Median Deviation Suite [InvestorUnknown]The Median Deviation Suite uses a median-based baseline derived from a Double Exponential Moving Average (DEMA) and layers multiple deviation measures around it. By comparing price to these deviation-based ranges, it attempts to identify trends and potential turning points in the market. The indicator also incorporates several deviation types—Average Absolute Deviation (AAD), Median Absolute Deviation (MAD), Standard Deviation (STDEV), and Average True Range (ATR)—allowing traders to visualize different forms of volatility and dispersion. Users should calibrate the settings to suit their specific trading approach, as the default values are not optimized.
Core Components
Median of a DEMA:
The foundation of the indicator is a Median applied to the 7-day DEMA (Double Exponential Moving Average). DEMA aims to reduce lag compared to simple or exponential moving averages. By then taking a median over median_len periods of the DEMA values, the indicator creates a robust and stable central tendency line.
float dema = ta.dema(src, 7)
float median = ta.median(dema, median_len)
Multiple Deviation Measures:
Around this median, the indicator calculates several measures of dispersion:
ATR (Average True Range): A popular volatility measure.
STDEV (Standard Deviation): Measures the spread of price data from its mean.
MAD (Median Absolute Deviation): A robust measure of variability less influenced by outliers.
AAD (Average Absolute Deviation): Similar to MAD, but uses the mean absolute deviation instead of median.
Average of Deviations (avg_dev): The average of the above four measures (ATR, STDEV, MAD, AAD), providing a combined sense of volatility.
Each measure is multiplied by a user-defined multiplier (dev_mul) to scale the width of the bands.
aad = f_aad(src, dev_len, median) * dev_mul
mad = f_mad(src, dev_len, median) * dev_mul
stdev = ta.stdev(src, dev_len) * dev_mul
atr = ta.atr(dev_len) * dev_mul
avg_dev = math.avg(aad, mad, stdev, atr)
Deviation-Based Bands:
The indicator creates multiple upper and lower lines based on each deviation type. For example, using MAD:
float mad_p = median + mad // already multiplied by dev_mul
float mad_m = median - mad
Similar calculations are done for AAD, STDEV, ATR, and the average of these deviations. The indicator then determines the overall upper and lower boundaries by combining these lines:
float upper = f_max4(aad_p, mad_p, stdev_p, atr_p)
float lower = f_min4(aad_m, mad_m, stdev_m, atr_m)
float upper2 = f_min4(aad_p, mad_p, stdev_p, atr_p)
float lower2 = f_max4(aad_m, mad_m, stdev_m, atr_m)
This creates a layered structure of volatility envelopes. Traders can observe which layers price interacts with to gauge trend strength.
Determining Trend
The indicator generates trend signals by assessing where price stands relative to these deviation-based lines. It assigns a trend score by summing individual signals from each deviation measure. For instance, if price crosses above the MAD-based upper line, it contributes a bullish point; crossing below an ATR-based lower line contributes a bearish point.
When the aggregated trend score crosses above zero, it suggests a shift towards a bullish environment; crossing below zero indicates a bearish bias.
// Define Trend scores
var int aad_t = 0
if ta.crossover(src, aad_p)
aad_t := 1
if ta.crossunder(src, aad_m)
aad_t := -1
var int mad_t = 0
if ta.crossover(src, mad_p)
mad_t := 1
if ta.crossunder(src, mad_m)
mad_t := -1
var int stdev_t = 0
if ta.crossover(src, stdev_p)
stdev_t := 1
if ta.crossunder(src, stdev_m)
stdev_t := -1
var int atr_t = 0
if ta.crossover(src, atr_p)
atr_t := 1
if ta.crossunder(src, atr_m)
atr_t := -1
var int adev_t = 0
if ta.crossover(src, adev_p)
adev_t := 1
if ta.crossunder(src, adev_m)
adev_t := -1
int upper_t = src > upper ? 3 : 0
int lower_t = src < lower ? 0 : -3
int upper2_t = src > upper2 ? 1 : 0
int lower2_t = src < lower2 ? 0 : -1
float trend = aad_t + mad_t + stdev_t + atr_t + adev_t + upper_t + lower_t + upper2_t + lower2_t
var float sig = 0
if ta.crossover(trend, 0)
sig := 1
else if ta.crossunder(trend, 0)
sig := -1
Practical Usage and Calibration
Default settings are not optimized: The given parameters serve as a starting point for demonstration. Users should adjust:
median_len: Affects how smooth and lagging the median of the DEMA is.
dev_len and dev_mul: Influence the sensitivity of the deviation measures. Larger multipliers widen the bands, potentially reducing false signals but introducing more lag. Smaller multipliers tighten the bands, producing quicker signals but potentially more whipsaws.
This flexibility allows the trader to tailor the indicator for various markets (stocks, forex, crypto) and time frames.
Backtesting and Performance Metrics
The code integrates with a backtesting library that allows traders to:
Evaluate the strategy historically
Compare the indicator’s signals with a simple buy-and-hold approach
Generate performance metrics (e.g., mean returns, Sharpe Ratio, Sortino Ratio) to assess historical effectiveness.
Disclaimer
No guaranteed results: Historical performance does not guarantee future outcomes. Market conditions can vary widely.
User responsibility: Traders should combine this indicator with other forms of analysis, appropriate risk management, and careful calibration of parameters.
Análise de Tendência
Pivot MeterThe "Pivot Meter" is a indicator designed to plot pivot levels (support and resistance) directly on the chart. It offers two types of pivot calculations STANDARD and FIBONACCI, allowing traders to choose their preferred method. Here's an overview of its features and functionalities:
________________________________________
Key Features
1. Pivot Types:
o STANDARD: Traditional calculation based on the previous period's high, low, and close.
o FIBONACCI: Uses Fibonacci ratios to calculate support and resistance levels.
2. Dynamic Time Frame Adjustment:
o The indicator adjusts its calculations based on the chart's timeframe, aligning pivot calculations with appropriate periods.
3. Pivot Levels:
o Resistance Levels (R1 to R5): Five resistance levels calculated based on the selected pivot type.
o Support Levels (S1 to S5): Five support levels corresponding to the pivot type.
o Central Pivot (P): The base pivot level for reference.
4. Visualization:
o All pivot levels are plotted as coloured horizontal bands on the chart for easy identification.
o Colours range from warm tones (red for higher resistance levels) to cool tones (blue for lower support levels).
o Thickness and styling make these levels visually prominent.
5. Real-Time Price Line:
o A dynamically updating line marks the current price, with customizable colour and width for visibility.
6. Labels for Levels:
o Labels are placed next to each pivot level for identification (e.g., R1, S1, Pivot).
o Labels dynamically adjust their position with the chart’s bar progression.
________________________________________
Purpose
This indicator helps traders identify potential reversal points, support and resistance levels, and critical price zones. It is especially useful for:
• Day Traders: Quickly assess key levels for short-term trades.
• Swing Traders: Spot significant support/resistance zones over longer periods.
• Trend Followers: Use pivot levels to confirm breakouts or bounces.
________________________________________
Customization Options
• Pivot Type Selection: Choose between STANDARD and FIBONACCI.
• Price Line Colour: Customize the colour of the current price line for better integration with your chart setup.
________________________________________
Technical Details
• Security Function: Data from higher timeframes is accessed using request.security, ensuring accurate and multi-timeframe pivot calculations.
• Dynamic Labelling: Labels update their positions with every new bar to remain synchronized with the latest data.
________________________________________
Usage
Traders can add this indicator to their TradingView charts to monitor critical levels and strategize entries, exits, and stop-loss placements based on the proximity to these pivots. The dual pivot calculation methods make it versatile for diverse trading styles.
COIN/BTC Trend OscillatorThe COIN/BTC Trend Oscillator is a versatile tool designed to measure and visualize momentum divergences between Coinbase stock ( NASDAQ:COIN ) and Bitcoin ( CRYPTOCAP:BTC ). It helps identify overbought and oversold conditions, while also highlighting potential trend reversals.
Key Features:
VWAP-Based Divergence Analysis:
• Tracks the difference between NASDAQ:COIN and CRYPTOCAP:BTC relative to their respective VWAPs.
• Highlights shifts in momentum between the two assets.
Normalized Oscillator:
• Uses ATR normalization to adapt to different volatility conditions.
• Displays momentum shifts on a standardized scale for better comparability.
Overbought and Oversold Conditions:
• Identifies extremes using customizable thresholds (default: ±80).
• Dynamic background colors for quick visual identification:
• Blue for overbought zones (potential sell).
• White for oversold zones (potential buy).
Rolling Highs and Lows Detection:
• Tracks turning points in the oscillator to identify possible trend reversals.
• Useful for spotting exhaustion or accumulation phases.
Use Case:
This indicator is ideal for trading Coinbase stock relative to Bitcoin’s momentum. It’s especially useful during strong market trends, helping traders time entries and exits based on extremes in relative performance.
Limitations:
• Performance may degrade in choppy or sideways markets.
• Assumes a strong correlation between NASDAQ:COIN and CRYPTOCAP:BTC , which may not hold during independent events.
Pro Tip: Use this oscillator with broader trend confirmation tools like moving averages or RSI to improve reliability. For macro strategies, consider combining with higher timeframes for alignment.
R-based Strategy Template [Daveatt]Have you ever wondered how to properly track your trading performance based on risk rather than just profits?
This template solves that problem by implementing R-multiple tracking directly in TradingView's strategy tester.
This script is a tool that you must update with your own trading entry logic.
Quick notes
Before we dive in, I want to be clear: this is a template focused on R-multiple calculation and visualization.
I'm using a basic RSI strategy with dummy values just to demonstrate how the R tracking works. The actual trading signals aren't important here - you should replace them with your own strategy logic.
R multiple logic
Let's talk about what R-multiple means in practice.
Think of R as your initial risk per trade.
For instance, if you have a $10,000 account and you're risking 1% per trade, your 1R would be $100.
A trade that makes twice your risk would be +2R ($200), while hitting your stop loss would be -1R (-$100).
This way of measuring makes it much easier to evaluate your strategy's performance regardless of account size.
Whenever the SL is hit, we lose -1R
Proof showing the strategy tester whenever the SL is hit: i.imgur.com
The magic happens in how we calculate position sizes.
The script automatically determines the right position size to risk exactly your specified percentage on each trade.
This is done through a simple but powerful calculation:
risk_amount = (strategy.equity * (risk_per_trade_percent / 100))
sl_distance = math.abs(entry_price - sl_price)
position_size = risk_amount / (sl_distance * syminfo.pointvalue)
Limitations with lower timeframe gaps
This ensures that if your stop loss gets hit, you'll lose exactly the amount you intended to risk. No more, no less.
Well, could be more or less actually ... let's assume you're trading futures on a 15-minute chart but in the 1-minute chart there is a gap ... then your 15 minute SL won't get filled and you'll likely to not lose exactly -1R
This is annoying but it can't be fixed - and that's how trading works anyway.
Features
The template gives you flexibility in how you set your stop losses. You can use fixed points, ATR-based stops, percentage-based stops, or even tick-based stops.
Regardless of which method you choose, the position sizing will automatically adjust to maintain your desired risk per trade.
To help you track performance, I've added a comprehensive statistics table in the top right corner of your chart.
It shows you everything you need to know about your strategy's performance in terms of R-multiples: how many R you've won or lost, your win rate, average R per trade, and even your longest winning and losing streaks.
Happy trading!
And remember, measuring your performance in R-multiples is one of the most classical ways to evaluate and improve your trading strategies.
Daveatt
Candle Open Time labels (& TAPDA Lines)Description of the "4-Hour Candle Opening Times (TAPDA Lines)" Indicator
The "4-Hour Candle Opening Times (TAPDA Lines)" indicator integrates key principles of the Time and Price Action Trading Algorithm (TAPTA) with practical tools for analyzing market behavior. This script is designed for traders who leverage the interaction between time and price to identify opportunities in the market. The indicator supports the identification of significant price levels and potential areas of interest based on historical data and recurring patterns tied to specific timeframes.
Core Concepts
Time and Price Interaction (TAPTA Logic):
The script implements TAPTA principles by focusing on time intervals (4-hour candles) and the price action associated with those intervals.
Traders use this logic to recognize how prices behave at specific times, identifying patterns, levels of support or resistance, and potential reversals.
Highs and Lows Recognition (TAPDA):
The indicator includes logic for identifying and marking "Tapped Highs and Lows," which occur when price action retraces to previously significant levels within a specified tolerance. These taps are visually represented with horizontal lines, enabling traders to spot recurring price behaviors and levels of interest.
Dynamic Levels for Decision-Making:
By combining time and price, the script visualizes key price levels and their relevance over time, equipping traders with actionable insights for entry, exit, and risk management.
Indicator Features
1. Visual Representation of Candle Opening Times
The indicator marks the opening times of 4-hour candles on the chart.
A customizable label system displays the time in either a 12-hour or 24-hour format, with options to toggle the visibility of AM/PM suffixes.
2. TAPDA Logic
Identifies and highlights price levels that have been tapped within a specified tolerance.
Horizontal lines are drawn to mark these levels, allowing traders to see historical price levels acting as support or resistance.
The "Tapped Highs and Lows" are updated dynamically based on the most recent price action.
3. Timeframe-Specific Filtering
Users can limit the display to specific times of interest, such as 2 AM, 6 AM, and 10 AM, by toggling the "GCT (General Candle Times)" option.
Additional options allow filtering TAPDA logic by AM or PM timeframes, catering to traders who focus on specific market sessions.
4. Adjustable Plotting Limits
The script incorporates settings for controlling the maximum number of labels and lines displayed on the chart:
Max Labels: Limits the number of labels plotted for 4-hour candle opening times.
Max TAPDA Lines: Limits the number of TAPDA horizontal lines displayed.
A "Sync Lines and Labels" option ensures the same number of labels and lines are plotted when enabled, providing a consistent and clutter-free visualization.
5. Plot Maximum Capability
A "Plot Max" feature allows users to override the default behavior and force the plotting of the maximum allowed labels and lines, providing a comprehensive view of historical data.
6. User-Friendly Customization
Fully customizable label styles, including options for position, size, color, and background opacity.
Adjustable tolerance levels for TAPDA lines ensure compatibility with different market conditions and trading strategies.
Settings for flipping or aligning label positions above or below candles, or locking them to the opening price.
Script Logic
The script is built to prioritize efficiency and clarity, adhering to TradingView's Pine Script best practices and community standards:
Initialization:
Arrays are used to store historical price data, including highs, lows, and timestamps, ensuring only the necessary amount of data is processed.
A flexible and efficient data management system maintains a rolling window of data for both labels and TAPDA lines, ensuring smooth performance.
Label and Line Plotting:
Labels are plotted dynamically at user-defined positions and styles to mark the opening times of 4-hour candles.
TAPDA lines are drawn between historical high or low points and the current price action when the tolerance condition is met.
Limit Management:
The script enforces limits on the number of labels and lines plotted on the chart to maintain visual clarity.
Users can enable synchronization between the maximum labels and lines to ensure consistent visualization.
Customization Options:
Extensive customization settings allow traders to tailor the indicator to their strategies and preferences, including:
Label and line styles.
Session filtering (AM, PM, or specific times).
Display limits and synchronization options.
Capabilities
1. Enhance Time-Based Analysis
By marking significant times (4-hour candle openings), traders can identify key market phases and recurring behaviors tied to specific hours.
2. Leverage Historical Price Action
TAPDA logic highlights areas where price action interacts with historical highs and lows, providing actionable insights into potential support or resistance zones.
3. Improve Decision-Making
The indicator supports informed decision-making by blending visual data with time and price action principles, helping traders spot opportunities and mitigate risks.
4. Flexible Application Across Strategies
Suitable for day traders, swing traders, and position traders who utilize time and price action for trend analysis, reversals, or breakout strategies.
Best Practices for Use
Key Levels Analysis:
Focus on labels and TAPDA lines near critical price zones to gauge potential market reactions.
Session-Based Trading:
Use AM/PM filters or GCT settings to isolate specific trading sessions relevant to your strategy.
Combine with Other Indicators:
Enhance the effectiveness of this indicator by combining it with moving averages, RSI, or other tools for confirmation.
Risk Management:
Use the identified levels for stop-loss placement or target setting to align with your risk tolerance.
IU EMA Channel StrategyIU EMA Channel Strategy
Overview:
The IU EMA Channel Strategy is a simple yet effective trend-following strategy that uses two Exponential Moving Averages (EMAs) based on the high and low prices. It provides clear entry and exit signals by identifying price crossovers relative to the EMAs while incorporating a built-in Risk-to-Reward Ratio (RTR) for effective risk management.
Inputs ( Settings ):
- RTR (Risk-to-Reward Ratio): Define the ratio for risk-to-reward (default = 2).
- EMA Length: Adjust the length of the EMA channels (default = 100).
How the Strategy Works
1. EMA Channels:
- High-based EMA: EMA calculated on the high price.
- Low-based EMA: EMA calculated on the low price.
The area between these two EMAs creates a "channel" that visually highlights potential support and resistance zones.
2. Entry Rules:
- Long Entry: When the price closes above the high-based EMA (crossover).
- Short Entry: When the price closes below the low-based EMA (crossunder).
These entries ensure trades are taken in the direction of momentum.
3. Stop Loss (SL) and Take Profit (TP):
- Stop Loss:
- For long positions, the SL is set at the previous bar's low.
- For short positions, the SL is set at the previous bar's high.
- Take Profit:
- TP is automatically calculated using the Risk-to-Reward Ratio (RTR) you define.
- Example: If RTR = 2, the TP will be 2x the risk distance.
4. Exit Rules:
- Positions are closed at either the stop loss or the take profit level.
- The strategy manages exits automatically to enforce disciplined risk management.
Visual Features
1. EMA Channels:
- The high and low EMAs are dynamically color-coded:
- Green: Price is above the EMA (bullish condition).
- Red: Price is below the EMA (bearish condition).
- The area between the EMAs is shaded for better visual clarity.
2. Stop Loss and Take Profit Zones:
- SL and TP levels are plotted for both long and short positions.
- Zones are filled with:
- Red: Stop Loss area.
- Green: Take Profit area.
Be sure to manage your risk and position size properly.
Wave Surge [UAlgo]The "Wave Surge " is a comprehensive indicator designed to provide advanced wave pattern analysis for market trends and price movements. Built with customizable parameters, it caters to both beginner and advanced traders looking to improve their decision-making process.
This indicator utilizes wave-based calculations, adaptive thresholds, and volume analysis to detect and visualize key market signals. By integrating multiple analysis techniques.
It calculates waves for high, low, and close prices using a configurable moving average (EMA) technique and pairs it with volume and baseline analysis to confirm patterns. The result is a robust framework for identifying potential entry and exit points in the market.
🔶 Key Features
Wave-Based Analysis: This indicator computes waves using exponential moving averages (EMA) of high, low, and close prices, with an adjustable wave period to suit different market conditions.
Customizable Baseline: Traders can select from multiple baseline types, including VWMA (Volume-Weighted Moving Average), EMA, SMA (Simple Moving Average), and HMA (Hull Moving Average), for trend confirmation.
Adaptive Thresholds: The adaptive threshold feature dynamically adjusts sensitivity based on a chosen period, ensuring the indicator remains responsive to varying market volatility.
Volume Analysis: The integrated volume analysis calculates volume ratios and allows traders to enable or disable this feature to refine signal accuracy.
Pattern Recognition: The indicator identifies specific wave patterns (Wave 1, Wave 3, Wave 4, Wave 5, Wave 6) and visually plots them on the chart for easy interpretation.
Visual and Color-Coded Signals: Clear visual signals (upward and downward arrows) are plotted on the chart to highlight potential bullish or bearish patterns. The baseline is color-coded for an intuitive understanding of market trends.
Configuration: Parameters for wave period, baseline length, volume factors, and sensitivity can be tailored to align with the trader’s strategy and market environment.
🔶 Interpreting the Indicator
Wave Patterns
The indicator detects and plots six unique wave patterns based on price changes that exceed an adaptive threshold. These patterns are validated by the direction of the baseline:
Wave 1 (Bullish): Triggered when the price increases above the threshold while the baseline is falling.
Wave 3, 4, and 6 (Bearish): Indicate potential downtrends validated by a rising baseline.
Wave 5 (Bullish): Suggests upward momentum when prices exceed the threshold with a falling baseline.
Baseline Trend
The baseline serves as a trend confirmation tool, dynamically changing color to reflect market direction:
Aqua (Rising): Indicates an upward trend.
Red (Falling): Indicates a downward trend.
Volume Confirmation
When enabled, the volume analysis feature ensures that signals are supported by significant volume movements. Patterns with high volume are considered more reliable.
Signal Visualization
Upward Arrows (🡹): Highlight potential bullish opportunities.
Downward Arrows (🡻): Highlight potential bearish opportunities.
Alerts
Alerts are triggered when key wave patterns are identified, providing traders with timely notifications to take action without being tied to the screen.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Volume and Price, EMA Hierarchy Scoring Relations V 1.1Understanding the Volume and Price, EMA Hierarchy Scoring Indicator
Financial markets are often analyzed through a series of technical indicators, each providing valuable but isolated insights into price movements, volume dynamics, and trends. While these tools are widely used, they often lack context when applied individually. The Volume and Price, EMA Hierarchy Scoring Indicator was developed to bridge this gap by introducing structure, context, and relationships between these known indicators.
By utilizing Exponential Moving Averages (EMAs) and assigning periods derived from prime numbers, this indicator creates a scoring system that evaluates the relative positioning and interaction of 13 widely used technical tools. This approach adds meaning to individual indicator outputs by:
Revealing how their results align, diverge, or complement each other.
Quantifying their collective behavior through a hierarchy scoring system.
Enabling traders to not only analyze indicators individually but also combine them to uncover how they influence and interact with each other.
The result is a tool that provides clarity and insight into market behavior, enabling traders to move beyond surface-level analysis and uncover deeper patterns and relationships within the data.
Key Features and Methodology
The Volume and Price, EMA Hierarchy Scoring Indicator is built on a robust mathematical framework that evaluates and visualizes the relationships between 13 widely used technical indicators. By leveraging Exponential Moving Averages (EMAs) and prime numbers, the indicator provides meaningful insights into individual indicator performance as well as their combined behavior.
1. EMA Hierarchy Scoring
At the core of the indicator is its ability to assess the hierarchy of EMAs for each tool. This hierarchy scoring evaluates how the EMAs are aligned relative to one another, providing traders with a quantifiable measure of the indicator's internal consistency and its alignment with trends.
How It Works:
Each EMA is assigned a period derived from a unique prime number. This ensures that no two EMAs overlap, preserving their individuality.
The scoring system measures the gaps between these EMAs, assigning weighted values to these relationships based on their position in the hierarchy.
Why Prime Numbers?
Prime numbers ensure that the EMA periods are distinct and mathematically unrelated, creating a structured yet diverse dataset for analysis.
This approach allows the scoring system to capture both short-term and long-term trends, while avoiding redundancy.
2. Independent Indicator Evaluation
One of the key features of this indicator is the ability to analyze any of the 13 tools individually. Each indicator has its own module, complete with adjustable parameters and dedicated visualizations:
Histograms: Represent the raw EMA hierarchy score. Positive bars indicate alignment with upward trends, while negative bars highlight potential reversals or misalignments.
Smoothed Line: Averages the histogram values, reducing short-term noise and emphasizing longer-term trends.
Signal Line: Highlights trend shifts by smoothing the smoothed line further. Crossovers between the smoothed line and the signal line act as actionable signals for traders.
3. Combining Indicators for Context
Beyond individual analysis, the indicator allows users to combine multiple indicators to evaluate their interactions. For example:
Pairing ALMA (price smoothing) with Volume enables traders to see how price trends are supported or contradicted by market activity.
Combining Delta Volume and CMF (Chaikin Money Flow) reveals nuanced dynamics of buying and selling pressure.
Number of Combinations
With 13 tools available, the indicator supports "two to the power of thirteen minus one," which equals 8,191possible combinations. This flexibility empowers traders to experiment with various subsets of indicators, tailoring their analysis to specific market conditions or strategies.
Detailed Breakdown of Indicators
The Volume and Price, EMA Hierarchy Scoring Indicator integrates 13 widely used technical indicators, each bringing a unique perspective to market analysis. These indicators are scored individually using the EMA hierarchy system and can also be combined for more comprehensive insights.
Here’s a detailed look at what each indicator contributes:
Price Analysis
Arnaud Legoux Moving Average (ALMA):
Purpose:
ALMA smooths price data, reducing noise while maintaining responsiveness to trends.
Unique Features:
The EMA hierarchy scoring highlights how well ALMA’s EMAs align, revealing the strength of price trends.
Visualization includes a histogram of ALMA scores, a smoothed line, and a signal line.
Settings:
Adjustable parameters for the window size, offset, and sigma.
Tooltips guide users on how each setting affects the calculation.
Application:
Evaluate price momentum or combine with volume-based indicators to validate trends.
2. Price Hierarchy Score (PRC):
Purpose:
Focuses solely on price behavior to identify consistency and strength.
Visualization:
Includes a histogram representing raw scores and smoothed and signal lines for trend detection.
Settings:
Adjustable EMA periods derived from prime numbers.
Customizable smoothing and signal periods.
Volume Insights
3. Chaikin Money Flow (CMF):
Purpose:
Integrates price and volume data to measure capital flow direction and strength.
Visualization:
Raw CMF hierarchy scores are plotted, alongside smoothed and signal lines for easier trend identification.
Settings:
Lookback period adjustment for CMF calculation.
Toggle for enabling/disabling the module.
Application:
Use alongside Delta Volume to assess buying and selling pressure.
Above chart snapshot, in addition to the well-known CMF indicator, the Volume and Price indicator and the EMA Hierarchy Scoring can also be seen in the chart. By enabling the CMF evaluation, you can observe both how the CMF is analyzed and how it aligns with the price chart.
4. Delta Volume:
Purpose:
Captures the balance between buying and selling activity in the market.
Visualization:
A histogram represents the raw divergence in buying and selling strength.
Signal lines help identify momentum shifts.
Settings:
Options to set lower timeframes for more granular analysis.
Adjustable smoothing and signal periods.
Application:
Combine with CMF for a deeper understanding of capital flow dynamics.
In the above chart, alongside the Volume Delta indicator, you can observe our evaluation of this indicator's performance.
In the above chart, as explained, you can observe the impact of our evaluation metrics both individually and in combination with other indicators. This chart featuring VPR (Volume and Price Indicator along with EMA Hierarchy Scoring) illustrates the interplay between CMF and Volume Delta.
5. Volume Hierarchy Score (VOL):
Purpose:
Tracks raw volume data to identify areas of heightened market activity.
Visualization:
Histogram and smoothed lines highlight volume trends.
Settings:
Prime-numbered EMA periods to analyze volume hierarchy.
Adjustable smoothing and signal line parameters.
In the above chart, as previously explained, by analyzing the EMA of volume data over 25 iterations within specified periods (based on the first 25 prime numbers), you can observe the relationship between volume and price. We are witnessing a price increase, while the current volume position shows significant deviation and instability relative to the EMAs calculated over 25 different time periods.
In the above chart, by simultaneously enabling the evaluation of both volume and price, you can clearly observe the interplay and impact of volume and price in relation to each other.
Momentum and Trend Strength
6. Aroon Up:
Purpose:
Evaluates the strength of trends by measuring time since price highs.
Visualization :
Hierarchy scores plotted as histograms with trend-tracking smoothed and signal lines.
Settings:
Lookback period adjustments.
Module toggle for focus on Aroon trends.
If the analysis and interpretation of Aroon lines seem somewhat complex, the Volume and Price Indicator along with EMA Hierarchy Scoring provides a clear and intuitive representation of the Aroon indicator in relation to the price chart, as you can see in the current chart.
7. Average Directional Index (ADX):
Purpose:
Quantifies the strength of trends, regardless of direction.
Visualization:
ADX scores and smoothed lines for trend confirmation.
Settings:
Adjustable directional indicator (DI) and ADX smoothing periods.
Tooltip guidance for parameter optimization.
The simultaneous chart of the well-known ADX indicator alongside the evaluation system of the Volume and Price Indicator with EMA Hierarchy Scoring provides an integrated perspective on the ADX indicator.
8. Elder Force Index (EFI):
Purpose:
Combines price and volume to measure the strength of price movements.
Visualization:
EFI hierarchy scores with clear trend representation through signal and smoothed lines.
Settings:
Length adjustments for sensitivity control.
Smoothing and signal line customization.
In the above chart, we simultaneously have the well-known EFI indicator and the Volume and Price Indicator along with EMA Hierarchy Scoring. As we progress further, you will become increasingly familiar with the functionality and precision of the Volume and Price Indicator along with EMA Hierarchy Scoring.
Volatility and Oscillators
9. Ehler Fisher Transform:
Purpose:
Highlights extreme price movements by transforming price data into a Gaussian distribution.
Visualization:
Fisher Transform scores with smoothed trend indicators.
Settings:
Fisher length adjustment.
Module toggle and smoothing controls.
10. McGinley Dynamic (MGD):
Purpose:
Tracks price trends while adjusting for volatility, providing a smoother signal.
Visualization:
Raw MGD hierarchy scores with smoothed and signal lines.
Settings:
Lookback period customization.
Adjustable smoothing and signal periods
.
Ichimoku Components
11. Conversion Line (ICMC):
Purpose:
Captures short-term price equilibrium levels within the Ichimoku framework.
Visualization:
Short-term hierarchy scores visualized with smoothed lines.
Settings:
Adjustable conversion line length.
Tooltips explaining Ichimoku-related insights.
12. Base Line (ICMB):
Purpose:
Identifies medium-term equilibrium levels in the Ichimoku system.
Visualization:
Scores and smoothed trend lines for medium-term trends.
Settings:
Base line period adjustments.
Tooltip guidance for Ichimoku analysis.
In the chart below, to better illustrate the capabilities of the Volume and Price, EMA Hierarchy Scoring relation, we present a chart that evaluates the simultaneous interaction of Ichimoku Base and Conversion lines, Price, Volume, and Delta Volume.
Market Health
13. Money Flow Index (MFI):
Purpose:
Detects overbought or oversold conditions using price and volume data.
Visualization:
MFI hierarchy scores with trend tracking through smoothed and signal lines.
Settings:
Lookback period customization for sensitivity adjustment.
Module toggle and visualization controls.
EMA of Indicators: A Unified Scoring Metric
The EMA of Indicators module introduces a unique way to aggregate and analyze the individual scores of all 13 indicators. By applying a unified EMA calculation to their hierarchy scores, this module provides a single, combined metric that reflects the overall market sentiment based on the collective behavior of all indicators.
How It Works
1. Indicator-Specific EMAs:
An EMA is calculated for each of the 13 indicator hierarchy scores. The EMA period is adjustable in the settings menu, allowing traders to control how responsive the metric is to recent changes.
2. Combined EMA Calculation:
The individual EMAs are summed and averaged to generate a single Combined EMA Value. This value represents the average performance and alignment of all the indicators.
3. Smoothed and Signal Lines:
To enhance the interpretability of the Combined EMA Value:
- A Smoothed EMA is calculated using an additional EMA to filter out short-term fluctuations.
- A Signal Line is applied to the Smoothed EMA, providing actionable signals when crossovers occur.
Visualization
The Combined EMA Value is visualized as:
Histogram Bars: Represent the raw Combined EMA Value, highlighting positive or negative market alignment.
Smoothed Line: Tracks longer-term trends by smoothing the combined value.
Signal Line: Marks potential shifts in market sentiment when it crosses the Smoothed Line.
Customization and Settings
The settings menu allows full control over the EMA calculation:
Enable/Disable Module: Toggle the entire EMA of Indicators functionality.
Adjust EMA Period: Define the responsiveness of the individual indicator EMAs.
Set Smoothing Period: Control the degree of smoothing applied to the combined score.
Signal Line Period: Fine-tune the signal line's sensitivity for detecting trend shifts.
Tooltips accompany each parameter, ensuring that users understand their impact on the final visualization.
Applications in Market Analysis
1. Market Health Overview:
Use the Combined EMA Value as a quick snapshot of overall market sentiment based on all 13 indicators.
2. Trend Confirmation:
Analyze crossovers between the Smoothed EMA and Signal Line to confirm market trends or reversals.
3. Flexible Strategy Development:
Adjust EMA and smoothing periods to align the module with short-term or long-term trading strategies.
From EMA Scoring to Divergence-Weighted Insights
While the EMA scoring system provides insights into individual indicators and their trends, the Divergence-Weighted Volatility Adjusted Score takes this analysis further by combining and comparing all 13 indicators into a unified metric.
The Divergence-Weighted Volatility Adjusted Score
This score evaluates how the EMA scores of the 13 indicators interact and diverge, adding a layer of context and collective behavior analysis to the raw hierarchy scores.
1. Normalization:
All EMA scores are scaled to a common range, ensuring comparability regardless of the magnitude of individual indicators.
2. Divergence Analysis:
The system calculates the average score of the 13 indicators and evaluates the deviation (or divergence) of each individual score from this average.
Indicators with significant divergence are highlighted, as they often signal critical market dynamics.
3. Dynamic Weighting:
Indicators with greater divergence are assigned higher weights in the combined score. This ensures that outliers with meaningful signals are emphasized.
4. Volatility Adjustment:
The combined score is adjusted based on market volatility (calculated as the standard deviation of the score over a defined lookback period). This stabilizes the output, making it reliable even during turbulent market conditions.
Visualization and Customization
The Divergence-Weighted Volatility Adjusted Score is plotted as a dynamic line chart, offering a clear visual summary of the collective behavior of all indicators. The chart includes:
Smoothed Score Line: Filters out noise and emphasizes longer-term trends.
Signal Line: Helps identify potential trend shifts by tracking smoothed score crossovers.
Settings:
Lookback Period: Defines the time frame for volatility calculation.
Smoothing Period: Controls the degree of noise reduction in the smoothed score line.
Signal Line Period: Adjusts the responsiveness of the signal line.
These settings are fully adjustable, with tooltips guiding users to understand their impact.
Applications
The Divergence-Weighted Volatility Adjusted Score has several practical applications:
1. Cross-Indicator Alignment:
Detect when multiple indicators align or diverge, signaling potential opportunities or risks.
2. Dynamic Market Insights:
Adapt to changing conditions with the volatility-adjusted scoring.
3. Trend Confirmation:
Use smoothed and signal lines to validate trends identified by individual indicators.
Conclusion
The Volume and Price, EMA Hierarchy Scoring Indicator redefines how traders analyze financial markets. By combining 13 widely used technical tools with a structured scoring system based on Exponential Moving Averages (EMAs) and prime-numbered periods, this indicator brings depth and context to market analysis.
Key features include:
Independent Analysis: Evaluate individual indicators with precise EMA hierarchy scoring to assess their alignment with market trends.
Dynamic Combinations: Explore the relationships between indicators through over 8,000 combinations to uncover nuanced interactions and patterns.
Divergence-Weighted Scoring: Compare the collective behavior of indicators using a divergence-weighted system, providing a holistic market perspective adjusted for volatility.
Customization: Enable or disable modules, adjust smoothing and signal periods, and fine-tune settings to align the indicator with specific trading strategies.
User-Friendly Visualizations: Intuitive histograms, smoothed lines, and signal lines help traders identify trends, reversals, and market alignment at a glance.
This indicator empowers traders to move beyond isolated analysis by creating meaning and context between known tools. Whether you’re a scalper seeking short-term trends or a swing trader analyzing broader market movements, the Volume and Price, EMA Hierarchy Scoring Indicator offers insights tailored to your strategy.
Disclaimer
The Volume and Price, EMA Hierarchy Scoring Indicator is a tool for technical analysis and market evaluation. While it provides structured insights into market behavior, no indicator can guarantee success or eliminate the inherent risks of trading. Market conditions are complex, and multiple factors influence price movements.
Users are advised to:
Combine this indicator with other analysis methods, such as fundamental analysis or risk management strategies.
Make informed decisions based on their own analysis, trading goals, and risk tolerance.
Trading involves significant risk, and past performance does not guarantee future results. Always consult with a financial advisor or professional before making trading decisions.
Sunil Spinning Top IndicatorThe spinning top is single candlestick pattern can be used as a reversal pattern.
Long Entry ->
If formed near the support go long on the next candle crossing over the high of the spinning top candle.
Stop Loss = Low of the Spinning Top Candle
If formed near the Resistance go short on the next candle crossing under the low of the spinning top candle.
Stop Loss = High of the Spinning Top Candle
Back test and give your feedback.
Double RSIDouble RSI (DRSI) Indicator
The Double RSI (DRSI) is a technical analysis tool designed to provide traders with enhanced buy and sell signals by identifying uptrend and downtrend thresholds. It refines traditional RSI-based signals by applying a "double calculation" to the Relative Strength Index (RSI), improving precision in detecting trend changes.
Key Concepts Behind the Indicator
1. Double RSI Calculation
The DRSI indicator takes the standard RSI (calculated using the closing price over a specified length) and applies a second RSI calculation to it. This creates a smoother, more refined RSI value, making it more effective at highlighting the general trend of the market.
RSI: Measures the strength of recent price movements, ranging from 0 to 100.
Double RSI (DRSI): Applies the RSI formula to the RSI values themselves, smoothing out fluctuations and generating clearer signals.
How Does the Indicator Work?
The DRSI identifies uptrends and downtrends using two user-defined thresholds:
Uptrend Threshold (Default = 59): A value above this threshold signals a potential shift into an uptrend.
Downtrend Threshold (Default = 52): A value below this threshold signals a potential shift into a downtrend.
Signal Generation
Buy Signal: A crossover occurs when the DRSI value crosses above the Downtrend Threshold, signaling the beginning of an upward movement.
Sell Signal: A crossunder occurs when the DRSI value crosses below the Uptrend Threshold, signaling the beginning of a downward movement.
Customizable Inputs
The indicator offers customizable settings for increased flexibility:
DRSI Length (Default = 13): Determines the lookback period for RSI calculations. A shorter length increases sensitivity, while a longer length smooths the signals.
Uptrend Threshold (Default = 59): Sets the level above which an uptrend is confirmed.
Downtrend Threshold (Default = 52): Sets the level below which a downtrend is confirmed.
Bar Color and Glow Effects: Traders can enable colored candles or glowing DRSI lines for better visual representation.
Why is This Indicator Useful for Traders?
1. Noise Reduction
By applying a second RSI calculation, the DRSI smooths out minor fluctuations and highlights the overall trend.
2. Clear Uptrend and Downtrend Signals
The indicator provides intuitive buy (green arrow) and sell (red arrow) markers, simplifying decision-making.
3. Customizable Thresholds
Traders can adjust the thresholds and length to better suit specific trading strategies or market conditions.
4. Bar Coloring
Bars are color-coded to indicate the trend:
Green (Above Uptrend Threshold): Indicates an uptrend.
Red (Below Downtrend Threshold): Indicates a downtrend.
How the Indicator Appears on the Chart
DRSI Line: A smooth line derived from the double RSI calculation.
Threshold Lines: Two horizontal lines (green for the Uptrend Threshold, red for the Downtrend Threshold) to visualize trend changes.
Colored Candles: Candlesticks dynamically change color based on the trend direction (green for uptrends, red for downtrends).
Buy/Sell Markers:
Buy Signal: A green upward triangle below the bar, marking the start of an uptrend.
Sell Signal: A red downward triangle above the bar, marking the start of a downtrend.
In Summary
The Double RSI (DRSI) indicator is a powerful tool for identifying uptrends and downtrends with:
Smoothed trend detection using double-calculated RSI values.
Clear, actionable buy and sell signals.
Customizable settings to match different trading styles.
By focusing on trend thresholds rather than overbought or oversold levels, the DRSI provides traders with precise, noise-free signals to optimize their trading decisions.
20/50 SMA Cross 200 SMAThis Pine Script code is designed to identify and visualize crossovers of two shorter-term Simple Moving Averages (SMAs), a 20-period SMA and a 50-period SMA, with a longer-term 200-period SMA on a price chart. It also includes alerts for these crossover events. Here's a breakdown:
**Purpose:**
The core idea behind this script is to detect potential trend changes. Crossovers of shorter-term moving averages over a longer-term moving average are often interpreted as bullish signals, while crossovers below are considered bearish.
**Key Components:**
1. **Moving Average Calculation:**
* `sma20 = ta.sma(close, 20)`: Calculates the 20-period SMA of the closing price.
* `sma50 = ta.sma(close, 50)`: Calculates the 50-period SMA of the closing price.
* `sma200 = ta.sma(close, 200)`: Calculates the 200-period SMA of the closing price.
2. **Crossover Detection:**
* `crossUp20 = ta.crossover(sma20, sma200)`: Returns `true` when the 20-period SMA crosses above the 200-period SMA.
* `crossDown20 = ta.crossunder(sma20, sma200)`: Returns `true` when the 20-period SMA crosses below the 200-period SMA.
* Similar logic applies for `crossUp50` and `crossDown50` with the 50-period SMA.
3. **Recent Crossover Tracking (Crucial Improvement):**
* `lookback = 7`: Defines a lookback period of 7 bars.
* `var bool hasCrossedUp20 = false`, etc.: Declares `var` (persistent) boolean variables to track if a crossover has occurred *within* the last 7 bars. This is the most important correction from previous versions.
* The logic using `ta.barssince()` is the key:
* If a crossover happens (`crossUp20` is true), the corresponding `hasCrossedUp20` is set to `true`.
* If no crossover happens on the current bar, it checks if a crossover happened within the last 7 bars using `ta.barssince(crossUp20) <= lookback`. If so, it keeps `hasCrossedUp20` as `true`. After 7 bars, it becomes `false`.
4. **Plotting Crossovers:**
* `plotshape(...)`: Plots circles on the chart to visually mark the crossovers.
* Green circles below the bars for bullish crossovers (20 and 50).
* Red circles above the bars for bearish crossovers (20 and 50).
* Different shades of green/red (green/lime, red/maroon) distinguish between 20 and 50 SMA crossovers.
5. **Plotting Moving Averages (Optional but Helpful):**
* `plot(sma20, color=color.blue, linewidth=1)`: Plots the 20-period SMA in blue.
* Similar logic for the 50-period SMA (orange) and 200-period SMA (gray).
6. **Alerts:**
* `alertcondition(...)`: Triggers alerts when crossovers occur. This is essential for real-time trading signals.
**How it Works (in Simple Terms):**
The script continuously calculates the 20, 50, and 200 SMAs. It then monitors for instances where the 20 or 50 SMA crosses the 200 SMA. When such a crossover happens, a colored circle is plotted on the chart, and an alert is triggered. The key improvement is that it remembers if a crossover occurred in the last 7 bars and continues to display the circle during that period.
**Use Case:**
Traders use this type of indicator to identify potential entry and exit points in the market. A bullish crossover (shorter SMA crossing above the longer SMA) might be a signal to buy, while a bearish crossover might be a signal to sell.
**Key Improvements over Previous Versions:**
* **Correct Lookback Implementation:** The use of `ta.barssince()` and `var` variables is the correct and efficient way to check for crossovers within a lookback period. This fixes the major flaw in earlier versions.
* **Clear Visualizations:** The use of `plotshape` with distinct colors makes it easy to distinguish between 20 and 50 SMA crossovers.
* **Alerts:** The inclusion of alerts makes the script much more practical for real-time trading.
This improved version provides a robust and useful tool for identifying and tracking SMA crossovers.
3_SMA_Strategy_V-Singhal by ParthibIndicator Name: 3_SMA_Strategy_V-Singhal by Parthib
Description:
The 3_SMA_Strategy_V-Singhal by Parthib is a dynamic trend-following strategy that combines three key simple moving averages (SMA) — SMA 20, SMA 50, and SMA 200 — to generate buy and sell signals. This strategy uses these SMAs to capture and follow market trends, helping traders identify optimal entry (buy) and exit (sell) points. Additionally, the strategy highlights the closing price (CP), which plays a critical role in confirming buy and sell signals.
The strategy also features a Second Buy Signal triggered if the price falls more than 10% after an initial buy signal, providing a re-entry opportunity with a different visual highlight for the second buy signal.
Features:
Three Simple Moving Averages (SMA):
SMA 20: Short-term moving average reflecting immediate market trends.
SMA 50: Medium-term moving average showing the prevailing trend.
SMA 200: Long-term moving average that indicates the overall market trend.
Buy Signal (B1):
Triggered when:
SMA 200 > SMA 50 > SMA 20, indicating a bullish market structure.
The closing price is positioned below all three SMAs, confirming a potential upward reversal.
A green label appears at the low of the bar with the text B1-Price, indicating the price at which the buy signal is generated.
Second Buy Signal (B2):
Triggered if the price falls more than 10% after the first buy signal, providing an opportunity to re-enter the market at a potentially better price.
A blue label appears at the low of the bar with the text B2-Price, showing the price at which the second buy opportunity arises.
Sell Signal (S):
Triggered when:
SMA 20 > SMA 50 > SMA 200, indicating a bearish trend.
The closing price (CP) is positioned above all three SMAs, confirming a potential downward movement.
A red label appears at the high of the bar with the text S-Price, showing the price at which the sell signal is triggered.
How It Works:
Buy Conditions:
SMA 200 > SMA 50 > SMA 20: Indicates a bullish market where the long-term trend (SMA 200) is above the medium-term (SMA 50), and the medium-term trend is above the short-term (SMA 20).
Closing price below all three SMAs: Confirms that the price is in a favorable position for a potential upward reversal.
Sell Conditions:
SMA 20 > SMA 50 > SMA 200: This setup indicates a bearish trend.
Closing price above all three SMAs: Confirms that the price is in a favorable position for a potential downward movement.
Second Buy Signal (B2): If the price falls more than 10% after the first buy signal, the strategy triggers a second buy opportunity (B2) at a potentially better price. This helps traders take advantage of pullbacks or corrections after an initial favorable entry.
Labeling System:
B1-Price: The first buy signal label, appearing when the market is bullish and the closing price is below all three SMAs.
B2-Price: The second buy signal label, triggered if the price falls more than 10% after the initial buy signal.
S-Price: The sell signal label, appearing when the market turns bearish and the closing price is above all three SMAs.
How to Use:
Add the Indicator: Add "3_SMA_Strategy_V-Singhal by Parthib" to your chart on TradingView.
Interpret Buy Signals (B1): Look for green labels with the text "B1-Price" when the closing price (CP) is below all three SMAs and the trend is bullish.
Interpret Second Buy Signals (B2): If the price falls more than 10% after the first buy, look for blue labels with "B2-Price" and a re-entry opportunity.
Interpret Sell Signals (S): Look for red labels with the text "S-Price" when the market turns bearish, and the closing price (CP) is above all three SMAs.
Conclusion:
The 3_SMA_Strategy_V-Singhal by Parthib is an efficient and simple trend-following tool for traders looking to make informed buy and sell decisions. By combining the power of three SMAs and the closing price (CP) confirmation, this strategy helps traders to buy when the market shows a strong bullish setup and sell when the trend turns bearish. Additionally, the second buy signal feature ensures that traders don’t miss out on re-entry opportunities after price corrections, giving them a chance to re-enter the market at a favorable price.
Johnny The Scalper - Momentum/Speed [by Oberlunar]The Johnny The Scalper indicator is designed to provide scalpers with insights into market momentum and speed dynamics by analyzing the price movement within candles. It calculates the "candle speed," defined as the range of a candle (high minus low) divided by the elapsed time in seconds since the candle opened. Users can customize the distance for comparison by specifying how many candles back the indicator should look when calculating the speed difference (`Diff`).
The script retrieves the speed of the specified candle from the past (`candle_speed_x`) and compares it to the speed of the current candle, calculating the difference (`speed_difference`). The indicator also identifies whether the current candle and the candle from the past are bullish (green) or bearish (red), using this information to interpret the dynamics of the difference.
If the difference is negative, it means the current candle's speed is slower than the reference candle's speed. A negative difference combined with candles of the same direction suggests a slowdown, while candles of opposite directions indicate a slowing reversal. A positive difference suggests that the current candle is faster. If the candles have the same direction, it signifies an acceleration in the current trend; if their directions differ, it indicates a faster reversal.
The results are displayed graphically as labels on the chart. Labels above the candles show the difference Diff with color-coded backgrounds based on the calculated dynamics:
orange for a slowdown in the same direction,
red for a slowing reversal,
green for acceleration in the same direction,
and blue for a faster reversal.
An additional label below the candle optionally displays the current candle's speed in real time. This indicator helps scalpers identify momentum shifts and potential reversals in a highly customizable manner, adapting to different trading strategies and timeframes.
Buying and Selling Volume Pressure S/RThis custom indicator aims to visualize underlying market pressure by cumulatively analyzing where trade volume occurs relative to each candle's price range. By separating total volume into "buying" (when price closes near the high of the bar) and "selling" (when price closes near the low of the bar), the indicator identifies shifts in dominance between buyers and sellers over a defined lookback period.
When cumulative buying volume surpasses cumulative selling volume (a "bullish cross"), it suggests that buyers are gaining control. Conversely, when cumulative selling volume exceeds cumulative buying volume (a "bearish cross"), it indicates that sellers are taking the upper hand.
Based on these crossovers, the indicator derives dynamic Support and Resistance lines. After a bullish cross, it continuously tracks and updates the lowest low that occurs while the trend is bullish, forming a support zone. Similarly, after a bearish cross, it updates the highest high that appears during the bearish trend, forming a resistance zone.
A Mid Line is then calculated as the average of the current dynamic support and resistance levels, providing a central reference point. Around this Mid Line, the script constructs an upper and lower channel based on standard deviation, offering a sense of volatility or "divergence" from the mean level.
Finally, the indicator provides simple buy and sell signals: a buy signal is triggered when the price closes back above the Mid Line, suggesting a potential shift toward bullish conditions, while a sell signal appears when the price closes below the Mid Line, hinting at a possible bearish move.
In summary, this indicator blends volume-based market pressure analysis with adaptive support and resistance detection and overlays them onto the chart. It helps traders quickly gauge who controls the market (buyers or sellers), identify dynamic levels of support and resistance, and receive alerts on potential trend changes—simplifying decision-making in rapidly evolving market conditions.
Important Notice:
Trading financial markets involves significant risk and may not be suitable for all investors. The use of technical indicators like this one does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research or consult with a qualified financial advisor before making trading decisions. Past performance is not indicative of future results.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
Auto Swing TPAutomatic TP generator from recent swing highs and swing lows
Multiple long & short TPs from current price are displayed.
Results will differ by timeframe.
The main parameter is the "cell size" which is the least significant price move for the current asset. The default value of 0.4% is optimized for crypto. You may want to use less for less volatile asset classes.
How it works
We divide price into cells of a certain percent sizes, mainly because this makes the computation a lot easier.
We note in which bar every price cell was last visited. We take the distance to the current bar and then the logarithm of that to a certain base (the "time dimension"). Using a logarithm gives a nice balance of near-term and long-term targets. We call that logarithmic value the "level" of that price cell.
If a price cell has a significantly higher or lower level (at least by +2 or -2) than the cell above or below, this is considered a possible TP area.
Finally we check if the trade makes sense (meaning is of a certain size, at least 10 cells by default). If yes, we reduce the TP by a bit (by default 2 cells) and add it to the chart.
Weekly Open LineThis indicator displays the weekly open price on the chart. It automatically updates every Monday to reflect the opening price of the current week. A dashed line is drawn to indicate the weekly open, and a label stating "Monday" is shown on each Monday for easy identification.
Features:
Automatically calculates the weekly open on Mondays.
Displays a dashed line at the weekly open price.
Labels the weekly open with the text "Monday" for visibility.
Indikator ini menampilkan harga open mingguan di grafik. Indikator ini secara otomatis diperbarui setiap hari Senin untuk mencerminkan harga pembukaan minggu berjalan. Garis putus-putus digambar untuk menunjukkan open mingguan, dan sebuah label yang menyatakan "Moday" ditampilkan setiap hari Senin untuk memudahkan identifikasi.
ETH - 12HR Double Kernel Regression Strategy ETH Double Kernel Regression Strategy
This ETH -focused, 12-hour Double Kernel Regression strategy is designed to cut through market noise and guide you toward data-backed, higher-probability trades. By utilizing two kernel regression models—Fast and Slow—this approach gauges momentum shifts and confirms trends. The strategy intelligently switches between these kernels based on identifying FOMO patterns, allowing it to adapt to changing market conditions. This ensures you enter trades when the trend is genuinely gaining strength, rather than blindly "buying the dip."
Key Concepts
Fine-Tuned Since Inception:
The strategy’s logic and filters—including price thresholds, trend moving averages (MAs), and kernel confirmations—are meticulously fine-tuned to perform consistently across all market conditions. This proactive planning enables confident entries during bullish recoveries, eliminating the need to second-guess every signal.
“Buy the Rise, Sell the Dip” Logic:
Unlike the traditional mantra, this strategy waits for slow kernel confirmation before entering uptrends. When market conditions shift, it identifies optimal entry points and holds steady if the trade isn’t losing money. This reduces guesswork and helps prevent buying into false rallies.
Sell the Hype:
The crypto market is often cluttered with noise—meme coins, last-minute hype, and social media influencers. The Double Kernel Regression approach distinguishes genuine trends from hype-driven movements. When the price exceeds simple moving averages (SMAs), the fast kernel generates a sell signal. This carefully crafted strategy helps you navigate the chaotic landscape, especially during hype-driven rallies, and ensures you sell at the top.
Try It Out
Import this strategy into your TradingView platform and observe how it reacts in real-time as market conditions change. Evaluate the signals, adjust parameters if necessary, and experience firsthand how combining sound trading philosophy with a data-driven backbone can transform your trading journey.
Market StructureThis is an advanced, non-repainting Market Structure indicator that provides a robust framework for understanding market dynamics across any timeframe and instrument.
Key Features:
- Non-repainting market structure detection using swing highs/lows
- Clear identification of internal and general market structure levels
- Breakout threshold system for structure adjustments
- Integrated multi-timeframe compatibility
- Rich selection of 30+ moving average types, from basic to advanced adaptive variants
What Makes It Different:
Unlike most market structure indicators that repaint or modify past signals, this implementation uses a fixed-length lookback period to identify genuine swing points.
This means once a structure level or pivot is identified, it stays permanent - providing reliable signals for analysis and trading decisions.
The indicator combines two layers of market structure:
1. Internal Structure (lighter lines) - More sensitive to local price action
2. General Structure (darker lines) - Shows broader market context
Technical Details:
- Uses advanced pivot detection algorithm with customizable swing size
- Implements consecutive break counting for structure adjustments
- Supports both close and high/low price levels for breakout detection
- Includes offset option for better visual alignment
- Each structure break is validated against multiple conditions to prevent false signals
Offset on:
Offset off:
Moving Averages Library:
Includes comprehensive selection of moving averages, from traditional to advanced adaptive types:
- Basic: SMA, EMA, WMA, VWMA
- Advanced: KAMA, ALMA, VIDYA, FRAMA
- Specialized: Hull MA, Ehlers Filter Series
- Adaptive: JMA, RPMA, and many more
Perfect for:
- Price action analysis
- Trend direction confirmation
- Support/resistance identification
- Market structure trading strategies
- Multiple timeframe analysis
This open-source tool is designed to help traders better understand market dynamics and make more informed trading decisions. Feel free to use, modify, and enhance it for your trading needs.
3 EMA + RSI with Trail Stop [Free990] (LOW TF)This trading strategy combines three Exponential Moving Averages (EMAs) to identify trend direction, uses RSI to signal exit conditions, and applies both a fixed percentage stop-loss and a trailing stop for risk management. It aims to capture momentum when the faster EMAs cross the slower EMA, then uses RSI thresholds, time-based exits, and stops to close trades.
Short Explanation of the Logic
Trend Detection: When the 10 EMA crosses above the 20 EMA and both are above the 100 EMA (and the current price bar closes higher), it triggers a long entry signal. The reverse happens for a short (the 10 EMA crosses below the 20 EMA and both are below the 100 EMA).
RSI Exit: RSI crossing above a set threshold closes long trades; crossing below another threshold closes short trades.
Time-Based Exit: If a trade is in profit after a set number of bars, the strategy closes it.
Stop-Loss & Trailing Stop: A fixed stop-loss based on a percentage from the entry price guards against large drawdowns. A trailing stop dynamically tightens as the trade moves in favor, locking in potential gains.
Detailed Explanation of the Strategy Logic
Exponential Moving Average (EMA) Setup
Short EMA (out_a, length=10)
Medium EMA (out_b, length=20)
Long EMA (out_c, length=100)
The code calculates three separate EMAs to gauge short-term, medium-term, and longer-term trend behavior. By comparing their relative positions, the strategy infers whether the market is bullish (EMAs stacked positively) or bearish (EMAs stacked negatively).
Entry Conditions
Long Entry (entryLong): Occurs when:
The short EMA (10) crosses above the medium EMA (20).
Both EMAs (short and medium) are above the long EMA (100).
The current bar closes higher than it opened (close > open).
This suggests that momentum is shifting to the upside (short-term EMAs crossing up and price action turning bullish). If there’s an existing short position, it’s closed first before opening a new long.
Short Entry (entryShort): Occurs when:
The short EMA (10) crosses below the medium EMA (20).
Both EMAs (short and medium) are below the long EMA (100).
The current bar closes lower than it opened (close < open).
This indicates a potential shift to the downside. If there’s an existing long position, that gets closed first before opening a new short.
Exit Signals
RSI-Based Exits:
For long trades: When RSI exceeds a specified threshold (e.g., 70 by default), it triggers a long exit. RSI > short_rsi generally means overbought conditions, so the strategy exits to lock in profits or avoid a pullback.
For short trades: When RSI dips below a specified threshold (e.g., 30 by default), it triggers a short exit. RSI < long_rsi indicates oversold conditions, so the strategy closes the short to avoid a bounce.
Time-Based Exit:
If the trade has been open for xBars bars (configurable, e.g., 24 bars) and the trade is in profit (current price above entry for a long, or current price below entry for a short), the strategy closes the position. This helps lock in gains if the move takes too long or momentum stalls.
Stop-Loss Management
Fixed Stop-Loss (% Based): Each trade has a fixed stop-loss calculated as a percentage from the average entry price.
For long positions, the stop-loss is set below the entry price by a user-defined percentage (fixStopLossPerc).
For short positions, the stop-loss is set above the entry price by the same percentage.
This mechanism prevents catastrophic losses if the market moves strongly against the position.
Trailing Stop:
The strategy also sets a trail stop using trail_points (the distance in price points) and trail_offset (how quickly the stop “catches up” to price).
As the market moves in favor of the trade, the trailing stop gradually tightens, allowing profits to run while still capping potential drawdowns if the price reverses.
Order Execution Flow
When the conditions for a new position (long or short) are triggered, the strategy first checks if there’s an opposite position open. If there is, it closes that position before opening the new one (prevents going “both long and short” simultaneously).
RSI-based and time-based exits are checked on each bar. If triggered, the position is closed.
If the position remains open, the fixed stop-loss and trailing stop remain in effect until the position is exited.
Why This Combination Works
Multiple EMA Cross: Combining 10, 20, and 100 EMAs balances short-term momentum detection with a longer-term trend filter. This reduces false signals that can occur if you only look at a single crossover without considering the broader trend.
RSI Exits: RSI provides a momentum oscillator view—helpful for detecting overbought/oversold conditions, acting as an extra confirmation to exit.
Time-Based Exit: Prevents “lingering trades.” If the position is in profit but failing to advance further, it takes profit rather than risking a trend reversal.
Fixed & Trailing Stop-Loss: The fixed stop-loss is your safety net to cap worst-case losses. The trailing stop allows the strategy to lock in gains by following the trade as it moves favorably, thus maximizing profit potential while keeping risk in check.
Overall, this approach tries to capture momentum from EMA crossovers, protect profits with trailing stops, and limit risk through both a fixed percentage stop-loss and exit signals from RSI/time-based logic.
Physical Levels (XAUUSD, 5$ Pricesteps)Functionality:
This indicator draws horizontal lines in the XAUUSD market at a fixed spacing of USD 5. The lines are both above and below the current market price. The number of lines is limited to optimize performance.
Use:
The indicator is particularly useful for traders who want to analyze psychological price levels, support and resistance areas, or significant price zones in the gold market. It helps to better visualize price movements and their proximity to round numbers.
How it works:
The indicator calculates a starting price based on the current price of XAUUSD, rounded to the nearest multiple of USD 5.
Starting from this starting price, evenly distributed lines are drawn up and down.
The lines are black throughout and are updated dynamically according to the current chart.
VWAP SlopeThis script calculates and displays the slope of the Volume Weighted Average Price (VWAP) . It compares the current VWAP with its value from a user-defined lookback period to determine the slope. The slope is color-coded: green for an upward trend (positive slope) and red for a downward trend (negative slope) .
Key Points:
VWAP Calculation: The script calculates the VWAP based on a user-defined timeframe (default: daily), which represents the average price weighted by volume.
Slope Determination: The slope is calculated by comparing the current VWAP to its value from a previous period, providing insight into market trends.
Color-Coding: The slope line is color-coded to visually indicate the market direction: green for uptrend and red for downtrend.
This script helps traders identify the direction of the market based on VWAP , offering a clear view of trends and potential turning points.
VWAP - TrendThis Pine Script calculates the Volume Weighted Average Price (VWAP) for a specified timeframe and plots its Linear Regression over a user-defined lookback period . The regression line is color-coded: green indicates an uptrend and red indicates a downtrend. The line is broken at the end of each day to prevent it from extending into the next day, ensuring clarity on a daily basis.
Key Features:
VWAP Calculation: The VWAP is calculated based on a selected timeframe, providing a smoothed average price considering volume.
Linear Regression: The script calculates a linear regression of the VWAP over a custom lookback period to capture the underlying trend.
Color-Coding: The regression line is color-coded to easily identify trends—green for an uptrend and red for a downtrend.
Day-End Break: The regression line breaks at the end of each day to prevent continuous plotting across days, which helps keep the analysis focused within daily intervals.
User Inputs: The user can adjust the VWAP timeframe and the linear regression lookback period to tailor the indicator to their preferences.
This script provides a visual representation of the VWAP trend, helping traders identify potential market directions and turning points based on the linear regression of the VWAP.
LRI Momentum Cycles [AlgoAlpha]Discover the LRI Momentum Cycles indicator by AlgoAlpha, a cutting-edge tool designed to identify market momentum shifts using trend normalization and linear regression analysis. This advanced indicator helps traders detect bullish and bearish cycles with enhanced accuracy, making it ideal for swing traders and intraday enthusiasts alike.
Key Features :
🎨 Customizable Appearance : Set personalized colors for bullish and bearish trends to match your charting style.
🔧 Dynamic Trend Analysis : Tracks market momentum using a unique trend normalization algorithm.
📊 Linear Regression Insight : Calculates real-time trend direction using linear regression for better precision.
🔔 Alert Notifications : Receive alerts when the market switches from bearish to bullish or vice versa.
How to Use :
🛠 Add the Indicator : Favorite and apply the indicator to your TradingView chart. Adjust the lookback period, linear regression source, and regression length to fit your strategy.
📊 Market Analysis : Watch for color changes on the trend line. Green signals bullish momentum, while red indicates bearish cycles. Use these shifts to time entries and exits.
🔔 Set Alerts : Enable notifications for momentum shifts, ensuring you never miss critical market moves.
How It Works :
The LRI Momentum Cycles indicator calculates trend direction by applying linear regression on a user-defined price source over a specified period. It compares historical trend values, detecting bullish or bearish momentum through a dynamic scoring system. This score is normalized to ensure consistent readings, regardless of market conditions. The indicator visually represents trends using gradient-colored plots and fills to highlight changes in momentum. Alerts trigger when the momentum state changes, providing actionable trading signals.
