Smart Voids(fvg)🧠 Smart Voids (fvg) by DuncanX 🔥 🔥
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It spots the real voids the market leaves behind.
Inspired by SMC and ICT’s Fair Value Gap logic —
but cleaner, faster, and smarter.
It only marks true displacement gaps where liquidity was taken.
One color. No noise. Just pure intent.
No clutter — just high-probability zones.
If a box appears,
someone’s likely to react there.
See it early.
Own the move.🔥 🔥 🔥
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Educational
congestion final1 by saurabh maggo
Title: Indian Market Congestion Indicator
Description:
The Indian Market Congestion Indicator is a powerful tool designed for traders in the Indian stock market, specifically tailored for indices like BANKNIFTY on a 5-minute chart. This indicator identifies periods of price congestion—where the market is consolidating within a tight range—and detects potential breakouts or breakdowns, helping you spot high-probability trading opportunities during the NSE session (9:15 AM–3:30 PM IST).
Key Features:
Congestion Detection: Identifies consolidation zones based on price range, ATR (Average True Range), volume, and RSI filters. A blue background or table cell indicates a congestion period.
Breakout/Breakdown Signals: Detects breakouts (green) and breakdowns (red) from congestion zones, confirmed by volume spikes, price movement, and volatility filters.
Post-Congestion and Pullback Detection: Highlights post-congestion periods (yellow) and pullback entries (purple) after breakouts/breakdowns for safer trade entries.
Customizable Colors: Adjust the colors and transparency for each state (Congestion, Breakout Up, Breakdown, Post-Congestion, Pullback) directly in the settings panel, allowing you to fine-tune visibility for both background and table displays.
State Table: Displays the current market state in a table at the top-right corner, with trend direction (light green/red) if the trend filter is enabled.
Advanced Filters: Includes optional filters like RSI, volume, volatility (ATR), trend, and momentum (MACD) to reduce false signals and improve accuracy.
Session and Timeframe Support: Designed for the NSE session, with options to show indicators only for the current day and adjust parameters for different timeframes.
Alerts: Set up alerts for congestion, breakouts, and breakdowns, with enhanced alert messages providing context like breakout level, volatility, and trend.
DTC Advanced | 1.4 📈 DTC Advanced | 1.4 – All-in-One Trading Indicator
DTC Advanced | 1.4 is a powerful, professional-grade trading tool designed to help traders identify trends, plan trades, and manage risk—all in one seamless, visual interface. It combines trend detection, real-time trade planning, and performance monitoring into a single overlay, making it ideal for active traders who want clarity, speed, and precision in their decision-making.
🧩 Core Features
🔹 1. Adaptive Trend Detection System
DTC Advanced uses a layered set of moving averages to track market momentum in real time. It identifies whether the market is trending upward, downward, or moving sideways. This system adapts to different market conditions and helps traders avoid false signals by waiting for clean alignment across multiple momentum layers.
* Bullish Trend: When all levels align upward.
* Bearish Trend: When all levels align downward.
* Neutral Trend: When there’s no clear alignment.
The trend is visually represented using colored clouds and optional candle coloring, making it easy to spot trend changes at a glance.
🔹 2. Real-Time Trade Signal Alerts
The indicator automatically detects and marks key moments when a new trend begins. It displays clear labels like “LONG” or “SHORT” on the chart when the market flips direction.
These trade signals are designed to:
* Appear only at confirmed turning points.
* Avoid noise and premature entries.
* Help traders align with new market momentum early.
🔹 3. Intelligent Trade Planning (Entry, SL, TP)
As soon as a trend shift is detected, DTC Advanced calculates:
* Entry Point – Based on current market price.
* Stop Loss – Based on recent price structure.
* Take Profits (TP1 to TP4) – Based on a consistent risk-reward ratio (from 1:1 to 4:1).
These levels are drawn on the chart as clear horizontal lines with labels, giving the trader a full, ready-made trade plan in real time. This allows for disciplined trading with predefined risk and profit targets.
🔹 4. Dynamic Stop Loss Sizing
Traders can choose how aggressive or conservative they want their Stop Loss to be:
* Tiny – Very tight SL for scalping or low-volatility environments.
* Small / Mid / Large – For larger market moves or longer-term trades.
This flexibility allows the indicator to adapt to different trading styles and asset classes.
🔹 5. Live Performance Dashboard
A built-in mini-dashboard displays everything the trader needs to know at a glance:
* Current trend direction
* Entry and Stop Loss prices
* Take Profit targets
* Real-time profit/loss estimate
* Capital and leverage input
The dashboard updates automatically as price action unfolds. It's fully integrated into the chart view and helps traders stay focused without switching between tools or calculating manually.
🔹 6. Clean Visuals with Custom Control
Traders can customize:
* Which elements to display (e.g., TP/SL levels, trend cloud, dashboard)
* The style and color of trend visuals
* Whether to color candles based on trend
This ensures that DTC Advanced fits seamlessly into any trader’s chart setup, without adding clutter.
✅ Key Benefits
* Simplifies Decision-Making: Trade with confidence using pre-calculated entries and exits.
* Improves Consistency: Follow a structured, repeatable process every time.
* Saves Time: No need to manually draw levels or calculate risk/reward.
* Enhances Discipline: Stick to your plan with clearly defined targets.
🎯 Who Is It For?
DTC Advanced | 1.4 is ideal for:
* Swing traders who want to catch full trend moves.
* Intraday traders looking for clean signals and fast decisions.
* Beginner traders seeking structure and clarity.
* Experienced traders who want to scale decisions and automate risk logic.
🧠 What Makes It Unique?
Unlike most indicators that offer either trend analysis or trade planning, DTC Advanced | 1.4 does **both**—plus real-time performance tracking.It acts like your personal trade assistant, always one step ahead, helping you read the market, plan your moves, and stick to a strategy.
Watermark DMT📌 Description – Watermark Static (Customizable)
This indicator displays a static watermark on your chart with fully customizable text. It's ideal for showing your channel name, brand, strategy title, or any personal message directly on the chart background.
✅ Features:
Custom text input
Adjustable text size, text color, and background color
Flexible positioning: top, middle, bottom × left, center, right
No blinking or animation – stable and always visible
Use it for:
Branding in screenshots or videos
Quick layout identification
Clean and organized visual appearance
2 CGC EMAChecks for 2 green closes above EMA.
Sends only one buy signal when this happens initially.
Won't send another buy signal until price closes below the EMA at least once (resets).
EMA is plotted with your offset visually.
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.
Bullish Reversal Hedge📋 Indicator Description – Bullish Reversal Hedge (XAUUSD, 15m Chart)
This indicator is specifically designed for XAUUSD (Gold) on the 15-minute timeframe. It uses RSI (Relative Strength Index) and bullish candle confirmation to detect potential reversal points.
When RSI crosses above the oversold level (30) and a bullish candle forms, the system triggers a Buy Entry (1 Lot). If the price drops by a certain number of points and the Buy Target is not hit, a Sell Entry (2 Lots) is placed as a hedge.
🔹 Key Hedging Feature:
The hedging logic is designed in such a way that loss-making trades are often closed at breakeven or in profit. It helps reduce the impact of wrong entries through dynamic reversal-based protection.
🔹 Core Features:
Point-based entry, target, and stop loss customized for XAUUSD volatility.
Smart hedge entry system after initial trade failure.
Visual labels and alert support for entries, targets, and stop loss.
Ideal for intraday strategies on the 15-minute chart.
⚠️ Disclaimer
This indicator is intended for educational and backtesting purposes only. The hedging logic is crafted to maximize the chance of recovering from loss-making positions by closing them at breakeven or in profit most of the time.
However, it does not guarantee any profits.
Trading in financial markets carries inherent risk. Please do your own analysis and consult a certified financial advisor before trading with real capital.
INDIAN HANUMAN 369 2.0🛕 INDIAN HANUMAN 369 2.0
Optimized for Heikin Ashi Candles
A powerful and versatile trading tool designed for scalping, intraday, swing, and long-term trading. This indicator delivers clean and reliable entry/exit signals that work well across stocks, options, futures, crypto, and forex.
🔍 How to Use:
📊 Use with Heikin Ashi candles for smooth trend detection
💰 Exit early if your profit target is achieved — no need to wait for a signal
🔔 Built-in alerts for Long/Short entries and exits
🕒 Timeframe Recommendations:
Use Case Recommended Timeframe
Scalping (Options Expiry) 1 Minute
Crypto/Forex (News Time) 1 Minute
Intraday (General) 3 Minutes
Consolidation (11 AM – 2 PM IST) 5 Minutes
Monthly Stock & Futures Trades 15 Minutes
Long-Term Holding (1+ Month) 1 Hour
📈 Pro Tips for Maximum Gains:
✅ Avoid Overtrading – Focus on 2–3 high-quality setups per day
📊 Backtest First – Validate performance on at least 3 months of historical data
📈 Scale Gradually – Start small and only increase size after 5 consecutive wins
✅ Best Practices:
Backtest on your preferred assets and timeframes before live use
Ideal during market hours for Indian equities and derivatives
Works equally well across global markets and crypto exchanges
💬 Final Note:
Practice for 2–3 days, trust the process, and trade smart! 📈🚀
⚠️ Disclaimer:
This tool is for educational purposes only. No indicator guarantees profits. Always use proper risk management.
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.
Gibbs - Algorithmic Macro TrackerThis script plots visual markers (lines and labels) on the price chart to highlight specific macro announcement windows (aka “macro times”) during the trading day.
Specifically:
It marks time windows like 08:20–08:40, 09:50–10:10, 03:20–03:40, etc., depending on session (US, London, Early US).
It draws vertical lines at the start and end of each window.
It optionally extends projection lines (dotted) up to the current high.
It places labels with the word “MACRO” and the time range, so you know visually when you’re in or near macro-sensitive periods.
The display works only on intraday timeframes (≤5min).
You can turn each macro window on or off using the input panel.
It adapts the timezone you set (default GMT-4, i.e., New York).
[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.
