Institutional Order Flow StrategyLa strategia implementata è denominata "Institutional Order Flow Strategy" e si basa sull'identificazione di Order Blocks e su specifiche condizioni di ingresso e uscita per le posizioni long e short. L'idea è di identificare i livelli dove operano i bot degli istituzionali, poi attraverso degli obbiettivi di profitto individuali, piazzare tre livelli di profitto atteso.
Ecco una spiegazione dettagliata delle varie sezioni del codice:
1. Impostazioni di Input
Input Session: Imposta una sessione di trading dalle 09:30 alle 16:00.
Lookback Period: Periodo di osservazione di 20 barre per identificare gli order blocks.
Target Percentuali: Tre obiettivi di profitto (Target 1, Target 2, Target 3) espressi in percentuale rispetto al prezzo medio di ingresso.
2. Identificazione degli Order Blocks
Il codice calcola i massimi e minimi più alti e più bassi nel periodo di lookback specificato:
Order Block Buy: Viene identificato come il massimo più alto quando la barra precedente è bearish (chiusura < apertura) e la barra corrente è bullish (chiusura > apertura).
Order Block Sell: Viene identificato come il minimo più basso quando la barra precedente è bullish e la barra corrente è bearish.
3. Logica di Ingresso
In Session: Verifica se il tempo attuale è all'interno della sessione di trading specificata.
Condizioni di Ingresso Long e Short:
Long: La chiusura deve essere superiore all'order block di acquisto e deve essere all'interno della sessione.
Short: La chiusura deve essere inferiore all'order block di vendita e deve essere all'interno della sessione.
4. Entrate nella Strategia
Se le condizioni di ingresso sono soddisfatte, vengono aperte posizioni long o short:
strategy.entry("Long", strategy.long) per le posizioni long.
strategy.entry("Short", strategy.short) per le posizioni short.
5. Calcolo degli Obiettivi per Scalare le Uscite
Per ogni posizione aperta, vengono calcolati tre obiettivi di prezzo per il take profit, basati sul prezzo medio di ingresso:
Long Targets: Calcolati aggiungendo le percentuali specificate al prezzo medio di ingresso.
Short Targets: Calcolati sottraendo le percentuali specificate dal prezzo medio di ingresso.
6. Logica di Uscita con Scalabilità
Quando ci sono posizioni aperte, vengono impostate le uscite:
Per le posizioni long, si esce dal 50% della posizione al Target 1, il 30% al Target 2 e il 20% al Target 3.
Per le posizioni short, la logica è simile, ma si esce a target di prezzo calcolati in senso inverso.
7. Visualizzazione degli Order Blocks
Infine, il codice visualizza gli order blocks sul grafico:
L'order block di acquisto viene tracciato in verde.
L'order block di vendita viene tracciato in rosso.
Conclusione
In sintesi, questa strategia di trading cerca di sfruttare i movimenti di mercato basati sugli order blocks, impostando condizioni di ingresso e uscita chiare, insieme a obiettivi di profitto scalabili.
Orderflow
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.
LIT_Globas_sys - Liquidity Inducement Theorem (SMC, IDM)LIT_GLOBAL_SYS Trading Tool Documentation, is a comprehensive market analysis tool that includes all components needed for trading according to Liquidity Inducement Theorem (LIT). LIT differs from classical trading methods and is considered a highly effective and profitable strategy.
What can LIT_GLOBAL_SYS do?
--- Market Structure
The main feature of Liquidity Inducement Theorem is building the correct structure, specifically construction taking into account inducement (IDM). Thus, a new HH or LL can only form when the price has taken the first correct pullback - inducement (IDM), and after this, we understand the location of BoS (break of structure) and CHoCH (change of character).
LIT_GLOBAL_SYS automatically and perfectly displays the correct structure following all LIT rules. Looking at the indicator, a trader always understands which range the price is currently in and where it's trending at the moment. The indicator also shows dynamic (live) levels, providing a clear understanding of the market structure in real-time.
The indicator settings allow customization of each structural element according to trader preferences. For example, you can change the style, color, and shape of structural objects.
--- Correct Pullbacks and Inside Bars
In Liquidity Inducement Theorem, correct pullbacks are fundamental. The structure, order blocks, liquidity levels, order flow, and single candle order blocks (CSOB) are all built based on pullbacks.
What is a pullback?
- When the next candle updates the low of the previous candle, we can finish drawing an upward pullback
- We can start drawing a downward correct pullback when the next candle updates the low of the previous candle
- The downward movement will continue until the opposite occurs - updating the high of the previous candle
There are complexities in determining pullbacks - these are inside bars. In Liquidity Inducement Theorem, inside bars are completely ignored!
For example, in an upward movement, at some point, candles may stop updating the high and low of the previous candle and remain within the boundaries of the previous candle. Theoretically, there could be any number of such candles from 1 to infinity. In such cases, it's important to wait for the price to exit the mother candle (the candle after which other candles remained within its high and low range).
LIT_GLOBAL_SYS easily handles this and displays both pullbacks and inside bars correctly.
--- Order Blocks and Fair Value Gaps (FVG)
In Liquidity Inducement Theorem, order blocks are defined differently from classical order blocks:
1. The order block must take liquidity from the previous candle
2. The order block must have Fair Value Gaps (FVG) before it
3. Inside bars are completely ignored for both Order Blocks and FVG
4. If an OB fulfills the first condition (taking liquidity from the previous candle) but doesn't have FVG before it, this block is moved forward along the candles until there is an imbalance before it
There are two most important order blocks in LIT strategy:
1. Inducement order block (idm ob) - the first order block after Inducement
2. Extreme order block (Ext ob) - the first order block before CHoCH
LIT_GLOBAL_SYS perfectly displays correct order blocks and Fair Value Gaps following all rules. It offers full customization options:
- Specify the number of displayed OBs
- Disable all order blocks except idm ob and Ext ob
- Change block frame color and style
- Disable or modify text display in blocks
--- Single Candle Order Block (Scob)
Rules for building Scob:
1. The candle takes liquidity from the previous candle and closes within the body of the previous candle
2. The candle following the Scob candle must close its body below the previous candle
3. Scob forms in continuation of the trend movement
4. Scob completely ignores inside bars
LIT_GLOBAL_SYS accurately displays Scob as triangles and fully ignores inside bars both left and right. The menu allows complete customization of display and quantity of displayed Scobs.
--- Liquidity Lines, Order Flow, and Three-Minute Rule
Auxiliary functions include:
- Liquidity Lines -
Each pullback is marked with a line, showing where unclosed liquidity exists. Completed lines can be hidden to help predict price movement and enter trades correctly.
- Order Flow -
The indicator implements order flow by drawing a line when a pullback is broken (closed by body) in the opposite direction until the second touch. If price moves away without a second touch, the line remains, showing unclosed OF and potential price return zones.
- Three-Minute Rule -
Some LIT traders use the three-minute rule: price manipulations in the last and first three minutes of each 15-minute candle are additional entry factors, especially in the last quarter of an hourly candle. LIT_GLOBAL_SYS displays this rule only on the one-minute timeframe with symbols below for M15 and H1.
--- Trading Sessions, PDH/PDL, and EMA
The system includes:
- Trading sessions (Tokyo, Frankfurt, London, New York) with customizable time settings
- Previous Day High and Previous Day Low (pdh/pdl) levels
- Exponential Moving Average (EMA) with adjustable length
- Equilibrium display between current BoS and CHoCH levels
--- Alert System
LIT_GLOBAL_SYS includes all necessary alerts for Liquidity Inducement Theorem:
1. SCOB
2. EMA
3. BoS, ChoCh, Sweep
4. IDM
5. IDM OB and Ext OB
Users can simply check the desired alerts in the menu and activate them to receive notifications when price reaches specified zones.
OrderFlow [Adjustable] | FractalystWhat's the indicator's purpose and functionality?
This indicator is designed to assist traders in identifying real-time probabilities of buyside and sellside liquidity .
It allows for an adjustable pivot level , enabling traders to customize the level they want to use for their entries.
By doing so, traders can evaluate whether their chosen entry point would yield a positive expected value over a large sample size, optimizing their strategy for long-term profitability.
For advanced traders looking to enhance their analysis, the indicator supports the incorporation of up to 7 higher timeframe biases .
Additionally, the higher timeframe pivot level can be adjusted according to the trader's preferences,
Offering maximum adaptability to different strategies and needs, further helping to maximize positive EV.
EV=(P(Win)×R(Win))−(P(Loss)×R(Loss))
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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
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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.
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What does the multi-timeframe functionality offer?
In the adjustable version of the orderflow indicator, you can incorporate up to 7 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.
This multi-timeframe functionality helps traders:
1. Simplify decision-making by offering a comprehensive view of multiple timeframes at once.
2. Identify confluence between timeframes, enhancing the confidence in trade setups.
3. Adapt strategies more effectively, as the higher timeframe pivot levels can be customized to meet individual preferences and goals.
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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.
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How does the Indicator Identifies Positive Expected Values?
OrderFlow indicator instantly calculates whether a trade setup has the potential for positive expected value (EV) in the long run.
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 over a large sample size.
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How can I know that the setup I'm going to trade with has a postive 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.
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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.
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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.
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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.
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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.
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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.
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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.
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How to use the indicator effectively?
For Amateur Traders:
Start Simple: Begin by focusing on one timeframe at a time with the pivot level set to the default (50%). This helps you understand the basic functionality of the indicator.
Entry and Exit Strategy: Focus on entering trades at the pivot level while targeting the higher probability side for take profit and the lower probability side for stop loss.
Use simulation or paper trading to practice this strategy.
Adjustments: Once you have a solid understanding of how the indicator works, you can start adjusting the pivot level to other values that suit your strategy.
Ensure that the RR labels are colored (blue or red) to indicate positive EV setups before executing trades.
For Advanced Traders:
1. Select Higher Timeframe Bias: Choose a higher timeframe (HTF) as your main bias. Start with the default pivot level and ensure the confidence level is above 95% to validate the probabilities.
2. Align Lower Timeframes: Switch between lower timeframes to identify which ones align with your predefined HTF bias. This helps in synchronizing your trading decisions across different timeframes.
3. Set Entries with Current Pivot Level: Use the current pivot level for trade entries. Ensure the HTF status label is active, indicating that the probabilities are valid and in play.
4. Target HTF Liquidity Level: Aim for liquidity levels that correspond to the higher timeframe, as these levels are likely to offer better trading opportunities.
5. Adjust Pivot Levels: As you gain experience, adjust the pivot levels to further optimize your strategy for high EV. Fine-tune these levels based on the aggregated data from multiple timeframes.
6. Practice on Paper Trading: Test your strategies through paper trading to eliminate discretion and refine your approach without financial risk.
7. Focus on Trade Management: Ultimately, effective trade management is crucial. Concentrate on managing your trades well to ensure long-term success. By aiming for setups that produce positive EV, you can position yourself similarly to how a casino operates.
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🎲 Becoming the House (Gaining Edge Over the Market):
In American roulette, the house has a 5.26% edge due to the 0 and 00. This means that while players have a 47.37% chance of winning on even-money bets, the true odds are 50%. The discrepancy between the true odds and the payout ensures that, statistically, the casino will win over time.
From the Trader's Perspective: In trading, you gain an edge by focusing on setups with positive expected value (EV). If you have a 55.48% chance of winning with a 1:1 risk-to-reward ratio, your setup has a higher probability of profitability than the losing side. By consistently targeting such setups and managing your trades effectively, you create a statistical advantage, similar to the casino’s edge.
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🎰 Applying the Concept to Trading:
Just as casinos rely on their mathematical edge, you can achieve long-term success in trading by focusing on setups with positive EV. By ensuring that your probabilities and risk-to-reward (RR) ratios are in your favor, you create an edge similar to that of the house.
And by systematically targeting trades with favorable probabilities and managing your trades effectively, you improve your chances of profitability over the long run. Which is going to help you “become the house” in your trading, leveraging statistical advantages to enhance your overall performance.
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What makes this indicator original?
Real-Time Probability Calculations: The indicator provides real-time calculations of buy and sell probabilities based on historical data, allowing traders to assess the likelihood of positive expected value (EV) setups instantly.
Adjustable Pivot Levels: It features an adjustable pivot level that traders can modify according to their preferences, enhancing the flexibility to align with different trading strategies.
Multi-Timeframe Integration: The indicator supports up to 7 higher timeframes, displaying their probabilities and biases in a single view, which helps traders make informed decisions without switching timeframes.
Confidence Levels: It includes confidence levels based on sample sizes, offering insights into the reliability of the probabilities. Traders can gauge the strength of the data before making trades.
Dynamic EV Labels: The indicator provides color-coded EV labels that change based on the validity of the setup. Blue indicates positive EV in a long bias, red indicates positive EV in a short bias and gray signals caution, making it easier for traders to identify high-quality setups.
HTF Probability Table: The HTF probability table displays buy and sell probabilities from user-defined higher timeframes, helping traders integrate broader market context into their decision-making process.
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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.
Cumulative Delta [TradingFinder] Volume + Periodic + EMA🔵 Introduction
To fully grasp the concept of Cumulative Volume Delta (CVD), it's essential first to understand Volume Delta. In trading and technical analysis, the term "Delta" typically refers to the difference between two values or the rate of change between two data points.
Volume Delta represents the difference between buying and selling pressure, calculated for each candlestick on a chart. This difference can vary across different timeframes.
A positive delta indicates that buying volume exceeds selling volume, while a negative delta shows that selling volume is greater. When buying and selling volumes are equal, the volume delta equals zero.
🟣 What is Cumulative Volume Delta (CVD)?
Cumulative Volume Delta (CVD) is a powerful tool in technical analysis that aggregates delta values for each candlestick, creating a comprehensive indicator that helps traders assess market trends.
Unlike the standard Volume Delta, which compares delta on a candle-by-candle basis, CVD provides insight into the overall buying and selling pressure during key market swings. A downward-trending CVD suggests that selling pressure is dominating, which is typically a bearish signal.
Conversely, an upward-trending CVD indicates bullish sentiment. This analysis becomes even more significant when comparing CVD with price action and market structure, helping traders to predict asset price directions.
By evaluating market highs and lows, one can determine the market trend. A consistent rise in these points indicates an uptrend, while a consistent fall suggests a downtrend.
🔵 How to Use
Understanding how to detect trend changes using Cumulative Volume Delta is crucial for traders. Typically, CVD aligns with market structure, moving in the same direction as price trends.
However, divergences between CVD and price trends or signs of exhaustion in volume can be powerful indicators of potential market reversals. Recognizing these patterns can help traders make informed decisions and improve their trading strategies.
🟣 Identifying Trend Exhaustion with Cumulative Volume Delta (CVD)
The Cumulative Volume Delta (CVD) indicator is especially effective in identifying weakening trends in the market. For instance, if gold's price hits a new low, but CVD does not follow suit, this may indicate a lack of seller interest despite the new low, signaling potential seller exhaustion.
Most traders interpret this as a possible reversal from a bearish to a bullish trend. Similarly, if gold reaches a new high but CVD fails to do the same, it can suggest that buyers lack the strength to push the market higher, indicating a possible trend reversal.
🟣 Utilizing Cumulative Volume Delta (CVD) Divergence in Price Trend Analysis
Another effective use of CVD is identifying divergences in price trends. For example, if CVD breaks a previous high or low while the price remains stable, this divergence often indicates that buying or selling pressure is being absorbed.
For instance, if CVD rises sharply without a corresponding increase in gold prices, it may suggest that sellers are absorbing the buying pressure, potentially leading to a strong sell-off. Conversely, if gold prices remain stable while CVD declines, it could indicate that buyers are absorbing selling pressure, likely leading to a price increase once selling subsides.
🔵 Setting
Cumulative Mode : It has three modes "Total", "Periodic" and "EMA". In "Total" mode, it collects the volume from the beginning to the end. In "Periodic" mode, it accumulates the volume periodically and in "EMA" mode, it calculates the moving average of the volume.
Period : You can set the period of " Periodic " and " EMA " modes.
Market Ultra Data : If you turn on this feature, 26 large brokers will be included in the calculation of the trading volume.
The advantage of this capability is to have more reliable volume data. You should be careful to specify the market you are in, FOREX brokers and Crypto brokers are different.
🔵 Conclusion
Cumulative Volume Delta (CVD) is a powerful analytical tool in financial markets that helps analysts and traders assess buying and selling pressure by aggregating and combining the volume delta for each candlestick.
CVD can indicate the strength or weakness of a market trend. When CVD moves upward, it signals that buying pressure is dominant and is considered a bullish signal; conversely, a downward movement in CVD indicates that selling pressure is stronger and is viewed as a bearish signal.
This indicator is particularly effective in identifying divergences and exhaustion in market trends. For example, if CVD does not align with price movements, it may suggest a potential trend reversal.
Traders use this information to make more informed trading decisions, especially when identifying entry and exit points in the market.
Overall, CVD is a tool that enables analysts to better understand market fluctuations and more accurately predict future market trends.
Efficiency Weighted OrderFlow [AlgoAlpha]Introducing the Efficiency Weighted Orderflow Indicator by AlgoAlpha! 📈✨
Elevate your trading game with our cutting-edge Efficiency Weighted Orderflow Indicator, designed to provide clear insights into market trends and potential reversals. This tool is perfect for traders seeking to understand the underlying market dynamics through efficiency-weighted volume calculations.
🌟 Key Features 🌟
✨ Smooth OrderFlow Calculation : Option to smooth order flow data for more consistent signals.
🔧 Customizable Parameters : Adjust the Order Flow Period and HMA Smoothing Length to fit your trading strategy.
🔍 Visual Clarity : Easily distinguish between bullish and bearish trends with customizable colors.
📊 Standard Deviation Normalization : Keeps order flow values normalized for better comparison across different market conditions.
🔔 Trend Reversal Alerts : Stay ahead with built-in alert conditions for significant order flow changes.
🚀 Quick Guide to Using the Efficiency Weighted Orderflow Indicator
🛠 Add the Indicator: Search for "Efficiency Weighted Orderflow " in TradingView's Indicators & Strategies. Customize settings like smoothing and order flow period to fit your trading style.
📊 Market Analysis: Watch for trend reversal alerts to capture trading opportunities by studying the behaviour of the indicator.
🔔 Alerts: Enable notifications for significant order flow changes to stay updated on market trends.
🔍 How It Works
The Efficiency Weighted Orderflow Indicator starts by calculating the efficiency of price movements using the absolute difference between the close and open prices, divided by volume. The order flow is then computed by summing these efficiency-weighted volumes over a specified period, with an option to apply Hull Moving Average (HMA) smoothing for enhanced signal stability. To ensure robust comparison, the order flow is normalized using standard deviation. The indicator plots these values as columns, with distinct colors representing bullish and bearish trends. Customizable parameters for period length and smoothing allow traders to tailor the indicator to their strategies. Additionally, visual cues and alert conditions for trend reversals and significant order flow changes keep traders informed and ready to act. This indicator improves on the Orderflow aspect of our Standardized Orderflow indicator. The Efficiency Weighted Orderflow is less susceptible to noise and is also quicker at detecting trend changes.
Activity and Volume Orderflow Profile [AlgoAlpha]🔍 Activity and Volume Orderflow Profile 📊
🚀 Unlock the power of market order flow analysis with the Activity and Volume Orderflow Profile indicator by AlgoAlpha . This versatile tool helps you visualize and understand the dynamics of buying and selling pressure within a specified lookback period. Perfect for traders who want to dig deeper into volume-based market insights!
Key Features:
📊 Profile Type Options : Choose between "Comparison" and "Net Order Flow" to analyze market activity based on your preferred method.
🔎 Adjustable Lookback Period : Customize the lookback period to fit your trading strategy.
🎨 Flexible Appearance Settings : Toggle the display of the profile, lookback period visualization, and heatmap to suit your preferences.
🖍 Color Customization : Set your preferred colors for up and down volumes.
🕹 High Activity Highlight : Use the minimum transparency setting to highlight areas of significant activity.
Quick Guide to Using the Activity and Volume Orderflow Profile
🛠 Add the Indicator: Add the indicator to your favorites. Customize settings like profile type, lookback period, and resolution to fit your trading style.
📊 Market Analysis: Use the profile to identify areas of high buying or selling pressure. In "Comparison" mode, look for significant volume differences; in "Net Order Flow" mode, focus on net volume changes. Additionally, you can use the activity heatmap to find key levels that can act as support and resistance as price is likely to react to the zones as indicated by the heatmap.
How it Works:
The indicator operates by first gathering data on high and low prices, as well as buy and sell volumes, over a user-defined lookback period. It then calculates the maximum and minimum prices during this period and divides this range into bins based on the chosen resolution. For each bin, it computes the total volume of buy and sell orders. In "Comparison" mode, it displays side-by-side boxes representing buy and sell volumes, while in "Net Order Flow" mode, it shows the net volume difference. The indicator visually presents these profiles on the chart with customizable colors, transparency levels, and the option to display a heatmap for enhanced volume activity insights.
Maximize your trading with the Activity and Volume Orderflow Profile from AlgoAlpha! 🚀✨
OrderFlow Absorption IndicatorWhat it Does
The OrderFlow Absorption Indicator marks areas where the price absorbs a large volume of aggressive market trades. This indicates areas where price may bounce back due to large limit (resting) orders absorbing significant aggressor volume (market orders). Absorption can also be seen as "preventing" or "stopping" the other side from breaking through a price level (e.g. bids stopping an influx of sell market orders). Absorption may signal a change in sentiment, potentially leading to a pullback or reversal.
An Example of Absorption
Of course, it is not always the case that such bullish absorption will initiate a trend as the example above. The OrderFlow Absorption Indicator merely serves as a tool for spotting possible absorption points in the market which you can incorporate into your trading arsenal.
How it Works
The indicator actively monitors price changes and records volume accumulated at a price level. If the price bounces back to at least where it was before the current price move, the indicator records this as absorption, provided it meets the Volume Requirement and optional Time Requirement.
How to Use it
1. Set Parameters
Choose your desired tick size and volume filter value. If unsure, refer to the table on the top right of the chart for recommended values. An automatic volume limit filter mode is also available.
Automatic Limit Mode : Enable this mode to have the indicator automatically select a volume filter value. It calculates the standard deviation of the last n minutes of volume and multiplies it by a volume multiplier. You can adjust these parameters.
Higher Volume Filter : Setting a higher volume filter value results in fewer, but higher quality detections, reducing noise.
2. Enabling the Time Limit
Enabling the time limit further improves detection quality by filtering out price levels that can defend against quick, sudden aggressive orders, acting as confirmation and indicating strong sentiment and resilient liquidity.
3. Enabling Historical Data Absorption
The indicator can also detect absorption in historical data, though less accurately than in real-time due to OHLCV aggregation.
You can select the granularity of historical data.
Lower granularity (e.g., 1 second) : Provides more accurate detections but may slow down the indicator.
Higher granularity : Improves speed but reduces detection accuracy.
Other Features
Hovering : When hovering over an absorption point, the interface reveals the price where the absorption occurred, along with the volume absorbed by the bids and asks, as well as the volume filter value used.
Delta Mode : In Delta mode, the system calculates the difference between the volume absorbed by bids and asks, revealing points only when the absolute value of this difference exceeds the volume filter value. Especially useful for larger tick sizes.
Troubleshooting
If the indicator doesn't mark anything, it means the traded volume hasn't exceeded the set volume filter value within the specified price intervals(tick size) and time limit. Adjust these settings as necessary.
Net Buying/Selling Flows Toolkit [AlgoAlpha]🌟📊 Introducing the Net Buying/Selling Flows Toolkit by AlgoAlpha 📈🚀
🔍 Explore the intricate dynamics of market movements with the Net Buying/Selling Flows Toolkit designed for precision and effectiveness in visualizing money inflows and outflows and their impact on asset prices.
🔀 Multiple Display Modes : Choose from "Flow Comparison", "Net Flow", or "Sum of Flows" to view the data in the most relevant way for your analysis.
📏 Adjustable Unit Display : Easily manage the magnitude of the values displayed with options like "1 Billion", "1 Million", "1 Thousand", or "None".
🔧 Lookback Period Customization : Tailor the sum calculation window with a configurable lookback period, applicable in "Sum of Flows" mode.
📊 Deviation Thresholds : Set up lower and upper deviation thresholds to identify significant changes in flow data.
🔄 Reversal Signals and Deviation Bands : Enable signals for potential reversals and visualize deviation bands for comparative analysis.
🎨 Color-coded Visualization : Distinct colors for upward and downward movements make it easy to distinguish between buying and selling pressures.
🚀 Quick Guide to Using the Net Buying/Selling Flows Toolkit :
🔍 Add the Indicator : Add the indicator to you favorites. Customize the settings to fit your trading requirements.
👁️🗨️ Data Analysis : Compare the trend of Buying and Selling to help indicate whether bulls or bears are in control of the market. Utilize the different display modes to present the data in different form to suite your analysis style.
🔔 Set Alerts : Activate alerts for reversal conditions to keep abreast of significant market movements without having to monitor the charts constantly.
🌐 How It Works :
The toolkit processes volume data on a lower timeframe to distinguish between buying and selling pressures based on intra-bar price closing higher or lower than it opened. It aggregates these transactions and finds the net selling and buying that took place during that bar, offering a clearer view of market fundamentals. The indicator then plots this data visually with multiple modes including comparisons between buying/selling and the net flow of the asset. Deviation thresholds help in identifying significant changes, allowing traders to spot potential buying or selling opportunities based on the money flow dynamics. The "Sum of Flows" mode is unique from other trend following indicators as it does not determine trend based on price action, but rather based on the net buying/selling. Therefore in some cases the "Sum of Flows" mode can be a leading indicator showing bullish/bearish net flows even before the prices move significantly.
Embark on a more informed trading journey with this dynamic and insightful tool, tailor-made for those who demand precision and clarity in their trading strategies. 🌟📉📈
Mxwll Liquidation Ranges - Mxwll CapitalIntroducing: Mxwll Liquidation Ranges
Mxwll Liquidation Ranges gathers data outside of TradingView to provide the highest quality, highest accuracy liquidation levels and ranges for popular crypto currencies.
Features
Real liquidation ranges and levels calculated outside of TradingView.
Real net position delta
Average leverage for long positions
Average leverage for short positions
Real number of bids for the cryptocurrency by the day
Real number of asks for the cryptocurrency by the day
Real Bid/Ask Ratio
Real Bid/Ask Delta
Real number of long market orders
Real number of short market orders
Real number of long limit orders
Real number of short limit orders
How do we obtain this data?
Using a now deprecated feature called "TradingView Pine Seeds", we are able to calculate the metrics listed above outside of TradingView and, consequently, import the data to TradingView for public use.
This means no indicators on TradingView that attempt to show liquidation levels, limit orders, net position delta, etc. can be as accurate as ours.
Why aren't other liquidation ranges indicators on TradingView as accurate as ours?
Simple: the data required to calculate liquidation levels and ranges isn't available on TradingView. No level 2 data, bids, asks, leverage information, pending limit orders, etc. This means any custom-coded indicator on TradingView attempting to use or show this information is just a guess, and is naturally inaccurate.
Mxwll Liquidation Ranges has access to all of the required data outside of TradingView, to which liquidation levels/ranges and other pertinent metrics are calculated and uploaded directly to TradingView using the Pine Seeds feature. This means that all information displayed by our indicator uses legitimate level 2 data outside of TradingView. Which means no "estimates" are required to produce this information. Consequently, unless a custom-coded indicator has access to the Pine Seeds feature and calculates liquidation levels and other level 2 data metrics outside of TradingView, then that indicator is inaccurate.
Liquidation Heatmap
The above image shows our liquidation heatmaps, which are calculated using level 2 data, in action.
Liquidation ranges are color coded. Purple/blue colored ranges indicate a lower number of net liquidations should the range be violated.
Green/yellow ranges indicate a liquidation range where the net number of liquidated positions, should the price range be violated, is substantial. Expect volatile price action around these areas and plan accordingly.
Yellow labels indicate the four highest liquidation ranges for the asset over the period.
Liquidation Levels
In addition to calculating a liquidation heatmap, Mxwll Liquidation Ranges also calculates liquidation levels by leverage. Level 2 data outside of TradingView is used.
Levels are colored coded by leverage used.
Green levels are 25x leverage liquidation areas.
Purple levels are 50x leverage liquidation areas.
Orange levels are 100x leverage liquidation areas.
Use this information to improve your trading plan and better pinpoint entries, exits, and key levels of expected volatility.
Other Metrics
Mxwll Liquidation Ranges uses level 2 data and the orderbook to calculate various metrics.
Average leverage for long positions
Average leverage for short positions
Real number of bids for the cryptocurrency by the day
Real number of asks for the cryptocurrency by the day
Real Bid/Ask Ratio
Real Bid/Ask Delta
Real number of long market orders
Real number of short market orders
Real number of long limit orders
Real number of short limit orders
How To Use
Understanding and interpreting heatmaps for predicting liquidation levels in trading can provide a significant edge. Here’s a basic guide on how to interpret these charts:
Understanding Liquidation Levels: Liquidation levels indicate where traders who are using leverage might be forced to exit their positions due to insufficient margin to cover their trades. These levels are crucial because they can trigger sudden price movements if many positions are liquidated at once.
Clusters on the Heatmap: On the heatmap, clusters of liquidation levels are represented by color-coded areas. These clusters show where significant numbers of leveraged positions are concentrated. The color intensity often indicates the density of liquidation points – darker or brighter colors suggest higher concentrations of liquidation risks.
Price Movements: By knowing where these clusters are, traders can anticipate potential price movements. For example, if a significant price drop moves the market closer to a cluster of liquidation levels, there’s an increased risk of those levels being triggered, potentially causing a sharp further drop due to cascading liquidations.
Strategic Trading: With this information, traders can strategically place their own stop losses or prepare to enter trades. Knowing where others might be forced to close their positions can help in predicting bullish or bearish movements.
Risk Management: Understanding liquidation levels helps in managing your own risk. Setting stop losses away from common liquidation points can avoid being caught in volatile price swings caused by mass liquidations.
- Mxwll Capital
[AlbaTherium] MTF External Ranges Analysis - ERA-Orion for SMC MTF External Ranges Analysis - ERA - Orion for Smart Money Concepts
Introduction:
The MTF External Ranges Analysis - ERA - Orion offers enhanced insights into multi-timeframe external structure points, swing structure points, POIs (Points of Interest), and order blocks (OB) . By incorporating this enhancement, your multi-timeframe analysis are streamlined, simplifying the process and reducing chart workload, no need for manual chart drawing anymore, stay focus on Low Time Frame and get High Time Frame insights in one single Time frame.
This identification process remains effective even when focusing on Lower Time Frames (LTF), providing detailed insights without sacrificing the broader market perspective.
The MTF External Ranges Analysis - ERA – Orion is specifically designed to be used in conjunction with OptiStruct™ Premium for Smart Money Concepts . This strategic combination enhances the workflow of identifying optimal entry points. OptiStruct acts as the analysis tool for Lower Time Frames (LTF), zeroing in on immediate interest areas, while Orion expands this analysis to Higher Time Frames (HTF), providing a broader view of market trends and importants key levels . The integration of Orion with OptiStruct seamlessly merges LTF and HTF analyses, ensuring a thorough understanding of market dynamics for informed and strategic decision-making. This toolkit in one package assembly is pivotal for traders relying on Smart Money Concepts, offering unmatched clarity and actionable insights to navigate the markets effectively.
This tool offers an advanced smart money technical analysis to improve your trading experience. It introduces four key concepts:
Main Features:
Entries Enhancements
Inducements HTF
High/Low Markings HTF
Multiple Timeframes and Confluences on Extreme, Dec and SMT Order Blocks
By integrating these concepts into one, traders can identify high-probability zones across multiple timeframes and develop a thorough understanding of market dynamics. These confluence zones enhance order block skills and potential, establishing them as essential pillars in smart money trading strategies and enabling traders to make more informed decisions.
Settings Overview:
HTF Settings Enable HTF Analysis
Select timeframe {Select or 4H Chart}
Labels Alignment for Lines and Boxes
Inside bar ranges HTF
Break of Structure /Change of Character HTF
Inducements HTF
High/Low Markings HTF
High/Low Sweeps HTF
Extreme Order Blocks HTF
Decisional Order Blocks HTF
Smart Money Traps HTF
IDM Demands and Supplies HTF
Historical Order Blocks HTF
OB Mitigation HTF {touch/ extended}
Understanding the Features:
Chapter 1: Entries Enhancements
In this chapter, we delve into strategies to refine trading entries, focusing on the multi-timeframe analysis of extreme or decisional order blocks in the High Time Frame timeframe as a key point of interest. We highlight the significance of transitioning to the Low Time Frame chart for observing pivotal shifts in market behavior. By examining these concepts, traders can gain deeper insights into market dynamics and make more informed entries decisions at critical junctures.
Practical Example:
We had an Order Block Extreme on the 1-hour timeframe, and currently, we are on the recommended chart for trade entry, which is the 5-minute timeframe. We are patiently waiting to observe a 5-minute ChoCh in the market to enter a buying position since it's an OB Extreme Demand on the 1-hour timeframe. Here, it's crucial and important to focus on the entry timeframe rather than checking what's happening in the higher timeframe. The indicator facilitates this task as it provides us with real-time perspective and visibility of everything happening in the higher timeframe.
Chapter 2: Inducements HTF
It is important and useful to be aware of the various liquidity points across the different timeframes we use; sometimes, a reliable entry point in the Lower Time Frame (LTF) may be surrounded by inducements. Consequently, this point becomes unreliable, and prior to the arrival of this functionality, such anomalies could not be detected, especially when focusing on the market in the LTF. From now on, there will be no more such issues.
Practical Example:
Suppose we identify an Order Block Extreme on the 5M timeframe, indicating a potential entry level. However, when we switch to the 5M timeframe to look for an entry point, we observe an accumulation of inducements around this Order Block coming from a higher timeframe, whether it's M15 or H1. This suggests a potential weakness in the entry point and significant market liquidity, which will act as a trap zone. Before the introduction of this feature, we might have missed this crucial observation, but now we can detect these anomalies and adjust our strategy accordingly.
The only practical way to see theses confluences is to use this Indicator, see the example below
Chapter 03: High/Low – Bos - ChoCh Markings HTF
The High/Low Markings HTF feature in the MTF External Ranges Analysis - ERA - Orion provides a comprehensive view into the market's heartbeat across different timeframes, right from within the convenience of the Lower Time Frame (LTF). It meticulously highlights pivotal shifts, allowing traders to seamlessly discern market sentiment and anticipate potential price reversals without needing to toggle between multiple charts. This innovation ensures that critical market movements and sentiment across various timeframes are visible and actionable from a single, focused LTF perspective, enhancing decision-making and strategic planning in trading activities.
Understanding High/Low Markings in HTF Analysis
High/Low Markings in High Time Frame (HTF) analysis mark the market's extremities within a given period, pinpointing potential areas for reversals or continuation and delineating crucial support and resistance levels. These markings are not arbitrary but represent significant market responses, serving as essential indicators for traders and analysts to gauge market momentum and sentiment.
The Role of HTF in Market Analysis
HTF analysis extends a comprehensive view over market movements, distinguishing between ephemeral fluctuations and substantial trend shifts. By scrutinizing these high and low points across wider time frames, analysts can unravel the underlying market momentum, enabling more strategic, informed trading decisions.
Identifying High/Low Markings
Identifying these crucial points entails detailed chart analysis over extended durations—daily, weekly, or monthly. The search focuses on the utmost highs and lows within these periods, which are more than mere points on a chart. They are significant market levels that have historically elicited robust market reactions, serving as key indicators for future market behavior.
Real-world Example:
Chapter 04: Multiple Timeframes and Confluences on Extreme, Dec and SMT Order Blocks Across HTF
The Orion indicator serves as a bridge between the multiple dimensions of the market, enabling a unified and strategic interpretation of potential movements. It's an indispensable tool for those seeking to capitalize on major opportunity zones, where the convergence of diverse perspectives creates ideal conditions for significant market movements.
Designed to navigate through the data of different timeframes and market analysis, Orion provides a clear and consolidated view of major points of interest. With this indicator, traders can not only spot opportunity zones where consensus is strongest but also adjust their strategies based on the dynamic interaction of various market participants, all while remaining within the Lower Time Frame (LTF).
Conclusion:
MTF External Ranges Analysis - ERA - Orion for Smart Money Concepts as “ The Orion ” indicator captures consensus among scalpers, day traders , swing traders, and investors, turning key areas into major opportunities. It allows for precise identification of areas of interest by analyzing the convergence of actions from various market participants. In short, Orion is crucial for detecting and leveraging the most promising points of convergence in the market.
This identification occurs even while focusing on Lower Time Frames (LTF), allowing for detailed insights without losing the broader market perspective.
This document provides an extensive overview of MTF External Ranges Analysis - ERA - Orion , emphasizing its importance in comprehending market dynamics and utilizing essential smart money concepts trading principles.
Order Chain [Kioseff Trading]Hello!
This indicator "Order Chain" uses live tick data (varip) to retrieve live tick volume.
This indicator must be used on a live market with volume data
Features
Live Tick Volume
Live Tick Volume Delta
Orders are appended to boxes, whose width and height are scaled proportional to the size of the order.
CVD recorded at relevant tick levels
Order chain spans up to 450 ticks (might include aggregates)
The image above shows key features for the indicator!
The image above explains line and color placements.
The image above shows the indicator in action for a live market!
How It Works
The indicator records the difference in volume from "now" and the previous tick. Predicated on whether the "now" price is greater than or less than price one tick prior, the difference in volume is recorded as "buy" or "sell" volume.
This filled order (or aggregates) is colored in congruence with price direction. The filled order is subsequently appended to its relevant tick level and added (buy order) or subtracted (sell order) from the CVD value at the identified tick level.
Of course, thank you to @PineCoders and @RicardoSantos for their awesome libraries :D
Thank you!
CBO (Candle Bias Oscillator)The Candle Bias Oscillator (CBO) with volume and ATR scaling is a unique technical analysis tool designed to capture market sentiment through the analysis of candlestick patterns, volume momentum, and market volatility. This indicator is built on the foundation of assessing the bias within a candlestick's body and wicks, adjusted for market volatility using the Average True Range (ATR), and further refined by comparing the Rate of Change (ROC) in volume and the adjusted bias. The culmination of these calculations results in the CBO, a smoothed oscillator that highlights potential market turning points through divergence analysis.
Key Features:
Bias Calculations: Utilizes the relationship between the candle's body and wicks to determine the market's immediate bias, offering a nuanced view beyond simple price action. Have you ever wanted to quantify exactly how bullish or bearish a particular candle or candlestick pattern is? Whether it's dojis, hammers, engulfing, gravestones, evening morning star, three soldiers etc. you don't have to memorize 50 candlestick patterns anymore.
Volatility Adjustment: Employs the ATR to adjust the bias calculation, ensuring the oscillator remains relevant across varying market conditions by accounting for volatility.
Momentum and Divergence: Measures the momentum in volume and bias through ROC calculations, identifying divergence that may signal reversals or significant price movements.
Signal Line: A smoothed version of the CBO, derived from its own values, serving as a benchmark for identifying potential crossovers and divergences.
Utility and Application:
The CBO with Divergence Scaling is developed for traders who seek a deeper understanding of market dynamics beyond price movements alone. It is particularly useful for identifying potential reversals or continuation patterns early, by highlighting divergence between market sentiment (as expressed through candlestick bias) and actual volume movements. In this way, it aligns us retail traders with institutional traders and smart money. This indicator is versatile and can be applied across various time frames and market instruments, offering value to both short-term traders and long-term investors.
How to Use:
Trend Identification: The direction and value of the CBO provide insights into the prevailing market trend. A positive oscillator value may indicate bullish sentiment, while a negative value suggests bearish sentiment.
Signal Line Crossovers: Crossovers between the CBO and its signal line can be used as potential buy or sell signals. A crossover above the signal line might indicate a buying opportunity, whereas a crossover below could suggest a selling point.
Divergence: Discrepancies between the CBO and price action (especially when confirmed by volume ROC) can highlight potential reversals.
Customization and Parameters: This script allows users to adjust several parameters, including oscillator periods, signal line periods, ATR periods, and ROC periods for divergence, to best fit their trading strategy and the characteristics of the market they are analyzing.
Conclusion:
The Custom Bias Oscillator with Divergence Scaling is a comprehensive tool designed to offer traders a multi-faceted view of market conditions, combining elements of price action, volatility, and momentum. By integrating these aspects into a single indicator, it aims to provide a more rounded and actionable insight into market trends and potential turning points.
To comply with best practices and ensure clarity regarding the informational nature of the Custom Bias Oscillator (CBO) tool, it's crucial to include a disclaimer about the non-advisory nature of the script. Here's a suitable disclaimer that you can add to the end of your script description or publication:
Disclaimer:
The Custom Bias Oscillator (CBO) with Divergence Scaling and its accompanying analysis are provided as tools for educational and informational purposes only and should not be construed as financial advice. The creator of this indicator does not guarantee any specific outcomes or profit, and all users should be aware of the risks involved in trading and investing. Users should conduct their own research and consult with a professional financial advisor before making any investment decisions. The use of this indicator is at the user's own risk, and the creator bears no responsibility for any direct or consequential loss arising from any use of this tool or the information provided herein.
Standardized Orderflow [AlgoAlpha]Introducing the Standardized Orderflow indicator by AlgoAlpha. This innovative tool is designed to enhance your trading strategy by providing a detailed analysis of order flow and velocity. Perfect for traders who seek a deeper insight into market dynamics, it's packed with features that cater to various trading styles. 🚀📊
Key Features:
📈 Order Flow Analysis: At its core, the indicator analyzes order flow, distinguishing between bullish and bearish volume within a specified period. It uses a unique standard deviation calculation for normalization, offering a clear view of market sentiment.
🔄 Smoothing Options: Users can opt for a smoothed representation of order flow, using a Hull Moving Average (HMA) for a more refined analysis.
🌪️ Velocity Tracking: The indicator tracks the velocity of order flow changes, providing insights into the market's momentum.
🎨 Customizable Display: Tailor the display mode to focus on either order flow, order velocity, or both, depending on your analysis needs.
🔔 Alerts for Critical Events: Set up alerts for crucial market events like crossover/crossunder of the zero line and overbought/oversold conditions.
How to Use:
1. Setup: Easily configure the indicator to match your trading strategy with customizable input parameters such as order flow period, smoothing length, and moving average types.
2. Interpretation: Watch for bullish and bearish columns in the order flow chart, utilize the Heiken Ashi RSI candle calculation, and look our for reversal notations for additional market insights.
3. Alerts: Stay informed with real-time alerts for key market events.
Code Explanation:
- Order Flow Calculation:
The core of the indicator is the calculation of order flow, which is the sum of volumes for bullish or bearish price movements. This is followed by normalization using standard deviation.
orderFlow = math.sum(close > close ? volume : (close < close ? -volume : 0), orderFlowWindow)
orderFlow := useSmoothing ? ta.hma(orderFlow, smoothingLength) : orderFlow
stdDev = ta.stdev(orderFlow, 45) * 1
normalizedOrderFlow = orderFlow/(stdDev + stdDev)
- Velocity Calculation:
The velocity of order flow changes is calculated using moving averages, providing a dynamic view of market momentum.
velocityDiff = ma((normalizedOrderFlow - ma(normalizedOrderFlow, velocitySignalLength, maTypeInput)) * 10, velocityCalcLength, maTypeInput)
- Display Options:
Users can choose their preferred display mode, focusing on either order flow, order velocity, or both.
orderFlowDisplayCond = displayMode != "Order Velocity" ? display.all : display.none
wideDisplayCond = displayMode != "Order Flow" ? display.all : display.none
- Reversal Indicators and Divergences:
The indicator also includes plots for potential bullish and bearish reversals, as well as regular and hidden divergences, adding depth to your market analysis.
bullishReversalCond = reversalType == "Order Flow" ? ta.crossover(normalizedOrderFlow, -1.5) : (reversalType == "Order Velocity" ? ta.crossover(velocityDiff, -4) : (ta.crossover(velocityDiff, -4) or ta.crossover(normalizedOrderFlow, -1.5)) )
bearishReversalCond = reversalType == "Order Flow" ? ta.crossunder(normalizedOrderFlow, 1.5) : (reversalType == "Order Velocity" ? ta.crossunder(velocityDiff, 4) : (ta.crossunder(velocityDiff, 4) or ta.crossunder(normalizedOrderFlow, 1.5)) )
In summary, the Standardized Orderflow indicator by AlgoAlpha is a versatile tool for traders aiming to enhance their market analysis. Whether you're focused on short-term momentum or long-term trends, this indicator provides valuable insights into market dynamics. 🌟📉📈
Whalemap [BigBeluga]The Whalemap indicator aims to spot big buying and selling activity represented as big orders for a possible bottom or top formation on the chart.
🔶 CALCULATION
The indicator uses volume to spot big volume activity represented as big orders in the market.
for i = 0 to len - 1
blV.vol += (close > close ? volume : 0)
brV.vol += (close < close ? volume : 0)
When volume exceeds its own threshold, it is a sign that volume is exceeding its normal value and is considered as a "Whale order" or "Whale activity," which is then plotted on the chart as circles.
🔶 DETAILS
The indicator plots Bubbles on the chart with different sizes indicating the buying or selling activity. The bigger the circle, the more impact it will have on the market.
On each circle is also plotted a line, and its own weight is also determined by the strength of its own circle; the bigger the circle, the bigger the line.
Old buying/selling activity can also be used for future support and resistance to spot interesting areas.
The more price enters old buying/selling activity and starts producing orders of the same direction, it might be an interesting point to take a closer look.
🔶 EXAMPLES
The chart above is showing us price reacting to big orders, finding good bottoms in price and good tops in confluence with old activity.
🔶 SETTINGS
Users will have the options to:
Filter options to adjust buying and selling sensitivity.
Display/Hide Lines
Display/Hide Bubbles
Choose which orders to display (from smallest to biggest)
Footprint Chart + Volume ProfileFootprint charts provide volume information to candlestick charts. This indicator specifically provides the quantity of Market Orders executed on each side of the Order Book, thereby showing you the number of contracts that had hit the bid or the offer - and it does so on each bar.
In addition, it visualises a Volume Profile for each bar, providing you an even better visualisation, contrasted to that which renders the numbers alone.
This Footprint Chart calculates executed orders by getting the change in volume for every price move and pooling them on their corresponding "tick bucket". Their specific "tick bucket" is calculated on the nearest "tick", the size of which you will provide by setting the "Tick Size/ Increment" to whichever tick size you need .
For instance, volume changes on a price of 10.4 on a 1 tick Footprint Chart will be recorded as part of the nearest whole number(10), while on a 3 tick Footprint Chart, it will be recorded as part of 9 as it is the nearest multiple of 3.
Calculating the "tick bucket" this way is most conservative, however, if you would like it calculated differently — Having the volume changes recorded on the succeeding tick, e.g. Recording 10.4 as 12 on a 3 tick Footprint Chart. Simply set the "Tick Basket Assignment" to "Next Tick", While setting the same to "Previous Tick" records volume changes on the preceding tick. Default is "Nearest Tick".
How to read the Footprint Chart?
This Footprint Chart depicts a portion of the Depth of Market, arranged in such a way that the left side represents the bid, while the right side represents the ask. It is therefore natural that orders hitting the bid (Market Sells) are to be placed on the Left Side of the chart while orders hitting the ask (Market Buys) are to be placed on the Right Side. This way, you can visualise how the current price came to be, as well as observe with the several order flow analysis concepts and ideas you can apply. In summary, numbers on the Left represents Sell Orders and numbers on the Right represents Buy Orders.
If, however, you wish to see only the total volume that transacted within the bar, you may do so by toggling the "Split Buy and Sell" option.
Footprint Chart showing only the total volume:
Furthermore, this chart has its own candles, the width of which can be adjusted accordingly.
Volume Profile
This Footprint Chart offers a Stacked Volume Profile and an Unstacked Volume Profile, the former renders a Volume Profile which compares the buys from the sells, the better to visualise levels of activity, the latter renders a standard Volume Profile which shows the total volume that transacted on a price tick.
The type of Volume Profile that this Footprint Chart renders is similar to that of a Periodic Volume Profile, which renders Volume Profiles for every bar on the chart. Furthermore, the width of each Volume Profile bar of this Footprint Chart is relative to the largest volume transacted on the current session, the session beginning from the point you have opened the Footprint Chart until the 500th bar, capped for optimisational purposes, and shall adjust the session start accordingly once this limit had been reached. The Volume Profile bars' width will therefore change agreeably to each significant volume update, and sized relatively with that of the others.
Optimisation
This Footprint Chart utilises several drawings and calculations for attaining its visuals, the arrangement of which makes it more pleasing and easier to understand. Several optimisations have been implemented within the code, e.g. utilising queues, however, if you wish for it to be even more optimised, you can use an "Unstacked" Volume Profile, using larger tick sizes, as well as using 0 decimal placements for the Footprint Chart.
Furthermore, deselecting "Use Stacked Bars" will allow more boxes to be drawn, and will double the amount of boxes the volume profile can use.
Limitations
No historical tick data have yet been made available for use and so this Footprint Chart only has realtime data at its disposal. Historical footprints are therefore not rendered, the boundary of which is delineated by a vertical broken line.
Tips
This Footprint Chart is best viewed on a chart of its own, and it is therefore ideal to clear the chart of other candles by hiding them or utilising a line chart alternatively . In addition, stretch the time scale to its utmost capacity, the better to see properly the Volume Profile, as well as stretch the price scale to a proper height, the better to read the footprint volumes inscribed on the indicator.
Warnings
Changing settings may cause the Footprint Chart to reset. If, in case you have been accumulating Footprint Charts and wish to change some settings for the benefit of your charting, it is best to take a snapshot of your chart prior, for recent changes may cause resets to occur.
Trend Flow Profile [AlgoAlpha]Description:
The "Trend Flow Profile" indicator is a powerful tool designed to analyze and interpret the underlying trends and reversals in a financial market. It combines the concepts of Order Flow and Rate of Change (ROC) to provide valuable insights into market dynamics, momentum, and potential trade opportunities. By integrating these two components, the indicator offers a comprehensive view of market sentiment and price movements, facilitating informed trading decisions.
Rationale:
The combination of Order Flow and ROC in the "Trend Flow Profile" indicator stems from the recognition that both factors play critical roles in understanding market behavior. Order Flow represents the net buying or selling pressure in the market, while ROC measures the rate at which prices change. By merging these elements, the indicator captures the interplay between market participants' actions and the momentum of price movements, enabling traders to identify trends, spot reversals, and gauge the strength of price acceleration or deceleration.
Calculation:
The Order Flow component is computed by summing the volume when prices move up and subtracting the volume when prices move down. This cumulative measure reflects the overall order imbalance in the market, providing insights into the dominant buying or selling pressure.
The ROC component calculates the percentage change in price over a given period. It compares the current price to a previous price and expresses the change as a percentage. This measurement indicates the velocity and direction of price movement, allowing traders to assess the market's momentum.
How to Use It?
The "Trend Flow Profile" indicator offers valuable information to traders for making informed trading decisions. It enables the identification of underlying trends and potential reversals, providing a comprehensive view of market sentiment and momentum. Here are some key ways to utilize the indicator:
Spotting Trends: The indicator helps identify the prevailing market trend, whether bullish or bearish. A consistent positive (green) histogram indicates a strong uptrend, while a consistent negative (red) histogram suggests a robust downtrend.
Reversal Signals: Reversal patterns can be identified when the histogram changes color, transitioning from positive to negative (or vice versa). These reversals can signify potential turning points in the market, highlighting opportunities for counter-trend trades.
Momentum Assessment: By observing the width and intensity of the histogram, traders can assess the acceleration or deceleration of price momentum. A wider histogram suggests strong momentum, while a narrower histogram indicates a potential slowdown.
Utility:
The "Trend Flow Profile" indicator serves as a valuable tool for traders, providing several benefits. Traders can easily identify the prevailing market trend, enabling them to align their trading strategies with the dominant direction of the market. The indicator also helps spot potential reversals, allowing traders to anticipate market turning points and capture counter-trend opportunities. Additionally, the green and red histogram colors provide visual cues to determine the optimal duration of a long or short position. Following the green histogram signals when in a long position and the red histogram signals when in a short position can assist traders in managing their trades effectively. Moreover, the width and intensity of the histogram offer insights into the acceleration or deceleration of momentum. Traders can gauge the strength of price movements and adjust their trading strategies accordingly. By leveraging the "Trend Flow Profile" indicator, traders gain a comprehensive understanding of market dynamics, which enhances their decision-making and improves their overall trading outcomes.
Liquidity composition / quantifytools- Overview
Liquidity composition divides each candle into sections that are used to display transaction activity at price. In simple terms, an X-ray through candle is formed, revealing the orderflow that built the candle in greater detail. Liquidity composition consists of two main components, lots and columns. Lots and columns can be used to visualize user specified volume types, currently supporting net volume and volume delta. Lots and columns can be used to visualize same or different volume types, allowing a combination of volume footprint, volume delta footprint and volume profile in one single view. Liquidity composition principally works on any chart, whether that is equities, currencies, cryptocurrencies or commodities, even charts with no volume data (in which case volatility is used to approximate transaction activity). The script also works on any timeframe, from minute charts to monthly charts. Orderflow can be observed in real-time as it develops and none of the indications are repainted.
Example: Displaying same volume types on lots and columns
Example: Displaying different volume types on lots and columns
Liquidity composition supports user specified derivative data, such as point of control(s) and net activity coloring. Derivative data can be calculated based on either net volume or volume delta, resulting in different highlights.
With net volume, volume delta and derivative data in one view, key orderflow events such as delta imbalances, high volume nodes, low volume nodes and point of controls can be used to quickly identify accumulation/distribution, imbalances, unfinished/finished auctions and trapped traders.
Accessing script 🔑
See "Author's instructions" section, found at bottom of the script page.
Key takeaways
- Liquidity composition breaks down transaction activity at price, measured in net volume or volume delta
- Developing activity can be observed real-time, none of the indications are repainted
- Transaction activity is calculated using volumes accrued in lower timeframe price movements
- Lots and columns can be used to display same or different volume types (e.g. volume delta lots and net volume columns) in single view
- Users can specify derivative data such as volume delta POCs, net volume POC and net activity coloring
- For practical guide with practical examples, see last section
Disclaimer
Orderflow data is estimated using lower timeframe price movement. While accurate and useful, it's important to note the calculations are estimations and are not based on orderbook data. Estimates are calculated by allotting volume developing on lower timeframe chart to its respective section based on closing price. Volume delta (difference between buyers/sellers) is calculated by subtracting down move volumes (sell volume) from up move volumes (buy volume). Accuracy of the orderflow estimations largely depends on quality of lower timeframe chart used for calculations, which is why this tool cannot be expected to work accurately on illiquid charts with broken data.
Liquidity composition does not provide a standalone trading strategy or financial advice. It also does 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. Liquidity composition should be viewed as one tool providing one kind of evidence, to be used in conjunction with other means of analysis.
- Example charts
Chart #1: BTCUSDT
Chart #2: EURUSD
Chart #3: ES futures
- Calculations
By default, size of sections and lower timeframe accuracy are automatically determined for all charts and timeframes. Number of lower timeframe price moves used for calculating orderflow is kept at fixed value, by default set to 350. Accuracy value dictates how many lower timeframe candles are included in the calculation of volume at price. At 350, the script will always use 350 lower timeframe price movements in calculations (when possible). When calculated dynamic timeframe is less than 1 minute, the script switches to available seconds based timeframes. Minimum dynamic timeframe can be capped to 1 minute (as seconds based timeframes are not available for all plans) or dynamic timeframe can be overridden using an user specified timeframe.
Example: Calculating dynamic lower timeframe
Main chart: 4H / 240 minutes
Accuracy value: 100
Formula: 240 minutes / 100 = 2.4 minutes
Timeframe used for calculations = 2 minutes
Section size is automatically determined based on typical historical candle range, the bigger it is, the bigger the section size as well. Like dynamic timeframe, automatic section size can be manually overridden by user specified size expressed in ticks (minimum price unit). Users can also adjust sensitivity of automatic sizing by setting it higher (smaller sections, more detail and more noise) or lower (less sections, less detail and less noise). Section size and dynamic timeframe can be monitored via metric table.
Volume at price is calculated by allotting volume associated with a lower timeframe price movement to its respective section based on closing price (volume is stored to the section that covers closing price). When used on a chart with no volume data, volatility is used instead to determine likely magnitude of participation. Volume delta (difference between buyers/sellers) is calculated by subtracting down move volumes (sell volume) from up move volumes (buy volume). Volumes accrued in sections are monitored over a longer period of time to determine a "normal" amount of activity, which is then used to normalize accrued volumes by benchmarking them against historical values.
Volume values displayed on the left side represent how close or far volume traded at given section is to an extreme, represented by value of 10 . The more value exceeds 10, the more extreme transaction activity is historically. The lesser the value, the less extreme (and therefore more typical) transaction activity is. Users can adjust sensitivity of volume extreme threshold, either by increasing it (more transaction activity is needed to constitute an extreme) or decreasing it (less transaction activity is needed to constitute an extreme).
Example: Interpreting volume scale
0 = Very little to no transaction activity compared to historical values
5 = Transaction activity equal to average historical values
10 = Transaction activity equal to an extreme in historical values
10+ = The more transaction activity exceeds value of 10, the more extreme it is historically
Accuracy of orderflow data largely depends on quality of lower timeframe data used in calculations. Sometimes quality of underlying lower timeframe data is insufficient due to suboptimal accuracy or broken lower timeframe data, usually caused by illiquid charts with gaps and inconsistent values. Therefore, one should always ensure the usage of most liquid chart available with no gaps in lower timeframe data. To combat poor orderflow data, a simple data quality check is conducted by calculating percentage of sections with volume data out of all available sections. Idea behind the test is to capture instances where unusual amount of sections are completely empty, most likely due to data gaps in LTF chart. E.g. 90% of sections hold some volume data, 10% are completely empty = 90% data quality score.
Data quality score should be viewed as a metric alerting when detail of underlying data is insufficient to consider accurate. When data quality score is slightly below threshold, lower timeframe chart used for calculations is likely fine, but accuracy value is too low. In this case, one should increase accuracy value or manually override used timeframe with a smaller one. When data quality score is well below threshold, lower timeframe chart used for calculations is likely broken and cannot be fixed. In this case, one should look for alternative charts with more reliable data (e.g. ES1! -> SPY, BITSTAMP:BTCUSD -> BINANCE:BTCUSDT).
Example : When insufficient data quality scores can/cannot be fixed
- Derivative data
Point of control
Point of control, referring to point in price where transaction activity is highest, can be calculated based on the volume type of lots or columns (based on net volume or volume delta). Depending on the calculation basis, displayed point of controls will vary. POC calculated based on net volume is no different from traditional POC, it is simply the section with highest amount of transaction activity, marked with an X. When calculating POC based on volume delta, the script will highlight two point of controls, named leading and losing point of control . Leading POC refers to lot with highest amount of volume delta, marked with an X. If leading POC was net buy volume, losing POC is marked on section with highest net sell volume, marked with S respectfully. Same logic applies in vice versa, if leading POC is net sell volume, losing POC is marked on highest buy volume section, using the letter B.
Net activity
Similarly to point of control calculation, net activity can be calculated based on either volume types, lots or columns. When calculating net activity based on net volume, candles will be colorized according to magnitude of total volume traded. When calculating net activity based on volume delta, candles will be colorized according to side with most volume traded (buyers or sellers). Net activity color can be applied on borders or body of a candle.
- Visuals
Lots, columns, candles and POCs can be colorized using a fixed color or a volume based dynamic color, with separate color options for buy side volume, sell side volume and net volume.
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 offsets for visuals are fully customizable using settings menu.
- Practical guide
OHLC data (candles) is a simple condensed visualization of an auction market process. Candles show where price was in the beginning of an auction period (timeframe), the highest/lowest point and where price was at the end of an auction. The core utility of Liquidity composition is being able to view the same auction market process in much greater detail, revealing likely intention, effort and magnitude driving the process. All basic orderflow concepts, such as ones presented by auction market theory can be applied to Liquidity composition as well.
The most obvious and easy to spot use case for orderflow tools is identifying trapped traders/absorption, seen in high transaction activity at the very highs/lows of a candle or even better, at wicks. High participation at wicks can be used to identify forced orders absorbed into limit orders, idea behind being that when high transaction activity is placed at a wick, price went one direction with a lot of participation (high effort) and came right back up (low impact) within the same time period.
Absorption can show itself in many ways:
- Extreme buy volume sections at wick highs or buy side POC at wick highs
- Multiple, clustered high buy volume sections (but not extreme) at wick highs
- Positive net volume delta into a reversal down
- Extreme sell volume sections at wick lows or sell side POC at wick lows
- Multiple, clustered high sell volume sections (but not extreme) at wick lows
- Negative net volume delta into a reversal up
- Extreme net volume sections at or net volume POC at wick highs/lows
- Extreme net volume into a reversal up/down
For accurate analysis, orderflow based events should be viewed in the context of price action. To identify absorption, it's best to look for opportunities where an opposing trend is clearly in place, e.g. absorption into highs on an uptrend, absorption into lows on a downtrend. When price is ranging without a clear trend or there's no opposing trend, extreme activity at an extreme end of a candle might be aggressive participants attempting to initiate a new trend, rather than getting absorbed in the same sense. With enough effort put into pushing price to the opposite direction at overextended price, a shift in trend direction might be near.
Price action based levels are a great way to get context around orderflow events. Simple range highs/lows as a single data point serve as a high probability regimes for reversals, making them a great point of confluence for identifying trapped traders.
Low to zero volume sections can be used to identify points in price with little to no trading, leaving a volume null/void behind. Typically sections like these represent gaps on a lower timeframe chart, which can be used as reference levels for targets and support/resistance.
Net volume can be used for same purposes as above, but for determining general intention of market participants it's a much more suitable tool than volume delta. According to auction market theory, low/no participation is considered to reject prices and high participation is considered to accept prices. With this concept in mind, unfinished auctions occur when participation is high at highs or high at lows, idea behind being that participants are showing willingness and interest to trade at higher or lower prices. Auction is considered finished when the opposite is true, i.e. when participants are not showing willingness to trade at higher/lower prices. In general, direction of unfinished auctions can be expected to continue shortly and direction of unfinished auctions can be expected to hold.
While shape of volume delta and net volume are usually similar, they're not the same thing and do not represent the same event under the hood. Volume delta at 0 does not necessarily mean participation is 0, but can also mean high participation with equal amount of buying and selling. With this distinction in mind, using volume delta and net volume in tandem has the benefit of being able to identify points in price with a lot of up and down price movement packed into a small area, i.e. consolidation. Points in price where price hangs around for an extended period of time can be used to identify levels of interest for re-tests and breakout opportunities.
Open interest flow / quantifytools- Overview
Open interest flow detects inflows (positions opening) and outflows (positions closing) using open interest and estimates delta (net buyers/sellers) for the flows. Users are able to choose any open interest source available on Tradingview, by default set to BTCUSDT OI fetched from Binance. Using historical open interest flows, bands depicting typical magnitude of flows are formed for benchmarking intensity of flows. On the inflow side, +1 represents average inflows while +2 represents 2x above average inflows, a level considered an extreme. In a vice versa manner, -1 represents average outflows while -2 represents 2x above average outflows. Extreme inflows indicate aggressive position opening, in other words exuberance. Extreme outflows on the other hand indicate forced exiting of positions, in other words liquidations.
- Concept
Open interest flow is calculated using position of OI source relative to its moving average (by default set to SMA 10), referred to as relative open interest from hereon. When relative OI is positive (open interest is above its moving average), new positions are considered to enter the market. When relative OI is negative (open interest is below its moving average), existing positions are considered to exit the market. Open interest delta (side opening/closing positions, either net buyers/sellers) is calculated using relative price in a similar fashion to relative OI, but using close of viewed symbol as source. Price is considered to be up when relative price is positive, down when relative price is negative. Using relative OI and relative price in tandem, the following assumptions are applied:
Price up, open interest up = longs entering market
Price down, open interest up = shorts entering market
Price down, open interest down = longs exiting market
Price up, open interest down = shorts exiting market
Bands depicting magnitude of open interest flows are calculated using average turning points in relative OI. +1 and -1 represent levels where flows on average turn towards mean rather than continue to increase/decrease. These levels are then multiplied up to +2 and -2, representing two times larger deviations from the normal. When inflows are above 1, positions opening have reached a point where flows historically turn down. Therefore, anything above 1 would be abnormal amount of open interest entering, an extreme stretch being at 2 or above. Same logic applies to outflows, but in a vice versa manner (below -1 abnormal, extreme at -2)
Flow bursts further refine indications of aggressive inflows/outflows by taking into account change in open interest flows. Burst indications are activated when open interest is above its average turning point, coupled with a sufficient increase/decrease in flows simultaneously. Bursts are essentially a filtered version of abnormal flows and therefore a more reliable indication of exuberance/liquidations. Burst sensitivity can be adjusted via input menu, available in 5 settings. 1 sets OI burst requirements to loosest (more signals, more noise) while 5 sets OI burst requirements to strictest (less signals, less noise). Exact criteria applied to bursts can be viewed via input menu tooltip.
- Features
Users can opt for OI source auto-select for CRYPTO/USDT pairs. When auto-select is enabled and another chart is opened, corresponding open interest source is automatically selected as long as requirements mentioned above are met.
Open interest flows can be visualized as chart color, available separately for flow states and flow bursts.
Relative price line and flow guidelines (reminders for flow interpretation) can be enabled via input menu. All colors are customizable.
- Alerts
Available alerts are the following:
- Abnormal long inflows/outflows
- Abnormal short inflows/outflows
- Abnormal inflows/outflows from either side
- Aggressive longs/shorts (flow burst up)
- Liquidated longs/shorts (flow burst down)
- Aggressive or liquidated longs/shorts
- Practical guide
Open interest as a standalone data point does not reveal which side is likely opening/exiting positions and how extreme the participant behavior is. Using the additional data provided by open interest flows, moments of greed and fear can be detected. Smart money does not short into dips and buy into rips. When buyers or sellers have participated in a large move and continue to show interest even when efforts are not rewarded at an already overextended price, participants are asking for trouble.
Similar events can be observed when extreme outflows take place, indicating forced exits such as stop-losses triggering. When enough participants are forced out, price is likely to take the path of least resistance which is to the opposite direction.
Order Block Scanner - Institutional ActivityIntroducing the Order Block Scanner: Unleash the Power of Institutional Insight!
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Institutional trading has long been veiled in secrecy, an exclusive realm accessible only to the chosen few. But with the Order Block Scanner, the doors to this realm swing open, inviting you to step inside and seize the advantage. Our revolutionary technology employs advanced algorithms to scan and analyze market data, pinpointing the telltale signs of institutional activity that can make or break your trades.
Imagine having the power to identify key levels where Institutional and Hedge Funds are initiating significant trades. With the Order Block Scanner, these hidden order blocks are unveiled, allowing you to ride the coattails of the market giants. This game-changing tool decodes their strategies, offering you a window into their actions and allowing you to align your trading decisions accordingly.
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The algorithm operates on data from Options and Darkpool markets, which is first exported to Quandl DB and then imported to TradingView using an API. The indicator also identifies patterns based on volume, volatility, and market movements, increasing the number of identified institutional activities on the markets.
MCumulativeDelta* MCumulativeDelta Indicator *
The MCumulativeDelta Indicator shows the Buying / Selling pressure that is happening in the market. The Delta is powered by the *MBox Precision Delta* Algorithm. This indicator serves to show overall Accumulation and Distribution of the BUYERS and the SELLERS. It becomes possible to gauge if the market is overall Bullish or Bearish. This helps determine trade direction and keeping out of other trades that are counter to what the overall Buying / Selling is showing.
* WHAT THE SCRIPT DOES *
The script draws a histogram that can either be positive or negative. When the histogram is positive it means there are more Buyers in the Market. When the histogram is negative it means there are more sellers in the market. The more positive the histogram gets, the more BUYERS are flooding the market. The more negative the histogram gets, the more SELLERS are flooding the market. When the histogram switches over from negative to positive it is a Bullish sign of Buying. When the histogram switches over from positive to negative, it is a Bearish sign of Selling.
* HOW TO USE IT *
As the histogram becomes more negative, this shows that the SELLERS have taken control of the markets. Conversely, as the histogram becomes more positive, this shows that the Buyers have taken control of the markets. The side that is in control is the direction to generally place trades in, and at the same time filter out trades of the opposite direction.
* HOW IT WORKS *
The MCumulativeDelta histogram on the chart represents overall Buying / Selling. This is the DELTA (difference) between the BUYING and the SELLING. Taking the total BUYING and subtracting the total of SELLING, we produce the DELTA (difference) between the Buying / Selling and this is what is drawn by the histogram.
Unlike other Cumulative Delta indicators which determine delta from the Up / Down wick and just multiply by volume (not a true delta), the MCumulativeDelta indicator uses a sophisticated algorithm that analyzes price movement corresponding to volume movement.
The way the DELTA, BUYING, and SELLING is calculated is computed by the *MBox Precision Delta* Algorithm. The algorithm considers the following data points when making it's computation
1. Price moving up on increasing volume
2. Price moving up on decreasing volume
3. Price moving horizontally on increasing volume
4. Price moving horizontally on decreasing volume
5. Price moving down on increasing volume
6. Price moving down on decreasing volume
Using these data points allows MCumulativeDelta to effectively compute and define the following scenarios
1. Accumulation / Distribution
2. Buying / Selling Exhaustion
3. Buying / Selling EFFORT / NO RESULT
Once the scenario is determined, it will greatly aid in trade decision making. These scenarios are explained in the examples below
* EXAMPLE AND USE CASES *
- Accumulation Example -
When you see a large amount of BUYING (large positive histogram) and price entering an up trend, this is indicative of Accumulation and you would be looking for PULLBACKS to get into the up trend move.
- Distribution Example -
When you see a large amount of SELLING (large negative histogram) and price entering a down trend, this is indicative of Distribution and you would be looking for pullbacks to get into the down trend move.
- Buying EXHAUSTION Divergence -
As price makes higher highs, but the MCumulativeDelta histogram drops (becomes less positive) on the higher highs, it means BUYERS are exhausted. Potentially a reversal or change in behavior in the markets.
- Selling EXHAUSTION Divergence -
As price makes lower lows, but the MCumulativeDelta histogram contracts (becomes less negative) on the lower lows, it means SELLERS are exhausted. Potentially a reversal or change in behavior in the markets.
- BUYING EFFORT / NO RESULT -
As the MCumulativeDelta histogram increases positively, but price fails to make higher highs, it is a sign of EFFORT / NO RESULT on behalf of the Buyers. In this case Buyers are pushing hard to move price up, but are unable to, due to being OVERBOUGHT. If this is accompanied by visible SELLING, it would be a good short entry.
- SELLING EFFORT / NO RESULT -
As the MCumulativeDelta histogram increases negatively, but price fails to make lower lows, it is a sign of EFFORT / NO RESULT on behalf of the Sellers. In this case Sellers are pushing hard to move price down, but are unable to, due to being OVERSOLD. If this is accompanied by visible BUYING, it would be a good long entry.
* SETTING ALERTS *
- FOR CROSSING FROM BUYING TO SELLING OR SELLING TO BUYING -
To be alerted when the histogram crosses over from Buying to Selling (Positive to Negative) or Selling to Buying (Negative to Positive)
1. Right Click Chart -> Add Alert...
2. Select Condition to be "MCumulativeDelta"
3. Select "Crossing" with Value = 0
4. Options set "Once Per Bar Close"
5. Customize Any other Alert Options you want
* AUTHOR *
This script is published by MBoxWave LLC
XPrecisionSwing (XPS)* XPrecisionSwing (XPS) Indicator *
Is a visual representation of the Forces of Supply / Demand in the markets in the form of UP and DOWN waves. The Supply / Demand (denoted by a number on top or below the wave line) is computed using the *MBox Precision Supply / Demand* algorithm. These numbers diligently show the forces of Supply and Demand moving price in the markets. The algorithm for computing the numbers on the top and bottom of the wave lines measures the strength of the Supply / Demand. It is this algorithm that makes this indicator unique as it gives an accurate representation of the forces pulling the market up and down. When forces oppose each other, meaning when the direction of price does not agree with the direction of the Supply or Demand it creates a divergence and an opportunity in the markets. These situations are called BUY / SELL Imbalances. Explanation about this below.
* WHAT THE SCRIPT DOES *
The XPrecisionSwing indicator draws swing waves lines going up and down. These waves lines are representative of Supply and Demand. Waves going up are Demand, while waves going down are Supply. The strength of the Supply / Demand corresponds to the number drawn either on top of the wave line or below it. The numbers drawn on the chart are powered by the *MBox Precision Supply / Demand* algorithm, which are representative of the Forces of Supply / Demand in the markets. This is not just volume added up like in a regular zig zag indicator, since volume alone does not show Supply / Demand, and regular volume will not show BUY / SELL Imbalances as depicted by XPrecisionSwing. Volume summated will not show both positive and negative numbers on the chart. Having Supply / Demand split into both positive and negative numbers allows us to see BUY / SELL Imbalances, which can be a very powerful divergence. Information on how these numbers are computed are in the "HOW IT WORKS" section.
The numbers drawn on the chart can be either negative or positive. Positive relates to Demand, while negative relates to Supply. In this manner the strength of Supply and Demand can be gauged in each wave. If the price goes up but the number is negative (More Supply) it is a divergence and called a SELL Imbalance. This means there was more Supply even though price went up. It is important to pay attention to these scenarios, as often it can be indicative of NO DEMAND. Conversely. if the price goes down but the number is positive (No Demand) it is a divergence and is called a BUY Imbalance. This means there was more Demand even though price went down. This is indicative of NO SUPPLY. As such, it now becomes possible to know when there is a sign of Supply, Demand, No Supply, No Demand, Supply Exhaustion, and Demand exhaustion. Supply occurs when the negative numbers on the charts begin to increase (more negatively). Demand occurs when the positive numbers on the chart begin to increase (more positively). A Supply Exhaustion pattern happens when the price is starting to move down more slowly, while Supply is decreasing, and Demand is increasing. This means that the behavior of the market is changing and also a signal to look to reverse positions. A Demand Exhaustion pattern happens when the price is starting to move up more slowly, while Demand is decreasing, and Supply is increasing. The behavior of the market here is also changing.
* HOW IT WORKS *
- Technical Details for the Numbers on the Swing -
The numbers on the chart represent Supply / Demand. Supply or Demand is determined by analyzing the movement of price and quantity of volume.
When price goes up and is combined with an increase in volume it is Expansion of Demand.
(Positive Numbers get larger)
However if price goes up and is combined with a decrease in volume it is Contraction of Demand.
(Positive Numbers get smaller)
When price goes down and is combined with an increase in volume it is Expansion of Supply.
(Negative Numbers get larger)
However if price goes down and is combined with a decrease in volume it is Contraction of Supply.
(Negative Numbers get smaller)
- Technical Details for the Swing -
The way XPrecisionSwing draws the swings is fractal in nature, which make it very convenient and easier to use over the traditional zig zag indicator. The traditional zig zag indicator uses a tick reversal which needs to be adjusted every time you change time frames. However, with XPrecisionSwing you do not have to change any settings every time you load a different time frame since it will adjust to any time frame you are loading. How the swing is drawn is explained below.
XPrecisionSwing uses 3 bars (by default) to define a swing
This parameter can be adjusted. Can be 1, 2, 4 bars, etc...
Swings are always drawn using High / Low of the bar
- Rules -
To start upswing, bar high needs to be higher than previous 3 candle highs
To start downswing, bar low needs to be lower than previous 3 candle lows
If in upswing, a higher high will continue the upswing
if in downswing, a lower low will continue the downswing
- Exceptions -
If outside bar (both high and low exceeds previous 3 bars) swing will continue in current direction
- Swing Confirmation -
Swing wave line in progress (unconfirmed) is denoted by a brown box around the swing number
Once the brown box disappears, that swing wave and number is confirmed
* HOW TO USE IT *
As the numbers on the down waves increase (negatively), this shows that the bears have taken control of the markets. Conversely, as the numbers on the up waves increase (positively), this shows the bulls have taken control of the markets. Whoever is in control is the direction you generally want to place your trades in. When you see an increase in Supply (numbers on down wave) accompanied with a decrease in Demand (numbers on up wave) this shows a Supply + Demand Exhaustion Pattern. This is stronger than if you only see an increase in Supply without a decrease in Demand.
- The Buy / Sell Imbalances -
If you see a positive blue number on the bottom of a DOWN Wave, this means that there was more buying than selling even though price moved down.
If you see a negative red number on the top of an UP Wave, this means that there was more selling than buying even though price moved up.
Both of these cases signify and imbalance and a divergence.
* EXAMPLE AND USE CASES *
- Sell Imbalance Example -
If you see a large negative number with a lower low on a down wave, and then the next up wave is a lower high also with a negative number it shows that there is only Supply flooding the market and no sign of Demand. This is a very powerful combo.
- Buy Imbalance Example -
If you see a large positive number with a higher high on an up wave, and then the next down wave is a higher low also with a positive number it shows that there is only Demand flooding the market and no sign of Supply. This is a very powerful combo.
- Supply Exhaustion example -
If you see price movement struggling to make newer lows and the Supply numbers on the down waves are decreasing, while the Demand numbers on the up waves are increasing this is indicative of a *Change of Behavior*, and that the market is showing signs of reversal.
- Break out on Demand example -
If you see price has been ranging and now the numbers on the UP waves begin to increase while breaking out of a previous area of resistance, it is a good sign that the movement is backed by the strength coming from the Demand.
* BUY / SELL IMBALANCE ALERTS *
The Green / Red crosses on the chart show exactly where the Buy / Sell Imbalance Alerts trigger.
These will NEVER repaint! The crosses can be hidden in Styles if you wish to.
Alerts can be set very easily with the instructions below.
1. Right Click Chart -> Add Alert...
(Ignore Caution Warning. These alerts will *ONLY* trigger on Confirmed BUY / SELL Imbalances and will NOT repaint)
2. Select Condition to be "XPrecisionSwing"
3. Select "Buy Imbalance" or "Sell Imbalance"
4. Select "Greater Than" with Value = 0
5. Options set "Once Per Bar"
6. Customize Any other Alert Options you want
* WHAT MAKES IT ORIGINAL *
XPrecisionSwing gives an inside look into the markets by showing price movements as a series of waves going up and down with their corresponding Supply / Demand numbers associated with each wave. Reading the numbers shows the strength of Supply / Demand. The bigger the number the stronger the Supply / Demand is. The smaller the number the weaker the Supply / Demand is. It becomes possible to see where Supply / Demand comes in, along with Exhaustion of Supply / Demand to spot opportunities to place trades. The Buy / Sell Imbalances show imbalances where price movement and the direction of the Supply / Demand diverge to create potential opportunities as well.
* AUTHOR *
This script is published by MBoxWave LLC
Initial Balance |ASE|Introduction
Initial Balance (IB) refers to the price data that is formed during the first hour of a trading session. It is an important concept in trading as it provides insights into the market's opening sentiment and potential trading opportunities or reversals for the day. There are multiple trading sessions throughout the day. The most popular, the NY Session, is open from 9:30 am to 4:00pm EST making the Initial Balance(IB) range the first hour (9:30-10:30) The other sessions include London, Tokyo, and Sydney.
IB Customization
The Initial Balance lines are fully customizable to fit the traders need.
Show Initial Balance
This setting will plot the Initial Balance
Fill/Extend IB Range
The Fill IB Range toggle fills the area in between the IB High and IB Low. Use the IB Fill Color option to change the fill color in the “Line Settings” group on the settings panel.
The Extend IB Range extends the IB lines until the market closes.
Show 1x/2x Extensions
The Show 1x Extension toggle displays 1 times the IB range line (IB High - IB Low) above IB High and 1 times the IB range line below IB Low.
The Show 2x Extension toggle displays the 2 times the IB range line (IB High - IB Low) above IB High and 2 times the IB range line below IB Low.
*Use the Extension Level Color in the “Line Settings” to change the color of the lines.
Show Middle Levels
The Show Middle Levels toggle shows all the 50% lines between the upper 2x and upper 1x line, upper 1x and IB high, IB high and IB low, IB low and lower 1x line, and the lower 1x and lower 2x line.
*Use the Mid Level Color in the “Line Settings” to change the color of the lines.
Delete Previous Day’s Levels
This setting will only show the current day's Initial Balance and delete all previous day levels to produce a clean chart.
How To Use:
The Initial Balance Range can support a bias as it shows the opening market sentiment. By watching price action interact with the Initial Balance Range we can watch for indications of trending or failing moves at the high or the low and overall a ranging or trending session.
The extension levels are projections as to where price could potentially reach in a trending market. If we are bullish and trending higher, we would want to see price reach the first extension, signs of strength at these levels can be used as confirmation to target other levels.
Overall, all these levels can and should be used as support and resistance levels, and as always, can not be used by themselves and require additional confirmation, whether that be an indicator or price action. Below you can see chart examples of these levels in action.
