Price based concepts / quantifytools- Overview
Price based concepts incorporates a collection of multiple price action based concepts. Main component of the script is market structure, on top of which liquidity sweeps and deviations are built on, leaving imbalances the only standalone concept included. Each concept can be enabled/disabled separately for creating a selection of indications that one deems relevant for their purposes. Price based concepts are quantified using metrics that measure their expected behavior, such as historical likelihood of supportive price action for given market structure state and volume traded at liquidity sweeps. The concepts principally work on any chart, whether that is equities, currencies, cryptocurrencies or commodities, charts with volume data or no volume data. Essentially any asset that can be considered an ordinary speculative asset. The concepts also work on any timeframe, from second charts to monthly charts. None of the indications are repainted.
Market structure
Market structure is an analysis of support/resistance levels (pivots) and their position relative to each other. Market structure is considered to be bullish on a series of higher highs/higher lows and bearish on a series of lower highs/lower lows. Market structure shifts from bullish to bearish and vice versa on a break of the most recent pivot high/low, indicating weak ability to defend a key level from the dominating side. Supportive market structure typically provides lengthier and sustained trending environment, making it an ideal point of confluence for establishing directional bias for trades.
Liquidity sweeps
Liquidity sweeps are formed when price exceeds a pivot level that served as a provable level of demand once and is expected to display demand again when revisited. A simple way to look at liquidity sweeps is re-tests of untapped support/resistance levels.
Deviations
Deviations are formed when price exceeds a reference level (market structure shift level/liquidity sweep level) and shortly closes back in, leaving participating breakout traders in an awkward position. On further adverse movement, stuck breakout traders are forced to cover their underwater positions, creating ideal conditions for a lengthier reversal.
Imbalances
Imbalances, also known as fair value gaps or single prints, depict areas of inefficient and one sided transacting. Given inclination for markets to trade efficiently, price is naturally attracted to areas that lack proper participation, making imbalances ideal targets for entries or exits.
Key takeaways
- Price based concepts consists of market structure, liquidity sweeps, deviations and imbalances.
- Market structure shifts from bullish to bearish and vice versa on a break of the most recent pivot high/low, indicating weak ability to defend a key level from the dominating side.
- Supportive market structure tends to provide lengthier and sustained movement for the dominating side, making it an ideal foundation for establishing directional bias for trades.
- Liquidity sweeps are formed when price exceeds an untapped support/resistance level that served as a provable level of demand in the past, likely to show demand again when revisited.
- Deviations are formed when price exceeds a key level and shortly closes back in, leaving breakout traders in an awkward position. Further adverse movement compels trapped participants to cover their positions, creating ideal conditions for a reversal.
- Imbalances depict areas of inefficient and one sided transacting where price is naturally attracted to, making them ideal targets for entries or exits.
- Price based concepts are quantified using metrics that measure expected behavior, such as historical likelihood of supportive structure and volume traded at liquidity sweeps.
- For practical guide with practical examples, see last section.
Accessing script 🔑
See "Author's instructions" section, found at bottom of the script page.
Disclaimer
Price based concepts are not buy/sell signals, a standalone trading strategy or financial advice. They also do not substitute knowing how to trade. Example charts and ideas shown for use cases are textbook examples under ideal conditions, not guaranteed to repeat as they are presented. Price based concepts notify when a set of conditions are in place from a purely technical standpoint. Price based concepts should be viewed as one tool providing one kind of evidence, to be used in conjunction with other means of analysis.
Price based concepts are backtested using metrics that reasonably depict their expected behaviour, such as historical likelihood of supportive price movement on each market structure state. The metrics are not intended to be elaborate and perfect, but to serve as a general barometer for feedback created by the indications. Backtesting is done first and foremost to exclude scenarios where the concepts clearly don't work or work suboptimally, in which case they can't be considered as valid evidence. Even when the metrics indicate historical reactions of good quality, price impact can and inevitably does deviate from the expected. Past results do not guarantee future performance.
- Example charts
Chart #1 : BTCUSDT
Chart #2 : EURUSD
Chart #3 : ES futures
Chart #4 : NG futures
Chart #5 : Custom timeframes
- Concepts
Market structure
Knowing when price has truly pivoted is much harder than it might seem at first. In this script, pivots are determined using a custom formula based on volatility adjusted average price, a fundamentally different approach to the widely used highest/lowest price within X amount of bars. The script calculates average price within set period and adjusts it to volatility. Using this formula, the script determines when price has turned significantly enough and aggressively enough to constitute a relevant pivot, resulting in high accuracy while ruling out subjective decision making completely. Users can adjust length of market structure basis and sensitivity of volatility adjustment to achieve desired magnitude of pivots, reflected on the average swing metrics. Note that structure pivots are backpainted. Typical confirmation time for a pivot is within 2-3 bars after peak in price.
Market structure shifts
Generally speaking, traders consider market structure to have shifted when most recent structure high/low gets taken out, flipping underlying bias from one side over to the other (e.g. from bullish structure favoring upside to bearish structure favoring downside). However, there are many ways to approach the concept and the most popular method might not always be the best one. Users can determine their own market structure shift rules by choosing source (close, high, low, ohlc4 etc.) for determining structure shift. Users can also choose additional rules for structure shift, such as two consecutive closes above/below pivot to qualify as a valid shift.
Liquidity sweeps
Users can set maximum amount of bars liquidity levels are considered relevant from the moment of confirmed pivot. By default liquidity levels are monitored for 250 bars and then discarded. Level of tolerance can be set to anything between 100 and 1000 bars. For each liquidity sweep, relative volume (volume relative to volume moving average) is stored and added to average calculations for keeping track of typical depth of liquidity found at sweeps.
Deviations
Users can set a maximum amount of bars price has to spend above/below reference level to consider a deviation to be in place. By default set to 6 bars.
Imbalances
Users can set a desired fill point for imbalances using the following options: 100%, 75%, 50%, 25%. Users can also opt for excluding insignificant imbalances to attain better relevance in indications.
- Backtesting
Built-in backtesting is based on metrics that are considered to reasonably quantify expected behaviour of the main concept, market structure. Structure feedback is monitored using two metrics, supportive structure and structure period gain. Rest of the metrics provided are informational in nature, such as average swing and average relative volume traded at liquidity sweeps. Main purpose of the metrics is to form a general barometer for monitoring whether or not the concepts can be viewed as valid evidence. When the concepts are clearly not working optimally, one should adjust expectations accordingly or take action to improve performance. To make any valid conclusions of performance, sample size should also be significant enough to eliminate randomness effectively. If sample size on any individual chart is insufficient, one should view feedback scores on multiple correlating and comparable charts to make up for the loss.
For more elaborate backtesting, price based concepts can be used in any other script that has a source input, including fully mechanic strategies utilizing Tradingview's native backtester. Each concept and their indications (e.g. higher low on a bearish structure, lower high on a bullish structure, market structure shift up, imbalance filled etc.) can be utilized separately and used as a component in a backtesting script of your choice.
Structure feedback
Structure feedback is monitored using two metrics, likelihood of supportive price movement following a market structure shift and average structure period gain. If either of the two employed tests indicate failed reactions beyond a tolerable level, one should take action to improve feedback by adjusting the settings. If feedback metrics after adjusting the settings are still insufficient, the concepts are working suboptimally for the given chart and cannot be regarded as valid technical evidence as they are.
Metric #1 : Supportive structure
Each structure pivot is benchmarked against its respective structure shift level. Feedback is considered successful if structure pivot takes place above market structure shift level (in the case of bullish structure) or below market structure shift level (in the case of bearish structure). Structure feedback constitutes as one test indicating how often a market structure state results in price movement that can be considered supportive.
Metric #2 : Structure period gain
Each structure period is expected to present favorable appreciation, measured from one market structure shift level to another. E.g. bullish structure period gain is measured from market structure shift up level to market structure shift down level that ends the bullish structure period. Bearish structure is measured in a vice versa manner, from market structure shift down level to market structure shift up level that ends the bearish structure period. Feedback is considered successful if average structure period gain is supportive for a given structure (positive for bullish structure, negative for bearish structure).
Additional metrics
On top of structure feedback metrics, percentage gain for each swing (distance between a pivot to previous pivot) is recorded and stored to average calculations. Average swing calculations shed light on typical pivot magnitude for better understanding changes made in market structure settings. Average relative volume traded at liquidity sweep on the other hand gives a clue of depth of liquidity typically found on a sweeps.
Feedback scores
When market structure (basis for most concepts) is working optimally, quality threshold for both feedback metrics are met. By default, threshold for supportive structure is set to 66%, indicating valid feedback on 2/3 of backtesting periods on average. On top, average structure period gain needs to be positive (for bullish structures) and negative (for bearish structure) to qualify as valid feedback. When both tests are passed, a tick indicating valid feedback will appear next to feedback scores, otherwise an exclamation mark indicating suboptimal performance on either or both. If both or either test fail, market structure parameters need to be optimized for better performance or one needs to adjust expectations accordingly.
Verifying backtest calculations
Backtest metrics can be toggled on via input menu, separately for bullish and bearish structure. When toggled on, both cumulative and average counters used in backtesting will appear on "Data Window" tab. Calculation states are shown at a point in time where cursor is hovered. E.g. when hovering cursor on 4th of January 2021, backtest calculations as they were during this date will be shown.
- Alerts
Available alerts are the following.
- HH/HL/LH/LL/EQL/EQH on a bullish/bearish structure
- Bullish/bearish market structure shift
- Bullish/bearish imbalance created
- Bullish/bearish imbalance filled
- Bullish/bearish liquidity sweep
- Bullish/bearish deviation
- Visuals
Each concept can be enabled/disabled separately for creating a selection indications that one deems relevant for their purposes. On top, each concept has a stealth visual option for more discreet visuals.
Unfilled imbalances and untapped liquidity levels can be extended forward to better gauge key areas of interest.
Liquidity sweeps have an intensity option, using color and width to visualize volume traded at sweep.
Market structure states and market structure shifts can be visualized as chart color.
Metric table can be offsetted horizontally or vertically from any four corners of the chart, allowing space for tables from other scripts.
Table sizes, label sizes and colors are fully customizable via input menu.
- Practical guide
The basic idea behind market structure is that a side (bulls or bears) have shown significant weakness on a failed attempt to defend a key level (most recent pivot high/low). In the same way, a side has shown significant strength on a successful attempt to break through a key level. This successful break through a key level often leads to sustained lengthier movement for the side that provably has the upper hand, making it an ideal tool for establishing directional bias.
Multi-timeframe view of market structure provides crucial guidance for analyzing market structure states on any individual timeframe. If higher timeframe market structure is bullish, it doesn't make sense to expect contradicting lower timeframe market structure to provide significant adverse movement, but rather a normal correction within a long term trend. In the same way, if lower timeframe market structure is in agreement with higher timeframe market structure, one can expect a reliable trending environment to ensue as multiple points of confluence are in place.
Bullish structure can be considered constructive on a series of higher highs and higher lows, indicating strong interest from bulls to sustain an uptrend. Vice versa is true for bearish structure, a series of lower highs and lower lows can be considered constructive. When structure does not indicate strong interest to maintain a supportive trend (lower highs on bullish structure, higher lows on bearish structure), a structure shift and a turn in trend might be nearing.
Market structure shifts are of great interest for breakout traders who position for continuation. Structure shifts can indeed be fertile ground for executing a breakout trade, but breakouts can easily turn into fakeouts that leave participants in an awkward position. When price moves further away from the underwater participants, potential for snowball effect of covering positions and driving price further away is elevated.
Liquidity sweeps as a concept is based on the premise that pivoting price is evidence of meaningful depth of liquidity found at/around pivot. If liquidity existed at a pivot once, it is likely to exist there in the future as well. When price grinds against liquidity, it is on a path of resistance rather than path of least resistance. Pivots are also attractive placements for traders to set stop-losses, which act as fuel for price to move to the opposite direction when swept and triggered.
Behind tightly formed pivots are potentially many stop-loss orders lulled in the comfort of having many layers of levels protecting their position. Compression that leaves such clusters of unswept liquidity rarely goes unvisited.
As markets strive for efficient and proper transacting most of the time, imbalances serve as points in price where price is naturally attracted to. However, imbalances too are contextual and sometimes one sided trading is rewarded with follow through, rather than with a fill. Identifying market regimes give further clue into what to expect from imbalances. In a ranging environment, one can expect imbalances to fill relatively quick, making them ideal targets for entries and exits.
On a strongly trending environment on the other hand imbalances tend to stick for a much longer time. In such environments continuation can be expected with no fills or only partial fills. Signs of demand preventing fill attempts serve as additional clues for imminent continuation.
Cerca negli script per "liquidity"
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.
Quantify [Entry Model] | FractalystWhat’s the indicator’s purpose and functionality?
Quantify is a machine learning entry model designed to help traders identify high-probability setups to refine their strategies.
➙ Simply pick your bias, select your entry timeframes, and let Quantify handle the rest for you.
Can the indicator be applied to any market approach/trading strategy?
Absolutely, all trading strategies share one fundamental element: Directional Bias
Once you’ve determined the market bias using your own personal approach, whether it’s through technical analysis or fundamental analysis, select the trend direction in the Quantify user inputs.
The algorithm will then adjust its calculations to provide optimal entry levels aligned with your chosen bias. This involves analyzing historical patterns to identify setups with the highest potential expected values, ensuring your setups are aligned with the selected direction.
Can the indicator be used for different timeframes or trading styles?
Yes, regardless of the timeframe you’d like to take your entries, the indicator adapts to your trading style.
Whether you’re a swing trader, scalper, or even a position trader, the algorithm dynamically evaluates market conditions across your chosen timeframe.
How can this indicator help me to refine my trading strategy?
1. Focus on Positive Expected Value
• The indicator evaluates every setup to ensure it has a positive expected value, helping you focus only on trades that statistically favor long-term profitability.
2. Adapt to Market Conditions
• By analyzing real-time market behavior and historical patterns, the algorithm adjusts its calculations to match current conditions, keeping your strategy relevant and adaptable.
3. Eliminate Emotional Bias
• With clear probabilities, expected values, and data-driven insights, the indicator removes guesswork and helps you avoid emotional decisions that can damage your edge.
4. Optimize Entry Levels
• The indicator identifies optimal entry levels based on your selected bias and timeframes, improving robustness in your trades.
5. Enhance Risk Management
• Using tools like the Kelly Criterion, the indicator suggests optimal position sizes and risk levels, ensuring that your strategy maintains consistency and discipline.
6. Avoid Overtrading
• By highlighting only high-potential setups, the indicator keeps you focused on quality over quantity, helping you refine your strategy and avoid unnecessary losses.
How can I get started to use the indicator for my entries?
1. Set Your Market Bias
• Determine whether the market trend is Bullish or Bearish using your own approach.
• Select the corresponding bias in the indicator’s user inputs to align it with your analysis.
2. Choose Your Entry Timeframes
• Specify the timeframes you want to focus on for trade entries.
• The indicator will dynamically analyze these timeframes to provide optimal setups.
3. Let the Algorithm Analyze
• Quantify evaluates historical data and real-time price action to calculate probabilities and expected values.
• It highlights setups with the highest potential based on your selected bias and timeframes.
4. Refine Your Entries
• Use the insights provided—entry levels, probabilities, and risk calculations—to align your trades with a math-driven edge.
• Avoid overtrading by focusing only on setups with positive expected value.
5. Adapt to Market Conditions
• The indicator continuously adapts to real-time market behavior, ensuring its recommendations stay relevant and precise as conditions change.
How does the indicator calculate the current range?
The indicator calculates the current range by analyzing swing points from the very first bar on your charts to the latest available bar it identifies external liquidity levels, also known as BSLQ (buy-side liquidity levels) and SSLQ (sell-side liquidity levels).
What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Pivot levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into pivot level level. Status: "■" - Inactive
2. Once pivot level is tapped into, the pivot status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
4. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
What does the multi-timeframe functionality offer?
You can incorporate up to 4 higher timeframe probabilities directly into the table.
This feature allows you to analyze the probabilities of buyside and sellside liquidity across multiple timeframes, without the need to manually switch between them.
By viewing these higher timeframe probabilities in one place, traders can spot larger market trends and refine their entries and exits with a better understanding of the overall market context.
What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and uses security function to request the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
How does the Indicator Identifies Positive Expected Values?
Quantify instantly calculates whether a trade setup has the potential to generate positive expected value (EV).
To determine a positive EV setup, the indicator uses the formula:
EV = ( P(Win) × R(Win) ) − ( P(Loss) × R(Loss))
where:
- P(Win) is the probability of a winning trade.
- R(Win) is the reward or return for a winning trade, determined by the current risk-to-reward ratio (RR).
- P(Loss) is the probability of a losing trade.
- R(Loss) is the loss incurred per losing trade, typically assumed to be -1.
By calculating these values based on historical data and the current trading setup, the indicator helps you understand whether your trade has a positive expected value.
How can I know that the setup I'm going to trade with has a positive EV?
If the indicator detects that the adjusted pivot and buy/sell side probabilities have generated positive expected value (EV) in historical data, the risk-to-reward (RR) label within the range box will be colored blue and red .
If the setup does not produce positive EV, the RR label will appear gray.
This indicates that even the risk-to-reward ratio is greater than 1:1, the setup is not likely to yield a positive EV because, according to historical data, the number of losses outweighs the number of wins relative to the RR gain per winning trade.
What is the confidence level in the indicator, and how is it determined?
The confidence level in the indicator reflects the reliability of the probabilities calculated based on historical data. It is determined by the sample size of the probabilities used in the calculations. A larger sample size generally increases the confidence level, indicating that the probabilities are more reliable and consistent with past performance.
How does the confidence level affect the risk-to-reward (RR) label?
The confidence level (★) is visually represented alongside the probability label. A higher confidence level indicates that the probabilities used to determine the RR label are based on a larger and more reliable sample size.
How can traders use the confidence level to make better trading decisions?
Traders can use the confidence level to gauge the reliability of the probabilities and expected value (EV) calculations provided by the indicator. A confidence level above 95% is considered statistically significant and indicates that the historical data supporting the probabilities is robust. This high confidence level suggests that the probabilities are reliable and that the indicator’s recommendations are more likely to be accurate.
In data science and statistics, a confidence level above 95% generally means that there is less than a 5% chance that the observed results are due to random variation. This threshold is widely accepted in research and industry as a marker of statistical significance. Studies such as those published in the Journal of Statistical Software and the American Statistical Association support this threshold, emphasizing that a confidence level above 95% provides a strong assurance of data reliability and validity.
Conversely, a confidence level below 95% indicates that the sample size may be insufficient and that the data might be less reliable. In such cases, traders should approach the indicator’s recommendations with caution and consider additional factors or further analysis before making trading decisions.
How does the sample size affect the confidence level, and how does it relate to my TradingView plan?
The sample size for calculating the confidence level is directly influenced by the amount of historical data available on your charts. A larger sample size typically leads to more reliable probabilities and higher confidence levels.
Here’s how the TradingView plans affect your data access:
Essential Plan
The Essential Plan provides basic data access with a limited amount of historical data. This can lead to smaller sample sizes and lower confidence levels, which may weaken the robustness of your probability calculations. Suitable for casual traders who do not require extensive historical analysis.
Plus Plan
The Plus Plan offers more historical data than the Essential Plan, allowing for larger sample sizes and more accurate confidence levels. This enhancement improves the reliability of indicator calculations. This plan is ideal for more active traders looking to refine their strategies with better data.
Premium Plan
The Premium Plan grants access to extensive historical data, enabling the largest sample sizes and the highest confidence levels. This plan provides the most reliable data for accurate calculations, with up to 20,000 historical bars available for analysis. It is designed for serious traders who need comprehensive data for in-depth market analysis.
PRO+ Plans
The PRO+ Plans offer the most extensive historical data, allowing for the largest sample sizes and the highest confidence levels. These plans are tailored for professional traders who require advanced features and significant historical data to support their trading strategies effectively.
For many traders, the Premium Plan offers a good balance of affordability and sufficient sample size for accurate confidence levels.
What is the HTF probability table and how does it work?
The HTF (Higher Time Frame) probability table is a feature that allows you to view buy and sellside probabilities and their status from timeframes higher than your current chart timeframe.
Here’s how it works:
Data Request: The table requests and retrieves data from user-defined higher timeframes (HTFs) that you select.
Probability Display: It displays the buy and sellside probabilities for each of these HTFs, providing insights into the likelihood of price movements based on higher timeframe data.
Detailed Tooltips: The table includes detailed tooltips for each timeframe, offering additional context and explanations to help you understand the data better.
What do the different colors in the HTF probability table indicate?
The colors in the HTF probability table provide visual cues about the expected value (EV) of trading setups based on higher timeframe probabilities:
Blue: Suggests that entering a long position from the HTF user-defined pivot point, targeting buyside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Red: Indicates that entering a short position from the HTF user-defined pivot point, targeting sellside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Gray: Shows that neither long nor short trades from the HTF user-defined pivot point are expected to generate positive EV, suggesting that trading these setups may not be favorable.
What machine learning techniques are used in Quantify?
Quantify offers two main machine learning approaches:
1. Adaptive Learning (Fixed Sample Size): The algorithm learns from the entire dataset without resampling, maintaining a stable model that adapts to the latest market conditions.
2. Bootstrap Resampling: This method creates multiple subsets of the historical data, allowing the model to train on varying sample sizes. This technique enhances the robustness of predictions by ensuring that the model is not overfitting to a single dataset.
How does machine learning affect the expected value calculations in Quantify?
Machine learning plays a key role in improving the accuracy of expected value (EV) calculations. By analyzing historical price action, liquidity hits, and market bias patterns, the model continuously adjusts its understanding of risk and reward, allowing the expected value to reflect the most likely market movements. This results in more precise EV predictions, helping traders focus on setups that maximize profitability.
What is the Kelly Criterion, and how does it work in Quantify?
The Kelly Criterion is a mathematical formula used to determine the optimal position size for each trade, maximizing long-term growth while minimizing the risk of large drawdowns. It calculates the percentage of your portfolio to risk on a trade based on the probability of winning and the expected payoff.
Quantify integrates this with user-defined inputs to dynamically calculate the most effective position size in percentage, aligning with the trader’s risk tolerance and desired exposure.
How does Quantify use the Kelly Criterion in practice?
Quantify uses the Kelly Criterion to optimize position sizing based on the following factors:
1. Confidence Level: The model assesses the confidence level in the trade setup based on historical data and sample size. A higher confidence level increases the suggested position size because the trade has a higher probability of success.
2. Max Allowed Drawdown (User-Defined): Traders can set their preferred maximum allowed drawdown, which dictates how much loss is acceptable before reducing position size or stopping trading. Quantify uses this input to ensure that risk exposure aligns with the trader’s risk tolerance.
3. Probabilities: Quantify calculates the probabilities of success for each trade setup. The higher the probability of a successful trade (based on historical price action and liquidity levels), the larger the position size suggested by the Kelly Criterion.
What is a trailing stoploss, and how does it work in Quantify?
A trailing stoploss is a dynamic risk management tool that moves with the price as the market trend continues in the trader’s favor. Unlike a fixed take profit, which stays at a set level, the trailing stoploss automatically adjusts itself as the market moves, locking in profits as the price advances.
In Quantify, the trailing stoploss is enhanced by incorporating market structure liquidity levels (explain above). This ensures that the stoploss adjusts intelligently based on key price levels, allowing the trader to stay in the trade as long as the trend remains intact, while also protecting profits if the market reverses.
Why would a trader prefer a trailing stoploss based on liquidity levels instead of a fixed take-profit level?
Traders who use trailing stoplosses based on liquidity levels prefer this method because:
1. Market-Driven Flexibility: The stoploss follows the market structure rather than being static at a pre-defined level. This means the stoploss is less likely to be hit by small market fluctuations or false reversals. The stoploss remains adaptive, moving as the market moves.
2. Riding the Trend: Traders can capture more profit during a sustained trend because the trailing stop will adjust only when the trend starts to reverse significantly, based on key liquidity levels. This allows them to hold positions longer without prematurely locking in profits.
3. Avoiding Premature Exits: Fixed stoploss levels may exit a trade too early in volatile markets, while liquidity-based trailing stoploss levels respect the natural flow of price action, preventing the trader from exiting too soon during pullbacks or minor retracements.
🎲 Becoming the House: Gaining an Edge Over the Market
In American roulette, the casino has a 5.26% edge due to the presence of the 0 and 00 pockets. On even-money bets, players face a 47.37% chance of winning, while true 50/50 odds would require a 50% chance. This edge—the gap between the payout odds and the true probabilities—ensures that, statistically, the casino will always win over time, even if individual players win occasionally.
From a Trader’s Perspective
In trading, your edge comes from identifying and executing setups with a positive expected value (EV). For example:
• If you identify a setup with a 55.48% chance of winning and a 1:1 risk-to-reward (RR) ratio, your trade has a statistical advantage over a neutral (50/50) probability.
This edge works in your favor when applied consistently across a series of trades, just as the casino’s edge ensures profitability across thousands of spins.
🎰 Applying the Concept to Trading
Like casinos leverage their mathematical edge in games of chance, you can achieve long-term success in trading by focusing on setups with positive EV and managing your trades systematically. Here’s how:
1. Probability Advantage: Prioritize trades where the probability of success (win rate) exceeds the breakeven rate for your chosen risk-to-reward ratio.
• Example: With a 1:1 RR, you need a win rate above 50% to achieve positive EV.
2. Risk-to-Reward Ratio (RR): Even with a win rate below 50%, you can gain an edge by increasing your RR (e.g., a 40% win rate with a 2:1 RR still has positive EV).
3. Consistency and Discipline: Just as casinos profit by sticking to their mathematical advantage over thousands of spins, traders must rely on their edge across many trades, avoiding emotional decisions or overleveraging.
By targeting favorable probabilities and managing trades effectively, you “become the house” in your trading. This approach allows you to leverage statistical advantages to enhance your overall performance and achieve sustainable profitability.
What Makes the Quantify Indicator Original?
1. Data-Driven Edge
Unlike traditional indicators that rely on static formulas, Quantify leverages probability-based analysis and machine learning. It calculates expected value (EV) and confidence levels to help traders identify setups with a true statistical edge.
2. Integration of Market Structure
Quantify uses market structure liquidity levels to dynamically adapt. It identifies key zones like swing highs/lows and liquidity traps, enabling users to align entries and exits with where the market is most likely to react. This bridges the gap between price action analysis and quantitative trading.
3. Sophisticated Risk Management
The Kelly Criterion implementation is unique. Quantify allows traders to input their maximum allowed drawdown, dynamically adjusting risk exposure to maintain optimal position sizing. This ensures risk is scientifically controlled while maximizing potential growth.
4. Multi-Timeframe and Liquidity-Based Trailing Stops
The indicator doesn’t just suggest fixed profit-taking levels. It offers market structure-based trailing stop-loss functionality, letting traders ride trends as long as liquidity and probabilities favor the position, which is rare in most tools.
5. Customizable Bias and Adaptive Learning
• Directional Bias: Traders can set a bullish or bearish bias, and the indicator recalculates probabilities to align with the trader’s market outlook.
• Adaptive Learning: The machine learning model adapts to changes in data (via resampling or bootstrap methods), ensuring that predictions stay relevant in evolving markets.
6. Positive EV Focus
The focus on positive EV setups differentiates it from reactive indicators. It shifts trading from chasing signals to acting on setups that statistically favor profitability, akin to how professional quant funds operate.
7. User Empowerment
Through features like customizable timeframes, real-time probability updates, and visualization tools, Quantify empowers users to make data-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.
SMC Liquidity ZonesThis script implements a "Smart Money Concept (SMC) Liquidity Zones" indicator in Pine Script™ for TradingView. It helps identify key liquidity zones, detect potential order blocks, and highlight market structure breaks. The script is designed for traders who use liquidity concepts and order blocks to make informed trading decisions based on price action.
1. Indicator Overview:
The "SMC Liquidity Zones" indicator plots areas of high and low liquidity and detects potential order blocks after price breaks these zones. It also highlights market structure shifts when price moves past the liquidity zones, allowing traders to identify potential areas of price reversal or continuation.
2. Key Features:
Liquidity Zones:
Liquidity zones are regions where price is likely to experience strong reactions due to resting orders (buy or sell).
The script identifies these zones by looking for pivot highs and pivot lows using a customizable lookback period.
High Liquidity Zone: Found at pivot highs, indicating a potential zone of sell-side liquidity (where sellers may overwhelm buyers).
Low Liquidity Zone: Found at pivot lows, indicating a potential buy-side liquidity zone (where buyers may absorb selling pressure).
Order Blocks Detection:
After a liquidity zone is broken, the script marks an order block.
Order Block: An area where institutional traders (smart money) might have placed large orders, and price is expected to return to this area for liquidity.
When the price closes above the high liquidity zone, the previous high is assumed to form the order block high, while the closing price forms the order block low.
Similarly, when price closes below the low liquidity zone, the previous low is assumed to form the order block low, and the closing price forms the order block high.
Market Structure Breaks:
Bullish Market Structure Break: Occurs when price closes above the high liquidity zone, potentially signaling an upward trend.
Bearish Market Structure Break: Occurs when price closes below the low liquidity zone, signaling a potential downward trend.
The script highlights these breaks by changing the chart’s background color to green for bullish structure and red for bearish structure.
Customizable Settings:
Pivot Lookback Period: You can set the lookback period to adjust how the indicator identifies pivot highs and lows.
Visibility of Liquidity Zones and Order Blocks: The script provides options to toggle the display of liquidity zones and order blocks on or off, allowing traders to customize the chart view.
3. Code Structure:
Liquidity Zones Identification:
The script uses the ta.pivothigh() and ta.pivotlow() functions to detect pivot points over a customizable lookback period.
These pivots mark significant areas of price where liquidity might rest, and the zones are displayed using dashed lines—red for high liquidity and green for low liquidity.
Order Block Logic:
When price breaks through a liquidity zone (either above or below), the script marks an order block. This block is a potential area where price could return, creating opportunities for entries or exits.
The order block is visualized as a blue box on the chart, indicating areas where smart money may have positioned their orders.
Market Structure Break Highlights:
The background color changes based on whether the market has broken into a bullish or bearish structure:
Bullish Market Structure: Green background.
Bearish Market Structure: Red background.
This visual cue helps traders quickly assess market sentiment and potential future price direction.
4. Use Case:
This indicator is particularly suited for traders following Smart Money Concepts (SMC), liquidity-based trading, or order block strategies. It helps them:
Identify potential price reaction zones (liquidity zones).
Spot order blocks, which are areas where institutional traders are likely to have placed large orders.
Recognize market structure shifts, signaling potential trend reversals or continuations.
Highlight trading opportunities based on liquidity breaks and market structure changes.
ICT Judas Swing | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Judas Swing Indicator! This indicator is built around the ICT's "Judas Swing" strategy. The strategy looks for a liquidity grab around NY 9:30 session and a Fair Value Gap for entry confirmation. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Judas Swing :
Implementation of ICT's Judas Swing Strategy
2 Different TP / SL Methods
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The strategy begins by identifying the New York session from 9:30 to 9:45 and marking recent liquidity zones. These liquidity zones are determined by locating high and low pivot points: buyside liquidity zones are identified using high pivots that haven't been invalidated, while sellside liquidity zones are found using low pivots. A break of either buyside or sellside liquidity must occur during the 9:30-9:45 session, which is interpreted as a liquidity grab by smart money. The strategy assumes that after this liquidity grab, the price will reverse and move in the opposite direction. For entry confirmation, a fair value gap (FVG) in the opposite direction of the liquidity grab is required. A buyside liquidity grab calls for a bearish FVG, while a sellside grab requires a bullish FVG. Based on the type of FVG—bullish for buys and bearish for sells—the indicator will then generate a Buy or Sell signal.
After the Buy or Sell signal, the indicator immediately draws the take-profit (TP) and stop-loss (SL) targets. The indicator has three different TP & SL modes, explained in the "Settings" section of this write-up.
You can set up alerts for entry and TP & SL signals, and also check the current performance of the indicator and adjust the settings accordingly to the current ticker using the backtesting dashboard.
🚩 UNIQUENESS
This indicator is an all-in-one suit for the ICT's Judas Swing concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. Different and customizable algorithm modes will help the trader fine-tune the indicator for the asset they are currently trading. Three different TP / SL modes are available to suit your needs. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️ SETTINGS
1. General Configuration
Swing Length -> The swing length for pivot detection. Higher settings will result in
FVG Detection Sensitivity -> You may select between Low, Normal, High or Extreme FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
2. TP / SL
TP / SL Method ->
a) Dynamic: The TP / SL zones will be auto-determined by the algorithm based on the Average True Range (ATR) of the current ticker.
b) Fixed : You can adjust the exact TP / SL ratios from the settings below.
Dynamic Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
Change in State of Delivery (CISD) [LuxAlgo]The Change In State Of Delivery (CISD) indicator detects and displays Change in State Of Delivery, a concept related to market structures.
Users can choose between two different CISD detection methods. Various filtering options are also included to filter out less significant CISDs.
🔶 USAGE
A Change in State of Delivery (CISD) is a concept closely related to market structures, where price breaks a level of interest, confirming trends and their continuations from the resulting breakouts.
Unlike more traditional market structures which rely on swing points, CISDs rely on a persistent sequence of candles, using the sequence extremes as breakout levels.
CISDs are detected as follows:
Bullish: The price closes above the opening price of the first candle in a sequence of bearish candles (or its own opening price if it's the only candle).
Bearish: The price closes below the opening price of the first candle in a sequence of bullish candles (or its own opening price if it's the only candle).
If a newly detected CISD aligns with the indicator's current established trend, this confirms a trend continuation (represented with a dashed line).
On the other hand, if a newly detected CISD is in the opposite direction to the detected trend it can confirm a trend reversal (represented with a solid line).
🔹 Liquidity Sweep Detection Method
Using Liquidity Sweeps to update CISD breakout levels allows us to obtain less frequent and more relevant levels that are less sensitive to noisy price variations.
Sweeps are obtained from detected Swing Points , with a higher Swing Length allowing us to obtain longer-term swing levels and potentially more detected sweeps from a specific level over time.
Note: The 'Swing Length' setting is only applicable on the Liquidity Sweep Detection Method and will only change the Liquidity levels.
A Liquidity Sweep is valid when the price reaches an important liquidity level , after which the price closes below/above this level.
Bullish scenario: The price goes below a previous unbroken Swing Low but closes above.
Bearish scenario: The price goes above a previous unbroken Swing High but closes below.
After a Liquidity Sweep has been detected, the last level of importance acts as support/resistance . Breaking this level in the other direction changes the state of delivery .
Users must keep observing the price and significant levels, as highlighted by the white rectangle in the above example.
🔹 CISD Filtering
Users can adjust the following two settings:
Minimum CISD Duration: The minimum length of the 'CISD' line
Maximum Swing Validity: The maximum length of the 'CISD' line; potential CISD lines that aren't broken are deleted when exceeding the limit.
The chart can get cluttered when the Minimum CISD Duration is low. Users could focus on a switch in trend (first solid line CISD ), where the following dashed CISD lines can be seen as extra opportunities/confirmations.
🔶 DETAIL
🔹 Using Different Timeframes
When an important liquidity level (Previous Swing high/low, FVG, etc.) is reached on the higher timeframe, the user can move to a lower timeframe to check whether there is a CISD .
Above example:
The high of the last candle breaches a liquidity level (previous Swing High). The opening price of the last candle acts as a trigger/confirmation level.
A confirmed CISD is seen in a lower timeframe, just after this Liquidity Sweep. This could be an early opportunity.
Later, a confirmed CISD on the higher timeframe is established.
🔶 SETTINGS
Detection Method: Classic or Liquidity Sweep
Swing Length: Period used for the swing detection, with higher values returning longer-term Swing Levels.
Minimum CISD Duration: The minimum length of the CISD line
Maximum Swing Validity: The maximum length of the CISD line; potential CISD lines that aren't broken are deleted when exceeding the limit.
ICT Turtle Soup | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Turtle Soup Indicator! This indicator is built around the ICT "Turtle Soup" model. The strategy has 5 steps for execution which are described in this write-up. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Turtle Soup Indicator :
Implementation of ICT's Turtle Soup Strategy
Adaptive Entry Method
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The ICT Turtle Soup strategy may have different implementations depending on the selected method of the trader. This indicator's implementation is described as :
1. Mark higher timerame liquidity zones.
Liquidity zones are where a lot of market orders sit in the chart. They are usually formed from the long / short position holders' "liquidity" levels. There are various ways to find them, most common one being drawing them on the latest high & low pivot points in the chart, which this indicator does.
2. Mark current timeframe market structure.
The market structure is the current flow of the market. It tells you if the market is trending right now, and the way it's trending towards. It's formed from swing higs, swing lows and support / resistance levels.
3. Wait for market to make a liquidity grab on the higher timeframe liquidity zone.
A liquidity grab is when the marked liquidity zones have a false breakout, which means that it gets broken for a brief amount of time, but then price falls back to it's previous position.
4. Buyside liquidity grabs are "Short" entries and Sellside liquidity grabs are "Long" entries by default.
5. Wait for the market-structure shift in the current timeframe for entry confirmation.
A market-structure shift happens when the current market structure changes, usually when a new swing high / swing low is formed. This indicator uses it as a confirmation for position entry as it gives an insight of the new trend of the market.
6. Place Take-Profit and Stop-Loss levels according to the risk ratio.
This indicator uses "Average True Range" when placing the stop-loss & take-profit levels. Average True Range calculates the average size of a candle and the indicator places the stop-loss level using ATR times the risk setting determined by the user, then places the take-profit level trying to keep a minimum of 1:1 risk-reward ratio.
This indicator follows these steps and inform you step by step by plotting them in your chart.
🚩UNIQUENESS
This indicator is an all-in-one suit for the ICT's Turtle Soup concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. It's designed for simplyfing a rather complex strategy, helping you to execute it with clean signals. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️SETTINGS
1. General Configuration
MSS Swing Length -> The swing length when finding liquidity zones for market structure-shift detection.
Higher Timeframe -> The higher timeframe to look for liquidity grabs. This timeframe setting must be higher than the current chart's timeframe for the indicator to work.
Breakout Method -> If "Wick" is selected, a bar wick will be enough to confirm a market structure-shift. If "Close" is selected, the bar must close above / below the liquidity zone to confirm a market structure-shift.
Entry Method ->
"Classic" : Works as described on the "HOW DOES IT WORK" section.
"Adaptive" : When "Adaptive" is selected, the entry conditions may chance depending on the current performance of the indicator. It saves the entry conditions and the performance of the past entries, then for the new entries it checks if it predicted the liquidity grabs correctly with the current setup, if so, continues with the same logic. If not, it changes behaviour to reverse the entries from long / short to short / long.
2. TP / SL
TP / SL Method -> If "Fixed" is selected, you can adjust the TP / SL ratios from the settings below. If "Dynamic" is selected, the TP / SL zones will be auto-determined by the algorithm.
Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
Global Liquidity IndexThe Global Liquidity Index offers a consolidated view of all major central bank balance sheets from around the world. For consistency and ease of comparison, all values are converted to USD using their relevant forex rates and are expressed in trillions. The indicator incorporates specific US accounts such as the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP), both of which are subtracted from the Federal Reserve's balance sheet to give a more nuanced view of US liquidity. Users have the flexibility to enable or disable specific central banks and special accounts based on their preference. Only central banks that both don’t engage in currency pegging and have reliable data available from late 2007 onwards are included in this aggregated liquidity model.
Global Liquidity Index = Federal Reserve System (FED) - Treasury General Account (TGA) - Reverse Repurchase Agreements (RRP) + European Central Bank (ECB) + People's Bank of China (PBC) + Bank of Japan (BOJ) + Bank of England (BOE) + Bank of Canada (BOC) + Reserve Bank of Australia (RBA) + Reserve Bank of India (RBI) + Swiss National Bank (SNB) + Central Bank of the Russian Federation (CBR) + Central Bank of Brazil (BCB) + Bank of Korea (BOK) + Reserve Bank of New Zealand (RBNZ) + Sweden's Central Bank (Riksbank) + Central Bank of Malaysia (BNM).
This tool is beneficial for anyone seeking to get a snapshot of global liquidity to interpret macroeconomic trends. By examining these balance sheets, users can deduce policy trajectories and evaluate the global economic climate. It also offers insights into asset pricing and assists investors in making informed capital allocation decisions. Historically, riskier assets, such as small caps and cryptocurrencies, have typically performed well during periods of rising liquidity. Thus, it may be prudent for investors to avoid additional risk unless there's a consistent upward trend in global liquidity.
M2 Liqudity WaveGlobal Liquidity Wave Indicator (M2-Based)
The Global Liquidity Wave Indicator is designed to track and visualize the impact of global M2 liquidity on risk assets—especially those highly correlated to monetary expansion, like Bitcoin, MSTR, and other macro-sensitive equities.
Key features include:
Leading Signal: Historically leads Bitcoin price action by approximately 70 days, offering traders and analysts a forward-looking edge.
Wave-Based Projection: Visualizes a "probability cloud"—a smoothed band representing the most likely trajectory for Bitcoin based on changes in global liquidity.
Min/Max Offset Controls: Adjustable offsets let you define the range of lookahead windows to shape the wave and better capture liquidity-driven inflection points.
Explicit Offset Visualization: Option to manually specify an exact offset to fine-tune the overlay, ideal for testing hypotheses or aligning with macro narratives.
Macro Alignment: Particularly effective for assets with high sensitivity to global monetary policy and liquidity cycles.
This tool is not just a chart overlay—it's a lens into the liquidity engine behind the market, helping anticipate directional bias in advance of price moves.
How to use?
- Enable the indicator for BTCUSD.
- Set Offset Range Start and End to 70 and 115 days
- Set Specific Offset to 78 days (this can change so you'll need to play around)
FAQ
Why a global liquidity wave?
The global liquidity wave accounts for variability in how much global liquidity affects an underlying asset. Think of the Global Liquidity Wave as an area that tracks the most probable path of Bitcoin, MSTR, etc. based on the total global liquidity.
Why the offset?
Global liquidity takes time to make its way into assets such as #Bitcoin, Strategy, etc. and there can be many reasons for that. It's never a specific number of days of offset, which is why a global liquidity wave is helpful in tracking probable paths for highly correlated risk assets.
One Shot One Kill ICT [TradingFinder] Liquidity MMXM + CISD OTE🔵 Introduction
The One Shot One Kill trading setup is one of the most advanced methods in the field of Smart Money Concept (SMC) and ICT. Designed with a focus on concepts such as Liquidity Hunt, Discount Market, and Premium Market, this strategy emphasizes precise Price Action analysis and market structure shifts. It enables traders to identify key entry and exit points using a structured Trading Model.
The core process of this setup begins with a Liquidity Hunt. Initially, the price targets areas like the Previous Day High and Previous Day Low to absorb liquidity. Once the Change in State of Delivery(CISD)is broken, the market structure shifts, signaling readiness for trade entry. At this stage, Fibonacci retracement levels are drawn, and the trader enters a position as the price retraces to the 0.618 Fibonacci level.
Part of the Smart Money approach, this setup combines liquidity analysis with technical tools, creating an opportunity for traders to enter high-accuracy trades. By following this setup, traders can identify critical market moves and capitalize on reversal points effectively.
Bullish :
Bearish :
🔵 How to Use
The One Shot One Kill setup is a structured and advanced trading strategy based on Liquidity Hunt, Fibonacci retracement, and market structure shifts (CISD). With a focus on precise Price Action analysis, this setup helps traders identify key market movements and plan optimal trade entries and exits. It operates in two scenarios: Bullish and Bearish, each with distinct steps.
🟣 Bullish One Shot One Kill
In the Bullish scenario, the process starts with the price moving toward the Previous Day Low, where liquidity is absorbed. At this stage, retail sellers are trapped as they enter short trades at lower levels. Following this, the market reverses upward and breaks the CISD, signaling a shift in market structure toward bullishness.
Once this shift is identified, traders draw Fibonacci levels from the lowest point to the highest point of the move. When the price retraces to the 0.618 Fibonacci level, conditions for a buy position are met. The target for this trade is typically the Previous Day High or other significant liquidity zones where major buyers are positioned, offering a high probability of price reversal.
🟣 Bearish One Shot One Kill
In the Bearish scenario, the price initially moves toward the Previous Day High to absorb liquidity. Retail buyers are trapped as they enter long trades near the highs. After the liquidity hunt, the market reverses downward, breaking the CISD, which signals a bearish shift in market structure. Following this confirmation, Fibonacci levels are drawn from the highest point to the lowest point of the move.
When the price retraces to the 0.618 Fibonacci level, a sell position is initiated. The target for this trade is usually the Previous Day Low or other key liquidity zones where major sellers are active.
This setup provides a precise and logical framework for traders to identify market movements and enter trades at critical reversal points.
🔵 Settings
🟣 CISD Logical settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
🟣 LIQUIDITY Logical 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.
🟣 CISD Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 LIQUIDITY Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🔵 Conclusion
The One Shot One Kill setup is one of the most effective and well-structured trading strategies for identifying and capitalizing on key market movements. By incorporating concepts such as Liquidity Hunt, CISD, and Fibonacci retracement, this setup allows traders to enter trades with high precision at optimal points.
The strategy emphasizes detailed Price Action analysis and the identification of Smart Money behavior, helping traders to execute successful trades against the general market trend.
With a focus on identifying liquidity in the Previous Day High and Low and aligning it with Fibonacci retracement levels, this setup provides a robust framework for entering both bullish and bearish trades.
The combination of liquidity analysis and Fibonacci retracement at the 0.618 level enables traders to minimize risk and exploit major market moves effectively.
Ultimately, success with the One Shot One Kill setup requires practice, patience, and strict adherence to its rules. By mastering its concepts and focusing on high-probability setups, traders can enhance their decision-making skills and build a sustainable and professional trading approach.
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.
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Follow Through Day (FTD) + Sweep [TrendX_]The Follow Through Day (FTD) + Sweep indicator is a Trend-following tool mixing William O'Neil's original FTD concept and Liquidity concept. This indicator helps you identify potential subsequent bullish trends with greater precision by combining volume analysis, price action, and liquidity concepts.
💎 FEATURES
Follow Through Day Candle (FTD Candle)
The FTD, pioneered by William O'Neil, serves as a reliable signal for identifying the beginning of new bull markets. It's particularly valuable because it combines multiple market factors - price action, volume, and timing - to confirm genuine market reversals rather than temporary bounces.
The power of the FTD lies in its ability to distinguish between ordinary market fluctuations and significant trend changes. By requiring specific criteria to be met across multiple sessions, it helps filter out false signals and identifies high-probability reversal points where institutional investors are likely beginning to accumulate positions.
Sweep Area
The Sweep area feature enhances the traditional FTD concept by incorporating modern liquidity analysis. This overlay identifies zones where large market participants are likely to trigger stop losses before continuing the trend. These areas often represent optimal entry points for traders looking to join the new uptrend with reduced risk.
🔎 BREAKDOWN
FTD Candle
The FTD formation process occurs in two distinct phases: Setup and Completion.
Setup Phase
Strong Market Decline
The market must first experience a significant downtrend
This selling pressure helps clear out weak hands and creates oversold conditions
The decline creates the potential energy for a powerful reversal
First Recovery Session
Marks the initial sign of buying pressure emerging
Often characterized by a strong reversal candle
Represents the first indication that selling pressure may be exhausting
Recovery Confirmation
The second and third days must maintain prices above the new pivot low
This consolidation period helps confirm the validity of the initial bounce
Shows that sellers are no longer in control of price action
Completion Phase:
Supply Test Session
Low volume indicates diminishing selling pressure
Price remains above the pivot low
Creates the foundation for institutional buyers to begin accumulating
Breakout Day
Price increase exceeds average profit of bullish candles
Volume increases by at least 15% compared to previous session
Shows strong institutional commitment to the new uptrend
Timing Window
Must occur between the 4th and 8th candle after First Recovery Session
This specific timing helps confirm the sustainability of the reversal
Based on O'Neil's research of historical market bottoms
FTD Sweep
The Post-FTD Phase introduces the Sweep concept, which is crucial for understanding how large market participants operate. This feature leverages the liquidity concept because institutional traders often need to trigger stop losses to accumulate larger positions at better prices. This helps:
Create liquidity pools for large position entries
Shake out weak hands before continuing the trend
Test the strength of the new trend by absorbing selling pressure
⚙️ USAGE
Sweep + TP & SL Strategy
Example: BTCUSDT (1D) - Replay back to 9th November 2024
After an FTD candle forms, traders can adopt a systematic approach to enhance their trading strategy. First, they should determine the swing range and convert the post-FTD zone into concrete stop loss and take profit levels, which are based on the price action during the FTD formation. Next, traders should wait for a sweep formation, as this indicates that institutional players are accumulating positions. A quick price rejection from the sweep level should be observed before executing an entry.
The reasoning behind this strategy is rooted in market microstructure. By waiting for the sweep, traders position themselves alongside institutional players who need to build large positions without causing adverse price movement. The sweep creates the liquidity they need, and the subsequent move often represents the true trend continuation.
DISCLAIMER
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur. Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Hourly Trading System (Zeiierman)█ Overview
The Hourly Trading System (Zeiierman) is designed to enhance your trading by highlighting critical price levels and trends on an hourly basis. This indicator plots the open prices of hourly and 4-hour candles, visualizes retests, displays average price lines, and overlays higher timeframe candlesticks. It is particularly beneficial for intraday traders seeking to capitalize on short-term price movements and volume patterns.
█ How It Works
This indicator works by plotting significant price levels and zones based on hourly and 4-hour candle opens. It also includes functionalities for identifying retests of these levels, calculating and displaying average prices, and showing high and low labels for each hour.
█ Timeframe
The Hourly Trading System is designed to be used on the 1-minute or 5-minute timeframe. This system is tailored for intraday trading, allowing traders to find optimal entries around hourly opening levels and providing an easy method to identify the hourly trend. It works effectively on any market.
█ How to Use
Trend Analysis
Quickly gauge where the current price stands relative to key hourly and 4-hour levels. The plotted lines and zones serve as potential support and resistance areas, helping traders identify crucial points for entry or exit.
Utilize the 1-hour average and higher timeframe candles to understand the overall market trend. Aligning intraday strategies with larger trends can enhance trading decisions.
Use the bar coloring to quickly gauge the 1-hour trend on a lower timeframe. The bar colors indicate whether the hourly trend is bullish (green) or bearish (red), helping traders make quicker decisions in alignment with the overall trend.
Retest Identification
Enable retest signals to see where the price retested the hourly open levels. These retest points often signal strong price reactions, offering opportunities for trades based on support/resistance flips.
One effective strategy to incorporate is looking for price flips when a new hour starts. This approach involves monitoring price action at the beginning of each hour. If the price breaks and retests the hourly open level with strong momentum, it could indicate a potential trend reversal or continuation. This strategy is effective in volatile markets where price movements are significant at the start of each new hour.
Liquidity Sweep Strategy
Another common and effective strategy is the liquidity sweep. This involves identifying key levels where liquidity is likely to accumulate, such as previous hour highs and lows, and observing how the price interacts with these price levels. When the price sweeps through these levels, triggering stop-loss orders or pending orders, it often results in a sharp price movement followed by a reversal. Traders can capitalize on these movements by entering trades in the direction of the reversal once the liquidity sweep has occurred.
Equal Highs and Lows Strategy
The Equal Highs and Lows strategy leverages the concept of identifying levels where the price forms multiple highs or lows at the same level over different hourly periods. These equal highs and lows often indicate strong support or resistance levels where liquidity is accumulated. When the price approaches these levels, it is likely to trigger stop-loss orders and lead to significant price movements. Traders can look for breakouts or reversals around these levels to enter trades with higher probability setups.
█ Settings
Zone Width: Specifies the width of the zone around the 1-Hour Open as a percentage. Adjust this to widen or narrow the zone.
Show Retests: Enables or disables the display of retest markers. Retest markers show where the price has retested the 1-Hour Open line.
Number of Retests: Sets the number of retests to display. Adjust this to see more or fewer retest markers.
Volume Filter: Enables or disables the volume filter for retests. Use this to highlight retests with significant volume.
Volume Filter Length: Sets the length of the volume filter, smoothing the volume data to reduce noise.
1-Hour Average Line: Enables or disables the 1-hour average price line. This line shows the average price over the past hour.
Hourly High & Low Labels: Enables or disables the display of hourly high and low labels, marking the highest and lowest prices within each hour.
Candlesticks: Enables or disables the display of candlesticks on the chart, providing a detailed view of price action.
Bar Color: Enables or disables bar coloring based on price direction, with up bars in green and down bars in red.
Timeframe: Sets the timeframe for higher timeframe candles. Adjust this to match the period you want to analyze.
Number of Candles: Sets the number of higher timeframe candles to display. Increase this to see more candles on the chart.
Location: Sets the location for higher timeframe candles, allowing you to position them left or right on the chart.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Global Liquidity Index (Candles)The Global Liquidity Index (Candles) provides a comprehensive overview of major central bank balance sheets worldwide, presenting values converted to USD for consistency and comparability, following relevant forex rates. This indicator, based on the code developed by user ingeforberg , incorporates essential US accounts including the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP), subtracted from the Federal Reserve's balance sheet to offer a nuanced perspective on US liquidity. Users can tailor their analysis by selectively enabling or disabling specific central banks and special accounts according to their preferences. The index exclusively includes central banks abstaining from currency pegging and with reliable data accessible since late 2007, ensuring a robust aggregated liquidity model.
The calculation of the Global Liquidity Index involves subtracting the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP) from the Federal Reserve System (FED) and adding the balance sheets of major central banks worldwide: the European Central Bank (ECB), the People's Bank of China (PBC), the Bank of Japan (BOJ), the Bank of England (BOE), the Bank of Canada (BOC), the Reserve Bank of Australia (RBA), the Reserve Bank of India (RBI), the Swiss National Bank (SNB), the Central Bank of the Russian Federation (CBR), the Central Bank of Brazil (BCB), the Bank of Korea (BOK), the Reserve Bank of New Zealand (RBNZ), Sweden's Central Bank (Riksbank), and the Central Bank of Malaysia (BNM).
This tool proves invaluable for individuals seeking a consolidated perspective on global liquidity to interpret macroeconomic trends. Analyzing these balance sheets enables users to discern policy trajectories and assess the global economic landscape, providing insights into asset pricing and assisting investors in making well-informed capital allocation decisions. Historically, assets perceived as riskier, such as small caps and cryptocurrencies, have tended to perform favorably during periods of escalating liquidity. Thus, investors may exercise caution regarding additional risk exposure unless a sustained upward trend in global liquidity is evident.
Main differences between the original and updated indicators:
The "Global Liquidity Index (Candles)" script, compared to the original "Global Liquidity Index" script, offers a more detailed and visually rich representation of liquidity data.
"Global Liquidity Index (Candles)" employs candlestick visualization to represent liquidity data. Each candlestick encapsulates open, high, low, and close prices over a given period. This format provides granular insights into liquidity fluctuations, facilitating a more nuanced analysis.
By using candlesticks, the script offers traders detailed information about liquidity dynamics. They can analyze the patterns formed by candlesticks to discern trends, reversals, and market sentiment shifts, aiding in making informed trading decisions.
Crypto USD LiquidityThe "Crypto USD Liquidity " indicator is designed to offer a comprehensive analysis of liquidity dynamics within the cryptocurrency market, specifically focusing on various stablecoins. This versatile tool allows users to tailor their analysis by adjusting key parameters such as the Rate of Change (ROC) length and the smoothing rate.
The indicator incorporates a user-friendly interface with options to selectively display the supply data for major stablecoins, including USDT, BUSD, USDC, DAI, and TUSD . Users can toggle these options to observe and compare the liquidity trends of different stablecoin assets.
The total liquidity is computed as the summation of the selected stablecoin supplies, providing a holistic view of the overall crypto market liquidity. The Rate of Change (ROC) and its smoothing are then applied to the aggregated liquidity data. This process helps users identify trends and potential turning points in the liquidity landscape.
The visual representation on the chart includes a color-coded display: positive changing ROC values are shaded in green, indicating potential increases in liquidity, while negative values are shaded in red, suggesting potential decreases. This color scheme enhances the user's ability to quickly interpret the changing dynamics of stablecoin liquidity.
Moreover, the script includes a Zero Line for reference and overlays the raw ROC values for additional insight. The resulting chart not only serves as a powerful analytical tool for traders and investors but also contributes to a deeper understanding of the nuanced movements within the broader cryptocurrency market.
In summary, the "Crypto USD Liquidity" Pine Script indicator empowers users with a customizable and visually informative tool for analyzing and interpreting the complex dynamics of stablecoin liquidity, facilitating more informed decision-making in the realm of cryptocurrency trading and investment.
Сoncentrated Market Maker Strategy by oxowlConcentrated Market Maker Strategy by oxowl. This script plots an upper and lower bound for liquidity provision, and checks for rebalancing conditions. It also includes alert conditions for when the price crosses the upper or lower bounds.
Here's an overview of the script:
It defines the input parameters: liquidity range percentage, rebalance frequency in minutes, and minimum trade size in assets.
It calculates the upper and lower bounds for liquidity provision based on the liquidity range percentage.
It initializes variables for the last rebalance time and price.
It defines a rebalance condition based on the frequency and current price within the specified range.
If the rebalance condition is met, it updates the last rebalance time and price.
It plots the upper and lower bounds on the chart as lines and adds price labels for both bounds.
It defines alert conditions for when the price crosses the upper or lower bounds.
Finally, it creates alert conditions with appropriate messages for when the price crosses the upper or lower bounds.
Concentrated liquidity is a concept often used in decentralized finance (DeFi) market-making strategies. It allows liquidity providers (LPs) to focus their liquidity within a specific price range, rather than across the entire price curve. Using an indicator with concentrated liquidity can offer several advantages:
Increased capital efficiency: Concentrated liquidity allows LPs to allocate their capital within a narrower price range. This means that the same amount of capital can generate more significant price impact and potentially higher returns compared to providing liquidity across a broader range.
Customized risk exposure: LPs can choose the price range they feel most comfortable with, allowing them to better manage their risk exposure. By selecting a range based on their market outlook, they can optimize their positions to maximize potential returns.
Adaptive strategies: Indicators that support concentrated liquidity can help traders adapt their strategies based on market conditions. For example, they can choose to provide liquidity around a stable price range during low-volatility periods or adjust their range when market conditions change.
To continue integrating this script into your trading strategy, follow these steps:
Import the script into your TradingView account. Navigate to the Pine editor, paste the code, and save it as a new script.
Apply the indicator to a trading pair chart. You can customize the input parameters (liquidity range percentage, rebalance frequency, and minimum trade size) based on your preferences and risk tolerance.
Set alerts for when the price crosses the upper or lower bounds. This will notify you when it's time to take action, such as adding or removing liquidity, or rebalancing your position.
Monitor the performance of your strategy over time. Adjust the input parameters as needed to optimize your returns and manage risk effectively.
(Optional) Integrate the script with a trading bot or automation platform. If you're using an API-based trading solution, you can incorporate the logic and conditions from the script into your bot's algorithm to automate the process of providing concentrated liquidity and rebalancing your positions.
Remember that no strategy is foolproof, and past performance is not indicative of future results. Always exercise caution when trading and carefully consider your risk tolerance.
BTC Regime Phase [HY|YC|GLI]The correlation between global liquidity and INDEX:BTCUSD has attracted a lot of attention. Building on this insight, I developed an indicator that not only tracks global liquidity but also integrates the high‑yield spread and yield‑curve slope to capture credit risk and growth expectations.
Essence and Logic
At its core, the Risk‑On Composite Z‑Score converts three macro factors global liquidity momentum, the US high‑yield spread and the slope of the US yield curve into standardized Z‑scores, weights them, and tracks moving‑average crossovers. Each factor has a rationale: high‑yield spreads are powerful business‑cycle indicators and often outperform other financial variables (Gertler & Lown, 2000). Yield‑curve steepness reflects investor optimism and prompts shifts toward riskier assets global liquidity drives cross‑border flows and risk sentiment (Goldberg, 2023; Lee, 2024). Combining these measures gives a composite signal that has historically aligned well with Bitcoin’s tops and bottoms. Usable also for other crypto coins: INDEX:ETHUSD CRYPTO:SOLUSD CRYPTO:LINKUSD
Limitations and My Current Model Outlook
I want to be transparent: the three model sections are highly correlated. Currently, the high‑yield spread and yield curve data come only from the US; I may add Euro or Japanese spreads later. I’m also aware that macro dynamics are evolving. Fiscal policy and political choices could shorten bear markets and make the current sell signals less relevant. In a stagflationary world, inflation‑adjusted liquidity may swing more violently and require an asset‑inflation adjustment. Yet, the model has captured Bitcoin’s tops and bottoms almost to the week—future patterns may rhyme, not repeat.
Questions and Ideas:
Do you think this model will still be useful as fiscal and monetary regimes shift?
Should I add a stagnation modulation perhaps real yields or inflation‑adjusted liquidity—to better capture a stagflation scenario?
Are there high‑yield spreads on TV beyond the US that I should include? (Euro and Japan indices do exist.)
Would it make sense to incorporate Bitcoin halving events or a stock‑to‑flow module?
The indicator is free to use. If it brings you value, you’re welcome to follow for updates. I appreciate your support and feedback. When you are interested in the source code, feel free to contact me for more details. When you feel like supporting me with some sats, contact me and I will give you a Lightning address. I am a student and that would help a lot – but please only if you can afford it!
♡ Thanks to everyone who contributes insight on TradingView ♡
© Robinhodl21
Features: Users can enable or disable each component, adjust weights and choose a short‑tenor (1‑year or 2‑year) for the yield curve. The script automatically scales lookback windows based on the chart timeframe (daily, weekly or monthly). It offers visual plots of each Z‑score, the composite score, and smoothed moving averages, with background colours highlighting regimes and markers for entries and exits. Trade logic includes optional dip‑buy triggers when the composite falls below a threshold, Friday‑only execution on daily charts to reduce whipsaws. A trend table summarises current Z‑scores and their trends. Settings are tuned for BTC weekly data but should be adjusted for other assets or timeframes. Because some inputs (e.g., GLI weights) have limited historical data, long backtests may be less reliable when using on other Risk On Assets like NASDAQ:NDX NCDEX:COPPER
‼ Disclaimer: This indicator is for educational purposes and does not constitute investment advice. Markets involve risk; past performance is not indicative of future results. Users should not rely solely on this script for trading decisions. Always test and adapt settings to your asset, timeframe and risk tolerance. The author assumes no liability for any trading losses.
Literature:
Gertler, M., & Lown, C. S. (2000). The information in the high yield bond spread for the business cycle: Evidence and some implications. NBER Working Paper 7549.
Lee, B. (2024). Staying ahead of the yield curve. CME Group.
McCauley, R. N. (2012). Risk‑on/risk‑off, capital flows, leverage and safe assets. BIS Working Paper 382.
Goldberg, L. (2023). Global liquidity: Drivers, volatility and toolkits. Federal Reserve Bank of New York Staff Report 1064.
FRED (2025). ICE BofA Euro High Yield Index Option‑Adjusted Spread (BAMLHE00EHYIOAS). St. Louis Fed Data.
Office of Financial Research (2025). Financial Stress Index sources: High yield indices..
Tashev, T. (2025). The Bitcoin Stock‑to‑Flow Model: A comprehensive guide. Webopedia.
Golden Sweep - ZTFGolden Sweep - ZTF: Multi-Confluence Reversal Detection System
Purpose & Methodology:
The Golden Sweep combines six distinct market structure analysis methods into a unified confluence system designed to identify high-probability reversal points at inverse Fair Value Gaps (iFVGs). Rather than relying on single-indicator signals, this system requires simultaneous confirmation across multiple independent market dimensions to filter out noise and reduce false signals.
Core Logic & Technical Approach:
1. Fair Value Gap Analysis Foundation
The system begins by detecting standard Fair Value Gaps (price inefficiencies where gaps exist between candle wicks) and monitors when price returns to fill these gaps, creating inverse FVGs. This forms the base signal trigger.
2. Liquidity Sweep Confirmation Engine
Uses pivot-based swing detection to identify when price has recently swept through key support/resistance levels, indicating stop-loss hunting activity. The algorithm tracks recent liquidity events within a configurable lookback period and correlates them with iFVG formations.
3. VWAP Statistical Positioning
Calculates real-time Volume Weighted Average Price with standard deviation bands. Signals are only validated when price is positioned at statistically significant VWAP deviations (configurable zones), ensuring alignment with institutional flow patterns.
4. Balanced Price Range (BPR) Structure Analysis
Detects overlapping bullish and bearish Fair Value Gaps that create consolidation zones. The system identifies when new iFVGs form within or near these balanced ranges, indicating potential breakout reversals from established accumulation/distribution areas.
5. Turtle Soup Reversal Pattern Recognition
Implements Larry Connors' turtle soup methodology to detect false breakouts. Identifies when price penetrates recent highs/lows but closes back within the prior range, indicating failed breakout attempts that often precede strong reversals.
6. Exhaustion Signal Detection
Employs dual-timeframe momentum analysis using Williams %R methodology with optimized smoothing parameters. Detects overbought/oversold exhaustion conditions and confirms when momentum shifts from extreme readings back toward equilibrium, indicating potential trend exhaustion reversals.
Confluence Requirement Logic:
A Golden Sweep signal only triggers when ALL enabled filters simultaneously confirm within their respective lookback periods. This six-dimensional approach significantly reduces signal frequency while increasing reliability by ensuring multiple market forces align before generating alerts.
Session & Timing Integration:
Incorporates session-based filtering to account for varying market dynamics across trading sessions (NY Open, London Close, etc.), as different sessions exhibit distinct liquidity and volatility characteristics.
Implementation Notes:
All calculations use confirmed bar data to prevent repainting
Configurable lookback periods allow adaptation to different timeframes and market conditions
Visual overlays are optional and independent of signal generation logic
Built-in risk management through signal rarity and confluence requirements
This systematic approach addresses the common problem of indicator overload by creating a structured framework where multiple analysis methods must agree before signaling, resulting in fewer but higher-quality trade opportunities.
⚠️ Disclaimer: This indicator is for educational purposes only. It does not constitute financial advice or a recommendation to buy or sell any security. Trading involves risk — always do your own research and use proper risk management.
Smart Money Trap Scanner [TradingFinder]🔵 Introduction
In many market conditions, what initially seems to be a decisive breakout often turns out to be nothing more than a false breakout or fake move. Price breaks through a significant structural level, such as a swing high or low or a key support and resistance zone, only to quickly return to its previous range. These moves, often driven by liquidity traps or market manipulation, typically signal structural weakness rather than the start of a new trend.
This screener is specifically designed to detect such situations. It focuses on identifying false breakouts and price returns to broken levels within a defined time window, and then looks for retracements into the Fibonacci zone. If price reenters the 0.618 to 1.0 retracement area and aligns with the time-based filters, the system flags a low-risk, high-probability entry opportunity.
To enhance the precision of signal detection, the screener categorizes setups into two distinct types based on the speed of the price reaction after a breakout. Type A signals occur when the price breaks a level and immediately returns to break-even within the very next candle indicating a sharp rejection and rapid invalidation of the breakout. In contrast, Type B signals involve a more gradual return to the broken level, typically taking between two to five candles. This differentiation allows traders to better assess the context and urgency of each trap, providing a clearer understanding of momentum and liquidity behavior behind the move.
Additionally, the screener includes a Signal Age feature, which displays how much time has passed since the last valid signal was generated. This allows traders to quickly assess signal freshness and avoid acting on outdated setups, especially in fast-moving market environments.
One of the key advantages of this tool is its ability to simultaneously scan multiple symbols and timeframes. It only triggers an alert when all conditions false breakout, structural return, and Fibonacci alignment are met. This allows traders to bypass the need for manually reviewing dozens of charts and instead concentrate on clean, valid, and structure-based setups with greater precision.
🔵 How to Use
This tool operates as a structure-based screener that continuously scans various symbols and timeframes. By combining price behavior analysis, structural breakout detection, and Fibonacci retracement zones, it only signals entries when the probability of reversal is significantly supported by liquidity logic and price correction depth.
The system doesn’t just monitor price movements beyond key levels like swing highs or lows. It also evaluates whether the move quickly reverses and absorbs liquidity. If so, Fibonacci is applied to measure the depth of the pullback and identify the most favorable entry zones.
🟣 Long Signal
A long setup is triggered when price temporarily breaks below a valid structural support or swing low. This initial move is typically designed to trigger stop losses and collect sell-side liquidity. If price returns to the broken level within five candles, it is considered a false breakout.
At this point, Fibonacci is drawn from the recent swing high to the new low. If price enters the 0.618 to 1.0 retracement zone within the next ten candles, a potential long entry aligned with Smart Money logic is activated. This deep retracement zone often offers the best low-risk entry, as it typically marks the area where liquidity has been absorbed and the breakout structure has failed.
The stop loss is placed slightly below the 1.0 level to account for minor fluctuations, while the target is set based on trend structure or risk-reward preferences.
🟣 Short Signal
A short setup begins with price temporarily breaking above a valid resistance or swing high. This breakout is often driven by buy-side liquidity collection or stop hunting. If price returns to the broken level within five candles, the move is marked as a breakout failure.
Fibonacci is then drawn from the recent swing low to the new high. If price enters the 0.618 to 1.0 zone within ten candles after the return, a short opportunity is confirmed. This area usually represents the maximum acceptable retracement before a continuation move to the downside and often triggers strong reactions.
The stop loss is placed just above the 1.0 level, and the target is defined based on the expected structure of the move or a predetermined reward ratio.
🟡 Advantages of the Screener
Unlike manual approaches that require constant monitoring of multiple charts, this tool functions as a fully automated screener across multiple symbols and timeframes. It continuously evaluates key levels, liquidity reactions, structural returns, and Fibonacci zones. An alert is only generated when all necessary conditions are met with high accuracy.
This ensures that traders avoid risky or misleading entries and stay focused on precise, verified, and logic-based setups — saving time, reducing noise, and improving consistency in decision-making.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
Valid After Trigger Bars : Limits how many candles after a fake breakout the entry zone remains valid.
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.
🟣 Display Settings
Table on Chart : Allows users to choose the position of the signal dashboard either directly on the chart or below it, depending on their layout preference.
Number of Symbols : Enables users to control how many symbols are displayed in the screener table, from 10 to 20, adjustable in increments of 2 symbols for flexible screening depth.
Table Mode : This setting offers two layout styles for the signal table :
Basic : Mode displays symbols in a single column, using more vertical space.
Extended : Mode arranges symbols in pairs side-by-side, optimizing screen space with a more compact view.
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 10 symbol slots comes with a full set of customizable parameters :
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
🟣 Alert Settings
Alert : Enables alerts for SMT Screener.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
Many trading mistakes stem from misinterpreting price breaks and entering too early into deceptive moves. In a market environment where false breakouts, liquidity traps, and engineered movements are increasingly common, having a tool that accurately filters these events and frames them within a Fibonacci-based and time-filtered structure provides a real strategic edge.
This indicator merges market structure logic, false breakout detection, and precise retracement analysis to ensure trades are only taken when multiple technical factors are aligned. It not only enhances trade success rates but also helps avoid emotional or impulsive entries.
Moreover, with the ability to scan across several symbols and timeframes simultaneously, the tool goes beyond being just an indicator it becomes a semi-automated structural analysis system. For traders who base their decisions on price behavior, Smart Money logic, and structural retracements, this screener can become a key component of a disciplined and effective trading approach.
Candle Range Detector by TradeTech AnalysisCandle Range Detector by TradeTech Analysis
This advanced indicator identifies and visualizes price compression zones based on inside bar formations, then tracks how price behaves around those zones — offering valuable insights into liquidity sweeps, range expansions, and trap/mitigation behavior.
The script builds upon the foundational concept of range-based price action, commonly used by institutional traders, and adds automation, mitigation tracking, and sweep detection to map how price reacts around these critical ranges.
🔍 How It Works:
• Range Formation: A new range is detected when the current candle forms entirely within the high and low of the previous candle (i.e., an inside bar). This behavior often indicates price compression and potential breakout zones.
• Range Extension: Once a range is confirmed, the script projects upper and lower boundaries (using either a percentage-based multiplier or Fibonacci log extension), providing context for expected breakout zones.
• Mitigation Tracking: The script continuously monitors whether price breaks above or below the projected extensions, marking that range as mitigated — useful for confirming whether liquidity was absorbed.
• Sweep Detection: If price re-visits a mitigated zone and shows signs of a liquidity sweep (via wick + close behavior), the indicator triggers visual sweep labels and optional alerts.
🧠 Optional Visual Enhancements:
• Highlight range-forming candles with light blue background (toggle on/off)
• Midpoint dotted line for symmetry analysis
• Labels for “Range High” and “Range Low” for visual clarity
• Dynamic box drawing that adapts upon mitigation or continuation
⚙️ Customizable Features:
• Choose between Normal and Fibonacci-based detection modes
• Toggle visibility of range boxes, extension lines, and sweep markers
• Configure sweep alerts, mitigation window size, and visual transparency
⸻
🧪 Use Cases
• Identify consolidation zones before major price moves
• Confirm liquidity sweeps for entry/exit traps
• Visualize and test mitigation behavior of past zones
• Combine with Order Flow or Volume Profile tools to enhance context
⸻
⚠️ This is a fully original implementation that goes beyond classical inside-bar scanners by incorporating mitigation, extension projection, and liquidity sweeps — making it a powerful tool for intraday, swing, and even Smart Money-based trading setups.
MTF Fractals [RunRox]🔽 MTF Fractals is a powerful indicator designed to visualize fractals from multiple timeframes directly on your chart, highlight liquidity sweeps at these fractal levels, and provide several additional features we’ll cover in detail below.
We created this indicator because we couldn’t find a suitable tool that met our specific needs on TradingView. Therefore, we decided to develop a valuable indicator for the entire TradingView community, combining simplicity and versatility.
⁉️ WHAT IS A FRACTALS?
In trading, a fractal is a technical analysis pattern composed of five consecutive candles, typically highlighting local market turning points. Specifically, a fractal high is formed when a candle’s high is higher than the highs of the two candles on either side, whereas a fractal low occurs when a candle’s low is lower than the lows of the two adjacent candles on both sides.
Traders use fractals as reference points for identifying significant support and resistance levels, potential reversal areas, and liquidity zones within price action analysis. Below is a screenshot illustrating clearly formed fractals on the chart.
📙 FRACTAL FORMATION
Here’s how fractals form depending on your chosen setting (3, 5, 7, or 9):
▶️ 3-bar fractal – forms when the central candle is higher (for highs) or lower (for lows) than one candle on each side.
▶️ 5-bar fractal – forms when the central candle is higher or lower than two candles on both sides.
▶️ 7-bar fractal – forms when the central candle is higher or lower compared to the three candles on each side.
▶️ 9-bar fractal – forms similarly but requires four candles on each side, making the fractal significantly more reliable and robust.
A higher number of bars ensures stronger fractal levels, highlighting more significant potential reversal points on the chart.
Now that we’ve covered the theory behind fractal formation, let’s explore the indicator’s functionality in more detail.
Below, I’ll explain each feature clearly and illustrate how you can effectively utilize this indicator in your trading.
🕐 MULTI-TIMEFRAME FRACTALS
We realized that displaying fractals only from the current timeframe isn’t always convenient, so we’ve introduced Multi-Timeframe Fractals into this indicator.
Now you can easily display fractals from higher timeframes directly on your current chart, providing you with broader market context and clearer trading signals.
Fractals from Current Timeframe – Fractals identified directly on the chart’s current timeframe.
Fractals from Higher Timeframes – Fractals sourced from higher timeframes and displayed clearly on your current chart for enhanced market perspective.
📈 FRACTAL LINES
Since fractals represent areas of high liquidity, we’ve added an option to extend fractal levels horizontally as Fractal Lines across your chart.
This feature allows you to clearly visualize critical liquidity areas from higher timeframes, directly on your current timeframe chart, as demonstrated in the screenshot below.
With this approach, you can clearly visualize significant fractal levels from higher timeframes directly on your current chart - for example, projecting fractals from the 1-hour (1H) timeframe onto a 3-minute (3m) chart. ✅ This helps you easily identify critical liquidity areas and potential reversal zones without the need to switch between multiple timeframes.
💰 LIQUDITY SWEEP (LIQUDITY GRAB)
To enhance your trading experience, we’ve introduced a feature that clearly identifies liquidity sweeps of fractal levels.
A Liquidity Sweep occurs when a candle closes beyond a fractal line, leaving a wick that pierces through it, signaling that liquidity has been collected at this level.
Below, you’ll find two examples illustrating this functionality:
▶️ Fractal lines from the current timeframe
▶️ Fractal lines projected from higher timeframes
The first example illustrates liquidity being swept from fractals on the current timeframe .
Here, the candle clearly closes beyond the fractal line, leaving a wick through it. This indicates a liquidity sweep at the fractal level, visually highlighting a potential reversal or continuation opportunity directly on your chart.
In the second example, fractals from the higher timeframe are projected onto your current chart.
When a candle on your current timeframe closes beyond an HTF fractal line - leaving a wick through this level - the indicator highlights it clearly. This signals to traders a potential reversal zone, indicating that liquidity has been swept, and price may reverse or significantly react from this area.
You can also enable the display of additional labels on the chart. These labels clearly mark liquidity sweeps at fractal levels, making it easier to visually identify potential reversal points directly on your chart.
⚙️ SETTINGS
Below are the indicator settings with detailed explanations for each parameter.
🔷 Bars in Fractal – Number of candles to the right and left required to form a fractal.
🔷 Fractal Timeframe – Select the timeframe from which you want to display fractals on the current chart.
🔷 Max Age, bars – Number of bars during which the fractal will remain active.
🔷 Show Fractal Line – Display or hide fractal lines.
🔷 Line Style – Choose the style of the line displayed on the chart.
🔷 Line Width – Thickness of the fractal line.
🔷 High Fractal – Style and color of bearish fractals.
🔷 Low Fractal – Style and color of bullish fractals.
🔷 Fractal Label Size – Select the size of fractal labels.
🔷 Show Sweep Labels – Option to display labels when a liquidity sweep occurs.
🔷 Label Color – Color and transparency of the area marked on the chart during a sweep.
🔷 Shade Sweep Area – Show or hide the sweep area shading.
🔷 Area Color – Color and transparency settings for the sweep area.
🔶 We’d love to hear your feedback and any suggestions for additional features you’d like to see in this indicator. We’ll be happy to consider your ideas and continue improving the indicator!
Advanced Market Structure & Order Blocks (fadi)Advanced Market Structure & Order Blocks indicator provides a new approach to understanding price action using ICT (Inner Circle Trader) concepts related to candle blocks to analyze the market behavior and eliminate much of the noise created by the price action.
This indicator is not intended to provide trade signals, it is designed to provide the traders with to support their trading strategies and add clarity where possible.
There are currently three main elements to this indicator:
Market Structure
Order Blocks
Liquidity Voids
Market Structure
In trading, market structure is often identified by observing higher highs and higher lows. An uptrend is characterized by a series of higher highs, where each peak surpasses the previous one, and higher lows, where each trough is higher than the preceding one. Conversely, a downtrend is marked by lower highs and lower lows.
Other indicators usually determine these peaks by calculating the highest or lowest levels within a predefined number of candles. For example, identifying the highest price level within the last 15 candles and marking it as a higher high or a lower high. While this approach offers some structure to price action, it can be arbitrary and random due to price fluctuations and the lack of proper structure analysis beyond finding the highest peaks and valleys within candle ranges.
In his 2022 mentorship, episode 12, ICT introduced an alternative approach focusing on three-candle pivots called Short Term High and Low (STH/STL), which are then used to calculate the Intermediate Term High and Low (ITH/ITL), and in turn, the Long Term High and Low (LTH/LTL). ICT’s approach provides better structure than the traditional method mentioned above. However, it can be confusing and difficult to track. There are great indicators that track and label ICT’s levels, but traders still find it challenging to follow and understand.
The Advanced Market Structure indicator takes a unique approach by analyzing candle formations, using ICT concepts, to identify possible turning points that mimic a real trader’s analysis of price action as closely as possible. However, it should be expected that Market Makers may use market manipulation to induce traders to make failed trades, and no tooling can eliminate these situations.
Advanced Market Structure tracks true Peaks and Valleys as they form, confirms them, and marks the chart with corresponding labels using traditional labeling methods (HH/HL/LH/LL), as such labeling makes it easier for traders to follow and understand. The indicator also draws levels to help identify possible liquidity areas and trade targets.
The indicator uses different calculation methods for the different type of market structure length, however all calculations are based on the same ICT candle blocks concepts.
Market Structure Settings
Other than the display settings, there are four (4) settings, mainly under the Level Settings section.
Allow Nested Candles
This option is only available on the Short Market Structure due to the methods used in calculating highs and lows. When used, the indicator will attempt to detect smaller fluctuations in price by tracking smaller candle moves, if any.
Level Settings
Level Settings allows the trader to decide two main calculations:
1. A new pivot point will form when a candle’s is crossed by the following candle’s
2. For a liquidity sweep and marking a level as mitigated, a candle’s must cross that level
Order Blocks
ICT (Inner Circle Trader) defines an Order Block as the last down-closing candle, or series of candles, before a significant upward price move or the last up-closing candle, or series of candles, before a significant downward price move. These key price levels, marked by substantial buy or sell orders from institutional traders or "smart money," create a block or zone on the price chart. When the price revisits these levels, it often leads to a strong market reaction. Order Blocks can consist of one or multiple consecutive candles of the same color, signaling areas of significant buying or selling interest. ICT's approach to Order Blocks provides traders with a structured method to identify potential areas of support or resistance, where price movements are more likely to change direction. Although ICT has shared some criteria for identifying Order Blocks publicly, the full details are reserved for his upcoming books. This indicator leverages the publicly available information to provide traders with valuable insights into these crucial price levels.
The Advanced Market Structure indicator is designed to be highly flexible, allowing traders to define their own combination of rules for identifying Order Blocks, thus customizing it to fit their unique trading strategies.
Order Block Configuration
Can be nested
An Order Block is defined as the last down candle or candles before a strong move higher, and vice versa for bearish Order Blocks. However, larger-than-usual candles resulting from news events or price action may not qualify as Order Blocks and can mute any Order Block within their range.
The "Can be nested" flag ensures that each Order Block is treated as an independent entity, even if it appears within the body of another Order Block.
Forms at swing point
Order Blocks formed at swing points typically have higher probabilities but are less frequent, assuming the same rules are applied. Additionally, Order Blocks at swing points may become Breaker and Mitigation blocks if they fail, providing more trading opportunities.
Forms a simple pivot point
A simple pivot point corresponds to ICT Short Term High and Low (STH/STL). Order Blocks using simple pivot points can occur in the middle of a move, not just at swing points. These are useful for identifying IOFED setups and supporting blocks that can bolster the price move.
Causes Market Structure Shift
Order Blocks that result in a break above or below a short swing point can help narrow down target order blocks, but they are less frequent. An Order Block causing a break above or below a pivot point does not necessarily indicate a strong Order Block. For example, an Order Block formed at a Lower Low is more likely to fail in a downtrend.
A clean close above order block
When the first candle breaks above an Order Block and closes above its high, this indicates a stronger Order Block. On the other hand, if a candle merely wicks through the Order Block without a solid close above it, it suggests a weaker Order Block. This may indicate hesitation or an impending reversal, as the wick represents a temporary and unsustained price movement.
Has displacement more than X the body
While some traders may capitalize on the initial break above an Order Block's CISD level, others prefer to focus on the return to an Order Block after displacement. Displacement is determined by the body size of the Order Block, and an Order Block cannot be tested until this level has been achieved.
Has a Fair Value Gap
When an Order Block is combined with a Fair Value Gap (FVG), it signifies a strong Order Block. The Fair Value Gap indicates a strong price movement away from the Order Block.
Has a liquidity void
A Liquidity Void occurs when two consecutive candles of the same color do not overlap, creating a gap similar to a Fair Value Gap, but involving one or more middle candles. Liquidity Voids can be utilized in combination with, or as an alternative to, the displacement setting.
Maximum number of OBs
The maximum number of Order Blocks to display.
Mitigated at block’s
An Order Block is considered mitigated when price reaches one of the main Order Block levels.
Liquidity Void
Liquidity Void refers to areas on a price chart where there is one-sided trading activity. This phenomenon occurs when the price of an asset moves sharply in one direction, leaving gaps where two consecutive candles of the same color do not overlap. These gaps can comprise one or more middle candles and indicates a pronounced lack of trading within that price range. Liquidity Voids are important because they highlight areas of minimal resistance, where price is more likely to return to fill the void and balance the market.
Liquidity Void vs Fair Value Gap
While both concepts are related to gaps in price action, they are distinct. A Fair Value Gap is a specific three-candle pattern where the middle candle creates a gap between the first and third candles. In contrast, a Liquidity Void represents a broader area on the chart where there is little to no trading activity, often encompassing multiple candles and indicating a more pronounced imbalance between buy and sell orders.
A FVG can be part of a Liquidity Void, a Liquidity Void can exist without necessarily including an FVG. Both concepts highlight areas of minimal resistance and potential price movement, but they differ in their formation and implications.
Advanced Market Structure and Order Blocks indicator focus on liquidity voids since a liquidity void can substitute for a FVG and it is usually less addressed by other indicators.
Cryptolabs Global Liquidity Cycle Momentum IndicatorCryptolabs Global Liquidity Cycle Momentum Indicator (LMI-BTC)
This open-source indicator combines global central bank liquidity data with Bitcoin price movements to identify medium- to long-term market cycles and momentum phases. It is designed for traders who want to incorporate macroeconomic factors into their Bitcoin analysis.
How It Works
The script calculates a Liquidity Index using balance sheet data from four central banks (USA: ECONOMICS:USCBBS, Japan: FRED:JPNASSETS, China: ECONOMICS:CNCBBS, EU: FRED:ECBASSETSW), augmented by the Dollar Index (TVC:DXY) and Chinese 10-year bond yields (TVC:CN10Y). This index is:
- Logarithmically scaled (math.log) to better represent large values like central bank balances and Bitcoin prices.
- Normalized over a 50-period range to balance fluctuations between minimum and maximum values.
- Compared to prior-year values, with the number of bars dynamically adjusted based on the timeframe (e.g., 252 for 1D, 52 for 1W), to compute percentage changes.
The liquidity change is analyzed using a Chande Momentum Oscillator (CMO) (period: 24) to measure momentum trends. A Weighted Moving Average (WMA) (period: 10) acts as a signal line. The Bitcoin price is also plotted logarithmically to highlight parallels with liquidity cycles.
Usage
Traders can use the indicator to:
- Identify global liquidity cycles influencing Bitcoin price trends, such as expansive or restrictive monetary policies.
- Detect momentum phases: Values above 50 suggest overbought conditions, below -50 indicate oversold conditions.
- Anticipate trend reversals by observing CMO crossovers with the signal line.
It performs best on higher timeframes like daily (1D) or weekly (1W) charts. The visualization includes:
- CMO line (green > 50, red < -50, blue neutral), signal line (white), Bitcoin price (gray).
- Horizontal lines at 50, 0, and -50 for improved readability.
Originality
This indicator stands out from other momentum tools like RSI or basic price analysis due to:
- Unique Data Integration: Combines four central bank datasets, DXY, and CN10Y as macroeconomic proxies for Bitcoin.
- Dynamic Prior-Year Analysis: Calculates liquidity changes relative to historical values, adjustable by timeframe.
- Logarithmic Normalization: Enhances visibility of extreme values, critical for cryptocurrencies and macro data.
This combination offers a rare perspective on the interplay between global liquidity and Bitcoin, unavailable in other open-source scripts.
Settings
- CMO Period: Default 24, adjustable for faster/slower signals.
- Signal WMA: Default 10, for smoothing the CMO line.
- Normalization Window: Default 50 periods, customizable.
Users can modify these parameters in the Pine Editor to tailor the indicator to their strategy.
Note
This script is designed for medium- to long-term analysis, not scalping. For optimal results, combine it with additional analyses (e.g., on-chain data, support/resistance levels). It does not guarantee profits but supports informed decisions based on macroeconomic trends.
Data Sources
- Bitcoin: INDEX:BTCUSD
- Liquidity: ECONOMICS:USCBBS, FRED:JPNASSETS, ECONOMICS:CNCBBS, FRED:ECBASSETSW
- Additional: TVC:DXY, TVC:CN10Y
