Turtle Soup + Raptor.RAW (PRO Trend Filters)Introducing our new ICT Turtle Soup Indicator! This indicator is built around the ICT "Turtle Soup" model. The strategy has 5 steps for execution which are described in this write-up. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Turtle Soup Indicator :
Implementation of ICT's Turtle Soup Strategy
Adaptive Entry Method
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
HOW DOES IT WORK ?
The ICT Turtle Soup strategy may have different implementations depending on the selected method of the trader. This indicator's implementation is described as :
1. Mark higher timerame liquidity zones.
Liquidity zones are where a lot of market orders sit in the chart. They are usually formed from the long / short position holders' "liquidity" levels. There are various ways to find them, most common one being drawing them on the latest high & low pivot points in the chart, which this indicator does.
2. Mark current timeframe market structure.
The market structure is the current flow of the market. It tells you if the market is trending right now, and the way it's trending towards. It's formed from swing higs, swing lows and support / resistance levels.
3. Wait for market to make a liquidity grab on the higher timeframe liquidity zone.
A liquidity grab is when the marked liquidity zones have a false breakout, which means that it gets broken for a brief amount of time, but then price falls back to it's previous position.
4. Buyside liquidity grabs are "Short" entries and Sellside liquidity grabs are "Long" entries by default.
5. Wait for the market-structure shift in the current timeframe for entry confirmation.
A market-structure shift happens when the current market structure changes, usually when a new swing high / swing low is formed. This indicator uses it as a confirmation for position entry as it gives an insight of the new trend of the market.
6. Place Take-Profit and Stop-Loss levels according to the risk ratio.
This indicator uses "Average True Range" when placing the stop-loss & take-profit levels. Average True Range calculates the average size of a candle and the indicator places the stop-loss level using ATR times the risk setting determined by the user, then places the take-profit level trying to keep a minimum of 1:1 risk-reward ratio.
This indicator follows these steps and inform you step by step by plotting them in your chart.
UNIQUENESS
This indicator is an all-in-one suit for the ICT's Turtle Soup concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. It's designed for simplyfing a rather complex strategy, helping you to execute it with clean signals. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
SETTINGS
1. General Configuration
MSS Swing Length -> The swing length when finding liquidity zones for market structure-shift detection.
Higher Timeframe -> The higher timeframe to look for liquidity grabs. This timeframe setting must be higher than the current chart's timeframe for the indicator to work.
Breakout Method -> If "Wick" is selected, a bar wick will be enough to confirm a market structure-shift. If "Close" is selected, the bar must close above / below the liquidity zone to confirm a market structure-shift.
Entry Method ->
"Classic" : Works as described on the "HOW DOES IT WORK" section.
"Adaptive" : When "Adaptive" is selected, the entry conditions may chance depending on the current performance of the indicator. It saves the entry conditions and the performance of the past entries, then for the new entries it checks if it predicted the liquidity grabs correctly with the current setup, if so, continues with the same logic. If not, it changes behaviour to reverse the entries from long / short to short / long.
2. TP / SL
TP / SL Method -> If "Fixed" is selected, you can adjust the TP / SL ratios from the settings below. If "Dynamic" is selected, the TP / SL zones will be auto-determined by the algorithm.
Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted
Pesquisar nos scripts por "文华财经tick价格"
Relative Strength TableRelative Strength Table
1. Overview and Key Features
The Relative Strength Table is an indicator that compares multiple tickers against a benchmark (default: SPY) and displays their relative strength.
It is designed to help analyze stock leadership, sector trends, and portfolio performance in one consolidated table.
You can freely input up to 20 tickers from the Inputs panel, allowing flexible comparisons.
(If 20 tickers feel too limited, let me know in the comments — I’ll expand it.)
2. How the RS Percentile Is Calculated and What It Means
The RS Percentile shows how strong the current price ratio is compared to past data, expressed as a percentile rank.
First, the indicator calculates the price ratio by dividing the ticker’s close by the benchmark’s close.
Then, it compares the latest ratio with historical ratio data and determines its percentile value.
Examples:
・80% or higher → relatively strong
・Around 50% → neutral
・40% or below → relatively weak
3. Indicator Features and Customization
3-1. RS Lookback Settings
You can set up to four lookback periods for RS calculation and customize the bar count for each.
Default values are 5, 21, 63, and 126 bars.
You can choose which column to sort by, and the selected column is marked with an asterisk.
Each RS column can be shown or hidden individually via checkboxes.
3-2. Visual Highlight Settings
Relative strength can be color-coded for clarity.
You can freely customize:
・Highlight colors
・Threshold values
・On/off toggles for each highlight layer
3-3. Default Tickers and Reset Function
These 16 sector ETFs are included as the default ticker set:
QQQ, QQQE, RSP, DIA, IWM, XLV, XLE, XLF, XLRE, XLB, XLP, XLU, XLY, XLK, XLC, XLI
You can return to the default list anytime by pressing the refresh button next to the ticker fields.
4. Use Cases and Analysis Examples
4-1. Sector Rotation Analysis
By comparing RS across multiple periods, you can easily identify:
・Sectors gaining short-term strength
・Sectors with steady long-term inflows
A sharp rise in short-term RS may signal the early stages of a rotation.
4-2. Identifying Leaders Within a Sector
You can compare up to 20 tickers at once, making it easy to spot true sector leaders.
4-3. Objective Evaluation of Portfolio Holdings
By entering your portfolio tickers, you can instantly see:
・Whether each name is outperforming or underperforming
・Which timeframes show strength
・How each ticker compares to the benchmark
NY ORB - Full Dynamic SystemNY ORB - Full Dynamic Strategy Summary
1. Opening Range and Session Timing
Opening Range (ORB) Calculation: The strategy identifies the ORB High and ORB Low by tracking the highest high and lowest low during the specified New York pre-market window, which is set by default from 8:30 to 8:45 (New York time).
Entry Window: Trading activity is restricted to a specific entry period, typically starting shortly after the ORB is established (default: 8:50 to 12:00).
Hard Exit Time: Any remaining open positions are automatically closed at a fixed exit time (default: 13:25).
2. Trade Entry Logic and Filters
An entry (Long or Short) is generated when the price breaks out of the established ORB, provided it passes a series of optional filters:
Direction Control: The user can restrict the strategy to trade Long Only, Short Only, or Both.
Second Breakout Logic: An optional filter that requires the price to break out, reverse back into the range, and then break out again, confirming momentum after a consolidation.
Confirmation Candle Count: An optional filter that checks the close of a previous candle (e.g., 1 or 2 candles ago) to ensure the price was still inside the range, preventing premature entry.
Technical Filters (Optional): The entry is only executed if it aligns with selected indicators:
RSI: Filters for non-overbought (Long) or non-oversold (Short) conditions.
MACD: Requires the MACD line to be above/below the Signal line for alignment.
VWAP: Requires the price to be above/below the Volume-Weighted Average Price.
Trend Filter (SMMA): Requires the price to be above/below a 50-period Simple Moving Average.
3. Dynamic Risk and Exit Management
This strategy features highly configurable stop-loss and profit-taking mechanics:
Primary Stop Loss Methods: The Stop Loss distance can be dynamically chosen from four types:
Fixed: A fixed number of ticks.
ATR: Based on a multiple of the Average True Range (ATR).
Capped ATR: ATR-based, but with a hard maximum tick limit.
OR-Based: Based on a multiple of the actual ORB High-to-Low range.
Dynamic Profit Target: The Take Profit level is calculated dynamically based on a multiplier of either the ATR or the ORB Range.
Breakeven Stop:
If enabled, the Stop Loss automatically moves to the entry price (Breakeven) once the price moves a predetermined distance in the profitable direction.
An Adaptive Breakeven option allows the trigger distance to be calculated as a percentage of the overall ATR Profit Target.
Trailing Stop: The strategy uses a trailing stop, which can be custom-set (fixed ticks) or dynamically tied to the ATR. An optional feature Auto Tighten Trailing reduces the trailing multiplier once the breakeven level is hit.
MA Cross Exit: An alternative, counter-trend exit mechanism that closes the trade if the price crosses back over the chosen Moving Average (either SMMA or VWAP), overriding the pending profit target.
4. Daily Account Management
The strategy includes crucial daily risk controls to protect capital and lock in profits:
Daily Profit Limit: If the total daily PnL (realized and unrealized) hits a predefined maximum profit threshold (in ticks), all trades are closed, and new entries are blocked for the remainder of the trading day.
Daily Loss Limit: Conversely, if the total daily PnL hits a predefined maximum loss threshold, all trades are closed, and new entries are blocked for the remainder of the day.
ATR DAILY PROGRESSION)Indicator: ATR Daily Progression — Final Compact Edition
1. Indicator Objective
The ATR Daily Progression indicator measures the progression of intraday volatility as a percentage of the daily Average True Range (ATR).
It provides a quick visual overview of whether the market has reached or exceeded its average daily range of movement.
This helps traders avoid entering low-probability continuation trades once the day’s ATR is already completed.
2. Visual Presentation
Horizontal bar ranging from 0% to 150% of the ATR.
Green color up to 100%, then red beyond that point.
Main ticks: 0, 25, 50, 75, 90, 100, and 150%.
Full-height white vertical lines at 0%, 100%, and 150%.
A floating badge displaying the current ATR completion percentage, always visible.
Compact Height mode enabled by default for optimal visual integration.
3. Key Features
Function Description
Precise alignment The transition from green to red occurs exactly after the 100% tick.
Audio & visual alerts Triggered at 75%, 90%, 100%, and 150%.
Session flash effects The filled bar blinks when the ATR is reached (100%) or exceeded (150%).
Dynamic badge Displays the current ATR %, green before 100%, red after.
Compact layout Three-line table format for better chart integration.
4. Recommended Settings
ATR Length (Daily): 14
Bar width (steps): 32–40 (depending on chart size)
Always green below 100%: enabled
Show floating % badge: enabled
Compact Height: enabled by default
Flash at 75% and 90%: enabled
Flash at 100% and 150%: enabled
5. Strategic Use
The ATR Done Today is a visual discipline tool designed to help traders:
Identify when the market has likely completed its daily move.
Avoid late-session counter-trend trades.
Visualize volatility compression or expansion.
Determine optimal times to take profits or pause trading.
Adaptive Volume Delta Map---
📊 Adaptive Volume Delta Map (AVDM)
What is Adaptive Volume Delta Map (AVDM)?
The Adaptive Volume Delta Map (AVDM) is a smart, multi-timeframe indicator that visualizes buy and sell volume imbalances directly on the chart.
It adapts automatically to the best available data resolution (tick, second, minute, or daily), allowing traders to analyze market activity with micro-level precision .
In addition to calculating volume delta (the difference between buying and selling pressure), AVDM can display a Volume Distribution Map — a per-price-level visualization showing how volume is split between buyers and sellers.
Key Features
✅ Adaptive Resolution Selection — Automatically chooses the highest possible data granularity — from tick to daily timeframe.
✅ Volume Delta Visualization — Displays delta candles reflecting the dominance of buyers (green), sellers (red), and delta (orange).
✅ Per-Level Volume Map (optional) — Shows detailed buy/sell volume distribution per price level, grouped by `Ticks Per Row`.
✅ Bid/Ask Classification — When enabled, AVDM uses bid/ask logic to classify trade direction with greater accuracy.
✅ Smart Auto-Disable Protection — Automatically disables volume map if too many price levels (>50) are detected — preventing performance degradation.
Inputs Overview
Use Seconds Resolution — Enables use of second-level data (if your TradingView subscription allows it).
Use Tick Resolution — Enables tick-based analysis for the most detailed view. If available, enable both tick and seconds resolution.
Use Bid/Ask Calculated — Uses bid/ask midpoint logic to classify trades.
Show Volume Distribution — Toggles per-price-level buy/sell volume visualization.
Ticks Per Row — Controls how many ticks are grouped per volume level. Reduce this value for finer detail, or increase it to reduce visual load.
Calculated Bars — Sets how many historical bars the indicator should process. Higher value increases accuracy but may impact performance.
How to Use
1. Add the indicator to your chart.
2. Ensure that your symbol provides volume data (and preferably tick or second-level data).
3. The indicator will automatically select the optimal timeframe for detailed calculation.
4. If your TradingView subscription allows second-level data , enable “Use Seconds Resolution.”
5. If your subscription allows tick-level data , enable both “Use Tick Resolution” and “Use Seconds Resolution.”
6. Adjust the “Calculated Bars” input to set how many historical bars the indicator should process.
7. Observe the Volume Delta Candles :
* Green = Buy pressure dominates
* Red = Sell pressure dominates
8. To see buy/sell clustering by price, enable “Show Volume Distribution.”
9. If the indicator disables the map and shows:
" Volume Distribution disabled: Too many price levels detected (>50). Try decreasing 'Ticks Per Row' or using a lower chart resolution. If you don’t care about the map, just turn off 'Show Volume Distribution'. "
— follow the instructions to reduce chart load.
Notes
* Automatically adapts to your chart’s resolution and data availability.
* If your symbol doesn’t provide volume data, a runtime warning will appear.
* Works best on futures , FX , and crypto instruments with high-frequency volume streams.
Why Traders Love It
AVDM combines adaptive resolution , volume delta analysis , and visual distribution mapping into one clean, efficient tool.
Perfect for traders studying:
* Market microstructure
* Aggressive vs. passive participation
* Volume absorption
* Order flow imbalance zones
* Delta-based divergence signals
Technical Highlights
* Built with Pine Script v6
* Adaptive resolution logic (`security_lower_tf`)
* Smart memory-safe map rendering
* Dynamic bid/ask classification
* Automatic overload protection
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BOCS Channel Scalper Strategy - Automated Mean Reversion System# BOCS Channel Scalper Strategy - Automated Mean Reversion System
## WHAT THIS STRATEGY DOES:
This is an automated mean reversion trading strategy that identifies consolidation channels through volatility analysis and executes scalp trades when price enters entry zones near channel boundaries. Unlike breakout strategies, this system assumes price will revert to the channel mean, taking profits as price bounces back from extremes. Position sizing is fully customizable with three methods: fixed contracts, percentage of equity, or fixed dollar amount. Stop losses are placed just outside channel boundaries with take profits calculated either as fixed points or as a percentage of channel range.
## KEY DIFFERENCE FROM ORIGINAL BOCS:
**This strategy is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities:
- **Original BOCS**: 1-3 signals per channel (only on breakout)
- **Scalper Version**: 5-15+ signals per channel (every touch of entry zones)
- **Trade Style**: Mean reversion vs trend following
- **Hold Time**: Seconds to minutes vs minutes to hours
- **Best Markets**: Ranging/choppy conditions vs trending breakouts
This makes the scalper ideal for active day traders who want continuous opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased trade frequency also means higher commission costs and requires tighter risk management.
## TECHNICAL METHODOLOGY:
### Price Normalization Process:
The strategy normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis.
### Volatility Detection:
A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars).
### Channel Formation Logic:
When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The strategy tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas.
### Entry Signal Generation:
The strategy uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%):
- **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2)
- **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2)
Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. This captures mean reversion opportunities as price reaches channel extremes.
### Cooldown Filter:
An optional cooldown period (measured in bars) prevents signal spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long signal will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period.
### ATR Volatility Filter:
The strategy includes a multi-timeframe ATR filter to avoid trading during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while trading on 5-minute charts). The filter compares current ATR to a user-defined minimum threshold:
- If ATR ≥ threshold: Trading enabled
- If ATR < threshold: No signals fire
This prevents entries during dead zones where mean reversion is unreliable due to insufficient price movement.
### Take Profit Calculation:
Two TP methods are available:
**Fixed Points Mode**:
- Long TP = Entry + (TP_Ticks × syminfo.mintick)
- Short TP = Entry - (TP_Ticks × syminfo.mintick)
**Channel Percentage Mode**:
- Long TP = Entry + (ChannelRange × TP_Percent)
- Short TP = Entry - (ChannelRange × TP_Percent)
Default 50% targets the channel midline, a natural mean reversion target. Larger percentages aim for opposite channel edge.
### Stop Loss Placement:
Stop losses are placed just outside the channel boundary by a user-defined tick offset:
- Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick)
- Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick)
This logic assumes channel breaks invalidate the mean reversion thesis. If price breaks through, the range is no longer valid and position exits.
### Trade Execution Logic:
When entry conditions are met (price in zone, cooldown satisfied, ATR filter passed, no existing position):
1. Calculate entry price at zone boundary
2. Calculate TP and SL based on selected method
3. Execute strategy.entry() with calculated position size
4. Place strategy.exit() with TP limit and SL stop orders
5. Update info table with active trade details
The strategy enforces one position at a time by checking strategy.position_size == 0 before entry.
### Channel Breakout Management:
Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations.
### Position Sizing System:
Three methods calculate position size:
**Fixed Contracts**:
- Uses exact contract quantity specified in settings
- Best for futures traders (e.g., "trade 2 NQ contracts")
**Percentage of Equity**:
- position_size = (strategy.equity × equity_pct / 100) / close
- Dynamically scales with account growth
**Cash Amount**:
- position_size = cash_amount / close
- Maintains consistent dollar exposure regardless of price
## INPUT PARAMETERS:
### Position Sizing:
- **Position Size Type**: Choose Fixed Contracts, % of Equity, or Cash Amount
- **Number of Contracts**: Fixed quantity per trade (1-1000)
- **% of Equity**: Percentage of account to allocate (1-100%)
- **Cash Amount**: Dollar value per position ($100+)
### Channel Settings:
- **Nested Channels**: Allow multiple overlapping channels vs single channel
- **Normalization Length**: Lookback for high/low calculation (1-500, default 100)
- **Box Detection Length**: Period for volatility detection (1-100, default 14)
### Scalping Settings:
- **Enable Long Scalps**: Toggle long entries on/off
- **Enable Short Scalps**: Toggle short entries on/off
- **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%)
- **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5)
- **Cooldown Period (Bars)**: Minimum spacing between signals (0 = no cooldown)
### ATR Filter:
- **Enable ATR Filter**: Toggle volatility filter on/off
- **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.)
- **ATR Length**: Smoothing period (1-100, default 14)
- **Min ATR Value**: Threshold for trade enablement (0.1+, default 10.0)
### Take Profit Settings:
- **TP Method**: Choose Fixed Points or % of Channel
- **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30)
- **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%)
### Appearance:
- **Show Entry Zones**: Toggle zone labels on channels
- **Show Info Table**: Display real-time strategy status
- **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right)
- **Color Settings**: Customize long/short/TP/SL colors
## VISUAL INDICATORS:
- **Channel boxes** with semi-transparent fill showing consolidation zones
- **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼"
- **Entry signal arrows** below/above bars marking long/short entries
- **Active TP/SL lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL)
- **Info table** showing position status, channel state, last signal, entry/TP/SL prices, and ATR status
## HOW TO USE:
### For 1-3 Minute Scalping (NQ/ES):
- ATR Timeframe: "1" (1-minute)
- ATR Min Value: 10.0 (for NQ), adjust per instrument
- Entry Zone %: 20-25%
- TP Method: Fixed Points, 20-40 ticks
- SL Offset: 5-10 ticks
- Cooldown: 2-3 bars
- Position Size: 1-2 contracts
### For 5-15 Minute Day Trading:
- ATR Timeframe: "5" or match chart
- ATR Min Value: Adjust to instrument (test 8-15 for NQ)
- Entry Zone %: 20-30%
- TP Method: % of Channel, 40-60%
- SL Offset: 5-10 ticks
- Cooldown: 3-5 bars
- Position Size: Fixed contracts or 5-10% equity
### For 30-60 Minute Swing Scalping:
- ATR Timeframe: "15" or "30"
- ATR Min Value: Lower threshold for broader market
- Entry Zone %: 25-35%
- TP Method: % of Channel, 50-70%
- SL Offset: 10-15 ticks
- Cooldown: 5+ bars or disable
- Position Size: % of equity recommended
## BACKTEST CONSIDERATIONS:
- Strategy performs best in ranging, mean-reverting markets
- Strong trending markets produce more stop losses as price breaks channels
- ATR filter significantly reduces trade count but improves quality during low volatility
- Cooldown period trades signal quantity for signal quality
- Commission and slippage materially impact sub-5-minute timeframe performance
- Shorter timeframes require tighter entry zones (15-20%) to catch quick reversions
- % of Channel TP adapts better to varying channel sizes than fixed points
- Fixed contract sizing recommended for consistent risk per trade in futures
**Backtesting Parameters Used**: This strategy was developed and tested using realistic commission and slippage values to provide accurate performance expectations. Recommended settings: Commission of $1.40 per side (typical for NQ futures through discount brokers), slippage of 2 ticks to account for execution delays on fast-moving scalp entries. These values reflect real-world trading costs that active scalpers will encounter. Backtest results without proper cost simulation will significantly overstate profitability.
## COMPATIBLE MARKETS:
Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features require data feed with volume information but are optional for core functionality.
## KNOWN LIMITATIONS:
- Immediate touch entry can fire multiple times in choppy zones without adequate cooldown
- Channel deletion at 10-tick breaks may be too aggressive or lenient depending on instrument tick size
- ATR filter from lower timeframes requires higher-tier TradingView subscription (request.security limitation)
- Mean reversion logic fails in strong breakout scenarios leading to stop loss hits
- Position sizing via % of equity or cash amount calculates based on close price, may differ from actual fill price
- No partial closing capability - full position exits at TP or SL only
- Strategy does not account for gap openings or overnight holds
## RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance does not guarantee future results. This strategy is for educational purposes and backtesting only. Mean reversion strategies can experience extended drawdowns during trending markets. Stop losses may not fill at intended levels during extreme volatility or gaps. Thoroughly test on historical data and paper trade before risking real capital. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Automated trading systems can malfunction - monitor all live positions actively.
## ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community.
Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based signals, multi-timeframe ATR volatility filtering, flexible position sizing (fixed/percentage/cash), cooldown period filtering, dual TP methods (fixed points vs channel percentage), automated strategy execution with exit management, and real-time position monitoring table.
NQ Position Size CalculatorNQ Position Size Line Calculator is designed specifically for Nasdaq 100 futures (NQ) and micro futures (MNQ) traders who want to maintain disciplined risk management. This visual tool eliminates the guesswork from position sizing by displaying distance lines and contract calculations directly on your chart.
The indicator creates horizontal lines at 10-tick intervals from your stop loss level, showing you exactly how many contracts to trade at each distance to maintain your predetermined risk amount. Whether you're trading regular NQ contracts or micro MNQ contracts, this calculator ensures you never risk more than intended while providing instant visual feedback for optimal position sizing decisions.
How to Use the Indicator
Step 1: Configure Your Settings
Stop Loss Price: Enter your exact stop loss level (e.g., 20000.00)
Risk Amount ($): Set your maximum dollar risk per trade (e.g., $500)
Contract Type: Choose between:
NQ (Regular): $5 per tick - for larger accounts
MNQ (Micro): $0.50 per tick - for smaller accounts or conservative sizing
Display Options:
Max Lines: Number of distance lines to show (default: 30)
Show Labels: Toggle tick distance and contract count labels
Line Color: Customize the color of distance lines
Label Size: Choose tiny, small, or normal label sizes
Step 2: Read the Visual Display
Once configured, the indicator displays:
Stop Loss Line:
Thick yellow line marking your exact stop loss level
Yellow label showing the stop loss price
Distance Lines:
Dashed red lines at 10-tick intervals above and below your stop loss
Lines appear on both sides for long and short position planning
Labels (if enabled):
Green labels (right side): For long positions above your stop loss
Red labels (left side): For short positions below your stop loss
Format: "20T 5x" means 20 ticks distance, 5 contracts maximum
Step 3: Use the Information Tables
The indicator provides two helpful tables:
Position Size Table (top-right):
Shows common tick distances (10, 20, 40, 80, 160 ticks)
Displays risk per contract at each distance
Contract count for your specified risk amount
Total risk with rounded contract numbers
Settings Table (bottom-right):
Confirms your current risk amount
Shows selected contract type
Displays current settings for quick reference
Step 4: Apply to Your Trading
For Long Positions:
Look at the green labels on the right side of your chart
Find your desired entry level
Read the label to see: distance in ticks and maximum contracts
Example: "30T 8x" = 30 ticks from stop, buy 8 contracts maximum
For Short Positions:
Look at the red labels on the left side of your chart
Find your desired entry level
Read the label for tick distance and contract count
Example: "40T 6x" = 40 ticks from stop, sell 6 contracts maximum
Step 5: Trading Execution
Before Entering a Trade:
Identify your stop loss level and input it into the indicator
Choose your entry point by looking at the distance lines
Note the contract count from the corresponding label
Verify the risk amount matches your trading plan
Execute your trade with the calculated position size
Risk Management Features:
Contract rounding: All position sizes are rounded down (never up) to ensure you don't exceed your risk limit
Zero position filtering: Lines only show where position size is at least 1 contract
Dual-sided display: Plan both long and short opportunities simultaneously
Share SizePurpose: The "Share Size" indicator is a powerful risk management tool designed to help traders quickly determine appropriate share/contract sizes based on their predefined risk per trade and the current market's volatility (measured by ATR). It calculates potential dollar differences from recent highs/lows and translates them into a recommended share/contract size, accounting for a user-defined ATR-based offset. This helps you maintain consistent risk exposure across different instruments and market conditions.
How It Works: At its core, the indicator aims to answer the question: "How many shares/contracts can I trade to keep my dollar risk within limits if my stop loss is placed at a recent high or low, plus an ATR-based buffer?"
Price Difference Calculation: It first calculates the dollar difference between the current close price and the high and low of the current bar (Now) and the previous 5 bars (1 to 5).
Tick Size & Value Conversion: These price differences are then converted into dollar values using the instrument's specific tickSize and tickValue. You can select common futures contracts (MNQ, MES, MGC, MCL), a generic "Stock" setting, or define custom values.
ATR Offset: An Average True Range (ATR) based offset is added to these dollar differences. This offset acts as a buffer, simulating a stop loss placed beyond the immediate high/low, accounting for market noise or volatility.
Risk-Based Share Size: Finally, using your Default Risk ($) input, the indicator calculates how many shares/contracts you can take for each of the 6 high/low scenarios (current bar, 5 previous bars) to ensure your dollar risk per trade remains constant.
Dynamic Table: All these calculations are presented in a clear, real-time table at the bottom-left of your chart. The table dynamically adjusts its "Label" to show the selected symbol preset, making it easy to see which instrument's settings are currently being used. The "Shares" rows indicate the maximum shares/contracts you can trade for a given risk and stop placement. The cells corresponding to the largest dollar difference (and thus smallest share size) for both high and low scenarios are highlighted, drawing your attention to the most conservative entry points.
Key Benefits:
Consistent Risk: Helps maintain a consistent dollar risk per trade, regardless of the instrument or its current price/volatility.
Dynamic Sizing: Automatically adjusts share/contract size based on market volatility and your chosen stop placement.
Quick Reference: Provides a real-time, easy-to-read table directly on your chart, eliminating manual calculations.
Informed Decision Making: Assists in quickly assessing trade opportunities and potential position sizes.
Setup Parameters (Inputs)
When you add the "Share Size" indicator to your chart, you'll see a settings dialog with the following parameters:
1. Symbol Preset:
Purpose: This is the primary setting to define the tick size and value for your chosen trading instrument.
Options:
MNQ (Micro Nasdaq 100 Futures)
MES (Micro E-mini S&P 500 Futures)
MGC (Micro Gold Futures)
MCL (Micro Crude Oil Futures)
Stock (Generic stock setting, with tick size/value of 0.01)
Custom (Allows you to manually input tick size and value)
Default: MNQ
Importance: Crucial for accurate dollar calculations. Ensure this matches the instrument you are trading.
2. Tick Size (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the smallest price increment for your instrument.
Type: Float
Default: 0.25
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. You might need to change display=display.none to display=display.inline in the code if you want to see and adjust it directly in the settings for "Custom" mode.
3. Tick Value (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the dollar value of one tickSize increment.
Type: Float
Default: 0.50
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. Similar to Tick Size, you might need to adjust its display property if you want it visible.
4. Default Risk ($):
Purpose: This is your maximum desired dollar risk per trade. All share size calculations will be based on this value.
Type: Float
Default: 50.0
Hidden: This input is hidden (display=display.none). It's a critical setting, so consider making it visible by changing display=display.none to display=display.inline in the code if you want users to easily adjust their risk.
ATR Offset Settings (Group): This group of settings allows you to fine-tune the ATR-based buffer added to your potential stop loss.
5. ATR Offset Length:
Purpose: Defines the lookback period for the Average True Range (ATR) calculation used for the offset.
Type: Integer
Default: 7
Hidden: This input is hidden (display=display.none).
6. ATR Offset Timeframe:
Purpose: Specifies the timeframe on which the ATR for the offset will be calculated. This allows you to use ATR from a higher timeframe for your stop buffer, even if your chart is on a lower timeframe.
Type: Timeframe string (e.g., "1" for 1 minute, "60" for 1 hour, "D" for Daily)
Default: "1" (1 Minute)
Hidden: This input is hidden (display=display.none).
7. ATR Offset Multiplier (x ATR):
Purpose: Multiplies the calculated ATR value to determine the final dollar offset added to your high/low price difference. A value of 1.0 means one full ATR is added. A value of 0.5 means half an ATR is added.
Type: Float
Minimum Value: 0 (no offset)
Default: 1.0
Hidden: This input is hidden (display=display.none).
AsturRiskPanelIndicator Summary
ATR Engine
Length & Smoothing: Choose how many bars to use (default 14) and the smoothing method (RMA/SMA/EMA/WMA).
Median ATR: Computes a rolling median of ATR over a user-defined look-back (default 14) to derive a “scalp” target.
Scalp Target
Automatically set at ½ × median ATR, snapped to the nearest tick.
Optional rounding to whole points for simplicity.
Stop Calculation
ATR Multiplier: Scales current ATR by a user input (default 1.5) to produce your stop distance in points (and ticks when appropriate).
Distortion Handling: Switches between point-only and point + tick displays based on contract specifications.
Risk & Sizing
Risk % of account per trade (default 2 %).
Calculates dollar risk per contract and optimal contract count.
Displays all metrics (scalp, stop, risk/contract, max contracts, max risk, account size) in a customizable on-chart table.
ATR-Based Stop Placement Guidelines
Trade Context ATR Multiplier Notes
Tight Range Entry 1.0 × ATR High-conviction, precise entries. Expect more shake-outs.
Standard Trend Entry 1.5 × ATR Balanced for H2/L2, MTR, DT/DB entries.
Breakouts/Microchannels 2.0 × ATR Wide stops through chop—Brooks-style breathing room.
How to Use
Select ATR Settings
Pick an ATR length (e.g. 14) and smoothing (RMA for stability).
Adjust the median length if you want a faster/slower scalp line.
Align Multiplier with Your Setup
For tight-range entries, set ATR Multiplier ≈ 1.0.
For standard trend trades, leave at 1.5.
For breakout/pullback setups, increase to 2.0 or more.
Customize Risk Parameters
Enter your account size and desired risk % per trade (e.g. 2 %).
The table auto-calculates how many contracts you can take.
Read the On-Chart Table
Scalp shows your intraday target.
Stop gives Brooks-style stop distance in points (and ticks).
Risk/Contract is the dollar risk per contract.
Max Contracts tells you maximum position size.
Max Risk confirms total dollar exposure.
Visual Confirmation
Place your entry, then eyeball the scalp and stop levels against chart structure (e.g. swing highs/lows).
Adjust the ATR multiplier if market context shifts (e.g. volatility spikes).
By blending this sizing panel with contextual ATR multipliers, you’ll consistently give your trades the right amount of “breathing room” while keeping risk in check.
Wick Size in USD with 10-Bar AverageWick Size in USD with 10-Bar Average
Version: 1.0
Author: QCodeTrader
🔍 Overview
This indicator converts the price wicks of your candlestick chart into USD values based on ticks, providing both raw and smoothed data via a 10-bar simple moving average. It helps traders visualize the monetary impact of price extremes, making it easier to assess volatility, potential risk, and plan appropriate stop loss levels.
⚙️ Key Features
Tick-Based Calculation:
Converts wick sizes into ticks (using a fixed tick size of 0.01, typical for stocks) and then into USD using a customizable tick value.
10-Bar Moving Average:
Smooths out the wick values over the last 10 bars, giving you a clearer view of average wick behavior.
Bullish/Bearish Visual Cues:
The chart background automatically highlights bullish candles in green and bearish candles in red for quick visual assessment.
Stop Loss Optimization:
The indicator highlights long wick sizes, which can help you set more accurate stop loss levels. Even when the price moves in your favor, long wicks may indicate potential reversals—allowing you to account for this risk when planning your stop losses.
User-Friendly Customization:
Easily adjust the USD value per tick through the settings to tailor the indicator to your specific instrument.
📊 How It Works
Wick Calculation:
The indicator calculates the upper and lower wicks by measuring the distance between the candle’s high/low and its body (open/close).
Conversion to Ticks & USD:
These wick sizes are first converted from price points to ticks (dividing by a fixed tick size of 0.01) and then multiplied by the user-defined tick value to convert the measurement into USD.
Smoothing Data:
A 10-bar simple moving average is computed for both the upper and lower wick values, providing smoothed data that helps identify trends and deviations.
Visual Representation:
Columns display the raw wick sizes in USD.
Lines indicate the 10-bar moving averages.
Background Color shifts between green (bullish) and red (bearish) based on candle type.
⚡ How to Use
Add the Indicator:
Apply it to your chart to begin visualizing wick sizes in monetary terms.
Customize Settings:
Adjust the Tick Value in USD in the settings to match your instrument’s tick value.
(Note: The tick size is fixed at 0.01, which is standard for many stocks.)
Optimize Your Stop Loss:
Analyze the raw and averaged wick values to understand volatility. Long wicks—even when the price moves in your favor—may indicate potential reversals. This insight can help you set more accurate stop loss levels to protect your gains.
Analyze:
Use the indicator’s data to gauge market volatility and assess the significance of price movements, aiding in more informed trading decisions.
This indicator is perfect for traders looking to understand the impact of extreme price movements in monetary terms, optimize stop loss levels, and effectively manage risk across stocks and other instruments with similar tick structures.
Mean Price
^^ Plotting switched to Line.
This method of financial time series (aka bars) downsampling is literally, naturally, and thankfully the best you can do in terms of maximizing info gain. You can finally chill and feed it to your studies & eyes, and probably use nothing else anymore.
(HL2 and occ3 also have use cases, but other aggregation methods? Not really, even if they do, the use cases are ‘very’ specific). Tho in order to understand why, you gotta read the following wall, or just believe me telling you, ‘I put it on my momma’.
The true story about trading volumes and why this is all a big misdirection
Actually, you don’t need to be a quant to get there. All you gotta do is stop blindly following other people’s contextual (at best) solutions, eg OC2 aggregation xD, and start using your own brain to figure things out.
Every individual trade (basically an imprint on 1D price space that emerges when market orders hit the order book) has several features like: price, time, volume, AND direction (Up if a market buy order hits the asks, Down if a market sell order hits the bids). Now, the last two features—volume and direction—can be effectively combined into one (by multiplying volume by 1 or -1), and this is probably how every order matching engine should output data. If we’re not considering size/direction, we’re leaving data behind. Moreover, trades aren’t just one-price dots all the time. One trade can consume liquidity on several levels of the order book, so a single trade can be several ticks big on the price axis.
You may think now that there are no zero-volume ticks. Well, yes and no. It depends on how you design an exchange and whether you allow intra-spread trades/mid-spread trades (now try to Google it). Intra-spread trades could happen if implemented when a matching engine receives both buy and sell orders at the same microsecond period. This way, you can match the orders with each other at a better price for both parties without even hitting the book and consuming liquidity. Also, if orders have different sizes, the remaining part of the bigger order can be sent to the order book. Basically, this type of trade can be treated as an OTC trade, having zero volume because we never actually hit the book—there’s no imprint. Another reason why it makes sense is when we think about volume as an impact or imbalance act, and how the medium (order book in our case) responds to it, providing information. OTC and mid-spread trades are not aggressive sells or buys; they’re neutral ticks, so to say. However huge they are, sometimes many blocks on NYSE, they don’t move the price because there’s no impact on the medium (again, which is the order book)—they’re not providing information.
... Now, we need to aggregate these trades into, let’s say, 1-hour bars (remember that a trade can have either positive or negative volume). We either don’t want to do it, or we don’t have this kind of information. What we can do is take already aggregated OHLC bars and extract all the info from them. Given the market is fractal, bars & trades gotta have the same set of features:
- Highest & lowest ticks (high & low) <- by price;
- First & last ticks (open & close) <- by time;
- Biggest and smallest ticks <- by volume.*
*e.g., in the array ,
2323: biggest trade,
-1212: smallest trade.
Now, in our world, somehow nobody started to care about the biggest and smallest trades and their inclusion in OHLC data, while this is actually natural. It’s the same way as it’s done with high & low and open & close: we choose the minimum and maximum value of a given feature/axis within the aggregation period.
So, we don’t have these 2 values: biggest and smallest ticks. The best we can do is infer them, and given the fact the biggest and smallest ticks can be located with the same probability everywhere, all we can do is predict them in the middle of the bar, both in time and price axes. That’s why you can see two HL2’s in each of the 3 formulas in the code.
So, summed up absolute volumes that you see in almost every trading platform are actually just a derivative metric, something that I call Type 2 time series in my own (proprietary ‘for now’) methods. It doesn’t have much to do with market orders hitting the non-uniform medium (aka order book); it’s more like a statistic. Still wanna use VWAP? Ok, but you gotta understand you’re weighting Type 1 (natural) time series by Type 2 (synthetic) ones.
How to combine all the data in the right way (khmm khhm ‘order’)
Now, since we have 6 values for each bar, let’s see what information we have about them, what we don’t have, and what we can do about it:
- Open and close: we got both when and where (time (order) and price);
- High and low: we got where, but we don’t know when;
- Biggest & smallest trades: we know shit, we infer it the way it was described before.'
By using the location of the close & open prices relative to the high & low prices, we can make educated guesses about whether high or low was made first in a given bar. It’s not perfect, but it’s ultimately all we can do—this is the very last bit of info we can extract from the data we have.
There are 2 methods for inferring volume delta (which I call simply volume) that are presented everywhere, even here on TradingView. Funny thing is, this is actually 2 parts of the 1 method. I wonder how many folks see through it xD. The same method can be used for both inferring volume delta AND making educated guesses whether high or low was made first.
Imagine and/or find the cases on your charts to understand faster:
* Close > open means we have an up bar and probably the volume is positive, and probably high was made later than low.
* Close < open means we have a down bar and probably the volume is negative, and probably low was made later than high.
Now that’s the point when you see that these 2 mentioned methods are actually parts of the 1 method:
If close = open, we still have another clue: distance from open/close pair to high (HC), and distance from open/close pair to low (LC):
* HC < LC, probably high was made later.
* HC > LC, probably low was made later.
And only if close = open and HC = LC, only in this case we have no clue whether high or low was made earlier within a bar. We simply don’t have any more information to even guess. This bar is called a neutral bar.
At this point, we have both time (order) and price info for each of our 6 values. Now, we have to solve another weighted average problem, and that’s it. We’ll weight prices according to the order we’ve guessed. In the neutral bar case, open has a weight of 1, close has a weight of 3, and both high and low have weights of 2 since we can’t infer which one was made first. In all cases, biggest and smallest ticks are modeled with HL2 and weighted like they’re located in the middle of the bar in a time sense.
P.S.: I’ve also included a "robust" method where all the bars are treated like neutral ones. I’ve used it before; obviously, it has lesser info gain -> works a bit worse.
Moving Average Crossover Swing StrategyMoving Average Crossover Swing Strategy
**Overview:**
The basic concept of this strategy is to generate a signal when a faster/shorter length moving average crosses over (for Longs) or crosses under (for Shorts) a medium/longer length moving average. All of which are customizable. This strategy can work on any timeframe, however the daily is the timeframe used for the default settings and screenshots, as it was designed to be a multi-day swing strategy. Once a signal has been confirmed with a candle close, based on user options, the strategy will enter the trade on the open of the next candle.
The crossover strategy is nothing new to trading, but what can make this strategy unique and helpful, is the addition of further confirmation points, ATR based stop loss and take profit targets, optional early exit criteria, customizable to your needs and style, and just about everything visual can be toggled on/off. This strategy is based on a Trend (MA) indicator and a Momentum (MACD) indicator. While a Volume-based indicator is not shown here, one could consider using their favorite from that category to further compliment the signal idea.
It should be noted that depending on the time frame, direction(s) chosen, the signal options, confirmation options, and exit options selected, that a ticker may not produce more than 100 trades on the back test. Depending on your style and frequency, one could consider adjusting options and/or testing multiple tickers. It should also be noted that this strategy simply tests the underlying stock prices, not options contracts. And of course, testing this strategy against historical data does not assume that the same results will occur in future price action.
Shoutout given to Ripster's Clouds Indicator as pieces of that code were taken and modified to create both the Cloud visualization effects, and the Moving Average Pair Plots that are implemented in this strategy.
BASIC DEFAULTS
All can be changed as normal
Initial capital = 10,000
Order Sizing = 25% of equity (use the "Inputs" tab to modify this)
Pyramiding = 0
Commission = 0.65 USD per order
Price Verification = 1 tick
Slippage = 1 tick
RISK MANAGMENT
You will notice two different percentage options and ATR multipliers. This strategy will adjust position sizing by not exceeding either one of those % values based on the ATR (Average True Range) of the symbol and the multipliers selected, should the stock hit the stop loss price.
For Example, lets assume these values are true:
Account size = $10,000,
Max Risk = 1% of account size
Max Position Size = 25% of the account size
Stock Price = 23.45
ATR = 3.5
ATR Stop Loss Multiplier = 1.4
Then the formulas would be:
ACCT_SIZE * MaxRisk_% = 10000 * .01 = $100 (MaxCashRisk)
-----
MaxCashRisk / (ATR * ATR_SL_MULTIPLIER) = 100 / (3.5 * 1.4) = 20.4 Shares based on Max Cash Risk
-----
(ACCT_SIZE * MaxEquity_%) / STOCK_PRICE = (10000 * .25) / 23.45 = 106.61 Shares based on Max Equity Allocation
The minimum value of each of those options is then used, which in this case would be to purchase 20 shares so as not to exceed the max dollar risk should the stock reach the stop loss target. Likewise, if the ATR were to be much lower, say 0.48 cents, and all else the same, then the strategy would purchase the 106 shares based on Max Equity Allocation because the Max Cash Risk would require 149.25 shares.
MOVING AVERAGE OPTIONS
Select between and change the length & type of up to 5 pairs (10 total) of moving averages
The "Show Cloud-x" option will display a fill color between the "a" and "b" pairs
All moving averages lines can be toggled on/off in the "Style" tab, as well as adjusting their colors.
Visualization features do not affect calculations, meaning you could have all or nothing on the chart and the strategy will still produce results
SIGNAL CHOICES
Choose the fast/shorter length MA and the medium/longer length MA to determine the entry signal
CONFIRMATION OPTIONS
Both of these have customizable values and can be toggled on/off
A candle close over a slower/much longer length moving average
An additional cross-over (cross-under for Shorts) on the MACD indicator using default MACD values. While the MACD indicator is not necessary to have on the chart, it can help to add that for visualization. The calculations will perform whether the indicator is on the chart or not.
EARLY EXIT CRITERIA
Both can be toggled on/off with customizable values
MA Cross Exit will exit the trade early if the select moving averages cross-under (for longs) or cross-over (for shorts), indicating a potential reversal.
Max Bars in Trades will act as a last-resort exit by simply calculating the amount of full bars the trade has been open, and exiting on the opening of the next bar. For example: the default value is 8 bars, so after 8 full bars in the trade, if no other exit has been triggered (Stop Loss, Take Profit, or MA Cross(if enabled)), then the trade will exit at the opening of the 9th bar.
Finally, there is a table displaying the amount of trades taken for each side, and the amount & percent of both early exits. This table can be turned off in the "Style" tab
ADDITIONAL PLOTS
MACD (Moving Average Convergence/Divergence):
- The MACD is an optional confirmation indicator for this strategy.
- Plotting the indicator is not necessary for the strategy to work, but it can be helpful to visually see the status and position of the MACD if this feature is enabled in the strategy
- This helps to identify if there is also momentum behind the entry signal
ICT Turtle Soup | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Turtle Soup Indicator! This indicator is built around the ICT "Turtle Soup" model. The strategy has 5 steps for execution which are described in this write-up. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Turtle Soup Indicator :
Implementation of ICT's Turtle Soup Strategy
Adaptive Entry Method
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The ICT Turtle Soup strategy may have different implementations depending on the selected method of the trader. This indicator's implementation is described as :
1. Mark higher timerame liquidity zones.
Liquidity zones are where a lot of market orders sit in the chart. They are usually formed from the long / short position holders' "liquidity" levels. There are various ways to find them, most common one being drawing them on the latest high & low pivot points in the chart, which this indicator does.
2. Mark current timeframe market structure.
The market structure is the current flow of the market. It tells you if the market is trending right now, and the way it's trending towards. It's formed from swing higs, swing lows and support / resistance levels.
3. Wait for market to make a liquidity grab on the higher timeframe liquidity zone.
A liquidity grab is when the marked liquidity zones have a false breakout, which means that it gets broken for a brief amount of time, but then price falls back to it's previous position.
4. Buyside liquidity grabs are "Short" entries and Sellside liquidity grabs are "Long" entries by default.
5. Wait for the market-structure shift in the current timeframe for entry confirmation.
A market-structure shift happens when the current market structure changes, usually when a new swing high / swing low is formed. This indicator uses it as a confirmation for position entry as it gives an insight of the new trend of the market.
6. Place Take-Profit and Stop-Loss levels according to the risk ratio.
This indicator uses "Average True Range" when placing the stop-loss & take-profit levels. Average True Range calculates the average size of a candle and the indicator places the stop-loss level using ATR times the risk setting determined by the user, then places the take-profit level trying to keep a minimum of 1:1 risk-reward ratio.
This indicator follows these steps and inform you step by step by plotting them in your chart.
🚩UNIQUENESS
This indicator is an all-in-one suit for the ICT's Turtle Soup concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. It's designed for simplyfing a rather complex strategy, helping you to execute it with clean signals. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️SETTINGS
1. General Configuration
MSS Swing Length -> The swing length when finding liquidity zones for market structure-shift detection.
Higher Timeframe -> The higher timeframe to look for liquidity grabs. This timeframe setting must be higher than the current chart's timeframe for the indicator to work.
Breakout Method -> If "Wick" is selected, a bar wick will be enough to confirm a market structure-shift. If "Close" is selected, the bar must close above / below the liquidity zone to confirm a market structure-shift.
Entry Method ->
"Classic" : Works as described on the "HOW DOES IT WORK" section.
"Adaptive" : When "Adaptive" is selected, the entry conditions may chance depending on the current performance of the indicator. It saves the entry conditions and the performance of the past entries, then for the new entries it checks if it predicted the liquidity grabs correctly with the current setup, if so, continues with the same logic. If not, it changes behaviour to reverse the entries from long / short to short / long.
2. TP / SL
TP / SL Method -> If "Fixed" is selected, you can adjust the TP / SL ratios from the settings below. If "Dynamic" is selected, the TP / SL zones will be auto-determined by the algorithm.
Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
Inversion Fair Value Gap Screener | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Inverse Fair Value Gap Screener! This screener can provide information about the latest Inverse Fair Value Gaps in up to 5 tickers. You can also customize the algorithm that finds the Inverse Fair Value Gaps and the styling of the screener.
Features of the new Inverse Fair Value Gap (IFVG) Screener :
Find Latest Inverse Fair Value Gaps Across 5 Tickers
Shows Their Information Of :
Latest Status
Number Of Retests
Consumption Percent
Volume
Customizable Algorithm / Styling
📌 HOW DOES IT WORK ?
A Fair Value Gap generally occur when there is an imbalance in the market. They can be detected by specific formations within the chart. An Inverse Fair Value Gap is when a FVG becomes invalidated, thus reversing the direction of the FVG.
IFVGs get consumed when a Close / Wick enters the IFVG zone. Check this example:
This screener then finds Fair Value Gaps across 5 different tickers, and shows the latest information about them.
Status ->
Far -> The current price is far away from the IFVG.
Approaching ⬆️/⬇️ -> The current price is approaching the IFVG, and the direction it's approaching from.
Inside -> The price is currently inside the IFVG.
Retests -> Retest means the price tried to invalidate the IFVG, but failed to do so. Here you can see how many times the price retested the IFVG.
Consumed -> IFVGs get consumed when a Close / Wick enters the IFVG zone. For example, if the price hits the middle of the IFVG zone, the zone is considered 50% consumed.
Volume -> Volume of a IFVG is essentially the volume of the bar that broke the original FVG that formed it.
🚩UNIQUENESS
This screener can detect latest Inverse Fair Value Gaps and give information about them for up to 5 tickers. This saves the user time by showing them all in a dashboard at the same time. The screener also uniquely shows information about the number of retests and the consumed percent of the IFVG, as well as it's volume. We believe that this extra information will help you spot reliable IFVGs easier.
⚙️SETTINGS
1. Tickers
You can set up to 5 tickers for the screener to scan Fair Value Gaps here. You can also enable / disable them and set their individual timeframes.
2. General Configuration
FVG Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
IFVG Zone Invalidation -> Select between Wick & Close price for IFVG Zone Invalidation. This setting also switches the type for IFVG consumption.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivities resulting in spotting bigger FVGs, and higher sensitivities resulting in spotting all sizes of FVGs.
Breaker Blocks Screener | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Breaker Blocks Screener! This screener can provide information about the latest breaker blocks in up to 5 tickers. You can also customize the algorithm that finds the breaker blocks and the styling of the screener.
Features of the new Breaker Blocks Screener :
Find Latest Breaker Blocks Accross 5 Tickers
Latest Status, Restests & Volume
Customizable Algoritm / Styling
📌 HOW DOES IT WORK ?
Breaker blocks form when an order block fails, or "breaks". It is often associated with market going in the opposite direction of the broken order block, and they can be spotted by following order blocks and finding the point they get broken, ie. price goes below a bullish order block.
The volume of a breaker block is simply the total volume of the bar that the original order block is broken. Often the higher the breaking bar's volume, the stronger the breaker block is.
This screener then finds breaker blocks accross 5 different tickers, and shows the latest information about them.
Status ->
Far -> The current price is far away from the breaker block.
Approaching ⬆️/⬇️ -> The current price is approaching the breaker block, and the direction it's approaching from.
Inside -> The price is currently inside the breaker block.
Retests -> Retest means the price to invalidate the breaker block, but failed to do so. Here you can see how many times the price retested the breaker block.
For the volume, check the top of the "How Does It Work" section.
🚩UNIQUENESS
This screener can detect latest breaker blocks and give information about them for up to 5 tickers. This saves the user time by showing them all in a dashboard at the same time. The screener shows the number of the retests of the breaker block as an unique trait. Another unique ability of the screener is that it shows the latest valid breaker block's volume in the dashboard.
⚙️SETTINGS
1. Tickers
You can set up to 5 tickers for the screener to scan breaker blocks here. You can also enable / disable them and set their individual timeframes.
2. General Configuration
Zone Invalidations -> Select between Wick & Close price for Order & Breaker Block Invalidation.
Swing Length -> Swing length is used when finding order block formations. Smaller values will result in finding smaller order blocks.
Fair Value Gap Screener | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Fair Value Gap Screener! This screener can provide information about the latest Fair Value Gaps in up to 5 tickers. You can also customize the algorithm that finds the Fair Value Gaps and the styling of the screener.
Features of the new Fair Value Gap (FVG) Screener :
Find Latest Fair Value Gaps Accross 5 Tickers
Shows Their Information Of :
Latest Status
Number Of Retests
Consumption Percent
Bullish & Bearish Volume
Customizable Algoritm / Styling
📌 HOW DOES IT WORK ?
A Fair Value Gap generally occur when there is an imbalance in the market. They can be detected by specific formations within the chart. This screener then finds Fair Value Gaps accross 5 different tickers, and shows the latest information about them.
Status ->
Far -> The current price is far away from the FVG.
Approaching ⬆️/⬇️ -> The current price is approaching the FVG, and the direction it's approaching from.
Inside -> The price is currently inside the FVG.
Retests -> Retest means the price tried to invalidate the FVG, but failed to do so. Here you can see how many times the price retested the FVG.
Consumed -> FVGs get consumed when a Close / Wick enters the FVG zone. For example, if the price hits the middle of the FVG zone, the zone is considered 50% consumed.
Bullish / Bearish Volume -> Bullish & Bearish volume of a FVG is calculated by analyzing the bars that formed it. For example in a bullish FVG, the bullish volume is the total volume of the first 2 bars forming the FVG, and the bearish volume is the volume of the 3rd bar that forms it.
🚩UNIQUENESS
This screener can detect latest Fair Value Gaps and give information about them for up to 5 tickers. This saves the user time by showing them all in a dashboard at the same time. The screener also uniquely shows information about the number of retests and the consumed percent of the FVG, as well as it's bullish & bearish volume. We believe that this extra information will help you spot reliable FVGs easier.
⚙️SETTINGS
1. Tickers
You can set up to 5 tickers for the screener to scan Fair Value Gaps here. You can also enable / disable them and set their individual timeframes.
2. General Configuration
Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
Order Blocks Screener | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Order Blocks Screener! This screener can provide information about the latest order blocks in up to 5 tickers. You can also customize the algorithm that finds the order blocks and the styling of the screener.
Features of the new Order Blocks Screener :
Find Latest Order Blocks Accross 5 Tickers
Latest Status, Restests, Bullish & Bearish Volume
Customizable Algoritm / Styling
📌 HOW DOES IT WORK ?
Order blocks occur when there is a high amount of market orders exist on a price range. It is possible to find order blocks using specific formations on the chart.
The high & low volume of order blocks should be taken into consideration while determining their strengths. The determination of the high & low volume of order blocks are similar to FVGs, in a bullish order block, the high volume is the last 2 bars' total volume, while the low volume is the oldest bar's volume. In a bearish order block scenerio, the low volume becomes the last 2 bars' total volume.
This screener then finds order blocks accross 5 different tickers, and shows the latest information about them.
Status ->
Far -> The current price is far away from the order block.
Approaching ⬆️/⬇️ -> The current price is approaching the order block, and the direction it's approaching from.
Inside -> The price is currently inside the order block.
Retests -> Retest means the price to invalidate the order block, but failed to do so. Here you can see how many times the price retested the order block.
For the bullish / bearish volume, check the "How Does It Work" section.
🚩UNIQUENESS
This screener can detect latest order blocks and give information about them for up to 5 tickers. This saves the user time by showing them all in a dashboard at the same time. The screener shows the number of the retests of the order block as an unique trait. Another unique ability of the screener is that it shows the latest valid order block's bullish and bearish volume in the dashboard.
⚙️SETTINGS
1. Tickers
You can set up to 5 tickers for the screener to scan order blocks here. You can also enable / disable them and set their individual timeframes.
2. General Configuration
Zone Invalidation -> Select between Wick & Close price for Order Block Invalidation.
Swing Length -> Swing length is used when finding order block formations. Smaller values will result in finding smaller order blocks.
MOST + Moving Average ScreenerScreener version of Anıl Özekşi's Moving Stop Loss (MOST) Indicator:
USERS MAY SCREEN MOST WITH 11 DIFFERENT TYPES OF MOVING AVERAGES + THEY CAN ALSO SCREEN SIGNALS WITH THAT 11 MOVING AVERAGES INSTEAD OF USING MOST LINE.
Adjustable Moving Average Types:
SMA : Simple Moving Average
EMA : Exponential Moving Average
WMA : Weighted Moving Average
DEMA : Double Exponential Moving Average
TMA : Triangular Moving Average
VAR : Variable Index Dynamic Moving Average aka VIDYA
WWMA : Welles Wilder's Moving Average
ZLEMA : Zero Lag Exponential Moving Average
TSF : True Strength Force
HULL : Hull Moving Average
TILL : Tillson T3 Moving Average
About Screener Panel:
Users can explore 20 different and user-defined tickers, which can be changed from the SETTINGS (shares, crypto, commodities...) on this screener version.
The screener panel shows up right after the bars on the right side of the chart.
-In this screener version of MOST, users can define the number of demanded tickers (symbols) from 1 to 20 by checking the relevant boxes on the settings tab.
-All selected tickers can be screened in different timeframes.
-Also, different timeframes of the same Ticker can be screened.
IMPORTANT NOTICE:
Screener shows the results in 3 different logic:
1st LOGIC (Default Settings):
BUY AND SELL SIGNALS of MOST and MOVING AVERAGE LINE
Most Buy Signal: Moving Average Crosses ABOVE the MOST LINE
Most Sel Signal: Moving Average Crosses BELOW the MOST LINE
Tickers seen in green are the ones that are in an uptrend, according to MOST.
The ones that appear in red are those in the SELL signal, in a downtrend.
The numbers before each Ticker indicate how many bars passed after MOST's last BUY or SELL signal.
For example, according to the indicator, when BTCUSDT appears (3) in GREEN, Bitcoin switched to a BUY signal 3 bars ago.
2nd LOGIC (Moving Average & Price Flips Screener Mode):
This mode can only be activated by checking the 'Activate Moving Average Screening Mode' box on the settings menu.
MOST line will be disappeared after checking the box.
Buy Signal: When the Selected Price crosses ABOVE the selected Moving Average.
Sell Signal: When the Selected Price crosses BELOW the selected Moving Average.
Tickers seen in green are the ones that are in an uptrend, according to Moving Average & Price Flips.
The ones that appear in red are those in the SELL signal, in a downtrend.
The numbers before each Ticker indicate how many bars passed after the last BUY or SELL signal of Moving Average & Price Flips.
For example, according to the indicator, when BTCUSDT appears (3) in GREEN, Bitcoin switched to a BUY signal 3 bars ago.
3rd LOGIC (Moving Average Color Change Screener Mode):
Both 'Activate Moving Average Screening Mode' and 'Activate Moving Average Color Change Screening Mode' boxes must be checked in the settings tab.
Moving Average Line will turn out into two colors.
Green color means the moving average value is greater than the previous bar's value.
Red color means the moving average value is smaller than the previous bar's value.
Buy Signal: After the Selected Moving Average turns GREEN from red.
Sell Signal: After the Selected Moving Average turns RED from green.
-Screener shows the information about the color changes of the selected Moving Average with default settings.
If this option is preferred, users are advised to enlarge the length to have better signals.
Tickers seen in green are the ones that are in an uptrend, according to Moving Average Color.
The ones that appear in red are those in the SELL signal, in a downtrend.
The numbers before each Ticker indicate how many bars passed after the last BUY or SELL signal of Moving Average Color Change.
For example, according to the indicator, when BTCUSDT appears (3) in GREEN, Bitcoin switched to a BUY signal 3 bars ago.
Mizar_LibraryThe "Mizar_Library" is a powerful tool designed for Pine Script™ programmer’s, providing a collection of general functions that facilitate the usage of Mizar’s DCA (Dollar-Cost-Averaging) bot system.
To begin using the Mizar Library, you first need to import it into your indicator script. Insert the following line below your indicator initiation line: import Mizar_Trading/Mizar_Library/1 as mizar (mizar is the chosen alias).
In the import statement, Mizar_Trading.Mizar_Library_v1 refers to the specific version of the Mizar Library you wish to use. Feel free to modify mizar to your preferred alias name.
Once the library is imported, you can leverage its functions by prefixing them with mizar. . This will prompt auto-completion suggestions displaying all the available user-defined functions provided by the Mizar Library.
Now, let's delve into some of the key functions available in the Mizar Library:
DCA_bot_msg(_cmd)
The DCA_bot_msg function accepts an user-defined type (UDT) _cmd as a parameter and returns a string with the complete JSON command for a Mizar DCA bot.
Parameters:
_cmd (bot_params) : ::: User-defined type (UDT) that holds all the necessary information for the bot command.
Returns: A string with the complete JSON command for a Mizar DCA bot.
rounding_to_ticks(value, ticks, rounding_type)
The rounding_to_ticks function rounds a calculated price to the nearest actual price based on the specified tick size.
Parameters:
value (float) : ::: The calculated price as float type, to be rounded to the nearest real price.
ticks (float) : ::: The smallest possible price obtained through a request in your script.
rounding_type (int) : ::: The rounding type for the price: 0 = closest real price, 1 = closest real price above, 2 = closest real price below.
Returns: A float value representing the rounded price to the next tick.
bot_params
Bot_params is an user-defined type (UDT) that represents the parameters required for a Mizar DCA bot.
Fields:
bot_id (series string) : The ID number of your Mizar DCA bot.
api_key (series string) : Your private API key from your Mizar account (keep it confidential!).
action (series string) : The command to perform: "open" (standard) or "close" optional .
tp_perc (series string) : The take profit percentage in decimal form (1% = "0.01") optional .
base_asset (series string) : The cryptocurrency you want to buy (e.g., "BTC").
quote_asset (series string) : The coin or fiat currency used for payment (e.g., "USDT" is standard if not specified) optional .
direction (series string) : The direction of the position: "long" or "short" (only applicable for two-way hedge bots) optional .
To obtain the JSON command string for the alert_function call, you can use the DCA_bot_msg function provided by the library. Simply pass the cmd_msg UDT as an argument and assign the returned string value to a variable.
Here's an example to illustrate the process:
// Import of the Mizar Library to use the included functions
import/Mizar_Trading/Mizar_Library/1 as mizar
// Example to set a variable called “cmd_msg” and all of its parameters
cmd_msg = mizar.bot_params. new()
cmd_msg.action := "open"
cmd_msg.api_key := "top secret"
cmd_msg.bot_id := "9999"
cmd_msg.base_asset := "BTC"
cmd_msg.quote_asset := "USDT"
cmd_msg.direction := "long"
cmd_msg.tp_perc := "0.015"
// Calling the Mizar conversion function named “DCA_bot_msg()” with the cmd_msg as argument to receive the JSON command and save it in a string variable called “alert_msg”
alert_msg = mizar.DCA_bot_msg(cmd_msg)
Feel free to utilize (series) string variables instead of constant strings. By incorporating the Mizar Library into your Pine Script, you gain access to a powerful set of functions and can leverage them according to your specific requirements.
For additional help or support, you can join the Mizar Discord channel. There, you'll find a dedicated Pine Script channel where you can ask any questions related to Pine Script.
SL and TP - ATRThis indicator is using ATR ( Average True Range ) to set the Target point and Stop loss.
Use the pink number as target, always.
If you are in Long position, use the green number as stop loss, so the red number is not useful in Buys.
If you are in Short position, use the Red number as stop loss, so the green number is not useful in Sells.
** Need to enter the numbers in ticks --> VERY IMPORTANT: Write it completely, even the numbers after the point sign but DO NOT WRITE the point sign itself. e.g. : if the target tick on indicator is 123.75, you have to write 12375 ticks for your TP. ( one more example: If the number is 0.0001203 , write 1203 ticks. )
Enter the information of the opening candle.
Most of the times, risk/reward ratio is a bit higher than 1.
Works on multi timeframes. P.S: Haven't checked the weekly timeframe.
Not trying to oversell the indicator, but this is perhaps the best TP/SL specifier.
For beauty purposes, change (Sl @ buy) and (TP @ sell) to histograms.
Histograms are only for visual purposes. Customize the indicator as you want :)) Hope you enjoy
Bitmex BTC Perpetual PremiumThis script tracks the premium of the Bitcoin Perpetual futures at Bimex exchange relative to 3 different reference prices.
The difference between this script and already published scripts is that it tracks the premium relative to 3 different reference prices. This tends to produce slightly different results.
This script is also open source, so you can verify the calculations, or use it as a basis for your own script.
The 3 plots uses the following reference prices:
Blue Area:
Bitmex Index price, ticker: BITMEX:XBT
Red line:
Bitmex Perpetual Premium, ticker XBTUSDPI
(This one is not used as reference, but simply plots the ticker*100)
Orange line:
The reference here is a price calculated by the tickers in trading view based on the Bitmex indices with weighing as follows:
Bitstamp:28,81%
Bittrex:5,5%
Coinbase: 38,07%
Gemini: 7,34%
Kraken: 20,28
Please note that Bitmex changes the bases of its indices regularly. Bitmex might also "rule out" on of these exchanges if there is a short term problem.
Realtime RenkoI've been working on real-time renko for a while as a coding challenge. The interesting problem here is building renko bricks that form based on incoming tick data rather than waiting for bar closes. Every tick that comes through gets processed immediately, and when price moves enough to complete a brick, that brick closes and a new one opens right then. It's just neat because you can run it and it updates as you'd expect with renko, forming bricks based purely on price movement happening in real time rather than waiting for arbitrary time intervals to pass.
The three brick sizing methods give you flexibility in how you define "enough movement" to form a new brick. Traditional renko uses a fixed price range, so if you set it to 10 ticks, every brick represents exactly 10 ticks of movement. This works well for instruments with stable tick sizes and predictable volatility. ATR-based sizing calculates the average true range once at startup using a weighted average across all historical bars, then divides that by your brick value input. If you want bricks that are one full ATR in size, you'd use a brick value of 1. If you want half-ATR bricks, use 2. This inverted relationship exists because the calculation is ATR divided by your input, which lets you work with multiples and fractions intuitively. Percentage-based sizing makes each brick a fixed percentage move from the previous brick's close, which automatically scales with price level and works well for instruments that move proportionally rather than in absolute tick increments.
The best part about this implementation is how it uses varip for state management. When you first load the indicator, there's no history at all. Everything starts fresh from the moment you add it to your chart because varip variables only exist in real-time. This means you're watching actual renko bricks form from real tick data as it arrives. The indicator builds its own internal history as it runs, storing up to 250 completed bricks in memory, but that history only exists for the current session. Refresh the page or reload the indicator and it starts over from scratch.
The visual implementation uses boxes for brick bodies and lines for wicks, drawn at offset bar indices to create the appearance of a continuous renko chart in the indicator pane. Each brick occupies two bar index positions horizontally, which spaces them out and makes the chart readable. The current brick updates in real time as new ticks arrive, with its high, low, and close values adjusting continuously until it reaches the threshold to close and become finalized. Once a brick closes, it gets pushed into the history array and a new brick opens at the closing level of the previous one.
What makes this especially useful for debugging and analysis are the hover tooltips on each brick. Clicking on any brick brings up information showing when it opened with millisecond precision, how long it took to form from open to close, its internal bar index within the renko sequence, and the brick size being used. That time delta measurement is particularly valuable because it reveals the pace of price movement. A brick that forms in five seconds indicates very different market conditions than one that takes three minutes, even though both bricks represent the same amount of price movement. You can spot acceleration and deceleration in trend development by watching how quickly consecutive bricks form.
The pine logs that generate when bricks close serve as breadcrumbs back to the main chart. Every time a brick finalizes, the indicator writes a log entry with the same information shown in the tooltip. You can click that log entry and TradingView jumps your main chart to the exact timestamp when that brick closed. This lets you correlate renko brick formation with what was happening on the time-based chart, which is critical for understanding context. A brick that closed during a major news announcement or at a key support level tells a different story than one that closed during quiet drift, and the logs make it trivial to investigate those situations.
The internal bar indexing system maintains a separate count from the chart's bar_index, giving each renko brick its own sequential number starting from when the indicator begins running. This makes it easy to reference specific bricks in your analysis or when discussing patterns with others. The internal index increments only when a brick closes, so it's a pure measure of how many bricks have formed regardless of how much chart time has passed. You can match these indices between the visual bricks and the log entries, which helps when you're trying to track down the details of a specific brick that caught your attention.
Brick overshoot handling ensures that when price blows through the threshold level instead of just barely touching it, the brick closes at the threshold and the excess movement carries over to the next brick. This prevents gaps in the renko sequence and maintains the integrity of the brick sizing. If price shoots up through your bullish threshold and keeps going, the current brick closes at exactly the threshold level and the new brick opens there with the overshoot already baked into its initial high. Without this logic, you'd get renko bricks with irregular sizes whenever price moved aggressively, which would undermine the whole point of using fixed-range bricks.
The timezone setting lets you adjust timestamps to your local time or whatever reference you prefer, which matters when you're analyzing logs or comparing brick formation times across different sessions. The time delta formatter converts raw milliseconds into human-readable strings showing days, hours, minutes, and seconds with fractional precision. This makes it immediately clear whether a brick took 12.3 seconds or 2 minutes and 15 seconds to form, without having to parse millisecond values mentally.
This is the script version that will eventually be integrated into my real-time candles library. The library version had an issue with tooltips not displaying correctly, which this implementation fixes by using a different approach to label creation and positioning. Running it as a standalone indicator also gives you more control over the visual settings and makes it easier to experiment with different brick sizing methods without affecting other tools that might be using the library version.
What this really demonstrates is that real-time indicators in Pine Script require thinking about state management and tick processing differently than historical indicators. Most indicator code assumes bars are immutable once closed, so you can reference `close ` and know that value will never change. Real-time renko throws that assumption out because the current brick is constantly mutating with every tick until it closes. Using varip for state variables and carefully tracking what belongs to finalized bricks versus the developing brick makes it possible to maintain consistency while still updating smoothly in real-time. The fact that there's no historical reconstruction and everything starts fresh when you load it is actually a feature, not a limitation, because you're seeing genuine real-time brick formation rather than some approximation of what might have happened in the past.
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action
1. Introduction
1.1 Overview
ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active.
The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured:
import TradingView/ta/10 as tvta
// Determine lower timeframe string based on user choice and chart resolution
string lower_tf_breakout = use_custom_tf_input ? custom_tf_input :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
// Request up/down volume (both positive)
= tvta.requestUpAndDownVolume(lower_tf_breakout)
Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity.
Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate.
Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history.
Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”)
2. Price‑Structure Backbone
Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations.
2.1 What it draws
• Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded.
• Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly.
• Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels.
• Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick.
2.2 Key settings
• length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels.
• pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings.
• point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded.
• label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price.
• Styling inputs for trend lines, horizontal lines and labels (color, width and line style).
Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots.
These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle.
The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable.
3. Breakout Module
3.1 Concept
This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled.
3.2 Inputs
• lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly.
• vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout.
• rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution.
• ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases).
• use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe.
• Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width.
3.3 Detection logic
1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume.
2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window.
3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive.
4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history.
5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1).
6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector.
Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move.
Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold.
4. Market Phase Module (Volume Only)
4.1 Concept
Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table.
4.2 Inputs
• phase_period_len: Number of bars over which to compute sums and ratios for phase detection.
• phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume.
• strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation).
• Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles.
• show_phase_module: Toggles the entire phase detection subsystem.
• show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected.
4.3 Detection logic
The module computes three families of statistics over the volume window defined by phase_period_len:
1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends.
2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction.
3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues.
The algorithm then combines these signals:
• For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case.
• For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category.
If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” .
4.4 Outputs
• Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral).
• On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences.
Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began.
Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window.
5. OB/OS Spike Module
5.1 What overbought/oversold means here
In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate.
5.2 Inputs
• minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print.
• syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals.
• Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike.
• Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable.
• Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width.
5.3 Detection logic
1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos.
2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS.
3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold).
4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought.
5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line.
Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels.
Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow.
6. Buyer/Seller Trap Module
6.1 Concept
A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps.
6.2 Inputs
• trap_lookback_len: Window length used to rank extremes and detect sweeps.
• trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep.
• trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.)
• trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed.
• Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps.
• Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart.
6.3 Scoring logic
The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped):
1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick.
2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick.
3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand.
4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa.
5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average.
The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars.
Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label.
Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range.
7. Sharp Move Module
7.1 Concept
Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation.
7.2 Inputs
• sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels.
• sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window.
• sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax.
• sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks.
• sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range).
• sharpScoreRisk: Minimum number of conditions that must be true to print a risk label.
• sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation.
• sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution).
• Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves.
• Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn.
7.3 Conditions (six per side)
For each side, the indicator computes six boolean conditions and sums them to form a score:
1. Dominance (instant and cumulative):
– Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume.
– Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks).
2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish).
3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window.
4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range).
5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile.
6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed.
Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores.
7.4 Scoring and labels
• Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar.
• Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1).
• Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled.
Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move.
Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window.
8. Market‑Maker / Spread‑Capture Module
8.1 Concept
Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets.
8.2 Inputs
• scalpLookback: Window length used to compute volume averages.
• scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple.
• scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement.
• scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%.
• Label settings: ATR length, multiplier, size, colors, connector style and width.
• Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels.
8.3 Signal
When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled.
Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window.
9. Money Flow Module
9.1 Concept
To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow.
9.2 Inputs
• mf_period_len_mf: Number of bars used for summing buy and sell dollars.
• Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width.
• Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed.
9.3 Calculations
• Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $.
• Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum().
• Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate.
• Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences.
Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context.
In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period.
10. Info Table
10.1 Purpose
When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active.
10.2 Symbols
• ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money.
• MA — Moving average. In the table it shows the average value of a series over the lookback period.
• Σ (Sigma) — Cumulative sum over the chosen lookback period.
• Δ (Delta) — Difference between buy and sell values.
• B / S — Buyer and seller share of total volume, expressed as percentages.
• Ref. Price — Reference price for breakout calculations, based on the latest pivot.
• Status — Indicates whether a breakout condition is currently active (True) or has failed.
10.3 Row definitions
1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period.
2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity.
3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period.
4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume.
5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period.
6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume.
7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more.
8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed.
9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral.
10. Money Flow – The final rows display dollar amounts and status:
– ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period.
– ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum.
– Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively.
– Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral.
– Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral.
The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out).
11. Conclusion & Final Remarks
This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart.
A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window.
Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
