Moving Average Pullback Signals [UAlgo]The "Moving Average Pullback Signals " indicator is designed to identify potential trend continuation or reversal points based on moving average (MA) pullback patterns. This tool combines multiple types of moving averages, customized trend validation parameters, and candlestick wick patterns to provide reliable buy and sell signals. By leveraging several advanced MA methods (such as TEMA, DEMA, ZLSMA, and McGinley-D), this script can adapt to different market conditions, providing traders with flexibility and more precise trend-based entries and exits. The addition of a gradient color-coded moving average line and wick validation logic enables traders to visualize market sentiment and trend strength dynamically.
๐ถ Key Features
Multiple Moving Average (MA) Calculation Methods: This indicator offers various MA calculation types, including SMA, EMA, DEMA, TEMA, ZLSMA, and McGinley-D, allowing traders to select the MA that best fits their strategy.
Trend Validation and Pattern Recognition: The indicator includes a customizable trend validation length, ensuring that the trend is consistent before buy/sell signals are generated. The "Trend Pattern Mode" setting provides flexibility between "No Trend in Progress," "Trend Continuation," and "Both," tailoring signals to the traderโs preferred style.
Wick Validation Logic: To enhance the accuracy of entries, this indicator identifies specific wick patterns for bullish or bearish pullbacks, which signal potential trend continuation or reversal. Wick length and validation factor are adjustable to suit various market conditions and timeframes.
Gradient Color-coded MA Line: This feature provides a quick visual cue for trend strength, with color changes reflecting relative highs and lows of the MA, enhancing market sentiment interpretation.
Alerts for Buy and Sell Signals: Alerts are triggered when either a bullish or bearish pullback is detected, allowing traders to receive instant notifications without continuously monitoring the chart.
Visual Labels for Reversal Points: The indicator plots labels ("R") at potential reversal points, with color-coded labels for bullish (green) and bearish (red) pullbacks, highlighting pullback opportunities that align with the trend or reversal potential.
๐ถ Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Cari dalam skrip untuk "Pattern recognition"
Daily Performance Analysis [Mr_Rakun]The Daily Performance Analysis indicator is a comprehensive trading performance tracker that analyzes your strategy's success rate and profitability across different days of the week and month. This powerful tool provides detailed statistics to help traders identify patterns in their trading performance and optimize their strategies accordingly.
Weekly Performance Analysis:
Tracks wins/losses for each day of the week (Monday through Sunday)
Calculates net profit/loss for each trading day
Shows profit factor (gross profit รท gross loss) for each day
Displays win rate percentage for each day
Monthly Performance Analysis:
Monitors performance for each day of the month (1-31)
Provides the same detailed metrics as weekly analysis
Helps identify monthly patterns and trends
Add to Your Strategy:
Copy the performance analysis code and integrate it into your existing Pine Script strategy
Optimize Strategy: Use insights to refine entry/exit timing or avoid trading on poor-performing days
Pattern Recognition: Identify which days of the week/month work best for your strategy
Risk Management: Avoid trading on historically poor-performing days
Strategy Optimization: Fine-tune your approach based on empirical data
Performance Tracking: Monitor long-term trends in your trading success
Data-Driven Decisions: Make informed adjustments to your trading schedule
Quad Rotation StochasticQuad Rotation Stochastic
The Quad Rotation Stochastic is a powerful and unique momentum oscillator that combines four different stochastic setups into one tool, providing an incredibly detailed view of market conditions. This multi-timeframe stochastic approach helps traders better anticipate trend continuations, reversals, and momentum shifts with greater precision than traditional single stochastic indicators.
Why this indicator is useful:
Multi-layered Momentum Analysis: Instead of relying on one stochastic, this script tracks four independent stochastic readings, smoothing out noise and confirming stronger signals.
Advanced Divergence Detection: It automatically identifies bullish and bearish divergences for each stochastic, helping traders spot potential reversals early.
Background Color Alerts: When a configurable number (e.g., 3 or 4) of the stochastics agree in direction and position (overbought/oversold), the background colors green (bullish) or red (bearish) to give instant visual cues.
ABCD Pattern Recognition: The script recognizes "shield" patterns when Stochastic 4 remains stuck at extreme levels (above 90 or below 10) for a set time, warning of potential trend continuation setups.
Super Signal Alerts: If all four stochastics align in extreme conditions and slope in the same direction, the indicator plots a special "Super Signal," offering high-confidence entry opportunities.
Why this indicator is unique:
Quad Confirmation Logic: Combining four different stochastics makes this tool much less prone to false signals compared to using a single stochastic.
Customizable Divergence Coloring: Traders can choose to have divergence lines automatically match the stochastic color for clear visual association.
Adaptive ABCD Shields: Innovative use of bar counting while a stochastic remains extreme acts as a "shield," offering a unique way to filter out minor fake-outs.
Flexible Configuration: Each stochastic's sensitivity, divergence settings, and visual styling can be fully customized, allowing traders to adapt it to their own strategy and asset.
Example Usage: Trading Bitcoin with Quad Rotation Stochastic
When trading Bitcoin (BTCUSD), you might set the minimum count (minCount) to 3, meaning three out of four stochastics must be in agreement to trigger a background color.
If the background turns green, and you notice an ABCD Bullish Shield (Green X), you might look for bullish candlestick patterns or moving average crossovers to enter a long trade.
Conversely, if the background turns red and a Super Down Signal appears, it suggests high probability for further downside, giving you strong confirmation to either short BTC or avoid entering new longs.
By combining divergence signals with background colors and the ABCD shields, the Quad Rotation Stochastic provides a layered confirmation system that gives traders greater confidence in their entries and exits โ particularly in fast-moving, volatile markets like Bitcoin.
Fractal Pattern AnalysisFractal Pattern Key Elements and How to Read Them
1. Williams Fractals (Triangle Markers)
Red Triangles Pointing Down: Bearish fractals - potential resistance points and selling opportunities
Green Triangles Pointing Up: Bullish fractals - potential support points and buying opportunities
When to Act: Look for bullish fractals forming during uptrends and bearish fractals during downtrends
2. Moving Averages
Yellow Line (20 EMA): Short-term trend
Blue Line (50 EMA): Medium-term trend
Red Line (200 EMA): Long-term trend
Interpretation: When shorter MAs cross above longer MAs, it's bullish; when they cross below, it's bearish
Key Signal: The alignment of all three MAs (stacked in order) confirms a strong trend
3. Background Color
Green Background: Uptrend (all MAs aligned bullishly)
Red Background: Downtrend (all MAs aligned bearishly)
Yellow Background: Sideways/neutral market (MAs not clearly aligned)
4. Market Structure Markers (Small Circles)
Green Circles: Higher highs and higher lows (bullish structure)
Red Circles: Lower highs and lower lows (bearish structure)
Pattern Recognition: Multiple green circles suggest continuing uptrend; multiple red circles suggest continuing downtrend
5. Reversal Diamonds ("Rev" Markers)
Yellow Diamonds: Potential trend reversal points
Usage: These mark where the current trend might be changing direction
Confirmation: Wait for price to close beyond the diamond before acting
6. Bollinger Bands (Blue Lines with Fill)
Middle Band: 20-period SMA
Upper/Lower Bands: Volatility channels
Signals: Price touching upper band in uptrend is strength; touching lower band in downtrend is weakness
Squeeze: When bands narrow, expect a volatility breakout soon
7. Status Table (Top Right)
Shows current trend, volume direction, and overall signal at a glance
"BUY" signal appears when multiple bullish conditions align
"SELL" signal appears when multiple bearish conditions align
ATR by Time [QuantVue]"ATR by Time" incorporates time-specific volatility patterns by calculating the Average True Range (ATR) over a customizable period and comparing it to historical ATR values
at specific times of the day.
The Average True Range (ATR) is a popular technical indicator that measures market volatility by decomposing the entire range of an asset price for that period.
By taking the ATR at certain times of the day and comparing it to the current bar's ATR, traders can gain several potential advantages:
Volatility Pattern Recognition: Different times of the trading day often exhibit different levels of volatility. For instance, markets might be more volatile at the open and close compared to midday. By tracking ATR at specific times, traders can recognize these patterns and better predict periods of high or low volatility.
Risk Management: Understanding volatility trends throughout the day helps in better risk management. During periods of high expected volatility (indicated by higher ATR compared to the historical average), traders can adjust their stop-loss levels and position sizes accordingly to protect their capital.
Trend Confirmation and Divergence: This indicator can help confirm trends or identify potential reversals. For example, if the current ATR consistently exceeds the average ATR at specific times, it may confirm a strong trend. Conversely, if the current ATR falls below the historical average, it could signal a potential slowdown or reversal.
This indicator will work on all markets on all time frames. User can customize ATR length as well as the lookback period.
This script utilizes TradingView's RelativeValue library and averageAtTime function, which is used to compare a current data point in a time interval to an average of data points with corresponding time offsets across historical periods. Its purpose is to assess the significance of a value by considering the historical context within past time intervals.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
Threshold counterOVERVIEW
The "Threshold Counter" is a tool for quantifying occurrences of closing prices of an asset that align with specified criteria and is a flexible and visual approach to studying price action.
A user-definable target threshold can be set and a comparator (<, =, >, and so on) can be selected. The indicator counts values on the main chart meeting these conditions, over a user-defined `lookback` period.
KEY FEATURES
User definable threshold: target value with optional upper bound can be specified
Versatile Comparisons: Choose from "=", ">=", ">", "<=", "<", "between", and "between (inclusive)" for diverse analysis.
Historical Analysis: Assess occurrences over a customisable period.
Visual Representation: Displays instances graphically on the chart with customisable colours.
Summary: Provides a summary label for a quick understanding of the analysed data.
USE-CASES
Pattern Recognition: Identify patterns or trends based on user-defined price criteria.
Threshold Analysis: Quantify occurrences of prices crossing or staying within a specified range.
Strategy Testing: Evaluate historical performance of strategies relying on specific price conditions.
Behavioural Insights: Gain insights into price behaviour by counting occurrences of interest.
The "Threshold Counter" indicator offers a flexible and visual approach to studying price action, which may aid in making decisions based on historical data.
IMPORTANT CONSIDERATIONS
Period selection: The effectiveness of the analysis may be influenced by the choice of the lookback period. Consider an appropriate duration based on the strategy or pattern being analysed.
Comparator Selection: Comparison operator selection will obviously affect the results. There are two range operators of `between` and `between (inclusive)`. The latter will add closing prices that exactly meet the threshold and upper bound. The former does not.
Visualisation: Interpretation of the visual representation is colour-coded.
Red is threshold condition is not met.
Green is threshold condition is met.
Aqua is outside of the lookback period.
User Discretion: This script relies on historical data and should be used with caution. Past performance is not indicative of future results.
Supplementary Analysis: Trading decisions should not rely solely on this script. Users should exercise judgment and consider market conditions.
Smart Bar Coloring: Tight Closes & Volume BreakoutsAdvanced Bar Coloring Indicator for Price Action and Volume Analysis
This sophisticated indicator automatically colors price bars based on two key market conditions: tight closing ranges and significant volume activity, helping traders quickly identify consolidation periods and potential breakout setups.
Key Features:
Tight Close Detection:
ATR-Based Analysis: Uses 14-period ATR to define "tight" price movement
Dual-Bar Confirmation: Requires both current and previous bar to have closing ranges โค 20% of ATR
Consolidation Identification: Highlights periods of reduced volatility that often precede significant moves
Customizable Color: Default amber/orange highlighting for easy visual identification
Volume Breakout Detection:
Multi-Criteria Volume Analysis: Triggers when volume exceeds any of three thresholds:
150% of 20-period volume SMA
150% of recent 3-bar average volume
150% of 50-period volume SMA
Price Action Filter: Requires bullish price action (close > previous close OR close in upper 75% of range)
Smart Volume Handling: Automatically detects and works only with instruments that have volume data
Customizable Color: Default teal highlighting for volume-driven moves
Technical Analysis Applications:
Consolidation Patterns: Identify tight trading ranges before potential breakouts
Volume Confirmation: Spot high-volume moves with supportive price action
Entry Timing: Use tight closes to identify potential accumulation zones
Breakout Validation: Volume-colored bars confirm legitimate breakout attempts
Risk Management: Tight closes often indicate lower immediate volatility
How to Use:
Amber/Orange Bars: Indicate tight closing ranges - potential accumulation or consolidation
Teal Bars: Show significant volume with bullish price action - potential breakout confirmation
Normal Bars: Standard market conditions without special highlighting
Pattern Recognition: Look for clusters of tight closes followed by volume breakouts
Technical Requirements:
Works on any timeframe
Automatically adapts to instruments with or without volume data
Compatible with all chart types and drawing tools
TCP | Market Session | Session Analyzer๐ TCP | Market Session Indicator | Crypto Version
A powerful, real-time market session visualization tool tailored for crypto traders. Track the heartbeat of Asia, Europe, and US trading hours directly on your chart with live session boxes, behavioral analysis, liquidity grab detection, and countdown timers. Know when the action starts, how the market behaves, and where the traps lie.
๐ฐ Introduction:
Trade the Right Hours with the Right Tools
Time matters in trading. Most significant moves happen during key sessionsโand knowing when and how each session unfolds can give you a sharp edge. The TCP Market Session Indicator, developed by Trade City Pro (TCP), puts professional session tracking and behavioral insights at your fingertips.
Whether you're a scalper or swing trader, this indicator gives you the timing context to enter and exit trades with greater confidence and clarity.
๐ Core Features
โข Live Session Boxes :
Highlight active ranges during Asia, Europe, and US sessions with dynamic high/low updates.
โข Session Start/End Labels :
Know exactly when each session begins and ends plotted clearly on your chart with context.
โข Session Behavior Analysis :
At the end of each session, the indicator classifies the price action as:
- Trend Up
- Trend Down
- Consolidation
- Manipulation
โข Liquidity Grab Detection: Automatically detects possible stop hunts (fake breakouts) and marks them on the chart with precision filters (volume, ATR, reversal).
โข Session Countdown Table: A live dashboard showing:
- Current active session
- Time left in session
- Upcoming session and how many minutes until it starts
- Utility time converter (e.g. 90 min = 01:30)
โข Vertical Session Lines: Visualize past and upcoming session boundaries with customizable history and future range.
โข Multi-Day Support: Draw session ranges for previous, current, and future days for better backtesting and forecasting.
โ๏ธ Settings Panel
Customize everything to fit your trading style and schedule:
โข Session Time Settings:
Set the opening and closing time for each session manually using UTC-based minute inputs.
โ For example, enter Asia Start: 0, Asia End: 480 for 00:00โ08:00 UTC.
This gives full flexibility to adjust session hours to match your preferred market behavior.
โข Enable or Disable Elements:
Toggle the visibility of each session (Asia, Europe, US), as well as:
- Session Boxes
- Countdown Table
- Session Lines
- Liquidity Grab Labels
โข Timezone Selection:
Choose between using UTC or your chartโs local timezone for session calculations.
โข Customization Options:
Select number of past and future days to draw session data
Adjust vertical line transparency
Fine-tune label offset and spacing for clean layout
๐ Smart Session Boxes
Each session box tracks high, low, open, and close in real time, providing visual clarity on market structure. Once a session ends, the box closes, and the behavior type is saved and labeled ideal for spotting patterns across sessions.
โข Asia: Green Box
โข Europe: Orange Box
โข US: Blue Box
๐ก Why Use This Tool?
โข Perfect Timing: Donโt get chopped in low-liquidity hours. Focus on sessions where volume and volatility align.
โข Pattern Recognition: Study how price behaves session-to-session to build better strategies.
โข Trap Detection: Spot manipulation moves (liquidity grabs) early and avoid common retail pitfalls.
โข Macro Session Mapping: Use as a foundational layer to align trades with market structure and news cycles.
๐ Example Use Case
You're watching BTC at 12:45 UTC. The indicator tells you:
The Asia session just ended (label shows โAsia Session End: Trend Upโ)
Europe session starts in 15 minutes
A liquidity grab just triggered at the previous highโlabel confirmed
Now you know whoโs active, what the market just did, and whatโs about to startโall in one glance.
โ
Why Traders Trust It
โข Visual & Intuitive: Fully chart-based, no clutter, no guessing
โข Crypto-Focused: Designed specifically for 24/7 crypto markets (not outdated forex models)
โข Non-Repainting: All labels and boxes stay as printedโno tricks
โข Reliable: Tested across multiple exchanges, pairs, and timeframes
๐งฉ Built by Trade City Pro (TCP)
The TCP Market Session Indicator is part of a suite of professional tools used by over 150,000 traders. Itโs coded in Pine Script v6 for full compatibility with TradingViewโs latest capabilities.
๐ Resources
โข Tutorial: Learn how to analyze sessions like a pro in our TradingView guide:
"TradeCityPro Academy: Session Mapping & Liquidity Traps"
โข More Tools: Explore our full library of indicators on
Ultimate JLines & MTF EMA (Configurable, Labels)## Ultimate JLines & MTF EMA (Configurable, Labels) โ Script Overview
This Pine Script is a comprehensive, multi-timeframe indicator based on J Trader concepts. It overlays various Exponential Moving Averages (EMAs), VWAP, inside bar highlights, and dynamic labels onto price charts. The script is highly configurable, allowing users to tailor which elements are displayed and how they appear.
### Key Features
#### 1. **Multi-Timeframe JLines**
- **JLines** are pairs of EMAs (default lengths: 72 and 89) calculated on several timeframes:
- 1 minute (1m)
- 3 minutes (3m)
- 5 minutes (5m)
- 1 hour (1h)
- Custom timeframe (user-selectable)
- Each pair can be visualized as individual lines and as a "cloud" (shaded area between the two EMAs).
- Colors and opacity for each timeframe are user-configurable.
#### 2. **200 EMA on Multiple Timeframes**
- Plots the 200-period EMA on selectable timeframes: 1m, 3m, 5m, 15m, and 1h.
- Each can be toggled independently and colored as desired.
#### 3. **9 EMA and VWAP**
- Plots a 9-period EMA, either on the chartโs current timeframe or a user-specified one.
- Plots VWAP (Volume-Weighted Average Price) for additional trend context.
#### 4. **5/15 EMA Cross Cloud (5min)**
- Calculates and optionally displays a shaded "cloud" between the 5-period and 15-period EMAs on the 5-minute chart.
- Highlights bullish (5 EMA above 15 EMA) and bearish (5 EMA below 15 EMA) conditions with different colors.
- Optionally displays the 5 and 15 EMA lines themselves.
#### 5. **Inside Bar Highlighting**
- Highlights bars where the current high is less than or equal to the previous high and the low is greater than or equal to the previous low (inside bars).
- Color is user-configurable.
#### 6. **9 EMA / VWAP Cross Arrows**
- Plots up/down arrows when the 9 EMA crosses above or below the VWAP.
- Arrow colors and visibility are configurable.
#### 7. **Dynamic Labels**
- On the most recent bar, displays labels for each enabled line (EMAs, VWAP), offset to the right for clarity.
- Labels include the timeframe, type, and current value.
### Customization Options
- **Visibility:** Each plot (line, cloud, arrow, label) can be individually toggled on/off.
- **Colors:** All lines, clouds, and arrows can be colored to user preference, including opacity for clouds.
- **Timeframes:** JLines and EMAs can be calculated on different timeframes, including a custom one.
- **Label Text:** Labels dynamically reflect current indicator values and are color-coded to match their lines.
### Technical Implementation Highlights
- **Helper Functions:** Functions abstract away the logic for multi-timeframe EMA calculation.
- **Security Calls:** Uses `request.security` to fetch data from other timeframes, ensuring accurate multi-timeframe plotting.
- **Efficient Label Management:** Deletes old labels and creates new ones only on the last bar to avoid clutter and maintain performance.
- **Conditional Plotting:** All visual elements are conditionally plotted based on user input, making the indicator highly flexible.
### Use Cases
- **Trend Identification:** Multiple EMAs and VWAP help traders quickly identify trend direction and strength across timeframes.
- **Support/Resistance:** 200 EMA and JLines often act as dynamic support/resistance levels.
- **Entry/Exit Signals:** Crosses between 9 EMA and VWAP, as well as 5/15 EMA clouds, can signal potential trade entries or exits.
- **Pattern Recognition:** Inside bar highlights aid in spotting consolidation and breakout patterns.
### Summary Table of Configurable Elements
| Feature | Timeframes | Cloud Option | Label Option | Color Customizable | Description |
|----------------------------|-------------------|--------------|--------------|--------------------|-----------------------------------------------|
| JLines (72/89 EMA) | 1m, 3m, 5m, 1h, Custom | Yes | Yes | Yes | Key trend-following EMAs with cloud fill |
| 200 EMA | 1m, 3m, 5m, 15m, 1h | No | Yes | Yes | Long-term trend indicator |
| 9 EMA | Any | No | Yes | Yes | Short-term trend indicator |
| VWAP | Chart TF | No | Yes | Yes | Volume-weighted average price |
| 5/15 EMA Cloud (5m) | 5m | Yes | No | Yes | Bullish/bearish cloud between 5/15 EMAs |
| Inside Bar Highlight | Chart TF | No | N/A | Yes | Highlights price consolidation |
| 9 EMA / VWAP Cross Arrows | Chart TF | No | N/A | Yes | Marks EMA/VWAP crossovers with arrows |
This script is ideal for traders seeking a robust, multi-timeframe overlay that combines trend, momentum, and pattern signals in a single, highly customizable indicator. I do not advocate to subscribe to JTrades or the system they tout. This is based on my own observations and not a copy of any JTrades scripts. It is open source to allow full transparency.
GCM Centre Line Candle MarkerGCM Centre Line Candle Marker (GCM-CLCM) - Descriptive Notes
Indicator Overview:
The "GCM Centre Line Candle Marker" is a versatile TradingView overlay indicator designed to enhance chart analysis by drawing short horizontal lines at user-defined "centre" points of candles. These lines provide a quick visual reference to key price levels within each candle, such as midpoints, open, close, or typical prices. The indicator offers extensive customization for line appearance, positioning, and conditional display, including an option to highlight only bullish engulfing patterns.
Key Features:
1. Customizable Line Position:
o Users can choose from various methods to calculate the "centre" price for the line:
๏ง (High + Low) / 2 (Default)
๏ง (Open + Close) / 2
๏ง Close
๏ง Open
๏ง (Open + High + Low + Close) / 4 (HLCO/4)
๏ง (Open + High + Close) / 3 (Typical Price HLC/3 variation)
๏ง (Open + Close + Low) / 3 (Typical Price OCL/3 variation)
2. Line Appearance Customization:
o Visibility: Toggle lines on/off.
o Style: Solid, dotted, or dashed lines.
o Width: Adjustable line thickness (1 to 5).
o Length: Defines how many candles forward the line extends (1 to 10).
o Color: Lines are colored based on candle type (bullish/bearish), with user-selectable base colors.
o Dynamic Opacity: Line opacity is dynamically adjusted based on the candle's size relative to recent candles. Larger candles produce more opaque lines (up to the user-defined maximum opacity), while smaller candles result in more transparent lines. This helps significant candles stand out.
3. Price Labels:
o Show Labels: Option to display price labels at the end of each center line.
o Label Background Color: Customizable.
o Dynamic Text Color: Label text color can change based on the movement of the center price:
๏ง Green: Current center price is higher than the previous.
๏ง Red: Current center price is lower than the previous.
๏ง Gray: No change or first label.
o Static Text Color: Alternatively, a fixed color can be used for all labels.
4. Conditional Drawing - Bullish Engulfing Filter:
o Users can enable an option to Only Show Bullish Engulfing Candles. When active, center lines will only be drawn for candles that meet bullish engulfing criteria (current bull candle's body engulfs the previous bear candle's body).
5. Performance Management:
o Max Lines to Show: Limits the number of historical lines displayed on the chart to maintain clarity and performance. Older lines are automatically removed as new ones are drawn.
6. Alert Condition:
o Includes a built-in alert: Big Bullish Candle. This alert triggers when a bullish candle's range (high - low) is greater than the 20-period simple moving average (SMA) of candle ranges.
How It Works:
โข For each new candle, the script calculates the "center" price based on the user's Line Position selection.
โข If showLines is enabled and (if applicable) the bullish engulfing condition is met, a new line is drawn from the current candle's bar_index at the calculated _center price, extending lineLength candles forward.
โข The line's color is determined by whether the candle is bullish (close > open) or bearish (close < open).
โข Opacity is calculated dynamically: scaledOpacity = int((100 - maxUserOpacity) * (1 - dynamicFactor) + maxUserOpacity), where dynamicFactor is candleSize / maxSize (current candle size relative to the max size in the last 20 candles). This means maxUserOpacity is the least transparent the line will be (for the largest candles), and smaller candles will have lines approaching full transparency.
โข Optional price labels are added at the end of these lines.
โข The script manages an array of drawn lines, removing the oldest ones if the maxLines limit is exceeded.
Potential Use Cases:
โข Visualizing Intra-Candle Levels: Quickly see midpoints or other key price points without manual drawing.
โข Short-Term Reference Points: The extended lines can act as very short-term dynamic support/resistance or points of interest.
โข Pattern Recognition: Highlight bullish engulfing patterns or simply emphasize candles based on their calculated center.
โข Volatility Indication: The dynamic opacity can subtly indicate periods of larger or smaller candle ranges.
โข Confirmation Tool: Use in conjunction with other indicators or trading strategies.
User Input Groups:
โข Line Settings: Controls all aspects of the line's appearance and calculation.
โข Label Settings: Manages the display and appearance of price labels.
โข Other Settings: Contains options for line management and conditional filtering (like Bullish Engulfing).
This indicator provides a clean and customizable way to mark significant price levels within candles, aiding traders in their technical analysis.
StatPivot- Dynamic Range Analyzer - indicator [PresentTrading]Hello everyone! In the following few open scripts, I would like to share various statistical tools that benefit trading. For this time, it is a powerful indicator called StatPivot- Dynamic Range Analyzer that brings a whole new dimension to your technical analysis toolkit.
This tool goes beyond traditional pivot point analysis by providing comprehensive statistical insights about price movements, helping you identify high-probability trading opportunities based on historical data patterns rather than subjective interpretations. Whether you're a day trader, swing trader, or position trader, StatPivot's real-time percentile rankings give you a statistical edge in understanding exactly where current price action stands within historical contexts.
Welcome to share your opinions! Looking forward to sharing the next tool soon!
โ Introduction and How it is Different
StatPivot is an advanced technical analysis tool that revolutionizes retracement analysis. Unlike traditional pivot indicators that only show static support/resistance levels, StatPivot delivers dynamic statistical insights based on historical pivot patterns.
Its key innovation is real-time percentile calculation - while conventional tools require new pivot formations before updating (often too late for trading decisions), StatPivot continuously analyzes where current price stands within historical retracement distributions.
Furthermore, StatPivot provides comprehensive statistical metrics including mean, median, standard deviation, and percentile distributions of price movements, giving traders a probabilistic edge by revealing which price levels represent statistically significant zones for potential reversals or continuations. By transforming raw price data into statistical insights, StatPivot helps traders move beyond subjective price analysis to evidence-based decision making.
โ Strategy, How it Works: Detailed Explanation
๐ถ Pivot Point Detection and Analysis
The core of StatPivot's functionality begins with identifying significant pivot points in the price structure. Using the parameters left and right, the indicator locates pivot highs and lows by examining a specified number of bars to the left and right of each potential pivot point:
Copyp_low = ta.pivotlow(low, left, right)
p_high = ta.pivothigh(high, left, right)
For a point to qualify as a pivot low, it must have left higher lows to its left and right higher lows to its right. Similarly, a pivot high must have left lower highs to its left and right lower highs to its right. This approach ensures that only significant turning points are recognized.
๐ถ Percentage Change Calculation
Once pivot points are identified, StatPivot calculates the percentage changes between consecutive pivot points:
For drops (when a pivot low is lower than the previous pivot low):
CopydropPercent = (previous_pivot_low - current_pivot_low) / previous_pivot_low * 100
For rises (when a pivot high is higher than the previous pivot high):
CopyrisePercent = (current_pivot_high - previous_pivot_high) / previous_pivot_high * 100
These calculations quantify the magnitude of each market swing, allowing for statistical analysis of historical price movements.
๐ถ Statistical Distribution Analysis
StatPivot computes comprehensive statistics on the historical distribution of drops and rises:
Average (Mean): The arithmetic mean of all recorded percentage changes
CopyavgDrop = array.avg(dropValues)
Median: The middle value when all percentage changes are arranged in order
CopymedianDrop = array.median(dropValues)
Standard Deviation: Measures the dispersion of percentage changes from the average
CopystdDevDrop = array.stdev(dropValues)
Percentiles (25th, 75th): Values below which 25% and 75% of observations fall
Copyq1 = array.get(sorted, math.floor(cnt * 0.25))
q3 = array.get(sorted, math.floor(cnt * 0.75))
VaR95: The maximum expected percentage drop with 95% confidence
Copyvar95D = array.get(sortedD, math.floor(nD * 0.95))
Coefficient of Variation (CV): Measures relative variability
CopycvD = stdDevDrop / avgDrop
These statistics provide a comprehensive view of market behavior, enabling traders to understand the typical ranges and extreme moves.
๐ถ Real-time Percentile Ranking
StatPivot's most innovative feature is its real-time percentile calculation. For each current price, it calculates:
The percentage drop from the latest pivot high:
CopycurrentDropPct = (latestPivotHigh - close) / latestPivotHigh * 100
The percentage rise from the latest pivot low:
CopycurrentRisePct = (close - latestPivotLow) / latestPivotLow * 100
The percentile ranks of these values within the historical distribution:
CopyrealtimeDropRank = (count of historical drops <= currentDropPct) / total drops * 100
This calculation reveals exactly where the current price movement stands in relation to all historical movements, providing crucial context for decision-making.
๐ถ Cluster Analysis
To identify the most common retracement zones, StatPivot performs a cluster analysis by dividing the range of historical drops into five equal intervals:
CopyrangeSize = maxVal - minVal
For each interval boundary:
Copyboundaries = minVal + rangeSize * i / 5
By counting the number of observations in each interval, the indicator identifies the most frequently occurring retracement zones, which often serve as significant support or resistance areas.
๐ถ Expected Price Targets
Using the statistical data, StatPivot calculates expected price targets:
CopytargetBuyPrice = close * (1 - avgDrop / 100)
targetSellPrice = close * (1 + avgRise / 100)
These targets represent statistically probable price levels for potential entries and exits based on the average historical behavior of the market.
โ Trade Direction
StatPivot functions as an analytical tool rather than a direct trading signal generator, providing statistical insights that can be applied to various trading strategies. However, the data it generates can be interpreted for different trade directions:
For Long Trades:
Entry considerations: Look for price drops that reach the 70-80th percentile range in the historical distribution, suggesting a statistically significant retracement
Target setting: Use the Expected Sell price or consider the average rise percentage as a reasonable target
Risk management: Set stop losses below recent pivot lows or at a distance related to the statistical volatility (standard deviation)
For Short Trades:
Entry considerations: Look for price rises that reach the 70-80th percentile range, indicating an unusual extension
Target setting: Use the Expected Buy price or average drop percentage as a target
Risk management: Set stop losses above recent pivot highs or based on statistical measures of volatility
For Range Trading:
Use the most common drop and rise clusters to identify probable reversal zones
Trade bounces between these statistically significant levels
For Trend Following:
Confirm trend strength by analyzing consecutive higher pivot lows (uptrend) or lower pivot highs (downtrend)
Use lower percentile retracements (20-30th percentile) as entry opportunities in established trends
โ Usage
StatPivot offers multiple ways to integrate its statistical insights into your trading workflow:
Statistical Table Analysis: Review the comprehensive statistics displayed in the data table to understand the market's behavior. Pay particular attention to:
Average drop and rise percentages to set reasonable expectations
Standard deviation to gauge volatility
VaR95 for risk assessment
Real-time Percentile Monitoring: Watch the real-time percentile display to see where the current price movement stands within the historical distribution. This can help identify:
Extreme movements (90th+ percentile) that might indicate reversal opportunities
Typical retracements (40-60th percentile) that might continue further
Shallow pullbacks (10-30th percentile) that might represent continuation opportunities in trends
Support and Resistance Identification: Utilize the plotted pivot points as key support and resistance levels, especially when they align with statistically significant percentile ranges.
Target Price Setting: Use the expected buy and sell prices calculated from historical averages as initial targets for your trades.
Risk Management: Apply the statistical measurements like standard deviation and VaR95 to set appropriate stop loss levels that account for the market's historical volatility.
Pattern Recognition: Over time, learn to recognize when certain percentile levels consistently lead to reversals or continuations in your specific market, and develop personalized strategies based on these observations.
โ Default Settings
The default settings of StatPivot have been carefully calibrated to provide reliable statistical analysis across a variety of markets and timeframes, but understanding their effects allows for optimal customization:
Left Bars (30) and Right Bars (30): These parameters determine how pivot points are identified. With both set to 30 by default:
A pivot low must be the lowest point among 30 bars to its left and 30 bars to its right
A pivot high must be the highest point among 30 bars to its left and 30 bars to its right
Effect on performance: Larger values create fewer but more significant pivot points, reducing noise but potentially missing important market structures. Smaller values generate more pivot points, capturing more nuanced movements but potentially including noise.
Table Position (Top Right): Determines where the statistical data table appears on the chart.
Effect on performance: No impact on analytical performance, purely a visual preference.
Show Distribution Histogram (False): Controls whether the distribution histogram of drop percentages is displayed.
Effect on performance: Enabling this provides visual insight into the distribution of retracements but can clutter the chart.
Show Real-time Percentile (True): Toggles the display of real-time percentile rankings.
Effect on performance: A critical setting that enables the dynamic analysis of current price movements. Disabling this removes one of the key advantages of the indicator.
Real-time Percentile Display Mode (Label): Chooses between label display or indicator line for percentile rankings.
Effect on performance: Labels provide precise information at the current price point, while indicator lines show the evolution of percentile rankings over time.
Advanced Considerations for Settings Optimization:
Timeframe Adjustment: Higher timeframes generally benefit from larger Left/Right values to identify truly significant pivots, while lower timeframes may require smaller values to capture shorter-term swings.
Volatility-Based Tuning: In highly volatile markets, consider increasing the Left/Right values to filter out noise. In less volatile conditions, lower values can help identify more potential entry and exit points.
Market-Specific Optimization: Different markets (forex, stocks, commodities) display different retracement patterns. Monitor the statistics table to see if your market typically shows larger or smaller retracements than the current settings are optimized for.
Trading Style Alignment: Adjust the settings to match your trading timeframe. Day traders might prefer settings that identify shorter-term pivots (smaller Left/Right values), while swing traders benefit from more significant pivots (larger Left/Right values).
By understanding how these settings affect the analysis and customizing them to your specific market and trading style, you can maximize the effectiveness of StatPivot as a powerful statistical tool for identifying high-probability trading opportunities.
ZigZag Based RSIDescription
ZigZag Trend RSI (ZZ-RSI) is an advanced momentum indicator that combines ZigZag-based trend detection with a trend-adjusted RSI to deliver smarter overbought and oversold signals. Unlike traditional RSI that reacts purely to price movement, this indicator adapts its sensitivity based on the prevailing trend structure identified via the ZigZag pattern.
By dynamically adjusting RSI thresholds according to market direction, ZZ-RSI helps filter out false signals and aligns RSI readings with broader trend contextโcrucial for trend-following strategies, counter-trend entries, and volatility-based timing.
Core Components
ZigZag Pattern Recognition:
Identifies significant swing highs and lows based on price deviation (%) and pivot sensitivity (length). The most recent pivot determines the prevailing trend direction:
๐ข Bullish: last swing is a higher high
๐ด Bearish: last swing is a lower low
โช Neutral: no recent significant movement
Trend-Weighted RSI:
Modifies traditional RSI input by emphasizing price changes in the direction of the trend:
In bull trends, upside moves are magnified.
In bear trends, downside moves are emphasized.
Dynamic RSI Zones:
Overbought and Oversold thresholds adapt to the trend:
In uptrends: higher OB and slightly raised OS โ tolerate stronger rallies
In downtrends: lower OS and slightly reduced OB โ accommodate stronger sell-offs
In neutral: default OB/OS values apply
How to Use
โ
Entries (Reversal or Mean Reversion Traders):
Look for oversold signals (green triangle) in downtrends or neutrals to catch potential reversals.
Look for overbought signals (red triangle) in uptrends or neutrals to fade momentum.
Confirm with price action or volume for higher conviction.
๐ Trend Continuation (Momentum or Trend-Followers):
Use the trend direction label (Bullish / Bearish / Neutral) to align your trades with the broader move.
Combine with moving averages or price structure for entry timing.
Avoid counter-trend signals unless confirmed by divergence or exhaustion.
๐ง Signal Interpretation Table (top right of chart):
Trend: Indicates the current market direction.
RSI: Real-time trend-adjusted RSI value.
Signal: OB/OS/Neutral classification.
Customization Options
ZigZag Length / Deviation %:
Adjust pivot sensitivity and filter out minor noise.
RSI Length:
Controls how fast RSI responds to trend-adjusted price.
Color Settings:
Personalize visual cues for trend direction and OB/OS backgrounds.
Alerts Included
๐ข Overbought/oversold conditions
๐ Trend reversals (bullish or bearish shift)
These alerts are ideal for automated strategies, mobile notifications, or algorithmic workflows.
Ideal For
Traders seeking smarter RSI signals filtered by market structure
Trend-followers and swing traders looking for reliable reversals
Those frustrated with false OB/OS signals in volatile or trending markets
Best Practices
Use in confluence with price structure, trendlines, or S/R levels.
For intraday: consider lowering ZigZag Length and RSI Length.
For higher timeframes: use higher deviation % and smoother RSI to reduce noise.
Elliott Wave Noise FilterElliott Wave Noise Filter
Overview
The Elliott Wave Noise Filter is a specialized indicator for TradingView, designed to solve one of the biggest challenges in Elliott Wave analysis on lower timeframes: the identification of market noise. By combining multiple advanced filtering techniques, this indicator helps distinguish meaningful price action from random fluctuations.
The Problem
On lower timeframesโespecially below 15 minutesโElliott Wave analysis is significantly impacted by excessive market noise. This noise can lead to misinterpretation of wave structures, making it difficult to execute reliable trading decisions.
The Solution
The Elliott Wave Noise Filter utilizes four powerful methods to detect and filter noise:
ATR-Based Volatility Analysis: Identifies price movements too small to be structurally meaningful
Volume Confirmation: Filters out price moves that occur with insufficient volume
Trend Strength Measurement (ADX): Detects periods of weak trend activity, where noise tends to dominate
Fractal Pattern Recognition: Marks significant turning points that could be relevant for Elliott Wave analysis
Features
Visual Indicators
Background Coloring: Red indicates noise; green signifies a clear signal
Hull Moving Average: Smooths price action and highlights the prevailing trend
Fractal Markers: Triangles mark significant highs and lows
Status Panel: Displays current noise status and ADX value
Customization Options
ATR Period: Adjust the lookback period for ATR calculations
Noise Threshold: Defines the percentage of ATR below which a movement is considered noise
Volume Filter: Can be enabled or disabled
Volume Threshold: Sets the ratio to average volume for a move to be deemed significant
Hull MA Display and Length: Configure the moving average settings
ADX Parameters: Adjust trend strength sensitivity
Use Cases
For Elliott Wave Analysis
Eliminate noise to identify cleaner wave structures
Use fractal markers as potential wave endpoints
Reference the Hull MA for determining the broader trend
For General Trading
Identify high-noise periods to avoid low-quality setups
Spot clearer market phases for better entries
Assess price action quality through visual cues
Multi-Timeframe Approach
Apply the indicator across different timeframes for a comprehensive view
Prefer trading when both higher and lower timeframes align with consistent signals
Optimal Settings
For Very Short Timeframes (1โ5 minutes)
Higher Noise Threshold (0.4โ0.5)
Longer ATR Period (20โ30)
Higher Volume Threshold (1.0โ1.2)
For Medium Timeframes (15โ60 minutes)
Medium Noise Threshold (0.2โ0.3)
Standard ATR Period (14)
Standard Volume Threshold (0.8)
For Higher Timeframes (4h and above)
Lower Noise Threshold (0.1โ0.2)
Shorter ATR Period (10)
Lower Volume Threshold (0.6โ0.7)
Conclusion
The Elliott Wave Noise Filter is an essential tool for any Elliott Wave analyst or trader working on lower timeframes. By reducing noise and emphasizing significant market movements, it enables more precise analysis and potentially more profitable trading decisions.
Note: As with any technical indicator, the Elliott Wave Noise Filter should be used as part of a broader trading strategy and not as a standalone signal for trade execution.
BTC Growth | AlchimistOfCrypto๐ BTC Regression Bands & Halvings โ Unveiling Bitcoin's Logarithmic Growth Fields ๐
"The Bitcoin Regression Bands, engineered through advanced logarithmic mathematics, visualizes the probabilistic distribution of Bitcoin's price evolution within a multi-cycle growth paradigm. This indicator employs principles from hyperbolic regression where decay coefficients create mathematical boundaries that define Bitcoin's long-term value progression. Our implementation features algorithmically enhanced rainbow visualization derived from extensive cycle analysis, creating a dynamic representation of Bitcoin's logarithmic growth with adaptive color gradients that highlight critical halving-based phase transitions in the asset's monetary evolution."
๐ Professional Trading Application
The Bitcoin Regression Bands transcends traditional price prediction models with a sophisticated multi-band illumination system that reveals the underlying structure of Bitcoin's monetary evolution. Scientifically calibrated across multiple halving cycles and featuring seamless rainbow visualization, it enables investors to perceive Bitcoin's position within its macro growth trajectory with unprecedented clarity.
- Visual Theming ๐จ
Scientifically designed rainbow gradient optimized for cycle pattern recognition:
- Violet-Blue: Lower value accumulation zones with highest mathematical growth potential
- Green: Fair value equilibrium zone representing the regression mean
- Yellow-Orange: Moderate overvaluation regions indicating potential resistance
- Red: Statistical extreme zones indicating mathematical cycle peaks
- Halving Visualization ๐
- Precise cycle boundaries demarcating Bitcoin's fundamental supply shock events
- Adaptive band spacing based on mathematical cycle progression
- Multiple sub-cycle markers revealing the probabilistic nature of Bitcoin's trajectory
๐ How to Use
1. Identify Macro Position โฐ: Locate Bitcoin's current price relative to the regression bands
2. Understand Cycle Context ๐๏ธ: Note position within the current halving cycle for time-based analysis
3. Assess Mathematical Value ๐: Determine potential over/undervaluation based on band location
4. Adjust Investment Strategy ๐: Modulate position sizing based on mathematical value assessment
5. Identify Cycle Phases โ
: Monitor band transitions to detect accumulation and distribution zones
6. Invest with Precision ๐ก๏ธ: Utilize lower bands for strategic accumulation, upper bands for strategic reduction
7. Manage Risk Dynamically ๐: Scale investment allocations based on mathematical cycle positioning
Balancelink : Partition Function 1.0This script computes the partition function values ๐(๐) using Eulerโs Pentagonal Number Theorem and displays them in a horizontally wrapped table directly on the chart. The partition function is a classic function in number theory that counts the number of ways an integer ๐ can be expressed as a sum of positive integers, disregarding the order of the summands.
Key Features
Efficient Calculation:
The script computes ๐(๐) for all orders from 0 up to a user-defined maximum (set by the "End Order" input). The recursive computation leverages Eulerโs Pentagonal Number Theorem, ensuring the function is calculated correctly for each order.
Display Range Selection:
Users can select a specific range of orders (for example, from ๐ = 100 to ๐ = 200 to display.) This means you can focus on a particular segment of the partition function results without cluttering the chart.
Horizontally Wrapped Table:
The partition values are organized into a clean, horizontal table with a customizable number of columns per row (default is 20). When the number of values exceeds the maximum columns, the table automatically wraps onto a new set of rows for better readability.
Medium Text Size:
The table cells use a medium (normal) text size for easy viewing and clarity.
How to Use
Inputs:
Start Order (n): The starting index from which you want to display the partition function (default is 100).
End Order (n): The ending index up to which the partition function values will be displayed (default is 200).
Max Columns Per Row: Determines how many results are shown per row before wrapping to the next (default is 20).
Calculation:
The script calculates all ๐(๐) values from 0 up to the specified "End Order". It then extracts and displays only the values in the chosen range.
Visualization:
The computed values are shown in a neatly arranged table at the top right of your TradingView chart, making it simple to scroll through and inspect the partition function values.
Use Cases
Educational & Research:
Ideal for educators and students exploring concepts of integer partitions and number theory.
Data Analysis & Pattern Recognition:
Useful for those interested in the behavior and growth of partition numbers as ๐ increases.
Multi-Factor Reversal AnalyzerMulti-Factor Reversal Analyzer โ Quantitative Reversal Signal System
OVERVIEW
Multi-Factor Reversal Analyzer is a comprehensive technical analysis toolkit designed to detect market tops and bottoms with high precision. It combines trend momentum analysis, price action behavior, wave oscillation structure, and volatility breakout potential into one unified indicator.
This indicator is not a random mix of tools โ each module is carefully selected for a specific purpose. When combined, they form a multi-dimensional view of the market, merging trend analysis, momentum divergence, and volatility compression to produce high-confidence signals.
Why Combine These Modules?
Module Combination Ideas & How to Use Them
Factor A: Trend Detector + Gold Zone
Concept:
โข The Trend Detector (light yellow histogram) evaluates market strength:
โข Histogram trending downward or staying below 50 โ bearish conditions;
โข Trending upward or staying above 50 โ bullish conditions.
โข The Gold Zone identifies areas of volatility compression โ typically a prelude to explosive market moves.
Practical Application:
โข When the Gold Zone appears and the Trend Detector is bearish โ likely downside move;
โข When the Gold Zone appears and the Trend Detector is bullish โ likely upside breakout.
โข Note: The Gold Zone does not mean the bottom is in. It is not a buy signal on its own โ always combine it with other modules for directional bias.
Factor B: PAI + Wave Trend
Concept:
โข PAI (Price Action Index) is a custom oscillator that combines price momentum with volatility dispersion, displaying strength zones:
โข Green area โ bullish dominance;
โข Red area โ bearish pressure.
โข Wave Trend offers smoothed crossover signals via the main and signal lines.
Practical Application:
โข When PAI is in the green zone and Wave Trend makes a bullish crossover โ potential reversal to the upside;
โข When PAI is in the red zone and Wave Trend shows a bearish crossover โ potential start of a downtrend.
Factor C: Trend Detector + PAI
Concept:
โข Combines directional trend strength with price action strength to confirm setups via confluence.
Practical Application:
โข Trend Detector histogram bottoms out + PAI enters the green zone โ high chance of upward reversal;
โข Histogram tops out + PAI in the red zone โ increased likelihood of downside continuation.
Multi-Factor Confluence (Advanced Use)
โข When Trend Detector, PAI, and Wave Trend all align in the same direction (bullish or bearish), the directional signal becomes significantly more reliable.
โข This setup is especially useful for trend-following or swing trade entries.
KEY FEATURES
1. Multi-Layer Reversal Logic
โขย Combines trend scoring, oscillator divergence, and volatility squeezes for triangulated reversal detection.
โขย Helps traders distinguish between trend pullbacks and true reversals.
2. Advanced Divergence Detection
โขย Detects both regular and hidden divergences using pivot-based confirmation logic.
โข Customizable lookback ranges and pivot sensitivity provide flexible tuning for different market styles.
3. Gold Zone Volatility Compression
โข Highlights pre-breakout zones using custom oscillation models (RSI, harmonic, Karobein, etc.).
โข Improves anticipation of breakout opportunities following low-volatility compressions.
4. Trend Direction Context
โข PAI and Trend Score components provide top-down insight into prevailing bias.
โข Built-in โStraddle Areaโ highlights consolidation zones; breakouts from this area often signal new trend phases.
5. Flexible Visualization
โข Color-coded trend bars, reversal markers, normalized oscillator plots, and trend strength labels.
โข Designed for both visual discretionary traders and data-driven system developers.
USAGE GUIDELINES
1. Applicable Markets
โข Suitable for stocks, crypto, futures, and forex
โข Supports reversal, mean-reversion, and breakout trading styles
2. Recommended Timeframes
โข Short-term traders: 5m / 15m / 1H โ use Wave Trend divergence + Gold Zone
โข Swing traders: 4H / Daily โ rely on Price Action Index and Trend Detector
โข Macro trend context: use PAI HTF mode for higher timeframe overlays
3. Reversal Strategy Flow
โข Watch for divergence (WT/PAI) + Gold Zone compression
โข Confirm with Trend Score weakening or flipping
โข Use Straddle Area breakout for final trigger
โข Optional: enable bar coloring or labels for visual reinforcement
โข The indicator performs optimally when used in conjunction with a harmonic pattern recognition tool
4. Additional Note on the Gold Zone
The โGold Zoneโ does not directly indicate a market bottom. Since it is displayed at the bottom of the chart, it may be misunderstood as a bullish signal. In reality, the Gold Zone represents a compression of price momentum and volatility, suggesting that a significant directional move is about to occur. The direction of that moveโupward or downwardโshould be determined by analyzing the histogram:
โข If histogram momentum is weakening, the Gold Zone may precede a downward move.
โข If histogram momentum is strengthening, it may signal an upcoming rebound or rally.
Treat the Gold Zone as a warning of impending volatility, and always combine it with trend indicators for accurate directional judgment.
RISK DISCLAIMER
โข This indicator calculates trend direction based on historical data and cannot guarantee future market performance. When using this indicator for trading, always combine it with other technical analysis tools, fundamental analysis, and personal trading experience for comprehensive decision-making.
โข Market conditions are uncertain, and trend signals may result in false positives or lag. Traders should avoid over-reliance on indicator signals and implement stop-loss strategies and risk management techniques to reduce potential losses.
โข Leverage trading carries high risks and may result in rapid capital loss. If using this indicator in leveraged markets (such as futures, forex, or cryptocurrency derivatives), exercise caution, manage risks properly, and set reasonable stop-loss/take-profit levels to protect funds.
โข All trading decisions are the sole responsibility of the trader. The developer is not liable for any trading losses. This indicator is for technical analysis reference only and does not constitute investment advice.
โข Before live trading, it is recommended to use a demo account for testing to fully understand how to use the indicator and apply proper risk management strategies.
CHANGELOG
v1.0: Initial release featuring integrated Price Action Index, Trend Strength Scoring, Wave Trend Oscillator, Gold Zone Compression Detection, and dual-type divergence recognition. Supports higher timeframe (HTF) synchronization, visual signal markers, and diversified parameter configurations.
Volume Predictor [PhenLabs]๐ Volume Predictor
Version: PineScriptโข v6
๐ Description
The Volume Predictor is an advanced technical indicator that leverages machine learning and statistical modeling techniques to forecast future trading volume. This innovative tool analyzes historical volume patterns to predict volume levels for upcoming bars, providing traders with valuable insights into potential market activity. By combining multiple prediction algorithms with pattern recognition techniques, the indicator delivers forward-looking volume projections that can enhance trading strategies and market analysis.
๐ Points of Innovation:
Machine learning pattern recognition using Lorentzian distance metrics
Multi-algorithm prediction framework with algorithm selection
Ensemble learning approach combining multiple prediction methods
Real-time accuracy metrics with visual performance dashboard
Dynamic volume normalization for consistent scale representation
Forward-looking visualization with configurable prediction horizon
๐ง Core Components
Pattern Recognition Engine : Identifies similar historical volume patterns using Lorentzian distance metrics
Multi-Algorithm Framework : Offers five distinct prediction methods with configurable parameters
Volume Normalization : Converts raw volume to percentage scale for consistent analysis
Accuracy Tracking : Continuously evaluates prediction performance against actual outcomes
Advanced Visualization : Displays actual vs. predicted volume with configurable future bar projections
Interactive Dashboard : Shows real-time performance metrics and prediction accuracy
๐ฅ Key Features
The indicator provides comprehensive volume analysis through:
Multiple Prediction Methods : Choose from Lorentzian, KNN Pattern, Ensemble, EMA, or Linear Regression algorithms
Pattern Matching : Identifies similar historical volume patterns to project future volume
Adaptive Predictions : Generates volume forecasts for multiple bars into the future
Performance Tracking : Calculates and displays real-time prediction accuracy metrics
Normalized Scale : Presents volume as a percentage of historical maximums for consistent analysis
Customizable Visualization : Configure how predictions and actual volumes are displayed
Interactive Dashboard : View algorithm performance metrics in a customizable information panel
๐จ Visualization
Actual Volume Columns : Color-coded green/red bars showing current normalized volume
Prediction Columns : Semi-transparent blue columns representing predicted volume levels
Future Bar Projections : Forward-looking volume predictions with configurable transparency
Prediction Dots : Optional white dots highlighting future prediction points
Reference Lines : Visual guides showing the normalized volume scale
Performance Dashboard : Customizable panel displaying prediction method and accuracy metrics
๐ Usage Guidelines
History Lookback Period
Default: 20
Range: 5-100
This setting determines how many historical bars are analyzed for pattern matching. A longer period provides more historical data for pattern recognition but may reduce responsiveness to recent changes. A shorter period emphasizes recent market behavior but might miss longer-term patterns.
๐ง Prediction Method
Algorithm
Default: Lorentzian
Options: Lorentzian, KNN Pattern, Ensemble, EMA, Linear Regression
Selects the algorithm used for volume prediction:
Lorentzian: Uses Lorentzian distance metrics for pattern recognition, offering excellent noise resistance
KNN Pattern: Traditional K-Nearest Neighbors approach for historical pattern matching
Ensemble: Combines multiple methods with weighted averaging for robust predictions
EMA: Simple exponential moving average projection for trend-following predictions
Linear Regression: Projects future values based on linear trend analysis
Pattern Length
Default: 5
Range: 3-10
Defines the number of bars in each pattern for machine learning methods. Shorter patterns increase sensitivity to recent changes, while longer patterns may identify more complex structures but require more historical data.
Neighbors Count
Default: 3
Range: 1-5
Sets the K value (number of nearest neighbors) used in KNN and Lorentzian methods. Higher values produce smoother predictions by averaging more historical patterns, while lower values may capture more specific patterns but could be more susceptible to noise.
Prediction Horizon
Default: 5
Range: 1-10
Determines how many future bars to predict. Longer horizons provide more forward-looking information but typically decrease accuracy as the prediction window extends.
๐ Display Settings
Display Mode
Default: Overlay
Options: Overlay, Prediction Only
Controls how volume information is displayed:
Overlay: Shows both actual volume and predictions on the same chart
Prediction Only: Displays only the predictions without actual volume
Show Prediction Dots
Default: false
When enabled, adds white dots to future predictions for improved visibility and clarity.
Future Bar Transparency (%)
Default: 70
Range: 0-90
Controls the transparency of future prediction bars. Higher values make future bars more transparent, while lower values make them more visible.
๐ฑ Dashboard Settings
Show Dashboard
Default: true
Toggles display of the prediction accuracy dashboard. When enabled, shows real-time accuracy metrics.
Dashboard Location
Default: Bottom Right
Options: Top Left, Top Right, Bottom Left, Bottom Right
Determines where the dashboard appears on the chart.
Dashboard Text Size
Default: Normal
Options: Small, Normal, Large
Controls the size of text in the dashboard for various display sizes.
Dashboard Style
Default: Solid
Options: Solid, Transparent
Sets the visual style of the dashboard background.
Understanding Accuracy Metrics
The dashboard provides key performance metrics to evaluate prediction quality:
Average Error
Shows the average difference between predicted and actual values
Positive values indicate the prediction tends to be higher than actual volume
Negative values indicate the prediction tends to be lower than actual volume
Values closer to zero indicate better prediction accuracy
Accuracy Percentage
A measure of how close predictions are to actual outcomes
Higher percentages (>70%) indicate excellent prediction quality
Moderate percentages (50-70%) indicate acceptable predictions
Lower percentages (<50%) suggest weaker prediction reliability
The accuracy metrics are color-coded for quick assessment:
Green: Strong prediction performance
Orange: Moderate prediction performance
Red: Weaker prediction performance
โ
Best Use Cases
Anticipate upcoming volume spikes or drops
Identify potential volume divergences from price action
Plan entries and exits around expected volume changes
Filter trading signals based on predicted volume support
Optimize position sizing by forecasting market participation
Prepare for potential volatility changes signaled by volume predictions
Enhance technical pattern analysis with volume projection context
โ ๏ธ Limitations
Volume predictions become less accurate over longer time horizons
Performance varies based on market conditions and asset characteristics
Works best on liquid assets with consistent volume patterns
Requires sufficient historical data for pattern recognition
Sudden market events can disrupt prediction accuracy
Volume spikes may be muted in predictions due to normalization
๐ก What Makes This Unique
Machine Learning Approach : Applies Lorentzian distance metrics for robust pattern matching
Algorithm Selection : Offers multiple prediction methods to suit different market conditions
Real-time Accuracy Tracking : Provides continuous feedback on prediction performance
Forward Projection : Visualizes multiple future bars with configurable display options
Normalized Scale : Presents volume as a percentage of maximum volume for consistent analysis
Interactive Dashboard : Displays key metrics with customizable appearance and placement
๐ฌ How It Works
The Volume Predictor processes market data through five main steps:
1. Volume Normalization:
Converts raw volume to percentage of maximum volume in lookback period
Creates consistent scale representation across different timeframes and assets
Stores historical normalized volumes for pattern analysis
2. Pattern Detection:
Identifies similar volume patterns in historical data
Uses Lorentzian distance metrics for robust similarity measurement
Determines strength of pattern match for prediction weighting
3. Algorithm Processing:
Applies selected prediction algorithm to historical patterns
For KNN/Lorentzian: Finds K nearest neighbors and calculates weighted prediction
For Ensemble: Combines multiple methods with optimized weighting
For EMA/Linear Regression: Projects trends based on statistical models
4. Accuracy Calculation:
Compares previous predictions to actual outcomes
Calculates average error and prediction accuracy
Updates performance metrics in real-time
5. Visualization:
Displays normalized actual volume with color-coding
Shows current and future volume predictions
Presents performance metrics through interactive dashboard
๐ก Note:
The Volume Predictor performs optimally on liquid assets with established volume patterns. Itโs most effective when used in conjunction with price action analysis and other technical indicators. The multi-algorithm approach allows adaptation to different market conditions by switching prediction methods. Pay special attention to the accuracy metrics when evaluating prediction reliability, as sudden market changes can temporarily reduce prediction quality. The normalized percentage scale makes the indicator consistent across different assets and timeframes, providing a standardized approach to volume analysis.
Enhanced Volume Flow Analysis Pro โพ๏ธ IFEnhanced Volume Flow Analysis Pro (EVFA Pro)
A Comprehensive Guide to Understanding and Using Volume Flow Analysis
Introduction
The Enhanced Volume Flow Analysis Pro (EVFA Pro) represents a sophisticated approach to understanding market dynamics through the lens of volume analysis. This advanced technical indicator has been designed to peel back the layers of market activity, revealing the intricate dance between institutional and retail traders. By combining volume analysis, participant behavior patterns, and market condition recognition, EVFA Pro provides traders with a deeper understanding of market movements and potential opportunities.
Understanding the Core Framework
At its heart, EVFA Pro works by analyzing and categorizing trading volume based on several key characteristics. The indicator examines not just the raw volume, but also the context in which that volume occurs. It considers factors such as price movement, historical patterns, and market conditions to classify trading activity as either institutional or retail in nature.
The framework adapts dynamically to different market environments. Whether you're trading stocks, ETFs, cryptocurrencies, or commodities, the indicator automatically adjusts its parameters to match the typical behavior patterns of each asset class. This adaptability extends to different trading styles as well, with optimizations for everything from quick-paced scalping to longer-term position trading.
Market Participant Analysis
One of the most powerful aspects of EVFA Pro is its ability to distinguish between institutional and retail trading activity. The indicator accomplishes this through a sophisticated analysis of volume patterns, order flow, and price action. Institutional trading typically leaves distinct footprints in the market - large, well-organized volume patterns that often occur at strategic price levels. EVFA Pro identifies these patterns and separates them from the more scattered, emotion-driven patterns typical of retail trading.
The indicator maintains a constant watch on participation rates from both groups. When institutional participation rises above normal levels, it could signal the beginning of a significant move. Similarly, spikes in retail activity, especially when combined with certain price patterns, might indicate potential market turning points.
Reading Market Conditions
Market conditions are not static, and EVFA Pro recognizes this fundamental truth. The indicator continuously evaluates market conditions, classifying them into four main categories: normal, volatile, ranging, and trending. This classification isn't merely descriptive - it directly influences how the indicator interprets various patterns and signals.
In volatile markets, the indicator becomes more conservative in its pattern recognition, requiring stronger confirmation before signaling potential opportunities. During ranging periods, it adjusts to look for shorter-term movements and potential breakout scenarios. In trending markets, the focus shifts to finding continuation patterns and potential exhaustion points.
Pattern Recognition and Signal Generation
Pattern recognition in EVFA Pro goes beyond simple technical patterns. The indicator looks for complex interactions between volume, price, and participant behavior. It identifies accumulation patterns - periods where institutional buyers are actively building positions, often while keeping price movements relatively subtle to avoid drawing attention. Similarly, it recognizes distribution patterns, where larger players are gradually reducing positions.
Signal generation involves a sophisticated weighing of multiple factors. Volume strength, institutional participation, trend alignment, and price momentum all play roles in determining signal strength. This multi-factor approach helps reduce false signals and provides a more reliable indication of potential market moves.
Visual Analysis Tools
The visual components of EVFA Pro have been carefully designed to present complex information in an intuitive format. The main chart overlay uses color-coded volume bars to show the relative participation of institutional and retail traders. The intensity of these colors varies with volume significance, helping traders quickly identify potentially important market activity.
The information table provides a real-time summary of market conditions, participant activity, and detected patterns. This dashboard-style display allows traders to quickly assess market conditions and potential opportunities without needing to analyze multiple indicators.
Practical Application in Trading
To use EVFA Pro effectively, traders should integrate it into a comprehensive trading strategy. The indicator works best when its signals are considered alongside other forms of analysis and risk management tools. Strong signals from EVFA Pro might suggest potential opportunities, but traders should always consider the broader market context, their own risk tolerance, and their overall trading plan.
The indicator's alerts system can help traders stay informed of potentially significant market developments. However, these alerts should be viewed as starting points for analysis rather than automatic trading signals. Each alert provides specific information about the type of pattern or condition detected, allowing traders to quickly assess whether further investigation is warranted.
Advanced Features and Customization
EVFA Pro offers extensive customization options to suit different trading styles and preferences. Traders can adjust sensitivity levels, color schemes, and display options to match their needs. The indicator also includes special considerations for different trading sessions, allowing for more accurate analysis during pre-market, regular trading hours, and after-hours periods.
Market Application and Interpretation
Success with EVFA Pro comes from understanding not just what it shows, but why it shows what it does. The indicator's patterns and signals reflect real market dynamics - the actions and reactions of different types of traders. By understanding these underlying dynamics, traders can make more informed decisions about market opportunities and risks.
Disclaimer
This indicator and documentation are provided for educational and informational purposes only. Trading in financial markets involves substantial risk of loss and is not suitable for every investor. The analysis provided by the Enhanced Volume Flow Analysis Pro indicator should not be considered as financial advice or a recommendation to make any specific trade or investment. Users of this indicator should understand that:
1. Past performance is not indicative of future results
2. All trading decisions and their outcomes are the responsibility of the individual trader
3. This tool should be used as part of a comprehensive trading strategy that includes proper risk management and due diligence
4. Markets can be highly unpredictable, and no technical analysis tool can guarantee success
Users should carefully consider their investment objectives, level of experience, and risk appetite before using this indicator. It is strongly recommended to consult with a qualified financial advisor before making any investment decisions.
Multiple (12) Strong Buy/Sell Signals + Momentum
Indicator Manual: "Multiple (12) Strong Buy/Sell Signals + Momentum"
This indicator is designed to identify strong buy and sell signals based on 12 configurable conditions, which include a variety of technical analysis methods such as trend-following indicators, pattern recognition, volume analysis, and momentum oscillators. It allows for customizable alerts and visual cues on the chart. The indicator helps traders spot potential entry and exit points by displaying buy and sell signals based on the selected conditions.
Key Observations:
โข The script integrates multiple indicators and pattern recognition methods to provide comprehensive buy/sell signals.
โข Trend-based indicators like EMAs and MACD are combined with pattern recognition (flags, triangles) and momentum-based signals (RSI, ADX, and volume analysis).
โข User customization is a core feature, allowing adjustments to the conditions and thresholds for more tailored signals.
โข The script is designed to be responsive to market conditions, with multiple conditions filtering out noise to generate reliable signals.
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Key Features:
1. 12 Combined Buy/Sell Signal Conditions: This indicator incorporates a diverse set of conditions based on trend analysis, momentum, and price patterns.
2. Minimum Conditions Input: You can adjust the threshold of conditions that need to be met for the buy/sell signals to appear.
3. Alert Customization: Set alert thresholds for both buy and sell signals.
4. Dynamic Visualization: Buy and sell signals are shown as triangles on the chart, with momentum signals highlighted as circles.
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Detailed Description of the 12 Conditions:
1. Exponential Moving Averages (EMA):
o Conditions: The indicator uses EMAs with periods 3, 8, and 13 for quick trend-following signals.
o Bullish Signal: EMA3 > EMA8 > EMA13 (Bullish stack).
o Bearish Signal: EMA3 < EMA8 < EMA13 (Bearish stack).
o Reversal Signal: The crossing over or under of these EMAs can signify trend reversals.
2. MACD (Moving Average Convergence Divergence):
o Fast MACD (2, 7, 3) is used to confirm trends quickly.
o Bullish Signal: When the MACD line crosses above the signal line.
o Bearish Signal: When the MACD line crosses below the signal line.
3. Donchian Channel:
o Tracks the highest high and lowest low over a given period (default 20).
o Breakout Signal: Price breaking above the upper band is bullish; breaking below the lower band is bearish.
4. VWAP (Volume-Weighted Average Price):
o Above VWAP: Bullish condition (price above VWAP).
o Below VWAP: Bearish condition (price below VWAP).
5. EMA Stacking & Reversal:
o Tracks the order of EMAs (3, 8, 13) to confirm strong trends and reversals.
o Bullish Reversal: EMA3 < EMA8 < EMA13 followed by a crossing to bullish.
o Bearish Reversal: EMA3 > EMA8 > EMA13 followed by a crossing to bearish.
6. Bull/Bear Flags:
o Bull Flag: Characterized by a strong price movement (flagpole) followed by a pullback and breakout.
o Bear Flag: Similar to Bull Flag but in the opposite direction.
7. Triangle Patterns (Ascending and Descending):
o Detects ascending and descending triangles using pivot highs and lows.
o Ascending Triangle: Higher lows and flat resistance.
o Descending Triangle: Lower highs and flat support.
8. Volume Sensitivity:
o Identifies price moves with significant volume increases.
o High Volume: When current volume is significantly above the moving average volume (set to 1.2x of the average).
9. Momentum Indicators:
o RSI (Relative Strength Index): Confirms overbought and oversold levels with thresholds set at 65 (overbought) and 35 (oversold).
o ADX (Average Directional Index): Confirms strong trends when ADX > 28.
o Momentum Up: Momentum is upward with strong volume and bullish RSI/ADX conditions.
o Momentum Down: Momentum is downward with strong volume and bearish RSI/ADX conditions.
10. Bollinger & Keltner Squeeze:
o Squeeze Condition: A contraction in both Bollinger Bands and Keltner Channels indicates low volatility, signaling a potential breakout.
o Squeeze Breakout: Price breaking above or below the squeeze bands.
11. 3 Consecutive Candles Condition:
o Bullish: Price rises for three consecutive candles with higher highs and lows.
o Bearish: Price falls for three consecutive candles with lower highs and lows.
12. Williams %R and Stochastic RSI:
o Williams %R: A momentum oscillator with signals when the line crosses certain levels.
o Stochastic RSI: Provides overbought/oversold levels with smoother signals.
o Combined Signals: You can choose whether to require both WPR and StochRSI to signal a buy/sell.
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User Inputs (Inputs Tab):
1. Minimum Conditions for Buy/Sell:
o min_conditions: Number of conditions required to trigger a buy/sell signal on the chart (1 to 12).
o Alert_min_conditions: User-defined alert threshold (how many conditions must be met before an alert is triggered).
2. Donchian Channel Settings:
o Show Donchian: Toggle visibility of the Donchian channel.
o Donchian Length: The length of the Donchian Channel (default 20).
3. Bull/Bear Flag Settings:
o Bull Flag Flagpole Strength: ATR multiplier to define the strength of the flagpole.
o Bull Flag Pullback Length: Length of pullback for the bull flag pattern.
o Bull Flag EMA Length: EMA length used to confirm trend during bull flag pattern.
Similar settings exist for Bear Flag patterns.
4. Momentum Indicators:
o RSI Length: Period for calculating the RSI (default 9).
o RSI Overbought: Overbought threshold for the RSI (default 65).
o RSI Oversold: Oversold threshold for the RSI (default 35).
5. Bollinger/Keltner Squeeze Settings:
o Squeeze Width Threshold: The maximum width of the Bollinger and Keltner Bands for squeeze conditions.
6. Stochastic RSI Settings:
o Stochastic RSI Length: The period for calculating the Stochastic RSI.
7. WPR Settings:
o WPR Length: Period for calculating Williams %R (default 14).
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User Inputs (Style Tab):
1. Signal Plotting:
o Control the display and colors of the buy/sell signals, momentum indicators, and pattern signals on the chart.
o Buy/Sell Signals: Can be customized with different colors and shapes (triangle up for buys, triangle down for sells).
o Momentum Signals: Custom circle placement for momentum-up or momentum-down signals.
2. Donchian Channel:
o Show Donchian: Toggle visibility of the Donchian upper, lower, and middle bands.
o Band Colors: Choose the color for each band (upper, lower, middle).
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How to Use the Indicator:
1. Adjust Minimum Conditions: Set the minimum number of conditions that must be met for a signal to appear. For example, set it to 5 if you want only stronger signals.
2. Set Alert Threshold: Define the number of conditions needed to trigger an alert. This can be different from the minimum conditions for visual signals.
3. Customize Appearance: Modify the colors and styles of the signals to match your preferences.
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Conclusion:
This comprehensive trading indicator uses a combination of trend-following, pattern recognition, and momentum-based conditions to help you spot potential buy and sell opportunities. By adjusting the input settings, you can fine-tune it to match your specific trading strategy, making it a versatile tool for different market conditions.
Signal Reliability Based on Condition Count
The reliability of the buy/sell signals increases as more conditions are met. Here's a breakdown of the probabilities:
1. 1-3 Conditions Met: Lower Probability
o Signals that meet only 1-3 conditions tend to have lower reliability and are considered less probable. These signals may represent false positives or weaker market movements, and traders should approach them with caution.
2. 4 Conditions Met: More Reliable Signal
o When 4 conditions are met, the signal becomes more reliable. This indicates that multiple indicators or market patterns are aligning, increasing the likelihood of a valid buy/sell opportunity. While not foolproof, it's a stronger indication that the market may be moving in a particular direction.
3. 5-6 Conditions Met: Strong Signal
o A signal meeting 5-6 conditions is considered a strong signal. This indicates a well-confirmed move, with several technical indicators and market factors aligning to suggest a higher probability of success. These are the signals that traders often prioritize.
4. 7+ Conditions Met: Rare and High-Confidence Signal
o Signals that meet 7 or more conditions are rare and should be considered high-confidence signals. These represent a significant alignment of multiple factors, and while they are less frequent, they are highly reliable when they do occur. Traders can be more confident in acting on these signals, but they should still monitor market conditions for confirmation.
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You can adjust the number of conditions as needed, but this breakdown should give a clear structure on how the signal strength correlates with the number of conditions met!
CNN Statistical Trading System [PhenLabs]๐ DESCRIPTION
An advanced pattern recognition system utilizing Convolutional Neural Network (CNN) principles to identify statistically significant market patterns and generate high-probability trading signals.
CNN Statistical Trading System transforms traditional technical analysis by applying machine learning concepts directly to price action. Through six specialized convolution kernels, it detects momentum shifts, reversal patterns, consolidation phases, and breakout setups simultaneously. The system combines these pattern detections using adaptive weighting based on market volatility and trend strength, creating a sophisticated composite score that provides both directional bias and signal confidence on a normalized -1 to +1 scale.
๐ CONCEPTS
โข Built on Convolutional Neural Network pattern recognition methodology adapted for financial markets
โข Six specialized kernels detect distinct price patterns: upward/downward momentum, peak/trough formations, consolidation, and breakout setups
โข Activation functions create non-linear responses with tanh-like behavior, mimicking neural network layers
โข Adaptive weighting system adjusts pattern importance based on current market regime (volatility < 2% and trend strength)
โข Multi-confirmation signals require CNN threshold breach (ยฑ0.65), RSI boundaries, and volume confirmation above 120% of 20-period average
๐ง FEATURES
Six-Kernel Pattern Detection:
Simultaneous analysis of upward momentum, downward momentum, peak/resistance, trough/support, consolidation, and breakout patterns using mathematically optimized convolution kernels.
Adaptive Neural Architecture:
Dynamic weight adjustment based on market volatility (ATR/Price) and trend strength (EMA differential), ensuring optimal performance across different market conditions.
Professional Visual Themes:
Four sophisticated color palettes (Professional, Ocean, Sunset, Monochrome) with cohesive design language. Default Monochrome theme provides clean, distraction-free analysis.
Confidence Band System:
Upper and lower confidence zones at 150% of threshold values (ยฑ0.975) help identify high-probability signal areas and potential exhaustion zones.
Real-Time Information Panel:
Live display of CNN score, market state with emoji indicators, net momentum, confidence percentage, and RSI confirmation with dynamic color coding based on signal strength.
Individual Feature Analysis:
Optional display of all six kernel outputs with distinct visual styles (step lines, circles, crosses, area fills) for advanced pattern component analysis.
User Guide
โข Monitor CNN Score crossing above +0.65 for long signals or below -0.65 for short signals with volume confirmation
โข Use confidence bands to identify optimal entry zones - signals within confidence bands carry higher probability
โข Background intensity reflects signal strength - darker backgrounds indicate stronger conviction
โข Enter long positions when blue circles appear above oscillator with RSI < 75 and volume > 120% average
โข Enter short positions when dark circles appear below oscillator with RSI > 25 and volume confirmation
โข Information panel provides real-time confidence percentage and momentum direction for position sizing decisions
โข Individual feature plots allow granular analysis of specific pattern components for strategy refinement
๐กConclusion
CNN Statistical Trading System represents the evolution of technical analysis, combining institutional-grade pattern recognition with retail accessibility. The six-kernel architecture provides comprehensive market pattern coverage while adaptive weighting ensures relevance across all market conditions. Whether youโre seeking systematic entry signals or advanced pattern confirmation, this indicator delivers mathematically rigorous analysis with intuitive visual presentation.
AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend)The AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend) is a cutting-edge indicator that combines advanced mathematical modeling, AI-driven analytics, and segment-based pattern recognition to forecast price movements with precision. This tool is designed to provide traders with deep insights into market dynamics by leveraging multivariate pattern detection and sophisticated predictive algorithms.
๐ฝ Core Features
Segment-Based Pattern Recognition
At its heart, the indicator divides price data into discrete segments, capturing key elements like candle bodies, high-low ranges, and wicks. These segments are normalized using ATR-based volatility adjustments to ensure robustness across varying market conditions.
AI-Powered k-Nearest Neighbors (kNN) Prediction
The predictive engine uses the kNN algorithm to identify the closest historical patterns in a multivariate dictionary. By calculating the distance between current and historical segments, the algorithm determines the most likely outcomes, weighting predictions based on either proximity (distance) or averages.
Dynamic Dictionary of Historical Patterns
The indicator maintains a rolling dictionary of historical patterns, storing multivariate data for:
Candle body ranges, High-low ranges, Wick highs and lows.
This dynamic approach ensures the model adapts continuously to evolving market conditions.
Volatility-Normalized Forecasting
Using ATR bands, the indicator normalizes patterns, reducing noise and enhancing the reliability of predictions in high-volatility environments.
AI-Driven Trend Detection
The indicator not only predicts price levels but also identifies market regimes by comparing current conditions to historically significant highs, lows, and midpoints. This allows for clear visualizations of trend shifts and momentum changes.
๐ฝ Deep Dive into the Core Mathematics
๐พ Segment-Based Multivariate Pattern Analysis
The indicator analyzes price data by dividing each bar into distinct segments, isolating key components such as:
Body Ranges: Differences between the open and close prices.
High-Low Ranges: Capturing the full volatility of a bar.
Wick Extremes: Quantifying deviations beyond the body, both above and below.
Each segment contributes uniquely to the predictive model, ensuring a rich, multidimensional understanding of price action. These segments are stored in a rolling dictionary of patterns, enabling the indicator to reference historical behavior dynamically.
๐พ Volatility Normalization Using ATR
To ensure robustness across varying market conditions, the indicator normalizes patterns using Average True Range (ATR). This process scales each component to account for the prevailing market volatility, allowing the algorithm to compare patterns on a level playing field regardless of differing price scales or fluctuations.
๐พ k-Nearest Neighbors (kNN) Algorithm
The AI core employs the kNN algorithm, a machine-learning technique that evaluates the similarity between the current pattern and a library of historical patterns.
Euclidean Distance Calculation:
The indicator computes the multivariate distance across four distinct dimensions: body range, high-low range, wick low, and wick high. This ensures a comprehensive and precise comparison between patterns.
Weighting Schemes: The contribution of each pattern to the forecast is either weighted by its proximity (distance) or averaged, based on user settings.
๐พ Prediction Horizon and Refinement
The indicator forecasts future price movements (Y_hat) by predicting logarithmic changes in the price and projecting them forward using exponential scaling. This forecast is smoothed using a user-defined EMA filter to reduce noise and enhance actionable clarity.
๐ฝ AI-Driven Pattern Recognition
Dynamic Dictionary of Patterns: The indicator maintains a rolling dictionary of N multivariate patterns, continuously updated to reflect the latest market data. This ensures it adapts seamlessly to changing market conditions.
Nearest Neighbor Matching: At each bar, the algorithm identifies the most similar historical pattern. The prediction is based on the aggregated outcomes of the closest neighbors, providing confidence levels and directional bias.
Multivariate Synthesis: By combining multiple dimensions of price action into a unified prediction, the indicator achieves a level of depth and accuracy unattainable by single-variable models.
Visual Outputs
Forecast Line (Y_hat_line):
A smoothed projection of the expected price trend, based on the weighted contribution of similar historical patterns.
Trend Regime Bands:
Dynamic high, low, and midlines highlight the current market regime, providing actionable insights into momentum and range.
Historical Pattern Matching:
The nearest historical pattern is displayed, allowing traders to visualize similarities
๐ฝ Applications
Trend Identification:
Detect and follow emerging trends early using dynamic trend regime analysis.
Reversal Signals:
Anticipate market reversals with high-confidence predictions based on historically similar scenarios.
Range and Momentum Trading:
Leverage multivariate analysis to understand price ranges and momentum, making it suitable for both breakout and mean-reversion strategies.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
[RS]ZigZag PA V1ZigZag Based on price oscilation.
added pattern recognition, also added recognition of head and shoulders and contracting/expanding triangles to previous list of patterns :p
Use Alt Timeframe: enables optional timeframes, use higher timeframes to reduce noise.
Timeframe: said Alt Timeframe.
Show Patterns: toggles Pattern Recognition on.
Warrior Trading Momentum Strategy
# ๐ Warrior Trading Momentum Strategy - Day Trading Excellence
## Strategy Overview
This comprehensive Pine Script strategy replicates the proven methodologies taught by Ross Cameron and the Warrior Trading community. Designed for active day traders, it identifies high-probability momentum setups with strict risk management protocols.
## ๐ Core Trading Setups
### 1. Gap and Go Trading
- **Primary Focus**: Stocks gapping up 2%+ with volume confirmation
- **Entry Logic**: Breakout above gap open with momentum validation
- **Volume Filter**: 2x average volume requirement for quality setups
### 2. ABCD Pattern Recognition
- **Pattern Detection**: Automated identification of classic ABCD reversal patterns
- **Validation**: A-B and C-D move relationship analysis
- **Entry Trigger**: D-point breakout with volume confirmation
### 3. VWAP Momentum Plays
- **Strategy**: Entries near VWAP with bounce confirmation
- **Distance Filter**: Configurable percentage distance for optimal entries
- **Direction Bias**: Above VWAP bullish momentum validation
### 4. Red to Green Reversals
- **Setup**: Reversal patterns after consecutive red candles
- **Confirmation**: Volume spike with bullish close required
- **Momentum**: Trend change validation with RSI support
### 5. Breakout Momentum
- **Logic**: Breakouts above recent highs with volume
- **Filters**: EMA20 and RSI confirmation for quality
- **Trend**: Established momentum direction validation
## โก Key Features
### Smart Risk Management
- **Position Sizing**: Automatic calculation based on account risk percentage
- **Stop Loss**: 2 ATR-based stops for volatility adjustment
- **Take Profit**: Configurable risk-reward ratios (default 1:2)
- **Trailing Stops**: Profit protection with adjustable triggers
### Advanced Filtering System
- **Time Filters**: Market hours trading with lunch hour avoidance
- **Volume Confirmation**: Multi-timeframe volume analysis
- **Momentum Indicators**: RSI and moving average trend validation
- **Quality Control**: Multiple confirmation layers for signal accuracy
### PDT-Friendly Design
- **Trade Limiting**: Built-in daily trade counter for accounts under $25K
- **Selective Trading**: Priority scoring system for A+ setups only
- **Quality over Quantity**: Maximum 2-3 high-probability trades per day
## ๐ฏ Optimal Usage
### Best Timeframes
- **Primary**: 5-minute charts for entry timing
- **Secondary**: 1-minute for precise execution
- **Context**: Daily charts for gap analysis
### Ideal Market Conditions
- **Volatility**: High-volume, momentum-driven markets
- **Stocks**: Market cap $100M+, average volume 1M+ shares
- **Sectors**: Technology, biotech, growth stocks with news catalysts
### Account Requirements
- **Minimum**: $500+ for proper position sizing
- **Recommended**: $25K+ for unlimited day trading
- **Risk Tolerance**: Active day trading experience preferred
## ๐ Performance Optimization
### Entry Criteria (All Must Align)
1. โ
Time filter (market hours, avoid lunch)
2. โ
Volume spike (2x+ average volume)
3. โ
Momentum confirmation (RSI 50-80)
4. โ
Trend alignment (above EMA20)
5. โ
Pattern completion (setup-specific)
### Risk Parameters
- **Maximum Risk**: 1-2% per trade
- **Position Size**: 25% of account maximum
- **Stop Loss**: 2 ATR below entry
- **Take Profit**: 2:1 risk-reward minimum
## ๐ง Customization Options
### Gap Trading Settings
- Minimum gap percentage threshold
- Volume multiplier requirements
- Gap validation criteria
### Pattern Recognition
- ABCD ratio parameters
- Swing point sensitivity
- Pattern completion filters
### Risk Management
- Risk-reward ratio adjustment
- Maximum daily trade limits
- Trailing stop trigger levels
### Time and Session Filters
- Trading session customization
- Lunch hour avoidance toggle
- Market condition filters
## โ ๏ธ Important Disclaimers
### Risk Warning
- **High Risk**: Day trading involves substantial risk of loss
- **Capital Requirements**: Only trade with risk capital
- **Experience**: Strategy requires active monitoring and experience
- **Market Conditions**: Performance varies with market volatility
### PDT Considerations
- **Day Trading Rules**: Accounts under $25K limited to 3 day trades per 5 days
- **Compliance**: Strategy includes trade counting for PDT compliance
- **Alternative**: Consider swing trading modifications for smaller accounts
### Backtesting vs Live Trading
- **Slippage**: Real trading involves execution delays and slippage
- **Commissions**: Factor in broker fees for accurate performance
- **Market Impact**: Large positions may affect fill prices
- **Psychological Factors**: Live trading involves emotional challenges
## ๐ Educational Value
This strategy serves as an excellent learning tool for understanding:
- Professional day trading methodologies
- Risk management principles
- Pattern recognition techniques
- Volume and momentum analysis
- Multi-timeframe analysis
## ๐ค Community and Support
Based on proven Warrior Trading methodologies with active community support. Strategy includes comprehensive plotting and information tables for educational purposes and trade analysis.
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**Disclaimer**: This strategy is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and never risk more than you can afford to lose.
**Tags**: #DayTrading #Momentum #WarriorTrading #GapAndGo #ABCD #VWAP #PatternTrading #RiskManagement
