Williams Fractals for ExtremesThis script, written in Pine Script (version 5), implements an indicator for the automatic detection and visualization of fractal extremes on the price chart. The core algorithm is based on Bill Williams' fractal theory and identifies local highs and lows, which are often used to determine potential reversal points and support/resistance levels in the market.
### Key Features:
#### Fractal Detection:
- The indicator identifies a fractal high if the middle candle in a sequence of five candles (two on the left and two on the right) has the highest value.
- A fractal low is identified if the middle candle in the same type of five-candle sequence has the lowest value.
#### Extreme Visualization:
- Fractal highs are displayed as red dots on the chart, signaling potential local peaks.
- Fractal lows are shown as green dots, indicating local troughs.
### Usage:
- The indicator is designed for use across all timeframes and can be applied to both cryptocurrency and traditional financial markets.
- Highlighted points allow traders to quickly spot key levels, aiding in identifying potential zones for trade entry or exit.
### Application in Trading:
#### Identifying Key Levels:
- Fractal highs and lows can serve as resistance and support levels. A breakout beyond a fractal in either direction may signal a continuation of movement in that direction.
#### Finding Reversal Points:
- Fractal extremes indicate potential market reversals, making them useful in counter-trend trading strategies.
#### Adaptability to Market Conditions:
- The indicator updates dynamically with the appearance of new candles, providing traders with real-time fractal extreme levels.
### Settings and Parameters:
- In its current version, the script does not include customizable settings as it implements the standard concept of Williams' fractals.
Cerca negli script per "support resistance"
Enhanced London Session SMC SetupEnhanced London Session SMC Setup Indicator
This Pine Script-based indicator is designed for traders focusing on the London trading session, leveraging smart money concepts (SMC) to identify potential trading opportunities in the GBP/USD currency pair. The script uses multiple techniques such as Order Block Detection, Imbalance (Fair Value Gap) Analysis, Change of Character (CHoCH) detection, and Fibonacci retracement levels to aid in market structure analysis, providing a well-rounded approach to trade setups.
Features:
London Session Highlight:
The indicator visually marks the London trading session (from 08:00 AM to 04:00 PM UTC) on the chart using a blue background, signaling when the high-volume, high-impulse moves tend to occur, helping traders focus their analysis on this key session.
Order Block Detection:
Identifies significant impulse moves that may form order blocks (supply and demand zones). Order blocks are areas where institutions have executed large orders, often leading to price reversals or continuation. The indicator plots the high and low of these order blocks, providing key levels to monitor for potential entries.
Imbalance (Fair Value Gap) Detection:
Detects and highlights price imbalances or fair value gaps (FVG) where the market has moved too quickly, creating a gap in price action. These areas are often revisited by price, offering potential trade opportunities. The upper and lower bounds of the imbalance are visually marked for easy reference.
Change of Character (CHoCH) Detection:
This feature identifies potential trend reversals by detecting significant changes in market character. When the price action shifts from bullish to bearish or vice versa, a CHoCH signal is triggered, and the corresponding level is marked on the chart. This can help traders catch trend reversals at key levels.
Fibonacci Retracement Levels:
The script calculates and plots the key Fibonacci retracement levels (0.618 and 0.786 by default) based on the highest and lowest points over a user-defined swing lookback period. These levels are commonly used by traders to identify potential pullback zones where price may reverse or find support/resistance.
Directional Bias Based on Market Structure:
The indicator provides a market structure analysis by comparing the current highs and lows to the previous periods' highs and lows. This helps in identifying whether the market is in a bullish or bearish state, providing a clear directional bias for trade setups.
Alerts:
The indicator comes with built-in alert conditions to notify the trader when an order block, imbalance, CHoCH, or other significant price action event is detected, ensuring timely action can be taken.
Ideal Usage:
Timeframe: Suitable for intraday trading, particularly focusing on the London session (08:00 AM to 04:00 PM UTC).
Currency Pair: Specifically designed for GBP/USD but can be adapted to other pairs with similar market behavior.
Trading Strategy: Best used in conjunction with a price action strategy, focusing on the key levels identified (order blocks, FVG, CHoCH) and using Fibonacci retracement levels for precision entries.
Target Audience: Ideal for traders who follow smart money concepts (SMC) and are looking for a structured approach to identify high-probability setups during the London session.
Jackson Volume breaker Indication# Jackson Volume Breaker Beta
### Advanced Volume Analysis Indicator
## Description
The Jackson Volume Breaker Beta is a sophisticated volume analysis tool that helps traders identify buying and selling pressure by analyzing price action and volume distribution. This indicator separates and visualizes buying and selling volume based on where the price closes within each candle's range, providing clear insights into market participation and potential trend strength.
## Key Features
1. **Smart Volume Distribution**
- Automatically separates buying and selling volume
- Color-coded volume bars (Green for buying, Red for selling)
- Winning volume always displayed on top for quick visual reference
2. **Real-time Volume Analysis**
- Shows current candle's buy/sell ratio
- Displays total volume with smart number formatting (K, M, B)
- Percentage-based volume distribution
3. **Technical Overlays**
- 20-period Volume Moving Average
- Dynamic scaling relative to price action
- Clean, uncluttered visual design
## How to Use
### Installation
1. Add the indicator to your chart
2. Adjust the Volume Scale input based on your preference (default: 0.08)
3. Toggle the Moving Average display if desired
### Reading the Indicator
#### Volume Bars
- **Green Bars**: Represent buying volume
- **Red Bars**: Represent selling volume
- **Stacking**: The larger volume (winning side) is always displayed on top
- **Height**: Relative to the actual volume, scaled for chart visibility
#### Information Table
The top-right table shows three key pieces of information:
1. **Left Percentage**: Winning side's volume percentage
2. **Middle Percentage**: Losing side's volume percentage
3. **Right Number**: Total volume (abbreviated)
### Trading Applications
1. **Trend Confirmation**
- Strong buying volume in uptrends confirms bullish pressure
- High selling volume in downtrends confirms bearish pressure
- Volume divergence from price can signal potential reversals
2. **Support/Resistance Breaks**
- High volume on breakouts suggests stronger moves
- Low volume on breaks might indicate false breakouts
- Monitor volume distribution for break direction confirmation
3. **Reversal Identification**
- Volume shift from selling to buying can signal potential bottoms
- Shift from buying to selling can indicate potential tops
- Use with price action for better entry/exit points
## Input Parameters
1. **Volume Scale (0.01 to 1.0)**
- Controls the height of volume bars
- Default: 0.08
- Adjust based on your chart size and preference
2. **Show MA (True/False)**
- Toggles 20-period volume moving average
- Useful for identifying volume trends
- Default: True
3. **MA Length (1+)**
- Changes the moving average period
- Default: 20
- Higher values for longer-term volume trends
## Best Practices
1. **Multiple Timeframe Analysis**
- Compare volume patterns across different timeframes
- Look for volume convergence/divergence
- Use higher timeframes for major trend confirmation
2. **Combine with Other Indicators**
- Price action patterns
- Support/resistance levels
- Momentum indicators
- Trend indicators
3. **Volume Pattern Recognition**
- Monitor for unusual volume spikes
- Watch for volume climax patterns
- Identify volume dry-ups
## Tips for Optimization
1. Adjust the Volume Scale based on your chart size
2. Use smaller timeframes for detailed volume analysis
3. Compare current volume bars to historical patterns
4. Watch for volume/price divergences
5. Monitor volume distribution changes near key price levels
## Note
This indicator works best when combined with proper price action analysis and risk management strategies. It should not be used as a standalone trading system but rather as part of a comprehensive trading approach.
## Version History
- Beta Release: Initial public version
- Features buy/sell volume separation, moving average, and real-time analysis
- Optimized for both intraday and swing trading timeframes
## Credits
Developed by Jackson based on other script creators
Special thanks to the trading community for feedback and suggestions
First 1-Minute Candle High/Low After Specific TimeDescription:
This indicator captures and marks the high and low of the first 1-minute candle after a specified time (default: 9:30 AM) and tracks the highs and lows of the first five candles. The levels marked by these initial candles are often critical in determining early session support and resistance, providing a visual guide for traders monitoring price action in the opening minutes of a trading session.
Key Features and Usage
1-Minute Candle High/Low: The indicator captures the high and low of the first 1-minute candle after the specified session start time. This level is marked with horizontal lines and labels, providing traders with an immediate reference for early-session price extremes.
5-Candle Range High/Low: After the first five candles, the indicator also highlights the highest and lowest levels within this range, offering additional support/resistance lines to aid in understanding early price movements.
Custom Labels and Dynamic Line Extension:
Labels update dynamically and display whether the 1-minute high/low coincides with the 5-minute range high/low, combining these labels if they match.
Horizontal lines extend to the current bar to remain visible throughout the session for consistent reference.
Customization Options
Colors and Label Text: Users can adjust colors for the 1-minute and 5-minute high/low lines and the label text for optimal readability.
Label Position Offset: Labels are placed slightly above or below their respective lines to avoid overlap with price action, maintaining clarity on the chart.
Intended Use
This indicator is especially useful for intraday traders focusing on opening range breakout strategies, scalping, or short-term trend analysis. It is intended for use on intraday charts (such as 1-minute or 5-minute intervals) and provides straightforward levels to assess early market structure.
Technical Details
Customization of Start Time: Users can change the default start time to any desired session opening time, adapting it to various markets or trading sessions.
Dynamic Line and Label Updates: Both lines and labels dynamically extend with the chart, while labels remain easy to read as they shift based on recent price action.
This script is designed to be simple yet powerful, offering key insights into session open levels without relying on predictive or lookahead features. It is useful for real-time analysis and adds value by helping traders identify critical levels in the market's early stages.
Dual price forecast with Projection Zone [FXSMARTLAB]The Dual Price Forecast with Projection Zone indicator is built to simulate potential future price paths based on historical price movements over two defined lookback periods. By running multiple trials (or simulations) on these historical price movements, the indicator achieves a more robust forecast, incorporating the inherent variability of price behavior.
Key Components and Calculation Details
1. Lookback Periods and Historical Price Movements
Lookback Period 1 and Lookback Period 2 specify the range of past data used to generate each projection. For each period, the indicator calculates the price variations (differences between the closing and opening prices) and stores these in arrays.
These historical price variations capture the volatility and price patterns within each period, serving as templates for future price behavior.
2. Trials: Purpose and Function
The trials are a critical element in the projection calculation. Each trial represents a single simulation of possible future price movements, derived from a random reordering of the historical price variations in each lookback period.
By running multiple trials , the indicator explores various sequences of historical movements, simulating different possible future paths. Each trial adds to the projection’s robustness by capturing a unique potential price path based on past behavior.
Running these multiple trials allows the indicator to account for randomness in price behavior, making the projections more comprehensive by covering a range of scenarios rather than relying on a single deterministic forecast.
3. Reverse Option
The reverse option allows the indicator to invert the direction of price movements within each lookback period. When enabled, historical uptrends are treated as downtrends, and vice versa.
This feature is particularly valuable in scenarios where traders expect a potential reversal in market direction. By enabling the reverse option, the indicator can simulate what might happen if past trends inverted, providing an alternative forecast path that considers possible market reversals.
This allows traders to assess both continuation and reversal scenarios, giving them a more balanced view of potential future price paths and helping them prepare for either market direction.
4. Generating the Average Projection Path
Once the trials are complete, the indicator calculates an average projected price path for each lookback period by averaging the results of all trials. This average represents the most likely price trend based on historical data and provides a smoothed projection that mitigates extreme outliers.
By averaging across all trial paths, the indicator generates a more reliable and balanced forecast line, smoothing out the fluctuations that might appear if only one trial or a small number of trials were used.
5. Projection Zone Visualization
The indicator plots the two average projection paths (one for each lookback period) as Projection 1 and Projection 2, each in a user-defined color.
The Projection Zone is the area between these two lines, filled with a semi-transparent color. This zone visually represents the potential range of future price movement, highlighting where prices are likely to oscillate if historical trends persist.
The Projection Zone effectively functions as a potential support and resistance boundary, providing traders with a visual reference for possible price fluctuations within a specific range.
6. Display of Lookback Zones
To give context to the projections, the indicator can also display colored lookback zones on the chart. These zones correspond to Lookback Period 1 and Lookback Period 2 and are color-coded to match their respective projection lines.
These zones allow traders to see the sections of historical data used in the calculation, helping them understand which past price behaviors influenced the current projections.
Benefits of the Indicator
The "Dual Price Forecast with Projection Zone" indicator provides a multi-scenario forecast based on past price dynamics. Its use of trials ensures that projections are not based on a single deterministic path but on a range of possible scenarios that better reflect the inherent randomness in financial markets.
By generating a probabilistic forecast within a defined zone, the indicator helps traders to:
Anticipate potential price ranges and areas of support/resistance based on historical trends.
Understand the influence of different timeframes (short-term and long-term lookbacks) on future price behavior.
Make informed decisions by visualizing the likely variability of future prices within a controlled projection zone.
Prepare for both continuation and reversal scenarios, thanks to the reverse option. This feature is especially useful in markets where trends may change direction, as it allows traders to explore what might happen
Gap Detector [MS]This indicator helps traders identify and visualize price gaps in market data. When price movements create gaps between trading sessions or periods, the script highlights these areas with colored clouds and markers.
Key Features:
Automatically detects price gaps based on a customizable gap percentage threshold
Visualizes gaps using color-coded clouds (green when price moves upward, red for downward price action)
Places small triangle markers at gap locations for easy identification of gaps, and if many happen close together
Shows gray clouds when price is within the last gap
Use it For:
Watching for gap-fills
Gap support/resistance levels
Trading gap breakouts
...and more
How it Works:
The script compares each bar's opening price with the previous bar's closing price. A gap is identified when the opening price is significantly different from the previous close (beyond the user-defined gap percentage). The gap area is then marked with a colored cloud:
Green clouds: Show gaps where price jumped higher
Red clouds: Show gaps where price dropped lower
Gray clouds: Indicate price action within the gap
Settings:
Gap %: Controls the minimum price difference required to identify a gap (default 0.01 or 1%)
This indicator can help traders:
Identify potential support/resistance levels at gap areas
Monitor gap-filling scenarios
Spot significant price movements between trading sessions
The script is designed to work across all timeframes and markets.
Custom Candlestick Pattern IndicatorCustom Candlestick Pattern Indicator - Buy Signal Based on Green Candles Breaking Previous Lows
Overview:
This custom candlestick pattern indicator is designed to highlight potential buy opportunities based on a simple yet powerful candlestick pattern. The indicator identifies green candles that break below the low of the previous candle. This combination may signal a potential market reversal or a bullish continuation after a pullback, depending on the market context. Traders can use this indicator to detect areas where prices may be bouncing from recent lows, indicating a potential buying opportunity.
Pattern Explanation:
The strategy underlying this indicator is a two-part condition that must be met before a buy signal is generated:
Green Candle: A green candle forms when the closing price of the current candle is higher than its opening price. This visually represents bullish momentum as buyers have taken control, closing the price higher than where it opened.
Breaking the Previous Low: The low of the current candle must be lower than the low of the previous candle. This suggests that, despite initial bearish pressure during the candle formation (which drove the price below the previous candle's low), buyers stepped in to push the price higher by the candle’s close. This pattern can signify a potential reversal or bullish continuation, as it demonstrates that buyers are overcoming initial selling pressure.
When the Pattern Occurs:
This pattern is particularly interesting to traders who look for potential reversal signals after a brief decline in price.
It may also work well in markets where pullbacks are common, as this pattern could mark the end of a retracement and the resumption of the bullish trend.
How the Indicator Works:
Green Candle: The indicator first identifies a green candle, where the close of the candle is greater than its open (close > open). This signals that the current period closed higher than it opened, which is generally a bullish sign.
Breaking Previous Low: The indicator checks if the current candle's low is below the low of the previous candle (low < low ). If this condition is met, it means the price dropped below the previous candle's low but was still able to close higher (green candle), signaling a potential reversal or buying opportunity.
Buy Signal: If both conditions are true (green candle + breaking previous low), the indicator plots a buy signal below the candle in the form of an upward-facing triangle labeled "Buy" in green. This serves as a visual cue for traders to consider entering a buy position.
Optional Previous Low Plot: For added reference, the indicator plots the previous candle's low as a red step-line on the chart. This helps traders visualize when the price has dipped below the prior candle's low, making it easier to spot instances where the pattern is forming.
How to Use:
This indicator can be used across multiple timeframes, whether you’re trading short-term intraday patterns or longer-term swing trades.
It works well in markets that experience pullbacks or minor retracements, as the pattern it identifies suggests a rejection of lower prices followed by a push higher.
Traders can combine this indicator with other technical analysis tools (such as moving averages, support/resistance levels, or momentum oscillators) to strengthen the buy signals and add more context to the trading decision.
Example Scenarios:
Reversal Signal: Suppose a market has been in a minor downtrend, and suddenly a green candle forms after a low that breaks the previous day’s low. This indicator would generate a buy signal, suggesting the downtrend may be losing strength and that buyers are taking control. This could be an early indication of a reversal.
Bullish Continuation After Pullback: Imagine a market in a steady uptrend experiences a temporary pullback. The price breaks the previous candle’s low, but the current candle closes higher (green candle). This buy signal could indicate that the pullback is over, and the uptrend is likely to continue.
Advantages:
Simplicity: This indicator relies on basic price action (green candles and lows) without requiring complicated indicators or oscillators, making it easy to understand and use.
Visual Alerts: The plotted buy signals and previous lows provide a clear, visual representation on the chart, simplifying decision-making for traders.
Versatility: It can be applied across different timeframes and asset classes (stocks, forex, crypto, etc.), making it a versatile tool for all kinds of traders.
Limitations:
As with any single indicator or pattern, this should not be used in isolation. It is important to incorporate broader market context, support/resistance levels, and other forms of analysis to avoid false signals.
The pattern tends to be more effective when there’s sufficient market liquidity and may perform better in trending or volatile markets compared to sideways or flat markets.
TrendWave EMA/VWAP IndicatorThe TrendWave EMA/VWAP Indicator is a powerful technical analysis tool designed for traders seeking to enhance their market strategies. By combining the dynamic Exponential Moving Average (EMA) and the Volume Weighted Average Price (VWAP), this indicator provides valuable insights into price trends and potential trading signals, allowing for informed decision-making in various market conditions.
Key Features:
Exponential Moving Average (EMA):
The EMA component helps traders identify the direction of the prevailing trend by giving more weight to recent price action. This responsiveness makes the EMA an essential tool for trend-following strategies.
Customizable Length: Users can adjust the EMA length (default set to 50 periods) to align with their specific trading style and preferences.
Volume Weighted Average Price (VWAP):
The VWAP is crucial for evaluating the average price of a security throughout the trading day, factoring in volume. It serves as a benchmark for price action and can help traders identify significant support and resistance levels.
Real-time Benchmarking: The VWAP enables traders to assess current prices against historical averages, improving their entry and exit strategies.
Signal Generation:
The TrendWave EMA/VWAP Indicator generates clear buy and sell signals based on the interaction between the price and the VWAP:
Bullish Signal: Triggered when the price crosses above the VWAP, indicating a potential upward movement.
Bearish Signal: Triggered when the price crosses below the VWAP, suggesting a potential downward movement.
These signals are visually represented with intuitive arrows on the chart, facilitating quick recognition of trading opportunities.
User-Friendly Interface:
The indicator allows traders to enable or disable components (EMA and VWAP) based on their preferences, ensuring a personalized trading experience.
Clear color coding enhances visual clarity: the EMA is displayed in blue, while the VWAP is shown in orange.
Use Cases:
Trend Following: Use the EMA to confirm the direction of the trend and make trades that align with that trend.
Price Action Analysis: Employ the VWAP to determine the average trading price and identify key support/resistance levels.
Signal Confirmation: Combine signals from both the EMA and VWAP to enhance trading strategies and decision-making.
The TrendWave EMA/VWAP Indicator is an essential addition to any trader's toolkit. By leveraging the strengths of both the EMA and VWAP, this indicator empowers traders to make informed, data-driven decisions and capitalize on market movements with confidence.
Dynamic Range EvaluatorThe Dynamic Range Evaluator script or indicator analyzes the dynamic movement of price ranges in the market, offering several key advantages:
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1. Identifies Market Volatility
It detects when price ranges expand or contract, helping traders gauge the market's current volatility—whether it is highly volatile (wide range) or calm (narrow range).
2. Adapts Strategies Based on Market Conditions
The script allows traders to implement suitable strategies:
Use Breakout strategies when the range expands.
Use Mean Reversion strategies when the price moves within a tight range.
3. Accurate Entry and Exit Points
By identifying dynamic price zones, it helps spot potential reversals or areas near key support/resistance levels, reducing the risk of poor entry decisions in unclear market phases.
4. Versatile Across Market Phases
Whether in a bullish, bearish, or sideways market, the Dynamic Range Evaluator adjusts smoothly to shifting conditions, minimizing the need for frequent modifications.
5. Effective Across Multiple Time Frames
It works well on both lower and higher time frames. For instance:
On lower time frames, it helps identify short-term trade entries/exits.
On higher time frames, it assists with analyzing broader trends.
6. Customizable Dynamic Parameters
Traders can modify range thresholds or evaluation criteria to suit specific asset classes or currency pairs, providing flexibility and improved accuracy.
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Use Cases
Combine with ATR (Average True Range) to identify optimal average ranges.
Align Take Profit / Stop Loss levels with current market ranges.
Integrate with Breakout Strategies by monitoring for range expansion and waiting for key support/resistance breakouts.
Price Action Analyst [OmegaTools]Price Action Analyst (PAA) is an advanced trading tool designed to assist traders in identifying key price action structures such as order blocks, market structure shifts, liquidity grabs, and imbalances. With its fully customizable settings, the script offers both novice and experienced traders insights into potential market movements by visually highlighting premium/discount zones, breakout signals, and significant price levels.
This script utilizes complex logic to determine significant price action patterns and provides dynamic tools to spot strong market trends, liquidity pools, and imbalances across different timeframes. It also integrates an internal backtesting function to evaluate win rates based on price interactions with supply and demand zones.
The script combines multiple analysis techniques, including market structure shifts, order block detection, fair value gaps (FVG), and ICT bias detection, to provide a comprehensive and holistic market view.
Key Features:
Order Block Detection: Automatically detects order blocks based on price action and strength analysis, highlighting potential support/resistance zones.
Market Structure Analysis: Tracks internal and external market structure changes with gradient color-coded visuals.
Liquidity Grabs & Breakouts: Detects potential liquidity grab and breakout areas with volume confirmation.
Fair Value Gaps (FVG): Identifies bullish and bearish FVGs based on historical price action and threshold calculations.
ICT Bias: Integrates ICT bias analysis, dynamically adjusting based on higher-timeframe analysis.
Supply and Demand Zones: Highlights supply and demand zones using customizable colors and thresholds, adjusting dynamically based on market conditions.
Trend Lines: Automatically draws trend lines based on significant price pivots, extending them dynamically over time.
Backtesting: Internal backtesting engine to calculate the win rate of signals generated within supply and demand zones.
Percentile-Based Pricing: Plots key percentile price levels to visualize premium, fair, and discount pricing zones.
High Customizability: Offers extensive user input options for adjusting zone detection, color schemes, and structure analysis.
User Guide:
Order Blocks: Order blocks are significant support or resistance zones where strong buyers or sellers previously entered the market. These zones are detected based on pivot points and engulfing price action. The strength of each block is determined by momentum, volume, and liquidity confirmations.
Demand Zones: Displayed in shades of blue based on their strength. The darker the color, the stronger the zone.
Supply Zones: Displayed in shades of red based on their strength. These zones highlight potential resistance areas.
The zones will dynamically extend as long as they remain valid. Users can set a maximum number of order blocks to be displayed.
Market Structure: Market structure is classified into internal and external shifts. A bullish or bearish market structure break (MSB) occurs when the price moves past a previous high or low. This script tracks these breaks and plots them using a gradient color scheme:
Internal Structure: Short-term market structure, highlighting smaller movements.
External Structure: Long-term market shifts, typically more significant.
Users can choose how they want the structure to be visualized through the "Market Structure" setting, choosing from different visual methods.
Liquidity Grabs: The script identifies liquidity grabs (false breakouts designed to trap traders) by monitoring price action around highs and lows of previous bars. These are represented by diamond shapes:
Liquidity Buy: Displayed below bars when a liquidity grab occurs near a low.
Liquidity Sell: Displayed above bars when a liquidity grab occurs near a high.
Breakouts: Breakouts are detected based on strong price momentum beyond key levels:
Breakout Buy: Triggered when the price closes above the highest point of the past 20 bars with confirmation from volume and range expansion.
Breakout Sell: Triggered when the price closes below the lowest point of the past 20 bars, again with volume and range confirmation.
Fair Value Gaps (FVG): Fair value gaps (FVGs) are periods where the price moves too quickly, leaving an unbalanced market condition. The script identifies these gaps:
Bullish FVG: When there is a gap between the low of two previous bars and the high of a recent bar.
Bearish FVG: When a gap occurs between the high of two previous bars and the low of the recent bar.
FVGs are color-coded and can be filtered by their size to focus on more significant gaps.
ICT Bias: The script integrates the ICT methodology by offering an auto-calculated higher-timeframe bias:
Long Bias: Suggests the market is in an uptrend based on higher timeframe analysis.
Short Bias: Indicates a downtrend.
Neutral Bias: Suggests no clear directional bias.
Trend Lines: Automatic trend lines are drawn based on significant pivot highs and lows. These lines will dynamically adjust based on price movement. Users can control the number of trend lines displayed and extend them over time to track developing trends.
Percentile Pricing: The script also plots the 25th percentile (discount zone), 75th percentile (premium zone), and a fair value price. This helps identify whether the current price is overbought (premium) or oversold (discount).
Customization:
Zone Strength Filter: Users can set a minimum strength threshold for order blocks to be displayed.
Color Customization: Users can choose colors for demand and supply zones, market structure, breakouts, and FVGs.
Dynamic Zone Management: The script allows zones to be deleted after a certain number of bars or dynamically adjusts zones based on recent price action.
Max Zone Count: Limits the number of supply and demand zones shown on the chart to maintain clarity.
Backtesting & Win Rate: The script includes a backtesting engine to calculate the percentage of respect on the interaction between price and demand/supply zones. Results are displayed in a table at the bottom of the chart, showing the percentage rating for both long and short zones. Please note that this is not a win rate of a simulated strategy, it simply is a measure to understand if the current assets tends to respect more supply or demand zones.
How to Use:
Load the script onto your chart. The default settings are optimized for identifying key price action zones and structure on intraday charts of liquid assets.
Customize the settings according to your strategy. For example, adjust the "Max Orderblocks" and "Strength Filter" to focus on more significant price action areas.
Monitor the liquidity grabs, breakouts, and FVGs for potential trade opportunities.
Use the bias and market structure analysis to align your trades with the prevailing market trend.
Refer to the backtesting win rates to evaluate the effectiveness of the zones in your trading.
Terms & Conditions:
By using this script, you agree to the following terms:
Educational Purposes Only: This script is provided for informational and educational purposes and does not constitute financial advice. Use at your own risk.
No Warranty: The script is provided "as-is" without any guarantees or warranties regarding its accuracy or completeness. The creator is not responsible for any losses incurred from the use of this tool.
Open-Source License: This script is open-source and may be modified or redistributed in accordance with the TradingView open-source license. Proper credit to the original creator, OmegaTools, must be maintained in any derivative works.
Volume-Supported Linear Regression Trend TableThe "Volume-Supported Linear Regression Trend Table" (VSLRT Table) script helps traders identify buy and sell opportunities by analyzing price trends and volume dynamics across multiple timeframes. It uses linear regression to calculate the trend direction and volume strength, visually representing this data with color-coded signals on the chart and in a table. Green signals indicate buying opportunities, while red signals suggest selling, with volume acting as confirmation of trend strength. Traders can use these signals for both short and long positions, with additional risk management and multi-timeframe validation to enhance the strategy.
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To use the "Volume-Supported Linear Regression Trend Table" (VSLRT Table) script in a trading strategy, you would incorporate it into your decision-making process to identify potential buy and sell opportunities based on the trend and volume dynamics. Here’s how you could apply it for trading:
1. Understanding the Key Elements:
Trend Direction (Slope of Price): The script uses linear regression to assess the trend direction of the price. If the price slope is positive, the asset is likely in an uptrend; if it's negative, the asset is in a downtrend.
Volume-Backed Signals: The buy or sell signal is not only based on the price trend but also on volume. Volume is crucial in validating the strength of a trend; large volume often indicates strong interest in a direction.
2. Interpreting the Table and Signals:
The table displayed at the bottom-right of your TradingView chart gives you a clear overview of the trends across different timeframes:
Trend Colors:
Green hues (e.g., ccol11, ccol12, etc.): Indicate a buying trend supported by volume.
Red hues (e.g., ccol21, ccol22, etc.): Indicate a selling trend supported by volume.
Gray: Indicates weak or unclear trends where no decisive direction is present.
Buy/Sell Signals:
The script plots triangles on the chart:
Upward triangle below the bar signals a potential buy.
Downward triangle above the bar signals a potential sell.
3. Building a Trading Strategy:
Here’s how you can incorporate the script’s information into a trading strategy:
Buy Signal (Long Entry):
Look for green triangles (indicating a buy signal) below a bar.
Confirm that the trend color in the table for the relevant timeframe is green, which shows that the buy signal is supported by strong volume.
Ensure that the price is in an uptrend (positive slope) and that volume is increasing on upward moves, as this indicates buying interest.
Execute a long position when these conditions align.
Sell Signal (Short Entry):
Look for red triangles (indicating a sell signal) above a bar.
Confirm that the trend color in the table for the relevant timeframe is red, which shows that the sell signal is supported by strong volume.
Ensure that the price is in a downtrend (negative slope) and that volume is increasing on downward moves, indicating selling pressure.
Execute a short position when these conditions align.
Exiting the Trade:
Exit a long position when a sell signal (red triangle) appears, or when the trend color in the table shifts to red.
Exit a short position when a buy signal (green triangle) appears, or when the trend color in the table shifts to green.
4. Multi-Timeframe Confirmation:
The script provides trends across multiple timeframes (tf1, tf2, tf3), which can help in validating your trade:
Short-Term Trading: Use shorter timeframes (e.g., 3, 5 minutes) for intraday trades. If both short and medium timeframes align in trend direction (e.g., both showing green), it strengthens the signal.
Longer-Term Trading: If you are trading on a higher timeframe (e.g., daily or weekly), confirm that the lower timeframes align with your intended trade direction.
5. Adding Risk Management:
Stop-Loss: Place stop-losses below recent lows (for long trades) or above recent highs (for short trades) to minimize risk.
Take Profit: Consider taking profit at key support/resistance levels or based on a fixed risk-to-reward ratio (e.g., 2:1).
Example Strategy Flow:
For Long (Buy) Trade:
Signal: A green triangle appears below a candle (Buy signal).
Trend Confirmation: Check that the color in the table for your selected timeframe is green, confirming the trend is supported by volume.
Execute Long: Enter a long trade if the price is trending upward (positive price slope).
Exit Long: Exit when a red triangle appears above a candle (Sell signal) or if the trend color shifts to red in the table.
For Short (Sell) Trade:
Signal: A red triangle appears above a candle (Sell signal).
Trend Confirmation: Check that the color in the table for your selected timeframe is red, confirming the trend is supported by volume.
Execute Short: Enter a short trade if the price is trending downward (negative price slope).
Exit Short: Exit when a green triangle appears below a candle (Buy signal) or if the trend color shifts to green in the table.
6. Fine-Tuning:
Backtesting: Before trading live, use TradingView’s backtesting features to test the strategy on historical data and optimize the settings (e.g., length of linear regression, timeframe).
Combine with Other Indicators: Use this strategy alongside other technical indicators (e.g., RSI, MACD) for better confirmation.
In summary, the script helps identify trends with volume support, giving more confidence in buy/sell decisions. Combining these signals with risk management and multi-timeframe analysis can create a solid trading strategy.
2x ATR Horizontal Rays2x ATR Horizontal Rays Indicator
This script plots horizontal rays based on the 2x ATR (Average True Range) of the previous candle. It helps traders visualize key support and resistance levels by extending lines from the last candle's price, calculated with a 2x ATR multiplier. The indicator draws two lines:
Upper ATR Line: Positioned above the previous candle’s close by 2x the ATR value.
Lower ATR Line: Positioned below the previous candle’s close by 2x the ATR value.
Key Features:
Customizable ATR Length: Allows users to input their preferred ATR period to suit different market conditions.
Dynamic Horizontal Lines: The lines update with each new candle, giving traders a clear visual of volatility levels.
Extended Right Lines: The horizontal rays extend to the right, serving as potential zones for price reversals or breakouts.
This indicator is useful for traders looking to gauge market volatility and set target levels or stops based on historical price movements.
How to Use:
Add the indicator to your chart and adjust the ATR length in the settings.
Watch how the price interacts with the upper and lower ATR lines as potential zones for support, resistance, or trend continuation.
Happy trading!
Fibonacci Swing Trading BotStrategy Overview for "Fibonacci Swing Trading Bot"
Strategy Name: Fibonacci Swing Trading Bot
Version: Pine Script v5
Purpose: This strategy is designed for swing traders who want to leverage Fibonacci retracement levels and candlestick patterns to enter and exit trades on higher time frames.
Key Components:
1. Multiple Timeframe Analysis:
The strategy uses a customizable timeframe for analysis. You can choose between 4hour, daily, weekly, or monthly time frames to fit your preferred trading horizon. The high and low-price data is retrieved from the selected timeframe to identify swing points.
2. Fibonacci Retracement Levels:
The script calculates two key Fibonacci retracement levels:
0.618: A common level where price often retraces before resuming its trend.
0.786: A deeper retracement level, often used to identify stronger support/resistance areas.
These levels are dynamically plotted on the chart based on the highest high and lowest low over the last 50 bars of the selected timeframe.
3. Candlestick Based Entry Signals:
The strategy uses candlestick patterns as the only indicator for trade entries:
Bullish Candle: A green candle (close > open) that forms between the 0.618 retracement level and the swing high.
Bearish Candle: A red candle (close < open) that forms between the 0.786 retracement level and the swing low.
When these candlestick patterns align with the Fibonacci levels, the script triggers buy or sell signals.
4. Risk Management:
Stop Loss: The stop loss is set at 1% below the entry price for long trades and 1% above the entry price for short trades. This tight risk management ensures controlled losses.
Take Profit: The strategy uses a 2:1 risk-to-reward ratio. The take profit is automatically calculated based on this ratio relative to the stop loss.
5. Buy/Sell Logic:
Buy Signal: Triggered when a bullish candle forms above the 0.618 retracement level and below the swing high. The bot then places a long position.
Sell Signal: Triggered when a bearish candle forms below the 0.786 retracement level and above the swing low. The bot then places a short position.
The stop loss and take profit levels are automatically managed once the trade is placed.
Strengths of This Strategy:
Swing Trading Focus: The strategy is ideal for swing traders, targeting longer-term price moves that can take days or weeks to play out.
Simple Yet Effective Indicators: By only relying on Fibonacci retracement levels and basic candlestick patterns, the strategy avoids complexity while capitalizing on well-known support and resistance zones.
Automated Risk Management: The built-in stop loss and take profit mechanism ensures trades are protected, adhering to a strict 2:1 risk/reward ratio.
Multiple Timeframe Analysis: The script adapts to various market conditions by allowing users to switch between different timeframes (4hour, daily, weekly, monthly), giving traders flexibility.
Strategy Use Cases:
Retracement Traders: Traders who focus on entering the market at key retracement levels (0.618 and 0.786) will find this strategy especially useful.
Trend Reversal Traders: The strategy’s reliance on candlestick formations at Fibonacci levels helps traders spot potential reversals in price trends.
Risk Conscious Traders: With its 1% risk per trade and 2:1 risk/reward ratio, the strategy is ideal for traders who prioritize risk management in their trades.
M & W Checklistindicator to Validate & Grade M & W Patterns.
Indicator Inputs
Table Color Palette
• Position Valid : Positions the Valid Trade table on the chart.
• Position Grade : Positions the Grade table on the chart, hover over the Column 1 Row 1 for a description of the bands.
• Size: Text size for all tables.
• Text Color : Sets text color.
• Border Color : Sets the table border color for all tables.
• Background Color : Sets table backgroud color for all tables.
Valid Trade Table
Checkboxes to indicate if the trade is valid. Fail is displayed if unchecked, Pass if checked.
Grade Table
• S/R Level 1: distance between neckline and 1st resistance area in % of the total distance between neckline and take profit. This is not for road blocks but pivot points etc before the initial run up/down in price. I have this set to 30% , this means that if there is a pivot point between the neckline and 30% of the TP level I weight it negatively.
• S/R Level 2: distance between neckline and 1st resistance area in % of the total distance between neckline and take profit. This is not for road blocks but pivot points etc before the initial run up/down in price. I have this set to 50% , this means that if there is a pivot point between the neckline and 50% of the TP level 2 weight it negatively but less so than level 1.
• S/R Level 3: distance between neckline and 1st resistance area in % of the total distance between neckline and take profit. This is not for road blocks but pivot points etc before the initial run up/down in price. I have this set to 70% , this means that if there is a pivot point between the neckline and 70% of the TP level 3 weight it negatively but less so than level 1 & level 2.
• Checkboxes are self explanatory, they are binary options, all are weighted negatively if checked and are weighted positively if unchecked. Divergence values for weighting are neutral if unckecked & weighted positively if checked.
• The select options are neutral weighting if set to neutral , if set to For its weighted positive and set to Against weighted negatively.
Technical Specification of the Scoring and Band System
Overview
The scoring system is designed to evaluate a set of technical trade conditions, assigning weights to various criteria that influence the quality of the trade. The system calculates a total score based on both positive and negative conditions. Based on the final score, the system assigns a grade or band (A, B, or C) for positive scores, and a "Negative" label for negative scores.
Scoring System
The system calculates the score by evaluating a set of 12 conditions (gradeCondition1 to gradeCondition12). These conditions are manually input by the user via checkboxes or dropdowns in a technical indicator (written in Pine Script for TradingView). The score weights vary according to the relative importance of each condition.
Condition Breakdown and Weighting:
1. Divergences (GradeCondition1 & GradeCondition2):
◦ 1H Divergence: +5 points if condition is true.
◦ 4H Divergence: +10 points if condition is true (stronger weight than 1H).
2. Support/Resistance at Neckline (GradeCondition3):
◦ Negative if present: -15 points if true (carries significant negative weight).
3. RB near Entry (GradeCondition4):
◦ Very Negative: -20 points if true (this is a critical negative condition).
4. RB can Manage (GradeCondition5):
◦ Slightly Negative: -5 points if true.
5. Institutional Value Zones (GradeCondition6 to GradeCondition8):
◦ For the trade: +5 points.
◦ Against the trade: -5 points.
◦ Neutral: 0 points.
6. S/R between Neckline & Targets (GradeCondition9 to GradeCondition11):
◦ Level 1: -10 points if true, +7 points if false.
◦ Level 2: -7 points if true, +7 points if false.
◦ Level 3: -5 points if true, +7 points if false.
◦ Use fib tool or Gann Box to measure any S/R levels setup according to your preferences.
7. News Timing (GradeCondition12):
◦ News within 3 hours: -20 points if true (strong negative factor).
◦ No upcoming news: +10 points if false.
Scoring Calculation Formula:
totalScore = score1 + score2 + score3 + score4 + score5 + score6 + score7 + score8 + score9 + score10 + score11 + score12
Where:
• score1 to score12 represent the points derived from the conditions described above.
Coloring and Visual Feedback:
• Positive Scores: Displayed in green.
• Negative Scores: Displayed in red.
Band System
The Band System classifies the total score into different grades, depending on the final value of totalScore. This classification provides an intuitive ranking for trades, helping users quickly assess trade quality.
Band Classification:
• Band A: If the totalScore is 41 or more.
◦ Represents a highly favorable trade setup.
• Band B: If the totalScore is between 21 and 40.
◦ Represents a favorable trade setup with good potential.
• Band C: If the totalScore is between 1 and 20.
◦ Represents a trade setup that is acceptable but may have risks.
• Negative: If the totalScore is 0 or less.
◦ Represents a poor trade setup with significant risks or unfavorable conditions.
Band Calculation Logic (in Pine Script):
var string grade = ""
if (totalScore >= 41)
grade := "Band A"
else if (totalScore >= 21)
grade := "Band B"
else if (totalScore >= 1)
grade := "Band C"
else
grade := "Negative"
Technical Key Points:
• Highly Negative Conditions:
◦ The system penalizes certain conditions more heavily, especially those that suggest significant risks (e.g., News in less than 3 hours, RB near Entry).
• Positive Trade Conditions:
◦ Divergences, Institutional Value Zones in favor of the trade, and lack of significant nearby resistance all contribute positively to the score.
• Flexible System:
◦ The system can be adapted or fine-tuned by adjusting the weights of individual conditions according to trading preferences.
Use Case Example:
• If a trade has 1H and 4H Divergence, RB near Entry (negative), and no upcoming news:
◦ 1H Divergence: +5 points.
◦ 4H Divergence: +10 points.
◦ RB near Entry: -20 points.
◦ No news: +10 points.
◦ Total Score: 5 + 10 - 20 + 10 = 5 → Band C.
This modular and flexible scoring system allows traders to systematically evaluate trades and quickly gauge the trade's potential based on technical indicators
Summary:
Maximum Score: 61
Minimum Score: -97
These are the bounds of the score range based on the current logic of the script.
Mean Reversion Cloud (Ornstein-Uhlenbeck) // AlgoFyreThe Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator detects mean-reversion opportunities by applying the Ornstein-Uhlenbeck process. It calculates a dynamic mean using an Exponential Weighted Moving Average, surrounded by volatility bands, signaling potential buy/sell points when prices deviate.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Adaptive Mean Calculation
🔸Volatility-Based Cloud
🔸Speed of Reversion (θ)
🔶 FUNCTIONALITY
🔸Dynamic Mean and Volatility Bands
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Visualization via Table and Plotshapes
🞘 Table Overview
🞘 Plotshapes Explanation
🞘 Code extract
🔶 INSTRUCTIONS
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) is a unique indicator that applies the Ornstein-Uhlenbeck stochastic process to identify mean-reverting behavior in asset prices. Unlike traditional moving average-based indicators, this model uses an Exponentially Weighted Moving Average (EWMA) to calculate the long-term mean, dynamically adjusting to recent price movements while still considering all historical data. It also incorporates volatility bands, providing a "cloud" that visually highlights overbought or oversold conditions. By calculating the speed of mean reversion (θ) through the autocorrelation of log returns, this indicator offers traders a more nuanced and mathematically robust tool for identifying mean-reversion opportunities. These innovations make it especially useful for markets that exhibit range-bound characteristics, offering timely buy and sell signals based on statistical deviations from the mean.
🔸Adaptive Mean Calculation Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Mean Reversion Cloud uses an Exponentially Weighted Moving Average (EWMA), which adapts to price movements by dynamically adjusting its calculation, offering a more responsive mean.
🔸Volatility-Based Cloud Unlike simple moving averages that only plot a single line, the Mean Reversion Cloud surrounds the dynamic mean with volatility bands. These bands, based on standard deviations, provide traders with a visual cue of when prices are statistically likely to revert, highlighting potential reversal zones.
🔸Speed of Reversion (θ) The indicator goes beyond price averages by calculating the speed at which the price reverts to the mean (θ), using the autocorrelation of log returns. This gives traders an additional tool for estimating the likelihood and timing of mean reversion, making the signals more reliable in practice.
🔶 FUNCTIONALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator is designed to detect potential mean-reversion opportunities in asset prices by applying the Ornstein-Uhlenbeck stochastic process. It calculates a dynamic mean through the Exponentially Weighted Moving Average (EWMA) and plots volatility bands based on the standard deviation of the asset's price over a specified period. These bands create a "cloud" that represents expected price fluctuations, helping traders to identify overbought or oversold conditions. By calculating the speed of reversion (θ) from the autocorrelation of log returns, the indicator offers a more refined way of assessing how quickly prices may revert to the mean. Additionally, the inclusion of volatility provides a comprehensive view of market conditions, allowing for more accurate buy and sell signals.
Let's dive into the details:
🔸Dynamic Mean and Volatility Bands The dynamic mean (μ) is calculated using the EWMA, giving more weight to recent prices but considering all historical data. This process closely resembles the Ornstein-Uhlenbeck (OU) process, which models the tendency of a stochastic variable (such as price) to revert to its mean over time. Volatility bands are plotted around the mean using standard deviation, forming the "cloud" that signals overbought or oversold conditions. The cloud adapts dynamically to price fluctuations and market volatility, making it a versatile tool for mean-reversion strategies. 🞘 How it works Step one: Calculate the dynamic mean (μ) The Ornstein-Uhlenbeck process describes how a variable, such as an asset's price, tends to revert to a long-term mean while subject to random fluctuations. In this indicator, the EWMA is used to compute the dynamic mean (μ), mimicking the mean-reverting behavior of the OU process. Use the EWMA formula to compute a weighted mean that adjusts to recent price movements. Assign exponentially decreasing weights to older data while giving more emphasis to current prices. Step two: Plot volatility bands Calculate the standard deviation of the price over a user-defined period to determine market volatility. Position the upper and lower bands around the mean by adding and subtracting a multiple of the standard deviation. 🞘 How to calculate Exponential Weighted Moving Average (EWMA)
The EWMA dynamically adjusts to recent price movements:
mu_t = lambda * mu_{t-1} + (1 - lambda) * P_t
Where mu_t is the mean at time t, lambda is the decay factor, and P_t is the price at time t. The higher the decay factor, the more weight is given to recent data.
Autocorrelation (ρ) and Standard Deviation (σ)
To measure mean reversion speed and volatility: rho = correlation(log(close), log(close ), length) Where rho is the autocorrelation of log returns over a specified period.
To calculate volatility:
sigma = stdev(close, length)
Where sigma is the standard deviation of the asset's closing price over a specified length.
Upper and Lower Bands
The upper and lower bands are calculated as follows:
upper_band = mu + (threshold * sigma)
lower_band = mu - (threshold * sigma)
Where threshold is a multiplier for the standard deviation, usually set to 2. These bands represent the range within which the price is expected to fluctuate, based on current volatility and the mean.
🞘 Code extract // Calculate Returns
returns = math.log(close / close )
// Calculate Long-Term Mean (μ) using EWMA over the entire dataset
var float ewma_mu = na // Initialize ewma_mu as 'na'
ewma_mu := na(ewma_mu ) ? close : decay_factor * ewma_mu + (1 - decay_factor) * close
mu = ewma_mu
// Calculate Autocorrelation at Lag 1
rho1 = ta.correlation(returns, returns , corr_length)
// Ensure rho1 is within valid range to avoid errors
rho1 := na(rho1) or rho1 <= 0 ? 0.0001 : rho1
// Calculate Speed of Mean Reversion (θ)
theta = -math.log(rho1)
// Calculate Volatility (σ)
sigma = ta.stdev(close, corr_length)
// Calculate Upper and Lower Bands
upper_band = mu + threshold * sigma
lower_band = mu - threshold * sigma
🔸Visualization via Table and Plotshapes
The table shows key statistics such as the current value of the dynamic mean (μ), the number of times the price has crossed the upper or lower bands, and the consecutive number of bars that the price has remained in an overbought or oversold state.
Plotshapes (diamonds) are used to signal buy and sell opportunities. A green diamond below the price suggests a buy signal when the price crosses below the lower band, and a red diamond above the price indicates a sell signal when the price crosses above the upper band.
The table and plotshapes provide a comprehensive visualization, combining both statistical and actionable information to aid decision-making.
🞘 Code extract // Reset consecutive_bars when price crosses the mean
var consecutive_bars = 0
if (close < mu and close >= mu) or (close > mu and close <= mu)
consecutive_bars := 0
else if math.abs(deviation) > 0
consecutive_bars := math.min(consecutive_bars + 1, dev_length)
transparency = math.max(0, math.min(100, 100 - (consecutive_bars * 100 / dev_length)))
🔶 INSTRUCTIONS
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator can be set up by adding it to your TradingView chart and configuring parameters such as the decay factor, autocorrelation length, and volatility threshold to suit current market conditions. Look for price crossovers and deviations from the calculated mean for potential entry signals. Use the upper and lower bands as dynamic support/resistance levels for setting take profit and stop-loss orders. Combining this indicator with additional trend-following or momentum-based indicators can improve signal accuracy. Adjust settings for better mean-reversion detection and risk management.
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
Adding the Indicator to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Mean Reversion Cloud (Ornstein-Uhlenbeck)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator:
Open the indicator settings by clicking on the gear icon next to its name on the chart.
Decay Factor: Adjust the decay factor (λ) to control the responsiveness of the mean calculation. A higher value prioritizes recent data.
Autocorrelation Length: Set the autocorrelation length (θ) for calculating the speed of mean reversion. Longer lengths consider more historical data.
Threshold: Define the number of standard deviations for the upper and lower bands to determine how far price must deviate to trigger a signal.
Chart Setup:
Select the appropriate timeframe (e.g., 1-hour, daily) based on your trading strategy.
Consider using other indicators such as RSI or MACD to confirm buy and sell signals.
🞘 Understanding What to Look For on the Chart
Indicator Behavior:
Observe how the price interacts with the dynamic mean and volatility bands. The price staying within the bands suggests mean-reverting behavior, while crossing the bands signals potential entry points.
The indicator calculates overbought/oversold conditions based on deviation from the mean, highlighted by color-coded cloud areas on the chart.
Crossovers and Deviation:
Look for crossovers between the price and the mean (μ) or the bands. A bullish crossover occurs when the price crosses below the lower band, signaling a potential buying opportunity.
A bearish crossover occurs when the price crosses above the upper band, suggesting a potential sell signal.
Deviations from the mean indicate market extremes. A large deviation indicates that the price is far from the mean, suggesting a potential reversal.
Slope and Direction:
Pay attention to the slope of the mean (μ). A rising slope suggests bullish market conditions, while a declining slope signals a bearish market.
The steepness of the slope can indicate the strength of the mean-reversion trend.
🞘 Possible Entry Signals
Bullish Entry:
Crossover Entry: Enter a long position when the price crosses below the lower band with a positive deviation from the mean.
Confirmation Entry: Use additional indicators like RSI (above 50) or increasing volume to confirm the bullish signal.
Bearish Entry:
Crossover Entry: Enter a short position when the price crosses above the upper band with a negative deviation from the mean.
Confirmation Entry: Look for RSI (below 50) or decreasing volume to confirm the bearish signal.
Deviation Confirmation:
Enter trades when the deviation from the mean is significant, indicating that the price has strayed far from its expected value and is likely to revert.
🞘 Possible Take Profit Strategies
Static Take Profit Levels:
Set predefined take profit levels based on historical volatility, using the upper and lower bands as guides.
Place take profit orders near recent support/resistance levels, ensuring you're capitalizing on the mean-reversion behavior.
Trailing Stop Loss:
Use a trailing stop based on a percentage of the price deviation from the mean to lock in profits as the trend progresses.
Adjust the trailing stop dynamically along the calculated bands to protect profits as the price returns to the mean.
Deviation-Based Exits:
Exit when the deviation from the mean starts to decrease, signaling that the price is returning to its equilibrium.
🞘 Possible Stop-Loss Levels
Initial Stop Loss:
Place an initial stop loss outside the lower band (for long positions) or above the upper band (for short positions) to protect against excessive deviations.
Use a volatility-based buffer to avoid getting stopped out during normal price fluctuations.
Dynamic Stop Loss:
Move the stop loss closer to the mean as the price converges back towards equilibrium, reducing risk.
Adjust the stop loss dynamically along the bands to account for sudden market movements.
🞘 Additional Tips
Combine with Other Indicators:
Enhance your strategy by combining the Mean Reversion Cloud with momentum indicators like MACD, RSI, or Bollinger Bands to confirm market conditions.
Backtesting and Practice:
Backtest the indicator on historical data to understand how it performs in various market environments.
Practice using the indicator on a demo account before implementing it in live trading.
Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The indicator reacts to price data and might not account for news-driven events that can cause large deviations.
🔸Customize settings 🞘 Decay Factor (λ): Defines the weight assigned to recent price data in the calculation of the mean. A value closer to 1 places more emphasis on recent prices, while lower values create a smoother, more lagging mean.
🞘 Autocorrelation Length (θ): Sets the period for calculating the speed of mean reversion and volatility. Longer lengths capture more historical data, providing smoother calculations, while shorter lengths make the indicator more responsive.
🞘 Threshold (σ): Specifies the number of standard deviations used to create the upper and lower bands. Higher thresholds widen the bands, producing fewer signals, while lower thresholds tighten the bands for more frequent signals.
🞘 Max Gradient Length (γ): Determines the maximum number of consecutive bars for calculating the deviation gradient. This setting impacts the transparency of the plotted bands based on the length of deviation from the mean.
🔶 CONCLUSION
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator offers a sophisticated approach to identifying mean-reversion opportunities by applying the Ornstein-Uhlenbeck stochastic process. This dynamic indicator calculates a responsive mean using an Exponentially Weighted Moving Average (EWMA) and plots volatility-based bands to highlight overbought and oversold conditions. By incorporating advanced statistical measures like autocorrelation and standard deviation, traders can better assess market extremes and potential reversals. The indicator’s ability to adapt to price behavior makes it a versatile tool for traders focused on both short-term price deviations and longer-term mean-reversion strategies. With its unique blend of statistical rigor and visual clarity, the Mean Reversion Cloud provides an invaluable tool for understanding and capitalizing on market inefficiencies.
Ultimate ZonesThe story is simple: I didn't find a support/resistance zones indicator that I actually liked, so I made my own.
Features:
Independent of the chart timeframe (zones don't change if you switch timeframes) - very important for practical use
Live mode (repainting) plus historic mode (non-repainting)
Selectable timeframe for zone calculation (default: daily)
Can adjust how far the indicator looks back into the past (default: 500 days)
Can adjust pivot period to find more or fewer zones
Zone heights are based on long-term ATR (to adapt to the asset's volatility automatically)
Price tolerance multiplier is adjustable
Option to merge zones which are close together into one ("fat zones")
I find that together these options (especially those in the "sensitivity" section) allow me to automatically generate almost all the zones I want to see. Occasionally, I do draw some additional zones to get the perfect image I'm looking for on the chart.
Explanation
We detect pivot points on the selected zone timeframe (taking pivot period and lookback limit into account). Then we combine these pivot points into a zone if they are close enough together in price (here the tolerance parameter comes into play). If "fat zones" is selected, we perform these merges more aggressively even if the resulting zone becomes taller than the standard tolerance.
The ATR used for the tolerance is a 500 period ATR, but if there are less than 500 bars available, we use the average of the bars available so far, so we always have a value to work with.
In order for a zone to be displayed, it must have been touched by at least 2 separate pivot points. We do not distinguish between pivot highs and pivot lows because support is known to turn into resistance and vice versa.
In live mode, we draw the currently active zones as boxes.
In historic mode, we plot the active zones at each bar using "plot" and "fill", so there is no repainting or erasing, and you can see which zones were active at any past date. For practical reasons, we draw a maximum of 15 zones around the current price (i.e. 7-8 zones above and 7-8 zones below the price).
Indicator 10**Indicator 10** is a sophisticated technical analysis tool designed for use on trading platforms that support Pine Script (version 5). This indicator is primarily focused on analyzing price movements over different timeframes, incorporating elements of ZigZag analysis, Fibonacci levels, and historical price range calculations. Below is a detailed description of its features and functionalities:
#### Key Features:
1. **Input Variables:**
- **Year_calc:** Specifies the number of years to consider for historical price range calculations.
- **Size_fibo:** Defines the size of the Fibonacci levels in points.
- **Dig:** Represents the minimum tick size for the instrument being analyzed.
- **ZigZag Parameters:**
- **Period (zigzag_len):** The length of the ZigZag indicator.
- **Depth (zigzag_depth):** The depth percentage for the ZigZag indicator.
- **Display Count (zigzag_hist):** The number of ZigZag points to display.
- **Font Size (font_size):** The size of the font used for labels.
2. **Historical Price Range Calculation:**
- The indicator calculates the average weekly and monthly price ranges over the specified number of years (`Year_calc`).
- These ranges are used to adjust the Fibonacci levels dynamically based on historical volatility.
3. **ZigZag Analysis:**
- The indicator employs a custom ZigZag function to identify significant price swings on different timeframes (H4, D1, W1).
- The ZigZag points are stored in arrays, allowing for the visualization of recent price swings.
4. **Fibonacci Adjustment:**
- The Fibonacci levels are adjusted based on the historical price ranges (`W1_Val`, `MN1_Val`, `D1_Val`).
- These adjusted levels are used to draw support and resistance lines on the chart.
5. **Visualization:**
- The indicator draws lines and labels on the chart to represent the ZigZag points and adjusted Fibonacci levels.
- Different colors are used to distinguish between upward and downward trends.
6. **Dynamic Updates:**
- The indicator continuously updates the ZigZag points and Fibonacci levels as new price data becomes available.
- It ensures that only the most recent ZigZag points are displayed, maintaining a clean and relevant chart.
#### How It Works:
1. **Initialization:**
- The indicator initializes variables for storing historical price ranges and ZigZag points.
- It sets the start date for historical calculations based on the current year minus the specified number of years (`Year_calc`).
2. **Historical Data Retrieval:**
- The indicator retrieves weekly and monthly high and low prices for the specified period.
- It calculates the total price range and the average range for each timeframe.
3. **ZigZag Calculation:**
- The custom ZigZag function identifies local highs and lows based on the specified period and depth.
- These points are stored in arrays for later visualization.
4. **Fibonacci Adjustment:**
- The Fibonacci levels are adjusted based on the historical price ranges and the specified Fibonacci size.
- These adjusted levels are used to draw lines on the chart.
5. **Visualization:**
- The indicator draws lines connecting ZigZag points and labels indicating the direction of the trend.
- It ensures that only the most recent ZigZag points are displayed, maintaining a clean and relevant chart.
6. **Continuous Updates:**
- The indicator continuously updates the ZigZag points and Fibonacci levels as new price data becomes available.
- It ensures that only the most recent ZigZag points are displayed, maintaining a clean and relevant chart.
#### Conclusion:
**Indicator 10** is a powerful tool for traders who rely on historical price analysis, ZigZag patterns, and Fibonacci levels to make trading decisions. Its dynamic and adaptive nature ensures that the chart remains relevant and useful, providing traders with a clear view of recent price movements and potential support/resistance levels.
Charan_Trading_IndicatorCharan_Trading_Indicator Overview:
The Charan_Trading_Indicator combines several technical analysis tools, including Bollinger Bands, RSI (Relative Strength Index), VWAP (Volume-Weighted Average Price), and ATR (Average True Range), to provide buy and sell signals. The script incorporates multiple strategies, such as crack snap setups, overbought/oversold levels, and trend continuation indicators, all tailored for precise market entry and exit points.
Key Components:
RSI (Relative Strength Index):
The indicator uses RSI to detect overbought (RSI > 70) and oversold (RSI < 30) market conditions.
Alerts are triggered when prices are within the specified buy/sell range and RSI crosses these thresholds.
Bollinger Bands:
Bollinger Bands are calculated based on a configurable moving average and standard deviation.
The script identifies potential buy signals when the price dips below the lower Bollinger Band and recovers, and sell signals when the price exceeds the upper Bollinger Band and retraces.
Crack Snap Strategies:
The indicator incorporates multiple variations of the crack snap strategy:
Buy Signals: Triggered when price opens below the lower Bollinger Band and closes above it, alongside certain conditions in previous candles.
Sell Signals: Triggered when price opens above the upper Bollinger Band and closes below it, with similar candle patterns.
Variations such as 3-candle (3C) and 4-candle (4C) versions refine the crack snap setups for more robust signals.
Isolated Candle Conditions:
The indicator tracks isolated candles, where the entire candle lies above or below the Bollinger Bands, to identify potential reversal points.
Trend Continuation Signals:
Conditions based on the candle range and previous highs/lows allow the indicator to generate signals for trend continuation:
Buy signals when price breaks above the previous two highs.
Sell signals when price breaks below the previous two lows.
VWAP (Volume-Weighted Average Price):
The indicator integrates VWAP to give additional support and resistance levels, ensuring signals align with volume trends.
ATR-Based Stop Loss:
For both buy and sell conditions, the script plots stop-loss levels based on the ATR (Average True Range), giving dynamic risk management levels.
Buy/Sell Ranges:
The user can set minimum and maximum price ranges for buy and sell signals, ensuring that the indicator only generates alerts within desired price ranges.
How It Works:
Buy Signals: The script generates buy signals based on multiple conditions, including the crack snap strategy, oversold RSI levels, and trend continuation setups. When these conditions are met, green triangles appear below the price bars, and an alert is triggered.
Sell Signals: Sell signals are triggered when the opposite conditions are met (overbought RSI, crack snap sell setups, trend breaks), and red triangles appear above the price bars.
Visual Indicators: The script plots upper and lower Bollinger Bands, stop loss levels, and VWAP on the chart, providing a comprehensive view of market conditions and support/resistance levels.
This indicator is versatile, combining multiple technical tools for robust decision-making in trading. It generates alerts, plots visual markers, and integrates risk management, making it a well-rounded tool for technical analysis.
This indicator is versatile, combining multiple technical tools for robust decision-making in trading. It generates alerts, plots visual markers, and integrates risk management, making it a well-rounded tool for technical analysis.
Market Indicator by Atilla YurtsevenThis TradingView script is designed to analyze and visualize market trends by showing the percentage drops from the all-time high (ATH) of a stock or any other financial instrument. It also calculates and displays key statistical levels such as the mean, median, and various percentage thresholds. This indicator helps traders identify significant retracement levels and possible support/resistance zones based on historical price movements.
Indicator Settings:
- The indicator is named "Market // Atilla Yurtseven" and can be overlaid on the price chart.
- Users can choose to use the closing price (Use Close Price) or the high/low prices.
- Options are provided to show the ATH, ATL (All-Time Low), mean, median, and various minor and macro percentage levels.
Color Customization:
- The script allows customization of text and line colors for different levels, making it adaptable to different charting styles.
Initial Variable Setup:
- The script initializes several variables, including ATH, ATL, and arrays to store price data.
The round and roundy functions are used to format the values for display purposes.
ATH/ATL Calculation:
- The script checks if the current price exceeds the previous ATH and updates the ATH accordingly.
- Similarly, the script calculates the ATL based on the lowest point after reaching the ATH.
Mean and Median Calculation:
- The mean is calculated as the average drop from the ATH, while the median is the middle value in the sorted array of drops.
- These statistics provide insight into the overall trend and are used to identify significant price levels.
Plotting the Levels:
The script plots the ATH, ATL, mean, median, and various percentage retracement levels (12.5%, 25%, 37.5%, etc.).
The levels are color-coded based on user preferences, making it easier to interpret the chart visually.
Labels and Text Display:
- The script dynamically creates and updates labels on the chart to show the values of the ATH, ATL, mean, median, and other key levels.
- This feature allows traders to see at a glance how far the current price is from these critical levels.
Hit Detection:
- The script includes logic to detect if the price is within the range of the mean and median. If the price is within this range, the color of the fill between these levels changes, highlighting this area on the chart.
This script is a powerful tool for traders who want to analyze the retracement levels from historical highs. By displaying the mean, median, and various percentage levels, it provides a comprehensive view of potential support and resistance areas, helping traders make more informed decisions. The customizable nature of the script allows it to fit seamlessly into different trading strategies and charting styles.
Disclaimer:
This script is provided for informational and educational purposes only and does not constitute financial or investment advice. The author, Atilla Yurtseven, is not responsible for any financial losses or damages that may occur as a result of using this script. Trading and investing in financial markets involve risk, and past performance is not indicative of future results. Users should conduct their own research and consult with a qualified financial advisor before making any investment decisions. Use this script at your own risk.
Trade smart, stay safe.
Atilla Yurtseven
Polynomial Regression Keltner Channel [ChartPrime]Polynomial Regression Keltner Channel
⯁ OVERVIEW
The Polynomial Regression Keltner Channel [ ChartPrime ] indicator is an advanced technical analysis tool that combines polynomial regression with dynamic Keltner Channels. This indicator provides traders with a sophisticated method for trend analysis, volatility assessment, and identifying potential overbought and oversold conditions.
◆ KEY FEATURES
Polynomial Regression: Uses polynomial regression for trend analysis and channel basis calculation.
Dynamic Keltner Channels: Implements Keltner Channels with adaptive volatility-based bands.
Overbought/Oversold Detection: Provides visual cues for potential overbought and oversold market conditions.
Trend Identification: Offers clear trend direction signals and change indicators.
Multiple Band Levels: Displays four levels of upper and lower bands for detailed market structure analysis.
Customizable Visualization: Allows toggling of additional indicator lines and signals for enhanced chart analysis.
◆ FUNCTIONALITY DETAILS
⬥ Polynomial Regression Calculation:
Implements a custom polynomial regression function for trend analysis.
Serves as the basis for the Keltner Channel, providing a smoothed centerline.
//@function Calculates polynomial regression
//@param src (series float) Source price series
//@param length (int) Lookback period
//@returns (float) Polynomial regression value for the current bar
polynomial_regression(src, length) =>
sumX = 0.0
sumY = 0.0
sumXY = 0.0
sumX2 = 0.0
sumX3 = 0.0
sumX4 = 0.0
sumX2Y = 0.0
n = float(length)
for i = 0 to n - 1
x = float(i)
y = src
sumX += x
sumY += y
sumXY += x * y
sumX2 += x * x
sumX3 += x * x * x
sumX4 += x * x * x * x
sumX2Y += x * x * y
slope = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX)
intercept = (sumY - slope * sumX) / n
n - 1 * slope + intercept
⬥ Dynamic Keltner Channel Bands:
Calculates ATR-based volatility for dynamic band width adjustment.
Uses a base multiplier and adaptive volatility factor for flexible band calculation.
Generates four levels of upper and lower bands for detailed market structure analysis.
atr = ta.atr(length)
atr_sma = ta.sma(atr, 10)
// Calculate Keltner Channel Bands
dynamicMultiplier = (1 + (atr / atr_sma)) * baseATRMultiplier
volatility_basis = (1 + (atr / atr_sma)) * dynamicMultiplier * atr
⬥ Overbought/Oversold Indicator line and Trend Line:
Calculates an OB/OS value based on the price position relative to the innermost bands.
Provides visual representation through color gradients and optional signal markers.
Determines trend direction based on the polynomial regression line movement.
Generates signals for trend changes, overbought/oversold conditions, and band crossovers.
◆ USAGE
Trend Analysis: Use the color and direction of the basis line to identify overall trend direction.
Volatility Assessment: The width and expansion/contraction of the bands indicate market volatility.
Support/Resistance Levels: Multiple band levels can serve as potential support and resistance areas.
Overbought/Oversold Trading: Utilize OB/OS signals for potential reversal or pullback trades.
Breakout Detection: Monitor price crossovers of the outermost bands for potential breakout trades.
⯁ USER INPUTS
Length: Sets the lookback period for calculations (default: 100).
Source: Defines the price data used for calculations (default: HLC3).
Base ATR Multiplier: Adjusts the base width of the Keltner Channels (default: 0.1).
Indicator Lines: Toggle to show additional indicator lines and signals (default: false).
⯁ TECHNICAL NOTES
Implements a custom polynomial regression function for efficient trend calculation.
Uses dynamic ATR-based volatility adjustment for adaptive channel width.
Employs color gradients and opacity levels for intuitive visual representation of market conditions.
Utilizes Pine Script's plotchar function for efficient rendering of signals and heatmaps.
The Polynomial Regression Keltner Channel indicator offers traders a sophisticated tool for trend analysis, volatility assessment, and trade signal generation. By combining polynomial regression with dynamic Keltner Channels, it provides a comprehensive view of market structure and potential trading opportunities. The indicator's adaptability to different market conditions and its customizable nature make it suitable for various trading styles and timeframes.
DSL Oscillator [BigBeluga]DSL Oscillator BigBeluga
The DSL (Discontinued Signal Lines) Oscillator is an advanced technical analysis tool that combines elements of the Relative Strength Index (RSI), Discontinued Signal Lines, and Zero-Lag Exponential Moving Average (ZLEMA). This versatile indicator is designed to help traders identify trend direction, momentum, and potential reversal points in the market.
What are Discontinued Signal Lines (DSL)?
Discontinued Signal Lines are an extension of the traditional signal line concept used in many indicators. While a standard signal line compares an indicator's value to its smoothed (slightly lagging) state, DSL takes this idea further by using multiple adaptive lines that respond to the indicator's current value. This approach provides a more nuanced view of the indicator's state and momentum, making it easier to determine trends and desired states of the indicator.
🔵 KEY FEATURES
● Discontinued Signal Lines (DSL)
Uses multiple adaptive lines that respond to the indicator's value
Provides a more nuanced view of the indicator's state and momentum
Helps determine trends and desired states of the indicator more effectively
Available in "Fast" and "Slow" modes for different responsiveness
Acts as dynamic support and resistance levels for the oscillator
● DSL Oscillator
Based on a combination of RSI and Discontinued Signal Lines
// Discontinued Signal Lines
dsl_lines(src, length)=>
UP = 0.
DN = 0.
UP := (src > ta.sma(src, length)) ? nz(UP ) + dsl_mode / length * (src - nz(UP )) : nz(UP )
DN := (src < ta.sma(src, length)) ? nz(DN ) + dsl_mode / length * (src - nz(DN )) : nz(DN )
Smoothed using Zero-Lag Exponential Moving Average for reduced lag
// Zero-Lag Exponential Moving Average function
zlema(src, length) =>
lag = math.floor((length - 1) / 2)
ema_data = 2 * src - src
ema2 = ta.ema(ema_data, length)
ema2
Oscillates between 0 and 100
Color-coded for easy interpretation of market conditions
● Signal Generation
Generates buy signals when the oscillator crosses above the lower DSL line below 50
Generates sell signals when the oscillator crosses below the upper DSL line above 50
Signals are visualized on both the oscillator and the main chart
● Visual Cues
Background color changes on signal occurrences for easy identification
Candles on the main chart are colored based on the latest signal
Oscillator line color changes based on its position relative to the DSL lines
🔵 HOW TO USE
● Trend Identification
Use the color and position of the DSL Oscillator relative to its Discontinued Signal Lines to determine the overall market trend
● Entry Signals
Look for buy signals (green circles) when the oscillator crosses above the lower DSL line
Look for sell signals (blue circles) when the oscillator crosses below the upper DSL line
Confirm signals with the triangles on the main chart and background color changes
● Exit Signals
Consider exiting long positions on exit signals and short positions on Entery signals
Watch for the oscillator crossing back between the DSL lines as a potential early exit signal
● Momentum Analysis
Strong momentum is indicated when the oscillator moves rapidly towards extremes and away from the DSL lines
Weakening momentum can be spotted when the oscillator struggles to reach new highs or lows, or starts converging with the DSL lines
The space between the DSL lines can indicate potential momentum strength - wider gaps suggest stronger trends
● Confirmation
Use the DSL lines as dynamic support/resistance levels for the oscillator
Look for convergence between oscillator signals and price action on the main chart
Combine signals with other technical indicators or chart patterns for stronger confirmation
🔵 CUSTOMIZATION
The DSL Oscillator offers several customization options:
Adjust the main calculation length for the DSL lines
Choose between "Fast" and "Slow" modes for the DSL lines calculation
By fine-tuning these settings, traders can adapt the DSL Oscillator to various market conditions and personal trading strategies.
The DSL Oscillator provides a multi-faceted approach to market analysis, combining trend identification, momentum assessment, and signal generation in one comprehensive tool. Its dynamic nature and visual cues make it suitable for both novice and experienced traders across various timeframes and markets. The integration of RSI, Discontinued Signal Lines, and ZLEMA offers traders a sophisticated yet intuitive tool to inform their trading decisions.
The use of Discontinued Signal Lines sets this oscillator apart from traditional indicators by providing a more adaptive and nuanced view of market conditions. This can potentially lead to more accurate trend identification and signal generation, especially in markets with varying volatility.
Traders can use the DSL Oscillator to identify trends, spot potential reversals, and gauge market momentum. The combination of the oscillator, dynamic signal lines, and clear visual signals provides a holistic view of market conditions. As with all technical indicators, it's recommended to use the DSL Oscillator in conjunction with other forms of analysis and within the context of a well-defined trading strategy.
Futures Settlement [NeoButane]Traders use settlement prices as both support/resistance and as a target for price to trend towards. The intention of this script is to provide possible entry and exit levels for swing and scalp trades by drawing horizontal lines of true settlement prices provided by TradingView.
The settlement price, which is calculated daily, is used to determine the profit/loss of a trader's futures position. Prior to the daily close, price settlement of futures contracts is performed by taking the average of its traded price during a specified period of time.
Usage
The settlement prices, shown as horizontal lines, serve as support or resistance for entry or exit. There are hundreds of ways to combine this with favorite indicators, or it can be used as levels for pure price action traders.
See how settlement price levels can be used in confluence with oscillators.
Configuration
Toggles to show each settlement. Reprint shows prior weeks or months after they've ended. Back-adjusted futures, which affect expired futures price history on continuous futures charts, should only be enabled on non-standard charts to match the user's chart settings.
What this script does
This script plots the daily, weekly, and monthly settlements for futures, including an average for the two most recent weekly or monthly settlements. The weekly settlement uses the last day of the week's daily settlement and the monthly settlement uses the last day of the month's daily settlement. For symbols that do not have settlement prices, which will be almost if not all symbols that are not futures, the settlement price instead becomes price at the last second before the daily/weekly/monthly close. In those cases, this script becomes a tool for automatically plotting daily/weekly/monthly closes.
See below for two different bitcoin charts. The chart on top is a non-futures chart and a futures chart is at the bottom. Note that CME bitcoin futures settle 4 hours (1500 CST) before bitcoin's daily close (UTC).
How this script works
TradingView has a built-in ability to display daily settlements instead of the actual daily close. This can be enabled in chart settings for futures on the daily timeframe and there is an argument for Pine Script to do so as well. Because settlement times are different for multiple products during the day, the script uses the settlement price from daily timeframe, which is guaranteed to be correct because TradingView is wonderful. I accidentally found the undocumented backadjustment and settlement_at_close when I was trying to use ticker.inherit() to create a symbol with its daily close time changed to another symbol's, which I still haven't figured out. TradingView has since added documentation for both of them, but there's still an ambiguous 'etc.' in the description of ticker.inherit() so maybe there's more secret arguments...
The script is able to be used on non-standard charts by using ticker.standard(), but back-adjustment will need to be changed by input to match chart settings.
References
Investopedia explanation of settlement price.
www.investopedia.com
Settlement prices for ES.
www.cmegroup.com
CME summary of settlement price.
www.cmegroup.com
How to enable settlement price as close for daily intervals in TradingView. This does not affect the use of this script.
www.tradingview.com
About back-adjustment for continuous futures charts in TradingView.
www.tradingview.com
Carlos IndexOverview:
The "Carlos Index" is designed to help traders identify potential buy and sell opportunities by combining an Exponential Moving Average (EMA) with recent high and low levels of price action. This indicator is particularly useful for those looking to spot trend reversals and potential support/resistance zones.
How It Works:
EMA Calculation: The indicator uses a customizable EMA to smooth price data, making it easier to identify the underlying trend. The default length of the EMA is set to 20 periods, but this can be adjusted to suit different trading styles or timeframes.
High and Low Levels: The script plots the highest and lowest prices over the last 8 periods, providing a visual representation of recent market extremes. These levels can act as potential support and resistance areas.
Buy and Sell Signals: The indicator generates buy and sell signals based on the crossover and crossunder of the price and the EMA. A "Buy" signal is generated when the price crosses above the EMA and was higher than the previous period, indicating a potential bullish reversal. Conversely, a "Sell" signal appears when the price crosses below the EMA and was lower than the previous period, suggesting a bearish reversal.
Customization:
Length: The period length for the EMA can be adjusted to better fit the user's trading strategy.
Source: Users can select the price source for the EMA calculation, such as close, open, high, or low prices.
Originality and Usefulness:
The "Carlos Index" combines traditional technical analysis tools in a unique way to enhance traders' decision-making processes. While moving averages and price extremes are commonly used in market analysis, this indicator integrates them to provide a more holistic view of market conditions. The combination of EMA crossovers with recent high and low levels helps identify potential trend reversals and market sentiment changes more effectively.
What sets the "Carlos Index" apart is its dual approach to signal generation: it not only uses EMA crossovers but also considers the immediate price movement relative to the previous period, adding a layer of confirmation to buy and sell signals. This feature aims to reduce false signals and improve the accuracy of market entry and exit points.
Additionally, the customizable settings allow traders to tailor the indicator to their specific trading strategies, making it adaptable across different market environments and timeframes. The clear visual cues provided by the plotted EMA and price levels, along with the buy/sell labels, offer an intuitive understanding of market dynamics, even for those new to technical analysis.
Chart Usage:
This indicator should be used on a clean chart for best visibility.
The plotted lines (EMA, highs, and lows) and signals (Buy/Sell labels) provide a straightforward visual guide for traders.
By using the Carlos Index, traders can gain a clearer understanding of market dynamics and make more informed trading decisions. This script combines both trend-following and mean-reversion elements, making it versatile across various market conditions.
