ATR Display ShorcutATR Value Display - On-Chart Volatility Monitor
Clean ATR display directly on your price chart - no extra panels needed!
This indicator displays the current Average True Range (ATR) value as a clean table overlay on your price chart, eliminating the need for a separate indicator panel below your main chart.
✨ Key Features:
On-chart display: ATR value shown directly on price chart
Customizable positioning: Choose from 4 corner positions
Clean design: Minimal, non-intrusive table format
Real-time updates: Always shows the latest ATR value
Adjustable period: Default 14-period, fully customizable
🎯 Perfect For:
Position sizing calculations
Stop-loss placement (1x, 1.5x, 2x ATR)
Volatility assessment at a glance
Clean chart setups without extra panels
Quick reference during live trading
📊 How to Use:
Add to chart
Select your preferred table position
Adjust ATR period if needed (default: 14)
The current ATR value displays automatically
💡 Pro Tip:
Use this ATR value to:
Set stop-losses at 1.5x or 2x ATR distance
Determine position size based on account risk
Compare current volatility to historical levels
Clean charts, clear data, better trading decisions.
Compatible with all timeframes and instruments. Pine Script v6.
Feel free to adjust this description to match your style or add any specific features you want to highlight!
Komut dosyalarını "stop loss" için ara
IPDA with Order Blocks [Enhanced]Summary of the Code
This script plots IPDA Standard Deviations on a price chart, helping traders visualize potential support and resistance levels based on a series of user-defined deviations. It uses swing high/low points and time-based fractal lookbacks (monthly, weekly, daily, or intraday) to define price anchors and compute deviation lines.
Key features include:
Deviations: It calculates and plots deviation levels based on the distance between swing highs and lows, which traders can use as price targets or zones of interest.
Timeframes:
Monthly (higher timeframe analysis)
Weekly (medium-term analysis)
Daily and Intraday (shorter-term precision)
Customization:
Choose which deviation levels (e.g., 0, 1, -1, -2) to display.
Hide labels or adjust their sizes for cleaner charts.
Option to remove invalidated deviation levels dynamically.
Visual Cleanliness: Automatically removes clutter by hiding or deleting invalid deviation levels and focusing on active price zones.
How to Utilize It for Intraday Trading to Make $1,000
Here’s how to effectively use the indicator to optimize intraday trading:
1. Set the Right Timeframe:
Use the 15-minute or 1-hour chart for intraday setups.
Ensure the "Intraday" lookback option is enabled to focus on shorter-term swings.
2. Interpret the Levels:
Bearish Order Blocks: Look for red lines (bearish deviation) as potential resistance zones where the price may reverse downward.
Bullish Order Blocks: Look for green lines (bullish deviation) as potential support zones where the price may bounce upward.
3. Plan Entries and Exits:
Entry: Buy near a green order block or short near a red order block, confirming the trade with additional signals (e.g., candlestick patterns, momentum indicators).
Stop Loss: Place your stop below the green line (for buys) or above the red line (for shorts).
Profit Targets: Use deviation levels as targets (e.g., from the 0 level to +1 or -1).
4. Combine with Market Context:
Use the script alongside volume profile, trend indicators, or news events for confirmation.
Avoid trading during major news events unless aligned with deviations.
5. Position Sizing for $1,000 Goal:
Trade liquid instruments like Nasdaq futures (NQ) or major forex pairs.
Risk 1-2% of your capital on each trade and scale into positions if confirmed.
Target a profit of 10-20 points per trade on Nasdaq futures, with 1-2 trades daily.
6. Monitor Key Timeframes:
Pre-market (before 9:30 AM EST): Mark deviation levels to predict market open behavior.
Midday & Power Hour (3-4 PM EST): Watch for breakouts or retests around key deviation levels.
By combining this tool with disciplined risk management and a clear trading plan, you can systematically work toward your profit target while minimizing unnecessary risks
[blackcat] L1 Net Volume DifferenceOVERVIEW
The L1 Net Volume Difference indicator serves as an advanced analytical tool designed to provide traders with deep insights into market sentiment by examining the differential between buying and selling volumes over precise timeframes. By leveraging these volume dynamics, it helps identify trends and potential reversal points more accurately, thereby supporting well-informed decision-making processes. The key focus lies in dissecting intraday changes that reflect short-term market behavior, offering critical input for both swing and day traders alike. 📊
Key benefits encompass:
• Precise calculation of net volume differences grounded in real-time data.
• Interactive visualization elements enhancing interpretability effortlessly.
• Real-time generation of buy/sell signals driven by dynamic volume shifts.
TECHNICAL ANALYSIS COMPONENTS
📉 Volume Accumulation Mechanisms:
Monitors cumulative buy/sell volumes derived from comparative closing prices.
Periodically resets accumulation counters aligning with predefined intervals (e.g., 5-minute bars).
Facilitates identification of directional biases reflecting underlying market forces accurately.
🕵️♂️ Sentiment Detection Algorithms:
Employs proprietary logic distinguishing between bullish/bearish sentiments dynamically.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy.
Supports adaptive thresholds adjusting sensitivities based on changing market conditions flexibly.
🎯 Dynamic Signal Generation:
Detects transitions indicating dominance shifts between buyers/sellers promptly.
Triggers timely alerts enabling swift reactions to evolving market dynamics effectively.
Integrates conditional logic reinforcing signal validity minimizing erroneous activations.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Utilizes moving averages along with standardized deviation formulas generating precise net volume measurements.
Implements Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent alignment with established statistical principles preserving fidelity.
🖱️ User Interface Elements:
Dedicated plots displaying real-time net volume markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively.
Background shading highlighting proximity to key threshold activations enhancing visibility.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals.
Validate entry decisions considering concurrent market sentiment factors.
Assess alignment between net volume readings and broader trend directions ensuring coherence.
🚫 Exit Mechanisms:
Trigger exits upon hitting predetermined thresholds derived from historical analyses.
Monitor continuous breaches signifying potential trend reversals promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Reset Interval: Governs responsiveness versus stability balancing sensitivity/stability.
Price Source: Dictates primary data series driving volume calculations selecting relevant inputs accurately.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts.
Evaluate adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity.
Sustain balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines.
Mandatorily apply trailing stop-loss orders conforming to script outputs reinforcing discipline.
Allocate positions proportionately relative to available capital reserves managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically.
Prepare contingency plans mitigating margin call possibilities preparing proactive responses effectively.
Continuously assess automated system reliability amidst fluctuating conditions ensuring seamless functionality.
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics:
Assess win percentages consistently across diverse trading instruments gauging reliability.
Calculate average profit ratios per successful execution measuring profitability efficiency accurately.
Measure peak drawdown durations alongside associated magnitudes evaluating downside risks comprehensively.
Analyze signal generation frequencies revealing hidden patterns potentially skewing outcomes uncovering systematic biases.
📈 Historical Data Analysis Tools:
Maintain comprehensive records capturing every triggered event meticulously documenting results.
Compare realized profits/losses against backtested simulations benchmarking actual vs expected performances accurately.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily.
Document evolving performance metrics tracking progress dynamically addressing identified shortcomings proactively.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities.
Overfitted models yielding suboptimal results post-extensive tuning demanding recalibrations.
Inaccuracies stemming from incomplete/inaccurate data feeds necessitating verification procedures.
💡 Effective Resolution Pathways:
Exclude low-liquidity assets prone to erratic movements enhancing signal integrity.
Introduce buffer intervals safeguarding major news/event impacts mitigating distortions effectively.
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations reliably.
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
Heartfelt acknowledgment extends to all developers contributing invaluable insights about volume-based trading methodologies! ✨
[blackcat] L2 Z-Score of PriceOVERVIEW
The L2 Z-Score of Price indicator offers traders an insightful perspective into how current prices diverge from their historical norms through advanced statistical measures. By leveraging Z-scores, it provides a robust framework for identifying potential reversals in financial markets. The Z-score quantifies the number of standard deviations that a data point lies away from the mean, thus serving as a critical metric for recognizing overbought or oversold conditions. 🎯
Key benefits encompass:
• Precise calculation of Z-scores reflecting true price deviations.
• Interactive plotting features enhancing visual clarity.
• Real-time generation of buy/sell signals based on crossover events.
STATISTICAL ANALYSIS COMPONENTS
📉 Mean Calculation:
Utilizes Simple Moving Averages (SMAs) to establish baseline price references.
Provides smooth representations filtering short-term noise preserving long-term trends.
Fundamental for deriving subsequent deviation metrics accurately.
📈 Standard Deviation Measurement:
Quantifies dispersion around established means revealing underlying variability.
Crucial for assessing potential volatility levels dynamically adapting strategies accordingly.
Facilitates precise Z-score derivations ensuring statistical rigor.
🕵️♂️ Z-SCORE DETECTION:
Measures standardized distances indicating relative positions within distributions.
Helps pinpoint extreme conditions signaling impending reversals proactively.
Enables early identification of trend exhaustion phases prompting timely actions.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Integrates SMAs along with standardized deviation formulas generating precise Z-scores.
Employs Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy.
🖱️ User Interface Elements:
Dedicated plots displaying real-time Z-score markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively.
Background shading highlighting proximity to key threshold activations enhancing visibility.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals.
Validate entry decisions considering concurrent market sentiment factors.
Assess alignment between Z-score readings and broader trend directions ensuring coherence.
🚫 Exit Mechanisms:
Trigger exits upon hitting predetermined thresholds derived from historical analyses.
Monitor continuous breaches signifying potential trend reversals promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Length: Governs responsiveness versus smoothing trade-offs balancing sensitivity/stability.
Price Source: Dictates primary data series driving Z-score computations selecting relevant inputs accurately.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts.
Evaluate adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity.
Sustain balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines.
Mandatorily apply trailing stop-loss orders conforming to script outputs reinforcing discipline.
Allocate positions proportionately relative to available capital reserves managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically.
Prepare contingency plans mitigating margin call possibilities preparing proactive responses effectively.
Continuously assess automated system reliability amidst fluctuating conditions ensuring seamless functionality.
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics:
Assess win percentages consistently across diverse trading instruments gauging reliability.
Calculate average profit ratios per successful execution measuring profitability efficiency accurately.
Measure peak drawdown durations alongside associated magnitudes evaluating downside risks comprehensively.
Analyze signal generation frequencies revealing hidden patterns potentially skewing outcomes uncovering systematic biases.
📈 Historical Data Analysis Tools:
Maintain comprehensive records capturing every triggered event meticulously documenting results.
Compare realized profits/losses against backtested simulations benchmarking actual vs expected performances accurately.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily.
Document evolving performance metrics tracking progress dynamically addressing identified shortcomings proactively.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities.
Overfitted models yielding suboptimal results post-extensive tuning demanding recalibrations.
Inaccuracies stemming from incomplete/inaccurate data feeds necessitating verification procedures.
💡 Effective Resolution Pathways:
Exclude low-liquidity assets prone to erratic movements enhancing signal integrity.
Introduce buffer intervals safeguarding major news/event impacts mitigating distortions effectively.
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations reliably.
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
Position Size Calculator (Fixed % or ATR-based Stop Support)Position Size Calculator (Fixed % or ATR-based Stop Support)
Purpose and Background
This indicator allows traders to calculate appropriate position sizes directly on the chart, based on a key rule:
“What percentage of your capital are you willing to risk per trade?”
While many traders focus on entries and indicators, position sizing and risk allocation are often overlooked.
This tool visualizes and simplifies the “1% risk rule” promoted by IBD (Investor’s Business Daily) and William J. O’Neil, helping both beginners and experienced traders maintain disciplined capital management.
Key Features
Automatically calculates and displays:
・ Position Size
The number of units (shares, contracts, coins) you can hold based on your stop-loss range and risk allowance.
・ Stop Price
The price level at which your stop-loss would be triggered.
・ Risk Amount
The maximum loss per trade based on your portfolio size and risk percentage.
Two stop-loss modes available:
・ Fixed % Mode
O’Neil suggests using up to 8% stop-loss in uptrends and keeping it tighter (around 4%) in corrections. This mode allows flexible manual settings.
・ ATR-Based Mode
Uses the asset’s average volatility to dynamically calculate stop-loss width using the Average True Range (ATR).
ATR Usage and Recommended Settings
ATR helps you avoid noise-based stop-outs and align your risk with market volatility.
There are two parameters you can adjust:
・ ATR Length
Defines how many bars are used to calculate the average range.
・Shorter values (5–10) respond faster for day trades
・Longer values (14–21) offer smoother ranges for swing/position trades(Default is 14)
・ATR Multiplier
Sets how wide the stop-loss is by multiplying the ATR value:
・Day trading: 1.0–1.5×
・Swing trading: 1.5–2.5×
・Position trading: 2.0–3.0×
Practical Examples: Risk % × Stop-Loss % → Max Positions
This tool helps estimate how many positions you can hold in a portfolio based on your risk per trade and stop width.
Examples:
・Risk 0.5%, Stop 8% → Max 16 positions
・Risk 0.5%, Stop 4% → Max 8 positions
・Risk 1.0%, Stop 8% → Max 8 positions
・Risk 1.0%, Stop 4% → Max 4 positions
・Risk 2.0%, Stop 8% → Max 4 positions
・Risk 2.0%, Stop 4% → Max 2 positions
These assume worst-case scenarios where all positions are stopped out simultaneously within your overall portfolio risk limit.
Display & Customization Options
・ Currency Display: USD or JPY
No currency conversion is applied. Select based on your trading region (e.g., USD for U.S. stocks, JPY for Japanese stocks).
Support for additional currencies can be added upon request.
・ Show/Hide Decimal Places
Toggle decimals for better visibility. Ideal for fractional assets like crypto and CFDs.
・ Position of Output
Choose from top-right, middle-right, or bottom-right on the chart.
・ Text Display Size: Large / Normal / Small
Choose the table size that best suits your viewing preferences.
・ Explanation of Displayed Labels
・ Position Size : Units to buy/sell based on risk
・ Stop Price : Price where stop-loss is triggered
・ Risk Amount : Max loss allowed for the trade
How to Use
１、Set your Portfolio Size
２、Choose your Currency (USD or JPY)
３、Input Risk per Trade (%) (e.g., 1%)
４、Select Stop Loss Method
・ Fixed % : Enter a manual stop-loss percent (e.g., 8%)
・ ATR : Then also enter:
・ ATR Length : Number of bars used to calculate ATR (e.g., 14)
・ ATR Multiplier : Factor applied to ATR to determine stop-loss (e.g., 2.0)
５、Adjust decimals, label position, or text size as needed
６、The result is displayed in a table directly on your chart
Notes
・ Uses the current close price (close) as the basis
Real-time bid/ask data isn't available in Pine Script, so the close price is used for consistent results.
・ No buy/sell signals are generated
This tool is for position sizing and risk calculation only, not trade entries.
Recommended For
・Traders who want precise, rule-based position sizing
・Users following IBD or O’Neil’s 1% risk principle
・Those incorporating ATR for stop-loss strategies
・Multi-asset traders (stocks, crypto, CFDs, etc.)
・ Anyone who wants to calculate position size and risk without using a calculator or external tool—fully inside TradingView
Dynamic Liquidity Depth [BigBeluga]
Dynamic Liquidity Depth
A liquidity mapping engine that reveals hidden zones of market vulnerability. This tool simulates where potential large concentrations of stop-losses may exist — above recent highs (sell-side) and below recent lows (buy-side) — by analyzing real price behavior and directional volume. The result is a dynamic two-sided volume profile that highlights where price is most likely to gravitate during liquidation events, reversals, or engineered stop hunts.
🔵 KEY FEATURES
Two-Sided Liquidity Profiles:
Plots two separate profiles on the chart — one above price for potential sell-side liquidity , and one below price for potential buy-side liquidity . Each profile reflects the volume distribution across binned zones derived from historical highs and lows.
Real Stop Zone Simulation:
Each profile is offset from the current high or low using an ATR-based buffer. This simulates where traders might cluster their stop-losses above swing highs (short stops) or below swing lows (long stops).
Directional Volume Analysis:
Buy-side volume is accumulated only from bullish candles (close > open), while sell-side volume is accumulated only from bearish candles (close < open). This directional filtering enhances accuracy by capturing genuine pressure zones.
Dynamic Volume Heatmap:
Each liquidity bin is rendered as a horizontal box with a color gradient based on volume intensity:
- Low activity bins are shaded lightly.
- High-volume zones appear more vividly in red (sell) or lime (buy).
- The maximum volume bin in each profile is emphasized with a brighter fill and a volume label.
Extended POC Zones:
The Point of Control (PoC) — the bin with the most volume — is extended backwards across the entire lookback period to mark critical resistance (sell-side) or support (buy-side) levels.
Total Volume Summary Labels:
At the center of each profile, a summary label displays Total Buy Liquidity and Total Sell Liquidity volume.
This metric helps assess directional imbalance — when buy liquidity is dominant, the market may favor upward continuation, and vice versa.
Customizable Profile Granularity:
You can fine-tune both Resolution (Bins) and Offset Distance to adjust how far profiles are displaced from price and how many levels are calculated within the ATR range.
🔵 HOW IT WORKS
The indicator calculates an ATR-based buffer above highs and below lows to define the top and bottom of the liquidity zones.
Using a user-defined lookback period, it scans historical candles and divides the buffered zones into bins.
Each bin checks if bullish (or bearish) candles pass through it based on price wicks and body.
Volume from valid candles is summed into the corresponding bin.
When volume exists in a bin, a horizontal box is drawn with a width scaled by relative volume strength.
The bin with the highest volume is highlighted and optionally extended backward as a zone of importance.
Total buy/sell liquidity is displayed with a summary label at the side of the profile.
🔵 USAGE/b]
Identify Stop Hunt Zones: High-volume clusters near swing highs/lows are likely liquidation zones targeted during fakeouts.
Fade or Follow Reactions: Price hitting a high-volume bin may reverse (fade opportunity) or break with strength (confirmation breakout).
Layer with Other Tools: Combine with market structure, order blocks, or trend filters to validate entries near liquidity.
Adjust Offset for Sensitivity: Use higher offset to simulate wider stop placement; use lower for tighter scalping zones.
🔵 CONCLUSION
Dynamic Liquidity Depth transforms raw price and volume into a spatial map of liquidity. By revealing areas where stop orders are likely hidden, it gives traders insight into price manipulation zones, potential reversal levels, and breakout traps. Whether you're hunting for traps or trading with the flow, this tool equips you to navigate liquidity with precision.
Guppy Multiple Moving Average (GMMA)The GMMA Momentum Indicator plots 12 EMAs on your chart, divided into two groups:
Short-term EMAs (6 lines, default periods: 3, 5, 8, 10, 12, 15): Represent short-term trader sentiment and momentum.
Long-term EMAs (6 lines, default periods: 30, 35, 40, 45, 50, 60): Reflect long-term investor behavior and broader market trends.
By analyzing the interaction between these two groups, the indicator identifies:
Bullish and bearish trends based on the relative positions of the short- and long-term EMAs.
Momentum strength through the spread or convergence of the EMAs.
Potential reversals or breakouts via compression signals.
This PineScript version enhances the traditional GMMA by adding visual cues like background colors, bearish signals, and compression detection, making it ideal for swing traders seeking clear, actionable insights.
The GMMA Momentum Indicator provides several key features:
1. Trend Identification
Bullish Trend: When the short-term EMAs (green lines) are above the long-term EMAs (blue lines) and spreading apart, it signals strong upward momentum. The chart background turns light green to highlight this condition.
Bearish Trend: When the short-term EMAs cross below the long-term EMAs and converge, it indicates downward momentum. The background turns light red, and an orange downward triangle appears above the bar to mark a new bearish signal.
2. Momentum Analysis
The spread between the short-term EMAs reflects the strength of short-term momentum. A wide spread suggests strong momentum, while a tight grouping indicates weakening momentum or consolidation. Similarly, the long-term EMAs act as dynamic support or resistance, guiding traders on the broader trend.
3. Compression Detection
Compression occurs when both the short-term and long-term EMAs converge, signaling low volatility and a potential breakout or reversal. A yellow upward triangle appears below the bar when compression is detected, alerting traders to watch for price action.
4. Visual Cues
Green short-term EMAs: Show short-term trader activity.
Blue long-term EMAs: Represent long-term investor sentiment.
Background colors: Light green for bullish trends, light red for bearish trends, and transparent for neutral conditions.
Orange downward triangles: Mark new bearish trends.
Yellow upward triangles: Indicate compression, hinting at potential breakouts.
How to Use the GMMA Momentum Indicator for Swing Trading
Swing trading involves capturing price moves over days to weeks, and the GMMA Momentum Indicator is an excellent tool for this strategy. Here’s how to use it effectively:
1. Identifying Trade Entries
Buy Opportunities:
Look for a bullish trend (green background) where the short-term EMAs are above the long-term EMAs and spreading apart, indicating strong momentum.
A compression signal (yellow triangle) followed by a breakout above resistance or a bullish candlestick pattern can confirm an entry.
Example: On a daily chart, if the short-term EMAs cross above the long-term EMAs and the background turns green, consider entering a long position, especially if volume supports the move.
Sell Opportunities:
Watch for a bearish signal (orange downward triangle) or a bearish trend (red background) where the short-term EMAs cross below the long-term EMAs.
Example: If the short-term EMAs collapse below the long-term EMAs and an orange triangle appears, it may signal a shorting opportunity or a time to exit longs.
2. Managing Trades
Use the long-term EMAs as dynamic support (in uptrends) or resistance (in downtrends) to set stop-loss levels or trail stops.
Monitor the spread of the short-term EMAs. A widening spread suggests the trend is strong, while convergence may indicate it’s time to take profits or tighten stops.
3. Anticipating Reversals
Compression signals (yellow triangles) highlight periods of low volatility, often preceding significant price moves. Combine these with price action (e.g., breakouts or reversals) or other indicators (e.g., RSI or volume) for confirmation.
Example: If a compression signal appears near a key support level and the price breaks upward, it could signal the start of a new bullish swing.
4. Best Practices
Timeframes: The indicator works well on daily or 4-hour charts for swing trading, but you can adjust the EMA periods for shorter (e.g., 1-hour) or longer (e.g., weekly) timeframes.
Confirmation: Combine the GMMA with other tools like support/resistance levels, candlestick patterns, or oscillators (e.g., MACD) to reduce false signals.
Risk Management: Always use proper position sizing and stop-losses, as EMAs are lagging indicators and may produce delayed signals in choppy markets.
OA - PowerZones Support And ResistancePowerZones - Dynamic Support/Resistance Identifier
Overview
PowerZones is an advanced technical analysis tool that automatically detects significant support and resistance zones using volume data and pivot points. This indicator pulls data from higher timeframes (weekly by default) to help you identify strong and meaningful levels that are filtered from short-term "noise."
Features
Multi-Timeframe Analysis: Create support/resistance levels from daily, weekly, or monthly data
Volume Filtering: Detect high-volume pivot points to identify more reliable levels
Dynamic Threshold: Volume filter that automatically adjusts to market conditions
Visual Clarity: Support/resistance zones are displayed as boxes with adjustable transparency
Optimal Level Selection: Filter out close levels to focus on the most significant support/resistance points
Use Cases
Entry/Exit Points: Identify trading opportunities at important support and resistance levels
Stop-Loss Placement: Use natural support levels to set more effective stop-losses
Target Setting: Use potential resistance levels as profit-taking targets
Understanding Market Structure: Detect long-term support/resistance zones to better interpret price movement
Input Parameters
Lookback Period: The period used to determine pivot points
Box Width : Adjusts the width of support/resistance zones
Relative Volume Period: The period used for relative volume calculation
Maximum Number of Boxes: Maximum number of support/resistance zones to display on the chart
Box Transparency: Transparency value for the boxes
Timeframe: Timeframe to use for support/resistance detection (Daily, Weekly, Monthly)
How It Works
PowerZones identifies pivot highs and lows in the selected timeframe. It filters these points using volume data to show only meaningful and strong levels. The indicator also consolidates nearby levels, allowing you to focus only on the most important zones on the chart.
Best Practices
Weekly timeframe setting is ideal for identifying long-term important support/resistance levels
Working with weekly levels on a daily chart allows you to combine long-term levels with short-term trades
ATR-based box width creates support/resistance zones that adapt to market volatility
Use the indicator along with other technical indicators such as RSI, MACD, or moving averages to confirm trading signals
Note: Like all technical indicators, this indicator does not guarantee 100% accuracy. Always apply risk management principles and use it in conjunction with other analysis methods to achieve the best results.
If you like the PowerZones indicator, please show your support by giving it a star and leaving a comment!
Ultimate MA & PSAR [TARUN]Overview
This indicator combines a customizable Moving Average (MA) and Parabolic SAR (PSAR) to generate precise long and short trade signals. A dashboard displays real-time trade conditions, including signal direction, entry price, stop loss, and PnL tracking.
Key Features
✅ Customizable MA Type & Period – Choose between SMA or EMA with adjustable length.
✅ Adaptive PSAR Settings – Modify start, increment, and max step values to fine-tune stop levels.
✅ Trade Signal Logic – Identifies potential buy (long) and sell (short) opportunities based on:
Price action relative to MA
MA trend direction (rising or falling)
PSAR confirmation
✅ Dynamic Stop Loss Calculation – Uses lowest low/highest high over a specified period for stop loss placement.
✅ Trade State & Reversal Handling – Manages active trades, pending signals, and stop loss exits dynamically.
✅ PnL & Dashboard Table – Displays real-time signal status, entry price, stop loss, and profit/loss (PnL) in an easy-to-read format.
How It Works
1.Buy (Long) Condition:
MA is rising
Price is above the MA
PSAR is below price
2.Sell (Short) Condition:
MA is falling
Price is below the MA
PSAR is above price
3.Stop Loss Handling:
For long trades → stop loss is set at the lowest low of the last X candles
For short trades → stop loss is set at the highest high of the last X candles
4.Trade Execution & PnL Calculation:
If a valid long/short setup is detected, a pending signal is placed.
On the next bullish (for long) or bearish (for short) candle, the trade is confirmed.
Real-time PnL updates help track trade performance.
Customization Options
🔹 Moving Average: SMA or EMA, adjustable period
🔹 PSAR Settings: Start, Increment, Maximum step values
🔹 Stop Loss Lookback: Choose how many candles to consider for stop loss placement
🔹 Dashboard Positioning: Select preferred display location (top/bottom, left/right)
🔹 Trade Signal Selection: Enable/Disable Long and Short signals individually
How to Use
Add the indicator to your chart.
Customize the MA & PSAR settings according to your trading strategy.
Follow the dashboard signals for trade setups.
Use stop loss levels to manage risk effectively.
Disclaimer
⚠️ This indicator is for educational purposes only and does not constitute financial advice. Always perform proper risk management and backtesting before using it in live trading.
Min-Max | Buy-Sell Alert with LevelsMin-Max | Buy-Sell Alert with Levels
Description:
The Min-Max | Buy-Sell Alert with Levels indicator is a powerful tool designed to help traders identify key levels of support and resistance based on the previous day's high and low prices. It plots horizontal lines for the previous day's minimum (Min) and maximum (Max) prices, along with four intermediate levels (Stop Loss 1 to Stop Loss 4) calculated as equal percentage steps between the Min and Max.
This indicator is perfect for traders who want to:
Identify potential entry points when the price returns within the Min-Max range.
Set stop-loss levels based on the calculated intermediate levels.
Receive alerts for buy, sell, and stop-loss conditions.
Key Features:
Previous Day's Min and Max Lines:
Automatically plots the Min (red line) and Max (green line) of the previous day.
These levels act as dynamic support and resistance zones.
Intermediate Stop Loss Levels:
Calculates and plots four intermediate levels (Stop Loss 1 to Stop Loss 4) between the Min and Max.
Each level is equally spaced, representing potential stop-loss or take-profit zones.
Customizable Alerts:
Buy Alert: Triggered when the price returns within the Min-Max range after breaking below the Min.
Sell Alert: Triggered when the price returns within the Min-Max range after breaking above the Max.
Stop Loss Alerts: Triggered when the price reaches any of the four intermediate levels (Stop Loss 1 to Stop Loss 4).
Customizable Appearance:
Adjust the thickness, color, and style (solid, dashed, dotted) of the lines.
Customize the colors of the Stop Loss labels for better visualization.
Labels on the Chart:
Displays "Buy" and "Sell" labels on the chart when the respective conditions are met.
Labels for Stop Loss levels are also displayed for easy reference.
How to Use:
Add the indicator to your chart.
Customize the settings (line colors, thickness, and alert preferences) in the indicator's settings panel.
Use the Min and Max lines as dynamic support and resistance levels.
Monitor the intermediate levels (Stop Loss 1 to Stop Loss 4) for potential stop-loss or take-profit zones.
Set up alerts for Buy, Sell, and Stop Loss conditions to stay informed about key price movements.
Why Use This Indicator?
Simple and Effective: Focuses on the most important levels from the previous day.
Customizable: Tailor the indicator to match your trading style and preferences.
Alerts: Never miss a trading opportunity with customizable alerts for key conditions.
Settings:
Line Thickness: Adjust the thickness of the Min, Max, and intermediate lines.
Line Colors: Customize the colors of the Min, Max, and intermediate lines.
Line Style: Choose between solid, dashed, or dotted lines.
Stop Loss Label Colors: Customize the colors of the Stop Loss labels.
Alerts: Enable or disable alerts for Buy, Sell, and Stop Loss conditions.
Ideal For:
Day traders and swing traders.
Traders who rely on support and resistance levels.
Anyone looking for a clear and customizable tool to identify key price levels.
Disclaimer:
This indicator is for educational and informational purposes only. It does not constitute financial advice. Always conduct your own analysis and trade responsibly.
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Add the Min-Max | Buy-Sell Alert with Levels indicator to your chart and take your trading to the next level. Customize it to fit your strategy and never miss a key trading opportunity again!
XGBoost Approximation Indicator with HTF Filter Ver. 3.2XGBoost Approx Indicator with Higher Timeframe Filter Ver. 3.2
What It Is
The XGBoost Approx Indicator is a technical analysis tool designed to generate trading signals based on a composite of multiple indicators. It combines Simple Moving Average (SMA), Relative Strength Index (RSI), MACD, Rate of Change (ROC), and Volume to create a composite indicator score. Additionally, it incorporates a higher timeframe filter (HTF) to enhance trend confirmation and reduce false signals.
This indicator helps traders identify long (buy) and short (sell) opportunities based on a weighted combination of trend-following and momentum indicators.
How to Use It Properly
Setup and Configuration:
Add the indicator to your TradingView chart.
Customize input settings based on your trading strategy. Key configurable inputs include:
HTF filter (default: 1-hour)
SMA, RSI, MACD, and ROC lengths
Custom weightings for each component
Thresholds for buy and sell signals
Understanding the Signals:
Green "Long" Label: Appears when the composite indicator crosses above the buy threshold, signaling a potential buy opportunity.
Red "Short" Label: Appears when the composite indicator crosses below the sell threshold, signaling a potential sell opportunity.
These signals are filtered by a higher timeframe SMA trend to improve accuracy.
Alerts:
The indicator provides alert conditions for long and short entries.
Traders can enable alerts in TradingView to receive real-time notifications when a new signal is triggered.
Safety and Best Practices
Use in Conjunction with Other Analysis: Do not rely solely on this indicator. Combine it with price action, support/resistance levels, and fundamental analysis for better decision-making.
Adjust Settings for Your Strategy: The default settings may not suit all markets or timeframes. Test different configurations before trading live.
Backtest Before Using in Live Trading: Evaluate the indicator’s past performance on historical data to assess its effectiveness in different market conditions.
Avoid Overtrading: False signals can occur, especially in low volatility or choppy markets. Use additional confirmation (e.g., trendlines or moving averages).
Risk Management: Always set stop-loss levels and position sizes to limit potential losses.
CandelaCharts - Liquidity Key Zones (LKZ)📝 Overview
The Liquidity Key Zones indicator displays the previous high and low levels for daily, weekly, monthly, quarterly, and yearly timeframes. These levels serve as crucial price zones for trading any market or instrument. They are also high-probability reaction zones, ideal for trading using straightforward confirmation patterns.
Each of these levels plays a significant role in determining whether the market continues its momentum or reverses its bias. I like to think of these levels as dual magnets—they simultaneously attract and repel price. You might wonder how having opposing views can be useful. The key is to remain neutral about direction and establish your own rules to identify when these zones are likely to attract or repel price. I have my own set of rules, and you can develop yours.
📦 Features
MTF
Styling
⚙️ Settings
Day: Shows previous day levels
Week: Shows previous week levels
Month: Shows previous month levels
Quarter: Shows previous quarter levels
Year: Shows previous year levels
Show Average: Shows previous level average price
Show Open: Shows previous level open price
⚡️ Showcase
Daily
Weekly
Monthly
Quarterly
Yearly
Average
Open
📒 Usage
When the price breaks through a significant level, such as a daily, weekly, or monthly high or low, it often signals a potential reversal in market direction. This occurs because these levels represent key areas of support or resistance, where traders anticipate heightened activity, including profit-taking, stop-loss orders, or new positions being initiated.
Once the price breaches these levels, it may trigger a sharp reaction as market participants adjust their strategies, leading to a reversal. Monitoring price action and volume around these levels can provide valuable confirmation of such reversals.
Another effective approach to utilizing these pivot points is by incorporating them into a structured trading strategy, such as the X Model, which leverages multiple timeframes and technical tools to refine trade entries and exits.
X Model conditions:
(D1) Previous Day High (ERL)
(H1) Bullish FVG/IFVG/OB (IRL)
(m15) MSS / SMT
Only Short Above 00:00
By combining these elements, the X Model offers a comprehensive framework for leveraging pivot levels effectively, emphasizing confluence between liquidity zones, time-based rules, and multi-timeframe analysis to enhance trading accuracy and consistency.
🚨 Alerts
This script provides alert options for all signals.
Bearish Signal
A bearish signal is generated when the price breaks below the previous low level.
Bullish Signal
A bullish signal is generated when the price breaks above the previous low level.
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
ICT Concepts: MML, Order Blocks, FVG, OTECore ICT Trading Concepts
These strategies are designed to identify high-probability trading opportunities by analyzing institutional order flow and market psychology.
1. Market Maker Liquidity (MML) / Liquidity Pools
Idea: Institutional traders ("market makers") place orders around key price levels where retail traders’ stop losses cluster (e.g., above swing highs or below swing lows).
Application: Look for "liquidity grabs" where price briefly spikes to these levels before reversing.
Example: If price breaks a recent high but reverses sharply, it may indicate a liquidity grab to trigger retail stops before a trend reversal.
2. Order Blocks (OB)
Idea: Institutional orders are often concentrated in specific price zones ("order blocks") where large buy/sell decisions occurred.
Application: Identify bullish order blocks (strong buying zones) or bearish order blocks (strong selling zones) on higher timeframes (e.g., 1H/4H charts).
Example: A bullish order block forms after a strong rally; price often retests this zone later as support.
3. Fair Value Gap (FVG)
Idea: A price imbalance occurs when candles gap without overlapping, creating an area of "unfair" price that the market often revisits.
Application: Trade the retracement to fill the FVG. A bullish FVG acts as support, and a bearish FVG acts as resistance.
Example: Three consecutive candles create a gap; price later returns to fill this gap, offering a entry point.
4. Time-Based Analysis (NY Session, London Kill Zones)
Idea: Institutional activity peaks during specific times (e.g., 7 AM – 11 AM New York time).
Application: Focus on trades during high-liquidity periods when banks and hedge funds are active.
Example: The "London Kill Zone" (2 AM – 5 AM EST) often sees volatility due to European market openings.
5. Optimal Trade Entry (OTE)
Idea: A retracement level (similar to Fibonacci retracement) where institutions re-enter trends after a pullback.
Application: Look for 62–79% retracements in a trend to align with institutional accumulation/distribution zones.
Example: In an uptrend, price retraces 70% before resuming upward—enter long here.
6. Stop Hunts
Idea: Institutions manipulate price to trigger retail stop losses before reversing direction.
Application: Avoid placing stops at obvious levels (e.g., above/below recent swings). Instead, use wider stops or wait for confirmation.
Uptrick: Zero Lag HMA Trend Suite1. Name and Purpose
Uptrick: Zero Lag HMA Trend Suite is a Pine Version 6 script that builds upon the Hull Moving Average (HMA) to offer an advanced trend analysis tool. Its purpose is to help traders identify trend direction, potential reversals, and overall market momentum with reduced lag compared to traditional moving averages. By combining the HMA with Average True Range (ATR) thresholds, slope-dependent coloring, Volume Weighted Average Price (VWAP) ribbons, and optional reversal signals, the script aims to give a detailed view of price activity in various market environments.
2. Overview
This script begins with the calculation of a Hull Moving Average, a method that blends Weighted Moving Averages in a way designed to cut down on lag while still smoothing out price fluctuations. Next, several enhancements are applied. The script compares current HMA values to previous ones for slope-based coloring, which highlights uptrends and downtrends at a glance. It also plots buy and sell signals when price moves beyond or below thresholds determined by the ATR and the user’s chosen signal multiplier. An optional VWAP ribbon can be shown to confirm bullish or bearish conditions relative to a volume-weighted benchmark. Additionally, the script can plot reversal signals (labeled with B) at points where price crosses back toward the HMA from above or below. Taken together, these elements allow traders to visualize both the short-term momentum and the broader context of how price interacts with volatility and overall market direction.
3. Why These Indicators Have Been Linked Together
The reason the Hull Moving Average, the Average True Range, and the VWAP have been integrated into one script is to tackle multiple facets of market analysis in a single tool. The Zero Lag Hull Moving Average provides a responsive trend line, the ATR offers a measure of volatility that helps distinguish significant price shifts from typical fluctuations, and the VWAP acts as a reference for fair value based on traded volume. By layering all three, the script helps traders avoid the need to juggle multiple separate indicators and offers a holistic perspective. The slope-based coloring focuses on trend direction, the ATR-based thresholds refine possible buy and sell zones, and the VWAP ribbons provide insight into how price stands relative to an important volume-weighted level. The inclusion of up and down signals and reversal B labels further refines entries and exits.
4. Why Use Uptrick: Zero Lag HMA Trend Suite
The Hull Moving Average is already known for reacting more quickly to price changes compared to other moving averages while retaining a degree of smoothness. This suite enhances the basic HMA by showing colored gradients that make it easy to spot trend direction changes, highlighting potential entry or exit points based on volatility-driven thresholds, and optionally layering a volume-based measure of bullish or bearish market sentiment. By relying on a zero lag approach and additional data points, the script caters to those wanting a more responsive method of identifying shifts in market dynamics. The added reversal signals and up or down alerts give traders extra confirmation for potential turning points.
5. How This Extension Improves on the Basic HMA
This extension not only plots the Hull Moving Average but also includes data-driven alerts and visual cues that traditional HMA lines do not provide. First, it offers multi-layered slope coloring, making up or down trends quickly apparent. Second, it uses ATR-based thresholds to pinpoint moments when price may be extending beyond normal volatility, thus generating buy or sell signals. Third, the script introduces an optional VWAP ribbon to indicate whether the market is trading above or below this pivotal volume-weighted benchmark, adding a further confirmation step for bullish or bearish conditions. Finally, it incorporates optional reversal signals labeled with B, indicating points where price might swing back toward the main HMA line.
6. Core Components
The script can be broken down into several primary functions and features.
a. Zero Lag HMA Calculation
Uses two Weighted Moving Averages (half-length and full-length) combined through a smoothing step based on the square root of the chosen length. This approach is designed to reduce lag significantly compared to other moving averages.
b. Slope Detection
Compares current and prior HMA values to determine if the trend is up or down. The slope-based coloring changes between turquoise shades for upward movement and magenta shades for downward movement, making trend direction immediately visible.
c. ATR-Based Thresholding for Up and Down Signals
The script calculates an Average True Range over a user-defined period, then multiplies it by a signal factor to form two bands around the HMA. When price crosses below the lower band, an up (buy) signal appears; when it crosses above the upper band, a down (sell) signal is shown.
d. Reversal Signals (B Labels)
Tracks when price transitions back toward the main HMA from an extreme zone. When enabled, these reversal points are labeled with a B and can help traders see potential turning points or mean-reversion setups.
e. VWAP Bands
An optional Volume Weighted Average Price ribbon that plots above or below the HMA, indicating bullish or bearish conditions relative to a volume-weighted price benchmark. This can also act as a kind of support/ resistance.
7. User Inputs
a. HMA Length
Controls how quickly the moving average responds to price changes. Shorter lengths react faster but can lead to more frequent signals, whereas longer lengths produce smoother lines.
b. Source
Specifies the price input, such as close or an alternative source, for the calculation. This can help align the HMA with specific trading strategies.
c. ATR Length and Signal Multiplier
Defines how the script calculates average volatility and sets thresholds for buy or sell alerts. Adjusting these values can help filter out noise or highlight more aggressive signals.
d. Slope Index
Determines how many bars to look back for detecting slope direction, influencing how sensitive the slope coloring is to small fluctuations.
e. Show Buy and Sell Signals, Reversal Signals, and VWAP
Lets users toggle the display of these features. Turning off certain elements can reduce chart clutter if traders prefer a simpler layout.
8. Calculation Process
The script’s calculation follows a step-by-step approach. It first computes two Weighted Moving Averages of the selected price source, one over half the specified length and one over the full length. It then combines these using 2*wma1 minus wma2 to reduce lag, followed by applying another weighted average using the square root of the length. Simultaneously, it computes the ATR for a user-defined period. By multiplying ATR by the signal multiplier, it establishes upper and lower bands around the HMA, where crossovers generate buy (up) or sell (down) signals. The script can also plot reversal signals (B labels) when price crosses back from these bands in the opposite direction. For the optional VWAP feature, Pine Script’s ta.vwap function is used, and differences between the HMA and VWAP levels determine the color and opacity of the ribbon.
9. Signal Generation and Filtering
The ATR-based thresholds reduce the influence of small, inconsequential price swings. When price falls below the lower band, the script issues an up (buy) signal. If price breaks above the upper band, a down (sell) signal appears. These signals are visible through labels placed near the bars. Reversal signals, labeled with B, can be turned on to help detect when price retraces from an extended area back toward the main HMA line. Traders can disable or enable these signals to match their preferred level of chart detail or risk tolerance.
10. Visualization on the Chart
The Zero HMA Lag Trend Suite aims for visual clarity. The HMA line is plotted multiple times with increasing transparency to create a gradient effect. Turquoise gradients indicate upward slopes, and magenta gradients signify downward slopes. Bar coloring can be configured to align with the slope direction, providing quick insight into current momentum. When enabled, buy or sell labels are placed under or above the bars as price crosses the ATR-defined boundaries. If the reversal option is active, B labels appear around areas where price changes direction. The optional VWAP ribbons form background bands, using distinct coloration to signal whether price is above or below the volume-weighted metric.
11. Market Adaptability
Because the script’s parameters (HMA length, ATR length, signal multiplier, and slope index) are user-configurable, it can adapt to a wide range of markets and timeframes. Intraday traders may prefer a shorter HMA length for quick signals, while swing or position traders might use a longer HMA length to filter out short-lived price changes. The source setting can also be adjusted, allowing for specialized data inputs beyond just close or open values.
12. Risk Management Considerations
The script’s signals and labels are based on past price data and volatility readings, and they do not guarantee profitable outcomes. Sharp market reversals or unforeseen fundamental events can produce false signals. Traders should combine this tool with broader risk management strategies, including stop-loss placement, position sizing, and independent market analyses. The Zero HMA Lag Trend Suite can help highlight potential opportunities, but it should not be relied upon as the sole basis for trade decisions.
13. Combining with Other Tools
Many traders choose to verify signals from the Zero HMA Lag Trend Suite using popular indicators like the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), or even simple volume-based metrics to confirm whether a price movement has sufficient momentum. Conventional techniques such as support and resistance levels, chart patterns, or candlestick analysis can also supplement signals generated by the script’s up, down, or reversal B labels.
14. Parameter Customization and Examples
a. Short-Term Day Trading
Using a shorter HMA length (for instance, 9 or 14) and a slightly higher ATR multiplier might provide timely buy and sell signals, though it may also produce more whipsaws in choppy markets.
b. Swing or Position Trading
Selecting a longer HMA length (such as 50 or 100) with a moderate ATR multiplier can help users track more significant and sustained market moves, potentially reducing the effect of minor fluctuations.
c. Multiple Timeframe Blends
Some traders load two versions of the indicator on the same chart, one for short-term signals (with frequent B label reversals) and another for the broader trend direction, aligning entry and exit decisions with the bigger picture.
15. Realistic Expectations
Even though the Hull Moving Average helps minimize lag and the script incorporates volatility-based filters and optional VWAP overlays, it cannot predict future market behavior with complete accuracy. Periods of low liquidity or sudden market shocks can still lead to signals that do not reflect longer-term trends. Frequent parameter review and manual confirmation are advised before executing trades based solely on the script’s outputs.
16. Theoretical Background
The Hull Moving Average formula aims to balance smoothness with reactivity, accomplished by combining Weighted Moving Averages at varying lengths. By subtracting a slower average from a faster one and then applying another smoothing step with the square root of the original length, the HMA is designed to respond more promptly to price changes than typical exponential or simple moving averages. The ATR component, introduced by J. Welles Wilder, calculates the average range of price movement over a user-defined period, allowing the script to assess volatility and adapt signals accordingly. VWAP provides a volume-weighted benchmark that many institutional traders track to gauge fair intraday value.
17. Originality and Uniqueness
Although multiple HMA-based indicators can be found, Uptrick: Zero Lag HMA Trend Suite sets itself apart by merging slope-based coloring, ATR thresholds, VWAP ribbons, up or down labels, and optional reversal signals all in one cohesive platform. This synergy aims to reduce chart clutter while still giving traders a comprehensive look at trend direction, volatility, and volume-based sentiment.
18. Summary
Uptrick: Zero Lag HMA Trend Suite is a specialized trading script designed to highlight potential market trends and reversals with minimal delay. It leverages the Hull Moving Average for an adaptive yet smooth price line, pairs ATR-based thresholds for detecting possible breakouts or dips, and provides VWAP-based ribbons for added volume-weighted context. Traders can further refine their entries and exits by enabling up or down signals and reversal labels (B) where price may revert toward the HMA. Suitable for a wide range of timeframes and instrument types, the script encourages a disciplined approach to trade management and risk control.
19. Disclaimer
This script is provided for informational and educational purposes only. Trading and investing involve significant financial risk, and no indicator can guarantee success under all conditions. Users should practice robust risk management, including the placement of stop losses and position sizing, and should confirm signals with additional analysis tools. The developer of this script assumes no liability for any trading decisions or outcomes resulting from its use.
RSI + ADX + ATR 18-01-25Combining RSI (Relative Strength Index), ADX (Average Directional Index), and ATR (Average True Range) creates a synergistic approach to technical analysis. This powerful trio covers momentum, trend strength, and volatility, providing comprehensive insights into market conditions. Here's a deeper exploration of their combined results:
1. Momentum Assessment with RSI
Purpose: RSI measures the speed and magnitude of recent price changes to determine overbought or oversold levels.
Benefit in Combination:
When RSI indicates overbought (above 70) or oversold (below 30) levels, it signals a potential reversal or correction.
However, these signals can be false in strongly trending markets, which is why ADX is used alongside it.
2. Trend Strength Confirmation with ADX
Purpose: ADX confirms the presence and strength of a trend.
Benefit in Combination:
If RSI shows a potential reversal but ADX indicates a strong trend (above 25), the trend is likely to continue, and RSI signals may need to be approached with caution.
Conversely, if ADX is below 20 (weak trend), RSI signals are more likely to indicate genuine reversals, as the market lacks a strong directional push.
3. Volatility Analysis with ATR
Purpose: ATR evaluates the level of price volatility.
Benefit in Combination:
High ATR values indicate volatile conditions where prices can move significantly; this helps in setting wider stop-loss levels to avoid premature exits.
Low ATR values suggest quieter markets, where tighter stop-losses and profit targets are more suitable.
Fibonacci Channel Standard Deviation levels based off 200MAThis script dynamically combines Fibonacci levels with the 200-period simple moving average (SMA), offering a powerful tool for identifying high-probability support and resistance zones. By adjusting to the changing 200 SMA, the script remains relevant across different market phases.
Key Features:
Dynamic Fibonacci Levels:
The script automatically calculates Fibonacci retracements and extensions relative to the 200 SMA.
These levels adapt to market trends, offering more relevant zones compared to static Fibonacci tools.
Support and Resistance Zones:
In uptrends, price often respects retracement levels above the 200 SMA (e.g., 38.2%, 50%, 61.8%).
In downtrends, price may interact with retracements and extensions below the 200 SMA (e.g., 23.6%, 1.618).
Customizable Confluence Zones:
Key levels such as the golden pocket (61.8%–65%) are highlighted as high-probability zones for reversals or continuations.
Extensions (e.g., 1.618) can serve as profit targets or bearish continuation points.
Practical Applications:
Identifying Reversal Zones:
Look for confluence between Fibonacci levels and the 200 SMA to identify potential reversal points.
Example: A pullback to the 61.8%–65% golden pocket near the 200 SMA often signals a bullish reversal.
Trend Confirmation:
In uptrends, price respecting Fibonacci retracements above the 200 SMA (e.g., 38.2%, 50%) confirms strength.
Use Fibonacci extensions (e.g., 1.618) as profit targets during strong trends.
Dynamic Risk Management:
Place stop-losses just below key Fibonacci retracement levels near the 200 SMA to minimize risk.
Bearish Scenarios:
Below the 200 SMA, Fibonacci retracements and extensions act as resistance levels and bearish targets.
How to Use:
Volume Confirmation: Watch for volume spikes near Fibonacci levels to confirm support or resistance.
Price Action: Combine with candlestick patterns (e.g., engulfing candles, pin bars) for precise entries.
Trend Indicators: Use in conjunction with shorter moving averages or RSI to confirm market direction.
Example Setup:
Scenario: Price retraces to the 61.8% Fibonacci level while holding above the 200 SMA.
Confirmation: Volume spikes, and a bullish engulfing candle forms.
Action: Enter long with a stop-loss just below the 200 SMA and target extensions like 1.618.
Key Takeaways:
The 200 SMA serves as a reliable long-term trend anchor.
Fibonacci retracements and extensions provide dynamic zones for trade entries, exits, and risk management.
Combining this tool with volume, price action, or other indicators enhances its effectiveness.
Supertrend EMA & KNNSupertrend EMA & KNN
The Supertrend EMA indicator cuts through the noise to deliver clear trend signals.
This tool is built using the good old Exponential Moving Averages (EMAs) with a novel of machine learning; KNN (K Nearest Neighbors) breakout detection method.
Key Features:
Effortless Trend Identification: Supertrend EMA simplifies trend analysis by automatically displaying a color-coded EMA. Green indicates an uptrend, red signifies a downtrend, and the absence of color suggests a potential range.
Dynamic Breakout Detection: Unlike traditional EMAs, Supertrend EMA incorporates a KNN-based approach to identify breakouts. This allows for faster color changes compared to standard EMAs, offering a more dynamic picture of the trend.
Customizable Parameters: Fine-tune the indicator to your trading style. Adjust the EMA length for trend smoothing, KNN lookback window for breakout sensitivity, and breakout threshold for filtering noise.
A Glimpse Under the Hood:
Dual EMA Power: The indicator utilizes two EMAs. A longer EMA (controlled by the "EMA Length" parameter) provides a smooth trend direction, while a shorter EMA (controlled by the "Short EMA Length" parameter) triggers color changes, aiming for faster response to breakouts.
KNN Breakout Detection: This innovative feature analyzes price action over a user-defined lookback period (controlled by the "KNN Lookback Length" parameter) to identify potential breakouts. If the price surpasses a user-defined threshold (controlled by the "Breakout Threshold" parameter) above the recent highs, a green color is triggered, signaling a potential uptrend. Conversely, a breakdown below the recent lows triggers a red color, indicating a potential downtrend.
Trading with Supertrend EMA:
Ride the Trend: When the indicator displays green, look for long (buy) opportunities, especially when confirmed by bullish price action patterns on lower timeframes. Conversely, red suggests potential shorting (sell) opportunities, again confirmed by bearish price action on lower timeframes.
Embrace Clarity: The color-coded EMA provides a clear visual representation of the trend, allowing you to focus on price action and refine your entry and exit strategies.
A Word of Caution:
While Supertrend EMA offers faster color changes than traditional EMAs, it's important to acknowledge a slight inherent lag. Breakout detection relies on historical data, and there may be a brief delay before the color reflects a new trend.
To achieve optimal results, consider:
Complementary Tools: Combine Supertrend EMA with other indicators or price action analysis for additional confirmation before entering trades.
Solid Risk Management: Always practice sound risk management strategies such as using stop-loss orders to limit potential losses.
Supertrend EMA is a powerful tool designed to simplify trend identification and enhance your trading experience. However, remember, no single indicator guarantees success. Use it with a comprehensive trading strategy and disciplined risk management for optimal results.
Disclaimer:
While the Supertrend EMA indicator can be a valuable tool for identifying potential trend changes, it's important to note that it's not infallible. Market conditions can be highly dynamic, and indicators may sometimes provide false signals. Therefore, it's crucial to use this indicator in conjunction with other technical analysis tools and sound risk management practices. Always conduct thorough research and consider consulting with a financial advisor before making any investment decisions.
Futures Beta Overview with Different BenchmarksBeta Trading and Its Implementation with Futures
Understanding Beta
Beta is a measure of a security's volatility in relation to the overall market. It represents the sensitivity of the asset's returns to movements in the market, typically benchmarked against an index like the S&P 500. A beta of 1 indicates that the asset moves in line with the market, while a beta greater than 1 suggests higher volatility and potential risk, and a beta less than 1 indicates lower volatility.
The Beta Trading Strategy
Beta trading involves creating positions that exploit the discrepancies between the theoretical (or expected) beta of an asset and its actual market performance. The strategy often includes:
Long Positions on High Beta Assets: Investors might take long positions in assets with high beta when they expect market conditions to improve, as these assets have the potential to generate higher returns.
Short Positions on Low Beta Assets: Conversely, shorting low beta assets can be a strategy when the market is expected to decline, as these assets tend to perform better in down markets compared to high beta assets.
Betting Against (Bad) Beta
The paper "Betting Against Beta" by Frazzini and Pedersen (2014) provides insights into a trading strategy that involves betting against high beta stocks in favor of low beta stocks. The authors argue that high beta stocks do not provide the expected return premium over time, and that low beta stocks can yield higher risk-adjusted returns.
Key Points from the Paper:
Risk Premium: The authors assert that investors irrationally demand a higher risk premium for holding high beta stocks, leading to an overpricing of these assets. Conversely, low beta stocks are often undervalued.
Empirical Evidence: The paper presents empirical evidence showing that portfolios of low beta stocks outperform portfolios of high beta stocks over long periods. The performance difference is attributed to the irrational behavior of investors who overvalue riskier assets.
Market Conditions: The paper suggests that the underperformance of high beta stocks is particularly pronounced during market downturns, making low beta stocks a more attractive investment during volatile periods.
Implementation of the Strategy with Futures
Futures contracts can be used to implement the betting against beta strategy due to their ability to provide leveraged exposure to various asset classes. Here’s how the strategy can be executed using futures:
Identify High and Low Beta Futures: The first step involves identifying futures contracts that have high beta characteristics (more sensitive to market movements) and those with low beta characteristics (less sensitive). For example, commodity futures like crude oil or agricultural products might exhibit high beta due to their price volatility, while Treasury bond futures might show lower beta.
Construct a Portfolio: Investors can construct a portfolio that goes long on low beta futures and short on high beta futures. This can involve trading contracts on stock indices for high beta stocks and bonds for low beta exposures.
Leverage and Risk Management: Futures allow for leverage, which means that a small movement in the underlying asset can lead to significant gains or losses. Proper risk management is essential, using stop-loss orders and position sizing to mitigate the inherent risks associated with leveraged trading.
Adjusting Positions: The positions may need to be adjusted based on market conditions and the ongoing performance of the futures contracts. Continuous monitoring and rebalancing of the portfolio are essential to maintain the desired risk profile.
Performance Evaluation: Finally, investors should regularly evaluate the performance of the portfolio to ensure it aligns with the expected outcomes of the betting against beta strategy. Metrics like the Sharpe ratio can be used to assess the risk-adjusted returns of the portfolio.
Conclusion
Beta trading, particularly the strategy of betting against high beta assets, presents a compelling approach to capitalizing on market inefficiencies. The research by Frazzini and Pedersen emphasizes the benefits of focusing on low beta assets, which can yield more favorable risk-adjusted returns over time. When implemented using futures, this strategy can provide a flexible and efficient means to execute trades while managing risks effectively.
References
Frazzini, A., & Pedersen, L. H. (2014). Betting against beta. Journal of Financial Economics, 111(1), 1-25.
Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. Journal of Finance, 47(2), 427-465.
Black, F. (1972). Capital Market Equilibrium with Restricted Borrowing. Journal of Business, 45(3), 444-454.
Ang, A., & Chen, J. (2010). Asymmetric volatility: Evidence from the stock and bond markets. Journal of Financial Economics, 99(1), 60-80.
By utilizing the insights from academic literature and implementing a disciplined trading strategy, investors can effectively navigate the complexities of beta trading in the futures market.
Demand and Supply Conditions with SignalsIntroduction:
This document outlines a trading strategy that utilizes price action analysis and color signals to make informed trading decisions. The strategy focuses on identifying demand and supply conditions, curve patterns, and generating signals based on historical price data. The colors associated with each condition and signal serve as visual indicators to assist in decision-making.
I. Strategy Overview:
Objective:
The objective of this trading strategy is to identify potential trading opportunities based on price action analysis and color signals.
Key Components:
Demand Condition: A green upward-facing triangle indicates a potential demand condition.
Supply Condition: A red downward-facing triangle indicates a potential supply condition.
Curve Pattern Condition: A blue upward-facing triangle indicates a potential curve pattern condition.
Signal Condition: A yellow upward-facing triangle indicates a potential buy signal.
II. Understanding the Colors:
* Green: Represents the demand condition, which suggests potential buying pressure in the market. A green upward-facing triangle is plotted on the chart when the demand condition is met at a specific candle or bar.
* Red: Represents the supply condition, which suggests potential selling pressure in the market. A red downward-facing triangle is plotted on the chart when the supply condition is met at a specific candle or bar.
* Blue: Represents the curve pattern condition, which suggests the presence of a specific pattern based on price action analysis. A blue upward-facing triangle is plotted on the chart when the curve pattern condition is met at a specific candle or bar.
* Yellow: Represents the signal condition, which is a combination of the demand condition and the curve pattern condition. A yellow upward-facing triangle is plotted on the chart when the signal condition is met at a specific candle or bar, indicating a potential buy signal.
III. Decision-Making Process:
* Demand and Supply Conditions: Identify potential buying opportunities when a green demand condition is present. Consider potential selling opportunities when a red supply condition is present. Use these conditions to assess the overall market sentiment and potential price reversals.
* Curve Patterns: Analyze the presence of blue curve pattern conditions to identify specific price patterns. These patterns can provide additional confirmation for potential trading decisions.
* Signal Condition: Pay attention to the yellow signal condition, which indicates a potential buy signal. Evaluate the overall market context and consider entering a buy position when the signal condition is met.
* Risk Management: Implement proper risk management techniques such as setting stop-loss orders and position sizing to protect against potential losses.
IV. Conclusion:
This trading strategy leverages price action analysis and color signals to identify potential trading opportunities. The colors associated with each condition and signal serve as visual aids to highlight specific points on the chart. It's important to thoroughly backtest and validate the strategy before applying it to real-world trading scenarios. Additionally, always consider market conditions, risk management, and individual trading preferences when making trading decisions.
Disclaimer: Trading involves risks, and this document does not guarantee profitable outcomes. Traders should exercise caution and perform their own due diligence before engaging in any trading activity.
Remember to continually review and adapt your trading strategy based on market conditions and personal experiences to enhance its effectiveness.
Heartbeat Momentum Strategy BetaHeartbeat Momentum Strategy Beta
Overview
The Heartbeat Momentum Strategy is an innovative approach to market analysis that draws inspiration from the rhythmic patterns of a heartbeat. This strategy aims to identify significant momentum shifts in the market by comparing short-term and long-term moving averages, analogous to detecting irregularities in a heartbeat.
Key Concepts
Market Heartbeat: The difference between short-term and long-term moving averages, representing the market's current 'pulse'.
Heartbeat Volatility: Measured by the standard deviation of the market heartbeat.
Momentum Signals: Generated when the heartbeat deviates significantly from its normal range.
How It Works
Calculates a short-term moving average (default 5 periods) and a long-term moving average (default 20 periods) of the closing price.
Computes the 'heartbeat' by subtracting the long-term MA from the short-term MA.
Measures the volatility of the heartbeat using its standard deviation over the long-term period.
Generates buy signals when the heartbeat exceeds 2 standard deviations above its mean.
Generates sell signals when the heartbeat falls 2 standard deviations below its mean.
Indicator Components
Blue Line: Short-term moving average
Red Line: Long-term moving average
Green Triangles: Buy signals
Red Triangles: Sell signals
Background Color: Light green during buy signals, light red during sell signals
Strategy Parameters
Short MA Window: The period for the short-term moving average (default: 5)
Long MA Window: The period for the long-term moving average (default: 20)
Standard Deviation Threshold: The number of standard deviations to trigger a signal (default: 2.0)
Interpretation
Buy Signal: Indicates a potential strong upward momentum shift. Consider opening long positions or closing short positions.
Sell Signal: Suggests a potential strong downward momentum shift. Consider opening short positions or closing long positions.
No Signal: The market is moving within its normal rhythm. Maintain current positions or look for other entry opportunities.
Customization
Users can adjust the strategy parameters to suit different assets, timeframes, or trading styles:
Decrease the MA windows for more frequent signals (more suitable for shorter timeframes).
Increase the MA windows for fewer, potentially more significant signals (better for longer timeframes).
Adjust the Standard Deviation Threshold to fine-tune sensitivity (lower for more signals, higher for fewer but potentially stronger signals).
Risk Management
While this strategy can provide valuable insights into market momentum, it should not be used in isolation:
Always use stop-loss orders to manage potential losses.
Consider the overall market context and other technical/fundamental factors.
Be aware of potential false signals, especially in ranging or highly volatile markets.
Backtest and forward-test the strategy with different parameters before live trading.
Conclusion
The Heartbeat Momentum Strategy offers a unique perspective on market movements by treating price action like a heartbeat. By identifying significant deviations from the normal market rhythm, it aims to capture strong momentum shifts while filtering out market noise. As with any trading strategy, use it as part of a comprehensive trading plan and always practice sound risk management.
Engulfing with Fibonacci LevelsIndicator Explanation
The indicator identifies bullish and bearish engulfing patterns and plots Fibonacci levels based on these patterns. Here's a detailed explanation of the script:
1. Bullish Engulfing Pattern
A bullish engulfing pattern is identified when:
- The previous candle is bearish (`close < open `).
- The current candle is bullish (`close > open`).
- The low of the current candle is lower than the low of the previous candle (`low < low `).
- The current candle's close is higher than the previous candle's open (`close > open `).
When a bullish engulfing pattern is identified:
- Fibonacci levels are plotted from the low (0%) to the high (100%) of the bullish candle.
- A green dot is plotted below the bullish candle to indicate a buy signal.
2. Bearish Engulfing Pattern
A bearish engulfing pattern is identified when:
- The previous candle is bullish (`close > open `).
- The current candle is bearish (`close < open`).
- The high of the current candle is higher than the high of the previous candle (`high > high `).
- The current candle's close is lower than the previous candle's open (`close < open `).
When a bearish engulfing pattern is identified:
- Fibonacci levels are plotted from the high (0%) to the low (100%) of the bearish candle.
- A red dot is plotted above the bearish candle to indicate a sell signal.
3. Plotting Fibonacci Levels
For both bullish and bearish patterns, Fibonacci levels are plotted at:
- 0% (high for bullish, low for bearish)
- 50%
- 61.8%
- 79%
- 100% (low for bullish, high for bearish)
Smart Money Concept (SMC) Explanation
Bearish Signal
In the context of Smart Money Concepts (SMC), a bearish engulfing pattern can indicate:
- **Buy Side Liquidity Grab**: The high of the current bearish candle goes above the high of the previous bullish candle, potentially grabbing buy-side liquidity (stop losses of short positions or buy stops).
- **Break of Structure (BoS)**: The close of the bearish candle below the open of the previous bullish candle indicates a shift in market structure.
After identifying this bearish engulfing pattern, a smart money trader might:
1. Wait for the market to retrace 50% of the bearish candle.
2. Enter a sell trade around the 50% retracement level, anticipating a continuation of the downward move.
#### Bullish Signal
Similarly, a bullish engulfing pattern can indicate:
- **Sell Side Liquidity Grab**: The low of the current bullish candle goes below the low of the previous bearish candle, potentially grabbing sell-side liquidity (stop losses of long positions or sell stops).
- **Break of Structure (BoS)**: The close of the bullish candle above the open of the previous bearish candle indicates a shift in market structure.
After identifying this bullish engulfing pattern, a smart money trader might:
1. Wait for the market to retrace 50% of the bullish candle.
2. Enter a buy trade around the 50% retracement level, anticipating a continuation of the upward move.
The indicator helps traders identify key engulfing patterns that align with smart money concepts of liquidity grabs and breaks of structure. By plotting Fibonacci levels, it visually aids traders in waiting for optimal retracement levels (50%) to enter trades in the direction of the anticipated move. This approach leverages the idea that significant market participants often seek liquidity and cause structural shifts, providing entry opportunities for informed traders.
Prometheus Polarized Fractal Efficiency (PFE)This indicator uses market data to calculate Polarized Fractal Efficiency (PFE) on an asset, so traders can have a better idea of which direction it may go.
Users can control the lookback length for the fractal calculation, the lookback length for the Exponential Moving Average (EMA), and whether or not to display lines at the -50 and 50 level, or -25 and 25 level.
Polarized Fractal Efficiency:
The Polarized Fractal Efficiency (PFE) indicator is a value between -100 and 100 with 0 as a midpoint.
A PFE above 0 indicates the asset may trend higher, a PFE below 0 indicates the asset may trend lower.
There are many ways to trade with PFE, the intuitive trend riding as described above, or reversals.
Even when the PFE is above 0, if it gets high enough, it may also be an indication of a reversal. A PFE of 90 - 100, or -100 - -90, may indicate price is ready to revert the other direction. Furthermore, traders already in a position may look to breaks of other levels to be their take profit or stop out spot.
Calculation:
Pi = 100 x (Price - Price )2 + N2 / Summation, j= 0, to N-2 (Price - Price )2 + 1
If Close < Close Pi = -Pi
PFEi = EMA(Pi, M)
Where:
N = period of indicator
M = smoothing period
Citation: www.investopedia.com
Scenarios:
Inputs are (9, 5) and every display option is on.
Trend example
Step 1: A short trade appears as PFE crosses below -25. We reach a safe take profit as PFE crosses below -50. Traders can use these levels to exit as well as enter.
Step 2: On the cross above 25 there is a safe long. As the PFE value breaks 0 a safe, early take profit could be appropriate for this trade. No guarantee we would see 50.
Step 3: Long scenario at break of 25, straight to 50. Simple, straightforward setup.
Step 4: This long results in a stop loss. Once again entry as PFE crosses 25, but as we cross the 0 line it is for a loss.
Step 5: The last trade in this example is reminiscent of step 3. This is a short trade entry at break of 25 and exit at break of 50.
Traders have liberty to use the PFE value to determine spots to enter and exit trades, long or short. 25 and 50 were chosen arbitrarily, values like 10 and 60 may work as well, we encourage traders to use their own discretion along with tools.
Reversal example
Step 1: PFE is around -100, crossing below it at one point! Strong zone for a potential reversal.
Step 2: PFE crosses above 25 adding conviction.
Step 3: Option to exit at 70.
Step 4: Option to exit at 90.
There is no “one size fits all method”, this approach may be more intuitive for some users and is just as feasible as the first.
Longer trend example
Step 1: Using -50 and 50 this time instead of -25 and 25 to be safer on our entries we see a short here. Was a good entry and as the value gets closer to -70 we can safely close.
Step 2: On this candle we see a long for the break of 50. On the next candle we break the 0 line, but because of our safe entry at 50, we could hold this and only stop out at a break of -25. We get close but stay in it and close at 70.
Step 3: Break of 50 for a long once again. This time the break of 0 line occurs as we are in profit, not letting a green trade go red is a golden rule of trading, so an early exit here.
Step 4: Same at step 2, break of 50 to long and stay in it, not stopping out at break of 0 line. The PFE value eventually reaches 70 and there is a good exit.
Quicker Reversal example
Step 1: Notice a close with PFE below -90, enter long for the reversal. Then close for profit when the PFE crosses above 70.
Step 2: When the PFE breaks above 90 we have a short entry. Like the long closing it when it crosses below -70.
Step 3: This step is the same setup as step 2. As PFE breaks above 90 we have a short entry. Closing it when it crosses below -70.
Recap:
Described above are 4 different examples with many different trades. Both trend and reversal trades. The PFE value is an indicator that can be used by traders in many different ways and Prometheus encourages traders to use their own discretion along with tools and not follow indicators blindly.
Options:
Users can control the input for the lookback of the indicator. The default is 9.
The smoothing factor for the EMA is also changeable, default is 5.
Users have options to display lines at -50, -25, 25, and 50.
CARNAC Trading Support and Resistance LevelsOverview
The "Carnac Trading Support and Resistance Levels" indicator is a powerful tool designed to help traders identify key support and resistance levels across multiple timeframes. This tool enhances trading strategies by visually marking significant price levels and providing configurable stop-loss and alert features.
Features
Support and Resistance Levels: Automatically calculates and plots support and resistance levels for the following timeframes:
5 minutes (5M)
10 minutes (10M)
15 minutes (15M)
30 minutes (30M)
1 hour (1H)
2 hours (2H)
4 hours (4H)
6 hours (6H)
12 hours (12H)
1 day (1D)
1 week (1W)
1 month (1M)
Configurable Stop-Loss (SL) Levels: Adds a stop-loss line below each support level and above each resistance level with customizable padding (as a percentage).
Visual Labels: Clearly labels support, resistance, and stop-loss levels with the corresponding prices and timeframes for easy identification.
Line Customization:
Support Levels: Green lines with varying thickness based on the timeframe.
Resistance Levels: Red lines with varying thickness based on the timeframe.
Stop-Loss Levels: Gray dotted lines for clear distinction.
Alerts: Alerts trigger when the price gets to a configurable percentage from the support or resistance levels, helping you stay informed about potential buying and selling opportunities.
Visibility Toggling: Easily toggle the visibility of support and resistance levels for each timeframe (default enabled for 2H, 4H, and 1D).
How to Use
Add the Indicator:
Navigate to the TradingView Pine Editor.
Paste the provided Pine Script code and click "Add to Chart."
Configure Inputs:
Lookback Periods: Adjust the lookback periods for each timeframe to suit your analysis needs.
Padding Percentage: Set the padding percentage for the stop-loss levels to define the distance below the support levels and above the resistance levels.
Visibility: Toggle the visibility of the support and resistance levels for each timeframe as needed (default enabled for 2H, 4H, and 1D).
Alert Trigger Distance: Set the alert trigger distance as a percentage to determine when the alerts should be triggered.
Interpret the Plotted Levels:
Green Lines: Indicate support levels for the respective timeframes.
Red Lines: Indicate resistance levels for the respective timeframes.
Gray Dotted Lines: Represent the stop-loss levels below each support level and above each resistance level, with the specified padding.
Labels: Provide clear indications of the price levels and their respective timeframes in white text for visibility.
Identifying Buying and Selling Opportunities:
Buying Opportunities:
Look for the price to approach or bounce off a support level (green line).
Confirm the potential for a reversal by checking if the price is nearing a key support level from multiple timeframes.
Use the stop-loss level (gray dotted line) to set your stop-loss order below the support level to minimize risk.
Selling Opportunities:
Look for the price to approach or get rejected at a resistance level (red line).
Confirm the potential for a reversal by checking if the price is nearing a key resistance level from multiple timeframes.
Use the stop-loss level (gray dotted line) to set your stop-loss order above the resistance level to minimize risk.
Alerts:
Alerts will notify you when the price gets within the specified percentage distance from each support or resistance level.
Use these alerts to stay informed about potential buying and selling opportunities.
