ILM COT Financials PlotUse this indicator on Daily Timeframe
Please refer to the below link for CFTC Financials
www.cftc.gov
This script is very similar to COT Financial Table indicator except that it plots the data (Longs - Shorts) instead of showing in a table.
Cari dalam skrip untuk " TABLE"
LazyScalp BoardThis indicator allows you to quickly view all important parameters in the table.
The table consists of a daily volume indicator, an average volume for a certain period, a volatility indicator (normalized ATR) and a correlation coefficient.
All parameters can be flexibly customized. You can also customize the table display, styles, and more.
This indicator is primarily useful for intraday traders and scalpers to quickly select an instrument to trade.
Position Size Calc. (Minimalist)This is a simplified position size calculator in the form of a table.
The reason I published this script is because all other position size calculator scripts try to provide way too much when it should be much simpler, position in strange areas of the chart and leave unwanted chart pollution.
This is a bare-bones functional table that takes your risk level, entry, stop and take profit as inputs, and calculates your loss, profit and required position size for your chosen risk level as a result.
Inspired by a table type position size calculator made by DojiEmoji design/color-wise. Functionally different however.
I hope you find this script useful and include it on your trading journey.
Everything Bitcoin [Kioseff Trading]Hello!
This script retrieves most of the available Bitcoin data published by Quandl; the script utilizes the new request.security_lower_tf() function.
Included statistics,
True price
Volume
Difficulty
My Wallet # Of Users
Average Block Size
api.blockchain size
Median Transaction Confirmation Time
Miners' Revenue
Hash Rate
Cost Per Transaction
Cost % of Transaction Volume
Estimated Transaction Volume USD
Total Output Volume
Number Of Transactions Per Block
# of Unique BTC Addresses
# of BTC Transactions Excluding Popular Addresses
Total Number of Transactions
Daily # of Transactions
Total Transaction Fees USD
Market Cap
Total BTC
Retrieved data can be plotted as line graphs; however, the data is initially split between two tables.
The image above shows how the requested Bitcoin data is displayed.
However, in the user inputs tab, you can modify how the data is displayed.
For instance, you can append the data displayed in the floating statistics box to the stagnant statistics box.
The image above exemplifies the instance.
You can hide any and all data via the user inputs tab.
In addition to data publishing, the script retrieves lower timeframe price/volume/indicator data, to which the values of the requested data are appended to center-right table.
The image above shows the script retrieving one-minute bar data.
Up arrows reflect an increase in the more recent value, relative to the immediately preceding value.
Down arrows reflect a decrease in the more recent value relative to the immediately preceding value.
The ascending minute column reflects the number of minutes/hours (ago) the displayed value occurred.
For instance, 15 minutes means the displayed value occurred 15 minutes prior to the current time (value).
Volume, price, and indicator data can be retrieved on lower timeframe charts ranging from 1 minute to 1440 minutes.
The image above shows retrieved 5-minute volume data.
Several built-in indicators are included, to which lower timeframe values can be retrieved.
The image above shows LTF VWAP data. Also distinguished are increases/decreases for sequential values.
The image above shows a dynamic regression channel. The channel terminates and resets each fiscal quarter. Previous channels remain on the chart.
Lastly, you can plot any of the requested data.
The new request.security_lower_tf() function is immensely advantageous - be sure to try it in your scripts!
Volatility Percentile🎲 Volatility is an important measure to be included in trading plan and strategy. Strategies have varied outcome based on volatility of the instruments in hand.
For example,
🚩 Trend following strategies work better on low volatility instruments and reversal patterns work better in high volatility instruments. It is also important for us to understand the median volatility of an instrument before applying particular strategy strategy on them.
🚩 Different instrument will have different volatility range. For instance crypto currencies have higher volatility whereas major currency pairs have lower volatility with respect to their price. It is also important for us to understand if the current volatility of the instrument is relatively higher or lower based on the historical values.
This indicator is created to study and understand more about volatility of the instruments.
⬜ Process
▶ Volatility metric used here is ATR as percentage of price. Other things such as bollinger bandwidth etc can also be used with few changes.
▶ We use array based counters to count ATR values in different range. For example, if we are measuring ATR range based on precision 2, we will use array containing 10000 values all initially set to 0 which act as 10000 buckets to hold counters of different range. But, based on the ATR percentage range, they will be incremented. Let's say, if atr percent is 2, then 200th element of the array is increased by 1.
▶ When we do this for every bar, we have array of counters which has the division on how many bars had what range of atr percent.
▶ Using this array, we can calculate how many bars had atr percent more than current value, how many had less than current value, and how many bars in history has same atr percent as current value.
▶ With these information, we can calculate the percentile of atr percentage value. We can also plot a detailed table mentioning what percentile each range map to.
⬜ Settings
▶ ATR Parameters - this include Moving average type and Length for atr calculation.
▶ Rounding type refers to rounding ATR percentage value before we put into certain bucket. For example, if ATR percentage 2.7, round or ceil will make it 3, whereas floor will make it 2 which may fall into different buckets based on the precision selected.
▶ Precision refers to how much detailed the range should be. If precision set to 0, then we get array of 100 to collect the range where each value will represent a range of 1%. Similarly precision of 1 will lead to array of 1000 with each item representing range of 0.1. Default value used is 2 which is also the max precision possible in this script. This means, we use array of 10000 to track the range and percentile of the ATR.
▶ Display Settings - Inverse when applied track percentile with respect to lowest value of ATR instead of high. By default this is set to false. Other two options allow users to enable stats table. When detailed stats are enabled, ATR Percentile as plot is hidden.
▶ Table Settings - Allows users to select set size and coloring options.
▶ Indicator Time Window - Allow users to select particular timeframe instead of all available bars to run the study. By default windows are disabled. Users can chose start and end time individually.
Indicator display components can be described as below:
Zigzag Trend/Divergence DetectorPullbacks are always hardest part of the trade and when it happen, we struggle to make decision on whether to continue the trade and wait for recovery or cut losses. Similarly, when an instrument is trending well, it is often difficult decision to make if we want to take some profit off the table. This indicator is aimed to make these decisions easier by providing a combined opinion of sentiment based on trend and possible divergence.
⬜ Process
▶ Use any indicator to find trend bias. Here we are using simple supertrend
▶ Use any oscillator. I have added few inbuilt oscillators as option. Default used is RSI.
▶ Find divergence by using zigzag to detect pivot high/low of price and observing indicator movement difference between subsequent pivots in the same direction.
▶ Combine divregence type, divergence bias and trend bias to derive overall sentiment.
Complete details of all the possible combinations are present here along with table legend
⬜Chart Legend
C - Continuation
D - Divergence
H - Hidden Divergence
I - Indeterminate
⬜ Settings
▶ Zigzag parameters : These let you chose zigzag properties. If you check "Use confirmed pivots", then unconfirmed pivot will be ignored in the table and in the chart
▶ Oscillator parameters : Lets you select different oscillators and settings. Available oscillators involve
CCI - Commodity Channel Index
CMO - Chande Momentum Oscillator
COG - Center Of Gravity
DMI - Directional Movement Index (Only ADX is used here)
MACD - Moving average convergence divergence (Can chose either histogram or MACD line)
MFI - Money Flow Index
MOM - Momentum oscillator
ROC - Rate Of Change
RSI - Relative Strength Index
TSI - Total Strength Index
WPR - William Percent R
BB - Bollinger Percent B
KC - Keltner Channel Percent K
DC - Donchian Channel Percent D
ADC - Adoptive Donchian Channel Percent D ( Adoptive-Donchian-Channel )
▶ Trend bias : Supertrend is used for trend bias. Coloring option color candles in the direction of supertrend. More option for trend bias can be added in future.
▶ Stats : Enables you to display history in tabular format.
Overview of settings present here:
⬜ Notes
Trend detection is done only with respect to previous pivot in the same direction. Hence, if chart has too many zigzags in short period, try increasing the zigzag length or chart timeframe. Similarly, if there is a steep trend, use lower timeframe charts to dig further.
Oscillators does not always make pivots at same bar as price. Due to this some the divergence calculation may not be correct. Hence visual inspection is always recommended.
⬜ Possible future enhancements
More options for trend bias
Enhance divergence calculation. Possible options include using oscillator based zigzag as primary or using close prices based zigzag instead of high/low.
Multi level zigzag option - Can be messy to include more than one zigzag. Option can be added to chose either Level1 or Level2 zigzags.
Alerts - Alerts can only be added for confirmed pivots - otherwise it will generate too many unwanted alerts. Will think about it :)
If I get time, I will try to make a video.
ST -Dashboard Volume MTF , [Sese04]User Guide: ST - Dashboard Volume MTF
Introduction
This script displays a multi-timeframe (MTF) volume dashboard, tracking buy and sell volumes and the moving averages of volume. It is designed for traders using ICT (Inner Circle Trader) and SMC (Smart Money Concepts) to quickly visualize market dynamics across multiple timeframes.
Settings and Features
📌 User Inputs
Customizable settings allow traders to adjust the dashboard display and volume moving averages.
Volume Display per Timeframe
show_vol_1m: Show volume for 1-minute chart.
show_vol_5m: Show volume for 5-minute chart.
show_vol_15m: Show volume for 15-minute chart.
show_vol_1h: Show volume for 1-hour chart.
show_vol_4h: Show volume for 4-hour chart.
show_vol_1d: Show volume for 1-day chart.
Volume Moving Average Settings
ma_length_short: Length of the short-term moving average (default 5 periods).
ma_length_long: Length of the long-term moving average (default 14 periods).
Dashboard Customization
dashboard_position: Dashboard position (Bottom Right, Bottom Left, Top Right, Top Left).
text_color: Text color for the dashboard.
text_size: Text size (small, normal, large).
How the Script Works
🔹 1. Calculating Buy and Sell Volume
The calculate_buy_sell function separates buy and sell volume based on the candle's open and close price:
If the closing price is higher than the opening price → Buy volume 📈.
If the closing price is lower or equal to the opening price → Sell volume 📉.
🔹 2. Retrieving Volume Data Across Multiple Timeframes
The function get_volumes collects buy and sell volume data for different timeframes using request.security().
The available timeframes are: 1m, 5m, 15m, 1h, 4h, and 1d.
🔹 3. Calculating Volume Moving Averages
The script uses ta.sma() to compute moving averages for volume trends:
ma_vol_short: Short-term moving average (e.g., 5 periods).
ma_vol_long: Long-term moving average (e.g., 14 periods).
🔹 4. Creating and Displaying the Dashboard
A table (table.new()) is generated at the last bar (barstate.islast) to display the volume data:
A title “📊 Volume Dashboard (Buy vs Sell)” in purple.
Column headers:
TIMEFRAME (e.g., 1M, 5M, 15M, 1H, 4H, 1D).
BUY VOLUME (dark blue).
SELL VOLUME (dark red).
Buy and Sell Volume values are displayed in their respective cells for easy reading.
How to Use This Script on TradingView?
Adding the Script
Open TradingView.
Go to Pine Editor and paste the script.
Click "Add to Chart".
Configuring the Settings
Open the indicator settings.
Enable/disable the desired timeframes.
Adjust the moving average lengths if necessary.
Interpreting the Data
Increasing buy volume across timeframes may indicate bullish momentum.
Rising sell volume suggests a bearish reversal.
Crossovers of volume moving averages can help detect market shifts.
Conclusion
This script is a powerful tool for analyzing volume dynamics across multiple timeframes. It provides a quick overview of the balance between buyers and sellers, essential for ICT scalping and liquidity-based trading.
🚀 Pro Tip: Combine this dashboard with other SMC indicators (engulfing candles, pivot points) to refine your trading decisions.
Micha Stocks Custom WatermarkThis Pine Script v5 indicator adds a customizable watermark to TradingView charts, displaying key stock information while allowing for flexible positioning and formatting.
📌 Features & Functionality:
✅ Custom Positioning:
• Fixed to the top-left corner.
• Adjustable spacing ensures the text is properly aligned.
✅ Displayed Information (Configurable):
• Company Name & Market Cap (Optional: Shows dynamically calculated market cap)
• Stock Ticker & Timeframe
• Industry & Sector
✅ Customization Options:
• Font Size: Huge, Large, Normal, Small
• Text Color & Transparency: Adjustable
• Proper Left Alignment for a clean, structured display
• Vertical Offset Tweaks to move text down for better visibility
✅ Optimized Table Layout:
• Uses table.new() for persistent placement.
• Added an empty row to fine-tune positioning, ensuring the watermark doesn’t overlap key chart areas.
🔧 Use Case:
Designed for traders who want a clear, customizable stock watermark to enhance their charting experience without obstructing price action.
GDCA ScreenerThis is upgrated system for Screener to DCA from "Grospector DCA V.3".
This has 5 zone Extreme high , high , normal , low , Extreme low. You can dynamic set min - max percent every zone.
Extreme zone is derivative short and long which It change Extreme zone to Normal zone all position will be closed.
Every Zone is splitted 10 channel. and this strategy calculate contribution.
and now can predict price in future.
Price Type: Allows the user to select the price type (open, high, low, close) for calculations.
ALL SET
Length MA for normal zone: The length of the moving average used in the normal zone.
Length for strong zone: The length of the moving average used in the strong zone, which is averaged from the normal zone moving average.
Multiple for Short: The multiplication factor applied to determine the threshold for the short zone.
Multiple for Strong Sell: The multiplication factor applied to determine the threshold for the strong sell zone.
Multiple for Sell Zone: The multiplication factor applied to determine the threshold for the sell zone.
Multiple for Buy Zone: The multiplication factor applied to determine the threshold for the buy zone.
Multiple for Strong Buy: The multiplication factor applied to determine the threshold for the strong buy zone.
Multiple for Long: The multiplication factor applied to determine the threshold for the long zone.
ZONE
Start Short Zone %: The start percentage of the short zone.
End Short Zone %: The end percentage of the short zone.
Start Sell Zone %: The start percentage of the sell zone.
End Sell Zone %: The end percentage of the sell zone.
Start Normal Zone %: The start percentage of the normal zone.
End Normal Zone %: The end percentage of the normal zone.
Start Buy Zone %: The start percentage of the buy zone.
End Buy Zone %: The end percentage of the buy zone.
Start Long Zone %: The start percentage of the long zone.
End Long Zone %: The end percentage of the long zone.
DISPLAY
Show Price: Controls the visibility of the price column in the display table.
Show Mode: Controls the visibility of the mode column in the display table.
Show GDCA: Controls the visibility of the GDCA column in the display table.
Show %: Controls the visibility of the percentage column in the display table.
Show Short: Controls the visibility of the short column in the display table.
Show Strong Sell: Controls the visibility of the strong sell column in the display table.
Show Sell: Controls the visibility of the sell column in the display table.
Show Buy: Controls the visibility of the buy column in the display table.
Show Strong Buy: Controls the visibility of the strong buy column in the display table.
Show Long: Controls the visibility of the long column in the display table.
Show Suggestion Trend: Controls the visibility of the suggestion trend column in the display table.
Show Manual Custom Code: Controls the visibility of the manual custom code column in the display table.
Show Dynamic Trend: Controls the visibility of the dynamic trend column in the display table.
Symbols: Boolean parameters that control the visibility of individual symbols in the display table.
Mode: Integer parameters that determine the mode for each symbol, specifying different settings or trends.
My mindset has been customed = AAPL , MSFT
To effectively make the DCA plan, I recommend adopting a comprehensive strategy that takes into consideration your mindset as the best indicator of the optimal approach. By leveraging your mindset, the task can be made more manageable and adaptable to any market
Dollar-cost averaging (DCA) is a suitable investment strategy for sound money and growth assets which It is Bitcoin, as it allows for consistent and disciplined investment over time, minimizing the impact of market volatility and potential risks associated with market timing
Double Stochastic & RSI Signals (Custom by TitikSona)This custom TradingView indicator combines two Stochastic oscillators with RSI to generate clear Buy and Sell signals on the chart. It is designed for traders who want a multi-timeframe confirmation using momentum and overbought/oversold conditions.
Features:
Dual Stochastic Oscillators: Two independent Stochastics (%K and %D) with customizable periods for flexible analysis.
RSI Filter: Confirms signals by checking if RSI is within a defined range.
Buy & Sell Signals:
Green triangle under the bar indicates a Buy signal.
Red triangle above the bar indicates a Sell signal.
Chart Labels: Displays indicator values (%K, %D, RSI) directly on the chart when signals appear.
Info Table: Shows real-time indicator values, signal status, market condition (Overbought/Oversold/Normal), and price.
Alerts: Set alerts for Buy and Sell signals directly from the indicator.
Inputs:
K & D periods and slowing for both Stochastics
RSI period and upper/lower levels
Usage:
Buy when both Stochastics are oversold and RSI is within the defined range.
Sell when both Stochastics are overbought and RSI is within the defined range.
Wait when conditions are not met.
Ideal for scalping, swing trading, day trading, and momentum strategies.
Global Risk Terminal – Multi-Asset Macro Sentiment IndicatorDescription:
The Global Risk Terminal is a sophisticated macro sentiment indicator that synthesizes signals from three key cross-asset relationships to produce a single, actionable risk appetite score. It is designed to help traders and investors identify whether global markets are in a risk-on (growth-seeking) or risk-off (defensive) regime. The indicator analyzes the behavior of commodities, equities, bonds, and currencies to generate a comprehensive view of market conditions.
Indicator Output:
The Global Risk Terminal produces a normalized risk score ranging from -1 to +1:
Positive values indicate risk-on conditions (growth assets favored)
Negative values indicate risk-off conditions (safe-haven assets favored)
Core Components:
Growth Pulse (Copper to Gold Ratio, HG/GC)
Purpose: Measures investor preference for industrial growth versus safe-haven assets.
Interpretation:
Rising ratio → Copper outperforming gold → Risk-on environment
Falling ratio → Gold outperforming copper → Risk-off environment
Flat ratio → Transitional market phase
Technical Implementation: Dual moving average slope method (fast MA default 20, slow MA default 40). Positive slope = +1, negative slope = -1, flat slope = 0
Equity Rotation (Russell 2000 to S&P 500 Ratio, RTY/ES)
Purpose: Tracks rotation between small-cap and large-cap equities, revealing market risk appetite.
Interpretation:
Rising ratio → Small-caps outperforming → Strong risk-on
Falling ratio → Large-caps outperforming → Defensive positioning
Technical Implementation: Dual moving average slope method (same as Growth Pulse)
Flow Gauge (10-Year Treasury to US Dollar Index, ZN/DXY)
Purpose: Captures liquidity conditions and cross-asset capital flows.
Interpretation:
Rising ratio → Treasury prices rising or USD weakening → Liquidity expansion, risk-on environment
Falling ratio → Treasury prices falling or USD strengthening → Liquidity contraction, risk-off environment
Technical Implementation: Dual moving average slope method
Composite Risk Score Calculation:
Analyze each component for trend using dual moving averages
Assign signal values: +1 (risk-on), -1 (risk-off), 0 (neutral)
Average the three signals:
Risk Score = (Growth Pulse + Equity Rotation + Flow Gauge) / 3
Optional smoothing with exponential moving average (default 3 periods) to reduce noise
Interpreting the Risk Score:
+0.66 to +1.0: Full risk-on – favor cyclical sectors, small-caps, growth strategies
+0.33 to +0.66: Moderate risk-on – mostly bullish environment, watch for fading momentum
-0.33 to +0.33: Neutral/transition – markets in flux, signals mixed, exercise caution
-0.66 to -0.33: Cautious risk-off – favor defensive sectors, reduce high-beta exposure
-1.0 to -0.66: Full risk-off – strong defensive positioning, prioritize safe-haven assets
How to Use the Global Risk Terminal to Frame Trades:
Aligning Trades with Market Regime
Risk-On (+0.33 and above): Look for buying opportunities in cyclical stocks, high-beta equities, commodities, and emerging markets. Use long entries for swing trades or intraday positions, following confirmed price action.
Risk-Off (-0.33 and below): Shift focus to defensive sectors, large-cap quality stocks, U.S. Treasuries, and safe-haven currencies. Prefer short entries or reduced exposure in risky assets.
Entry and Exit Framing
Use the risk score as a macro filter before executing trades:
Example: The risk score is +0.7 (strong risk-on). Prefer long positions in equities or commodities that are showing bullish confirmation on your regular chart.
Conversely, if the risk score is -0.7 (strong risk-off), avoid aggressive longs and consider short or defensive trades.
Watch for threshold crossings (+/-0.33, +/-0.66) as potential inflection points for adjusting position size, stop-loss levels, or sector rotation.
Confirming Trade Decisions
Combine the Global Risk Terminal with price action, volume, and trend indicators:
If equities rally but the risk score is declining, this may indicate a fragile rally driven by few leaders—trade cautiously.
If equities fall but the risk score is rising, consider counter-trend entries or buying dips.
Risk Management and Position Sizing
Strong alignment across components → increase position size and hold with wider stops
Mixed or neutral signals → reduce exposure, tighten stops, or avoid new trades
Defensive regimes → rotate into stable, low-volatility assets and increase cash buffer
Framing Trades Across Timeframes
Use the indicator as a strategic guide rather than a precise timing tool. Even without the MTF table:
Daily trend alignment → Guide swing trade bias
Shorter timeframe price action → Refine entry points and stop placement
Example: Daily chart shows +0.6 risk score → identify high-probability long setups using intraday technical patterns (breakouts, trend continuation).
Sector and Asset Rotation
Risk-On: Focus on cyclical sectors (financials, industrials, materials, energy), small-caps, high-beta instruments
Risk-Off: Focus on defensive sectors (utilities, consumer staples, healthcare), large-caps, safe-haven instruments
Alert Integration
Set alerts on the risk score to notify you when markets move from neutral to risk-on or risk-off regimes. Use these alerts to plan entries, exits, or portfolio adjustments in advance.
Customization Options:
Moving Average Length (5–100): Adjust sensitivity of trend detection
Score Smoothing (1–10): Reduce noise or see raw risk score
Visual Themes: Six preset themes (Cyber, Ocean, Sunset, Monochrome, Matrix, Custom)
Display Options: Show or hide component dashboards, main header, risk level lines, gradient fill, and component signals
Label Size: Tiny, Small, Normal, Large
Alert Conditions:
Risk score crosses above +0.66 → Strong risk-on
Risk score crosses below -0.66 → Strong risk-off
Risk score crosses zero → Neutral line
Risk score crosses above +0.33 → Moderate risk-on
Risk score crosses below -0.33 → Moderate risk-off
Data Sources:
HG1! – Copper Futures (COMEX)
GC1! – Gold Futures (COMEX)
RTY1! – Russell 2000 E-mini Futures (CME)
ES1! – S&P 500 E-mini Futures (CME)
ZN1! – 10-Year U.S. Treasury Note Futures (CBOT)
DXY – U.S. Dollar Index (ICE)
Notes and Limitations:
Works best during clear macro regimes and aligned trends
Use with price action, volume, and other technical tools
Not a standalone trading system; serves as a macro context filter
Equal weighting assumes all three components are equally important, but market conditions may vary
Past performance does not guarantee future results
Conclusion:
The Global Risk Terminal consolidates complex cross-asset signals into a simple, actionable score that informs market regime, portfolio positioning, sector rotation, and trading decisions. Its user-friendly layout and extensive customization options make it suitable for traders of all experience levels seeking macro-driven insights. By framing trades around risk score thresholds and combining macro context with tactical execution, traders can identify higher-probability opportunities and optimize position sizing, entries, and exits across a wide range of market conditions.
⚡ QUANTUM MOMENTUM ⚡Overview
Quantum Momentum is a sophisticated technical analysis tool designed to help traders identify relative strength between assets through advanced momentum comparison. This cyberpunk-themed indicator visualizes momentum dynamics between your current trading symbol and any comparison asset of your choice, making it ideal for pairs trading, crypto correlation analysis, and multi-asset portfolio management.
Key Features
📊 Multi-Asset Momentum Comparison
Dual Symbol Analysis: Compare momentum between your chart symbol and any other tradable asset
Real-Time Tracking: Monitor relative momentum strength as market conditions evolve
Difference Visualization: Clear histogram display showing which asset has stronger momentum
🎯 Multiple Momentum Calculation Methods
Choose from four different momentum calculation types:
ROC (Rate of Change): Traditional percentage-based momentum measurement
RSI (Relative Strength Index): Oscillator-based momentum from 0-100 range
Percent Change: Simple percentage change over the lookback period
Raw Change: Absolute price change in native currency units
📈 Advanced Trend Filtering System
Enable optional trend filters to align momentum signals with prevailing market direction:
SMA (Simple Moving Average): Classic trend identification
EMA (Exponential Moving Average): Responsive trend detection
Price Action: Identifies trends through higher highs/lows or lower highs/lows patterns
ADX (Average Directional Index): Measures trend strength with customizable threshold
🎨 Futuristic Cyberpunk Design
Neon Color Scheme: Eye-catching cyan, magenta, and matrix green color palette
Glowing Visual Effects: Enhanced visibility with luminescent plot lines
Dynamic Background Shading: Subtle trend state visualization
Real-Time Data Table: Sleek information panel displaying current momentum values and trend status
How It Works
The indicator calculates momentum for both your current chart symbol and a comparison symbol (default: BTC/USDT) using your selected method and lookback period. The difference between these momentum values reveals which asset is exhibiting stronger momentum at any given time.
Positive Difference (Green): Your chart symbol has stronger momentum than the comparison asset
Negative Difference (Pink/Red): The comparison asset has stronger momentum than your chart symbol
When the trend filter is enabled, the indicator will only display signals that align with the detected market trend, helping filter out counter-trend noise.
Settings Guide
Symbol Settings
Compare Symbol: Choose any tradable asset to compare against (e.g., major indices, cryptocurrencies, forex pairs)
Momentum Settings
Momentum Length: Lookback period for momentum calculations (default: 14 bars)
Momentum Type: Select your preferred momentum calculation method
Display Options
Toggle visibility of current symbol momentum line
Toggle visibility of comparison symbol momentum line
Toggle visibility of momentum difference histogram
Optional zero line reference
Trend Filter Settings
Use Trend Filter: Enable/disable trend-based signal filtering
Trend Method: Choose from SMA, EMA, Price Action, or ADX
Trend Length: Period for trend calculations (default: 50)
ADX Threshold: Minimum ADX value to confirm trend strength (default: 25)
Best Use Cases
✅ Pairs Trading: Identify divergences in momentum between correlated assets
✅ Crypto Market Analysis: Compare altcoin momentum against Bitcoin or Ethereum
✅ Stock Market Rotation: Track sector or index relative strength
✅ Forex Strength Analysis: Monitor currency pair momentum relationships
✅ Multi-Timeframe Confirmation: Use alongside other indicators for confluence
✅ Mean Reversion Strategies: Spot extreme momentum divergences for potential reversals
Visual Indicators
⚡ Cyan Line: Your chart symbol's momentum
⚡ Magenta Line: Comparison symbol's momentum
📊 Green/Pink Histogram: Momentum difference (positive = green, negative = pink)
▲ Green Triangle: Bullish trend detected (when filter enabled)
▼ Red Triangle: Bearish trend detected (when filter enabled)
◈ Yellow Diamond: Neutral/sideways trend (when filter enabled)
Pro Tips
💡 Look for crossovers between the momentum lines as potential trade signals
💡 Combine with volume analysis for stronger confirmation
💡 Use momentum divergence (price making new highs/lows while momentum doesn't) for reversal signals
💡 Enable trend filter during ranging markets to reduce false signals
💡 Experiment with different momentum types to find what works best for your trading style
Technical Requirements
TradingView Pine Script Version: v6
Chart Type: Works on all chart types
Indicator Placement: Separate pane (overlay=false)
Data Requirements: Needs access to comparison symbol data
Quarterly Earnings - v1This script shows company fundamentals in a TradingView table: Earnings Per Share (EPS), Price-to-Earnings Ratio (P/E, TTM), Sales (in Crores), Operating Margin (OPM %), Return on Assets (ROA %), and Return on Equity (ROE %).
Quarterly Earnings - v1This script shows company fundamentals in a TradingView table: Earnings Per Share (EPS), Price-to-Earnings Ratio (P/E, TTM), Sales (in Crores), Operating Margin (OPM %), Return on Assets (ROA %), and Return on Equity (ROE %).
Adaptive Machine Learning Trading System [PhenLabs]📊Adaptive ML Trading System
Version: PineScript™v6
📌Description
The Adaptive ML Trading System is a sophisticated machine learning indicator that combines ensemble modeling with advanced technical analysis. This system uses XGBoost, Random Forest, and Neural Network algorithms to generate high-confidence trading signals while incorporating robust risk management features. Traders benefit from objective, data-driven decision-making that adapts to changing market conditions.
🚀Points of Innovation
• Machine Learning Ensemble - Three integrated models (XGBoost, Random Forest, Neural Network)
• Confidence-Based Trading - Only executes trades when ML confidence exceeds threshold
• Dynamic Risk Management - ATR-based stop loss and max drawdown protection
• Adaptive Position Sizing - Volatility-adjusted position sizing with confidence weighting
• Real-Time Performance Metrics - Live tracking of win rate, Sharpe ratio, and performance
• Multi-Timeframe Feature Analysis - Adaptive lookback periods for different market regimes
🔧Core Components
• ML Ensemble Engine - Weighted combination of XGBoost, Random Forest, and Neural Network outputs
• Feature Normalization System - Advanced preprocessing with custom tanh/sigmoid activation
• Risk Management Module - Dynamic position sizing and drawdown protection
• Performance Dashboard - Real-time metrics and risk status monitoring
• Alert System - Comprehensive alert conditions for entries, exits, and risk events
🔥Key Features
• High-confidence ML signals with customizable confidence thresholds
• Multiple trading modes (Conservative, Balanced, Aggressive) for different risk profiles
• Integrated stop loss and risk management with ATR-based calculations
• Real-time performance metrics including win rate and Sharpe ratio
• Comprehensive alert system with entry, exit, and risk management notifications
• Visual confidence bands and threshold indicators for easy signal interpretation
🎨Visualization
• ML Signal Line - Primary signal output ranging from -1 to +1
• Confidence Bands - Visual representation of model confidence levels
• Threshold Lines - Customizable buy/sell threshold levels
• Position Histogram - Current market position visualization
• Performance Tables - Real-time metrics display in customizable positions
📖Usage Guidelines
Model Configuration
• Confidence Threshold: Default 0.55, Range 0.5-0.95 - Minimum confidence for signals
• Model Sensitivity: Default 0.9, Range 0.1-2.0 - Adjusts signal sensitivity
• Ensemble Mode: Conservative/Balanced/Aggressive - Trading style preference
• Signal Threshold: Default 0.55, Range 0.3-0.9 - ML signal threshold for entries
Risk Management
• Position Size %: Default 10%, Range 1-50% - Portfolio percentage per trade
• Max Drawdown %: Default 15%, Range 5-30% - Maximum allowed drawdown
• Stop Loss ATR: Default 2.0, Range 0.5-5.0 - Stop loss in ATR multiples
• Dynamic Sizing: Default true - Volatility-based position adjustment
Display Settings
• Show Signals: Default true - Display entry/exit signals
• Show Threshold Signals: Default true - Display ±0.6 threshold crosses
• Show Confidence Bands: Default true - Display ML confidence levels
• Performance Dashboard: Default true - Show metrics table
✅Best Use Cases
• Swing trading with 1-5 day holding periods
• Trend-following strategies in established trends
• Volatility breakout trading during high-confidence periods
• Risk-adjusted position sizing for portfolio management
• Multi-timeframe confirmation for existing strategies
⚠️Limitations
• Requires sufficient historical data for accurate ML predictions
• May experience low confidence periods in choppy markets
• Performance varies across different asset classes and timeframes
• Not suitable for very short-term scalping strategies
• Requires understanding of basic risk management principles
💡What Makes This Unique
• True machine learning ensemble with multiple model types
• Confidence-based trading rather than simple signal generation
• Integrated risk management with dynamic position sizing
• Real-time performance tracking and metrics
• Adaptive parameters that adjust to market conditions
🔬How It Works
Feature Calculation: Computes 20+ technical features from price/volume data
Feature Normalization: Applies custom normalization for ML compatibility
Ensemble Prediction: Combines XGBoost, Random Forest, and Neural Network outputs
Signal Generation: Produces confidence-weighted trading signals
Risk Management: Applies position sizing and stop loss rules
Execution: Generates alerts and visual signals based on thresholds
💡Note:
This indicator works best on daily and 4-hour timeframes for most assets. Ensure you understand the risk management settings before live trading. The system includes automatic risk-off modes that halt trading during excessive drawdown periods.
Midpoints Table:by AGRThis is midpoint indicator for 5m, 15m, 30m, 60m, Day and Week.
This is simple indicator for intraday use 5, 15 and 30m. unless 30m cross any side dont take trade on that side. Also read along with day and week midpoints
CCI PKTELUGUTRADERThe Commodity Channel Index (CCI) is a momentum oscillator that helps traders identify potential buy and sell opportunities by measuring how far the price of a security deviates from its average price over a specific period. It’s widely used for spotting new trends, overbought and oversold conditions, and possible price reversals in various financial markets.
Description of CCI
The CCI calculates the difference between the current price and its historical average price, normalized by mean deviation. Unlike indicators such as RSI, the CCI is an unbounded oscillator, meaning its values can go above +100 or below -100, providing broader insights into momentum shifts in prices.
The formula for CCI is:
CCI
=
Typical Price
−
SMA of Typical Price
0.015
×
Mean Deviation
CCI=
0.015×Mean Deviation
Typical Price−SMA of Typical Price
where:
Typical Price = (High + Low + Close) / 3
SMA is the Simple Moving Average of the Typical Price over the chosen period
Mean Deviation is the average deviation from the SMA.
Buy and Sell Signals
A buy signal is typically generated when the CCI moves above +100, indicating the start of a strong uptrend.
A sell signal occurs when the CCI drops below -100, signaling a strong downtrend.
Many traders close their buy positions when the CCI falls back below +100 and close their sell positions when it rises above -100, or use price action confirmation to validate signals.
Values above +100 suggest overbought conditions, while below -100 indicate oversold; extreme values (like +200 or -200) suggest even stronger momentum.
CCI divergences (price moves not confirmed by the indicator) may indicate potential reversals.
Summary Table: CCI Signals
CCI Level Market Condition Potential Action
Above +100 Overbought/Uptrend Consider Buying
Below -100 Oversold/Downtrend Consider Selling
Back between -100 and +100 Neutral/Indecision Exit or Wait
The CCI is best used alongside other technical indicators for confirmation, as it can generate false signals during sideways markets.
References:
Guide to Commodity Channel Index
What Is CCI?
CCI Trading Strategies
CCI: Technical Indicator
Commodity channel index
CMC Macro Regime PanelOverview (what it is):
A macro‑regime gate built entirely from TradingView-native symbols (CRYPTOCAP, FRED, DXY/VIX, HYG/LQD). It aggregates central‑bank liquidity (Fed balance sheet − RRP − Treasury General Account), USD strength, credit conditions, stablecoin flows/dominance, tech beta and BTC–NDX co‑move into one normalized score (CLRC). The panel outputs Risk‑ON/OFF regimes, an Early 3/5 pre‑signal, and an automatic BTC vs ETH vs ALTs preference. It is intentionally scoped to Daily & Weekly reads (no intraday timing). Publish with a clean chart and a clear description as per TradingView rules.
TradingView
Why we also use other TradingView screens (and why that is compliant)
This script pulls data via request.security() from official TV symbols only; users often want to open the raw series on separate charts to sanity‑check:
CRYPTOCAP indices: TOTAL, TOTAL2, TOTAL3 (market cap aggregates) and dominance tickers like BTC.D, USDT.D. Helpful for regime & rotation (ALTs vs BTC). TradingView provides definitions for crypto market cap and dominance symbols.
TradingView
+3
TradingView
+3
TradingView
+3
FRED releases: WALCL (Fed assets, weekly), RRPONTSYD (ON RRP, daily), WTREGEN (TGA, weekly), M2SL (M2, monthly). These are the official macro sources exposed on TV.
FRED
+3
FRED
+3
FRED
+3
Risk proxies: TVC:DXY (USD index), TVC:VIX (implied vol), AMEX:HYG/AMEX:LQD (credit), NASDAQ:NDX (tech beta), BINANCE:ETHBTC. VIX/NDX relationship is well-documented; VIX measures 30‑day expected S&P500 vol.
TradingView
+2
TradingView
+2
Compliance note: Using multiple screens is optional for users, but it explains/justifies how components work together (a requirement for public scripts). Keep publication chart clean; use extra screens only to illustrate in the description.
TradingView
How it works (high level)
Liquidity block (Weekly/Monthly)
Net Liquidity = WALCL − RRPONTSYD − WTREGEN (YoY z‑score). WALCL is weekly (as of Wednesday) via H.4.1; RRP is daily; TGA is a Fed liability series. M2 YoY is monthly.
FRED
+3
FRED
+3
FRED
+3
Risk conditions (Daily)
DXY 3‑month momentum (inverted), VIX level (inverted), Credit (HYG/LQD ratio or HY OAS). VIX is a 30‑day constant‑maturity implied vol index per Cboe methodology.
Cboe
+1
Crypto‑internal (Daily)
Stablecoins (USDT+USDC+DAI 30‑day log change), USDT dominance (20‑day, inverted), TOTAL3 (63‑day momentum). Dominance symbols on TV follow a documented formula.
TradingView
Beta & co‑move (Daily)
NDX 63‑day momentum, BTC↔NDX 90‑day correlation.
All components become z‑scores (optionally clipped), weighted, missing inputs drop and weights renormalize. We never use lookahead; we confirm on bar close to avoid repainting per Pine docs (barstate.isconfirmed, multi‑TF).
TradingView
+2
TradingView
+2
What you see on the chart
White line (CLRC) = macro regime score.
Background: Green = Risk‑ON, Red = Risk‑OFF, Teal = Early 3/5 (pre‑signal).
Table: shows each component’s z‑score and the Preference: BTC / ETH / ALTs / Mixed.
Signals & interpretation
Designed for Daily (1D) and Weekly (1W) only.
Regime gates (default Fast preset):
Enter ON: CLRC ≥ +0.8; Hold ON while ≥ +0.5.
Enter OFF: CLRC ≤ −1.0; Hold OFF while ≤ −0.5.
0 / ±1 reading: CLRC is a standardized composite.
~0 = neutral baseline (no macro edge).
≥ +1 = strong macro tailwind (≈ +1σ).
≤ −1 = strong headwind (≈ −1σ).
Early 3/5 (teal): a fast pre‑signal when at least 3 of 5 daily checks align: USDT.D↓, DXY↓, VIX↓, HYG/LQD↑, ETHBTC↑ or TOTAL3↑. It often precedes a full ON flip—use for pre‑positioning rather than full sizing.
BTC/ETH/ALTs selector (only when ON):
ALTs when BTC.D↓ and (ETHBTC↑ or TOTAL3↑) ⇒ rotate down the risk curve.
BTC when BTC.D↑ and ETHBTC↓ ⇒ keep it concentrated.
ETH when ETHBTC↑ while BTC.D flat/up ⇒ add ETH beta.
(Dominance mechanics are documented by TV.)
TradingView
Dissonance (incompatibility) rules — when to stand down
Use these overrides to avoid false comfort:
CLRC > +1 but USDT.D↑ and/or VIX spikes day‑over‑day → downgrade to Neutral; wait for USDT.D to stabilize and VIX to cool (VIX is a fear gauge of 30‑day expectation).
Cboe Global Markets
CLRC > +1 but DXY↑ sharply (USD squeeze) → size below normal; require DXY momentum to roll over.
CLRC < −1 but Early 3/5 = true two days in a row → start reducing underweights; look for ON flip within a few bars.
NetLiq improving (W) but credit (HYG/LQD) deteriorating (D) → treat as mixed regime; prefer BTC over ALTs.
How to use (step‑by‑step)
A. Read on Daily (1D) — main regime
Open CRYPTOCAP:TOTAL3, 1D (panel applied).
Wait for bar close (use alerts on confirmed bar). Pine docs recommend barstate.isconfirmed to avoid repainting on realtime bars.
TradingView
If ON, check Preference (BTC / ETH / ALTs).
Then drop to 4H on your trading pair for micro entries (this indicator itself is not for intraday timing).
B. Confirm weekly macro (1W) — once per week)
Review WALCL/RRP/TGA after the H.4.1 release on Thursdays ~4:30 pm ET. WALCL is “Weekly, as of Wednesday”; M2 is Monthly—so do not expect daily responsiveness from these.
Federal Reserve
+2
FRED
+2
Recommended check times (practical schedule)
Daily regime read: right after your chart’s daily close (confirmed bar). For consistent timing across crypto, many users set chart timezone to UTC and read ~00:05 UTC; you can change chart timezone in TV’s settings.
TradingView
In‑day monitoring: optional spot checks 16:00 & 20:00 UTC (DXY/VIX move during US hours), but act only after the daily bar confirms.
Weekly macro pass: Thu 21:30–22:30 UTC (after H.4.1 4:30 pm ET) or Fri after daily close, to let weekly FRED series propagate.
Federal Reserve
Limitations & data latency (be explicit)
Higher‑TF data & confirmation: FRED weekly/monthly series will not reflect intraday risk in crypto; we aggregate them for regime, not for entry timing.
Repainting 101: Realtime bars move until close. This script does not use lookahead and follows Pine guidance on multi‑TF series; still, always act on confirmed bars.
TradingView
+1
Public‑library compliance: Title EN‑only; description starts in EN; clean chart; justify component mash‑up; no lookahead; no unrealistic claims.
TradingView
Alerts you can use
“Macro Risk‑ON (entry)” — fires on ON flip (confirmed bar).
“Macro Risk‑OFF (entry)” — fires on OFF flip.
“Early 3/5” — fires when the teal pre‑signal appears (not a regime flip).
“Preference change” — BTC/ETH/ALTs toggles while ON.
Publish note: Alerts are fine; just avoid implying guaranteed accuracy/performance.
TradingView
Background research (why these inputs matter)
Liquidity → Crypto: Fed H.4.1 timing and series definitions (WALCL, RRP, TGA) formalize the “net liquidity” concept used here.
FRED
+3
Federal Reserve
+3
FRED
+3
Stablecoins ↔ Non‑stable crypto: empirical work shows bi‑directional causality between stablecoin market cap and non‑stable crypto cap; stablecoin growth co‑moves with broader crypto activity.
Global liquidity link: world liquidity positively relates to total crypto market cap; lagged effects are observed at monthly horizons.
VIX/Uncertainty effect: fear shocks impair BTC’s “safe haven” behavior; VIX is a meaningful risk‑off read.
Elliott Wave Auto (Impulse + Correction) — stable deleteAutomatic pivot detection: The script identifies swing highs and swing lows using ta.pivothigh and ta.pivotlow.
Impulse wave labeling (1–5):
Detects 5 alternating pivots and labels them as waves 1 to 5.
Uses green/red labels for impulse and correction legs.
Connects waves with blue lines for visual clarity.
Corrective wave labeling (A–B–C):
Detects the next 3 alternating pivots after wave 5.
Labels them as A, B, C with orange lines connecting them.
Dynamic cleanup:
Stores labels and lines in arrays.
Deletes previous drawings automatically before redrawing, keeping the chart clean.
Optional pivot markers:
Plots tiny triangles for detected pivots (green for lows, red for highs).
Information table:
Displays the direction (Bullish/Bearish) and percentage move of the 1–5 impulse waves.
Pine Script v5 compliant:
Uses str.tostring() and array-based deletion to avoid tostring() or line.deleteall() errors.
If you want, I can also add an alert feature to notify you when a full impulse + corrective wave pattern completes. This makes it actionable for trading.
EvoTrend-X Indicator — Evolutionary Trend Learner ExperimentalEvoTrend-X Indicator — Evolutionary Trend Learner
NOTE: This is an experimental Pine Script v6 port of a Python prototype. Pine wasn’t the original research language, so there may be small quirks—your feedback and bug reports are very welcome. The model is non-repainting, MTF-safe (lookahead_off + gaps_on), and features an adaptive (fitness-based) candidate selector, confidence gating, and a volatility filter.
⸻
What it is
EvoTrend-X is adaptive trend indicator that learns which moving-average length best fits the current market. It maintains a small “population” of fast EMA candidates, rewards those that align with price momentum, and continuously selects the best performer. Signals are gated by a multi-factor Confidence score (fitness, strength vs. ATR, MTF agreement) and a volatility filter (ATR%). You get a clean Fast/Slow pair (for the currently best candidate), optional HTF filter, a fitness ribbon for transparency, and a themed info panel with a one-glance STATUS readout.
Core outputs
• Selected Fast/Slow EMAs (auto-chosen from candidates via fitness learning)
• Spread cross (Fast – Slow) → visual BUY/SELL markers + alert hooks
• Confidence % (0–100): Fitness ⊕ Distance vs. ATR ⊕ MTF agreement
• Gates: Trend regime (Kaufman ER), Volatility (ATR%), MTF filter (optional)
• Candidate Fitness Ribbon: shows which lengths the learner currently prefers
• Export plot: hidden series “EvoTrend-X Export (spread)” for downstream use
⸻
Why it’s different
• Evolutionary learning (on-chart): Each candidate EMA length gets rewarded if its slope matches price change and penalized otherwise, with a gentle decay so the model forgets stale regimes. The best fitness wins the right to define the displayed Fast/Slow pair.
• Confidence gate: Signals don’t light up unless multiple conditions concur: learned fitness, spread strength vs. volatility, and (optionally) higher-timeframe trend.
• Volatility awareness: ATR% filter blocks low-energy environments that cause death-by-a-thousand-whipsaws. Your “why no signal?” answer is always visible in the STATUS.
• Preset discipline, Custom freedom: Presets set reasonable baselines for FX, equities, and crypto; Custom exposes all knobs and honors your inputs one-to-one.
• Non-repainting rigor: All MTF calls use lookahead_off + gaps_on. Decisions use confirmed bars. No forward refs. No conditional ta.* pitfalls.
⸻
Presets (and what they do)
• FX 1H (Conservative): Medium candidates, slightly higher MinConf, modest ATR% floor. Good for macro sessions and cleaner swings.
• FX 15m (Active): Shorter candidates, looser MinConf, higher ATR% floor. Designed for intraday velocity and decisive sessions.
• Equities 1D: Longer candidates, gentler volatility floor. Suits index/large-cap trend waves.
• Crypto 1H: Mid-short candidates, higher ATR% floor for 24/7 chop, stronger MinConf to avoid noise.
• Custom: Your inputs are used directly (no override). Ideal for systematic tuning or bespoke assets.
⸻
How the learning works (at a glance)
1. Candidates: A small set of fast EMA lengths (e.g., 8/12/16/20/26/34). Slow = Fast × multiplier (default ×2.0).
2. Reward/decay: If price change and the candidate’s Fast slope agree (both up or both down), its fitness increases; otherwise decreases. A decay constant slowly forgets the distant past.
3. Selection: The candidate with highest fitness defines the displayed Fast/Slow pair.
4. Signal engine: Crosses of the spread (Fast − Slow) across zero mark potential regime shifts. A Confidence score and gates decide whether to surface them.
⸻
Controls & what they mean
Learning / Regime
• Slow length = Fast ×: scales the Slow EMA relative to each Fast candidate. Larger multiplier = smoother regime detection, fewer whipsaws.
• ER length / threshold: Kaufman Efficiency Ratio; above threshold = “Trending” background.
• Learning step, Decay: Larger step reacts faster to new behavior; decay sets how quickly the past is forgotten.
Confidence / Volatility gate
• Min Confidence (%): Minimum score to show signals (and fire alerts). Raising it filters noise; lowering it increases frequency.
• ATR length: The ATR window for both the ATR% filter and strength normalization. Shorter = faster, but choppier.
• Min ATR% (percent): ATR as a percentage of price. If ATR% < Min ATR% → status shows BLOCK: low vola.
MTF Trend Filter
• Use HTF filter / Timeframe / Fast & Slow: HTF Fast>Slow for longs, Fast threshold; exit when spread flips or Confidence decays below your comfort zone.
2) FX index/majors, 15m (active intraday)
• Preset: FX 15m (Active).
• Gate: MinConf 60–70; Min ATR% 0.15–0.30.
• Flow: Focus on session opens (LDN/NY). The ribbon should heat up on shorter candidates before valid crosses appear—good early warning.
3) SPY / Index futures, 1D (positioning)
• Preset: Equities 1D.
• Gate: MinConf 55–65; Min ATR% 0.05–0.12.
• Flow: Use spread crosses as regime flags; add timing from price structure. For adds, wait for ER to remain trending across several bars.
4) BTCUSD, 1H (24/7)
• Preset: Crypto 1H.
• Gate: MinConf 70–80; Min ATR% 0.20–0.35.
• Flow: Crypto chops—volatility filter is your friend. When ribbon and HTF OK agree, favor continuation entries; otherwise stand down.
⸻
Reading the Info Panel (and fixing “no signals”)
The panel is your self-diagnostic:
• HTF OK? False means the higher-timeframe EMAs disagree with your intended side.
• Regime: If “Chop”, ER < threshold. Consider raising the threshold or waiting.
• Confidence: Heat-colored; if below MinConf, the gate blocks signals.
• ATR% vs. Min ATR%: If ATR% < Min ATR%, status shows BLOCK: low vola.
• STATUS (composite):
• BLOCK: low vola → increase Min ATR% down (i.e., allow lower vol) or wait for expansion.
• BLOCK: HTF filter → disable HTF or align with the HTF tide.
• BLOCK: confidence → lower MinConf slightly or wait for stronger alignment.
• OK → you’ll see markers on valid crosses.
⸻
Alerts
Two static alert hooks:
• BUY cross — spread crosses up and all gates (ER, Vol, MTF, Confidence) are open.
• SELL cross — mirror of the above.
Create them once from “Add Alert” → choose the condition by name.
⸻
Exporting to other scripts
In your other Pine indicators/strategies, add an input.source and select EvoTrend-X → “EvoTrend-X Export (spread)”. Common uses:
• Build a rule: only trade when exported spread > 0 (trend filter).
• Combine with your oscillator: oscillator oversold and spread > 0 → buy bias.
⸻
Best practices
• Let it learn: Keep Learning step moderate (0.4–0.6) and Decay close to 1.0 (e.g., 0.99–0.997) for smooth regime memory.
• Respect volatility: Tune Min ATR% by asset and timeframe. FX 1H ≈ 0.10–0.20; crypto 1H ≈ 0.20–0.35; equities 1D ≈ 0.05–0.12.
• MTF discipline: HTF filter removes lots of “almost” trades. If you prefer aggressive entries, turn it off and rely more on Confidence.
• Confidence as throttle:
• 40–60%: exploratory; expect more signals.
• 60–75%: balanced; good daily driver.
• 75–90%: selective; catch the clean stuff.
• 90–100%: only A-setups; patient mode.
• Watch the ribbon: When shorter candidates heat up before a cross, momentum is forming. If long candidates dominate, you’re in a slower trend cycle.
⸻
Non-repainting & safety notes
• All request.security() calls use lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_on.
• No forward references; decisions rely on confirmed bar data.
• EMA lengths are simple ints (no series-length errors).
• Confidence components are computed every bar (no conditional ta.* traps).
⸻
Limitations & tips
• Chop happens: ER helps, but sideways microstructure can still flicker—use Confidence + Vol filter as brakes.
• Presets ≠ oracle: They’re sensible baselines; always tune MinConf and Min ATR% to your venue and session.
• Theme “Auto”: Pine cannot read chart theme; “Auto” defaults to a Dark-friendly palette.
⸻
Publisher’s Screenshots Checklist
1) FX swing — EURUSD 1H
• Preset: FX 1H (Conservative)
• Params: MinConf=70, ATR Len=14, Min ATR%=0.12, MTF ON (TF=4H, 20/50)
• Show: Clear BUY cross, STATUS=OK, green regime background; Fitness Ribbon visible.
2) FX intraday — GBPUSD 15m
• Preset: FX 15m (Active)
• Params: MinConf=60, ATR Len=14, Min ATR%=0.20, MTF ON (TF=60m)
• Show: SELL cross near London session open. HTF lines enabled (translucent).
• Caption: “GBPUSD 15m • Active session sell with MTF alignment.”
3) Indices — SPY 1D
• Preset: Equities 1D
• Params: MinConf=60, ATR Len=14, Min ATR%=0.08, MTF ON (TF=1W, 20/50)
• Show: Longer trend run after BUY cross; regime shading shows persistence.
• Caption: “SPY 1D • Trend run after BUY cross; weekly filter aligned.”
4) Crypto — BINANCE:BTCUSDT 1H
• Preset: Crypto 1H
• Params: MinConf=75, ATR Len=14, Min ATR%=0.25, MTF ON (TF=4H)
• Show: BUY cross + quick follow-through; Ribbon warming (reds/yellows → greens).
• Caption: “BTCUSDT 1H • Momentum break with high confidence and ribbon turning.”
Smarter Money Concepts Dashboard [PhenLabs]📊Smarter Money Concepts Dashboard
Version: PineScript™v6
📌Description
The Smarter Money Concepts Dashboard is a comprehensive institutional trading analysis tool that combines six of our most powerful smarter money concepts indicators into one unified suite. This advanced system automatically detects and visualizes Fair Value Gaps, Inverted FVGs, Order Blocks, Wyckoff Springs/Upthrusts, Wick Rejection patterns, and ICT Market Structure analysis.
Built for serious traders who need institutional-grade market analysis, this dashboard eliminates subjective interpretation by automatically identifying where smart money is likely positioned. The integrated real-time dashboard provides instant status updates on all active patterns, making it easy to monitor market conditions at a glance.
🚀Points of Innovation
● Multi-Module Integration: Six different SMC concepts unified in one comprehensive system
● Real-Time Dashboard Display: Live tracking of all active patterns with customizable positioning
● Advanced Volume Filtering: Institutional volume confirmation across all pattern types
● Automated Pattern Management: Smart memory system prevents chart clutter while maintaining relevant zones
● Probability-Based Wyckoff Detection: Mathematical probability calculations for spring/upthrust patterns
● Dual FVG System: Both standard and inverted Fair Value Gap detection with equilibrium analysis
🔧Core Components
● Fair Value Gap Engine: Detects standard FVGs with volume confirmation and equilibrium line analysis
● Inverted FVG Module: Advanced IFVG detection using RVI momentum filtering for inversion confirmation
● Order Block System: Institutional order block identification with customizable mitigation methods
● Wyckoff Pattern Recognition: Automated spring and upthrust detection with probability scoring
● Wick Rejection Analysis: High-probability reversal patterns based on wick-to-body ratios
● ICT Market Structure: Simplified institutional concepts with commitment tracking
🔥Key Features
● Comprehensive Pattern Detection: All major SMC concepts in one indicator with automatic identification
● Volume-Confirmed Signals: Multiple volume filters ensure only institutional-grade patterns are highlighted
● Interactive Dashboard: Real-time status display with active pattern counts and module status
● Smart Memory Management: Automatic cleanup of old patterns while preserving relevant market zones
● Full Alert System: Complete notification coverage for all pattern types and signal generations
● Customizable Display Options: Adjustable colors, transparency, and positioning for all visual elements
🎨Visualization
● Color-Coded Zones: Distinct color schemes for bullish/bearish patterns across all modules
● Dynamic Box Extensions: Automatically extending zones until mitigation or invalidation
● Equilibrium Lines: Fair Value Gap midpoint analysis with dotted line visualization
● Signal Markers: Clear spring/upthrust signals with directional arrows and probability indicators
● Dashboard Table: Professional-grade status panel with module activation and pattern counts
● Candle Coloring: Wick rejection highlighting with transparency-based visual emphasis
📖Usage Guidelines
Fair Value Gap Settings
● Days to Analyze: Default 15, Range 1-100 - Controls historical FVG detection period
● Volume Filter: Enables institutional volume confirmation for gap validity
● Min Volume Ratio: Default 1.5 - Minimum volume spike required for gap recognition
● Show Equilibrium Lines: Displays FVG midpoint analysis for precise entry targeting
Order Block Configuration
● Scan Range: Default 25 bars - Lookback period for structure break identification
● Volume Filter: Institutional volume confirmation for order block validation
● Mitigation Method: Wick or Close-based invalidation for different trading styles
● Min Volume Ratio: Default 1.5 - Volume threshold for significant order block formation
Wyckoff Analysis Parameters
● S/R Lookback: Default 20 - Support/resistance calculation period for spring/upthrust detection
● Volume Spike Multiplier: Default 1.5 - Required volume increase for pattern confirmation
● Probability Threshold: Default 0.7 - Minimum probability score for signal generation
● ATR Recovery Period: Default 5 - Price recovery calculation for pattern strength assessment
Market Structure Settings
● Auto-Detect Zones: Automatic identification of high-volume thin zones
● Proximity Threshold: Default 0.20% - Price proximity requirements for zone interaction
● Test Window: Default 20 bars - Time period for zone commitment calculation
Display Customization
● Dashboard Position: Four corner options for optimal chart layout
● Text Size: Scalable from Tiny to Large for different screen configurations
● Pattern Colors: Full customization of all bullish and bearish zone colors
✅Best Use Cases
● Swing Trading: Identify major institutional zones for multi-day position entries
● Day Trading: Precise intraday entries at Fair Value Gaps and Order Block boundaries
● Trend Analysis: Market structure confirmation for directional bias establishment
● Risk Management: Clear invalidation levels provided by all pattern boundaries
● Multi-Timeframe Analysis: Works across all timeframes from 1-minute to monthly charts
⚠️Limitations
● Market Condition Dependency: Performance varies between trending and ranging market environments
● Volume Data Requirements: Requires accurate volume data for optimal pattern confirmation
● Lagging Nature: Some patterns confirmed after initial price movement has begun
● Pattern Density: High-volatility markets may generate excessive pattern signals
● Educational Tool: Requires understanding of smart money concepts for effective application
💡What Makes This Unique
● Complete SMC Integration: First indicator to combine all major smart money concepts comprehensively
● Real-Time Dashboard: Instant visual feedback on all active institutional patterns
● Advanced Volume Analysis: Multi-layered volume confirmation across all detection modules
● Probability-Based Signals: Mathematical approach to Wyckoff pattern recognition accuracy
● Professional Memory Management: Sophisticated pattern cleanup without losing market relevance
🔬How It Works
1. Pattern Detection Phase:
● Multi-timeframe scanning for institutional footprints across all enabled modules
● Volume analysis integration confirms patterns meet institutional trading criteria
● Real-time pattern validation ensures only high-probability setups are displayed
2. Signal Generation Process:
● Automated zone creation with precise boundary definitions for each pattern type
● Dynamic extension system maintains relevance until mitigation or invalidation occurs
● Alert system activation provides immediate notification of new pattern formations
3. Dashboard Update Cycle:
● Live status monitoring tracks all active patterns and module states continuously
● Pattern count updates provide instant feedback on current market condition density
● Commitment tracking for market structure analysis shows institutional engagement levels
💡Note:
This indicator represents institutional trading concepts and should be used as part of a comprehensive trading strategy. Pattern recognition accuracy improves with understanding of smart money principles. Combine with proper risk management and multiple confirmation methods for optimal results.
Stop Loss vs Take Profit Probability and EVThis stop loss and take profit calculator uses a Monte Carlo simulation to calculate the probability of hitting your Stop Loss or Take Profit levels across different time horizons (expressed in bars).
It provides data-driven insights to optimize your risk management and position sizing by showing Expected Value for each scenario.
As a quant, I love using statistical data to help my decisions and get better EV from my trades.
🔬 How It's Calculated
Monte Carlo Simulation: Runs 1,000-10,000 price simulations using a random walk model
Volatility Analysis: Combines ATR-based and Historical Volatility for accurate price movement modeling
Expected Value: Calculates profit/loss expectation using formula: (TP_Probability × Reward) - (SL_Probability × Risk)
Time Horizons: Tests multiple timeframes (1, 5, 10, 20, 50 bars) to find optimal holding periods
Risk/Reward Ratios: Automatically calculates and displays R:R ratios for quick assessment
💡 Use Cases
Position Sizing - Determine optimal risk per trade based on Expected Value
Time Horizon Optimization - Find the best holding period for your strategy
Stop Loss Placement - Validate SL levels using probability analysis
Take Profit Optimization - Set TP levels with statistical backing
Strategy Backtesting - Compare different R:R setups before entering trades
Risk Management - Avoid trades with negative Expected Value
Swing vs Day Trading - Choose timeframes with highest success probability
🎯 How to Use
Setup Trade: Enter your entry price, stop loss, and take profit levels
You can add or remove time horizons denominated in bars. Say you are looking at 1h candles, adding a 24-bar time horizon means you are looking into 24 hours
Choose Direction: Select Long or Short position
Review Table
Analyze Expected Value: Focus on positive EV scenarios (green background)
Optimize Timing: Select time horizons with best risk/reward profile
Adjust Parameters: Modify volatility calculation method and simulation count if needed
Examples
Here's how you can read the tables.
Example 1:
In this chart, we are analyzing the TP and SL probabilities as well as the EV (expected value) for a stock. I want to check what the likelihood is that my SL and TP get triggered over the next 5 days. The stock market is open for 6.5 hours per day, which is 13 bars in this 30-minute bar chart. 26 bars is 2 days, 39 bars is 3 days and so on.
Although this trade is more likely to trigger my SL than my TP, in some of the time horizons we have a positive expected value because of the risk/reward of our trade (i.e. distance of the SL and TP from the price) and the probability of hitting SL and TP.
Example 2:
In this example, we have applied the indicator to gold. Because the TP is much closer to the price, the probability of hitting the TP is much higher.
We can also observe that the expected Value in the shorter time frames is better than in the longer ones. This can give us some clues to set up our trade. If we know that the EV is positive, we can allocate more to that specific trade.
Enjoy, and please let me know your feedback! 😊🥂
Swing Oracle Stock// (\_/)
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📌 Swing Oracle Stock – Professional Cycle & Trend Detection Indicator
The Swing Oracle Stock is an advanced market analysis tool designed to highlight price cycles, trend shifts, and key trading zones with precision. It combines trendline dynamics, normalized oscillators, and multi-timeframe confirmation into a single comprehensive indicator.
🔑 Key Features
NDOS (Normalized Dynamic Oscillator System):
Measures price strength relative to recent highs and lows to detect overbought, neutral, and oversold zones.
Dynamic Trendline (EMA8 or SMA231):
Flexible source selection for adapting to different trading styles (scalping vs. swing).
Multi-Timeframe H1 Confirmation:
Adds higher-timeframe validation to improve signal reliability.
Automated Buy & Sell Signals:
Triggered only on significant crossovers above/below defined levels.
Weekly Cycles (7-day M5 projection):
Tracks recurring time-based market cycles to anticipate reversal points.
Intuitive Visualization:
Colored zones (high, low, neutral) for quick market context.
Optional background and candlestick coloring for better clarity.
Multi-Timeframe Cross Table:
Automatically compares SMA50 vs. EMA200 across multiple timeframes (1m → 4h), showing clear status:
⭐️⬆️ UP = bullish trend confirmation
💀⬇️ Drop = bearish trend confirmation
📊 Built-in Statistical Tools
Normalized difference between short and long EMA.
Projected normalized mean levels plotted directly on the main chart.
Dynamic analysis of price distance from SMA50 to capture market “waves.”
🎯 Use Cases
Spot trend reversals with multi-timeframe confirmation.
Identify powerful breakout and breakdown zones.
Time entries and exits based on trend + cycle confluence.
Enhance market timing for swing trades, scalps, or long-term positions.
⚡ Swing Oracle Stock brings together cycle detection, oscillator normalization, and multi-timeframe confirmation into one streamlined indicator for traders who want a professional edge.