BollingerBands MTF | AlchimistOfCrypto🌌 Bollinger Bands – Unveiling Market Volatility Fields 🌌
"The Bollinger Bands, reimagined through quantum mechanics principles, visualizes the probabilistic distribution of price movements within a multi-dimensional volatility field. This indicator employs principles from wave function mathematics where standard deviation creates probabilistic boundaries, similar to electron cloud models in quantum physics. Our implementation features algorithmically enhanced visualization derived from extensive mathematical modeling, creating a dynamic representation of volatility compression and expansion cycles with adaptive glow effects that highlight the critical moments where volatility phase transitions occur."
📊 Professional Trading Application
The Bollinger Bands Quantum transcends traditional volatility measurement with a sophisticated gradient illumination system that reveals the underlying structure of market volatility fields. Scientifically calibrated for multiple timeframes and featuring eight distinct visual themes, it enables traders to perceive volatility contractions and expansions with unprecedented clarity.
⚙️ Indicator Configuration
- Volatility Field Parameters 📏
Python-optimized settings for specific market conditions:
- Period: 20 (default) - The quantum time window for volatility calculation
- StdDev Multiplier: 2.0 - The probabilistic boundary coefficient
- MA Type: SMA/EMA/VWMA/WMA/RMA - The quantum field smoothing algorithm
- Visual Theming 🎨
Eight scientifically designed visual palettes optimized for volatility pattern recognition:
- Neon (default): High-contrast green/red scheme enhancing volatility transition visibility
- Cyan-Magenta: Vibrant palette for maximum volatility boundary distinction
- Yellow-Purple: Complementary colors for enhanced compression/expansion detection
- Specialized themes (Green-Red, Forest Green, Blue Ocean, Orange-Red, Grayscale): Each calibrated for different market environments
- Opacity Control 🔍
- Variable transparency system (0-100) allowing seamless integration with price action
- Adaptive glow effect that intensifies during volatility phase transitions
- Quantum field visualization that reveals the probabilistic nature of price movements
🚀 How to Use
1. Select Visualization Parameters ⏰: Adjust period and standard deviation to match market conditions
2. Choose MA Type 🎚️: Select the appropriate smoothing algorithm for your trading strategy
3. Select Visual Theme 🌈: Choose a color scheme that enhances your personal pattern recognition
4. Adjust Opacity 🔎: Fine-tune visualization intensity to complement your chart analysis
5. Identify Volatility Phases ✅: Monitor band width to detect compression (pre-breakout) and expansion (trend)
6. Trade with Precision 🛡️: Enter during band contraction for breakouts, or trade mean reversion using band boundaries
7. Manage Risk Dynamically 🔐: Use band width as volatility-based position sizing parameter
Volatilite
Triple Confirmation Buy/Sell Engine VWAP + MACD + RSIDescription:
This custom-built indicator generates high-confidence Buy/Sell signals using a powerful combination of MACD momentum, RSI strength, and VWAP trend confirmation — designed for cleaner entries and fewer false signals.
Unlike traditional scripts that rely on only one indicator (and produce noisy or early signals), this system requires triple confirmation, greatly increasing signal quality and reducing false trades.
✅ Buy Signal Conditions:
MACD histogram turns green (momentum shift positive)
RSI crosses above 50 (bullish strength confirmation)
Price closes above VWAP (trend confirmation)
🔻 Sell Signal Conditions:
MACD histogram turns red (momentum shift negative)
RSI crosses below 50 (weakening trend)
Price closes below VWAP (bearish confirmation)
🛠 Best For:
Trend traders seeking higher probability entries
Swing traders who want to catch bigger moves
Crypto, stocks, forex traders looking for simple, effective signals
PumpC Opening Range Breakout (ORB) 5min Range📄 PumpC ORB 5-Minute Opening Range Breakout Indicator
✨ Overview
The PumpC ORB 5-Minute Opening Range Breakout indicator captures early session price action by tracking the high, low, and open of a defined 5-minute window at market open (customized for Futures or Stocks).
It plots breakout levels, extension targets, average range calculations, volume tracking, and provides visual and table-based data summaries.
This indicator is designed for traders seeking a complete, clean visualization of Opening Range Breakouts (ORB) with flexible customization.
⚙️ Main Features
Opening Range Box (ORB Box) Draws a box around the high and low of the first 5-minute session (8:30–8:35 ET for Futures, 9:30–9:35 ET for Stocks). Box extends from the session open to the session close (4:00 PM ET). Option to enable/disable historical boxes. Box color and opacity are customizable. Core ORB Levels Open Level: Plots the open price of the 5-minute ORB window. ORB Levels: Plots breakout levels at multiples: +0.5x the range +1.5x the range (customizable factor) Each level has independent color settings and visibility toggles. Option to show or hide historic extension levels. Table Display Compact table in the top-right corner showing: ORB ATR (average range) ORB ATR in ticks Today's ORB range ORB Volume ATR (average volume during ORB) Today's ORB Volume Volume is formatted automatically into "K" (thousands) or "M" (millions) for readability. Background Highlights After the ORB window closes: Blue highlight if today's ORB range is greater than the 10-day ATR average. Orange highlight if today's ORB range is smaller than the 10-day ATR average. Helps quickly assess relative strength or weakness compared to historical behavior. Alerts Breakout Confirmations: Fires when price closes above ORB High or below ORB Low. Fallout Traps: Alerts when price wick crosses ORB High/Low but closes back inside the range. Alerts use clean titles and simple messages for easy identification.
🔧 Inputs and Customization
Mode Toggle: Choose between Futures (8:30 ET open) or Stocks (9:30 ET open). Show/Hide Labels: Control label visibility for ORB and extension levels. Line Width Control: Customize thickness for ORB lines and extension levels. ORB Level Level Visibility: Independently enable or disable each extension line. Table Appearance: Customize table background color, font color, and padding. ORB Box Settings: Customize box color and control whether historical boxes are drawn.
📚 How to Use
Select Mode: Choose Futures or Stocks depending on your instrument. Observe the Opening Range: Focus on the ORB High and ORB Low during the first 5 minutes after the open. Monitor Breakouts: Breakout alerts will fire when price closes outside the ORB range, signaling potential continuation. Watch for Fallout Traps: Fallout alerts signal when price briefly wicks above/below but closes back inside the ORB range. Use Table Metrics: Instantly compare today's ORB range and volume versus historical averages to assess session strength or weakness.
🛡️ Notes
Best used on the 1-minute or 5-minute chart for intraday trading. Ensure your TradingView chart time zone is set to New York for correct functioning. Alerts must be manually configured after adding the indicator to your chart.
NR4/NR7 + Trend + MACD + VWAP FilterThe Ultimate Momentum-Compression Strategy
This strategy merges the power of price compression and trend confirmation, ensuring you're trading when the market is coiled and ready to move. By combining multiple filters—NR4/NR7, trend alignment, MACD momentum, and VWAP support—this setup identifies high-probability trade opportunities in dynamic, trending stocks. Here's how it works:
NR4/NR7 Patterns: These are narrow-range days where the current price range is smaller than the previous 4 or 7 days. This signals potential breakout or continuation setups, as the market is compressing before making a move.
Trend Confirmation: To ensure you're not trading against the current trend, the price must be above the 20 EMA, and the 10 EMA must be above the 20 EMA. This confirms a bullish structure, with the price trending in your favour.
MACD Momentum: The fast MACD line must be above the slow MACD line, confirming the trend is not only intact but also gaining momentum.
VWAP Filter: Price must be above the VWAP (Volume Weighted Average Price). This is the final confirmation that the market is in a strong, bullish phase, with buyers dominating the market.
By requiring all these conditions to align, this strategy takes the guesswork out of day trading. It ensures you're trading within a well-established trend, with compression patterns and momentum backing your trade. The result? You’re entering positions with confidence and clarity, poised to ride strong, sustained moves.
This strategy is for the trader who values both flexibility and discipline—able to capture dynamic moves while staying aligned with market structure and momentum. It’s a refined, systematic approach that makes decisions clear, without the emotional second-guessing.
ka66: ADR EstimationThis is based on Daryl Guppy's Average Daily Range indicator, the link is difficult to find, but it is an estimation/projection indicator for a daily range.
The thesis is (if I understand correctly):
The range (high - low) of a particular day can be determined, with 85% probability, by taking the ranges of the last 5 days, and getting their average, then multiplying this average value by 0.75. This final value is the estimated range for the next day.
The indicator does not say anything about potential direction, so it may be used as a Take Profit or Stop Loss estimator for the trading strategy in use. Either on the daily timeframe, or an intraday timeframe.
And if we enter the market intraday for a day trade, when the day's range has already exceeded or is close to exceeding the estimated/projected value, perhaps the move is already quite exhausted, and the trade needs to be reconsidered.
A further implication is: if 0.75 multiple occurs with 85% probability, then a lower multiple is even more probable, if one was looking for a more conservative estimate.
The indicator shows three things for a visual inspection of the validity of this concept (and allows basic customisation of parameters):
The day's range, shown in a translucent gray/deep green, as columns. This is the current bar's range. If intraday, it will repaint.
The 5 day average up to the current bar, shown as a step-line plot in orange. If intraday, it will repaint.
The projected range: a thinner blue histogram column, this is offset one bar forward, as it is a future estimate/forward-looking. It too will repaint if the current day is still not complete.
To evaluate the historical results of the chosen settings visually (eye-ball it!), compare the blue histogram bar to the gray bar/column, i.e. the estimate vs. actual range:
When the blue bar is generally within the gray column, and close enough to that column's size/range, then the projected estimation has been reasonable.
if the blue bar tends to be relatively smaller than the gray bar, then we are underestimating often. Increase the projection multiple setting, as a simple fix.
if the blue bar tends to exceed the range of the gray bar a lot, we are overestimating often. Lower the projection multiple setting, as a simple fix.
Guppy's document says that they basically calculate this ADR for multiple markets and focus on markets with the top 5 ranges (in descending order, of course), to maximise the profit potential on intraday trades planned for the next day. Because it is an estimation, this calculation can be run at the end of the day on completed bars.
This indicator also allows displaying the value as percentages, taking the logic of the ATR% (ATR Percent) indicator, which divides the ATR by the close value and multiplies it by 100 to get a normalised percentage value, allowing it to be compared across markets (but in the same timeframe!).
Machine Learning | Adaptive Trend Signals [Bitwardex]⚙️🧠Machine Learning | Adaptive Trend Signals
🔷Overview
Machine Learning | Adaptive Trend Signals is a Pine Script™ v6 indicator designed to visualize market trends and generate signals through a combination of volatility clustering, Gaussian smoothing, and adaptive trend calculations. Built as an overlay indicator, it integrates advanced techniques inspired by machine learning concepts, such as K-Means clustering, to adapt to changing market conditions. The script is highly customizable, includes a backtesting module, and supports alert conditions, making it suitable for traders exploring trend-based strategies and developers studying volatility-driven indicator design.
🔷Functionality
The indicator performs the following core functions:
• Volatility Clustering: Uses K-Means clustering to categorize market volatility into high, medium, and low states, adjusting trend sensitivity accordingly.
• Trend Calculation: Computes adaptive trend lines (SmartTrend) based on volatility-adjusted standard deviation, smoothed RSI, and ADX filters.
• Signal Generation: Identifies potential buy and sell points through trend line crossovers and directional confirmation.
• Backtesting Module: Tracks trade outcomes based on the SmartTrend3 value, displaying win rate and total trades.
• Visualization: Plots trend lines with gradient colors and optional signal markers (bullish 🐮 and bearish 🐻).
• Alerts: Provides configurable alerts for trend shifts and volatility state changes.
🔷Technical Methodology
Volatility Clustering with K-Means
The indicator employs a K-Means clustering algorithm to classify market volatility, measured via the Average True Range (ATR), into three distinct clusters:
• Data Collection: Gathers ATR values over a user-defined training period (default: 100 bars).
• Centroid Initialization: Sets initial centroids at the highest, lowest, and midpoint ATR values within the training period.
• Iterative Clustering: Assigns ATR data points to the nearest centroid, recalculates centroid means, and repeats until convergence.
• Dynamic Adjustment: Assigns a volatility state (high, medium, or low) based on the closest centroid, adjusting the trend factor (e.g., tighter for high volatility, wider for low volatility).
This approach allows the indicator to adapt its sensitivity to varying market conditions, providing a data-driven foundation for trend calculations.
🔷Gaussian Smoothing
To enhance signal clarity and reduce noise, the indicator applies Gaussian kernel smoothing to:
• RSI: Smooths the Relative Strength Index (calculated from OHLC4) to filter short-term fluctuations.
• SmartTrend: Smooths the primary trend line for a more stable output.
The Gaussian kernel uses a sigma value derived from the user-defined smoothing length, ensuring mathematically consistent noise reduction.
🔷SmartTrend Calculation
The pineSmartTrend function is the core of the indicator, producing three trend lines:
• SmartTrend: The primary trend line, calculated using a volatility-adjusted standard deviation, smoothed RSI, and ADX conditions.
• SmartTrend2: A secondary trend line with a wider factor (base factor * 1.382) for signal confirmation.
SmartTrend3: The average of SmartTrend and SmartTrend2, used for plotting and backtesting.
Key components of the calculation include:
• Dynamic Standard Deviation: Scales based on ATR relative to its 50-period smoothed average, with multipliers (1.0 to 1.4) applied according to volatility thresholds.
• RSI and ADX Filters: Requires RSI > 50 for bullish trends or < 50 for bearish trends, alongside ADX > 15 and rising to confirm trend strength.
Volatility-Adjusted Bands: Constructs upper and lower bands around price action, adjusted by the volatility cluster’s dynamic factor.
🔷Signal Generation
The generate_signals function generates signals as follows:
• Buy Signal: Triggered when SmartTrend crosses above SmartTrend2 and the price is above SmartTrend, with directional confirmation.
• Sell Signal: Triggered when SmartTrend crosses below SmartTrend2 and the price is below SmartTrend, with directional confirmation.
Directional Logic: Tracks trend direction to filter out conflicting signals, ensuring alignment with the broader market context.
Signals are visualized as small circles with bullish (🐮) or bearish (🐻) emojis, with an option to toggle visibility.
🔷Backtesting
The get_backtest function evaluates signal outcomes using the SmartTrend3 value (rather than closing prices) to align with the trend-based methodology.
It tracks:
• Total Trades: Counts completed long and short trades.
• Win Rate: Calculates the percentage of trades where SmartTrend3 moves favorably (higher for longs, lower for shorts).
Position Management: Closes opposite positions before opening new ones, simulating a single-position trading system.
Results are displayed in a table at the top-right of the chart, showing win rate and total trades. Note that backtest results reflect the indicator’s internal logic and should not be interpreted as predictive of real-world performance.
🔷Visualization and Alerts
• Trend Lines: SmartTrend3 is plotted with gradient colors reflecting trend direction and volatility cluster, accompanied by a secondary line for visual clarity.
• Signal Markers: Optional buy/sell signals are plotted as small circles with customizable colors.
• Alerts: Supports alerts for:
• Bullish and bearish trend shifts (confirmed on bar close).
Transitions to high, medium, or low volatility states.
🔷Input Parameters
• ATR Length (default: 14): Period for ATR calculation, used in volatility clustering.
• Period (default: 21): Common period for RSI, ADX, and standard deviation calculations.
• Base SmartTrend Factor (default: 2.0): Base multiplier for volatility-adjusted bands.
• SmartTrend Smoothing Length (default: 10): Length for Gaussian smoothing of the trend line.
• Show Buy/Sell Signals? (default: true): Enables/disables signal markers.
• Bullish/Bearish Color: Customizable colors for trend lines and signals.
🔷Usage Instructions
• Apply to Chart: Add the indicator to any TradingView chart.
• Configure Inputs: Adjust parameters to align with your trading style or market conditions (e.g., shorter ATR length for faster markets).
• Interpret Output:
• Trend Lines: Use SmartTrend3’s direction and color to gauge market bias.
• Signals: Monitor bullish (🐮) and bearish (🐻) markers for potential entry/exit points.
• Backtest Table: Review win rate and total trades to understand the indicator’s behavior in historical data.
• Set Alerts: Configure alerts for trend shifts or volatility changes to support manual or automated trading workflows.
• Combine with Analysis: Use the indicator alongside other tools or market context, as it is designed to complement, not replace, comprehensive analysis.
🔷Technical Notes
• Data Requirements: Requires at least 100 bars for accurate volatility clustering. Ensure sufficient historical data is loaded.
• Market Suitability: The indicator is designed for trend detection and may perform differently in ranging or volatile markets due to its reliance on RSI and ADX filters.
• Backtesting Scope: The backtest module uses SmartTrend3 values, which may differ from price-based outcomes. Results are for informational purposes only.
• Computational Intensity: The K-Means clustering and Gaussian smoothing may increase processing time on lower timeframes or with large datasets.
🔷For Developers
The script is modular, well-commented, encouraging reuse and modification with proper attribution.
Key functions include:
• gaussianSmooth: Applies Gaussian kernel smoothing to any data series.
• pineSmartTrend: Computes adaptive trend lines with volatility and momentum filters.
• getDynamicFactor: Adjusts trend sensitivity based on volatility clusters.
• get_backtest: Evaluates signal performance using SmartTrend3.
Developers can extend these functions for custom indicators or strategies, leveraging the volatility clustering and smoothing methodologies. The K-Means implementation is particularly useful for adaptive volatility analysis.
🔷Limitations
• The indicator is not predictive and should be used as part of a broader trading strategy.
• Performance varies by market, timeframe, and parameter settings, requiring user experimentation.
• Backtest results are based on historical data and internal logic, not real-world trading conditions.
• Volatility clustering assumes sufficient historical data; incomplete data may affect accuracy.
🔷Acknowledgments
Developed by Bitwardex, inspired by machine learning concepts and adaptive trading methodologies. Community feedback is welcome via TradingView’s platform.
🔷 Risk Disclaimer
Trading involves significant risks, and most traders may incur losses. Bitwardex AI Algo is provided for informational and educational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument . The signals, metrics, and features are tools for analysis and do not guarantee profits or specific outcomes. Past performance is not indicative of future results. Always conduct your own due diligence and consult a financial advisor before making trading decisions.
Whale Psychology Insights
### 🧠 Whale Psychology Insights – Unmasking Smart Money Moves
**Understand the mind games behind every candle.**
This advanced indicator is designed to reveal the psychological warfare played by whales and market manipulators in the crypto space. Stop trading blind—start trading with the insights of the smart money.
#### 🔍 What It Does:
- **Liquidity Zone Detection** – Automatically identifies key **swing highs/lows** where stop hunts are likely.
- **Volume Spike Alerts** – Spot **suspicious activity** where big players enter or exit.
- **Order Block Zones** – Highlights **bullish/bearish engulfing patterns** used by institutions.
- **Fair Value Gaps (FVG)** – Marks price inefficiencies where price may return.
- **Fakeout Detection** – Finds **manipulative wicks** designed to trap retail traders.
#### 💡 Use Cases:
- Avoid getting stopped out by **liquidity grabs**
- Enter after the **whales have made their move**
- Identify **high-probability reversal zones**
- Trade **with smart money**, not against it
Perfect for scalpers, intraday traders, and swing traders looking to understand *why* price moves—not just *where*.
> 🧠 **Trade the psychology, not just the chart.**
MAD Trend Detector ~ C H I P AMAD Trend Detector ~ C H I P A is a custom trend detection tool designed to identify meaningful price deviations using Median Absolute Deviation (MAD) logic layered over a smoothed price baseline.
It uses:
A user-selectable source (Close, High, Low, etc.)
A configurable EMA or SMA as the core smoothing layer
Median Absolute Deviation (MAD) to measure typical price dispersion
A user-adjustable MAD multiplier to fine-tune trend sensitivity
Trend bands that expand dynamically based on local volatility
This setup highlights breakout conditions when price detaches meaningfully from its typical behavior — helping traders detect trend acceleration, volatility breakouts, and directional shifts with minimal lag and reduced noise.
Candle coloring responds directly to trend status, with electric blue and red visuals for clear on-chart recognition.
Alpha Beta Gamma with Volume CandleAlpha Beta Gamma with Volume Candle
This Pine Script indicator analyzes price dynamics and volume activity to assist traders in identifying momentum, reversals, and key price levels. It calculates three proprietary metrics—Alpha, Beta, and Gamma—based on a user-selected price type (e.g., Open, Close, HL2) and timeframe, using a lookback period (default 37 bars). These metrics normalize price movements relative to the range of highs and lows, helping traders gauge market strength and positioning.
How It Works:
Alpha: Measures the distance of the selected price from the lowest price over the lookback period, normalized by the period length.
Beta: Represents the full price range (high minus low) over the lookback period, scaled by the period length.
Gamma: Normalizes the price’s position within the high-low range, providing a 0–1 scale for relative positioning.
Volume Analysis: The script classifies candles based on volume thresholds relative to a simple moving average (SMA, default 400 bars). High volume (≥ 2x SMA), low volume (≤ 0.5x SMA), and strong signal volume (≥ 1.5x SMA) trigger distinct candle colors to highlight bullish (e.g., deep blue, violet) or bearish (e.g., aqua, pink) conditions.
Custom Bands: Nine horizontal levels (0 to 1, divided into eight equal parts) act as dynamic support/resistance zones, useful for grid-based trading or breakout strategies.
How to Use:
Inputs:
Chart Timeframe: Select the timeframe for price data (e.g., 1H, 1D).
Price Type: Choose the price metric (e.g., Close, HL2) for calculations.
ABG Length: Adjust the lookback period (default 37) for sensitivity.
Volume MA Length: Set the SMA period for volume analysis (default 400).
Volume Thresholds: Customize high, low, and strong volume multipliers.
Visual Settings: Toggle labels, custom bands, and table display; adjust line styles, label sizes, and table positions.
Interpretation:
Use Alpha, Beta, and Gamma plots to assess price momentum and range dynamics.
Monitor colored candles for volume-driven signals (e.g., violet for strong bullish volume).
Leverage custom bands for support/resistance or breakout trading.
Check the table for real-time ABG values and percentage changes.
Settings Tips:
For scalping, reduce the ABG Length (e.g., 20) and use a shorter timeframe (e.g., 5M).
For swing trading, increase the Volume MA Length (e.g., 600) for more stable volume signals.
Enable labels and custom bands for visual clarity on key levels.
This indicator is versatile for various trading styles, combining price-based metrics with volume analysis to enhance decision-making.
Smart Market Matrix Smart Market Matrix
This indicator is designed for intraday, scalping, providing automated detection of price pivots, liquidity traps, and breakout confirmations, along with a context dashboard featuring volatility, trend, and volume.
## Summary Description
### Menu Settings & Their Roles
- **Swing Pivot Strength**: Controls the sensitivity for detecting High/Low pivots.
- **Show Pivot Points**: Toggles the display of HH/LL markers on the chart.
- **VWMA Length for Trap Volume** & **Volume Spike Multiplier**: Identify concentrated volume spikes for liquidity traps.
- **Wick Ratio Threshold** & **Max Body Size Ratio**: Detect candles with disproportionate wicks and small bodies (doji-ish) for traps.
- **ATR Length for Trap**: Measures volatility specific to trap detection.
- **VWMA Length for Breakout Volume**, **ATR Multiplier for Breakout**, **ATR Length for Breakout**, **Min Body/Range Ratio**: Set adaptive breakout thresholds based on volatility and volume.
- **OBV Smooth Length**: Smooths OBV momentum for breakout confirmation.
- **Enable VWAP Filter for Confirmations**: Optionally validate breakouts against the VWAP.
- **Enable Higher-TF Trend Filter** & **Trend Filter Timeframe**: Align breakout signals with the 1h/4h/Daily trend.
- **ADX Length**, **EMA Fast/Slow Length for Context**: Parameters for the context dashboard (Volatility, Trend, Volume).
- **Show Intraday VWAP Line**, **VWAP Line Color/Width**: Display the intraday VWAP line with custom style.
### Signal Interpretation Map
| Signal | Description | Recommended Action |
|--------------------------------|-----------------------------------------------------------|-------------------------------------------|
| 📌 **HH / LL (pivot)** | Market structure (support/resistance) | Note key levels |
| **Bull Trap(green diamond)** | Sweep down + volume spike + wick + rejection | Go long with trend filter
| **Bear Trap(red diamond)** | Sweep up + volume spike + wick + rejection | Go short with trend filter
| 🔵⬆️ **Breakout Confirmed Up** | Close > ATR‑scaled high + volume + OBV↑ | Go long with trend filter |
| 🔵⬇️ **Breakout Confirmed Down** | Close < ATR‑scaled low + volume + OBV↓ | Go short with trend filter |
| 📊 **VWAP Line** | Intraday reference to guide price | Use as dynamic support/resistance |
| ⚡ **Volatility** | ATR ratio High/Med/Low | Adjust position size |
| 📈 **Trend Context** | ADX+EMA Strong/Moderate/Weak | Confirm trend direction |
| 🔍 **Volume Context** | Breakout / Rising / Falling / Calm | Check volume momentum |
*This summary gives you a quick overview of the key settings and how to interpret signals for efficient intraday scalping.*
### Suggested Settings
- **Intraday Scalping (5m–15m)**
- `Swing Pivot Strength = 5`
- `VWMA Length for Trap Volume = 10`, `Volume Spike Multiplier = 1.6`
- `ATR Length for Trap = 7`
- `VWMA Length for Breakout Volume = 12`, `ATR Length for Breakout = 9`, `ATR Multiplier for Breakout = 0.5`
- `Min Body/Range Ratio for Breakout = 0.5`, `OBV Smooth Length = 7`
- `Enable Higher-TF Trend Filter = true` (TF = 60)
- `Show Intraday VWAP Line = true` (Color = orange, Width = 2)
- **Swing Trading (4h–Daily)**
- `Swing Pivot Strength = 10`
- `VWMA Length for Trap Volume = 20`, `Volume Spike Multiplier = 2.0`
- `ATR Length for Trap = 14`
- `VWMA Length for Breakout Volume = 30`, `ATR Length for Breakout = 14`, `ATR Multiplier for Breakout = 0.8`
- `Min Body/Range Ratio for Breakout = 0.7`, `OBV Smooth Length = 14`
- `Enable Higher-TF Trend Filter = true` (TF = D)
- `Show Intraday VWAP Line = false`
*Adjust these values based on the symbol and market volatility for optimal performance.*
RSI Divergence Strategy - AliferCryptoStrategy Overview
The RSI Divergence Strategy is designed to identify potential reversals by detecting regular bullish and bearish divergences between price action and the Relative Strength Index (RSI). It automatically enters positions when a divergence is confirmed and manages risk with configurable stop-loss and take-profit levels.
Key Features
Automatic Divergence Detection: Scans for RSI pivot lows/highs vs. price pivots using user-defined lookback windows and bar ranges.
Dual SL/TP Methods:
- Swing-based: Stops placed a configurable percentage beyond the most recent swing high/low.
- ATR-based: Stops placed at a multiple of Average True Range, with a separate risk/reward multiplier.
Long and Short Entries: Buys on bullish divergences; sells short on bearish divergences.
Fully Customizable: Input groups for RSI, divergence, swing, ATR, and general SL/TP settings.
Visual Plotting: Marks divergences on chart and plots stop-loss (red) and take-profit (green) lines for active trades.
Alerts: Built-in alert conditions for both bullish and bearish RSI divergences.
Detailed Logic
RSI Calculation: Computes RSI of chosen source over a specified period.
Pivot Detection:
- Identifies RSI pivot lows/highs by scanning a lookback window to the left and right.
- Uses ta.barssince to ensure pivots are separated by a minimum/maximum number of bars.
Divergence Confirmation:
- Bullish: Price makes a lower low while RSI makes a higher low.
- Bearish: Price makes a higher high while RSI makes a lower high.
Entry:
- Opens a Long position when bullish divergence is true.
- Opens a Short position when bearish divergence is true.
Stop-Loss & Take-Profit:
- Swing Method: Computes the recent swing high/low then adjusts by a percentage margin.
- ATR Method: Uses the current ATR × multiplier applied to the entry price.
- Take-Profit: Calculated as entry price ± (risk × R/R ratio).
Exit Orders: Uses strategy.exit to place bracket orders (stop + limit) for both long and short positions.
Inputs and Configuration
RSI Settings: Length & price source for the RSI.
Divergence Settings: Pivot lookback parameters and valid bar ranges.
SL/TP Settings: Choice between Swing or ATR method.
Swing Settings: Swing lookback length, margin (%), and risk/reward ratio.
ATR Settings: ATR length, stop multiplier, and risk/reward ratio.
Usage Notes
Adjust the Pivot Lookback and Range values to suit the volatility and timeframe of your market.
Use higher ATR multipliers for wider stops in choppy conditions, or tighten swing margins in trending markets.
Backtest different R/R ratios to find the balance between win rate and reward.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Trading carries significant risk and you may lose more than your initial investment. Always conduct your own research and consider consulting a professional before making any trading decisions.
Highest/Lowest Range in TimeframeThis script helps traders visually identify the highest high and lowest low within a customizable range of recent bars.
🔍 Key Features
Scans the last 100 to 1000 bars (user-defined)
Automatically detects:
The highest wick (high) and lowest wick (low)
Draws dotted green horizontal lines at both levels
Shows a label indicating the percentage range between high and low
Displays real-time high and low price labels directly on the chart
⚙️ Use Cases
Quickly spot price extremes over your desired time window
Visually measure market range and volatility
Identify breakout potential or reversal zones
✅ How to Use
Add the script to your chart.
Set the “Bars to Scan” input to your desired lookback period (between 100–1000).
Use the displayed lines and labels to identify key high/low price levels and range metrics.
Polygot Moving AveragesDescription
This is essentially a source merger of Bollinger Bands by Trading View and Simple Moving Averages by stoxxinbox. My additions and subtractions are minimal. There is the BB MA, which I default at 5d, and the other 4 averages are the standard 21, 50, 100, 200, day moving averages. I default the averaging method to WMA (Weighted Moving Average). The method of averaging can be changed as also can the lengths of the inputs to match user preferences. This is what I wanted for an indicator and didn't find.
Usage
The same as you would use any other BB or MA indicator. The benefit of this one is that it has 4 MAs, one MA with the Bollinger Bands attached, and the colours adjusted to be easy on the eyes when using high contrast themes, to be discernible yet sit quietly in the background with lines and candle sticks everywhere shouting for attention. I use it as a base first indicator which I can hide easily (imagine hiding five MA indicators individually constantly) when the more serious indicators come into play.
Uptrick: Dynamic Z-Score DeviationOverview
Uptrick: Dynamic Z‑Score Deviation is a trading indicator built in Pine Script that combines statistical filters and adaptive smoothing to highlight potential reversal points in price action. It combines a hybrid moving average, dual Z‑Score analysis on both price and RSI, and visual enhancements like slope‑based coloring, ATR‑based shadow bands, and dynamically scaled reversal signals.
Introduction
Statistical indicators like Z‑Scores measure how far a value deviates from its average relative to the typical variation (standard deviation). Standard deviation quantifies how dispersed a set of values is around its mean. A Z‑Score of +2 indicates a value two standard deviations above the mean, while -2 is two below. Traders use Z‑Scores to spot unusually high or low readings that may signal overbought or oversold conditions.
Moving averages smooth out price data to reveal trends. The Arnaud Legoux Moving Average (ALMA) reduces lag and noise through weighted averaging. A Zero‑Lag EMA (approximated here using a time‑shifted EMA) seeks to further minimize delay in following price. The RSI (Relative Strength Index) is a momentum oscillator that measures recent gains against losses over a set period.
ATR (Average True Range) gauges market volatility by averaging the range between high and low over a lookback period. Shadow bands built using ATR give a visual mood of volatility around a central trend line. Together, these tools inform a dynamic but statistically grounded view of market extremes.
Purpose
The main goal of this indicator is to help traders spot short‑term reversal opportunities on lower timeframes. By requiring both price and momentum (RSI) to exhibit statistically significant deviations from their norms, it filters out weak setups and focuses on higher‑probability mean‑reversion zones. Reversal signals appear when price deviates far enough from its hybrid moving average and RSI deviates similarly in the same direction. This makes it suitable for discretionary traders seeking clean entry cues in volatile environments.
Originality and Uniqueness
Uptrick: Dynamic Z‑Score Deviation distinguishes itself from standard reversal or mean‑reversion tools by combining several elements into a single framework:
A composite moving average (ALMA + Zero‑Lag EMA) for a smooth yet responsive baseline
Dual Z‑Score filters on price and RSI rather than relying on a single measure
Adaptive visual elements, including slope‑aware coloring, multi‑layer ATR shadows, and signal sizing based on combined Z‑Score magnitude
Most indicators focus on one aspect—price envelopes or RSI thresholds—whereas Uptrick: Dynamic Z‑Score Deviation requires both layers to align before signaling. Its visual design aids quick interpretation without overwhelming the chart.
Why these indicators were merged
Every component in Uptrick: Dynamic Z‑Score Deviation has a purpose:
• ALMA: provides a smooth moving average with reduced lag and fewer false crossovers than a simple SMA or EMA.
• Zero‑Lag EMA (ZLMA approximation): further reduces the delay relative to price by applying a time shift to EMA inputs. This keeps the composite MA closer to current price action.
• RSI and its EMA filter: RSI measures momentum. Applying an EMA filter on RSI smooths out false spikes and confirms genuine overbought or oversold momentum.
• Dual Z‑Scores: computing Z‑Scores on both the distance between price and the composite MA, and on smoothed RSI, ensures that signals only fire when both price and momentum are unusually stretched.
• ATR bands: using ATR‑based shadow layers visualizes volatility around the MA, guiding traders on potential support and resistance zones.
At the end, these pieces merge into a single indicator that detects statistically significant mean reversions while staying adaptive to real‑time volatility and momentum.
Calculations
1. Compute ALMA over the chosen MA length, offset, and sigma.
2. Approximate ZLMA by applying EMA to twice the price minus the price shifted by the MA length.
3. Calculate the composite moving average as the average of ALMA and ZLMA.
4. Compute raw RSI and smooth it with ALMA. Apply an EMA filter to raw RSI to reduce noise.
5. For both price and smoothed RSI, calculate the mean and standard deviation over the Z‑Score lookback period.
6. Compute Z‑Scores:
• z_price = (current price − composite MA mean) / standard deviation of price deviations
• z_rsi = (smoothed RSI − mean RSI) / standard deviation of RSI
7. Determine reversal conditions: both Z‑Scores exceed their thresholds in the same direction, RSI EMA is in oversold/overbought zones (below 40 or above 60), and price movement confirms directionality.
8. Compute signal strength as the sum of the absolute Z‑Scores, then classify into weak, medium, or strong.
9. Calculate ATR over the chosen period and multiply by layer multipliers to form shadow widths.
10.Derive slope over the chosen slope length and color the MA line and bars based on direction, optionally smoothing color transitions via EMA on RGB channels.
How this indicator actually works
1. The script begins by smoothing price data with ALMA and approximating a zero‑lag EMA, then averaging them for the main MA.
2. RSI is calculated, then smoothed and filtered.
3. Using a rolling window, the script computes statistical measures for both price deviations and RSI.
4. Z‑Scores tell how far current values lie from their recent norms.
5. When both Z‑Scores cross configured thresholds and momentum conditions align, reversal signals are flagged.
6. Signals are drawn with size and color reflecting strength.
7. The MA is plotted with dynamic coloring; ATR shadows are layered beneath to show volatility envelopes.
8. Bars can be colored to match MA slope, reinforcing trend context.
9. Alert conditions allow automated notifications when signals occur.
Inputs
Main Length: Main MA Length. Sets the period for ALMA and ZLMA.
RSI Length: RSI Length. Determines the lookback for momentum calculations.
Z-Score Lookback: Z‑Score Lookback. Window for mean and standard deviation computations.
Price Z-Score Threshold: Price Z‑Score Threshold. Minimum deviation required for price.
RSI Z-Score threshold: RSI Z‑Score Threshold. Minimum deviation required for momentum.
RSI EMA Filter Length: RSI EMA Filter Length. Smooths raw RSI readings.
ALMA Offset: Controls ALMA’s focal point in the window.
ALMA Sigma: Adjusts ALMA’s smoothing strength.
Show Reversal Signals : Toggle to display reversal signal markers.
Slope Sensitivity: Length for slope calculation. Higher values smooth slope changes.
Use Bar Coloring: Enables coloring of price bars based on MA slope.
Show MA Shadow: Toggle for ATR‑based shadow bands.
Shadow Layer Count: Number of shadow layers (1–4).
Base Shadow ATR Multiplier: Multiplier for ATR when sizing the first band.
Smooth Color Transitions (boolean): Smooths RGB transitions for line and shadows, if enabled.
ATR Length for Shadow: ATR Period for computing volatility bands.
Use Dynamic Signal Size: Toggles dynamic scaling of reversal symbols.
Features
Moving average smoothing: a hybrid of ALMA and Zero‑Lag EMA that balances responsiveness and noise reduction.
Slope coloring: MA line and optionally price bars change color based on trend direction; color transitions can be smoothed for visual continuity.
ATR shadow layers: translucent bands around the MA show volatility envelopes; up to four concentric layers help gauge distance from normal price swings.
Dual Z‑Score filters: price and momentum must both deviate beyond thresholds to trigger signals, reducing false positives.
Dynamic signal sizing: reversal markers scale in size based on the combined Z‑Score magnitude, making stronger signals more prominent.
Adaptive visuals: optional smoothing of color channels creates gradient effects on lines and fills for a polished look.
Alert conditions: built‑in buy and sell alerts notify traders when reversal setups emerge.
Conclusion
Uptrick: Dynamic Z‑Score Deviation delivers a structured way to identify short‑term reversal opportunities by fusing statistical rigor with adaptive smoothing and clear visual cues. It guides traders through multiple confirmation layers—hybrid moving average, dual Z‑Score analysis, momentum filtering, and volatility envelopes—while keeping the chart clean and informative.
Disclaimer
This indicator is provided for informational and educational purposes only and does not constitute financial advice. Trading carries risk and may not be suitable for all participants. Past performance is not indicative of future results. Always do your own analysis and risk management before making trading decisions.
Bullish and Bearish Breakout Alert for Gold Futures PullbackBelow is a Pine Script (version 6) for TradingView that includes both bullish and bearish breakout conditions for my intraday trading strategy on micro gold futures (MGC). The strategy focuses on scalping two-legged pullbacks to the 20 EMA or key levels with breakout confirmation, tailored for the Apex Trader Funding $300K challenge. The script accounts for the Daily Sentiment Index (DSI) at 87 (overbought, favoring pullbacks). It generates alerts for placing stop-limit orders for 175 MGC contracts, ensuring compliance with Apex’s rules ($7,500 trailing threshold, $20,000 profit target, 4:59 PM ET close).
Script Requirements
Version: Pine Script v6 (latest for TradingView, April 2025).
Purpose:
Bullish: Alert when price breaks above a rejection candle’s high after a two-legged pullback to the 20 EMA in a bullish trend (price above 20 EMA, VWAP, higher highs/lows).
Bearish: Alert when price breaks below a rejection candle’s low after a two-legged pullback to the 20 EMA in a bearish trend (price below 20 EMA, VWAP, lower highs/lows).
Context: 5-minute MGC chart, U.S. session (8:30 AM–12:00 PM ET), avoiding overbought breakouts above $3,450 (DSI 87).
Output: Alerts for stop-limit orders (e.g., “Buy: Stop=$3,377, Limit=$3,377.10” or “Sell: Stop=$3,447, Limit=$3,446.90”), quantity 175 MGC.
Apex Compliance: 175-contract limit, stop-losses, one-directional news trading, close by 4:59 PM ET.
How to Use the Script in TradingView
1. Add Script:
Open TradingView (tradingview.com).
Go to “Pine Editor” (bottom panel).
Copy the script from the content.
Click “Add to Chart” to apply to your MGC 5-minute chart .
2. Configure Chart:
Symbol: MGC (Micro Gold Futures, CME, via Tradovate/Apex data feed).
Timeframe: 5-minute (entries), 15-minute (trend confirmation, manually check).
Indicators: Script plots 20 EMA and VWAP; add RSI (14) and volume manually if needed .
3. Set Alerts:
Click the “Alert” icon (bell).
Add two alerts:
Bullish Breakout: Condition = “Bullish Breakout Alert for Gold Futures Pullback,” trigger = “Once Per Bar Close.”
Bearish Breakout: Condition = “Bearish Breakout Alert for Gold Futures Pullback,” trigger = “Once Per Bar Close.”
Customize messages (default provided) and set notifications (e.g., TradingView app, SMS).
Example: Bullish alert at $3,377 prompts “Stop=$3,377, Limit=$3,377.10, Quantity=175 MGC” .
4. Execute Orders:
Bullish:
Alert triggers (e.g., stop $3,377, limit $3,377.10).
In TradingView’s “Order Panel,” select “Stop-Limit,” set:
Stop Price: $3,377.
Limit Price: $3,377.10.
Quantity: 175 MGC.
Direction: Buy.
Confirm via Tradovate.
Add bracket order (OCO):
Stop-loss: Sell 175 at $3,376.20 (8 ticks, $1,400 risk).
Take-profit: Sell 87 at $3,378 (1:1), 88 at $3,379 (2:1) .
Bearish:
Alert triggers (e.g., stop $3,447, limit $3,446.90).
Select “Stop-Limit,” set:
Stop Price: $3,447.
Limit Price: $3,446.90.
Quantity: 175 MGC.
Direction: Sell.
Confirm via Tradovate.
Add bracket order:
Stop-loss: Buy 175 at $3,447.80 (8 ticks, $1,400 risk).
Take-profit: Buy 87 at $3,446 (1:1), 88 at $3,445 (2:1) .
5. Monitor:
Green triangles (bullish) or red triangles (bearish) confirm signals.
Avoid bullish entries above $3,450 (DSI 87, overbought) or bearish entries below $3,296 (support) .
Close trades by 4:59 PM ET (set 4:50 PM alert) .
Momentum + Keltner Stochastic Combo)The Momentum-Keltner-Stochastic Combination Strategy: A Technical Analysis and Empirical Validation
This study presents an advanced algorithmic trading strategy that implements a hybrid approach between momentum-based price dynamics and relative positioning within a volatility-adjusted Keltner Channel framework. The strategy utilizes an innovative "Keltner Stochastic" concept as its primary decision-making factor for market entries and exits, while implementing a dynamic capital allocation model with risk-based stop-loss mechanisms. Empirical testing demonstrates the strategy's potential for generating alpha in various market conditions through the combination of trend-following momentum principles and mean-reversion elements within defined volatility thresholds.
1. Introduction
Financial market trading increasingly relies on the integration of various technical indicators for identifying optimal trading opportunities (Lo et al., 2000). While individual indicators are often compromised by market noise, combinations of complementary approaches have shown superior performance in detecting significant market movements (Murphy, 1999; Kaufman, 2013). This research introduces a novel algorithmic strategy that synthesizes momentum principles with volatility-adjusted envelope analysis through Keltner Channels.
2. Theoretical Foundation
2.1 Momentum Component
The momentum component of the strategy builds upon the seminal work of Jegadeesh and Titman (1993), who demonstrated that stocks which performed well (poorly) over a 3 to 12-month period continue to perform well (poorly) over subsequent months. As Moskowitz et al. (2012) further established, this time-series momentum effect persists across various asset classes and time frames. The present strategy implements a short-term momentum lookback period (7 bars) to identify the prevailing price direction, consistent with findings by Chan et al. (2000) that shorter-term momentum signals can be effective in algorithmic trading systems.
2.2 Keltner Channels
Keltner Channels, as formalized by Chester Keltner (1960) and later modified by Linda Bradford Raschke, represent a volatility-based envelope system that plots bands at a specified distance from a central exponential moving average (Keltner, 1960; Raschke & Connors, 1996). Unlike traditional Bollinger Bands that use standard deviation, Keltner Channels typically employ Average True Range (ATR) to establish the bands' distance from the central line, providing a smoother volatility measure as established by Wilder (1978).
2.3 Stochastic Oscillator Principles
The strategy incorporates a modified stochastic oscillator approach, conceptually similar to Lane's Stochastic (Lane, 1984), but applied to a price's position within Keltner Channels rather than standard price ranges. This creates what we term "Keltner Stochastic," measuring the relative position of price within the volatility-adjusted channel as a percentage value.
3. Strategy Methodology
3.1 Entry and Exit Conditions
The strategy employs a contrarian approach within the channel framework:
Long Entry Condition:
Close price > Close price periods ago (momentum filter)
KeltnerStochastic < threshold (oversold within channel)
Short Entry Condition:
Close price < Close price periods ago (momentum filter)
KeltnerStochastic > threshold (overbought within channel)
Exit Conditions:
Exit long positions when KeltnerStochastic > threshold
Exit short positions when KeltnerStochastic < threshold
This methodology aligns with research by Brock et al. (1992) on the effectiveness of trading range breakouts with confirmation filters.
3.2 Risk Management
Stop-loss mechanisms are implemented using fixed price movements (1185 index points), providing definitive risk boundaries per trade. This approach is consistent with findings by Sweeney (1988) that fixed stop-loss systems can enhance risk-adjusted returns when properly calibrated.
3.3 Dynamic Position Sizing
The strategy implements an equity-based position sizing algorithm that increases or decreases contract size based on cumulative performance:
$ContractSize = \min(baseContracts + \lfloor\frac{\max(profitLoss, 0)}{equityStep}\rfloor - \lfloor\frac{|\min(profitLoss, 0)|}{equityStep}\rfloor, maxContracts)$
This adaptive approach follows modern portfolio theory principles (Markowitz, 1952) and Kelly criterion concepts (Kelly, 1956), scaling exposure proportionally to account equity.
4. Empirical Performance Analysis
Using historical data across multiple market regimes, the strategy demonstrates several key performance characteristics:
Enhanced performance during trending markets with moderate volatility
Reduced drawdowns during choppy market conditions through the dual-filter approach
Optimal performance when the threshold parameter is calibrated to market-specific characteristics (Pardo, 2008)
5. Strategy Limitations and Future Research
While effective in many market conditions, this strategy faces challenges during:
Rapid volatility expansion events where stop-loss mechanisms may be inadequate
Prolonged sideways markets with insufficient momentum
Markets with structural changes in volatility profiles
Future research should explore:
Adaptive threshold parameters based on regime detection
Integration with additional confirmatory indicators
Machine learning approaches to optimize parameter selection across different market environments (Cavalcante et al., 2016)
References
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L., Nobrega, J. P., & Oliveira, A. L. (2016). Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications, 55, 194-211.
Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (2000). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.
Kaufman, P. J. (2013). Trading systems and methods (5th ed.). John Wiley & Sons.
Kelly, J. L. (1956). A new interpretation of information rate. The Bell System Technical Journal, 35(4), 917-926.
Keltner, C. W. (1960). How to make money in commodities. The Keltner Statistical Service.
Lane, G. C. (1984). Lane's stochastics. Technical Analysis of Stocks & Commodities, 2(3), 87-90.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228-250.
Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. New York Institute of Finance.
Pardo, R. (2008). The evaluation and optimization of trading strategies (2nd ed.). John Wiley & Sons.
Raschke, L. B., & Connors, L. A. (1996). Street smarts: High probability short-term trading strategies. M. Gordon Publishing Group.
Sweeney, R. J. (1988). Some new filter rule tests: Methods and results. Journal of Financial and Quantitative Analysis, 23(3), 285-300.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
VolVolVolVol: Volatility & Volume
The indicator consists of 3 oscillating components that are all represented on a positive/negative percentage scale.
Direction : Green/Red shaded area
Smoothened distance between Close and EMA of Close relative to StDev of Close
Intensity : Turquoise line
If direction = bullish: Smoothened distance between Low and EMA of Low relative to StDev of Low
If direction = bearish: Smoothened distance between High and EMA of High relative to StDev of High
Momentum : Fuchsia line
Double exponential average of bullish closing volume - bearish closing volume
The indicator provides the following signals on the candlestick charts based on the above components' movements.
Bullish position signals: Below candles
Bearish position signals: Above candles
Entry signal : Increase in all 3 factors or sharp increase in Intensity + Momentum
Add signal : Trend slowdown because of volume drop or retracement following a temporary consolidation
Exit signal : Increase in Intensity and Momentum against the prevailing trend direction
There may be simultaneous Bullish and Bearish signals. These should be treated as hedges for existing positions.
Daily ATR BandsATR Finder – Volatility Scanner for Smarter Trade Setups
The ATR Finder is a precision tool designed to help traders quickly identify high-volatility assets using the Average True Range (ATR) – a key metric in assessing market momentum and potential breakout zones. By automatically scanning and highlighting tickers or candles with elevated ATR values relative to their recent historical range, this indicator helps you filter for setups that are more likely to experience significant price moves.
Whether you're a day trader seeking intraday momentum or a swing trader looking for setups with strong follow-through potential, the ATR Finder cuts through the noise and visually signals which assets are "on the move." It can be paired with other indicators or price action tools to create a high-conviction trading strategy focused on volatility expansion.
Key Features:
Dynamic ATR Calculation over a user-defined period
Visual Alerts or Color-Coding for above-threshold volatility spikes
Supports Multiple Timeframes for both short- and long-term volatility analysis
Great for spotting breakout opportunities, gap continuations, or trend reversals
Use the ATR Finder to stay ahead of price action and build a watchlist that moves with purpose. Perfect for scalpers, breakout traders, and anyone who respects the power of volatility.
Fibonacci Levels with MACD ConfirmationHow to Understand and Use the Fibonacci Levels with MACD Confirmation Script
This custom Pine Script is designed to give traders a clear visual framework by combining dynamic Fibonacci retracement levels, MACD histogram confirmation, and volatility-based swing zones. It aims to simplify trend analysis, improve entry timing, and adapt to various market conditions.
How to Interpret the 23.6% & 61.8% Labels
These Fibonacci levels represent key retracement zones where price often reacts during trend pullbacks or reversals.
The 23.6% level indicates a shallow retracement, useful in strong trends where price resumes early.
The 61.8% level is a deeper retracement, often a "last line of defense" before trend invalidation.
The script labels these zones with "CC 23.6" and "CC 61.8" when the price crosses them with MACD histogram confirmation:
Green label (CC) = bullish confirmation
Red label (CC) = bearish confirmation
How to Modify Inputs (Manual Adjustments)
Input Purpose Default How to Use
ATR Period Measures volatility 14 Increase for smoother, slower reactions; reduce for faster swings
Min Lookback Minimum bars for swing zone 20 Avoids short-term noise
Max Lookback Cap for swing zone scan 100 Avoids excessively wide retracement levels
Inverse Candle Chart Flips high/low logic false Enable for inverted analysis or backtesting "opposite logic"
How to Use the Inverse Candle Chart Option
Activating inverse mode flips candle logic:
Highs become negative lows, and vice versa.
Useful for:
Contrarian analysis
Inverse ETFs or short-biased views
Backtesting reverse-pattern behavior
How to Adjust the Style
You can manually personalize the script’s visual appearance:
Change line width in plot(..., linewidth=2) for bolder or thinner Fib levels.
Change colors from color.green, color.red, etc., to suit your theme.
Modify label.size, label.style, and label.color for different labeling visuals.
Customize MACD histogram style from plot.style_columns to other styles like style_histogram.
How the MACD is Set and Displayed
The MACD uses non-standard values:
Fast Length = 24
Slow Length = 52
Signal Smoothing = 18
These values slow down the indicator, reducing noise and aligning better with medium- to long-term trends.
MACD histogram is plotted directly on the main chart for faster, on-screen decision making.
Color-coded histogram:
Green/Lime = Bullish momentum increasing or steady
Red/Maroon = Bearish momentum increasing or steady
How to Use the Indicator in Real-World Trading
This indicator is most effective when used to:
✅ 1. Spot High-Probability Trend Continuation Zones
In a strong trend, price will often retrace to 23.6% or 61.8%, then resume.
Wait for:
Price to cross 23.6 or 61.8
MACD histogram rising (bullish) or falling (bearish)
"CC 23.6" or "CC 61.8" label to appear
🟢 Entry Example: Price retraces to Fib 61.8%, crosses up with green MACD histogram → take long position
✅ 2. Validate Reversal or Breakout Zones
These Fib levels also act as support/resistance.
If price crosses a Fib level but MACD fails to confirm, it may be a fake breakout.
Use confirmation labels only when MACD aligns.
✅ 3. Add Volatility Context (ATR) for Risk Management
The ATR label shows both value and %.
Use ATR to:
Set dynamic stop-losses (e.g., 1.5x ATR below entry)
Decide trade size based on volatility
How to Combine the Indicator With Other Tools
You can combine this script with other technical tools for a powerful trading framework:
🔁 With Moving Averages
Use 50/200 MA for overall trend direction
Take signals only in the direction of MA slope
🔄 With Price Action Patterns
Use the Fib/MACD signals at confluence points:
Support/resistance zones
Breakout retests
Candlestick patterns (pin bars, engulfing)
🔺 With Volume or Order Flow
Combine with volume spikes or order book signals
Confirm that Fib/MACD signals align with strong volume for conviction
✅ Trade Setup Summary
Criteria Long Setup Short Setup
Price at Fib Level At or crossing Fib 23.6 / 61.8 Same
MACD Histogram Rising and above previous bar Falling and below previous bar
Label Appears Green "CC 23.6" or "CC 61.8" Red "CC 23.6" or "CC 61.8"
Optional Filters Trend direction, ATR range, volume, price pattern Same
Impulse Volume Oscillator [Alpha Extract]Impulse Volume Oscillator
A sophisticated indicator designed to identify market impulse moves and volume-based momentum shifts, helping traders capture significant price movements with precision.
Combining price deviations with volume analysis, this oscillator dynamically measures market strength and weakness, providing clear signals for potential trend continuations and reversals.
🔶 Volume-Adjusted Normalization
Utilizes a unique normalization technique that incorporates volume impact to enhance signal quality. This approach ensures the indicator responds more strongly to high-volume price movements while filtering out low-volume noise.
vol_ratio = ta.rsi(volume, 14) / 50
vol_factor = vol_impact > 0 ? 1 + (vol_ratio - 1) * vol_impact : 1
raw_normalized = dev / (ta.stdev(source, bars) * mult)
vol_adjusted = raw_normalized * vol_factor
normalized = ta.sma(vol_adjusted, smooth)
🔶 Adaptive Regime Detection
Incorporates threshold-based regime identification that clearly distinguishes between trending and mean-reverting market conditions. The customizable threshold system allows traders to adapt to different market volatilities and timeframes.
🔶 Customizable Parameters
Fine-tune detection sensitivity with adjustable inputs for lookback period, standard deviation multiplier, volume impact, and signal smoothing. These parameters enable traders to optimize the indicator for various trading styles and market conditions.
❓How It Works
🔶 Impulse Calculation
The oscillator measures price deviation from a moving average baseline, normalized by standard deviation, and then adjusts the signal based on relative volume strength. This creates a responsive yet stable indicator that accurately reflects market momentum.
// Calculate the basis using the selected MA
basis = get_ma(source, bars)
// Calculate the normalized value with volume impact
dev = source - basis
🔶 Dynamic Visualization
The histogram changes color based on signal strength, providing instant visual cues about market conditions. Green bars indicate positive momentum while red bars represent negative momentum, with color intensity reflecting signal strength.
🔶 Trend Confirmation
Built-in trend direction analysis provides confluence with the primary signal, helping traders distinguish between counter-trend bounces and genuine trend reversals. This dual-confirmation approach significantly reduces false signals.
🔶 Visual Alerts & Boundary Tracking
Monitors signal extremes and dynamically adjusts visualization transparency based on signal strength. The indicator highlights particularly strong impulse moves with background shading, making potential trading opportunities immediately apparent.
🔶 Custom Candle Coloring
Optional candle coloring applies the same color logic as the histogram directly to price candles, providing a unified visual framework that helps traders correlate indicator signals with price action.
🔶 Momentum Shift Detection
Automatically identifies important zero-line crossovers that often signify the beginning of new impulse moves. These transition points frequently offer favorable risk/reward entry opportunities.
🔶 Snapshot samples
1 Week
1 Day
15 Min
🔶 Why Choose AE - Impulse Volume Oscillator?
This indicator provides a comprehensive approach to identifying significant market moves by combining volume analysis with price momentum. By offering clear visual signals for both trend continuation and reversal scenarios, it empowers traders to make more informed decisions across various market conditions and timeframes.
Chandelier Exit with ZLSMA SwiftEdgeChandelier Exit with ZLSMA
Overview
The "Chandelier Exit with ZLSMA" indicator is a powerful trading tool designed to identify trend reversals and high-probability entry points in financial markets. By combining the volatility-based Chandelier Exit with the low-lag Zero Lag Least Squares Moving Average (ZLSMA), this indicator provides clear Buy and Sell signals, enhanced with a unique signal strength score to help traders prioritize high-quality opportunities. Visual enhancements, including dynamic color coding, background highlights, and trend arrows, make it intuitive and visually appealing for both novice and experienced traders.
What It Does
This indicator generates Buy and Sell signals when a trend reversal is detected by the Chandelier Exit, but only if the price crosses the ZLSMA for the first time in the direction of the trend. Each signal is accompanied by a percentage score (0-100%) that measures its strength based on price movement and momentum. The indicator overlays directly on the price chart, displaying:
Buy/Sell labels with signal strength (e.g., "Buy (85%)").
A ZLSMA line that changes color (green for bullish, red for bearish) to indicate trend direction.
Background highlights to mark signal candles.
Trend arrows to visually confirm signal points.
How It Works
The indicator combines two complementary components:
Chandelier Exit:
Uses the Average True Range (ATR) to create dynamic trailing stop levels (long_stop and short_stop) that adapt to market volatility.
Signals a Buy when the price crosses above the short stop (indicating a potential uptrend) and a Sell when it crosses below the long stop (indicating a potential downtrend).
Default settings use an ATR period of 1 and a multiplier of 2.0 for high sensitivity to short-term price movements.
Zero Lag LSMA (ZLSMA):
A low-lag moving average based on linear regression, designed to reduce delay compared to traditional moving averages.
Acts as a trend filter: Buy signals are only generated when the price closes above ZLSMA for the first time, and Sell signals when it closes below for the first time.
Default length of 50 balances smoothness with responsiveness.
Signal Strength Score:
Each signal is assigned a score (0-100%) based on:
Distance to ZLSMA (60% weight): How far the price is from ZLSMA, normalized by ATR. Larger distances indicate stronger breakouts.
Candlestick size (40% weight): The size of the signal candle, normalized by ATR. Larger candles suggest stronger momentum.
A high score (e.g., >80%) indicates a robust signal, while a low score (e.g., <50%) suggests caution.
Visual Features:
The ZLSMA line changes color (green for bullish, red for bearish) to reflect the trend.
Signal candles are highlighted with a subtle green (Buy) or red (Sell) background.
Tiny triangular arrows appear below Buy signals and above Sell signals for clear visual confirmation.
Why Combine Chandelier Exit and ZLSMA?
The Chandelier Exit excels at identifying trend reversals through volatility-based stops, but it can generate false signals in choppy markets due to its sensitivity (especially with a short ATR period of 1). The ZLSMA addresses this by acting as a trend filter, ensuring signals are only triggered when the price confirms a trend by crossing the ZLSMA for the first time. This combination reduces noise and focuses on high-probability setups. The signal strength score further enhances decision-making by quantifying the conviction behind each signal, making the indicator feel intuitive and "smart."
How to Use
Setup:
Add the indicator to your chart in TradingView.
Adjust inputs in the settings panel:
ATR Period (default: 1): Controls the sensitivity of Chandelier Exit. Increase for smoother signals.
ATR Multiplier (default: 2.0): Sets the distance of stop levels from price extremes.
ZLSMA Length (default: 50): Adjusts the smoothness of the ZLSMA line. Shorter lengths (e.g., 20-30) are more responsive; longer lengths (e.g., 50-100) are smoother.
Use Close Price for Extremums (default: true): Determines whether Chandelier Exit uses closing prices or high/low prices for calculations.
Interpreting Signals:
Buy Signal: A green "Buy (X%)" label appears below a candle when the price crosses above the Chandelier Exit short stop and closes above ZLSMA for the first time. The percentage indicates signal strength (higher = stronger).
Sell Signal: A red "Sell (X%)" label appears above a candle when the price crosses below the Chandelier Exit long stop and closes below ZLSMA for the first time.
Use the ZLSMA line’s color (green for bullish, red for bearish) to confirm the overall trend.
Prioritize signals with high strength scores (e.g., >70%) for better reliability.
Trading Considerations:
Combine signals with other analysis (e.g., support/resistance, volume) for confirmation.
Test the indicator on a demo account or use TradingView’s Strategy Tester to evaluate performance.
Be cautious with the default ATR period of 1, as it is highly sensitive and may generate frequent signals in volatile markets.
What Makes It Unique
This indicator stands out due to its thoughtful integration of Chandelier Exit and ZLSMA, creating a synergy that balances sensitivity with reliability. The first-cross filter ensures signals are triggered only at the start of potential trends, reducing false positives. The signal strength score adds a layer of intelligence, helping traders assess the quality of each signal without needing external tools. Visual enhancements, such as dynamic ZLSMA coloring, background highlights, and trend arrows, make the indicator user-friendly and visually engaging, appealing to traders seeking a modern, intuitive tool.
Limitations and Notes
The short ATR period (1) makes the indicator highly sensitive, which suits short-term traders but may produce noise in sideways markets. Increase the ATR period for smoother signals.
The signal strength score is a heuristic based on price movement and momentum, not a predictive model. Use it as a guide, not a definitive predictor.
Always backtest the indicator on your preferred market and timeframe to ensure it aligns with your trading strategy.
SwiftEdge NW EnvelopeSwiftEdge NW Envelope
Overview
The SwiftEdge NW Envelope is a visually striking technical indicator designed for traders seeking to identify high-probability buy and sell opportunities in volatile markets. By combining the Relative Strength Index (RSI), Average True Range (ATR), and Nadaraya-Watson Envelope, this indicator provides a unique blend of momentum, volatility, and non-linear trend analysis. Its futuristic, AI-inspired aesthetic—featuring neon gradients and dynamic colors—enhances chart readability while delivering actionable trading signals.
What It Does
The SwiftEdge NW Envelope generates buy and sell signals based on price interactions with dynamically calculated support and resistance bands, confirmed by RSI conditions. The indicator:
Plots a Nadaraya-Watson Envelope to identify smooth, non-linear price trends and dynamic support/resistance zones.
Uses ATR to scale the envelope’s bands, adapting to market volatility.
Employs RSI to confirm overbought/oversold conditions, ensuring signals align with momentum.
Visualizes signals with neon-colored markers, background zones, and labels for intuitive decision-making.
How It Works
The indicator integrates three key components:
Nadaraya-Watson Envelope:
A kernel-based regression technique that smooths price data to create a central trend line (mean) and dynamic upper/lower bands.
Unlike traditional moving averages, it provides a non-linear, adaptive view of price trends, making it ideal for capturing complex market movements.
The band width is determined by ATR, ensuring responsiveness to volatility.
Average True Range (ATR):
Measures market volatility to scale the envelope’s bands.
A multiplier (default: 0.5) adjusts the sensitivity of the bands, allowing traders to fine-tune the indicator for different assets or market conditions.
Relative Strength Index (RSI):
A momentum oscillator with a shortened period (default: 5) for increased sensitivity.
Confirms buy signals when RSI is oversold (default: <30) and sell signals when RSI is overbought (default: >70).
Signal Logic
Buy Signal: Triggered when the price crosses above the lower band of the Nadaraya-Watson Envelope and RSI is below the oversold threshold. Marked by a green circle and a "BUY" label below the candle.
Sell Signal: Triggered when the price crosses below the upper band and RSI is above the overbought threshold. Marked by a magenta circle and a "SELL" label above the candle.
Background Zones: Green (buy) or red (sell) translucent zones highlight signal areas for quick recognition.
Visual Features
Dynamic Colors: The central trend line shifts between cyan (uptrend), purple (downtrend), or gray (neutral) based on price position relative to the mean.
Neon Gradient Fill: A translucent blue fill between the upper (green) and lower (red) bands creates a glowing, futuristic effect.
Modern Signal Markers: Small, vibrant circles (green for buy, magenta for sell) and clear labels enhance visual clarity.
Why This Combination?
The SwiftEdge NW Envelope combines RSI, ATR, and Nadaraya-Watson Envelope to create a robust trading tool:
RSI provides momentum confirmation, filtering out false signals in choppy markets.
ATR ensures the envelope adapts to changing volatility, making it suitable for both trending and ranging markets.
Nadaraya-Watson Envelope offers a sophisticated, non-linear alternative to traditional bands (e.g., Bollinger Bands), capturing subtle price dynamics. Together, these components deliver a balanced approach to trend-following and mean-reversion strategies, with RSI acting as a gatekeeper to improve signal reliability.
Customize Settings:
RSI Period (5): Adjust for more/less sensitivity to momentum.
RSI Overbought/Oversold (70/30): Modify thresholds to tighten or loosen signal conditions.
ATR Period (14) and Multiplier (0.5): Tune volatility sensitivity.
NW Length (25), Bandwidth (8.0), Multiplier (3.0): Adjust the smoothness and width of the envelope.
Interpret Signals:
Buy: Look for green circles and "BUY" labels when price crosses above the lower band, confirmed by low RSI.
Sell: Look for magenta circles and "SELL" labels when price crosses below the upper band, confirmed by high RSI.
Use background zones to quickly spot active signal areas.
Combine with Other Tools:
Pair with support/resistance levels or volume analysis for additional confirmation.
Test signals on a demo account before live trading.
Originality
The SwiftEdge NW Envelope stands out due to:
Its innovative use of Nadaraya-Watson regression, a less common but powerful tool for non-linear trend analysis.
A unique visual design with neon gradients and dynamic colors, inspired by AI and futuristic interfaces, making it both functional and visually engaging.
A streamlined signal system that balances momentum (RSI), volatility (ATR), and trend (Nadaraya-Watson), reducing noise and enhancing trade precision.
Notes
Best suited for volatile markets (e.g., forex, crypto, stocks) where price swings create clear envelope breakouts.
Adjust input parameters to match your trading style (e.g., shorter RSI period for scalping, wider bands for swing trading).
Always backtest and validate signals in your specific market and timeframe before trading.
Multi Timeframe ATR, CCI & RSIMulti Timeframe ATR, CCI & RSI (MTF IND)
This indicator displays ATR, CCI, and RSI values from a custom selected timeframe in a clean table overlay.
It helps monitor volatility and momentum from higher/lower timeframes directly on your current chart.
Features:
• Select custom timeframe for all indicators (e.g., 1D, 1W, 65m, etc.)
• ATR with selectable smoothing type (RMA, SMA, EMA, WMA)
• CCI & RSI with trend arrows (▲ rising, ▼ falling, ▬ neutral)
• Compact summary table
