FVG-BPR-Candle Volume-v2 [Elykia]FVG-BPR & Volume Z-Score - SMC Enhanced
This indicator is a complete toolkit for traders using Smart Money Concepts (SMC) and Price Action analysis. It combines three essential elements to identify high-probability zones: Price Inefficiencies (FVG), Balanced Price Ranges (BPR), and Statistical Volume Anomalies (Z-Score).
The goal is simple: Stop trading "blind" levels and start validating every institutional zone with real volume activity.
Key Features
1. 📊 Volume Z-Score (Statistical Analysis):
Colors candles based on volume intensity relative to its historical average (Bollinger/Standard Deviation logic).
Yellow Candles (Z-Score > 2): High volume, significant activity.
Red Candles (Z-Score > 3): Extreme volume, often a sign of "Capitulation" or major impulse.
Circles Option: Displays a circle on extreme candles for enhanced visibility.
2. ⚡ Fair Value Gaps (FVG):
Automatically detects imbalance zones (Buy-side & Sell-side).
Multi-Timeframe (MTF): Ability to display FVGs from a higher timeframe on your current chart (e.g., H1 FVG on M5 chart).
Dynamic Management: Zones automatically delete once filled (mitigated) to keep the chart clean.
3. 🔄 Balanced Price Ranges (BPR):
Identifies zones where a Bullish FVG and a Bearish FVG overlap.
This is a strong institutional signature indicating aggressive re-pricing. BPRs often act as more reliable support/resistance zones than simple FVGs.
💎 Strategy: "Volume-Backed Rebalancing"
This strategy uses the confluence between SMC structure (FVG/BPR) and Volume confirmation.
1. Zone Identification: Wait for price to form a clear BPR or FVG (M15 or H1 recommended).
2. The Retest (Pullback): Wait for price to return to test this zone. Do not enter blindly (Limit Order), wait for the reaction.
3. Volume Confirmation:
Observe the candle colors within the zone.
If price hits the FVG and a Yellow or Red candle (Volume Z-Score) appears rejecting the zone, this is your signal.
This indicates that institutions are actively defending this level.
4. Entry & Exit: Enter at the close of the volume candle. Place Stop Loss below the FVG/BPR. Target the next liquidity pool (Previous High/Low).
⚠️ DISCLAIMER
This script and the strategy described are provided for educational and research purposes only. Trading financial markets (Forex, Crypto, Indices, Futures) involves a high level of risk and may not be suitable for all investors. You may lose all or part of your initial capital.
Past performance is not indicative of future results. The author implies no guarantee of profit or protection from loss. Use this tool at your own risk and always perform your own analysis before taking a position.
Volatilität
ATR Levels Trade PlanOverview
This indicator is a trade management tool designed to help traders visualize volatility-based targets and stop-losses instantly. By anchoring calculations to the Daily Opening Price and the Average True Range (ATR), it projects objective, mathematical support and resistance levels for the current session.
How It Works
The script detects the start of the trading day (or a manually defined period) and draws a vertical marker. From there, it projects horizontal lines representing key multiples of the ATR:
Green Line: Opening Price (The baseline).
Blue Lines (Targets): +0.5 ATR, +1.0 ATR, and +2.0 ATR. These serve as dynamic profit-taking zones based on current market volatility.
Orange Line (Stop Loss): -2.0 ATR. A standard volatility-based stop level.
Red Line (Emergency Exit): -3.0 ATR. A level indicating extreme adverse moves.
Multi-Ticker Database & Date Verification This version includes a built-in configuration menu capable of storing unique trade plans for up to 20 different stocks.
20-Slot Memory: You can pre-load the Ticker Symbol, Planned Open, and ATR for up to 20 individual assets in the settings.
Date/Period of Trade: Each slot includes a "Date" field (YYYYMMDD). This assigns the manual values to a specific trading session.
Default Behavior (Auto-Fallback): The indicator intelligently scans the database when you switch charts.
If the Ticker matches a slot AND the Date matches the current session, it loads your manual values.
If the Ticker is not in the database, or if the Date is expired (from a previous day), the script automatically defaults to the live Daily Open and standard ATR-14.
Key Features
Clean Visuals: Uses the Drawing API to plot lines only on the current/last bar, keeping historical price action clean and uncluttered.
Text Customization: Users can align text to the Right, Left, or Center, adjust the offset distance, and change text size to fit their chart layout.
Flexible Alerts: Includes a dedicated "Alert Configuration" menu. Users can toggle alerts on/off for individual lines (e.g., enable the Stop Loss alert but disable the +0.5 ATR alert). All enabled settings work via a single "Any alert() function call."
Settings
Stock Database: 20 configuration groups to input Ticker, Date, Open, and ATR.
Global/Fallback Values: Input custom Open/ATR prices (leave at 0 for automatic) to be used if the specific stock is not in the database.
Text & Alignment: Adjust label position, offset, and size.
Alert Configuration: Checkboxes to enable/disable alerts for specific price levels.
Methodology The levels are calculated using the standard formula: Level = Opening Price + (Multiplier * ATR)
[longshorti] Auto Fibonacci Grid (Long/Short) 🌟 Auto Fibonacci Grid (Long/Short) — Smart Retracement Tool
The Auto Fibonacci Grid (Long/Short) is an advanced trading utility designed to automate the process of identifying key Fibonacci retracement levels for both bullish and bearish swings. This indicator provides traders with precise zones for potential entries during market corrections.
✨ Key Features and Originality:
True Auto-Detection: The script automatically analyzes the market impulse within the lookback window to determine if the current grid should be calculated for a Bullish (Long) or Bearish (Short) scenario.
Impulse Filtered Alerts: A custom alert system triggers only when the price enters your designated key zone and when the underlying market impulse exceeds a user-defined Minimum Impulse Percentage. This is crucial for filtering out false signals generated by weak, consolidating movements.
Dynamic Correction Zones: Define any range of Fibonacci levels (e.g., 0.5 to 0.618) to be highlighted as your Key Zone (Buy or Sell Zone), with dedicated color schemes for Long and Short setups.
Visual Tracking: Fills between levels dynamically change color to indicate the impulse direction and track which zones have already been successfully tested by the price action.
🧠 How It Works:
The indicator scans the last N bars (Fixed Window Lookback) to identify the Low and High of the swing. It then compares the bar indices to determine the final direction. The calculateFibPrice function internally adapts to project correction levels from the High down (for Long) or from the Low up (for Short), ensuring the grid is always applied correctly to the impulse.
⚙️ Settings Overview:
The script includes comprehensive settings for:
Grid Mode: Auto Detect, Force Bullish, or Force Bearish.
Impulse Filter: Set the minimum percentage (0% = Off) required for alerts to trigger.
MFI/RSI Settings: Used for additional signal confirmation (internal logic).
Display & Style: Full control over line colors, fill colors, and text sizes.
SMC Statistical Liquidity Walls [PhenLabs]📊 SMC Statistical Liquidity Walls
Version: PineScript™ v6
📌 Description
The SMC Statistical Liquidity Walls indicator is designed to visualize market volatility and potential reversal zones using advanced statistical modeling. Unlike traditional Bollinger Bands that use simple lines, this script utilizes an “Inverted Sigmoid” opacity function to create a “fog of war” effect. This visualizes the density of liquidity: the further price moves from the equilibrium (mean), the “harder” the liquidity wall becomes.
This tool solves the problem of over-trading in low-probability areas. By automatically mapping “Premium” (Resistance) and “Discount” (Support) zones based on Standard Deviation (SD), traders can instantly see when price is overextended. The result is a clean, intuitive overlay that helps you identify high-probability mean reversion setups without cluttering your chart with manual drawings.
🚀 Points of Innovation
Inverted Sigmoid Logic: A custom mathematical function maps Standard Deviation to opacity, creating a realistic “wall” density effect rather than linear gradients.
Dynamic “Solidity”: The indicator is transparent at the center (Equilibrium) and becomes visually solid at the edges, mimicking physical resistance.
Separated Directional Bias: distinct Red (Premium) and Green (Discount) coding helps SMC traders instantly recognize expensive vs. cheap pricing.
Smart “Safe” Deviation: Includes fallback logic to handle calculation errors if deviation hits zero, ensuring the indicator never crashes during data gaps.
🔧 Core Components
Basis Calculation: Uses a Simple Moving Average (SMA) to determine the market’s equilibrium point.
Standard Deviation Zones: Calculates 1SD, 2SD, and 3SD levels to define the statistical extremes of price action.
Sigmoid Alpha Calculation: Converts the SD distance into a transparency value (0-100) to drive the visual gradient.
🔥 Key Features
Automated Premium/Discount Zones: Red zones indicate overbought (Premium) areas; Green zones indicate oversold (Discount) areas.
Customizable Density: Users can adjust the “Steepness” and “Midpoint” of the sigmoid curve to control how fast the walls become solid.
Integrated Alerts: Built-in alert conditions trigger when price hits the “Solid” wall (2SD or higher), perfect for automated trading or notifications.
Visual Clarity: The center of the chart remains clear (high transparency) to keep focus on price action where it matters most.
🎨 Visualization
Equilibrium Line: A gray line representing the mean price.
Gradient Fills: The space between bands fills with color that increases in opacity as it moves outward.
Premium Wall: Upper zones fade from transparent red to solid red.
Discount Wall: Lower zones fade from transparent green to solid green.
📖 Usage Guidelines
Range Period: Default 20. Controls the lookback period for the SMA and Standard Deviation calculation.
Source: Default Close. The price data used for calculations.
Center Transparency: Default 100 (Clear). Controls how transparent the middle of the chart is.
Edge Transparency: Default 45 (Solid). Controls the opacity of the outermost liquidity wall.
Wall Steepness: Default 2.5. Adjusts how aggressively the gradient transitions from clear to solid.
Wall Start Point: Default 1.5 SD. The deviation level where the gradient shift begins to accelerate.
✅ Best Use Cases
Mean Reversion Trading: Enter trades when price hits the solid 2SD or 3SD wall and shows rejection wicks.
Take Profit Targets: Use the Equilibrium (Gray Line) as a logical first target for reversal trades.
Trend Filtering: Do not initiate new long positions when price is deep inside the Red (Premium) wall.
⚠️ Limitations
Lagging Nature: As a statistical tool based on Moving Averages, the walls react to past price data and may lag during sudden volatility spikes.
Trending Markets: In strong parabolic trends, price can “ride” the bands for extended periods; mean reversion should be used with caution in these conditions.
💡 What Makes This Unique
Physics-Based Visualization: We treat liquidity as a physical barrier that gets denser the deeper you push, rather than just a static line on a chart.
🔬 How It Works
Step 1: The script calculates the mean (SMA) and the Standard Deviation (SD) of the source price.
Step 2: It defines three zones above and below the mean (1SD, 2SD, 3SD).
Step 3: The custom `get_inverted_sigmoid` function calculates an Alpha (transparency) value based on the SD distance.
Step 4: Plot fills are colored dynamically, creating a seamless gradient that hardens at the extremes to visualize the “Liquidity Wall.”
💡 Note
For best results, combine this indicator with Price Action confirmation (such as pin bars or engulfing candles) when price touches the solid walls.
ATR Based Stoploss LineThis indicator dynamically plots a horizontal stop-loss level using an RMA-based Average True Range (ATR). The stop value is calculated from the current closing price minus ATR (with optional multiplier) to provide a systematic risk reference during active price movement. A fixed line extends across recent bars for clear visualization, with the stop-loss price displayed at the midpoint of that line for intuitive charting. This tool should be strictly used for breakout environments, aligned with your risk management protocol, and always confirmed with volume analysis before execution. The intent is to drive disciplined entries, strengthen downside protection, and support robust trade management in volatile market conditions.
Hierarchical Hidden Markov ModelHierarchical Hidden Markov Models (HHMMs) are an advanced version of standard Hidden Markov Models (HMMs). While HMMs model systems with a single layer of hidden states, each transitioning to other states based on fixed probabilities, HHMMs introduce multiple layers of hidden states. This hierarchical structure allows for more complex and nuanced modeling of systems, making HHMMs particularly useful in representing systems with nested states or regimes. In HHMMs, the hidden states are organized into levels, where each state at a higher level is defined by a set of states at a lower level. This nesting of states enables the model to capture longer-term dependencies in the time series, as each state at a higher level can represent a broader regime, and the states within it can represent finer sub-regimes. For example, in financial markets, a high-level state might represent a general market condition like high volatility, while the nested lower-level states could represent more specific conditions such as trending or oscillating within the high volatility regime.
The hierarchical nature of HHMMs is facilitated through the concept of termination probabilities. A termination probability is the probability that a given state will stop emitting observations and transition control back to its parent state. This mechanism allows the model to dynamically switch between different levels of the hierarchy, thereby modeling the nested structure effectively. Beside the transition, emission and initial probabilities that generally define a HMM, termination probabilities distinguish HHMMs from HMMs because they define when the process in a sub-state concludes, allowing the model to transition back to the higher-level state and potentially move to a different branch of the hierarchy.
In financial markets, HHMMs can be applied similiarly to HMMs to model latent market regimes such as high volatility, low volatility, or neutral, along with their respective sub-regimes. By identifying the most likely market regime and sub-regime, traders and analysts can make informed decisions based on a more granular probabilistic assessment of market conditions. For instance, during a high volatility regime, the model might detect sub-regimes that indicate different types of price movements, helping traders to adapt their strategies accordingly.
MODEL FIT:
By default, the indicator displays the posterior probabilities, which represent the likelihood that the market is in a specific hidden state at any given time, based on the observed data and the model fit. These posterior probabilities strictly represent the model fit, reflecting how well the model explains the historical data it was trained on. This model fit is inherently different from out-of-sample predictions, which are generated using data that was not included in the training process. The posterior probabilities from the model fit provide a probabilistic assessment of the state the market was in at a particular time based on the data that came before and after it in the training sequence. Out-of-sample predictions, on the other hand, offer a forward-looking evaluation to test the model's predictive capability.
MODEL TESTING:
When the "Test Out of Sample" option is enabled, the indicator plots the selected display settings based on models' out-of-sample predictions. The display settings for out-of-sample testing include several options:
State Probability option displays the probability of each state at a given time for segments of data points not included in the training process. This is particularly useful for real-time identification of market regimes, ensuring that the model's predictive capability is tested on unseen data. These probabilities are calculated using the forward algorithm, which efficiently computes the likelihood of the observed sequence given the model parameters. Higher probabilities for a particular state suggest that the market is currently in that state. Traders can use this information to adjust their strategies according to the identified market regime and their statistical features.
Confidence Interval Bands option plots the upper, lower, and median confidence interval bands for predicted values. These bands provide a range within which future values are expected to lie with a certain confidence level. The width of the interval is determined by the current probability of different states in the model and the distribution of data within these states. The confidence level can be specified in the Confidence Interval setting.
Omega Ratio option displays a risk-adjusted performance measure that offers a more comprehensive view of potential returns compared to traditional metrics like the Sharpe ratio. It takes into account all moments of the returns distribution, providing a nuanced perspective on the risk-return tradeoff in the context of the HHMM's identified market regimes. The minimum acceptable return (MAR) used for the calculation of the omega can be specified in the settings of the indicator. The plot displays both the current Omega ratio and a forecasted "N day Omega" ratio. A higher Omega ratio suggests better risk-adjusted performance, essentially comparing the probability of gains versus the probability of losses relative to the minimum acceptable return. The Omega ratio plot is color-coded, green indicates that the long-term forecasted Omega is higher than the current Omega (suggesting improving risk-adjusted returns over time), while red indicates the opposite. Traders can use omega ratio to assess the risk-adjusted forecast of the model, under current market conditions with a specific target return requirement (MAR). By leveraging the HHMM's ability to identify different market states, the Omega ratio provides a forward-looking risk assessment tool, helping traders make more informed decisions about position sizing, risk management, and strategy selection.
Model Complexity option shows the complexity of the model, as well as complexity of individual states if the “complexity components” option is enabled. Model complexity is measured in terms of the entropy expressed through transition probabilities. The used complexity metric can be related to the models entropy rate and is calculated as the sum of the p*log(p) for every transition probability of a given state. Complexity in this context informs us on how complex the models transitions are. A model that might transition between states more often would be characterised by higher complexity, while a model that tends to transition less often would have lower complexity. High complexity can also suggest the model captures noise rather than the underlying market structure also known as overfitting, whereas lower complexity might indicate underfitting, where the model is too simplistic to capture important market dynamics. It is useful to assess the stability of the model complexity as well as understand where changes come from when a shift happens. A model with irregular complexity values can be strong sign of overfitting, as it suggests that the process that the model is capturing changes siginficantly over time.
Akaike/Bayesian Information Criterion option plots the AIC or BIC values for the model on both the training and out-of-sample data. These criteria are used for model selection, helping to balance model fit and complexity, as they take into account both the goodness of fit (likelihood) and the number of parameters in the model. The metric therefore provides a value we can use to compare different models with different number of parameters. Lower values generally indicate a better model. AIC is considered more liberal while BIC is considered a more conservative criterion which penalizes the likelihood more. Beside comparing different models, we can also assess how much the AIC and BIC differ between the training sets and test sets. A test set metric, which is consistently significantly higher than the training set metric can point to a drift in the models parameters, a strong drift of model parameters might again indicate overfitting or underfitting the sampled data.
Indicator settings:
- Source : Data source which is used to fit the model
- Training Period : Adjust based on the amount of historical data available. Longer periods can capture more trends but might be computationally intensive.
- EM Iterations : Balance between computational efficiency and model fit. More iterations can improve the model but at the cost of speed.
- Test Out of Sample : turn on predict the test data out of sample, based on the model that is retrained every N bars
- Out of Sample Display: A selection of metrics to evaluate out of sample. Pick among State probability, confidence interval, model complexity and AIC/BIC.
- Test Model on N Bars : set the number of bars we perform out of sample testing on.
- Retrain Model on N Bars: Set based on how often you want to retrain the model when testing out of sample segments
- Confidence Interval : When confidence interval is selected in the out of sample display you can adjust the percentage to reflect the desired confidence level for predictions.
- Omega forecast: Specifies the number of days ahead the omega ratio will be forecasted to get a long run measure.
- Minimum Acceptable Return : Specifies the target minimum acceptable return for the omega ratio calculation
- Complexity Components : When model complexity is selected in the out of sample display, this option will display the complexity of each individual state.
-Bayesian Information Criterion : When AIC/BIC is selected, turning this on this will ensure BIC is calculated instead of AIC.
Hidden Markov ModelHidden Markov Models (HMMs) are a class of statistical models used to represent systems that follow a Markov process with hidden states. In such models, the system being modeled transitions between a finite number of states, with the probability of each transition dependent only on the current state. The hidden states are not directly observable; instead, we observe a sequence of emissions or outputs generated by these states. HMMs are widely used in various fields, including speech recognition, bioinformatics, and financial market analysis. In the context of financial markets, HMMs can be utilized to model the latent market regimes (e.g., bullish, bearish, or neutral) that influence the observed market data such as asset prices or returns. By estimating the posterior probabilities of these hidden states, traders and analysts can identify the most likely market regime and make informed decisions based on the probabilistic assessment of market conditions.
The Hidden Markov Model (HMM) comprises several states that work together to model the hidden market dynamics. The states represent the unobservable market regimes such as bullish, bearish or neutral. The states are 'hidden' in nature because we need to infer them from the data and cannot directly observe them.
Model components:
Initial Probabilities: These denote the likelihood of starting in each hidden state. They can be related to long-run probabilities, reflecting the overall likelihood of each state across extended periods. In equilibrium, these initial probabilities may converge to the stationary distribution of the Markov chain.
Transition Probabilities: These capture the likelihood of moving between states, including the probability of remaining in the current state. They model how market regimes evolve over time, allowing the HMM to adapt to changing conditions.
Emission Probabilities: Also known as observation likelihoods, these represent the probability of observing specific market data (like returns) given each hidden state. Emission probabilities can be often represented by continuous probability distributions. In our case we are using a laplace distribution with its location parameter reflecting the central tendency of returns in each state and the scale reflecting the dispersion or the magnitude of the returns.
The power of HMMs in financial modeling lies in their ability to capture complex market dynamics probabilistically. By analyzing patterns in market, the model can estimate the likelihood of being in each state at any given time. This can reveal insights into market behavior and dynamics that might not be apparent from data alone.
MODEL FIT:
By default, the indicator displays the posterior probabilities, which represent the likelihood that the market is in a specific hidden state at any given time, based on the observed data and the model fit. It is crucial to understand that these posterior probabilities strictly represent the model fit, reflecting how well the model explains the historical data it was trained on. This model fit is inherently different from out-of-sample predictions, which are generated using data that was not included in the training process. The posterior probabilities from the model fit provide a probabilistic assessment of the state the market was in at a particular time based on the data that came before and after it in the training sequeence. Out-of-sample predictions on the other hand offer a forward-looking evaluation to test the model's predictive capability.
MODEL TEST:
When the "Test Out of Sample” option is enabled, the indicator plots the selected display settings based on models out-of-sample predictions. The display settings for out-of-sample testing include several options:
State Probability option displays the probability of each state at a given time for segments of datapoints that were not included in the traning process. This is particularly useful for real-time identification of market regimes, ensuring that the model's predictive capability is rigorously tested on unseen data. These probabilities are calculated using the forward algorithm, which efficiently computes the likelihood of the observed sequence given the model parameters. Higher probability for a particular state indicate a higher likelihood that the market is currently in that state. Traders can use this information to adjust their strategies according to the identified market regime and their statistical features.
Confidence Interval Bands option plots the upper, lower, and median confidence interval bands for predicted values. These bands provide a range within which future values are expected to lie with a certain confidence level. The width of the interval is determined by the current probability of different states in the model and the distribution of data within these states. The confidence level can be specified in the Confidence Interval setting.
Omega Ratio option displays a risk-adjusted performance measure that offers a more comprehensive view of potential returns compared to traditional metrics like the Sharpe ratio. It takes into account all moments of the returns distribution, providing a nuanced perspective on the risk-return tradeoff in the context of the HHMM's identified market regimes. The minimum acceptable return (MAR) used for the calculation of the omega can be specified in the settings of the indicator. The plot displays both the current Omega ratio and a forecasted "N day Omega" ratio. A higher Omega ratio suggests better risk-adjusted performance, essentially comparing the probability of gains versus the probability of losses relative to the minimum acceptable return. The Omega ratio plot is color-coded, green indicates that the long-term forecasted Omega is higher than the current Omega (suggesting improving risk-adjusted returns over time), while red indicates the opposite. Traders can use omega ratio to assess the risk-adjusted forecast of the model, under current market conditions with a specific target return requirement (MAR). By leveraging the HHMM's ability to identify different market states, the Omega ratio provides a forward-looking risk assessment tool, helping traders make more informed decisions about position sizing, risk management, and strategy selection.
Model Complexity option shows the complexity of the model, as well as complexity of individual states if the “complexity components” option is enabled. Model complexity is measured in terms of the entropy expressed through transition probabilities. The used complexity metric can be related to the models entropy rate and is calculated as the sum of the p*log(p) for every transition probability of a given state. Complexity in this context informs us on how complex the models transitions are. A model that might transition between states more often would be characterised by higher complexity, while a model that tends to transition less often would have lower complexity. High complexity can also suggest the model captures noise rather than the underlying market structure also known as overfitting, whereas too low complexity might indicate underfitting, where the model is too simplistic to capture important market dynamics. It is also useful to assess the stability of the model complexity. A model with irregular complexity values can be sign of overfitting, as it suggests that the process that the model is capturing changes significantly over time.
Akaike/Bayesian Information Criterion option plots the AIC or BIC values for the model on both the training and out-of-sample data. These criteria are used for model selection, helping to balance model fit and complexity, as they take into account both the goodness of fit (likelihood) and the number of parameters in the model. The metric therefore provides a value we can use to compare different models with different number of parameters. Lower values generally indicate a better model. AIC is considered more liberal while BIC is considered a more conservative criterion which penalizes the likelihood more. Beside comparing different models, we can also assess how much the AIC and BIC differ between the training sets and test sets. A test set metric, which is consistently significantly higher than the training set metric can point to a drift in the models parameters, a strong drift of model parameters might again indicate overfitting or underfitting the sampled data.
Indicator settings:
- Source : Data source which is used to fit the model
- Training Period : Adjust based on the amount of historical data available. Longer periods can capture more trends but might be computationally intensive.
- EM Iterations : Balance between computational efficiency and model fit. More iterations can improve the model but at the cost of speed.
- Test Out of Sample : turn on predict the test data out of sample, based on the model that is retrained every N bars
- Out of Sample Display: A selection of metrics to evaluate out of sample. Pick among State probability, confidence interval, model complexity and AIC/BIC.
- Test Model on N Bars : set the number of bars we perform out of sample testing on.
- Retrain Model on N Bars: Set based on how often you want to retrain the model when testing out of sample segments
- Confidence Interval : When confidence interval is selected in the out of sample display you can adjust the percentage to reflect the desired confidence level for predictions.
- Omega forecast: Specifies the number of days ahead the omega ratio will be forecasted to get a long run measure.
- Minimum Acceptable Return : Specifies the target minimum acceptable return for the omega ratio calculation
- Complexity Components : When model complexity is selected in the out of sample display, this option will display the complexity of each individual state.
-Bayesian Information Criterion : When AIC/BIC is selected, turning this on this will ensure BIC is calculated instead of AIC.
Scalping 4D+ Engine (Advanced Entry Modes {SMC})Scalping 4D+ Engine (Advanced Entry Modes {SMC}) is a next-generation quantitative trading model engineered for traders who want fewer but higher-probability signals.
This system combines Smart Money Concepts (SMC), quantitative volume analysis, volatility regime modeling, and momentum confirmation into a unified scoring engine that filters out noise and highlights only the strongest directional opportunities.
Unlike conventional indicators that rely on a single trigger (EMA crosses, RSI oversold, MACD flips), the SMC 4D+ engine evaluates multiple market dimensions simultaneously, allowing it to track the true underlying state of the market before issuing a BUY or SELL signal.
Humontre Signal Channel — Free EditionHumontre Signal Channel is a clean, high-clarity trend and volatility tool designed to help traders identify directional bias, momentum shifts, and breakout conditions with minimal noise.
The Free Edition provides the core engine behind the Humontre system: dynamic EMA bands, adaptive trend coloring, and precise LONG / SHORT signals.
Whether you trade Crypto, Forex, Indices or Stocks , the Signal Channel keeps you aligned with market structure in a simple and intuitive way.
🔍 How It Works
1. Dynamic EMA Channel
A fast-reacting EMA forms the core of the system. The channel boundaries can be calculated using:
ATR × Multiplier (recommended)
Percentage mode (alternative for low-volatility markets)
This creates a flexible volatility envelope that naturally highlights trend strength and momentum expansion.
2. Adaptive Trend Coloring
The EMA automatically shifts colors:
Green → bullish pressure
Red → bearish pressure
Clear, objective trend visualization without interpretation.
3. Long & Short Signals
Signals appear when price closes outside the band:
LONG → Close crosses above the upper band
SHORT → Close crosses below the lower band
Repeated signals in the same direction are filtered for cleaner momentum confirmation.
4. Multi-Market Ready
Works on all markets and timeframes:
Crypto
Forex
Indices
Stocks
Commodities
🆓 Free Edition Includes
Dynamic EMA Channel
ATR or % Band Mode
Adaptive Trend Colors
Clean LONG / SHORT Signals
Basic Alerts
Minimal, unobtrusive chart visuals
Ideal for learning the Humontre system and spotting breakout opportunities.
⭐ Upgrade to the Pro Edition (Invite-Only)
The Humontre Signal Channel — Pro Edition unlocks advanced professional features:
Automatic SL & TP levels
Dynamic Risk-to-Reward box
SL/TP labels & smart line system
Live trade tracking
Full trade history table
UI & theme customization
Alerts for SL/TP hits
Much more coming…
If you’d like access, feel free to contact me.
📌 Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Always use proper risk management.
Global BB Resonance [by TESTEDED]📈 Global BB Resonance Hunter
1. Design Philosophy: Dimensional Reduction
In modern trading, "Information Overload" is the enemy. Traders often clutter their charts with 15+ Bollinger Band lines across 1H, 4H, Daily, and Weekly timeframes, resulting in a "spaghetti chart" that is impossible to read quickly.
The core logic of this indicator is "Dimensional Reduction." Instead of drawing every single line, this script runs a background algorithm to detect "Confluence" (Resonance).
The Thesis: A single Bollinger line (e.g., 1H Upper) is easily broken. However, when multiple dimensions overlap (e.g., 1H Upper + Daily Mid + Weekly Low) at the exact same price level, a "Market Consensus" is formed. These are the critical "Walls" of the market.
The Solution: We sort all data by Price, not Time. If lines cluster together within a specific threshold (e.g., 0.15%), the script draws a single Resonance Box instead of multiple confusing lines.
2. Key Features
🛡️ Multi-Timeframe Monitoring: Simultaneously monitors 1H, 4H, Daily, Weekly, and Monthly Bollinger Bands in the background, regardless of your chart's current timeframe.
⚡ Smart Resonance Detection: Automatically groups overlapping levels into "Resonance Boxes."
⚡ (2-Line Confluence): Watch closely.
⚡⚡ (3-Line Confluence): Strong Support/Resistance.
⚡⚡⚡ (4+ Lines): "Iron Wall" Resonance.
📊 Volatility State Perception: Detects if the bands are Squeezing (accumulating energy) or Expanding (trending).
Style Options: Choose between Icons (🧊/🔥) or Geek Symbols (>.< / <^>).
🧘 Focus Mode (Sniper View): A unique feature that hides all individual lines, leaving only the Resonance Boxes and the Dashboard. This keeps your chart clean and distraction-free.
🔔 Smart Alerts: Get notified immediately when Price touches a Resonance Box or when a Squeeze occurs.
3. Visual Guide
A. The Symbols (State Indicators)
You can switch styles in the settings.
B. The Resonance Boxes
Red Box: Resistance Zone (Above Price).
Green Box: Support Zone (Below Price).
Label: E.g., ⚡⚡ 1H Up + D Mid. This tells you exactly which levels are overlapping.
4. Usage Strategy
The "Reversal" Setup: Look for a Green Resonance Box below price with High Confluence (⚡⚡). Ensure the state is NOT Expanding (<^> or 🔥).
The "Breakout" Setup: Look for the Squeeze Symbol (>.< or 🧊) on the dashboard. If price approaches a Resonance Box while Squeezing, expect a breakout.
The "Sniper" Method: Turn on Focus Mode. Set Alerts. Only look at the chart when price hits a "Wall."
How to use： youtu.be
📈 布林带多维共振捕猎者
1. 设计哲学：降维打击
在现代交易中，“信息过载”是最大的敌人。交易者经常在图表上叠加 1H、4H、日线、周线等 15 条以上的布林带线条，导致图表像“盘丝洞”一样难以阅读。
本指标的核心逻辑是“降维打击”与“数据可视化”。 我们不再画出每一条线，而是在后台运行算法来捕捉**“共振”（Confluence）**。
核心理念：单一周期的布林线（如 1H 上轨）很容易被刺破。但是，当多个维度的力量（如 1H 上轨 + 日线中轨 + 周线下轨）在同一个价格水平重叠时，就形成了**“市场合力”**。这些位置才是市场真正的“铜墙铁壁”。
解决方案：系统按价格而非时间对数据进行排序。如果多条线在特定阈值（如 0.15%）内聚集，脚本会画出一个**“共振框”**，而不是无数条混乱的线。
2. 核心功能
🛡️ 全维幽灵监控：无论当前图表周期如何，脚本都会在后台实时监控 1H, 4H, 日线, 周线, 月线 的数据。
⚡ 智能共振雷达：自动检测并合并重叠的关键位。
⚡ (2线共振)：值得关注。
⚡⚡ (3线共振)：强力支撑/阻力。
⚡⚡⚡ (4线以上)：核弹级/铁壁共振。
📊 波动率状态感知：自动识别布林带是处于 挤压蓄势 还是 扩张爆发 阶段。
风格切换：支持 图标模式 (🧊/🔥) 或 极客符号模式 (>.< / <^>)。
🧘 专注模式 (Focus Mode)：一键隐藏所有单线，只保留共振框和仪表盘。让您的图表瞬间清空，像狙击手一样只关注目标。
🔔 智能警报：当价格触及共振框，或出现极度压缩信号时，立即发送警报。
3. 视觉指南
A. 状态符号说明
您可以在设置中切换显示风格。
B. 共振框说明
红色方框：上方阻力区 (Resistance)。
绿色方框：下方支撑区 (Support)。
标签示例：⚡⚡ 1H Up + D Mid —— 明确告知您是哪几条线发生了共振。
4. 实战策略
“反转”交易：寻找价格下方的绿色共振框，且具有高星级 (⚡⚡)。前提是当前状态不是扩张状态 (<^> 或 🔥)。
“突破”交易：在仪表盘上看到 挤压符号 (>.< 或 🧊)。如果价格在挤压状态下逼近共振框，不要逆势阻挡，大概率会发生强力突破。
“狙击”模式：开启 专注模式。设置好警报。不要盯着 K 线波动，直到价格撞上“墙壁”触发警报时再介入。
使用说明： youtu.be
Macro Opportunity Drawdown Engine (MODE)Strategic Drawdown Classification for Macro-Cycle Accumulation. MODE identifies market drawdowns that historically align with discounted accumulation zones. Instead of treating pullbacks as risk events, it classifies them as structural opportunity phases based on distance from prior cycle highs.
The indicator continuously measures drawdown severity and labels current conditions as:
- Correction: –10% to –19%
- Bear Market: –20% to –29%
- Major Crash Opportunity: –30% or deeper
These levels are displayed directly on the chart, along with a live drawdown reading from the most recent peak.
MODE is built for long-term, macro-minded investors who view volatility as an advantage. It helps identify when the market has entered deep value phases often associated with stronger forward returns, liquidity resets, and cycle bottoms.
In short:
MODE turns market stress into clear signals of potential opportunity, providing a disciplined, data-driven framework for accumulation during corrections, bear markets, and crashes.
Intraday Volatility Map (Bajrang Bali Indicator)Indicator Name
Bollinger Bands on Historical Volatility (BB-HV) – Intraday Volatility Map
Concept
This indicator applies Bollinger Bands directly on Historical Volatility (HV) instead of price.
HV tells you the “energy” behind the move
Bollinger Bands on HV tell you when volatility is compressing or expanding
Works on all intraday timeframes for indices and stocks
You are not watching price alone — you are watching the strength behind price movement .
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Core Logic
Historical Volatility is calculated using log returns, annualized
Bollinger Bands are plotted on the HV line (separate pane)
Upper/Lower bands show volatility expansion or contraction
User inputs: HV length, BB length, BB multiplier
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What This Indicator Shows
Volatility Squeeze (Low HV) – HV stays below lower BB → quiet market, breakout coming
Volatility Expansion (High HV) – HV breaches upper BB → trend day or news-driven move
Normal Regime – HV oscillates between bands → balanced intraday structure
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How to Use – Indices (NIFTY / BankNifty)
Trend Day Detection – Early HV breakout above upper band suggests strong directional movement
Range Day Identification – HV hugging lower band implies consolidation and mean reversion
Event Risk Mapping – Sudden HV spikes warn of macro data, gaps, policy events
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How to Use – Stocks
Stock Selection – Choose stocks where HV is rising above mid-band → active, tradable
Entry Confirmation – Breakouts with rising HV have stronger follow-through
Risk Management – High HV → wide stops, low size; Low HV → tight stops, fakeouts possible
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Signals Generated (For Alerts)
Squeeze Signal – HV < lower band for a set number of bars
Expansion Signal – HV crossing above upper band
Reversion Signal – HV falls back inside bands after a volatility spike
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Best Timeframes
1m, 3m, 5m, 15m intraday
Works best on indices and liquid stocks
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Suggested Inputs
HV Length: 20
BB Length: 20
BB Multiplier: 2.0
Squeeze Bars: 5–10
Expansion Filter: HV closing above upper band
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Who Should Use This Indicator?
Scalpers – Identify high-energy zones
Day Traders – Ride trend days via volatility regime shifts
Option Traders – Read intraday realized volatility patterns
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Trading Notes
This is a volatility-regime tool, not a buy/sell signal generator
Works best when combined with VWAP, structure, volume, or trend indicators
Always use personal judgment and risk management
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Disclaimer
This script is for educational and research use only. It does not provide investment advice or guaranteed trading outcomes. Use at your own risk.
ATR Volatility HistogramATR Volatility Histogram showing result as coloured histogram where Rising > Greenand Fallig < Red. Input can be varied in settings.
複合ガチイカ🦑🦑🦑 日本語説明は英文の後ーーーーーーーーーーーーーーー
🦑 Composite Gachi Squid Indicator – A fun and intuitive trading overlay combining SuperTrend, ATR, and RSI.
Body color shows trend direction and strength.
Tentacles visualize volatility.
Eyes indicate overbought/oversold conditions.
🦑↑ / 🦑↓ marks provide clear entry signals.
Perfect for visual traders who want both style and actionable insights.
日本語説明-------------------------------------------------------------
🦑 複合ガチイカ・インジケーター – SuperTrend、ATR、RSI を組み合わせた遊び心と実用性を両立したチャートオーバーレイ。
イカの体の色でトレンドの方向と強さを表示
触手でボラティリティを可視化
目で買われすぎ・売られすぎを表示
🦑↑ / 🦑↓ が分かりやすいエントリーシグナル
見た目も楽しく、トレード判断にも使えるインジケーターです。
Brahmastra PremiumBrahmastra Trade System is a complete institutional trading engine designed for traders who want precision entries, clean trends, and automated risk management.
It combines multi-timeframe confirmation, ATR-based volatility logic, trend structure, and angle analytics—giving you a highly reliable and visually clean trading framework.
🔥 Key Features
✅ 1. Institutional Trend Engine (Triple Confirmation):
The trend is detected using:
Fast MA (5)
Slow SMA/EMA (51)
Custom ATR Trend (SuperTrend-like algorithm)
This three-layer confirmation ensures you only trade when the trend is solid, real, and clean.
✅ 2. Multi-Timeframe Breakout Confirmation (1-Minute)
Most retail breakouts are fake.
This indicator validates entries using lower timeframe 5-minute candle closes.
✔ Helps avoid traps
✔ Ensures genuine breakout momentum
✔ Great for intraday & swing traders
✅ 3. Smart Entry & Exit Signals
Clear on-chart signals:
Bullish Entry (Triangle Up)
Bearish Entry (Triangle Down)
Buy Exit
Sell Exit
Exit logic uses:
Fast MA breakdown
ATR trend reversal
This catches trend reversals early and protects profits.
✅ 4. Automatic SL + TP1/TP2/TP3 Projection (ATR-Based)
On every entry, Brahmastra automatically plots:
Stop Loss (SL),Target 1,Target 2,Target 3
Targets are based on volatility (ATR), not random lines. This gives:
✔ Stable stops
✔ Dynamic targets
✔ Accurate risk–reward mapping
✅ 5. Smart Trailing Stop Loss (TSL)
TSL activates only after TP1 hits.
Buy trades → TSL moves upward
Sell trades → TSL moves downward
The trailing SL never moves backward → flawless institutional money management.
✅ 6. Volume-Powered Candle Coloring
Candles change color based on:
Trend direction
Volume intensity
Makes momentum extremely easy to read:
High volume bull → Neon green
High volume bear → Neon red
✅ 7. Multi-Angle Trendline System (3 Layers)
Brahmastra auto-draws support/resistance trendlines for:
L1 (Scalp) – Short trend
L2 (Swing) – Medium trend
L3 (Macro) – Larger trend
Each trendline is analyzed for angle strength:
🚀 Parabolic (Dangerous / Vertical)
💪 Strong Trend (Ideal)
😴 Weak / Accumulation (Sideways)
This helps you see whether the market is:
About to explode
Losing strength
Moving sideways
⚠️ Disclaimer
This indicator is an advanced trading tool, NOT financial advice.
Always backtest, understand the logic, and trade responsibly.
Delta+CVD&CVD CandlesDelta + CVD & CVD Candles
Order-flow indicator combining Delta (Ask–Bid), Cumulative Volume Delta (CVD), and a unique CVD-based synthetic candle system. Shows buy/sell pressure, volume aggressiveness, and momentum shifts with optional Delta histogram, CVD line, and CVD+Delta combined candles. Useful for scalping, intraday trading, divergence detection, and understanding buyer/seller dominance.
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📘 Overview
The Delta + CVD & CVD Candles Indicator combines multiple order-flow tools into one clean visual package. It displays:
• Delta (Ask–Bid) to measure aggressive buying/selling
• Cumulative Volume Delta (CVD) to track accumulated pressure
• Combined CVD Candles showing synthetic candles built entirely from order-flow data
This indicator helps traders read market intent, find momentum shifts, and detect absorption or hidden buying/selling without needing Level-2 data.
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📊 Features
1. Delta (Ask-Bid) Histogram
Shows buying vs selling pressure per candle.
• Green = Buyers (Ask > Bid)
• Red = Sellers (Bid > Ask)
2. CVD (Cumulative Delta) Line
Tracks whether buyers or sellers dominate over time.
Useful for spotting divergences and trend strength.
3. Delta + CVD Combined Candles
Synthetic candles built from order-flow:
• Candle body = change in CVD
• Wicks = size of Delta imbalance
• Colors = green (bullish), red (bearish)
These candles reveal aggressive buying/selling much more clearly than price candles.
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🛠 Inputs & Options
• Show/Hide Delta Histogram
• Show/Hide CVD Line
• Show/Hide Combined CVD Candles
• Bull Color
• Bear Color
• CVD Line Color
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📈 How to Trade With It
• Rising CVD + bullish Delta → Strong up momentum
• Falling CVD + bearish Delta → Strong down momentum
• Price HH but CVD failing → Bearish divergence
• Price LL but CVD not making LL → Bullish divergence
• Long wick in combined candle → High imbalance (aggressive buyers/sellers)
Great for scalping, day trading, and momentum confirmation.
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⚠️ Notes
• Uses TradingView’s volume feed (not Level-2 depth).
• Works on all markets and timeframes.
• Volume accuracy depends on exchange data.
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✔️ Recommended Use-Cases
• Intraday trading
• Volume/Delta analysis
• Divergence trading
• Identifying exhaustion and absorption
• Understanding buyer/seller strength visually
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👤 Credits
Paraskumarpatel5026@gmail.com
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Deviaton Tracker - QuantSyDeviation Tracker - QuantSy
An adaptive volatility band system that maps price behavior across statistical deviation zones. Provides visual context for market extremes and tracks duration patterns for probabilistic mean reversion analysis.
What it offers:
Dynamic bands that adjust to current volatility conditions, creating clear visual zones for price action. The system continuously monitors time spent in each zone and builds a statistical profile of typical duration patterns, helping identify when price may be overextended.
Best for:
Spotting potential reversal areas at volatility extremes
Understanding current price positioning relative to recent behavior
Timing entries and exits based on statistical probabilities
Risk management and position sizing decisions
Clean gradient visualization provides immediate context while the underlying statistical engine tracks behavioral patterns across all market conditions.
**⚠️ Disclaimer**
Educational tool only - does not constitute investment advice. The developer assumes no liability for any trading profits or losses incurred through the use/misuse of this indicator.
This indicator does not include any features related to interest, leverage, or gambling. Users are fully responsible for making sure their assets and trading practices align with Islamic guidelines.
Real Relative Strength Indicator### What is RRS (Real Relative Strength)?
RRS is a volatility-normalized relative strength indicator that shows you – in real time – whether your stock, crypto, or any asset is genuinely beating or lagging the broader market after adjusting for risk and volatility. Unlike the classic “price ÷ SPY” line that gets completely fooled by volatility regimes, RRS answers the only question that actually matters to professional traders:
“Is this ticker moving better (or worse) than the market on a risk-adjusted basis right now?”
It does this by measuring the excess momentum of your ticker versus a benchmark (SPY, QQQ, BTC, etc.) and then dividing that excess by the average volatility (ATR) of both instruments. The result is a clean, centered-around-zero oscillator that works the same way in calm markets, crash markets, or parabolic bull runs.
### How to Use the RRS Indicator (Aqua/Purple Area Version) in Practice
The indicator is deliberately simple to read once you know the rules:
Positive area (aqua) means genuine outperformance.
Negative area (purple) means genuine underperformance.
The farther from zero, the stronger the leadership or weakness.
#### Core Signals and How to Trade Them
- RRS crossing above zero → one of the highest-probability long signals in existence. The asset has just started outperforming the market on a risk-adjusted basis. Enter or add aggressively if price structure agrees.
- RRS crossing below zero → leadership is ending. Tighten stops, take partial or full profits, or flip short if you trade both sides.
- RRS above +2 (bright aqua area) → clear leadership. This is where the real money is made in bull markets. Trail stops, add on pullbacks, let winners run.
- RRS below –2 (bright purple area) → clear distribution or capitulation. Avoid new longs, consider short entries or protective puts.
- Extreme readings above +4 or below –4 (background tint appears) → rare, very high-conviction moves. Treat these like once-a-month opportunities.
- Divergence (not plotted here, but easy to spot visually): price making new highs while the aqua area is shrinking → distribution. Price making new lows while the purple area is shrinking → hidden buying and coming reversal.
#### Best Settings by Style and Asset Class
For stocks and ETFs: keep benchmark as SPY (or QQQ for tech-heavy names) and length 14–20 on daily/4H charts.
For crypto: change the benchmark to BTCUSD (or ETHUSD) immediately — otherwise the reading is meaningless. Length 10–14 works best on 1H–4H crypto charts because volatility is higher.
For day trading: drop length to 10–12 and use 15-minute or 5-minute charts. Signals are faster and still extremely clean.
#### Highest-Edge Setups (What Actually Prints Money)
- RRS crosses above zero while price is still below a major moving average (50 EMA, 200 SMA, etc.) → early leadership, often catches the exact bottom of a new leg up.
- RRS already deep aqua (+3 or higher) and price pulls back to support without RRS dropping below +1 → textbook add-on or re-entry zone.
- RRS deep purple and suddenly turns flat or starts curling up while price is still falling → hidden accumulation, usually the exact low tick.
That’s it. Master these few rules and the RRS becomes one of the most powerful edge tools you will ever use for rotation trading...
Meet The Neural Brain: The "Glass Box" AnalystIt observes. It thinks. It speaks.
Most indicators are "Black Boxes"—they give you a signal, but they never tell you why. If you don't know the why, you can't trust the trade.
The Neural Brain is different. It is a "Glass Box" AI Market Analyst that lives on your chart. It breaks down its decision-making process into plain English, so you never have to guess.
How It "Thinks" (The 3-Layer Cortex)
It processes market data through three human-like layers:
1. PERCEPTION (The Eyes)
Forensic Analysis: It scans price action for "clean" vs. "noisy" movement.
Spread History: It tracks momentum expansion in real-time.
2. COGNITION (The Mind)
Mode Selection: It mathematically decides whether to TRACK a trend or REPEL choppy conditions.
Conviction Monitor: It tells you if its confidence in the trade is growing or fading.
3. NARRATIVE (The Voice)
The Killer Feature: It synthesizes all data into a final strategic summary displayed right on your screen:
"STRONG TREND + NOISY ACTION = HOLDING (Ignoring Noise)"
"Is this Real AI?"
Transparency is our priority. This is not "Generative AI" (like ChatGPT) that hallucinates or scours the internet. This is Expert Systems Machine Learning.
The Math: We utilize the Rational Quadratic Kernel, a sophisticated technique used in Gaussian Process Regression. This allows the code to "learn" the structure of volatility without being explicitly hard-coded. It adapts to the market curve.
The Logic: It mimics the thought process of a professional trader running a complex Decision Tree:
Human Thought: "The trend is up, but it's choppy, so I should wait."
Neural Logic: IF (Trend > 0) AND (Efficiency < 0.3) THEN Strategy = "HOLDING"
The Result: A Synthetic Cortex that adapts to the situation just like a pro trader would, giving you the clarity to execute with zero hesitation.
Volume based liquidity This indicator finds area where the price moves relatively mildly compared to the size of the volume, the target area. It also finds weak areas, that have low volume in a relatively large price movement. Larger and more recent target areas are much more useful in finding liquidity. the weak areas could be a tell for when price will reverse into a target area. Make sure a target area hasn't already had its liquidity swept.
ATR Trade Plan ToolOverview
This indicator is a trade management tool designed to help traders visualize volatility-based targets and stop-losses instantly. By anchoring calculations to the Daily Opening Price and the Average True Range (ATR), it projects objective, mathematical support and resistance levels for the current session.
How It Works
The script detects the start of the trading day (or a manually defined period) and draws a vertical marker. From there, it projects horizontal lines representing key multiples of the ATR:
Green Line: Opening Price (The baseline).
Blue Lines (Targets): +0.5 ATR, +1.0 ATR, and +2.0 ATR. These serve as dynamic profit-taking zones based on current market volatility.
Orange Line (Stop Loss): -2.0 ATR. A standard volatility-based stop level.
Red Line (Emergency Exit): -3.0 ATR. A level indicating extreme adverse moves.
Key Features
Auto or Manual Mode: By default, the script automatically fetches the Daily Open and ATR-14. However, users can manually input a specific Opening Price or ATR value in settings to simulate trade plans or override automatic data.
Clean Visuals: Uses the Drawing API to plot lines only on the current/last bar, keeping historical price action clean and uncluttered.
Text Customization: Users can align text to the Right, Left, or Center, adjust the offset distance, and change text size to fit their chart layout.
Flexible Alerts: Includes a dedicated "Alert Configuration" menu. Users can toggle alerts on/off for individual lines (e.g., enable the Stop Loss alert but disable the +0.5 ATR alert). All enabled settings work via a single "Any alert() function call."
Settings
Values: Input custom Open/ATR prices (leave at 0 for automatic).
Text & Alignment: Adjust label position, offset, and size.
Alert Configuration: Checkboxes to enable/disable alerts for specific price levels.
Methodology The levels are calculated using the standard formula: Level = Opening Price + (Multiplier * ATR)
BT MA BandsThe BT MA Bands indicator is built around a central moving average (MA) with upper and lower bands derived from it, similar to Bollinger Bands but focused on exponential moving averages (EMAs) for smoother responsiveness.
The core idea is to visualize trend strength, volatility squeezes, and potential reversal points through dynamic bands that expand/contract based on price deviation. It includes trend-based color fills, entry/exit signals, an optional ATR (Average True Range) overlay for additional volatility bands, and flexible MA source options to adapt to different market conditions.
Inputs
MA Type and Length: Choose from EMA (default), SMA, WMA, or HMA. Default length is 20 periods, but adjustable (e.g., 10-50) for short-term scalping or longer swings.
Deviation Multiplier: Sets the band width as a multiple of the standard deviation from the MA (default: 2.0). Higher values create wider bands for trending markets; lower for ranging ones.
Source Data: Select price source for the MA calculation—close (default), open, high, low, (high+low)/2, or weighted (hlc3/hlcc4) to emphasize different aspects of price action.
ATR Toggle and Multiplier: Optional ATR-based outer bands (default off). When enabled, multiplier (default: 1.5) adds volatility sensitivity, helping filter noise in choppy conditions.
Signal Sensitivity: Threshold for generating buy/sell alerts (e.g., 0-100 scale; default 50) based on band crossovers or squeezes.
Style Options: Enable/disable fills, signals, and colors for personalization.
Visual Elements
Central MA Line: A solid line (e.g., blue by default) representing the chosen moving average, acting as the baseline.
Upper and Lower Bands: Dotted or dashed lines (green/red defaults) that flank the MA, widening during volatility and narrowing in consolidations.
Color-Changing Fills: The area between bands fills with color shifts—bullish (green) when price is above the MA and bands are expanding, bearish (red) when below and contracting, or neutral (gray) during flat trends.
Entry Signals: Arrow plots (up green for bullish, down red for bearish) appear on the chart when price crosses the bands or a squeeze resolves, with optional text labels like "Buy" or "Sell."
ATR Overlay (if enabled): Additional dashed outer bands in a lighter color (e.g., purple) to highlight extreme volatility zones.
How to Use It in Trading
Trend Identification: Use the central MA and band fills to gauge direction—price above the MA with green fills signals an uptrend (favor longs); below with red indicates downtrends (favor shorts). Narrow bands suggest a "squeeze" setup, often preceding big moves.
Entry Points:
Bullish Entries: Enter long when price breaks above the upper band on a bullish signal arrow, especially after a squeeze. Confirm with volume spike or RSI >50 on timeframes like 5m-1h for quick trades.
Bearish Entries: Enter short on a break below the lower band with a bearish arrow, post-squeeze. Ideal on 4h+ frames for swings, paired with MACD crossovers.
Exits and Risk Management: Exit longs when price hits the lower band or a bearish signal fires; vice versa for shorts. Set stops just beyond the opposite band (e.g., below lower for longs). Target 1.5-3x risk-reward, using ATR bands for trailing stops in volatile markets.
General Tips: Best in trending environments; avoid during news events causing false breakouts. Backtest parameters on historical data, and combine with other indicators like RSI or volume for confluence. It's great for spotting reversals but not infallible—always apply position sizing and monitor for band "walks" (price hugging one band) as continuation signals.
Eurovision - EURUSD Market SpecialistProfessional EURUSD trading signals with adaptive parameters
Performance Expectations
Win Rate || 60-70% || Adaptive parameters
Risk/Reward || 1:2.0 || Session optimization
Max Drawdown || <15% || News filter protection
Sharpe Ratio || >1.5 || Multi-timeframe confluence
Signals per Day || 3-8 || EURUSD-specific filtering
Tip: The indicator works best as an overlay on EURUSD M5 charts!
