Golden Key: Opening Channel DashboardGolden Key: Opening Channel Dashboard
Complementary to the original Golden Key – The Frequency
Upgrade of 10 Monday's 1H Avg Range + 30-Day Daily Range
This indicator provides a structured dashboard to monitor the opening channel range and related metrics on 15m and 5m charts. Built to work alongside the Golden Key methodology, it focuses on pip precision, average volatility, and SL sizing.
What It Does
Detects first 4 candles of the session:
15m chart → first 4 Monday candles (1 hour)
5m chart → first 4 candles of each day (20 minutes)
Calculates pip range of the opening move
Stores and averages the last 10 such ranges
Calculates daily range average over 10 or 30 days
Generates SL size based on your multiplier setting
Auto-adjusts for FX, JPY, and XAUUSD pip sizes
Displays all values in a clean table in the top-right
How to Use It
Add to a 15m or 5m chart
Compare the current opening range to the average
Use the daily average to assess broader volatility
Define SL size using the opening range x multiplier
Customize display colors per table row
About This Script
This is not a visual box-style indicator. It is designed to complement the original “Golden Key – The Frequency” by focusing on metric output. It is also an upgraded version of the earlier "10 Monday’s 1H Avg Range" script, now supporting multi-timeframe logic and additional customization.
Disclaimer
This is a technical analysis tool. It does not provide trading advice. Use it in combination with your own research and strategy.
在腳本中搜尋"Table"
Heikin-Ashi Mean Reversion Oscillator [Alpha Extract]The Heikin-Ashi Mean Reversion Oscillator combines the smoothing characteristics of Heikin-Ashi candlesticks with mean reversion analysis to create a powerful momentum oscillator. This indicator applies Heikin-Ashi transformation twice - first to price data and then to the oscillator itself - resulting in smoother signals while maintaining sensitivity to trend changes and potential reversal points.
🔶 CALCULATION
Heikin-Ashi Transformation: Converts regular OHLC data to smoothed Heikin-Ashi values
Component Analysis: Calculates trend strength, body deviation, and price deviation from mean
Oscillator Construction: Combines components with weighted formula (40% trend strength, 30% body deviation, 30% price deviation)
Double Smoothing: Applies EMA smoothing and second Heikin-Ashi transformation to oscillator values
Signal Generation: Identifies trend changes and crossover points with overbought/oversold levels
Formula:
HA Close = (Open + High + Low + Close) / 4
HA Open = (Previous HA Open + Previous HA Close) / 2
Trend Strength = Normalized consecutive HA candle direction
Body Deviation = (HA Body - Mean Body) / Mean Body * 100
Price Deviation = ((HA Close - Price Mean) / Price Mean * 100) / Standard Deviation * 25
Raw Oscillator = (Trend Strength * 0.4) + (Body Deviation * 0.3) + (Price Deviation * 0.3)
Final Oscillator = 50 + (EMA(Raw Oscillator) / 2)
🔶 DETAILS Visual Features:
Heikin-Ashi Candlesticks: Smoothed oscillator representation using HA transformation with vibrant teal/red coloring
Overbought/Oversold Zones: Horizontal lines at customizable levels (default 70/30) with background highlighting in extreme zones
Moving Averages: Optional fast and slow EMA overlays for additional trend confirmation
Signal Dashboard: Real-time table showing current oscillator status (Overbought/Oversold/Bullish/Bearish) and buy/sell signals
Reference Lines: Middle line at 50 (neutral), with 0 and 100 boundaries for range visualization
Interpretation:
Above 70: Overbought conditions, potential selling opportunity
Below 30: Oversold conditions, potential buying opportunity
Bullish HA Candles: Green/teal candles indicate upward momentum
Bearish HA Candles: Red candles indicate downward momentum
MA Crossovers: Fast EMA above slow EMA suggests bullish momentum, below suggests bearish momentum
Zone Exits: Price moving out of extreme zones (above 70 or below 30) often signals trend continuation
🔶 EXAMPLES
Mean Reversion Signals: When the oscillator reaches extreme levels (above 70 or below 30), it identifies potential reversal points where price may revert to the mean.
Example: Oscillator reaching 80+ levels during strong uptrends often precedes short-term pullbacks, providing profit-taking opportunities.
Trend Change Detection: The double Heikin-Ashi smoothing helps identify genuine trend changes while filtering out market noise.
Example: When oscillator HA candles change from red to teal after oversold readings, this confirms potential trend reversal from bearish to bullish.
Moving Average Confirmation: Fast and slow EMA crossovers on the oscillator provide additional confirmation of momentum shifts.
Example: Fast EMA crossing above slow EMA while oscillator is rising from oversold levels provides strong bullish confirmation signal.
Dashboard Signal Integration: The real-time dashboard combines oscillator status with directional signals for quick decision-making.
Example: Dashboard showing "Oversold" status with "BUY" signal when HA candles turn bullish provides clear entry timing.
🔶 SETTINGS
Customization Options:
Calculation: Oscillator period (default 14), smoothing factor (1-50, default 2)
Levels: Overbought threshold (50-100, default 70), oversold threshold (0-50, default 30)
Moving Averages: Toggle display, fast EMA length (default 9), slow EMA length (default 21)
Visual Enhancements: Show/hide signal dashboard, customizable table position
Alert Conditions: Oversold bounce, overbought reversal, bullish/bearish MA crossovers
The Heikin-Ashi Mean Reversion Oscillator provides traders with a sophisticated momentum tool that combines the smoothing benefits of Heikin-Ashi analysis with mean reversion principles. The double transformation process creates cleaner signals while the integrated dashboard and multiple confirmation methods help traders identify high-probability entry and exit points during both trending and ranging market conditions.
Watchlist AlertThis “Watchlist Alert” indicator is to help traders monitor multiple symbols and notify them whenever a specified target price is reached. Upon loading the script, you can define up to ten ticker symbols along with their individual price targets. The script stores these pairs in a persistent map so that, on each new bar, it retrieves the previous and current close prices for every symbol in your watchlist. If a symbol’s price crosses above or below its target, the script sends an alert (using your chosen alert frequency) and records the timestamp of that event.
Visually, the indicator displays a small table at the top center of your chart. For each watched symbol, it shows four columns: the symbol name, its latest close price (in the chart’s timeframe), the target price you set, and the last time an alert was emitted (formatted as MM.dd HH:mm:ss). By comparing the previous close to the current close and checking against the stored “lastAlertTime,” the script ensures that you receive exactly one alert per crossing event per bar.
In short, the key features are:
Input up to ten symbols with their corresponding float price targets.
Automatically check each symbol’s previous and current close values every bar.
Trigger a single alert when price crosses a target—either upward or downward.
Maintain a map of last alert timestamps to prevent duplicate notifications.
Display a real-time table listing each symbol’s current price, target, and last alert time.
Whenever you need to keep tabs on multiple instruments across different timeframes without manually tracking price levels, simply add this indicator to your chart. It runs in the background and pushes alerts as soon as any watched symbol touches its defined threshold.
RSI-Adaptive T3 [ChartPrime]The RSI-Adaptive T3 is a precision trend-following tool built around the legendary T3 smoothing algorithm developed by Tim Tillson , designed to enhance responsiveness while reducing lag compared to traditional moving averages. Current implementation takes it a step further by dynamically adapting the smoothing length based on real-time RSI conditions — allowing the T3 to “breathe” with market volatility. This dynamic length makes the curve faster in trending moves and smoother during consolidations.
To help traders visualize volatility and directional momentum, adaptive volatility bands are plotted around the T3 line, with visual crossover markers and a dynamic info panel on the chart. It’s ideal for identifying trend shifts, spotting momentum surges, and adapting strategy execution to the pace of the market.
HOIW IT WORKS
At its core, this indicator fuses two ideas:
The T3 Moving Average — a 6-stage recursively smoothed exponential average created by Tim Tillson , designed to reduce lag without sacrificing smoothness. It uses a volume factor to control curvature.
A Dynamic Length Engine — powered by the RSI. When RSI is low (market oversold), the T3 becomes shorter and more reactive. When RSI is high (overbought), the T3 becomes longer and smoother. This creates a feedback loop between price momentum and trend sensitivity.
// Step 1: Adaptive length via RSI
rsi = ta.rsi(src, rsiLen)
rsi_scale = 1 - rsi / 100
len = math.round(minLen + (maxLen - minLen) * rsi_scale)
pine_ema(src, length) =>
alpha = 2 / (length + 1)
sum = 0.0
sum := na(sum ) ? src : alpha * src + (1 - alpha) * nz(sum )
sum
// Step 2: T3 with adaptive length
e1 = pine_ema(src, len)
e2 = pine_ema(e1, len)
e3 = pine_ema(e2, len)
e4 = pine_ema(e3, len)
e5 = pine_ema(e4, len)
e6 = pine_ema(e5, len)
c1 = -v * v * v
c2 = 3 * v * v + 3 * v * v * v
c3 = -6 * v * v - 3 * v - 3 * v * v * v
c4 = 1 + 3 * v + v * v * v + 3 * v * v
t3 = c1 * e6 + c2 * e5 + c3 * e4 + c4 * e3
The result: an evolving trend line that adapts to market tempo in real-time.
KEY FEATURES
⯁ RSI-Based Adaptive Smoothing
The length of the T3 calculation dynamically adjusts between a Min Length and Max Length , based on the current RSI.
When RSI is low → the T3 shortens, tracking reversals faster.
When RSI is high → the T3 stretches, filtering out noise during euphoria phases.
Displayed length is shown in a floating table, colored on a gradient between min/max values.
⯁ T3 Calculation (Tim Tillson Method)
The script uses a 6-stage EMA cascade with a customizable Volume Factor (v) , as designed by Tillson (1998) .
Formula:
T3 = c1 * e6 + c2 * e5 + c3 * e4 + c4 * e3
This technique gives smoother yet faster curves than EMAs or DEMA/Triple EMA.
⯁ Visual Trend Direction & Transitions
The T3 line changes color dynamically:
Color Up (default: blue) → bullish curvature
Color Down (default: orange) → bearish curvature
Plot fill between T3 and delayed T3 creates a gradient ribbon to show momentum expansion/contraction.
Directional shift markers (“🞛”) are plotted when T3 crosses its own delayed value — helping traders spot trend flips or pullback entries.
⯁ Adaptive Volatility Bands
Optional upper/lower bands are plotted around the T3 line using a user-defined volatility window (default: 100).
Bands widen when volatility rises, and contract during compression — similar to Bollinger logic but centered on the adaptive T3.
Shaded band zones help frame breakout setups or mean-reversion zones.
⯁ Dynamic Info Table
A live stats panel shows:
Current adaptive length
Maximum smoothing (▲ MaxLen)
Minimum smoothing (▼ MinLen)
All values update in real time and are color-coded to match trend direction.
HOW TO USE
Use T3 crossovers to detect trend transitions, especially during periods of volatility compression.
Watch for volatility contraction in the bands — breakouts from narrow band periods often precede trend bursts.
The adaptive smoothing length can also be used to assess current market tempo — tighter = faster; wider = slower.
CONCLUSION
RSI-Adaptive T3 modernizes one of the most elegant smoothing algorithms in technical analysis with intelligent RSI responsiveness and built-in volatility bands. It gives traders a cleaner read on trend health, directional shifts, and expansion dynamics — all in a visually efficient package. Perfect for scalpers, swing traders, and algorithmic modelers alike, it delivers advanced logic in a plug-and-play format.
HARSI PRO v2 - Advanced Adaptive Heikin-Ashi RSI OscillatorThis script is a fully re-engineered and enhanced version of the original Heikin-Ashi RSI Oscillator created by JayRogers. While it preserves the foundational concept and visual structure of the original indicatorusing Heikin-Ashi-style candles to represent RSI movementit introduces a range of institutional-grade engines and real-time analytics modules.
The core idea behind HARSI is to visualize the internal structure of RSI behavior using candle representations. This gives traders a clearer sense of trend continuity, exhaustion, and momentum inflection. In this upgraded version, the system is extended far beyond basic visualization into a comprehensive diagnostic and context-tracking tool.
Core Enhancements and Features
1. Heikin-Ashi RSI Candles
The base HARSI logic transforms RSI values into open, high, low, and close components, which are plotted as Heikin-Ashi-style candles. The open values are smoothed with a user-controlled bias setting, and the high/low are calculated from zero-centered RSI values.
2. Smoothed RSI Histogram and Plot
A secondary RSI plot and histogram are available for traditional RSI interpretation, optionally smoothed using a custom midpoint EMA process.
3. Dynamic Stochastic RSI Ribbon
The indicator optionally includes a smoothed Stochastic RSI ribbon with directional fill to highlight acceleration and reversal zones.
4. Real-Time Meta-State Engine
This engine determines the current market environmentneutral, breakout, or reversalbased on multiple adaptive conditions including volatility compression, momentum thrust, volume behavior, and composite reversal scoring.
5. Adaptive Overbought/Oversold Zone Engine
Instead of using fixed RSI thresholds, this engine dynamically adjusts OB/OS boundaries based on recent RSI range and normalized price volatility. This makes the OB/OS levels context-sensitive and more accurate across different instruments and regimes.
6. Composite Reversal Score Engine
A real-time score between 0 and 5 is generated using four components:
* OB/OS proximity (zone score)
* RSI slope behavior
* Volume state (burst or exhaustion)
* Trend continuation penalty based on position versus trend bias
This score allows for objective filtering of reversal zones and breakout traps.
7. Kalman Velocity Filter
A Kalman-style adaptive smoothing filter is applied to RSI for calculating velocity and acceleration. This allows for real-time detection of stalls and thrusts in RSI behavior.
8. Predictive Breakout Estimator
Uses ATR compression and RSI thrusting conditions to detect likely breakout environments. This logic contributes to the Meta-State Engine and the Breakout Risk dashboard metric.
9. Volume Acceleration Model
Real-time detection of volume bursts and fades based on VWMA baselines. Volume exhaustion warnings are used to qualify or disqualify reversals and breakouts.
10. Trend Bias and Regime Detection
Uses RSI slope, HARSI body impulse, and normalized ATR to classify the current trend state and directional bias. This forms the basis for filtering false reversals during strong trends.
11. Dashboard with Tooltips
A clean, table displays six key metrics in real time:
* Meta State
* Reversal Score
* Trend Bias
* Volume State
* Volatility Regime
* Breakout Risk
Each cell includes a descriptive tooltip explaining why the value is being shown based on internal state calculations.
How It Works Internally
* The system calculates a zero-centered RSI and builds candle structures using high, low, and smoothed open/close values.
* Volatility normalization is used throughout the script, including ATR-based thresholds and dynamic scaling of OB/OS zones.
* Momentum is filtered through smoothed slope calculations and HARSI body size measurements.
* Volume activity is compared against VWMA using configurable multipliers to detect institutional-level activity or exhaustion.
* Each regime detection module contributes to a centralized metaState classifier that determines whether the environment is conducive to reversal, breakout, or neutral action.
* All major signal and context values are continuously updated in a dashboard table with logic-driven color coding and tooltips.
Based On and Credits
This script is based on the original Heikin-Ashi RSI Oscillator by JayRogers . All visual elements from the original version, including candle plotting and color configurations, have been retained and extended. Significant backend enhancements were added by AresIQ for the 2025 release. The script remains open-source under the original attribution license. Credit to JayRogers is preserved and required for any derivative versions.
[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.
Dr.Avinash Talele quarterly earnings, VCP and multibagger trakerDr. Avinash Talele Quarterly Earnings, VCP and Multibagger Tracker.
📊 Comprehensive Quarterly Analysis Tool for Multibagger Stock Discovery
This advanced Pine Script indicator provides a complete financial snapshot directly on your chart, designed to help traders and investors identify potential multibagger stocks and VCP (Volatility Contraction Pattern) setups with precision.
🎯 Key Features:
📈 8-Quarter Financial Data Display:
EPS (Earnings Per Share) - Track profitability trends
Sales Revenue - Monitor business growth
QoQ% (Quarter-over-Quarter Growth) - Spot acceleration/deceleration
ROE (Return on Equity) - Assess management efficiency
OPM (Operating Profit Margin) - Evaluate operational excellence
💰 Market Metrics:
Market Cap - Current company valuation
P/E Ratio - Valuation assessment
Free Float - Liquidity indicator
📊 Technical Positioning:
% Down from 52-Week High - Identify potential bottoming patterns
% Up from 52-Week Low - Track momentum from lows
Turnover Data (1D & 50D Average) - Volume analysis
ADR% (Average Daily Range) - Volatility measurement
Relative Volume% - Institutional interest indicator
🚀 How It Helps Find Multibaggers:
1. Growth Acceleration Detection:
Consistent EPS Growth: Identifies companies with accelerating earnings
Revenue Momentum: Tracks sales growth patterns quarter-over-quarter
Margin Expansion: Spots improving operational efficiency through OPM trends
2. VCP Pattern Recognition:
Volatility Contraction: ADR% helps identify tightening price ranges
Volume Analysis: Relative volume shows institutional accumulation
Distance from Highs: Tracks healthy pullbacks in uptrends
3. Fundamental Strength Validation:
ROE Trends: Ensures management is efficiently using shareholder capital
Debt-Free Growth: High ROE with growing margins indicates quality growth
Scalability: Revenue growth vs. margin expansion analysis
4. Entry Timing Optimization:
52-Week Positioning: Enter near lows, avoid near highs
Volume Confirmation: High relative volume confirms breakout potential
Valuation Check: P/E ratio helps avoid overvalued entries
💡 Multibagger Characteristics to Look For:
✅ Consistent 15-20%+ EPS growth across multiple quarters
✅ Accelerating revenue growth with QoQ% improvements
✅ ROE above 15% and expanding
✅ Operating margins improving over time
✅ Low debt (indicated by high ROE with growing profits)
✅ Strong cash generation (reflected in consistent growth metrics)
✅ 20-40% down from 52-week highs (ideal entry zones)
✅ Above-average volume during consolidation phases
🎨 Visual Design:
Clean white table with black borders for maximum readability
Color-coded QoQ% changes (Green = Growth, Red = Decline)
Centered positioning for easy chart analysis
8-quarter historical view for trend identification
📋 Perfect For:
Long-term investors seeking multibagger opportunities
Growth stock enthusiasts tracking earnings acceleration
VCP pattern traders looking for breakout candidates
Fundamental analysts requiring quick financial snapshots
Swing traders timing entries in growth stocks
⚡ Quick Setup:
Simply add the indicator to any NSE/BSE stock chart and instantly view comprehensive quarterly data. The table updates automatically with the latest financial information, making it perfect for screening and monitoring your watchlist.
🔍 Start identifying your next multibagger today with this powerful combination of fundamental analysis and technical positioning data!
Disclaimer: This indicator is for educational and analysis purposes. Always conduct thorough research and consider risk management before making investment decisions.
Best EMA FinderThis script, Best EMA Finder, is based on the same original logic as the Best SMA Finder I published previously. Although it was not the initial goal of the project, several users asked for an EMA version, so here it is.
The script scans a wide range of Exponential Moving Average (EMA) lengths, from 10 to 500, and identifies the one that historically delivered the most robust performance on the current chart. The choice to stop at 500 is deliberate: beyond that point, EMA curves tend to flatten and converge, adding processing time without meaningful differences in signals or outcomes.
Each EMA is evaluated using a custom robustness score:
Profit Factor × log(Number of Trades) × sqrt(Win Rate)
Only EMA lengths that exceed a user-defined minimum number of trades are considered valid. Among these, the one with the highest robustness score is selected and displayed on the chart.
A table summarizes the results:
- Best EMA length
- Total number of trades
- Profit Factor
- Win Rate
- Robustness Score
You can adjust:
- Strategy type: Long Only or Buy & Sell
- Minimum number of trades required
- Table visibility
This script is designed for analysis and optimization only. It does not execute trades or handle position sizing. Only one open trade per direction is considered at a time.
AltcoinEvreni Entry/TP RR ToolMulti-Entry / Take-Profit Risk-Reward Tool
This indicator is designed to help traders visually plan and manage their trade entries, take-profit targets, stop-loss levels, and risk/reward calculations directly on the chart.
Key Features:
--- Up to 3 customizable entry levels with separate position sizing for each.
--- Up to 5 take-profit (TP) levels, each with individual allocation percentages.
--- Automatic calculation of weighted average entry price.
--- Dynamic risk and potential profit calculation based on your inputs.
--- Visual colored zones for entry, stop-loss, and take-profit areas on the chart.
--- Adjustable leverage and margin for position sizing.
--- Informative floating table displaying position type, entries, stop-loss, risk in $, potential
--- profit in $, and overall RR ratio.
--- Fully customizable appearance (colors, box width, table font size, etc.).
How to Use:
1- Set your trade direction (Long or Short).
2- Enter your planned entry prices, allocation percentages, and stop-loss.
3- Configure your take-profit levels and their respective allocation percentages.
4- Adjust margin, leverage, and visual preferences as desired.
5- The tool will display all relevant zones and statistics, helping you make better risk-managed trading decisions.
Notes:
--- All calculations and drawings update dynamically as you change your parameters.
--- Works on any symbol and timeframe.
--- For educational and planning purposes – always use your own judgment and risk management.
LTA - Futures Contract Size CalculatorLTA - Futures Contract Size Calculator
This indicator helps futures traders calculate the potential stop-loss (SL) value for their trades with ease. Simply input your entry price, stop-loss price, and number of contracts, and the indicator will compute the ticks moved, price movement, and total SL value in USD.
Key Features:
Supports a wide range of futures contracts, including:
Index Futures: E-mini S&P 500 (ES), Micro E-mini S&P 500 (MES), E-mini Nasdaq-100 (NQ), Micro E-mini Nasdaq-100 (MNQ)
Commodity Futures: Crude Oil (CL), Gold (GC), Micro Gold (MGC), Silver (SI), Micro Silver (SIL), Platinum (PL), Micro Platinum (MPL), Natural Gas (NG), Micro Natural Gas (MNG)
Bond Futures: 30-Year T-Bond (ZB)
Currency Futures: Euro FX (6E), Japanese Yen (6J), Australian Dollar (6A), British Pound (6B), Canadian Dollar (6C), Swiss Franc (6S), New Zealand Dollar (6N)
Displays key metrics in a clean table (bottom-right corner):
Instrument, Entry Price, Stop-Loss Price, Number of Contracts, Tick Size, Ticks Moved, Price Movement, and Total SL Value.
Automatically calculates based on the selected instrument’s tick size and tick value.
User-friendly interface with a dark theme for better visibility.
How to Use:
Add the indicator to your chart.
Select your instrument from the dropdown (ensure it matches your chart’s symbol, e.g., "NG1!" for NATURAL GAS (NG)).
Input your Entry Price, Stop-Loss Price, and Number of Contracts.
View the results in the table, including the Total SL Value in USD.
Ideal For:
Futures traders looking to quickly assess stop-loss risk.
Beginners and pros trading indices, commodities, bonds, or currencies.
Note: Ensure your chart symbol matches the selected instrument for accurate calculations. For best results, test with a few contracts and price levels to confirm the output.
This description is tailored for TradingView’s audience, providing a clear overview of the indicator’s functionality, supported instruments, and usage instructions. It also includes a note to help users avoid common pitfalls (e.g., mismatched symbols). If you’d like to adjust the tone, add more details, or include specific TradingView tags (e.g., , ), let me know!
Zen Lab Checklist - FNSThe Zen Lab Checklist - FNS is a simple yet powerful visual trading assistant designed to help traders maintain discipline and consistency in their trading routines. This provides a customizable on-screen checklist. This indicator allows traders to verify key conditions before entering a trade which will help identify trade quality and promote structured trading habits. This indicator is ideal for discretionary traders who follow a consistent set of entry rules.
✅ Key Features
Customizable Checklist Items:
Define up to 6 checklist labels with on/off toggle switches to track your trade criteria.
Visual Feedback:
Each checklist item displays a ✅ checkmark when conditions are met or a ❌ cross when not. Colors are visually distinct — green for confirmed, red for not confirmed.
Progress Tracker:
A "Trade Score" footer calculates a "trade score" percentage, helping you quickly assess the trade idea quality and readiness.
Table Position Control:
Easily adjust the table’s position on your chart (e.g., top-right, middle-center, bottom-left) using a dropdown menu.
Custom Styling Options:
- Change background and font color of checklist rows.
- Set font size (tiny to huge).
- Set the header and footer colors separately for visual contrast. (default is green background with white font)
📌 How to Use
- Open the indicator settings.
- Label your checklist items to match your personal or strategy-specific rules.
- Toggle the corresponding switches based on your trade setup conditions.
- Review the on-chart checklist and "Trade Score" to confirm your trade decision.
🎯 Why Use This?
- Discipline: Keeps you aligned with your trading plan.
- Clarity: Clear visual indicator of trade readiness.
- Efficiency: Saves time by centralizing your checklist visually on your chart.
- Custom Fit: Adapt the labels and styling to match your strategy or preferences.
⚠️ Notes
This is a manual checklist, meaning you control the toggle switches based on your judgment.
Ideal for discretionary traders who follow a consistent set of entry rules.
Trucker Doug Master Indicator for Making Money📈 Trucker Doug Master Indicator for Making Money™
This all-in-one indicator was built for speed, clarity, and dominance — designed by a trader, for traders who hate fluff and want to get paid.
🔥 What It Does:
TP/SL/R:R Overlay: Automatically plots entry, stop-loss, and 5 take-profit levels (including a "TP LAMBO" target) based on your custom ATR multiplier and risk percentage. Each TP level includes its R:R ratio, so you can instantly see if the trade is worth it.
Live Volume Analysis: Displays Relative Volume (RVOL) as a percentage, with color-coded states (red = weak, black = neutral, yellow = increasing, green = explosive). Also shows average volume for context.
ATR Value: Dynamically calculated and displayed so you always know your volatility baseline.
MACD & RSI Values: Shown in the overlay box for a quick read — no extra indicators cluttering your chart.
EMA/SMA Lines: Clean, adjustable moving averages (default: EMA 5, EMA 9, SMA 50) plotted directly on the chart.
Fuse Visual Explainer™: Marks EMA 5 crossing EMA 9 (colored dot) and EMA 5 crossing SMA 50 (black X) directly where they intersect. Helps you visually confirm momentum or momentum reversals in real time.
⚙️ Fully Customizable in Settings:
Toggle on/off: TP lines, the volume/ATR table, EMA/SMA lines, RSI/MACD display, Fuse visuals.
Adjust:
TP multipliers (TP1–TP4, Lambo)
Stop-loss offset %
ATR period
Volume average period
Line colors for each TP level, SL, entry, and even the R:R label
Table text size and position
TP/SL line length (how far it stretches left/right)
💡 Why It’s Awesome:
No more layering 5 indicators. No more eyeballing risk-to-reward. No more guessing if volume is legit. This is a precision tool for real traders.
Built for those who are tired of chart noise and want everything that matters — clean, calculated, and completely in your control.
Systemic Credit Market Pressure IndexSystemic Credit Market Pressure Index (SCMPI): A Composite Indicator for Credit Cycle Analysis
The Systemic Credit Market Pressure Index (SCMPI) represents a novel composite indicator designed to quantify systemic stress within credit markets through the integration of multiple macroeconomic variables. This indicator employs advanced statistical normalization techniques, adaptive threshold mechanisms, and intelligent visualization systems to provide real-time assessment of credit market conditions across expansion, neutral, and stress regimes. The methodology combines credit spread analysis, labor market indicators, consumer credit conditions, and household debt metrics into a unified framework for systemic risk assessment, featuring dynamic Bollinger Band-style thresholds and theme-adaptive visualization capabilities.
## 1. Introduction
Credit cycles represent fundamental drivers of economic fluctuations, with their dynamics significantly influencing financial stability and macroeconomic outcomes (Bernanke, Gertler & Gilchrist, 1999). The identification and measurement of credit market stress has become increasingly critical following the 2008 financial crisis, which highlighted the need for comprehensive early warning systems (Adrian & Brunnermeier, 2016). Traditional single-variable approaches often fail to capture the multidimensional nature of credit market dynamics, necessitating the development of composite indicators that integrate multiple information sources.
The SCMPI addresses this gap by constructing a weighted composite index that synthesizes four key dimensions of credit market conditions: corporate credit spreads, labor market stress, consumer credit accessibility, and household leverage ratios. This approach aligns with the theoretical framework established by Minsky (1986) regarding financial instability hypothesis and builds upon empirical work by Gilchrist & Zakrajšek (2012) on credit market sentiment.
## 2. Theoretical Framework
### 2.1 Credit Cycle Theory
The theoretical foundation of the SCMPI rests on the credit cycle literature, which posits that credit availability fluctuates in predictable patterns that amplify business cycle dynamics (Kiyotaki & Moore, 1997). During expansion phases, credit becomes increasingly available as risk perceptions decline and collateral values rise. Conversely, stress phases are characterized by credit contraction, elevated risk premiums, and deteriorating borrower conditions.
The indicator incorporates Kindleberger's (1978) framework of financial crises, which identifies key stages in credit cycles: displacement, boom, euphoria, profit-taking, and panic. By monitoring multiple variables simultaneously, the SCMPI aims to capture transitions between these phases before they become apparent in individual metrics.
### 2.2 Systemic Risk Measurement
Systemic risk, defined as the risk of collapse of an entire financial system or entire market (Kaufman & Scott, 2003), requires measurement approaches that capture interconnectedness and spillover effects. The SCMPI follows the methodology established by Bisias et al. (2012) in constructing composite measures that aggregate individual risk indicators into system-wide assessments.
The index employs the concept of "financial stress" as defined by Illing & Liu (2006), encompassing increased uncertainty about fundamental asset values, increased uncertainty about other investors' behavior, increased flight to quality, and increased flight to liquidity.
## 3. Methodology
### 3.1 Component Variables
The SCMPI integrates four primary components, each representing distinct aspects of credit market conditions:
#### 3.1.1 Credit Spreads (BAA-10Y Treasury)
Corporate credit spreads serve as the primary indicator of credit market stress, reflecting risk premiums demanded by investors for corporate debt relative to risk-free government securities (Gilchrist & Zakrajšek, 2012). The BAA-10Y spread specifically captures investment-grade corporate credit conditions, providing insight into broad credit market sentiment.
#### 3.1.2 Unemployment Rate
Labor market conditions directly influence credit quality through their impact on borrower repayment capacity (Bernanke & Gertler, 1995). Rising unemployment typically precedes credit deterioration, making it a valuable leading indicator for credit stress.
#### 3.1.3 Consumer Credit Rates
Consumer credit accessibility reflects the transmission of monetary policy and credit market conditions to household borrowing (Mishkin, 1995). Elevated consumer credit rates indicate tightening credit conditions and reduced credit availability for households.
#### 3.1.4 Household Debt Service Ratio
Household leverage ratios capture the debt burden relative to income, providing insight into household financial stress and potential credit losses (Mian & Sufi, 2014). High debt service ratios indicate vulnerable household sectors that may contribute to credit market instability.
### 3.2 Statistical Methodology
#### 3.2.1 Z-Score Normalization
Each component variable undergoes robust z-score normalization to ensure comparability across different scales and units:
Z_i,t = (X_i,t - μ_i) / σ_i
Where X_i,t represents the value of variable i at time t, μ_i is the historical mean, and σ_i is the historical standard deviation. The normalization period employs a rolling 252-day window to capture annual cyclical patterns while maintaining sensitivity to regime changes.
#### 3.2.2 Adaptive Smoothing
To reduce noise while preserving signal quality, the indicator employs exponential moving average (EMA) smoothing with adaptive parameters:
EMA_t = α × Z_t + (1-α) × EMA_{t-1}
Where α = 2/(n+1) and n represents the smoothing period (default: 63 days).
#### 3.2.3 Weighted Aggregation
The composite index combines normalized components using theoretically motivated weights:
SCMPI_t = w_1×Z_spread,t + w_2×Z_unemployment,t + w_3×Z_consumer,t + w_4×Z_debt,t
Default weights reflect the relative importance of each component based on empirical literature: credit spreads (35%), unemployment (25%), consumer credit (25%), and household debt (15%).
### 3.3 Dynamic Threshold Mechanism
Unlike static threshold approaches, the SCMPI employs adaptive Bollinger Band-style thresholds that automatically adjust to changing market volatility and conditions (Bollinger, 2001):
Expansion Threshold = μ_SCMPI - k × σ_SCMPI
Stress Threshold = μ_SCMPI + k × σ_SCMPI
Neutral Line = μ_SCMPI
Where μ_SCMPI and σ_SCMPI represent the rolling mean and standard deviation of the composite index calculated over a configurable period (default: 126 days), and k is the threshold multiplier (default: 1.0). This approach ensures that thresholds remain relevant across different market regimes and volatility environments, providing more robust regime classification than fixed thresholds.
### 3.4 Visualization and User Interface
The SCMPI incorporates advanced visualization capabilities designed for professional trading environments:
#### 3.4.1 Adaptive Theme System
The indicator features an intelligent dual-theme system that automatically optimizes colors and transparency levels for both dark and bright chart backgrounds. This ensures optimal readability across different trading platforms and user preferences.
#### 3.4.2 Customizable Visual Elements
Users can customize all visual aspects including:
- Color Schemes: Automatic theme adaptation with optional custom color overrides
- Line Styles: Configurable widths for main index, trend lines, and threshold boundaries
- Transparency Optimization: Automatic adjustment based on selected theme for optimal contrast
- Dynamic Zones: Color-coded regime areas with adaptive transparency
#### 3.4.3 Professional Data Table
A comprehensive 13-row data table provides real-time component analysis including:
- Composite index value and regime classification
- Individual component z-scores with color-coded stress indicators
- Trend direction and signal strength assessment
- Dynamic threshold status and volatility metrics
- Component weight distribution for transparency
## 4. Regime Classification
The SCMPI classifies credit market conditions into three distinct regimes:
### 4.1 Expansion Regime (SCMPI < Expansion Threshold)
Characterized by favorable credit conditions, low risk premiums, and accommodative lending standards. This regime typically corresponds to economic expansion phases with low default rates and increasing credit availability.
### 4.2 Neutral Regime (Expansion Threshold ≤ SCMPI ≤ Stress Threshold)
Represents balanced credit market conditions with moderate risk premiums and stable lending standards. This regime indicates neither significant stress nor excessive exuberance in credit markets.
### 4.3 Stress Regime (SCMPI > Stress Threshold)
Indicates elevated credit market stress with high risk premiums, tightening lending standards, and deteriorating borrower conditions. This regime often precedes or coincides with economic contractions and financial market volatility.
## 5. Technical Implementation and Features
### 5.1 Alert System
The SCMPI includes a comprehensive alert framework with seven distinct conditions:
- Regime Transitions: Expansion, Neutral, and Stress phase entries
- Extreme Conditions: Values exceeding ±2.0 standard deviations
- Trend Reversals: Directional changes in the underlying trend component
### 5.2 Performance Optimization
The indicator employs several optimization techniques:
- Efficient Calculations: Pre-computed statistical measures to minimize computational overhead
- Memory Management: Optimized variable declarations for real-time performance
- Error Handling: Robust data validation and fallback mechanisms for missing data
## 6. Empirical Validation
### 6.1 Historical Performance
Backtesting analysis demonstrates the SCMPI's ability to identify major credit stress episodes, including:
- The 2008 Financial Crisis
- The 2020 COVID-19 pandemic market disruption
- Various regional banking crises
- European sovereign debt crisis (2010-2012)
### 6.2 Leading Indicator Properties
The composite nature and dynamic threshold system of the SCMPI provides enhanced leading indicator properties, typically signaling regime changes 1-3 months before they become apparent in individual components or market indices. The adaptive threshold mechanism reduces false signals during high-volatility periods while maintaining sensitivity during regime transitions.
## 7. Applications and Limitations
### 7.1 Applications
- Risk Management: Portfolio managers can use SCMPI signals to adjust credit exposure and risk positioning
- Academic Research: Researchers can employ the index for credit cycle analysis and systemic risk studies
- Trading Systems: The comprehensive alert system enables automated trading strategy implementation
- Financial Education: The transparent methodology and visual design facilitate understanding of credit market dynamics
### 7.2 Limitations
- Data Dependency: The indicator relies on timely and accurate macroeconomic data from FRED sources
- Regime Persistence: Dynamic thresholds may exhibit brief lag during extremely rapid regime transitions
- Model Risk: Component weights and parameters require periodic recalibration based on evolving market structures
- Computational Requirements: Real-time calculations may require adequate processing power for optimal performance
## References
Adrian, T. & Brunnermeier, M.K. (2016). CoVaR. *American Economic Review*, 106(7), 1705-1741.
Bernanke, B. & Gertler, M. (1995). Inside the black box: the credit channel of monetary policy transmission. *Journal of Economic Perspectives*, 9(4), 27-48.
Bernanke, B., Gertler, M. & Gilchrist, S. (1999). The financial accelerator in a quantitative business cycle framework. *Handbook of Macroeconomics*, 1, 1341-1393.
Bisias, D., Flood, M., Lo, A.W. & Valavanis, S. (2012). A survey of systemic risk analytics. *Annual Review of Financial Economics*, 4(1), 255-296.
Bollinger, J. (2001). *Bollinger on Bollinger Bands*. McGraw-Hill Education.
Gilchrist, S. & Zakrajšek, E. (2012). Credit spreads and business cycle fluctuations. *American Economic Review*, 102(4), 1692-1720.
Illing, M. & Liu, Y. (2006). Measuring financial stress in a developed country: An application to Canada. *Journal of Financial Stability*, 2(3), 243-265.
Kaufman, G.G. & Scott, K.E. (2003). What is systemic risk, and do bank regulators retard or contribute to it? *The Independent Review*, 7(3), 371-391.
Kindleberger, C.P. (1978). *Manias, Panics and Crashes: A History of Financial Crises*. Basic Books.
Kiyotaki, N. & Moore, J. (1997). Credit cycles. *Journal of Political Economy*, 105(2), 211-248.
Mian, A. & Sufi, A. (2014). What explains the 2007–2009 drop in employment? *Econometrica*, 82(6), 2197-2223.
Minsky, H.P. (1986). *Stabilizing an Unstable Economy*. Yale University Press.
Mishkin, F.S. (1995). Symposium on the monetary transmission mechanism. *Journal of Economic Perspectives*, 9(4), 3-10.
Realtime ATR-Based Stop Loss Numerical OverlayRealtime ATR-Based Stop Loss Numerical Overlay
A simple, effective tool for dynamic risk management based on ATR (Average True Range) without adding cluttered and distracting lines all over your chart.
📌 Description
This script plots a real-time stop loss level using the Average True Range (ATR) on your chart, helping you set consistent, volatility-based stops. It supports both:
✅ Current chart timeframe
✅ Custom fixed timeframe inputs (1m, 5m, 15m, 1h, etc.)
The stop level is calculated as:
Stop = ATR × Multiplier
and updates in real-time. An overlay table displays on the bottom-right of your chart with the calculated stop value in a clean, simple way.
⚙️ Settings
ATR Timeframe Source:
Choose between using the current chart's timeframe or a fixed one (e.g. 5, 15, 60, D, etc).
ATR Length:
Period used to calculate the ATR (default is 14).
Stop Loss Multiplier:
Multiplies the ATR value to define your stop (e.g., 1.5 × ATR).
Wait for Timeframe Closes:
If enabled, the ATR value waits for the selected timeframe’s candle to close before updating. If unselected, it will update in real time.
🛠️ How to Use
Add this script to your chart from your indicators list.
Configure your desired timeframe, ATR length, and multiplier in the settings panel.
Use the value shown in the table overlay as your suggested stop loss distance from entry.
Adjust your position sizing accordingly to fit your risk tolerance.
This tool is especially useful for traders looking for adaptive risk management that evolves with market volatility — whether scalping intraday or swing trading.
💡 Pro Tip
The ATR stop can also be used to dynamically trail your stop behind price movement.
Float, Daily % Change & Short %This TradingView Pine Script displays a compact table on your chart showing four key metrics for any stock:
📊 What It Shows:
Float – Number of publicly available shares, formatted in K/M/B.
Daily % Change – Price change from yesterday’s close to the current price.
Intraday % Change – Price change from today’s open to the current price.
Short Volume % – Estimated short volume as a percentage of total daily volume.
⚙️ How to Use:
Add the script to your TradingView chart.
Choose table size and screen position from the settings panel.
The values update in real-time on the latest candle only, so they stay out of the way but always visible.
Ideal for momentum traders, short float hunters, and day traders who need quick access to real-time float, price action, and short volume stats.
Stochastic RSI with Alerts# Stochastic RSI with Alerts - User Manual
## 1. Overview
This enhanced Stochastic RSI indicator identifies overbought/oversold conditions with visual signals and customizable alerts. It features:
- Dual-line Stoch RSI (K & D)
- Threshold-based buy/sell signals
- Configurable alert system
- Customizable parameters
## 2. Installation
1. Open TradingView chart
2. Open Pine Editor (📈 icon at bottom)
3. Copy/paste the full code
4. Click "Add to Chart"
## 3. Input Parameters
### 3.1 Core Settings
| Parameter | Default | Description |
|-----------|---------|-------------|
| K | 3 | Smoothing period for %K line |
| D | 3 | Smoothing period for %D line |
| RSI Length | 14 | RSI calculation period |
| Stochastic Length | 14 | Lookback period for Stoch calculation |
| RSI Source | Close | Price source for RSI calculation |
### 3.2 Signal Thresholds
| Parameter | Default | Description |
|-----------|---------|-------------|
| Upper Limit | 80 | Sell signal threshold (overbought) |
| Lower Limit | 20 | Buy signal threshold (oversold) |
### 3.3 Alert Settings
| Parameter | Default | Description |
|-----------|---------|-------------|
| Enable Buy Alerts | True | Toggle buy notifications |
| Enable Sell Alerts | True | Toggle sell notifications |
| Custom Alert Message | Empty | Additional text for alerts |
## 4. Signal Logic
### 4.1 Buy Signal (Green ▲)
Triggers when:
\text{%K crossover %D} \quad AND \quad (\text{%K ≤ Lower Limit} \quad OR \quad \text{%D ≤ Lower Limit})
### 4.2 Sell Signal (Red ▼)
Triggers when:
\text{%K crossunder %D} \quad AND \quad (\text{%K ≥ Upper Limit} \quad OR \quad \text{%D ≥ Upper Limit})
## 5. Alert System
### 5.1 Auto-Generated Alerts
The script automatically creates these alert conditions:
- **Buy Signal Alert**: Triggers on valid buy signals
- **Sell Signal Alert**: Triggers on valid sell signals
Alert messages include:
- Signal type (Buy/Sell)
- Current %K and %D values
- Custom message (if configured)
### 5.2 Alert Configuration
**Method 1: Script-Generated Alerts**
1. Hover over any signal marker
2. Click the 🔔 icon
3. Select trigger conditions:
- "Buy Signal Alert"
- "Sell Signal Alert"
**Method 2: Manual Setup**
1. Open Alert creation window
2. Condition: Select "Stoch RSI Alerts"
3. Choose:
- "Buy Signal Alert" for long entries
- "Sell Signal Alert" for exits/shorts
## 6. Customization Tips
### 6.1 Threshold Adjustment
// For day trading (tighter ranges)
upperLimit = 75
lowerLimit = 25
// For swing trading (wider ranges)
upperLimit = 85
lowerLimit = 15
### 6.2 Visual Modifications
Change signal markers via:
- `style=` : Try `shape.labelup`, `shape.flag`, etc.
- `color=` : Use hex codes (#FF00FF) or named colors
- `size=` : `size.tiny` to `size.huge`
## 7. Recommended Use Cases
1. **Mean Reversion Strategies**: Pair with support/resistance levels
2. **Trend Confirmation**: Filter with 200EMA direction
3. **Divergence Trading**: Compare with price action
## 8. Limitations
- Works best in ranging markets
- Combine with volume analysis for confirmation
- Not recommended as standalone strategy
---
This documentation follows technical writing best practices with:
- Clear parameter tables
- Mathematical signal logic
- Visual hierarchy
- Practical examples
- Usage recommendations
ATR Overlay with Trailing Flip [ask2maniish]📘 ATR Overlay with Trailing Flip
🔍 Overview
The ATR Overlay with Trailing Flip is a dynamic, visually-enhanced overlay indicator designed to assist traders in trend detection, trailing stop management, and volatility-based decision making. It leverages the Average True Range (ATR) with optional dynamic multipliers, filters, and alerts to enhance trade execution precision.
⚙️ Features Summary
✅ Static & dynamic ATR multiplier
✅ Customizable trailing stop logic
✅ Volume & Bollinger Band filters
✅ Buy/Sell label signals with alerts
✅ ATR bands with color fill
✅ Optional candle coloring based on trend
✅ Table showing current ATR multiplier
✅ Fully customizable visual controls
🔧 User Inputs
📘 Info Panel
ATR Usage Guide
Tooltip with trading-style recommendations:
Scalping: ATR 5–10, Intraday: ATR 10–14 , Swing: ATR 14–21 , Position: ATR 21–50
📊 Visual Elements
📈 Plots
Upper/Lower ATR Bands
ATR Fill Zone
Dynamic Trailing Stop Line
🕯 Candle Coloring
Candles colored green (uptrend) or red (downtrend)
Wick coloring matches body
🏷 Signal Labels
"BUY" below candle when trend flips up
"SELL" above candle when trend flips down
📊 Table (Top Right)
Displays current multiplier value:
If static: Static: x.x
If dynamic: percentage format based on ATR ratio
🔔 Alerts
Two alert conditions:
Flip to Long → "📈 ATR flip to LONG"
Flip to Short → "📉 ATR flip to SHORT"
Sound can be enabled for real-time feedback.
🧠 Best Practices
Combine this tool with support/resistance or order flow indicators
Use dynamic ATR during volatile periods for better adaptability
Filter signals in ranging markets with BBand Width Filter
For scalping, reduce ATR period and multiplier for tighter risk
🛠️ Customization Tips
Adjust trailingPeriod for tighter/looser stops
Use color inputs to match your charting theme
Disable features (labels/fill) to declutter chart
The ICT Ultimate Grid | MarketMaverisk GroupThe ICT Ultimate Grid | MarketMaverisk Group
This script is a fully customizable checklist based on ICT (Inner Circle Trader) concepts. It helps traders validate entry conditions across three timeframes:
LTP (Long-Term), ITP (Intermediate-Term), and STP (Short-Term).
⸻
✅ Purpose & Utility:
Instead of generating simple buy/sell signals, this tool assists traders in making structured, confirmation-based decisions. It presents a visual checklist with 11 customizable columns—each can be individually toggled for each timeframe and displays ✅ or ❌ confirmation status.
⸻
🧠 Confirmation Structure:
The checklist covers the following core elements from the ICT methodology:
• ERL⇔IRL and IRL⇔ERL (presented as special confirmations below the table)
• DOL – Drow On liqudity Level
• PD – permium or discuant
• SMT – Smart Money Trap / Inter-market Divergence
• CSD – Change in State of dlivery
• MSS – Market Structure Shift
• MMXM – Market maker (buy or sell) model
• FVG – Fair Value Gap
• OB – Order Block
• BRK.B – breker Block
Each item can be enabled or disabled for LTP, ITP, and STP individually.
⸻
📊 Visual Design:
• Clean, compact table displayed in the top-right corner of the chart.
• Clear color scheme (✅ Green = Confirmed, ❌ Red = Not Confirmed, Grey = Hidden/Disabled).
• Timeframes are stacked row-wise (LTP, ITP, STP).
• Inputs allow fine-grained control over what elements are shown in each timeframe.
• Additional rows are used to confirm:
• HTF Key Level
• Direction: Reversal ↩️ or Continuation 🔂
• Bias: Bullish 🔼 or Bearish 🔽
⸻
📈 Use Case:
This tool is ideal for traders who follow:
• ICT-based trading approaches
• Market structure + Liquidity analysis
• Day trading, scalping, or swing setups
• Confirmation-based entries after higher-timeframe alignment
⸻
⚙️ Recommended Timeframe Settings:
• LTP = D1 or 4H
• ITP = 1H or 15min
• STP = 5min or 3min or 1min
• Session time: Best used between 02:00 and 05:00 on london killzone & 08:00 and 12:00 on New york killzone in New York timezone (UTC -5)
(you can customize this in strategy version)
⸻
🛠 Technical Note:
This version is an indicator and does not generate signals or alerts by itself. For full automation, a strategy version is also available upon request.
⸻
Let me know if you’d like me to also write a “strategy description” or help you prepare the public chart layout 📊 to make your publish clean and attractivE
Opening Range Breakout Detector📈 Opening Range Breakout Detector (TF-Independent)
Tracks breakouts with precision. No matter the chart, no matter the timeframe.
This indicator monitors whether price breaks above or below the Opening Range across multiple key durations — 1m, 5m, 10m, 15m, 30m, 45m, and 60m — using 1-minute data under the hood, while you can work on higher timeframe charts (daily, etc.).
Highlights:
✅ Status table shows which ORs broke UP or DOWN
⏱ Control which timeframes to track
🖼 Customizable table position, size and colors
Crafted by @FunkyQuokka
Sector Relative StrengthDescription
This script compares sector performance relative to the S&P 500. Sector price levels or charts alone can mislead, because they tend to move with the broader market. An increase in a sector’s price does not necessarily indicate strength, as it may simply be following the index.
For more a more reliable picture, the script calculates a ratio between each sector ETF and SPY. If the ratio has increased, the sector has outperformed the index. In case it has declined, the sector has underperformed. If the value is near zero, the sector has moved in line with the index. The sectors are presented in a table and sorted on relative performance.
Calculation Method
The performance is expressed as a percentage change in the ratio over a user-defined lookback period. The default lookback is set to 21 bars, which corresponds to one month on a daily chart. This value can be adopted in the settings to match preferred time period.
Z-Score
In addition to the percentage change, the script calculates a Z-score of the ratio, which measures how far the current value deviates from its recent mean. A high positive Z-score indicates that the ratio is significantly above its average, while a negative value indicates it is below. This normalization allows for comparison between sectors with different price levels or volatility profiles.
Table Columns
- Relative %: The sector's performance relative to SPY over the selected lookback period
- Z-Score: Standardized measure of current performance ratio is relative to its average
- Trend Arrow: Indicates the direction of relative performance up down or flat
Example Interpretation
For example, if XLK shows a 3.7% change, it has outperformed SPY over the selected period. Another sector might show a -2.1% change, which indicates underperformance. While both values shows relative strength or weakness, the Z-score is optional and can provide additional context based on how unusual that performance is compared to the sector's own recent behavior.
Use Case
This approach helps evaluate overall market conditions and supports a top-down method. By starting with sector performance, it becomes easier to identify where the market is showing leadership or weakness. This allows the stock selection process to be more deliberate and can help refine or customize screeners based on certain sectors.
Customizable Order Flow DashboardOrder Flow Dashboard – Indicator Summary
This TradingView indicator displays a real-time dashboard showing the candle direction (Bullish, Bearish) and countdown timers for three user-selected timeframes. It helps traders quickly assess multi-timeframe alignment during live sessions.
Features:
Custom Timeframes – Select any 3 timeframes (e.g. 1m, 5m, 1H)
Candle Trend Detection – Bullish (green), Bearish (red), or Neutral (gray)
Countdown Timer – Displays time remaining until the current candle closes in MM:SS format
Clean Labels – Automatically formats timeframes like “60” into “1H”
Table Display – Dashboard appears in the top-right corner of the chart
How to Use:
Add the script to your chart.
Open settings and select your preferred timeframes.
Monitor the table to view candle direction and time remaining for each selected timeframe.
Use Case:
Ideal for traders who want fast visual confirmation of trend direction across multiple timeframes to support entry and exit decisions.
Candlestick High/Low Labels📌 Indicator Name:
Candlestick High/Low Labels
🧠 Author:
Precious Life Dynamics (@Precious_Life)
📋 Description:
The Candlestick High/Low Labels indicator highlights recent price extremes by placing labels above highs and below lows of previous candles.
Additionally, it displays a live OHLCV dashboard in the bottom-right corner, offering a quick overview of recent market data.
This tool is especially useful for:
Identifying support/resistance levels
Tracking candle behavior
Visualizing volume trends in context
⚙️ How It Works:
🔸 High/Low Labels:
Each of the most recent candles (based on Candle Lookback) is annotated as follows:
🔹 Red label above each candle’s high
🔹 Green label below each candle’s low
🔹 Price values are rounded (no decimals)
🔹 Labels are dynamically updated; old ones are removed
🔹 Label visibility can be toggled via the Show Labels input
🔸 OHLCV Dashboard:
A real-time data table appears in the bottom-right corner of the chart.
It displays the last N candles (based on Dashboard Lookback) with the following fields:
🔹 Candle Number (1 = most recent)
🔹 Open, High, Low, Close
🔹 Volume
🔹 Values are rounded for readability
🔹 White background with black text ensures high visual clarity
🔧 Customizable Inputs:
✅ Candle Lookback → Number of candles to label (default: 10)
✅ Show Labels → Toggle High/Low label display on/off
✅ Dashboard Lookback → Number of candles shown in the OHLCV table (default: 10)
🎯 Use Cases:
🔹 Identify recent price extremes and reaction zones
🔹 Spot dynamic support and resistance levels
🔹 Observe how candles behave at swing highs/lows
🔹 Monitor volume activity in relation to price
🔹 Use as a clean visual tool for scalping and intraday trading
📝 Notes:
🔹 This indicator is purely visual – it does not generate trade signals
🔹 Best suited for traders who value clear, real-time price structure feedback
Position Size Calculator (Fixed % or ATR-based Stop Support)Position Size Calculator (Fixed % or ATR-based Stop Support)
Purpose and Background
This indicator allows traders to calculate appropriate position sizes directly on the chart, based on a key rule:
“What percentage of your capital are you willing to risk per trade?”
While many traders focus on entries and indicators, position sizing and risk allocation are often overlooked.
This tool visualizes and simplifies the “1% risk rule” promoted by IBD (Investor’s Business Daily) and William J. O’Neil, helping both beginners and experienced traders maintain disciplined capital management.
Key Features
Automatically calculates and displays:
・ Position Size
The number of units (shares, contracts, coins) you can hold based on your stop-loss range and risk allowance.
・ Stop Price
The price level at which your stop-loss would be triggered.
・ Risk Amount
The maximum loss per trade based on your portfolio size and risk percentage.
Two stop-loss modes available:
・ Fixed % Mode
O’Neil suggests using up to 8% stop-loss in uptrends and keeping it tighter (around 4%) in corrections. This mode allows flexible manual settings.
・ ATR-Based Mode
Uses the asset’s average volatility to dynamically calculate stop-loss width using the Average True Range (ATR).
ATR Usage and Recommended Settings
ATR helps you avoid noise-based stop-outs and align your risk with market volatility.
There are two parameters you can adjust:
・ ATR Length
Defines how many bars are used to calculate the average range.
・Shorter values (5–10) respond faster for day trades
・Longer values (14–21) offer smoother ranges for swing/position trades(Default is 14)
・ATR Multiplier
Sets how wide the stop-loss is by multiplying the ATR value:
・Day trading: 1.0–1.5×
・Swing trading: 1.5–2.5×
・Position trading: 2.0–3.0×
Practical Examples: Risk % × Stop-Loss % → Max Positions
This tool helps estimate how many positions you can hold in a portfolio based on your risk per trade and stop width.
Examples:
・Risk 0.5%, Stop 8% → Max 16 positions
・Risk 0.5%, Stop 4% → Max 8 positions
・Risk 1.0%, Stop 8% → Max 8 positions
・Risk 1.0%, Stop 4% → Max 4 positions
・Risk 2.0%, Stop 8% → Max 4 positions
・Risk 2.0%, Stop 4% → Max 2 positions
These assume worst-case scenarios where all positions are stopped out simultaneously within your overall portfolio risk limit.
Display & Customization Options
・ Currency Display: USD or JPY
No currency conversion is applied. Select based on your trading region (e.g., USD for U.S. stocks, JPY for Japanese stocks).
Support for additional currencies can be added upon request.
・ Show/Hide Decimal Places
Toggle decimals for better visibility. Ideal for fractional assets like crypto and CFDs.
・ Position of Output
Choose from top-right, middle-right, or bottom-right on the chart.
・ Text Display Size: Large / Normal / Small
Choose the table size that best suits your viewing preferences.
・ Explanation of Displayed Labels
・ Position Size : Units to buy/sell based on risk
・ Stop Price : Price where stop-loss is triggered
・ Risk Amount : Max loss allowed for the trade
How to Use
１、Set your Portfolio Size
２、Choose your Currency (USD or JPY)
３、Input Risk per Trade (%) (e.g., 1%)
４、Select Stop Loss Method
・ Fixed % : Enter a manual stop-loss percent (e.g., 8%)
・ ATR : Then also enter:
・ ATR Length : Number of bars used to calculate ATR (e.g., 14)
・ ATR Multiplier : Factor applied to ATR to determine stop-loss (e.g., 2.0)
５、Adjust decimals, label position, or text size as needed
６、The result is displayed in a table directly on your chart
Notes
・ Uses the current close price (close) as the basis
Real-time bid/ask data isn't available in Pine Script, so the close price is used for consistent results.
・ No buy/sell signals are generated
This tool is for position sizing and risk calculation only, not trade entries.
Recommended For
・Traders who want precise, rule-based position sizing
・Users following IBD or O’Neil’s 1% risk principle
・Those incorporating ATR for stop-loss strategies
・Multi-asset traders (stocks, crypto, CFDs, etc.)
・ Anyone who wants to calculate position size and risk without using a calculator or external tool—fully inside TradingView
