Position Size Calculator ProPosition Size Calculator Pro is a professional risk management tool that helps traders calculate optimal position sizes based on their account size, risk tolerance, and trade setup. The indicator provides real-time calculations with interactive price lines and a comprehensive horizontal table display for quick decision-making.
✨ Key Features
Multiple Entry Modes: Current price, manual price, or interactive buy line
Flexible Stop Loss Options: LOD (Low of Day), manual price, percentage-based, or interactive stop line
Advanced Risk Calculations: Includes brokerage impact and adjusted risk metrics
Interactive Price Lines: Visual buy and stop loss lines with real-time updates
Horizontal Table Display: Compact 2-row table showing all critical metrics
Smart Color Coding: Visual feedback based on risk and allocation levels
Professional UI: Clean, modern interface with intuitive controls
Indian Market Ready: Optimized for Indian trading with ₹ currency display
🔧 Input Parameters
💰 Risk Management
Account Size (₹): Total trading capital (default: 10,00,000)
Risk per Trade (%): Maximum risk percentage per trade (default: 0.25%, range: 0.01-5%)
Brokerage (%): Combined buy and sell brokerage (default: 0.12%, range: 0-2%)
📊 Entry & Stop Loss
Entry Mode: Choose between Current Price, Manual Price, or Buy Line
Manual Entry Price: Custom entry price (when Manual Price selected)
Stop Loss Mode: LOD SL, Manual SL, Manual SL %, or SL Line
Manual Stop Loss: Custom stop loss price
SL Percentage (%): Percentage below entry for stop loss (default: 2%, range: 0.1-20%)
📈 Interactive Lines
Buy Line Price: Interactive buy line (click on chart to set)
Stop Loss Line: Interactive stop loss line (click on chart to set)
Show Lines: Toggle line visibility
🎨 Display Options
Show Table: Toggle calculation table visibility
Table Size: Adjustable from tiny to huge
Position: Top, middle, or bottom placement
Alignment: Left, center, or right alignment
Update Frequency: Real-time or bar close
📊 Calculation Methodology
Position Size Formula
Position Size = (Account Size × Risk %) ÷ (Adjusted Risk per Share)
Risk Calculations
Base Risk: |(Entry Price - Stop Loss)| ÷ Entry Price × 100
Adjusted Risk: Includes brokerage impact on both entry and exit
Risk Amount: Position Size × Base Risk per Share
Brokerage Impact
Entry with Brokerage: Entry Price × (1 + Brokerage% ÷ 200)
Exit with Brokerage: Stop Loss × (1 - Brokerage% ÷ 200)
🎮 How to Use
Basic Setup
Set your account size and risk percentage
Configure brokerage percentage according to your broker
Choose entry and stop loss modes
The calculator automatically updates position size
Interactive Lines Setup
⚠️ IMPORTANT: After selecting line modes, refresh the chart to ensure lines are visible
For Buy Line:
Select Entry Mode: "Buy Line"
Set "Buy Line Price" or leave 0 for current price
Refresh chart to see the green buy line
Adjust price by clicking on chart or changing input value
For Stop Loss Line:
Select Stop Loss Mode: "SL Line"
Set "Stop Loss Line" or leave 0 for current low
Refresh chart to see the red stop loss line
Adjust price by clicking on chart or changing input value
Table Information
The horizontal calculation table displays:
SL: Stop Loss price
Entry: Entry price level
Risk%: Adjusted risk percentage (with brokerage)
SL%: Base stop loss risk percentage
Cap%: Account risk percentage setting
Qty: Recommended quantity to buy
Investment: Total investment amount required
Alloc%: Portfolio allocation percentage
Risk ₹: Total risk amount in Rupees
Color Coding Guide
Green Values: Positive/profitable metrics
Red Values: Risk/loss related metrics
Orange Values: Warning levels (high risk/allocation)
Blue Headers: Table headers
Bright Green Line: Buy line with target icon
Bright Red Line: Stop loss line with shield icon
🚨 Alert Conditions
Built-in Alerts
High Allocation Warning: Triggers when position exceeds 20% of account
High Risk Warning: Triggers when stop loss risk exceeds 5%
Invalid Position: Triggers when calculation parameters are invalid
Setting Up Alerts
Click "Add Alert" on the chart
Select "Position Size Calculator Pro"
Choose desired alert condition
Configure notification settings
⚠️ Important Notes & Troubleshooting
Interactive Lines
Lines not visible? Refresh the chart after selecting line modes
Lines moving together? Each line operates independently - check you're adjusting the correct price input
Default behavior: Buy line starts at current price, Stop line starts at current low
Price = 0: Uses automatic defaults (current price/low)
Risk Disclaimers
This tool is for educational purposes only
Always verify calculations independently
Consider market conditions, gaps, and liquidity
Past performance doesn't guarantee future results
Technical Limitations
Interactive lines require chart refresh for initial visibility
Calculations update based on selected frequency
Maximum 10 lines and 10 labels on chart simultaneously
Best Practices
Always set realistic account size
Never risk more than you can afford to lose
Consider slippage and market gaps in volatile conditions
Review calculations before placing actual trades
Use appropriate position sizing for your trading strategy
Refresh chart when switching between line modes
🛠️ Technical Requirements
TradingView account (any tier)
Pine Script v6 compatibility
Modern browser for interactive features
Real-time or delayed data feed
📈 Performance Features
The script includes several optimizations:
Efficient calculation updates based on frequency setting
Smart memory management for line drawings
Conditional table updates to reduce resource usage
Optimized number formatting for better readability
🎯 Use Cases
Day Trading
Quick position sizing for intraday setups
Real-time risk assessment
Interactive line placement for entry/exit planning
Swing Trading
Portfolio allocation management
Multi-timeframe risk analysis
Position size optimization for longer holds
Investment Planning
Capital allocation for stock purchases
Risk-based position sizing
Long-term portfolio management
Disclaimer: This tool is for educational and informational purposes only. Trading involves substantial risk of loss and is not suitable for all investors. Always conduct your own research and consider seeking advice from qualified financial professionals.
Educational
Candle Range 915Candle Range 915 (CR915) is a multi-session visualization tool designed for traders applying Candle Range Theory to intraday decision-making.
This script highlights key range zones formed by the following session-specific candles (based on New York time):
• 9:00 PM – Asia session
• 1:00 AM – London expansion candle
• 5:00 AM – NY continuation/reversal candle
• 8:00 AM – CRT staging candle
• 9:00 AM – CRT decision candle
• 5:00 PM – CBDR (Central Bank Dealers Range)
For each session, the high, low, and optional equilibrium (EQ) levels are plotted with customizable extensions. Labels are placed at the end of each range, and breakout alerts are available for the 8:00 AM and 5:00 PM CRT zones.
The script also includes:
Previous Day High/Low reference lines
EQ toggle per session
Dynamic Daylight Saving Time (DST) adjustment
Optional labeling and color control
This tool is built with a time-based narrative in mind and supports traders analyzing structure, order flow, and key liquidity windows across intraday sessions.
Note: This is a visualization tool only. It does not generate signals or make buy/sell recommendations.
Advanced Petroleum Market Model (APMM)Advanced Petroleum Market Model (APMM): A Multi-Factor Fundamental Analysis Framework for Oil Market Assessment
## 1. Introduction
The petroleum market represents one of the most complex and globally significant commodity markets, characterized by intricate supply-demand dynamics, geopolitical influences, and substantial price volatility (Hamilton, 2009). Traditional fundamental analysis approaches often struggle to synthesize the multitude of relevant indicators into actionable insights due to data heterogeneity, temporal misalignment, and subjective weighting schemes (Baumeister & Kilian, 2016).
The Advanced Petroleum Market Model addresses these limitations through a systematic, quantitative approach that integrates 16 verified fundamental indicators across five critical market dimensions. The model builds upon established financial engineering principles while incorporating petroleum-specific market dynamics and adaptive learning mechanisms.
## 2. Theoretical Framework
### 2.1 Market Efficiency and Information Integration
The model operates under the assumption of semi-strong market efficiency, where fundamental information is gradually incorporated into prices with varying degrees of lag (Fama, 1970). The petroleum market's unique characteristics, including storage costs, transportation constraints, and geopolitical risk premiums, create opportunities for fundamental analysis to provide predictive value (Kilian, 2009).
### 2.2 Multi-Factor Asset Pricing Theory
Drawing from Ross's (1976) Arbitrage Pricing Theory, the model treats petroleum prices as driven by multiple systematic risk factors. The five-factor decomposition (Supply, Inventory, Demand, Trade, Sentiment) represents economically meaningful sources of systematic risk in petroleum markets (Chen et al., 1986).
## 3. Methodology
### 3.1 Data Sources and Quality Framework
The model integrates 16 fundamental indicators sourced from verified TradingView economic data feeds:
Supply Indicators:
- US Oil Production (ECONOMICS:USCOP)
- US Oil Rigs Count (ECONOMICS:USCOR)
- API Crude Runs (ECONOMICS:USACR)
Inventory Indicators:
- US Crude Stock Changes (ECONOMICS:USCOSC)
- Cushing Stocks (ECONOMICS:USCCOS)
- API Crude Stocks (ECONOMICS:USCSC)
- API Gasoline Stocks (ECONOMICS:USGS)
- API Distillate Stocks (ECONOMICS:USDS)
Demand Indicators:
- Refinery Crude Runs (ECONOMICS:USRCR)
- Gasoline Production (ECONOMICS:USGPRO)
- Distillate Production (ECONOMICS:USDFP)
- Industrial Production Index (FRED:INDPRO)
Trade Indicators:
- US Crude Imports (ECONOMICS:USCOI)
- US Oil Exports (ECONOMICS:USOE)
- API Crude Imports (ECONOMICS:USCI)
- Dollar Index (TVC:DXY)
Sentiment Indicators:
- Oil Volatility Index (CBOE:OVX)
### 3.2 Data Quality Monitoring System
Following best practices in quantitative finance (Lopez de Prado, 2018), the model implements comprehensive data quality monitoring:
Data Quality Score = Σ(Individual Indicator Validity) / Total Indicators
Where validity is determined by:
- Non-null data availability
- Positive value validation
- Temporal consistency checks
### 3.3 Statistical Normalization Framework
#### 3.3.1 Z-Score Normalization
The model employs robust Z-score normalization as established by Sharpe (1994) for cross-indicator comparability:
Z_i,t = (X_i,t - μ_i) / σ_i
Where:
- X_i,t = Raw value of indicator i at time t
- μ_i = Sample mean of indicator i
- σ_i = Sample standard deviation of indicator i
Z-scores are capped at ±3 to mitigate outlier influence (Tukey, 1977).
#### 3.3.2 Percentile Rank Transformation
For intuitive interpretation, Z-scores are converted to percentile ranks following the methodology of Conover (1999):
Percentile_Rank = (Number of values < current_value) / Total_observations × 100
### 3.4 Exponential Smoothing Framework
Signal smoothing employs exponential weighted moving averages (Brown, 1963) with adaptive alpha parameter:
S_t = α × X_t + (1-α) × S_{t-1}
Where α = 2/(N+1) and N represents the smoothing period.
### 3.5 Dynamic Threshold Optimization
The model implements adaptive thresholds using Bollinger Band methodology (Bollinger, 1992):
Dynamic_Threshold = μ ± (k × σ)
Where k is the threshold multiplier adjusted for market volatility regime.
### 3.6 Composite Score Calculation
The fundamental score integrates component scores through weighted averaging:
Fundamental_Score = Σ(w_i × Score_i × Quality_i)
Where:
- w_i = Normalized component weight
- Score_i = Component fundamental score
- Quality_i = Data quality adjustment factor
## 4. Implementation Architecture
### 4.1 Adaptive Parameter Framework
The model incorporates regime-specific adjustments based on market volatility:
Volatility_Regime = σ_price / μ_price × 100
High volatility regimes (>25%) trigger enhanced weighting for inventory and sentiment components, reflecting increased market sensitivity to supply disruptions and psychological factors.
### 4.2 Data Synchronization Protocol
Given varying publication frequencies (daily, weekly, monthly), the model employs forward-fill synchronization to maintain temporal alignment across all indicators.
### 4.3 Quality-Adjusted Scoring
Component scores are adjusted for data quality to prevent degraded inputs from contaminating the composite signal:
Adjusted_Score = Raw_Score × Quality_Factor + 50 × (1 - Quality_Factor)
This formulation ensures that poor-quality data reverts toward neutral (50) rather than contributing noise.
## 5. Usage Guidelines and Best Practices
### 5.1 Configuration Recommendations
For Short-term Analysis (1-4 weeks):
- Lookback Period: 26 weeks
- Smoothing Length: 3-5 periods
- Confidence Period: 13 weeks
- Increase inventory and sentiment weights
For Medium-term Analysis (1-3 months):
- Lookback Period: 52 weeks
- Smoothing Length: 5-8 periods
- Confidence Period: 26 weeks
- Balanced component weights
For Long-term Analysis (3+ months):
- Lookback Period: 104 weeks
- Smoothing Length: 8-12 periods
- Confidence Period: 52 weeks
- Increase supply and demand weights
### 5.2 Signal Interpretation Framework
Bullish Signals (Score > 70):
- Fundamental conditions favor price appreciation
- Consider long positions or reduced short exposure
- Monitor for trend confirmation across multiple timeframes
Bearish Signals (Score < 30):
- Fundamental conditions suggest price weakness
- Consider short positions or reduced long exposure
- Evaluate downside protection strategies
Neutral Range (30-70):
- Mixed fundamental environment
- Favor range-bound or volatility strategies
- Wait for clearer directional signals
### 5.3 Risk Management Considerations
1. Data Quality Monitoring: Continuously monitor the data quality dashboard. Scores below 75% warrant increased caution.
2. Regime Awareness: Adjust position sizing based on volatility regime indicators. High volatility periods require reduced exposure.
3. Correlation Analysis: Monitor correlation with crude oil prices to validate model effectiveness.
4. Fundamental-Technical Divergence: Pay attention when fundamental signals diverge from technical indicators, as this may signal regime changes.
### 5.4 Alert System Optimization
Configure alerts conservatively to avoid false signals:
- Set alert threshold at 75+ for high-confidence signals
- Enable data quality warnings to maintain system integrity
- Use trend reversal alerts for early regime change detection
## 6. Model Validation and Performance Metrics
### 6.1 Statistical Validation
The model's statistical robustness is ensured through:
- Out-of-sample testing protocols
- Rolling window validation
- Bootstrap confidence intervals
- Regime-specific performance analysis
### 6.2 Economic Validation
Fundamental accuracy is validated against:
- Energy Information Administration (EIA) official reports
- International Energy Agency (IEA) market assessments
- Commercial inventory data verification
## 7. Limitations and Considerations
### 7.1 Model Limitations
1. Data Dependency: Model performance is contingent on data availability and quality from external sources.
2. US Market Focus: Primary data sources are US-centric, potentially limiting global applicability.
3. Lag Effects: Some fundamental indicators exhibit publication lags that may delay signal generation.
4. Regime Shifts: Structural market changes may require model recalibration.
### 7.2 Market Environment Considerations
The model is optimized for normal market conditions. During extreme events (e.g., geopolitical crises, pandemics), additional qualitative factors should be considered alongside quantitative signals.
## References
Baumeister, C., & Kilian, L. (2016). Forty years of oil price fluctuations: Why the price of oil may still surprise us. *Journal of Economic Perspectives*, 30(1), 139-160.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. McGraw-Hill.
Brown, R. G. (1963). *Smoothing, Forecasting and Prediction of Discrete Time Series*. Prentice-Hall.
Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. *Journal of Business*, 59(3), 383-403.
Conover, W. J. (1999). *Practical Nonparametric Statistics* (3rd ed.). John Wiley & Sons.
Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. *Journal of Finance*, 25(2), 383-417.
Hamilton, J. D. (2009). Understanding crude oil prices. *Energy Journal*, 30(2), 179-206.
Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. *American Economic Review*, 99(3), 1053-1069.
Lopez de Prado, M. (2018). *Advances in Financial Machine Learning*. John Wiley & Sons.
Ross, S. A. (1976). The arbitrage theory of capital asset pricing. *Journal of Economic Theory*, 13(3), 341-360.
Sharpe, W. F. (1994). The Sharpe ratio. *Journal of Portfolio Management*, 21(1), 49-58.
Tukey, J. W. (1977). *Exploratory Data Analysis*. Addison-Wesley.
[Top] Simple Position + SL CalculatorThis indicator is a user-friendly tool designed to help traders easily calculate optimal position sizing, determine suitable stop-loss levels, and quantify maximum potential losses in dollar terms based on their personalized trading parameters.
Key Features:
Position Size Calculation: Automatically computes the number of shares to purchase based on the trader’s total account size and specified percentage of the account allocated per trade.
Stop-Loss Level: Suggests an appropriate stop-loss price point calculated based on the trader’s defined risk percentage per trade.
Max Loss Visualization: Clearly displays the maximum potential loss (in dollars) should the stop-loss be triggered.
Customizable Interface: Provides the flexibility to place the calculation table in different chart positions (Top Left, Top Right, Bottom Left, Bottom Right) according to user preference.
How to Use:
Enter your total Account Size.
Set the desired Position Size as a percentage of your account. (Typically, 1%–5% per trade is recommended for cash accounts.)
Define the Risk per Trade percentage (commonly between 0.05%–0.5%).
Choose your preferred Table Position to comfortably integrate with your trading chart.
Note:
If you identify a technical support level below the suggested stop-loss point, consider reducing your position size to manage the increased risk effectively.
Keep in mind that the calculations provided by this indicator are based solely on standard industry best practices and the specific inputs entered by you. They do not account for market volatility, news events, or any other factors outside the provided parameters. Always complement this indicator with sound technical and fundamental analysis.
ARX Sniper Checklist🔹 ARX Sniper Checklist 🔹
This script is a **manual visual checklist**, not a signal based or automated indicator.
It helps traders stay disciplined and follow step-by-step confirmation rules used in the ARX Sniper strategy.
🧠 What It Does:
- Displays a visual table on the chart
- Lets traders **manually tick boxes** to confirm their trade setup criteria
- Does **not calculate signals, alerts, or automation**
✅ Manual Checklist Items:
1. HTF Bias Confirmed
2. Key Level Marked
3. Rejection or Entry Zone Hit
4. Liquidity Sweep
5. Displacement + Rejection Block
6. Inducement / Trap Detection
7. Entry Taken Without Fear
⚠️ **Closed-source** to preserve layout. This script is purely for discipline and process not for predictive signals.
No alerts, automation, or trading signals are included.
LB | SB | OH | OL (Auto Futures OI)This indicator is for trading purposes, particularly in futures markets given the inclusion of open interest (OI) data.
Indicator Name and Overlay: The indicator is named "LB | SB | OH | OL" and is set to overlay on the price chart (overlay=true).
Override Symbol Input: Users can input a symbol to override the default symbol for analysis.
Open Interest Data Retrieval: It retrieves open interest data for the specified symbol and time frame. If no data is found, it generates a runtime error.
Dashboard Configuration: Users can choose to display a dashboard either at the top right, bottom right, or bottom left of the chart.
Calculations:
It calculates the percentage change in open interest (oi_change).
It calculates the percentage change in price compared to the previous day's close (price_change).
Build Up Conditions:
Long Build Up: When there's a significant increase in open interest (OIChange threshold) and price rises (PriceChange threshold).
Short Build Up: When there's a significant increase in open interest (OIChange threshold) and price falls (PriceChange threshold).
Display Table:
It creates a table on the chart showing the build-up conditions, open interest change percentage, and price change percentage.
Labeling:
It allows for the labeling of buy and sell conditions based on price movements.
Overall, this indicator provides a visual representation of open interest and price movements, helping traders identify potential trading opportunities based on build-up conditions and price behavior.
The "LB | SB | OH | OL" indicator is a tool designed to assist traders in analyzing price movements and open interest (OI) changes in FNO markets. This indicator combines various elements to provide insights into long build-up (LB), short build-up (SB), open-high (OH), and open-low (OL) scenarios.
Key features of the indicator include:
Override Symbol Input: Traders can override the default symbol and input their preferred symbol for analysis.
Open Interest Data: The indicator retrieves open interest data for the selected symbol and time frame, facilitating analysis based on changes in open interest.
Dashboard: The indicator features a customizable dashboard that displays key information such as build-up conditions, OI change, and price change.
Build-Up Conditions: The indicator identifies long build-up and short build-up scenarios based on user-defined thresholds for OI change and price change percentages.
Customization Options: Traders have the flexibility to customize various aspects of the indicator, including colors for long build-up, short build-up, positive OI change, negative OI change, positive price change, and negative price change.
Label Plots: Buy and sell labels are plotted on the chart to highlight potential trading opportunities. Traders can customize the colors and text colors of these labels based on their preferences.
Overall, the "LB | SB | OH | OL" indicator offers traders a comprehensive tool for analyzing price movements and open interest changes, helping them make informed trading decisions in the FNO markets.
ATR | LOTSIZE | Risk (Futures)This Pine Script is a futures-specific trading utility designed to help F\&O (Futures and Options) traders quickly assess the volatility and position sizing for any selected stock on the chart — even if it's not a futures chart.
What the Script Does:
* Automatically detects the futures symbol for the underlying equity using a dynamic mapping system.
* Calculates the ATR (Average True Range) of the futures contract using either SMA or EMA.
* Fetches the Lot Size (Point Value) of the futures instrument.
* Computes risk per lot by multiplying ATR with lot size (Risk = ATR × Lot Size).
* Displays all 3 values — ATR, Lot Size, and Risk in INR — in a compact table on the chart.
Why This Is Useful for F\&O Traders:
* ✅ Quick Risk Assessment: Helps traders understand how much is at risk per lot without switching to the actual futures chart.
* ✅ Position Sizing: Provides data to calculate how many lots to trade based on a defined risk per trade.
* ✅ Volatility Awareness:ATR gives insights into how much the stock typically moves, guiding stop-loss and target placements.
* ✅ Efficient Workflow:No need to load separate futures charts or lookup lot sizes manually — saves time and reduces error.
This tool is ideal for discretionary and systematic traders who want risk and volatility context for every trade, especially in the NSE Futures & Options segment.
Kram Dollar Risk SizingFlat-Based Risk Sizing Table
Quick, reliable contract counts for any fixed per-point risk—no math required.
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Overview
This indicator draws an on-chart lookup table showing exactly how many micro-E-mini contracts to trade for a given index-point stop distance. Simply pick your market (MNQ or MES) and your target dollar-risk tier (200 USD, 300 USD or 400 USD); the script handles the rest. Perfect for pre-trade sizing at a glance.
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Key Benefits
Instant Sizing : See “Point Risk → # Contracts” without ever opening a calculator.
Error-Proof : Table size adapts automatically so you’ll never hit an “out of bounds” error.
Consistent Execution : Apply the same risk grid every time and eliminate second-guessing.
Custom Look : Match your chart’s theme by adjusting colors, fonts, borders and placement.
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Inputs & Settings
Data Inputs
1. Instrument
Choose **MNQ** (Micro-Nasdaq) or **MES** (Micro-S\&P).
2. Price Tier
Select the total dollar-risk you want each grid to represent: **200**, **300** or **400** USD.
3. Table Position
Anchor the table in any corner or midpoint of your chart.
Appearance Settings
Title Background Color and Text Color
Header Background Color and Text Color
Body Background Color and Text Color
Font Size (tiny ▶ large)
Column Widths (set character-based widths for each column)
Border Width and Frame Width (outline thickness)
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How to Use
1. Add the Script
Add the indicator to your chart.
2. Configure Data
Set Instrument to MNQ or MES.
Set Price Tier to the dollar-risk level you want.
Choose a Table Position that doesn’t block your price action.
3. Style to Your Taste
Tweak all appearance settings so the table blends in or stands out as you prefer.
4. Read & Trade
Left Column lists your stop-distance in index-points (e.g. 8.0, 12.0, 25.0).
Right Column shows exactly how many contracts match your chosen dollar-risk.
Find the row matching your planned stop and place your order with confidence.
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Tips & Reminders
Points, Not Ticks : Always enter your stop in full index-points (e.g. “8.0”), even though the market moves in 0.25-point ticks.
Validate Your Data : If you ever edit the dollar-risk tiers or add new ones, be sure each contract count equals
“floor( tier ÷ (pointRisk × \$/point) )”
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Disclaimer:
This tool is provided “as-is” for guidance. Always verify contract counts against live tick values before trading. Trade responsibly!
Credit
Credit to Tempo Trades for the formula that this indicator is based on
Kram Risk PercentStreamline Your Trading with Instant, Percent-Based Position Sizing
Take the guesswork—and the calculator—out of your risk management. This on-chart tool turns your account size and chosen risk percentage into exact contract counts across a range of stop-distances, so you can focus on the market, not the math.
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What It Does for You
Your Risk, Your Rules
Enter your total account value (e.g. $50 000) and the exact percent you’re willing to risk (e.g. 1.0 %). The script immediately calculates your dollar-risk (in this case, $500).
Market-Specific Pricing
MNQ (Micro-Nasdaq) : $2 per index-point (each 0.25 pt “tick” = $0.50).
MES (Micro-S\&P) : $5 per index-point (each 0.25 pt “tick” = $1.25)
Point-Risk to Contracts
You get a clean table that lists **Index-Point Stop (e.g. 2.0 pts)** → **# of Contracts**. No confusion between “ticks” and “points”: you choose your stop in full index-points, and the script does the rest.
At-a-Glance Summary
The table header reminds you:
MNQ | $50 000 @ 1.0 % → $500 risk
so you always know exactly what you’re sizing.
Fully Customizable Look
Pick your background and text colors, font size, column widths, table border thickness—and place it in any corner or edge of your chart.
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Step-by-Step Usage
1. Add the Indicator
Apply “Percent Risk Sizing Table” to your chart in TradingView.
2. Enter Your Parameters
Instrument**: MNQ or MES
Account Size : Your total equity in dollars
Risk % : The percent of your account you’ll risk (e.g. 0.5 %, 2 %)
3. Read the Table
Column 1 : Stop-distance in index-points (1.0, 1.5, 2.0…)
Column 2 : How many contracts you should trade to risk exactly your chosen dollar amount.
4. Customize Appearance
Use the style inputs to match your chart theme:
Colors : Title, header, body
Font size : tiny → large
Column widths : narrow → wide
Border & frame : subtle → bold
Position : any corner or middle edge
5. Execute with Confidence
No manual math. No guessing. Just scan to the row matching your planned stop-distance and place your order.
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Tips for Best Results
Think in Points, Not Ticks
Always enter your stop as a whole number of index-points (e.g. 2.0 points), even though the market moves in 0.25-point ticks.
Adjust on the Fly
Change your risk % or switch instruments and watch the table update instantly.
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Add this indicator now and make every trade sized precisely to your rules—because consistent risk control is the foundation of consistent profits.
🛡️ Disclaimer
This script is educational and provided “as-is.” Always verify contract counts with your broker’s live tick values before executing real orders. Trade responsibly and keep your risk in check!
Random State Machine Strategy📌 Random State Machine Strategy (Educational)
This strategy showcases a randomized entry model driven by a finite state machine, integrated with user-defined exit controls and a full-featured moving average filter.
🧠 Trade Entry Logic
Entries occur only when:
A random trigger occurs (~5% probability per bar)
The state machine accepts a new transition (sm.step())
Price is:
Above the selected MA for long entries
Below the selected MA for short entries
This ensures that entries are both stochastically driven and trend-aligned, avoiding frequent or arbitrary trades.
⚙️ How It Works
Randomized Triggers
A pseudo-random generator (seeded with time and volume) attempts to trigger state transitions.
Finite State Machine
Transitions are managed using the StateMachine from robbatt/lib_statemachine — credit to @robbatt for the modular FSM design.
Controlled Reset
The state machine resets every N bars (default: 100) if at least two transitions have occurred. This prevents stale or locked states.
Backtest Range
Define a specific test window using Start and End Date inputs.
Risk & Exits
Specify risk in points and a target risk/reward ratio. TP is auto-computed. Timed and MA-based exits can be toggled.
🧪 How to Use
Enable Long or Short trades
Choose your Moving Average type and length
Set Risk per trade and R/R ratio
Toggle TP/SL, timed exit, or MA cross exit
Adjust the State Reset Interval to suit your signal frequency
📘 Notes
Educational use only — not financial advice
Random logic is used to model structure, not predict movement
Thanks to @robbatt for the lib_statemachine integration
Volume pressure by GSK-VIZAG-AP-INDIA🔍 Volume Pressure by GSK-VIZAG-AP-INDIA
🧠 Overview
“Volume Pressure” is a multi-timeframe, real-time table-based volume analysis tool designed to give traders a clear and immediate view of buying and selling pressure across custom-selected timeframes. By breaking down buy volume, sell volume, total volume, and their percentages, this indicator helps traders identify demand/supply imbalances and volume momentum in the market.
🎯 Purpose / Trading Use Case
This indicator is ideal for intraday and short-term traders who want to:
Spot aggressive buying or selling activity
Track volume dynamics across multiple timeframes *1 min time frame will give best results*
Use volume pressure as a confirming tool alongside price action or trend-based systems
It helps determine when large buying/selling activity is occurring and whether such behavior is consistent across timeframes—a strong signal of institutional interest or volume-driven trend shifts.
🧩 Key Features & Logic
Real-Time Table Display: A clean, dynamic table showing:
Buy Volume
Sell Volume
Total Volume
Buy % of total volume
Sell % of total volume
Multi-Time frame Analysis: Supports 8 user-selectable custom time frames from 1 to 240 minutes, giving flexibility to analyze volume pressure at various granularities.
Color-Coded Volume Bias:
Green for dominant Buy pressure
Red for dominant Sell pressure
Yellow for Neutral
Intensity-based blinking for extreme values (over 70%)
Dynamic Data Calculation:
Uses volume * (close > open) logic to estimate buy vs sell volumes bar-by-bar, then aggregates by timeframe.
⚙️ User Inputs & Settings
Timeframe Selectors (TF1 to TF8): Choose any 8 timeframes you want to monitor volume pressure across.
Text & Color Settings:
Customize text colors for Buy, Sell, Total volumes
Choose Buy/Sell bias colors
Enable/disable blinking for visual emphasis on extremes
Table Appearance:
Set header color, metric background, and text size
Table positioning: top-right, bottom-right, etc.
Blinking Highlight Toggle: Enable this to visually highlight when Buy/Sell % exceeds 70%—a sign of strong pressure.
📊 Visual Elements Explained
The table has 6 rows and 10 columns:
Row 0: Headers for Today and TF1 to TF8
Rows 1–3: Absolute values (Buy Vol, Sell Vol, Total Vol)
Rows 4–5: Relative percentages (Buy %, Sell %), with dynamic background color
First column shows the metric names (e.g., “Buy Vol”)
Cells blink using alternate background colors if volume pressure crosses thresholds
💡 How to Use It Effectively
Use Buy/Sell % rows to confirm potential breakout trades or identify volume exhaustion zones
Look for multi-timeframe confluence: If 5 or more TFs show >70% Buy pressure, buyers are in control
Combine with price action (e.g., breakouts, reversals) to increase conviction
Suitable for equities, indices, futures, crypto, especially on lower timeframes (1m to 15m)
🏆 What Makes It Unique
Table-based MTF Volume Pressure Display: Most indicators only show volume as bars or histograms; this script summarizes and color-codes volume bias across timeframes in a tabular format.
Customization-friendly: Full control over colors, themes, and timeframes
Blinking Alerts: Rare visual feature to capture user attention during extreme pressure
Designed with performance and readability in mind—even for fast-paced scalping environments.
🚨 Alerts / Extras
While this script doesn’t include TradingView alert functions directly, the visual blinking serves as a strong real-time alert mechanism.
Future versions may include built-in alert conditions for buy/sell bias thresholds.
🔬 Technical Concepts Used
Volume Dissection using close > open logic (to estimate buyer vs seller pressure)
Simple aggregation of volume over custom timeframes
Table plotting using Pine Script table.new, table.cell
Dynamic color logic for bias identification
Custom blinking logic using na(bar_index % 2 == 0 ? colorA : colorB)
⚠️ Disclaimer
This indicator is a tool for analysis, not financial advice. Always backtest and validate strategies before using any indicator for live trading. Past performance is not indicative of future results. Use at your own risk and apply proper risk management.
✍️ Author & Signature
Indicator Name: Volume Pressure
Author: GSK-VIZAG-AP-INDIA
TradingView Username: prowelltraders
Bullish Bearish Signal with EMA Color + LabelsThis script generates clear BUY and SELL signals based on a combination of trend direction, momentum, and confirmation from multiple indicators. It is intended to help traders identify strong bullish or bearish conditions using commonly trusted tools: EMA 200, MACD, and RSI.
🔍 How it works:
The strategy combines three key elements:
EMA 200 Trend Filter
Identifies the long-term trend:
Price above EMA200 → Bullish trend bias
Price below EMA200 → Bearish trend bias
The EMA line is color-coded:
🔵 Blue for bullish
🔴 Red for bearish
⚪ Gray for neutral/unclear
MACD Crossover
Detects shifts in market momentum:
Bullish: MACD line crosses above signal line
Bearish: MACD line crosses below signal line
RSI Confirmation
Adds an extra layer of confirmation:
Bullish: RSI is above its signal line
Bearish: RSI is below its signal line
✅ Signal Logic:
BUY Signal appears when:
Price > EMA200
MACD crosses up
RSI > its signal line
SELL Signal appears when:
Price < EMA200
MACD crosses down
RSI < its signal line
Labels will appear on the chart to highlight these events.
🔔 Alerts:
The script includes alerts for both Buy and Sell conditions, so you can be notified in real-time when they occur.
📈 How to Use:
Best used in trending markets.
Recommended for higher timeframes (1H and above).
May be combined with other tools such as support/resistance or candlestick analysis.
⚠️ Disclaimer: This script is intended for educational purposes only and does not constitute financial advice or a trading recommendation.
Multi-Indicator Trend-Following Strategy v6Multi-Indicator Trend-Following Strategy v6
This strategy uses a combination of technical indicators to identify potential trend-following trade entries and exits. It is intended for educational and research purposes.
How it works:
Moving Averages (EMA): Entry signals are generated on crossovers between a fast and slow exponential moving average.
RSI Filter: Confirms momentum with a threshold above/below 50 for long/short entries.
Volume Confirmation: Requires volume to exceed a moving average multiplied by a user-defined factor.
ATR-Based Risk Management: Stop loss and take profit levels are calculated using the Average True Range (ATR), allowing for dynamic risk control based on market volatility.
Customizable Inputs:
Fast/Slow MA lengths
RSI length and levels
MACD settings (used in calculation, not directly in signal)
Volume MA and multiplier
ATR period and multipliers for stop loss and take profit
Notes:
This strategy does not guarantee future results.
It is provided for analysis and backtesting only.
Alerts are available for buy/sell conditions.
Feel free to adjust parameters to explore different market conditions and asset classes.
[RenkoCore] PublicWhen it comes the Renko chart, we all know it has its advantages & disadvantages compared to the candle-stick chart. My aim of this was to alleviate some of the disadvantages by providing some sort of structure on Renko chart. These set of tools may hopefully help your trading journey on Renko chart.
Helpful tips:
a) Enable wicks on your Renko settings, this indicator needs wicks to work.
b) Choose correct size (I recommend traditional size option) for your Renko chart as well as for your instrument.
c) Keep it on 1-second time frame, anything other than that doesn't work on TradingView's Renko. This is important as price will not repaint.
d) If you want to see bigger picture (like 4hr/daily on candle-stick chart), just increase your Renko size, but still keep it on 1-second timeframe.
This toolset includes couple different methods to provide some structures as explained below:
1. 📌 Balance | Price Action Equilibrium Zones
Overview
The Balance is a visual framework designed to evaluate directional bias and internal structure in price action. It measures net bullish/bearish momentum within a configurable rolling window, while highlighting key structural turning points based on multiple custom sensitivity levels. This tool helps traders stay in sync with market rhythm by emphasizing balance, imbalance, and inflection zones.
🔧 How It Works:
Inflection Tiers
Three customizable rounds of pivot-based divergence detection—labeled as 1°, 2°, and 3°—automatically identify regular bullish and regular bearish pivot structures. Though may not be always accurate, these structural signals are intended to keep user's focus to continually reflect emerging internal market shifts.
Balance Limit
Monitors directional bar disparity within a customizable retrospective span. When the net balance exceeds ±50% of the range, the line turns green to suggest strong directional bias. A red fill zone between these thresholds indicates equilibrium or no-trade conditions.
Volatility Based Reversal (Candle Reversal Detector)
This tool scans for extreme price movements relative to local volatility baselines, helping traders detect possible tops and bottoms before major price reversals or pauses. Compares current price action to the lowest recent volatility anchor or if price sharply dips below the highest recent volatility anchor.
🧠 Use Case Recommendations:
Discretionary trading to visually confirm balance and momentum shifts.
Confluence strategies, combining the balance counter with trend indicators or support/resistance levels.
Structure mapping, to highlight exhaustion zones or emerging reversals based on internal divergences.
Avoid using this tool in isolation. It is most effective when combined with broader market context or other confirmation layers.
2. 📌 Primary Level Detection
Overview
This is a precision tool for detecting dynamic price zones where significant market reversals may begin. Using a blend of momentum, price tension, and volatility structure, it identifies potential top and bottom areas — and tracks them with adaptive channel levels that evolve in real time.
🔧 How It Works:
Combines price action, RSI-based bias, and volatility deviation to identify moments when price is overextended.
Reacts only to major changes — reducing false positives in choppy markets.
Levels persist on the chart until a new valid reversal is confirmed, giving you visual structure and actionable areas to work with.
🧠 Use Case Recommendations:
Trading reversals, reversion-to-mean, or liquidity sweeps
Confirming entries from other indicators (like divergence, order blocks, or support/resistance)
Analyzing volatile markets where rapid direction changes are common (e.g., crypto, futures, scalping)
3. 📌 Secondary Level Detection
Overview
This tool highlights where price may be overextended and due for a short-term reversal, based on recent price structure.
🔧 How It Works:
It uses dynamic bar-count and swing conditions to identify potential price turning points after extended directional moves or strong sequence of bars in same direction.
Levels persist on the chart until a new valid reversal is confirmed, giving you visual structure and actionable areas to work with.
🧠 Use Case Recommendations:
Trading reversals, reversion-to-mean, or liquidity sweeps
Confirming entries from other indicators (like divergence, order blocks, or support/resistance)
⚠️ Important Notes:
This indicator does not repaint. All pivots and plots are based on closed candles and verified conditions.
This tool does not provide trade signals. It is a structural analysis tool intended to assist in discretionary decision-making. This indicator is for informational and educational purposes only. Use in combination with your own trading strategy, risk management, and market context. The signals generated do not guarantee outcomes and should not be used in isolation.
It is not intended to be financial advice or a recommendation to buy or sell any security or asset. Trading involves risk. Always do your own research and consult with a licensed financial advisor before making any trading decisions. Past performance is not indicative of future results.
The author is not responsible for any losses incurred from the use of this script.
[TehThomas] - Previous Day/Week/Month High, Low, Open, CloseThis script is a powerful visual tool designed to automatically plot the key high, low, open, and close levels from the previous day, previous week, and previous month directly onto your active chart. These historical price levels are some of the most significant reference points for traders, often acting as natural magnets for price, areas of liquidity, or decision points where reversals, continuations, or fakeouts commonly occur.
Whether you’re a scalper working off intraday charts or a swing trader using higher timeframes, having these levels marked automatically keeps your chart structured and your strategy grounded in recent price behavior.
What This Script Displays on Your Chart
Once added to your chart, this script draws horizontal lines at the exact price levels where the previous day, week, and month ended or found their highs and lows. For each timeframe, you have full control over what’s shown, with toggle switches to enable or disable specific lines like:
Previous Day High and Low
Previous Day Open and Close
Previous Week High and Low
Previous Week Open and Close
Previous Month High and Low
Each level is color-coded, clearly labeled, and extended a set number of candles into the future so you can quickly identify which level is which. The labels are minimalist and clean, placed directly next to each line so they don’t distract from price action. This keeps your workspace visually organized without sacrificing context.
Why These Levels Are Important
These historical levels serve as psychological and technical anchors for the market. Traders and algorithms alike often react to the highs and lows of previous sessions, and open/close levels serve as polarity zones where support becomes resistance or vice versa.
Here are just a few practical uses:
Support and Resistance: Previous session highs and lows frequently act as strong areas where price reacts or consolidates.
Liquidity Zones: These levels often sit just above or below pools of stop-loss orders, making them common targets for liquidity grabs.
Market Context: Having previous opens and closes lets you see if price is trading above or below prior value areas, helping define bullish or bearish bias.
Entry and Exit Planning: Knowing where major levels sit helps refine your entries, manage risk, or take partial profits at high-probability reversal areas.
By automatically drawing these reference points, the script helps traders stay objective, focus on structure, and avoid emotional trading decisions.
How It Works Behind the Scenes
At the core, the script tracks the most recent completed daily, weekly, and monthly candles. It records the high, low, open, and close of those time periods and scans recent price history to find the exact bar where those levels were printed. Once found, it draws clean, extendable horizontal lines from those points forward on your chart.
The script includes built-in cleanup logic to ensure that only the latest relevant levels are visible. Whenever new session data becomes available, it removes old lines and replaces them with updated levels so your chart stays clean and accurate without any manual effort. You can also adjust how far these lines extend into the future, change their width, and personalize the colors to match your charting style.
This makes it a fully automatic, no-maintenance tool that always keeps your chart aligned with current session structure.
Whether you're watching for stop hunts at the previous week's high, looking for reaction zones around the prior day's close, or simply want to align your bias with institutional reference points, this script delivers the clean structure and clarity you need to trade more confidently and effectively.
Special thanks to: meddymarkusvanhala
For helping me optimise the script for faster load times
CPR by DSKThis CPR (Central Pivot Range) indicator is designed to provide multi-timeframe insights and simplify trend analysis for traders of all levels. Key features include:
1. Dynamic CPR Levels
Automatically adapts and displays CPR levels based on the current chart timeframe (Daily, Weekly, or Monthly).
Useful for identifying intraday or swing trading opportunities.
2. Market Sentiment Summary Table
A compact summary table indicates the market bias (Bullish/Bearish) using the relative position of the price to the Daily, Weekly, and Monthly CPR Pivots.
Helps you instantly assess the prevailing trend across key timeframes.
3. Target Achievement Status
The summary also highlights if any CPR-based targets or key levels have been hit, offering valuable confirmation for trade setups and exits.
This indicator is ideal for traders seeking a quick, visual overview of market structure and trend strength using the well-known CPR method.
Abusuhil Bullish Candles (Label + Table)Abusuhil Bullish Candles is a pattern recognition indicator designed to identify key bullish reversal candlestick formations including Hammer, Bullish Engulfing, Morning Star, Piercing Line, Three White Soldiers, and Three Inside Up.
The script includes optional filters such as Stochastic and Volume Confirmation, providing more precise signal detection.
Each pattern and filter is fully customizable via settings. Alerts are also included to support active trading workflows.
This script was written originally and does not copy open-source indicators. It's ideal for traders seeking visual clarity on bullish opportunities with professional-grade logic.
مؤشر الشموع الصعودية هو مؤشر احترافي يكتشف أبرز نماذج الانعكاس الصعودي في الشموع اليابانية مثل: Hammer، Bullish Engulfing، Morning Star، Piercing Line، Three White Soldiers، و Three Inside Up.
يوفر المؤشر فلاتر إضافية مثل فلتر Stochastic وفلتر الفوليوم لتعزيز دقة الإشارات. جميع الإعدادات قابلة للتعديل بما يتناسب مع احتياج كل متداول.
يحتوي المؤشر أيضًا على تنبيهات تلقائية لدعم استراتيجيات التداول اللحظي. تمت برمجة المؤشر من الصفر ويعتمد على منطق خاص غير منسوخ من سكربتات مفتوحة المصدر.
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🇸🇦 التحديثات – النسخة الجديدة (Abusuhil Bullish Candles)
✅ تم تغيير الملصقات بشكل أوضح: باستخدام دوائر ملونة أسفل الشموع بدلًا من المربعات لتفادي التراكب.
🟦 إضافة جدول تفاعلي على الشارت يعرض أسماء النماذج وألوانها المخصصة.
🎨 إمكانية تغيير ألوان كل نموذج من الإعدادات حسب رغبة المستخدم.
🧩 تفعيل/تعطيل كل نموذج على حدة من خلال إعدادات منفصلة.
🔔 إضافة تنبيه احترافي واحد يتم تفعيله عند تحقق أي نموذج نشط من النماذج المحددة.
📋 توافق كامل مع سياسة TradingView:
لا يحتوي على أكواد منسوخة أو مبنية على مؤشرات داخلية.
لا تكرار للوظائف أو العناوين.
وصف واضح مع تحكم كامل للمستخدم.
🇬🇧 Updates – Latest Version (Abusuhil Bullish Candles)
✅ Clearer Signal Labels: Now uses colored circles under candles instead of labels to avoid overlapping.
🟦 Interactive Table showing pattern names and user-defined colors.
🎨 Customizable colors for each candlestick pattern from the settings menu.
🧩 Toggle each pattern independently using dedicated checkboxes.
🔔 Single professional alert condition that triggers only when any enabled pattern is detected.
📋 Fully compliant with TradingView's publishing policy:
No reused or built-in indicator code.
No duplicated logic or misleading titles.
Clean and modular design with full user customization.
NoNoiseMA & SlopeHappy trade,
This is a noise-reduced moving average — let's call it the No-Noise MA. A MA where false breakout price action should have little to no impact, while the main trend remains fully represented. In comparison to previous MAs this one's trend appear more linear, and sideways price actions becomes easier to detect thanks to it's unique two filter stages.
In short, the No-Noise-MA (Noise-Reduced Moving Average) is calculated as the cumulative sum of the slopes derived from the center line of the last x pivot points. Let’s break it down step by step:
Pivot Detection:
A pivot algorithm (an adapted variant of the Bilson-Gann-Count method) identifies consecutive pivot points (high, low, high, low, etc.) in the close price series. Let's call this set of Pivots S.
Center Line Calculation:
Out of the set S the last x pivots are used to compute a center line (linear regression line). Always when a new pivot is confirmed, the oldest pivot in the queue is removed, and the new pivot is added.
Slope Extraction:
The center line is defined by its equation shown in the image below
Image 1
Cumulative Slope Sum:
As shown in the image 1 the slope is a series with values around zero. The No-Noise-MA is then just the cumulative sum of the slope series and a correction term. A correction term is needed otherwise the No-Noise-MA would run away over time from the original close price. The correction term is just the deviation between close price and cumulative slope sum multiply with a factor around 0.01 added to the No-Noise-MA.
Noise Reduction:
The goal of noise reduction is done by two filter stages. First Filter is the reduction of the input values. As shown above not all bars close prices are use, instead it uses just the pivot points delivered by the Bilson-Gann-Count method. Favorable the Bilson-Gann-Count method delivers the Pivot points in most cases much faster as other Pivot methods. Already after two bars a new Pivot is confirmed. This takes out all ups and downs between two consecutive Pivots. This first filter stage is legit because all price action in between is hedged by the Pivots.
The second filter stage is the done by the length of the center line. As more pivots are used to calculate the center line as smoother the slope becomes. Out liners just gets less impact if the base is bigger. So the number of involved Pivots has the same meaning as the lengths in any other MA.
Comparison with usual MAs:
For a comparison with other MAs this script also calculate the average lengths of the center line, shown in the upper right chart. So choose for example SMA and set the length parameter to the average length of the center line. As shown in the following image 2.
Image 2
This way both MAs have the same data base and can be objectively compared.
Trend detection:
The slope of the center line can be used for trend confirmation. A slope bigger then zero is an up trend while a slope smaller then zero is a down trend. And side way price action is indicated when the slope is around zero within a certain threshold.
Image 3
One hint should be mentioned here. The side way section gets indicated much later. About the number of bars as the center line is long. Before that there are just up or down trend predicted. In the image 2 you see the slope is firstly tin and as more bars past by the slope becomes more thick. This should indicate the point where no side way predictions will happens anymore.
Variation of calculation
In the settings menu you can find the setting "Include last close to center line". With this activated the center line is calculated with the last pivots and the last close price. The last close price is assumed as a pivot too. This gives the slope a more early reaction to volatile price action. But also brings back some noise.
Abusuhil Bullish CandlesAbusuhil Bullish Candles is a pattern recognition indicator designed to identify key bullish reversal candlestick formations including Hammer, Bullish Engulfing, Morning Star, Piercing Line, Three White Soldiers, and Three Inside Up.
The script includes optional filters such as Stochastic and Volume Confirmation, providing more precise signal detection.
Each pattern and filter is fully customizable via settings. Alerts are also included to support active trading workflows.
This script was written originally and does not copy open-source indicators. It's ideal for traders seeking visual clarity on bullish opportunities with professional-grade logic.
مؤشر الشموع الصعودية هو مؤشر احترافي يكتشف أبرز نماذج الانعكاس الصعودي في الشموع اليابانية مثل: Hammer، Bullish Engulfing، Morning Star، Piercing Line، Three White Soldiers، و Three Inside Up.
يوفر المؤشر فلاتر إضافية مثل فلتر Stochastic وفلتر الفوليوم لتعزيز دقة الإشارات. جميع الإعدادات قابلة للتعديل بما يتناسب مع احتياج كل متداول.
يحتوي المؤشر أيضًا على تنبيهات تلقائية لدعم استراتيجيات التداول اللحظي. تمت برمجة المؤشر من الصفر ويعتمد على منطق خاص غير منسوخ من سكربتات مفتوحة المصدر.
Swing High/Low LQ TrackerAn interactive tool to track liquidity events. Select start and end points on your chart—this indicator will automatically detect and plot the highest high and lowest low from that window, then extend those levels forward. If price sweeps either level, it marks the event with a clean "LQ" tag.
Perfect for traders who want to identify session-based liquidity, like killzone highs/lows, without manually drawing and deleting lines every day.
How It Works
-Select start and end time directly from settings
-Indicator calculates the swing high and low during that range
-Lines extend beyond the session until broken
-“LQ” markers appear when price sweeps the swing levels
It’s a must-have for ICT traders, smart money traders, or anyone who wants to track key liquidity levels without clutter.
Simple and effective tool for marking important ranges and tracking when liquidity is taken. No complex settings - just select your range and monitor the levels.
SD Median NUPL-Z🧠 Overview
SD Median NUPL-Z is a trend-following indicator that leverages a normalized version of Bitcoin’s Net Unrealized Profit/Loss (NUPL) metric, filtered through a median-based volatility band. Unlike traditional NUPL which is often used to spot extremes, this indicator is designed to identify sustained directional trends — entering only when both on-chain momentum and price structure align.
🧩 Key Features
Z-Scored NUPL Trend Engine: Normalizes NUPL using rolling mean and standard deviation to create a smoothed trend signal.
Price Structure Filter: Implements a median-based price band to avoid false entries during short-term volatility.
Custom Thresholds: User-defined thresholds determine when the trend signal is strong enough to justify a long or short directional bias.
Directional Candle Coloring: Reinforces current trend regime visually with aqua (bullish) and red (bearish) plots and candles.
Optimized for BTC: Uses Bitcoin’s Market Cap and Realized Cap to construct the NUPL input.
🔍 How It Works
On-Chain Core: NUPL is calculated as the percentage of unrealized profit in the market: (Market Cap - Realized Cap) / Market Cap * 100.
Z-Score Transformation: The raw NUPL value is normalized using a rolling average and standard deviation over a set window (default 134 days), producing the NUPL-Z series.
Median-Based Price Filter: A rolling 50th percentile (median) of price is used alongside its own standard deviation to create upper and lower bounds.
These bounds define a "volatility corridor" around price; the trend signal is only acted upon if price confirms by staying outside these bands.
Signal Logic:
A Long signal is triggered when NUPL-Z rises above the long threshold and price is not below the lower band.
A Short signal is triggered when NUPL-Z falls below the short threshold.
State Variable (CD): Tracks the current market regime, used to control plotting and color changes.
🔁 Use Cases & Applications
Momentum-Based Trend Following: Helps traders align with directional moves backed by both on-chain sentiment and supportive price structure.
Filtered Entry Timing: Reduces premature or noise-based entries by requiring price confirmation before committing to NUPL-based signals.
Best Suited for BTC: This tool is designed specifically around Bitcoin’s on-chain metrics and is not intended for altcoins or low-volume assets.
✅ Conclusion
SD Median NUPL-Z repurposes a traditionally cyclical valuation tool into a modern trend-following signal by combining statistical normalization with dynamic price structure filtering. It offers a more robust way to participate in high-conviction directional trends, reducing the likelihood of entering during short-lived counter moves.
⚠️ Disclaimer
The content provided by this indicator is for educational and informational purposes only. Nothing herein constitutes financial or investment advice. Trading and investing involve risk, including the potential loss of capital. Always backtest and apply risk management suited to your strategy.
NUPL-Z For Loop🧠 Overview
NUPL-Z For Loop is a trend-following indicator built on Bitcoin’s on-chain Net Unrealized Profit/Loss (NUPL) metric. It uses a Z-scored transformation of NUPL and a custom loop-based scoring system to measure the consistency of directional movement. Rather than identifying tops and bottoms, this tool is designed to track sustained trends and filter out short-term noise, making it ideal for momentum-aligned strategies.
🧩 Key Features
Loop-Based Trend Logic: Assesses trend strength by summing the number of upward vs. downward moves in Z-scored NUPL across a custom lookback.
Z-Score Normalization: Applies long-term statistical normalization to NUPL to emphasize deviation from average behavior over time.
Threshold-Based Regime Shifts: Custom input thresholds define when trend strength is significant enough to trigger long or short signals.
Directional Market State Tracking: Internally tracks bullish, bearish, or neutral conditions to guide trend entries.
BTC-Focused On-Chain Analysis: Tailored specifically for Bitcoin using Market Cap and Realized Cap inputs.
🔍 How It Works
NUPL Calculation: Derived as the percentage of net unrealized profit relative to market cap: (MC - RMC) / MC * 100.
Z-Scoring: NUPL is normalized using a rolling mean and standard deviation over a long window (default 1300 days) to create a smoothed trend signal.
Directional Loop: A custom loop iterates from the start_loop to the end_loop, comparing the current Z-score to past values.
Each instance where NUPL_Z > NUPL_Z adds +1 to the score; otherwise, it subtracts -1.
This cumulative score reflects how consistently NUPL-Z has been trending.
Signal Logic:
Long signal when loop score exceeds long_threshold.
Short signal when score falls below short_threshold.
CD State Engine: Maintains the current trend regime (1 for long, -1 for short), which drives plot coloring and overlays.
🔁 Use Cases & Applications
Momentum Trend Filter: Detects and confirms sustained directional strength in BTC’s profit/loss positioning.
Noise Suppression: Avoids reactive signals from one-off spikes or dips in NUPL by requiring a consistent trend before confirming bias.
Best Suited for BTC: Designed specifically for Bitcoin’s price and on-chain structure, using its unique NUPL dynamics.
✅ Conclusion
NUPL-Z For Loop transforms a traditionally mean-reverting indicator into a trend-following signal engine. By scoring the consistency of movement in normalized NUPL, this tool identifies trend strength rather than reversal potential — providing more reliable context for momentum-aligned trades on Bitcoin.
⚠️ Disclaimer
The content provided by this indicator is for educational and informational purposes only. Nothing herein constitutes financial or investment advice. Trading and investing involve risk, including the potential loss of capital. Always backtest and apply risk management suited to your strategy.
MVRV-Z For Loop🧠 Overview
MVRV-Z For Loop is a trend-following indicator that applies a custom directional for-loop logic to the MVRV Z-score. By evaluating the number of consecutive Z-score improvements or deteriorations over time, it identifies sustained directional pressure in Bitcoin’s on-chain trend — helping traders align with prevailing market strength rather than reacting to single-point extremes.
🧩 Key Features
Loop-Based Trend Filter: Applies a running comparison loop to assess whether MVRV-Z has been consistently strengthening or weakening.
Directional Scoring System: Each upward movement contributes positively, and each downward movement negatively, producing a cumulative trend score.
Z-Scored MVRV: Leverages on-chain valuation via the Market Cap to Realized Cap ratio, normalized using a long-term rolling average and standard deviation.
Custom Thresholds: User-defined thresholds for long and short signals based on trend score magnitude.
Dynamic Candle Coloring: Visually reinforces trend state with aqua for bullish and red for bearish environments.
🔍 How It Works
Z-score Transformation: The MVRV ratio is normalized over a long lookback (default 1050 days), creating a standardized valuation signal.
For-Loop Engine: A directional loop compares the current MVRV-Z value to previous values within a defined range (start to end).
If today’s value is higher than ma , it adds +1 to the score; otherwise, it subtracts -1.
This loop effectively measures momentum consistency rather than magnitude alone.
Signal Logic:
A Long signal is triggered when the cumulative trend score exceeds the long_threshold.
A Short signal is triggered when the score drops below the short_threshold.
State Variable (CD): Tracks the market regime (1 = long, -1 = short), updating only when a valid condition is met.
🔁 Use Cases & Applications
Trend Confirmation Tool: Helps traders assess whether a directional move has been sustained over time before committing.
Momentum Alignment: Filters out short-term noise by scoring consistency in MVRV-Z movement rather than relying on single-bar reversals.
Best Suited for BTC: This indicator is specifically built using Bitcoin’s Market Cap and Realized Cap metrics, making it ideal for BTC trend tracking.
✅ Conclusion
MVRV-Z For Loop transforms the traditional MVRV Z-score into a trend-following signal using a cumulative scoring approach. It excels in highlighting sustained directional strength and avoids premature entries during valuation whipsaws. This makes it a strong tool for traders looking to stay on the right side of the trend without overreacting to short-term fluctuations.
⚠️ Disclaimer
The content provided by this indicator is for educational and informational purposes only. Nothing herein constitutes financial or investment advice. Trading and investing involve risk, including the potential loss of capital. Always backtest and apply risk management suited to your strategy.
