Box Chart Overlay StrategyExploring the Box Chart Overlay Strategy with RSI & Bollinger Confirmation
The “Box Chart Overlay Strategy by BD” is a sophisticated TradingView strategy script written in Pine Script (version 5). It combines a box charting method with two widely used technical indicators—Relative Strength Index (RSI) and Bollinger Bands—to generate trade entries. In this article, we break down the strategy’s components, its logic, and how it visually represents trading signals on the chart.
1. Strategy Setup and User Inputs
Strategy Declaration
At the top of the script, the strategy is declared with key parameters:
Overlay: The indicator is plotted directly on the price chart.
Initial Capital & Position Sizing: It uses a simulated trading account with an initial capital of 10,000 and positions sized as a percentage of equity (10% by default).
Commission: A commission of 0.1% is factored into trades.
Input Parameters
The strategy is highly customizable. Users can adjust various inputs such as:
Box Settings:
Box Size (RSboxSize): Defines the size of each price “box.”
Box Options: Choose from three modes:
Standard: Boxes are calculated continuously from the start of the chart.
Anchored: The first box is fixed at a specified time and price.
Daily Reset: The boxes reset each day based on a defined session time.
Color Customizations:
Options to customize the appearance of boxes, borders, labels, and even repainting the candles based on the current price’s relation to box levels.
RSI Settings:
Length, overbought, and oversold levels are set to filter trades.
Bollinger Bands Settings:
Users can set the length of the moving average and the multiplier for standard deviation, which will be used to compute the upper and lower bands.
2. The Box Chart Mechanism
Box Construction
The core idea of a box chart is to group price movement into discrete blocks—or boxes—of a fixed size. In this strategy:
Standard Mode:
The script calculates boxes starting at a rounded price level. When the price moves sufficiently above or below the current box’s boundaries, a new box is drawn.
Anchored and Daily Reset Modes:
These modes allow traders to control where the box calculations begin or to reset them during a specific intraday session.
Visual Elements
Several custom functions handle the visual components:
drawBoxUp() and drawBoxDn():
These functions create boxes in bullish or bearish directions respectively, based on whether the price has exceeded the current box’s high or low.
drawLines() and drawLabels():
Lines are drawn to extend the current box levels, and labels are updated to display key levels or the “remainder” (the difference needed to trigger a new box).
Projected Boxes:
A “projected” box is drawn to indicate potential upcoming box levels, providing an additional visual cue about the price action.
3. Integrating RSI and Bollinger Bands for Trade Confirmation
RSI Integration
The strategy computes the RSI using a user-defined length. It then uses the following conditions to validate entries:
Long Trades (Box Up):
The strategy waits for the RSI to be at or below the oversold level before considering a long entry.
Short Trades (Box Down):
It requires the RSI to be at or above the overbought level before triggering a short entry.
Bollinger Bands Confirmation
In addition to the RSI filter:
For Long Entries:
The price must be at or below the lower Bollinger Band.
For Short Entries:
The price must be at or above the upper Bollinger Band.
By combining these filters with the box breakout logic, the strategy aims to enhance the quality of its trade signals.
4. Dynamic Trade Entries and Alerts
Box Logic and Entry Functions
Two key functions—BoxUpFunc() and BoxDownFunc()—handle the creation of new boxes and also check if trade conditions are met:
When a new box is drawn, the script evaluates if the RSI and Bollinger conditions align.
If conditions are satisfied, the script places an entry order:
Long Entry: Initiated when the price moves upward, RSI indicates oversold, and the price touches or falls below the lower Bollinger Band.
Short Entry: Triggered when the price falls downward, RSI signals overbought, and the price touches or exceeds the upper Bollinger Band.
Alerts
Built-in alert functions notify traders when a new box level is reached. Users can set custom alert messages to ensure they are aware of potential trade opportunities as soon as the conditions are met.
5. Visual Enhancements and Candle Repainting
The script also includes options for repainting candles based on their relation to the current box’s boundaries:
Above, Below, or Within the Box:
Candles are color-coded using user-defined colors, making it easier to visually assess where the price is in relation to the box levels.
Labels and Lines:
These continuously update to reflect current levels and provide an immediate visual reference for potential breakout points.
Conclusion
The Box Chart Overlay Strategy by BD is a multi-faceted approach that marries the traditional box chart technique with modern technical indicators—RSI and Bollinger Bands—to refine entry signals. By offering various customization options for box creation, visual styling, and confirmation criteria, the strategy allows traders to adapt it to different market conditions and personal trading styles. Whether you prefer a continuously running “Standard” mode or a more controlled “Anchored” or “Daily Reset” approach, this strategy provides a robust framework for integrating price action with momentum and volatility measures.
Bantlar ve Kanallar
Kase Permission StochasticOverview
The Kase Permission Stochastic indicator is an advanced momentum oscillator developed from Kase's trading methodology. It offers enhanced signal smoothing and filtering compared to traditional stochastic oscillators, providing clearer entry and exit signals with fewer false triggers.
How It Works
This indicator calculates a specialized stochastic using a multi-stage smoothing process:
Initial stochastic calculation based on high, low, and close prices
Application of weighted moving averages (WMA) for short-term smoothing
Progressive smoothing through differential factors
Final smoothing to reduce noise and highlight significant trend changes
The indicator oscillates between 0 and 100, with two main components:
Main Line (Green): The smoothed stochastic value
Signal Line (Yellow): A further smoothed version of the main line
Signal Generation
Trading signals are generated when the main line crosses the signal line:
Buy Signal (Green Triangle): When the main line crosses above the signal line
Sell Signal (Red Triangle): When the main line crosses below the signal line
Key Features
Multiple Smoothing Algorithms: Uses a combination of weighted and exponential moving averages for superior noise reduction
Clear Visualization: Color-coded lines and background filling
Reference Levels: Horizontal lines at 25, 50, and 75 for context
Customizable Colors: All visual elements can be color-customized
Customization Options
PST Length: Base period for the stochastic calculation (default: 9)
PST X: Multiplier for the lookback period (default: 5)
PST Smooth: Smoothing factor for progressive calculations (default: 3)
Smooth Period: Final smoothing period (default: 10)
Trading Applications
Trend Confirmation: Use crossovers to confirm entries in the direction of the prevailing trend
Reversal Detection: Identify potential market reversals when crossovers occur at extreme levels
Range-Bound Markets: Look for oscillations between overbought and oversold levels
Filter for Other Indicators: Use as a confirmation tool alongside other technical indicators
Best Practices
Most effective in trending markets or during well-defined ranges
Combine with price action analysis for better context
Consider the overall market environment before taking signals
Use longer settings for fewer but higher-quality signals
The Kase Permission Stochastic delivers a sophisticated approach to momentum analysis, offering a refined perspective on market conditions while filtering out much of the noise that affects standard oscillators.
HTF Support & Resistance Zones📌 English Description:
HTF Support & Resistance Zones is a powerful indicator designed to auto-detect key support and resistance levels from higher timeframes (Daily, Weekly, Monthly, Yearly).
It displays the number of touches for each level and automatically classifies its strength (Weak – Strong – Very Strong) with full customization options.
✅ Features:
Auto-detection of support/resistance from HTFs
Strength calculation based on touch count
Clean visual display with color, size, and label customization
Ideal for scalping and intraday trading
📌 الوصف العربي:
مؤشر "HTF Support & Resistance Zones" يساعد المتداولين على تحديد أهم مناطق الدعم والمقاومة المستخرجة تلقائيًا من الفريمات الكبيرة (اليومي، الأسبوعي، الشهري، السنوي).
يعرض المؤشر عدد اللمسات لكل مستوى ويقيّم قوته تلقائيًا (ضعيف – قوي – قوي جدًا)، مع خيارات تخصيص كاملة للعرض.
✅ ميزات المؤشر:
دعم/مقاومة تلقائية من الفريمات الكبيرة
تقييم تلقائي لقوة المستويات بناءً على عدد اللمسات
عرض مرئي مرن مع تحكم بالألوان، الحجم، الشكل، والخلفية
مناسب للتداولات اليومية والسكالبينج
EMA Channel Key K-LinesEMA Channel Setup :
Three 32-period EMAs (high, low, close prices)
Visually distinct colors (red, blue, green)
Gray background between high and low EMAs
Key K-line Identification :
For buy signals: Close > highest EMA, K-line height ≥ channel height, body ≥ 2/3 of range
For sell signals: Close < lowest EMA, K-line height ≥ channel height, body ≥ 2/3 of range
Alternating signals only (no consecutive buy/sell signals)
Visual Markers :
Green "BUY" labels below key buy K-lines
Red "SELL" labels above key sell K-lines
Clear channel visualization
Logic Flow :
Tracks last signal direction to prevent consecutive same-type signals
Strict conditions ensure only significant breakouts are marked
All calculations based on your exact specifications
Fibonacci Sequence NumbersThe "Fibonacci Sequence Numbers" indicator overlays horizontal lines on a trading chart based on Fibonacci sequence values (0, 34, 55, 89, 144, 233, 377, 610) relative to a user-defined reference price and time. Users can specify the direction ("Above," "Below," or "Both") to plot these levels above and/or below the reference price, with customizable line length, width, and colors for each level (e.g., red for Level 0, blue for 34). A vertical dashed line marks the reference time, while horizontal lines extend rightward, accompanied by labeled annotations shifted slightly left for clear view.
[TABLE] Moving Average Stage Indicator Table📈 MA Stage Indicator Table
🧠 Overview:
This script analyzes market phases based on moving average (MA) crossovers, classifying them into 6 distinct stages and displaying statistical summaries for each.
🔍 Key Features:
• Classifies market condition into Stage 1 to Stage 6 based on the relationship between MA1 (short), MA2 (mid), and MA3 (long)
• Provides detailed stats for each stage:
• Average Duration
• Average Width (MA distance)
• Slope (Angle) - High / Low / Average
• Shows current stage details in real-time
• Supports custom date range filtering
• Choose MA type: SMA or EMA
• Optional background coloring for stages
• Clean summary table displayed on the chart
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy?
The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach.
It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation.
Ideal for swing traders seeking to ride strong trends while managing risk.
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How does the strategy work?
The strategy follows a systematic process to capture high-momentum breakouts:
Pre-Breakout Criteria:
Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles).
Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation.
Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend.
Price Break: Enters when price clears the consolidation high with conviction.
Risk Management:
Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside.
Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run.
Trailing Stop (Unique Edge):
Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms.
Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns.
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What markets or timeframes is this suited for?
This is a long-only strategy designed for trending markets, and it performs best in:
Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures).
Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends.
Key Advantage: The TradingView script allows instant backtesting with adjustable parameters
You can:
- Test historical performance across multiple markets to identify which assets align best with the strategy.
- Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile.
Build a diversified portfolio by filtering for markets that show consistent profitability in backtests.
For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently.
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What indicators or tools does the strategy use?
The strategy combines customizable technical tools with strict anti-lookahead safeguards:
Core Indicators:
Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets.
Breakout Parameters:
Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern.
Entry Models: Flexible entry logics (Breakouts and fractals)
Anti-Lookahead Design:
All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal.
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How do I manage risk with this strategy?
The strategy prioritizes customizable risk controls to align with your trading style and account size:
User-Defined Risk Inputs:
Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade.
Flexibility: Choose between fixed risk or equity-based scaling.
The script adjusts position sizing dynamically based on your selection.
Pyramiding Feature:
Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact.
Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk.
Risk-Free Trade Mechanic:
Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk.
The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable.
Impact on Net Profit & Drawdown:
Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach.
Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity.
Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly.
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How does the strategy identify market structure for its trailing stoploss?
The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
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What are the underlying calculations?
The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
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What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
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What type of break-even method is used in this strategy? What are the underlying calculations?
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
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What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What Makes This Strategy Unique?
This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical:
1. Adapts to Any Market Rhythm
Works on daily, weekly, or intraday charts without code changes.
Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts).
2. Smarter Stop-Loss System
No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages.
Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets.
3. Safe Profit-Boosting Pyramiding
Adds new positions only after prior trades are risk-free (stops moved above breakeven).
Scales up using locked-in profits, not new capital, to grow gains safely.
4. Built-In Momentum Check
Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
BB LevelsBB Levels — Volatility-Based Weekly Trading Ranges
Overview:
BB Levels is a multi-timeframe indicator that projects weekly trading ranges using historical price behavior and volatility modeling. It combines data from both the 4H and Daily timeframes to provide a dual-perspective view of expected price extremes.
Solid Lines → Based on the Daily timeframe (smoother, broader volatility)
Dashed Lines → Based on the 4H timeframe (finer, more reactive to short-term volatility)
How It Works:
The indicator employs a Markov Switching Model to estimate the prevailing market regime and generate a forecasted directional bias. It then applies average historical volatility to project a weekly range:
The centerline is a forecasted “zero level” based on the prior week’s close, adjusted by regime and trend forecast.
The upper and lower bounds are derived from average weekly volatility, scaled to reflect expected movement.
Two versions are shown:
Daily (solid): Represents the more conservative, long-term expectations.
4H (dashed): Captures short-term momentum and faster volatility shifts.
Important Note:
These levels represent statistical expectations, not fixed boundaries. Price may:
Consolidate within the dashed (4H) range during quiet periods
Break beyond the solid (Daily) range during news events or trending expansions
Designed For:
Swing traders seeking structured, volatility-adjusted weekly levels
Day traders targeting high-probability reversal zones
Strategists combining trend forecasting with expected price behavior
ADR Nivele Horizontale dhe EMAThe user provided a Pine Script code for an indicator called "ADR Nivele Horizontale dhe EMA". The task is to explain how this code works. Hmm, first, I need to understand what this indicator does. The title mentions ADR levels and EMA, so it's probably combining horizontal lines based on Average Daily Range and some Exponential Moving Averages.
Looking at the code, the first part is the indicator declaration with version 6. The settings include an ADR period, levels above and below the mid, and line style. Then there's a section for calculations. They request daily high and low to compute the daily range. The ADR is the SMA of the daily range over the specified period. The mid is the average of daily high and low. The adr_val is half of ADR, maybe to create symmetrical levels around the mid.
Next, they create arrays for lines and labels above and below the mid. The loops go from 1 to levels_above/below, calculate each level, draw lines and labels. The mid line is also drawn with a different color. Then, there are several EMAs plotted: 13, 50, 200, 400, 600, 800, each with different colorsWait, but in Pine Script, when you use arrays to store lines and labels, you have to manage them properly to avoid repainting or memory issues. The code uses array.concat to add new lines and labels each bar. However, since this code is running on each bar, the for loops might be creating multiple lines each time, leading to too many objects. Oh right, but they use var to initialize the arrays, so they are only initialized once. Wait, no. The var keyword initializes the variable once, but in each iteration, they are concatenating new lines. Wait, no: the for loops are inside the main script, which runs on each bar. So every time a new bar is processed, the loops will run again, adding new lines and labels. That's a problem because each bar would create new lines, leading to an ever-increasing number of lines, which could hit the maximum limit (max_lines_count is set to 20, but maybe they have more bars). Oh, the indicator has max_lines_count=20, but the code might be creating multiple lines per bar. So maybe the code isn't handling the line management correctly. For example, if levels_above is 2, then each bar would create 2 new lines above and 2 below, plus the mid line. Over 20 bars, that's way over 20 lines. So this could cause the indicator to stop drawing after 20 lines. The user might not have realized that the lines are being recreated every bar, leading to a buildup. But perhaps the original code intended to have the lines update each bar, extending to the current bar. Let's see: in line.new, they use bar_index as the starting x1 and bar_index as x2. So each line is drawn from the previous bar's index to the current one. But since this is done on every bar, each line is only one bar long. Wait, no. Because on each new bar, the code creates a new line from the previous bar's index (bar_index , which is now the bar before the current one) to the current bar_index. So each line is just a segment from the previous bar to the current bar. But when the next bar comes, a new line is created again. So the result is that each level line is a series of one-bar-length segments, which might not be intended. The user probably wants continuous lines that extend from the left to the right, not just per bar. So this approach is incorrect. The correct way would be to have a line that starts at the first bar of the calculation and extends to the right, updating each bar. But the current code creates a new line each bar, leading to multiple short lines instead of one continuous line. That's a mistake.
So the main issue here is that the code is generating a new line segment for each bar, which is not efficient and would quickly hit the line limit. To fix this, instead of creating a new line every bar, they should create the line once and then update its position each bar. But in Pine Script, you can't directly update a line after it's created; instead, you need to track the line ID and use line.set_xy() to extend it. However, the current code uses array.concat to add new lines each bar, which isn't the right approach.
Therefore, the code as written will create multiple short lines instead of continuous horizontal lines. The correct approach for horizontal levels that extend to the right is to create the line once, starting at a certain bar and extending indefinitely, or to update the line's end point each new bar. But in Pine Script, you can't extend lines infinitely; you have to manage them each bar. Alternatively, using the 'line.extend' style might help, but I think the original code's logic is flawed here.
Additionally, the EMA part is straightforward: plotting multiple EMAs with different periods. That part should work as expected.
So the explanation should mention that the ADR levels are calculated based on the daily high and low, then the code attempts to draw horizontal lines above and below the mid-point. However, the way the lines are drawn may lead to multiple short segments instead of continuous lines, potentially causing performance issues or hitting the maximum line count. The EMAs are plotted correctly with various periods..
Multi-TF Support LevelsThe Multi-TF Support Levels indicator identifies and displays key support levels based on swing lows across three user-selected timeframes.
How it works:
Input Parameters:
Lookback Period (100) — historical depth to search for swing lows.
Timeframe 1-3 (15, 45, 240) — three timeframes (e.g., 15min, 45min, 4hr).
Logic:
For each timeframe, a swing low is detected: the lowest price within the lookback period that is also lower than the two preceding candles.
Support levels update dynamically when new swing lows are formed.
The most recent levels are plotted as horizontal cross marks (blue, red, green for each timeframe).
Purpose: Visualize significant support zones from multiple timeframes to identify confluent areas for trading decisions.
Индикатор Multi-TF Support Levels (Мультитаймфреймовые уровни поддержки) определяет и отображает ключевые уровни поддержки на основе минимумов свингов (swing lows) на трёх выбранных таймфреймах.
Как работает:
Входные параметры:
Lookback Period (100) — глубина анализа для поиска минимумов.
Timeframe 1-3 (15, 45, 240) — три таймфрейма (например, 15 минут, 45 минут, 4 часа).
Логика:
Для каждого таймфрейма определяется свинг-минимум: цена, которая является самой низкой за период lookback и ниже двух предыдущих свечей.
Уровни поддержки обновляются при появлении новых свинг-минимумов.
Последние актуальные уровни отображаются на графике в виде горизонтальных линий-крестиков (синий, красный, зелёный для каждого таймфрейма).
Цель: Визуализировать значимые уровни поддержки с разных таймфреймов для поиска зон "конфлюэнса".
Intraday Trend LinesTradingView Indicator Description: Options-Based Swing Range Forecast
Core Mechanism
This indicator calculates expected price swing ranges for key assets using daily post-market options block trade data, projecting high (resistance) and low (support) levels for:
Next Trading Day (T+1)
Two Days Ahead (T+2)
End of Current Week (Friday)
End of Next Week (Next Friday)
Dual horizontal lines connect the prediction start time (16:00 EST) to the target date's close time (16:00 EST), marking the forecasted range.
Supported Assets
Direct Calculation Indirect Derivation*
SPY SPX (via SPY data)
IWM NDX (via QQQ data)
QQQ IXIC (via QQQ data)
DIA RUT (via IWM data)
TLT SOX
*Indices derived from ETF options data using volatility conversion.
Key Features
Dynamic Updates:
New ranges calculated daily after market close.
Click the 🌀 Refresh button next to the indicator name to load latest data.
Visual Clarity:
Resistance (blue) and support (purple) lines with semi-transparent labels.
Hover labels show date range and swing metrics (e.g., Swing: 36.1 (2.5%)).
Algorithm Basis
Options Gamma Exposure: Identifies high gamma strike clusters.
Volatility Surface Fitting: Derives expected move boundaries.
ETF-to-Index Conversion: SPX/NDX/IXIC ranges scaled from SPY/QQQ data.
Usage Notes
⚠️ Critical Reminders:
SPX/NDX/IXIC: Ranges inferred from ETF liquidity (not direct options data).
Intraday Expiry: Lines auto-expire at 16:00 EST on target dates.
Market Risks: Ranges reflect options trader consensus, not guarantees. Combine with volume/trend analysis.
Compliance Statement
Closed-source logic compliant with TradingView rules.
Core methodology reviewed by moderators (gamma/volatility analysis).
PowerZone Trading StrategyExplanation of the PowerZone Trading Strategy for Your Users
The PowerZone Trading Strategy is an automated trading strategy that detects strong price movements (called "PowerZones") and generates signals to enter a long (buy) or short (sell) position, complete with predefined take profit and stop loss levels. Here’s how it works, step by step:
1. What is a PowerZone?
A "PowerZone" (PZ) is a zone on the chart where the price has shown a significant and consistent movement over a specific number of candles (bars). There are two types:
Bullish PowerZone (Bullish PZ): Occurs when the price rises consistently over several candles after an initial bearish candle.
Bearish PowerZone (Bearish PZ): Occurs when the price falls consistently over several candles after an initial bullish candle.
The code analyzes:
A set number of candles (e.g., 5, adjustable via "Periods").
A minimum percentage move (adjustable via "Min % Move for PowerZone") to qualify as a strong zone.
Whether to use the full candle range (highs and lows) or just open/close prices (toggle with "Use Full Range ").
2. How Does It Detect PowerZones?
Bullish PowerZone:
Looks for an initial bearish candle (close below open).
Checks that the next candles (e.g., 5) are all bullish (close above open).
Ensures the total price movement exceeds the minimum percentage set.
Defines a range: from the high (or open) to the low of the initial candle.
Bearish PowerZone:
Looks for an initial bullish candle (close above open).
Checks that the next candles are all bearish (close below open).
Ensures the total price movement exceeds the minimum percentage.
Defines a range: from the high to the low (or close) of the initial candle.
These zones are drawn on the chart with lines: green or white for bullish, red or blue for bearish, depending on the color scheme ("DARK" or "BRIGHT").
3. When Does It Enter a Trade?
The strategy waits for a breakout from the PowerZone range to enter a trade:
Buy (Long): When the price breaks above the high of a Bullish PowerZone.
Sell (Short): When the price breaks below the low of a Bearish PowerZone.
The position size is set to 100% of available equity (adjustable in the code).
4. Take Profit and Stop Loss
Take Profit (TP): Calculated as a multiple (adjustable via "Take Profit Factor," default 1.5) of the PowerZone height. For example:
For a buy, TP = Entry price + (PZ height × 1.5).
For a sell, TP = Entry price - (PZ height × 1.5).
Stop Loss (SL): Calculated as a multiple (adjustable via "Stop Loss Factor," default 1.0) of the PZ height, placed below the range for buys or above for sells.
5. Visualization on the Chart
PowerZones are displayed with lines on the chart (you can hide them with "Show Bullish Channel" or "Show Bearish Channel").
An optional info panel ("Show Info Panel") displays key levels: PZ high and low, TP, and SL.
You can also enable brief documentation on the chart ("Show Documentation") explaining the basic rules.
6. Alerts
The code generates automatic alerts in TradingView:
For a bullish breakout: "Bullish PowerZone Breakout - LONG!"
For a bearish breakdown: "Bearish PowerZone Breakdown - SHORT!"
7. Customization
You can tweak:
The number of candles to detect a PZ ("Periods").
The minimum percentage move ("Min % Move").
Whether to use highs/lows or just open/close ("Use Full Range").
The TP and SL factors.
The color scheme and what elements to display on the chart.
Practical Example
Imagine you set "Periods = 5" and "Min % Move = 2%":
An initial bearish candle appears, followed by 5 consecutive bullish candles.
The total move exceeds 2%.
A Bullish PowerZone is drawn with a high and low.
If the price breaks above the high, you enter a long position with a TP 1.5 times the PZ height and an SL equal to the height below.
The system executes the trade and exits automatically at TP or SL.
Conclusion
This strategy is great for capturing strong price movements after consolidation or momentum zones. It’s automated, visual, and customizable, making it useful for both beginner and advanced traders. Try it out and adjust it to fit your trading style!
Nasan Risk Score & Postion Size Estimator** THE RISK SCORE AND POSITION SIZE WILL ONLY BE CALCUTAED ON DIALY TIMEFRAME NOT IN OTHER TIMEFRAMES.
The typically accepted generic rule for risk management is not to risk more than 1% - 2 % of the capital in any given trade. It has its own basis however it does not take into account the stocks historic & current performance and does not consider the traders performance metrics (like win rate, profit ratio).
The Nasan Risk Score & Position size calculator takes into account all the listed parameters into account and estimates a Risk %. The position size is calculated using the estimated risk % , current ATR and a dynamically adjusted ATR multiple (ATR multiple is adjusted based on true range's volatility and stocks relative performance).
It follows a series of calculations:
Unadjusted Nasan Risk Score = (Min Risk)^a + b*
Min Risk = ( 5 year weighted avg Annual Stock Return - 5 year weighted avg Annual Bench Return) / 5 year weighted avg Annual Max ATR%
Max Risk = ( 5 year weighted avg Annual Stock Return - 5 year weighted avg Annual Bench Return) / 5 year weighted avg Annual Min ATR%
The min and max return is calculated based on stocks excess return in comparison to the Benchmark return and adjusted for volatility of the stock.
When a stock underperforms the benchmark, the default is, it does not calculate a position size , however if we opt it to calculate it will use 1% for Min Risk% and 2% for Max Risk% but all the other calculations and scaling remain the same.
Rationale:
Stocks outperforming their benchmark with lower volatility (ATR%) score higher.
A stock with high returns but excessive volatility gets penalized.
This ensures volatility-adjusted performance is emphasized rather than absolute returns.
Depending on the risk preference aggressive or conservative
Aggressive Risk Scaling: a = max (m, n) and b = min (m, n)
Conservative Scaling: a = min (m, n) and b = max (m, n)
where n = traders win % /100 and m = 1 - (1/ (1+ profit ratio))
A default of 50% is used for win factor and 1.5 for profit ratio.
Aggressive risk scaling increases exposure when the strategy's strongest factor is favorable.
Conservative risk scaling ensures more stable risk levels by focusing on the weaker factor.
The Unadjusted Nasan risk is score is further refined based on a tolerance factor which is based on the stocks maximum annual drawdown and the trader's maximum draw down tolerance.
Tolerance = /100
The correction factor (Tolerance) adjusts the risk score based on downside risk. Here's how it works conceptually:
The formula calculates how much the stock's actual drawdown exceeds your acceptable limit.
If stocks maximum Annual drawdown is smaller than Trader's maximum acceptable drawdown % , this results in a positive correction factor (indicating the drawdown is within your acceptable range and increases the unadjusted score.
If stocks maximum Annual drawdown exceeds Trader's maximum acceptable drawdown %, the correction factor will decrease (indicating that the downside risk is greater than what you are comfortable with, so it will adjust the risk exposure).
Once the Risk Score (numerically equal to Risk %) The position size is calculated based on the current market conditions.
Nasan Risk Score (Risk%) = Unadjusted Nasan Risk Score * Tolerance.
Position Size = (Capital * Risk% )/ ATR-Multiplier * ATR
The ATR Multiplier is dynamically adjusted based on the stocks recent relative performance and the variability of the true range itself. It would range between 1 - 3.5.
The multiplier widens when conditions are not favorable decreasing the position size and increases position size when conditions are favorable.
This Calculation /Estimate Does not give you a very different result than the arbitrary 1% - 2%. However it does fine tune the % based on sock performance, traders performance and tolerance level.
Momentum Volatility Ratio | AlphaNattMomentum Volatility Ratio | AlphaNatt
The Momentum Volatility Ratio (MVR) is a sophisticated indicator that measures price impulses relative to an asset's inherent volatility. Unlike standard momentum indicators, MVR adapts to changing market conditions by normalizing momentum against historical volatility patterns, helping traders identify truly significant price movements.
Key Features:
• Adapts automatically to each asset's volatility profile
• Distinguishes between normal market noise and significant impulses
• Beautiful gradient visualization with modern Quantra-inspired aesthetics
• Responsive and clear signals with minimal lag
• Customizable sensitivity and appearance settings
How It Works:
The MVR calculates normalized price momentum and adjusts it by recent volatility metrics. This volatility-adjustment ensures the indicator remains consistent across different market environments and timeframes. When price momentum exceeds what would be expected given the asset's normal volatility, the indicator shows a significant impulse that traders can act upon.
Indicator Components:
• Cyan Histogram/Background - Represents positive momentum impulses
• Magenta Histogram/Background - Represents negative momentum impulses
• Neutral Bands - Define the transition between normal and significant impulses
• Gradient Background - Provides visual context for impulse strength
• Smooth Histogram - Shows the main impulse signal with a beautiful glow effect
Trading Signals:
1. Strong Positive Impulse - When cyan histogram bars grow significantly above the zero line
2. Strong Negative Impulse - When magenta histogram bars extend significantly below the zero line
3. Impulse Weakening - When histogram bars begin to shrink toward the zero line
4. Momentum Shift - When the histogram changes color, indicating a potential trend change
Customizable Parameters:
• Length - Base calculation period for momentum (default: 6)
• Volatility Lookback - Historical period for volatility calculation (default: 100)
• Neutral Bands Length - Smoothing period for neutral bands (default: 15)
• Neutral Bands Multiplier - Controls width of neutral bands (default: 0.5)
• Standard Deviation Lookback - Period for standard deviation calculation (default: 150)
• Standard Deviation Multiplier - Controls sensitivity of extreme bands (default: 2.5)
• Style - Choose between Classic, Modern, and Signal visualization modes
Best Practices:
• Use MVR alongside price action for confirmation
• Watch for extreme readings followed by momentum shifts
• Pay attention to divergences between price and MVR
• Consider longer-term trends when interpreting signals
• Use shorter settings for more frequent signals, longer settings for less noise
About the Opus Series:
The MVR indicator is part of the Opus series of premium-quality technical indicators designed with both functional excellence and aesthetic beauty. Opus indicators feature smooth gradients, crisp visualization, and powerful analytical capabilities to enhance your trading experience.
For questions, feedback, or custom indicator requests, please feel free to leave a comment or contact me directly.
Happy Trading!
Not financial Advice
Supply & Demand Zones + Order Block (Pro Fusion) - Auto Order Strategy Title:
Smart Supply & Demand Zones + Order Block Auto Strategy with ScalpPro (Buy-Focused)
📄 Strategy Description:
This strategy combines the power of Supply & Demand Zone analysis, Order Block detection, and an enhanced Scalp Pro momentum filter, specifically designed for automated decision-making based on high-volume breakouts.
✅ Key Features:
Auto Entry (Buy Only) Based on Breakouts
Automatically enters a Buy position when the price breaks out of a valid demand zone, confirmed by EMA 50 trend and volume spike.
Order Block Logic
Identifies bullish and bearish order blocks using consecutive candle structures and significant price movement.
Dynamic Stop Loss & Trailing Stop
Implements a trailing stop once price moves in profit, along with static initial stop loss for risk management.
Clear Visual Labels & Alerts
Displays BUY/SELL, Demand/Supply, and Order Block labels directly on the chart. Alerts trigger on valid breakout signals.
Scalp Pro Momentum Filter (Optimized)
Uses a modified MACD-style momentum indicator to confirm trend strength and filter out weak signals.
Supply & Demand Zones + Order Block (Pro Fusion) SuroLevel up your trading edge with this all-in-one Supply and Demand Zones + Order Block TradingView indicator, built for precision traders who focus on price action and smart money concepts.
🔍 Key Features:
Automatic detection of Supply & Demand Zones based on refined swing highs and lows
Dynamic Order Block recognition with customizable thresholds
Highlights Breakout signals with volume confirmation and trend filters
Built-in EMA 50 trend detection
Take Profit (TP1, TP2, TP3) projection levels
Clean visual labels for Demand, Supply, and OB zones
Uses smart box plotting with long extended zones for better zone visibility
🔥 Ideal for:
Traders who follow Smart Money Concepts (SMC)
Supply & Demand strategy practitioners
Breakout & Retest pattern traders
Scalpers, swing, and intraday traders using Order Flow logic
📈 Works on all markets: Forex, Crypto, Stocks, Indices
📊 Recommended timeframes: M15, H1, H4, Daily
✅ Enhance your trading strategy using this powerful zone-based script — bringing structure, clarity, and automation to your chart.
#SupplyAndDemand #OrderBlock #TradingViewScript #SmartMoney #BreakoutStrategy #TPProjection #ForexIndicator #SMC
SuperTrader Trend Analysis and Trade Study DashboardSuperTrader Trend Analysis and Trade Study Dashboard
Overview
This script offers a multi-faceted look at market behavior. It combines signals from different momentum indicators, daily cross checks, and a specialized dashboard to reveal trend strength, potential divergences, and how far price has traveled from its recent averages.
Three Musketeers Method
This script uses a special set of three indicators (the “Three Musketeers”) to determine bullish or bearish pressure on the current chart.
Trend Condition – Compares fast vs. slow EMAs (50 and 200) and checks which side of the line price is favoring.
Mean Reversion Condition – Watches RSI crossing typical oversold or overbought thresholds (e.g., crossing above 30 or below 70).
Bollinger Condition – Checks whether price pushes above/below the Bollinger Bands (based on a 20 SMA + standard deviations).
When at least two out of these three conditions align in a bullish way, the script issues a Buy Signal . Conversely, if at least two align in a bearish way, a Sell Signal is triggered. This “Three Musketeers” synergy ensures multiple confirmations before calling a potential market turn.
Mag 8 Daily Performance
The script tracks eight highly influential stocks (AAPL, AMZN, GOOG, NFLX, NVDA, TSLA, META, MSFT) to see which are green (higher) or red (lower) compared to yesterday’s close. It then prints a quick tally – helpful in gauging overall market mood via these major players.
Golden / Death Cross Signals
On a daily time frame, the script notes when the 50-day SMA crosses above or below the 200-day SMA. A “Golden Cross” often signals rising momentum, while a “Death Cross” can hint at oncoming weakness.
RSI & Divergence Checks
RSI helps identify hidden turning points. Whenever a bullish or bearish divergence is spotted, the script updates you via a concise readout.
Hardcoded Settings
EMA lengths for trend checks, Bollinger parameters, etc., are locked in, letting you focus on adjusting only the pivotal study inputs (e.g., RSI length, VIDYA momentum).
VIDYA Trend Line & Fill
Built on an adaptive Variable Index Dynamic Average, it plots a line that quickly reacts to changing momentum. Users can set a “Trend Band Distance” to mark ATR-based thresholds around that line, identifying possible breakouts or breakdowns.
YoYo Distance
This concept measures how far price strays from SMA(10). If it’s too far, the script colors your display to indicate potential snapbacks.
Gap Up/Down Probability
By weighing volume, MACD signals, and whether price sits above/below its midrange, the script estimates probabilities of a gap up or down on the next daily candle.
Table Output & Trend Label
Turning on Show Table Widget reveals a quick dashboard on the chart detailing RSI, CCI, divergences, bull/bear scores, and more. A label on the last bar further summarizes overall trend, gap distance, and the Mag 8 snapshot – perfect for a fast read of current market posture.
Use this script to unify multiple signals in one place, see how far price has ventured from typical patterns, and get daily cross signals plus real-time bullish/bearish calls – all at a glance.
TrendWave Bands [BigBeluga]This is a trend-following indicator that dynamically adapts to market trends using upper and lower bands. It visually highlights trend strength and duration through color intensity while providing additional wave bands for deeper trend analysis.
🔵Key Features:
Adaptive Trend Bands:
➣ Displays a lower band in uptrends and an upper band in downtrends to indicate trend direction.
➣ The bands act as dynamic support and resistance levels, helping traders identify potential entry and exit points.
Wave Bands for Additional Analysis:
➣ A dashed wave band appears opposite the main trend band for deeper trend confirmation.
➣ In an uptrend, the upper dashed wave band helps analyze momentum, while in a downtrend, the lower dashed wave band serves the same purpose.
Gradient Color Intensity:
➣ The trend bands have a color gradient that fades as the trend continues, helping traders visualize trend duration.
➣ The wave bands have an inverse gradient effect—starting with low intensity at the trend's beginning and increasing in intensity as the trend progresses.
Trend Change Signals:
➣ Circular markers appear at trend reversals, providing clear entry and exit points.
➣ These signals mark transitions between bullish and bearish phases based on price action.
🔵Usage:
Trend Following: Use the lower band for confirmation in uptrends and the upper band in downtrends to stay on the right side of the market.
Trend Duration Analysis: Gradient wavebands give an idea of the duration of the current trend — new trends will have high-intensity colored wavebands and as time goes on, trends will fade.
Trend Reversal Detection: Circular markers highlight trend shifts, making it easier to spot entry and exit opportunities.
Volatility Awareness: Volatility-based bands help traders adjust their strategies based on market volatility, ensuring better risk management.
TrendWave Bands is a powerful tool for traders seeking to follow market trends with enhanced visual clarity. By combining trend bands, wave bands, and gradient-based color scaling, it provides a detailed view of market dynamics and trend evolution.
SMA Channel AlertsThe "SMA Channel with Alerts" indicator is designed to help traders visualize dynamic support and resistance zones based on a simple moving average (SMA). It computes the SMA on a user-specified timeframe and then applies user-configurable percentage deviations to generate a price channel. The channel consists of five lines:
Central SMA: The primary moving average (default is 12-period on a daily timeframe).
Upper Lines: Two lines plotted above the SMA, representing small and large positive percentage offsets.
Lower Lines: Two lines plotted below the SMA, representing small and large negative percentage offsets.
Key Features:
Customizable SMA:
Choose the SMA length.
Select the timeframe for the SMA calculation.
Specify the data source (default is closing price).
Adjustable Percentage Offsets:
Configure the upward offsets (small and large) as percentages.
Configure the downward offsets (small and large) as percentages.
Versatile Alert System:
Set alerts for price crossing any channel line upward or downward.
Receive individual alerts for each line when crossed in either direction.
A consolidated alert option for any crossing across all channel lines.
How to Use the Indicator:
Configuration:
Adjust the SMA settings (length, timeframe, source) to match your trading strategy.
Set your desired percentage deviations for the channel lines.
Alert Setup:
Open TradingView's alert creation window.
Choose the specific alert condition from the indicator (e.g., “Any Cross Upper Large (+)” or “Any Cross ANY Line”).
Configure your alert preferences (notification type, sound, etc.).
Trading Application:
Use the channel lines to gauge potential support and resistance levels.
Monitor the alerts for timely notifications when the price breaks through these key levels, signaling possible trend shifts or breakout opportunities.
This indicator is ideal for traders looking for a visual method to monitor price action relative to a moving average-based channel and to automate alert notifications for better trade timing.
Chop ZonesThis indicator plots two "zones" in the form of shaded boxes, one between PMH and PML and one between PDH and PDL, the area that is shaded more has the highest probability of price action to be "choppy", the lesser shaded area has less probability for "choppy" action whilst outside the shaded areas there is high probability of a trend.
This indicator can be used to determine one of the three types of day:
Chop day
Bullish trend day
Bearish trend day
Chop day example today on AMEX:SPY
Bullish trend day example on NASDAQ:DLTR
Bearish trend day example on NASDAQ:UAL
Price Extreme BandsPrice Extreme Bands Description
This indicator calculates and displays Price Extreme Bands based on an Exponential Moving Average (EMA) and True Range Average True Range (TR ATR). It utilizes a custom "Super Smoother" function to smooth the bands, providing a clearer representation of potential price extremes without sacrificing accuracy.
Usage
Built for specifically for intraday timeframes, this indicator identifies short term price extremes and volatility ranges. Traders can observe when price moves towards the outer bands, suggesting strong momentum or potential overbought/oversold conditions. The filled zones highlight areas of increased volatility which can used as exit criteria for a trade, possible reversal points in ranging markets or price ranges where price momentum could slow in trending markets.
Key Features
Length Input: Controls the length of the EMA and TR ATR calculations.
Multiplier Inputs: Uses two fixed multipliers (1.71 and 2.50) to create bands.
Super Smoother: Applies a custom smoothing function to the bands for reduced noise.
Fill Zones: Fills the areas between the inner and outer bands to highlight potential volatility ranges.
Calculation:
1. EMA (Basis): Calculates the Exponential Moving Average of the selected source.
2. TR ATR: Calculates the True Range and then smoothes it using RMA (Rolling Moving Average).
3. Bands: Calculates upper and lower bands using the EMA and ATR, with multipliers of 1.71 and 2.50.
4. Super Smoother: Applies a smoothing function to the calculated bands.
Visuals:
Basis Line: Plots the EMA (basis) (invisible by default).
Inner Bands (1.71 Multiplier): Plots the smoothed bands with a distinct color (e.g., orange) (invisible by default).
Outer Bands (2.50 Multiplier): Plots the smoothed bands with a different color (e.g., purple) (invisible by default).
Fill Zones: Fills the region between the inner and outer upper bands and the inner and outer lower bands with a translucent color (e.g. light blue).
// Note: The plot lines are invisible by default. To view the basis, upper and lower band lines, adjust the visibility settings in the indicator's settings.
Uniqueness: Ready of the box. Code and parameters built specifically for 1m to 15m timeframes provides users with an indicator to easily identify price extremes. The use of TR ATR and addition of the Super Smoother calculation create a easier visualization and implementation compared to existing price band options.
Wyckoff Range Detector [Beta] + Smart Money ElementsThis indicator detects the key phases of the Wyckoff market structure and integrates smart money elements, such as Order Blocks (OB), Fair Value Gaps (FVG), and Breaker Blocks. It also helps identify potential reversal zones (LPS, UTAD, Spring), breakout opportunities, and provides automatic Risk-Reward (R:R) calculations.
Key Features:
Wyckoff Phases Detection:
Automatically detects key phases of Wyckoff's market structure:
B (Range) – The initial range of accumulation.
C (Spring Phase) – Accumulation phase with a potential breakout.
C (UTAD Phase) – Upthrust After Distribution, indicating a potential reversal.
D (LPS Phase) – Last Point of Support, signaling accumulation before a breakout.
E (Breakout) – Phase marking breakout from range.
Re-Accumulation – Possible continuation in the range after a breakout.
Re-Distribution – Possible breakdown of a distribution phase.
Smart Money Elements:
Order Blocks (OB): Identifies Bullish and Bearish OBs to anticipate market entries.
Fair Value Gap (FVG): Highlights imbalance areas where price is likely to return.
Breaker Blocks: Marks areas where the price has previously broken a structure, indicating strong supply/demand zones.
Automatic Risk-Reward Calculation:
Smart RR: Automatically calculates Risk-Reward (R:R) ratios from LPS phases and Order Blocks. It draws lines to indicate target and stop levels with green for the target and red for the stop.
Visual representation of the entry signal with target and stop levels displayed.
Alerts:
Set alerts for phase changes, breakout, re-accumulation, or re-distribution to stay updated on the market’s movements.
Visual Tools:
Labels are used to indicate key zones such as AR, SC, LPS, and Spring Zones.
Draw boxes for the Spring and LPS phases to highlight areas where price action is likely to reverse.
Lines to represent potential breakouts, with customizable risk-reward indicators.
How to Use:
Apply the Indicator on any chart.
Identify Wyckoff phases to understand market trends.
Monitor Smart Money Elements (OB, FVG, Breaker) for entry and exit points.
Use automatic Risk-Reward levels for managing trades.
Set alerts for various Wyckoff phases and smart money signals to stay updated.
