The running sum of the number of trades closed.
> Profitability: The calculation of the number of profitable trades over the total number of
trades.
> Avg. Profit / Trade: The calculation of the average profit per trade in both $ and % terms.
> Avg. Loss / Trade: The calculation of the average loss per trade in both $ and % terms.
> Max Run-Up: The maximum run-up the algorithm has seen in both $ and % terms.
> Max Drawdown: The maximum draw-down the algorithm has seen in both $ and % terms.
> Return-Over-Max-Drawdown: the ratio of the maximum drawdown against the current net profits.
- `Text Output`
LTA will output, if desired, signals to the text output field every time it analysis or performs and action. These messages can include information such as:
"
08:00:00 >> AM Protocol activated ... exiting position ...
08:00:00 >> Exit Order Created for qty: 2, profit: 380 (4.34%)
...
09:30:00 >> Checking conditions ...
09:30:00 >> AM protocol prevented entry ... waiting ...
"
This way, you can keep an eye out on what is happening "under the hood", as it were.
LTA will produce a message at the end of its assessment at the end of each candle interval, as well as when a position is exited due to a `Stop` or due to `AMS` being activated.
Additionally, the `Text Output` includes a initial message, but for space-constraints, this
can be toggled off with the `Blank Text Output` option within LTA's configurations.
For additional information, please refer to the Author's Instructions below.
QuantFrame | FractalystWhat’s the purpose of this indicator?
The purpose of QuantFrame is to provide traders with a systematic approach to analyzing market structure, eliminating subjectivity, and enhancing decision-making. By clearly identifying and labeling structural breaks, QuantFrame helps traders:
1. Refine Market Analysis: Transition from discretionary market observation to a structured framework.
2. Identify Key Levels: Highlight important liquidity and invalidation zones for potential entries, exits, and risk management.
3. Streamline Multi-Timeframe Analysis: Track market trends and structural changes across different timeframes seamlessly.
4. Enhance Consistency: Reduce guesswork by following a rule-based methodology for identifying structural breaks.
How Does This Indicator Identify Market Structure?
1. Swing Detection
• The indicator identifies key swing points on the chart. These are local highs or lows where the price reverses direction, forming the foundation of market structure.
2. Structural Break Validation
• A structural break is flagged when a candle closes above a previous swing high (bullish) or below a previous swing low (bearish).
• Break Confirmation Process:
To confirm the break, the indicator applies the following rules:
• Valid Swing Preceding the Break: There must be at least one valid swing point before the break.
3. Numeric Labeling
• Each confirmed structural break is assigned a unique numeric ID starting from 1.
• This helps traders track breaks sequentially and analyze how the market structure evolves over time.
4. Liquidity and Invalidation Zones
• For every confirmed structural break, the indicator highlights two critical zones:
1. Liquidity Zone (LIQ): Represents the structural liquidity level.
2. Invalidation Zone (INV): Acts as Invalidation point if the structure fails to hold.
What do the extremities show us on the charts?
When using QuantFrame for market structure analysis, the extremities—Liquidity Level (LIQ) and Invalidation Level (INV)—serve as critical reference points for understanding price behavior and making informed trading decisions.
Here's a detailed explanation of what these extremities represent and how they function:
Liquidity Level (LIQ)
Definition: The Liquidity Level is a key price zone where the market is likely to retest, consolidate, or seek liquidity. It represents areas where orders are concentrated, making it a high-probability reaction zone.
Purpose: Traders use this level to anticipate potential pullbacks or continuation patterns. It helps in identifying areas where price may pause or reverse temporarily due to the presence of significant liquidity.
Key Insight: If a candle closes above or below the LIQ, it results in another break of structure (BOS) in the same direction. This indicates that price is continuing its trend and has successfully absorbed liquidity at that level.
Invalidation Level (INV)
Definition: The Invalidation Level marks the threshold that, if breached, signifies a structural shift in the market. It acts as a critical point where the current market bias becomes invalid.
Purpose: This level is often used as a stop-loss or re-evaluation point for trading strategies. It ensures that traders have a clear boundary for risk management.
Key Insight: If a candle closes above or below the INV, it signals a shift in market structure:
A closure above the INV in a bearish trend indicates a shift from bearish to bullish bias.
A closure below the INV in a bullish trend indicates a shift from bullish to bearish bias.
What does the top table display?
The top table in QuantFrame serves as a multi-timeframe trend overview. Here’s what it provides:
1. Numeric Break IDs Across Multiple Timeframes:
• Each numeric break corresponds to a confirmed structural break on a specific timeframe, helping traders track the most recent breaks systematically.
2. Trend Direction via Text Color:
• The color of the text reflects the current trend direction:
• Blue indicates a bullish structure.
• Red signifies a bearish structure.
3. Higher Timeframe Insights Without Manual Switching:
• The table eliminates the need to switch between timeframes by presenting a consolidated view of the market trend across multiple timeframes, saving time and improving decision-making.
What is the Multi-Timeframe Trend Score (MTTS)?
MTTS is a score that quantifies trend strength and direction across multiple timeframes.
How does MTTS work?
1. Break Detection:
• Analyzes bullish and bearish structural breaks on each timeframe.
2. Trend Scoring:
• Scores each timeframe based on the frequency and quality of bullish/bearish breaks.
3. MTTS Calculation:
• Averages the scores across all timeframes to produce a unified trend strength value.
How is MTTS interpreted?
• ⬆ (Above 50): Indicates an overall bullish trend.
• ⬇ (Below 50): Suggests an overall bearish trend.
• ⇅ (Exactly 50): Represents a neutral or balanced market structure.
How to Use QuantFrame?
1. Implement a Systematic Market Structure Framework:
• Use QuantFrame to analyze market structure objectively by identifying key structural breaks and marking liquidity (LIQ) and invalidation (INV) zones.
• This eliminates guesswork and provides a clear framework for understanding market movements.
2. Leverage MTTS for Directional Bias:
• Refer to the MTTS table to identify the multi-timeframe directional bias, giving you the broader market context.
• Align your trading decisions with the overall trend or structure to improve accuracy and consistency.
3. Apply Your Preferred Entry Model:
• Once the market context is clear, use your preferred entry model to capitalize on the identified structure and trend.
• Manage trades dynamically as price delivers, using the provided liquidity and invalidation zones for risk management.
What Makes QuantFrame Original?
1. Objective Market Structure Analysis:
• Unlike subjective methods, QuantFrame uses a rule-based approach to identify structural breaks, ensuring consistency and reducing emotional decision-making.
2. Multi-Timeframe Integration:
• The MTTS table consolidates trend data across multiple timeframes, offering a bird’s-eye view of market trends without the need to switch charts manually.
• This unique feature allows traders to align strategies with higher-timeframe trends for more informed decision-making.
3. Liquidity and Invalidation Zones:
• Automatically marks Liquidity (LIQ) and Invalidation (INV) zones for every structural break, providing actionable levels for entries, exits, and risk management.
• These zones help traders define their risk-reward setups with precision.
4. Dynamic Trend Scoring (MTTS):
• The Multi-Timeframe Trend Score (MTTS) quantifies trend strength and direction across selected timeframes, offering a single, consolidated metric for market sentiment.
• This score is visualized with intuitive symbols (⬆, ⬇, ⇅) for quick decision-making.
5. Numeric Labeling of Breaks:
• Each structural break is assigned a unique numeric ID, making it easy to track, analyze, and backtest specific market scenarios.
6. Systematic Yet Flexible:
• While it provides a structured framework for market analysis, QuantFrame seamlessly integrates with any trading style. Traders can use it alongside their preferred entry models, adapting it to their unique strategies.
7. Enhanced Market Context:
• By combining structural insights with directional bias (via MTTS), the indicator equips traders with a complete market context, enabling them to make better-informed decisions.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
[GrandAlgo] Liquidity HeatmapThe Liquidity Heatmap is a unique indicator designed to identify and highlight zones where price is likely to react based on liquidity dynamics. Unlike tools that analyze volume across all price levels, this indicator focuses specifically on liquidity concentrated around potential reversal zones. By evaluating price action and volume at these critical levels, it identifies areas of heightened interest for traders.
Key Features:
Dynamic Liquidity Zones:
Automatically calculates liquidity zones based on historical price activity, ensuring real-time relevance.
Volume-Based or Candle Interaction Analysis:
Choose between volume-based evaluation to focus on order flow or candle-based interaction for a broader perspective.
Customizable Percentile Threshold:
Filter zones based on their significance by setting a threshold to display only the top liquidity areas.
Lookback Period Control:
Define how many candles the indicator should analyze, allowing you to focus on short-term or long-term liquidity levels.
Color-Coded Visuals:
Liquidity zones are displayed using gradients, with green representing potential bullish zones (below price) and red representing potential bearish zones (above price). Stronger zones are indicated with darker colors.
How It Works:
The Liquidity Heatmap divides the price range into multiple levels, evaluating each level for interaction with historical price data. Liquidity zones are calculated based on:
Volume Concentration: When enabled, the indicator evaluates zones using historical volume, highlighting areas with significant order flow.
Candle Interactions: When volume-based analysis is disabled, the indicator calculates the number of candles interacting with each zone to determine its importance.
Zones that meet the user-defined percentile threshold are highlighted on the chart. Color gradients indicate the strength of each zone, allowing traders to prioritize the most significant areas. Real-time alerts notify users when the price touches these zones, providing actionable insights.
The image illustrates the volume-based analysis feature of the Liquidity Heatmap indicator. Liquidity zones are dynamically highlighted with intuitive color gradients—green for bullish volume and red for bearish volume—providing a clear visual representation of areas with concentrated liquidity at potential reversal points. This feature helps traders focus on zones with significant market activity, enhancing their decision-making process.
Disclaimer
This indicator is a technical analysis tool designed to assist traders by providing insights into market conditions. It does not guarantee future price movements or trading outcomes and should not be relied upon as a sole decision-making tool. The effectiveness of this indicator depends on its application, which requires your trading knowledge, experience, and judgment.
Trading involves significant financial risk, including the potential loss of capital. Past performance of any tool or indicator does not guarantee future results. This script is intended for educational and informational purposes only and does not constitute financial or investment advice. Users are strongly encouraged to perform their own analysis and consult with a qualified financial professional before making trading decisions.
JJ Highlight Time Ranges with First 5 Minutes and LabelsTo effectively use this Pine Script as a day trader , here’s how the various elements can help you manage trades, track time sessions, and monitor price movements:
Key Components for a Day Trader:
1. First 5-Minute Highlight:
- Purpose: Day traders often rely on the first 5 minutes of the trading session to gauge market sentiment, watch for opening price gaps, or plan entries. This script draws a horizontal line at the high or low of the first 5 minutes, which can act as a key level for the rest of the day.
- How to Use: If the price breaks above or below the first 5-minute line, it can signal momentum. You might enter a long position if the price breaks above the first 5-minute high or a short if it breaks below the first 5-minute low.
2. Session Time Highlights:
- Morning Session (9:15–10:30 AM): The market often shows its strongest price action during the first hour of trading. This session is highlighted in yellow. You can use this highlight to focus on the most volatile period, as this is when large institutional moves tend to occur.
- Afternoon Session (12:30–2:55 PM): The blue highlight helps you track the mid-afternoon session, where liquidity may decrease, and price action can sometimes be choppier. Day traders should be more cautious during this period.
- How to Use: By highlighting these key times, you can:
- Focus on key breakouts during the morning session.
- Be more conservative in your trades during the afternoon, as market volatility may drop.
3. Dynamic Labels:
- Top/Bottom Positioning: The script places labels dynamically based on the selected position (Top or Bottom). This allows you to quickly glance at the session's start and identify where you are in terms of time.
- How to Use: Use these labels to remind yourself when major time segments (morning or afternoon) begin. You can adjust your trading strategy depending on the session, e.g., being more aggressive in the morning and more cautious in the afternoon.
Trading Strategy Suggestions:
1. Momentum Trades:
- After the first 5 minutes, use the high/low of that period to set up breakout trades.
- Long Entry: If the price breaks the high of the first 5 minutes (especially if there's a strong trend).
- Short Entry: If the price breaks the low of the first 5 minutes, signaling a potential downtrend.
2. Session-Based Strategy:
- Morning Session (9:15–10:30 AM):
- Look for strong breakout patterns such as support/resistance levels, moving average crossovers, or candlestick patterns (like engulfing candles or pin bars).
- This is a high liquidity period, making it ideal for executing quick trades.
- Afternoon Session (12:30–2:55 PM):
- The market tends to consolidate or show less volatility. Scalping and mean-reversion strategies work better here.
- Avoid chasing big moves unless you see a clear breakout in either direction.
3. Support and Resistance:
- The first 5-minute high/low often acts as a key support or resistance level for the rest of the day. If the price holds above or below this level, it’s an indication of trend continuation.
4. Breakout Confirmation:
- Look for breakouts from the highlighted session time ranges (e.g., 9:15 AM–10:30 AM or 12:30 PM–2:55 PM).
- If a breakout happens during a key time window, combine that with other technical indicators like volume spikes , RSI , or MACD for confirmation.
---
Example Day Trader Usage:
1. First 5 Minutes Strategy: After the market opens at 9:15 AM, watch the price action for the first 5 minutes. The high and low of these 5 minutes are critical levels. If the price breaks above the high of the first 5 minutes, it might indicate a strong bullish trend for the day. Conversely, breaking below the low may suggest bearish movement.
2. Morning Session: After the first 5 minutes, focus on the **9:15 AM–10:30 AM** window. During this time, look for breakout setups at key support/resistance levels, especially when paired with high volume or momentum indicators. This is when many institutions make large trades, so price action tends to be more volatile and predictable.
3. Afternoon Session: From 12:30 PM–2:55 PM, the market might experience lower volatility, making it ideal for scalping or range-bound strategies. You could look for reversals or fading strategies if the market becomes too quiet.
Conclusion:
As a day trader, you can use this script to:
- Track and react to key price levels during the first 5 minutes.
- Focus on high volatility in the morning session (9:15–10:30 AM) and **be cautious** during the afternoon.
- Use session-based timing to adjust your strategies based on the time of day.
Multi-Timeframe Liquidity LevelsMulti-Timeframe Liquidity Levels – Overview
The Multi-Timeframe Liquidity Levels indicator automatically displays significant highs and lows from various timeframes (Daily, Weekly, Monthly, and Quarterly) on your current chart. This allows traders to quickly identify potential support and resistance zones without frequently switching between different timeframe charts. Additionally, the script offers extra lines for special reference points (e.g., the “Midnight” midpoint of the current day and the previous day’s open/close) to highlight potential liquidity zones even more clearly.
1. Core Idea and Benefits
Time-Saving: Instead of manually reviewing charts in different timeframes, the indicator fetches relevant high/low levels automatically and shows them on your active timeframe.
Clear Layout: Traders instantly see where the Daily, Weekly, Monthly, and Quarterly highs and lows lie—areas often associated with institutional orders or liquidity hunts.
Customizable: You can tailor the color scheme, line style (Solid, Dashed, Dotted), and line width, ensuring the displayed levels fit your personal charting style.
2. How It Works
Multi-Timeframe High/Low
For each timeframe (Day, Week, Month, Quarter), the indicator references the previous candle’s high and low (high , low ).
Using request.security(...), these values are plotted on the chart you’re currently viewing.
Flexible Display
You can individually enable or disable the Daily, Weekly, Monthly, and Quarterly lines, depending on which levels are most relevant to your trading.
With Line Style (Solid, Dashed, Dotted) and Line Width, you can easily emphasize certain lines you consider more important.
Additional Lines
“Midnight” Line: A theoretical midpoint between today’s high and low, which can be useful for gauging daily pivot areas.
Previous Day’s Open/Close: Many traders track these reference points to anticipate market reactions. You can show or hide these lines as desired.
Automatic Line Removal & Creation
When a particular timeframe (e.g., “Show Monthly Levels”) is disabled, the script automatically removes the existing monthly lines.
Enabling it again recreates those lines without hassle.
3. Usage and Interpretation
Identifying Support and Resistance
Highs and lows from higher timeframes are often key zones for entries, exits, or major market reactions.
A Daily level may be crucial for short-term traders, whereas Monthly or Quarterly levels can indicate long-term liquidity areas.
Spotting Market Shifts
If price decisively moves above a Higher-Timeframe line, it could signal strong momentum.
Conversely, a failed breakout (where price quickly returns under or above a level) might warn of a potential reversal.
Extra Lines as Filters
The “Midnight” Line helps visualize a rough central price for the current day, aiding in intraday directional bias.
Previous Day’s Open/Close: Common reference points for day traders, where swift approaches and rejections can indicate potential entries or partial take-profit zones.
4. Practical Tips
Use Color-Coding Wisely: Assign distinct colors (e.g., Blue for Daily, Green for Weekly, Orange for Monthly, Purple for Quarterly) so you can easily discern which timeframe you’re looking at.
Toggle On/Off As Needed: Day traders might focus on Daily and Weekly, while long-term traders may pay closer attention to Monthly and Quarterly.
Combine with Price Action: Lines alone don’t constitute a trading strategy. Use them alongside candlestick patterns, volume analysis, or other indicators for a more complete market perspective.
5. Important Notes & Recommendations
Not Financial Advice: This indicator simply reflects historical high/low data across multiple timeframes and does not constitute a buy or sell recommendation.
Trader Responsibility: Observe how the market actually behaves around these lines and adapt your risk management accordingly.
