Power Play Signal Indicator [Masky18]Power Play Signal Indicator
The Power Play Signal Indicator is a sophisticated custom trading strategy designed to identify high-probability breakout and breakdown opportunities by combining consolidation detection, trend alignment, volume analysis, and relative strength ranking. Unlike simple mashups of existing indicators, this script integrates multiple technical concepts into a cohesive strategy that helps traders capitalize on market momentum with precision.
What Makes This Indicator Unique?
The PowerPlay Signal Indicator is not just a combination of existing indicators; it is a custom-built strategy that uses original logic to filter out low-probability setups and focus on high-quality trading opportunities. Here’s how it works:
Consolidation Detection:
The script identifies consolidation zones by analyzing price action over a user-defined period (default: 6 bars). It calculates the high, low, and midpoint of the consolidation range and ensures the price stays within a specified percentage range (default: 13%).
Consolidations are classified as Tight, Loose, or Okay, helping traders gauge the strength of the potential breakout or breakdown.
Breakout & Breakdown Logic:
Breakouts and breakdowns are confirmed using a combination of:
Price Action: The script checks if the price closes above the consolidation high (breakout) or below the consolidation low (breakdown).
Volume Analysis: A significant volume spike (default: 20% increase) is required to confirm the move.
MACD & Moving Averages: The script uses MACD and moving averages (50-day and 200-day) to ensure the breakout/breakdown aligns with the prevailing trend.
Trend Alignment:
The script ensures trades are aligned with the long-term trend by using:
50-day SMA and 200-day SMA to confirm uptrends or downtrends.
150-day SMA as an additional filter to ensure the trend is strong.
52-week high/low conditions to ensure the price is in a favorable position relative to its historical range.
Relative Strength Ranking:
The script compares the asset’s performance against a benchmark asset (e.g., SPY) to ensure it is outperforming the market. This is done using a customizable Relative Strength (RS) Threshold (default: 70).
Golden Candle Signals:
For high-probability setups, the script identifies Golden Candles—strong breakout or breakdown candles with:
Large price movement (default: 7.5% to 12.5% candle size).
High volume (default: 2x the average consolidation volume).
Alignment with MACD and moving averages.
Risk Management:
The script provides stop loss, trailing stop, and take profit levels based on:
ATR (Average True Range): Dynamic stop loss levels are calculated using ATR (default: 14-period ATR with a 2x multiplier).
Trailing Stop Percentage: User-defined trailing stop (default: 2%).
Take Profit Percentage: User-defined take profit (default: 5%).
Performance Tracking:
The script includes a Performance Table that tracks:
Total breakouts and breakdowns.
Successful and failed trades.
Win rates for breakouts and breakdowns.
Golden candle signals.
How Does It Work?
The PowerPlay Signal Indicator combines the following key components to generate signals:
Consolidation Detection:
The script calculates the high, low, and midpoint of the consolidation range over a user-defined period.
It ensures the price stays within a specified percentage range (default: 13%) to confirm consolidation.
Breakout/Breakdown Confirmation:
A breakout is confirmed when:
The price closes above the consolidation high.
Volume increases by at least 20%.
MACD is positive and above the signal line.
The price is above the 50-day and 200-day SMAs.
A breakdown is confirmed when:
The price closes below the consolidation low.
Volume increases by at least 20%.
MACD is negative and below the signal line.
The price is below the 50-day and 200-day SMAs.
Golden Candle Signals:
Golden Candles are identified when:
The candle size is between 7.5% and 12.5%.
Volume is at least 2x the average consolidation volume.
The candle aligns with the prevailing trend and MACD.
Risk Management:
Stop loss levels are calculated using ATR (default: 14-period ATR with a 2x multiplier).
Trailing stop and take profit levels are based on user-defined percentages.
How to Use the Indicator
Input Parameters:
Consolidation Periods: Set the number of bars to analyze for consolidation (default: 6).
Maximum Consolidation Range: Define the maximum percentage range for consolidation (default: 13%).
Stop Loss Factor: Adjust the stop loss multiplier based on the midpoint of the consolidation range (default: 0.985).
RS Threshold: Set the relative strength threshold for trend alignment (default: 70).
Comparison Asset: Enable comparison with a benchmark asset (e.g., SPY) to ensure the asset is outperforming the market.
Trailing Stop Percentage: Set the trailing stop percentage (default: 2%).
Take Profit Percentage: Set the take profit percentage (default: 5%).
Time Exit Bars: Define the maximum number of bars to hold a trade (default: 10).
Interpreting Signals:
Breakout Signal: A green label ("BO") appears when a breakout is detected.
Breakdown Signal: A red label ("BD") appears when a breakdown is detected.
Golden Candle Signal: A gold medal icon (🥇) appears for high-probability setups.
Performance Table:
The performance table displays the number of trades, successful trades, failed trades, and win rates for breakouts and breakdowns.
Alerts:
Enable alerts for breakouts, breakdowns, and golden candles to stay informed about potential trading opportunities.
Why Choose the PowerPlay Signal Indicator?
Original Logic: Combines consolidation detection, trend alignment, volume analysis, and relative strength ranking into a unique strategy.
High-Probability Signals: Focuses on high-quality setups with strong volume and trend alignment.
Risk Management: Built-in stop loss, trailing stop, and take profit options help you manage risk effectively.
Performance Tracking: Tracks trade outcomes and win rates to help you refine your strategy.
Customizable: Fully adjustable inputs allow you to adapt the indicator to your trading style and market conditions.
Pesquisar nos scripts por "averages"
Crypto Divergence from BTCThis script is used to indicate when price action of a crypto coin is diverging significantly from that of BTC.
Explanation of the Script:
Inputs:
roc_length: The period used for calculating the Rate of Change.
ma_length: The period used for the moving average of the ROC.
threshold: The percentage difference that indicates a divergence.
Price Data:
The script retrieves the current asset's price and Bitcoin's price.
ROC Calculation:
The ROC for both the current asset and BTC is calculated based on the defined roc_length.
Moving Averages:
Simple moving averages (SMA) of the ROC values are calculated to smooth out the data.
Divergence Detection:
The indicator checks if the current asset's ROC MA is significantly higher or lower than Bitcoin's ROC MA based on the specified threshold.
Plotting:
The script plots the ROC values and their moving averages.
It also highlights the background in green when a bullish divergence is detected (when the asset is moving up while BTC is lagging) and in red for a bearish divergence.
[KVA]Volume ImpulseThe Volume Impulse indicator is designed to provide insights into market momentum by analyzing volume dynamics. It helps traders identify periods of strong buying and selling pressure, which can be crucial for making informed trading decisions.
What does the indicator do?
The Volume Impulse indicator calculates positive and negative volume percentages based on the price range within each bar. It allows traders to visualize the distribution of volume and detect potential shifts in market sentiment.
How does it work?
The indicator uses a customizable lookback period to analyze volume data, smoothing the results with user-defined moving averages. By comparing the positive and negative volume percentages, the indicator highlights overbought and oversold conditions, aiding in trend detection and potential reversal points.
How to use it?
Identify Momentum: Use the positive and negative volume percentages to gauge market momentum within the specified lookback period.
Detect Overbought/Oversold Conditions: Look for the indicator crossing above the overbought level or below the oversold level to identify potential reversal points.
Smooth Trends: Adjust the moving average type and lengths to smooth out the volume data and identify trends more clearly.
Key Features
Volume Analysis: Calculates the positive and negative volume based on the price range within each bar.
Lookback Period: Allows you to define a lookback period over which the indicator calculations are performed, providing flexibility in analyzing different timeframes.
Customizable Moving Averages: Choose from various types of moving averages (EMA, SMA, WMA, Hull) to smooth the volume data.
Overbought/Oversold Levels: Visual markers for overbought, middle, and oversold conditions to help identify potential reversal points.
Color-Coded Areas: Highlights overbought and oversold regions with customizable colors for easy visual interpretation.
Plotting Options: Displays the positive volume and its smoothed version using the selected moving average type and length.
Inputs:
Lookback Period: Define the period over which the volume analysis is performed.
Moving Average Type: Select the type of moving average (EMA, SMA, WMA, Hull) to be applied.
Moving Average Length: Set the length for the primary moving average.
Smooth Length: Define the length for the smoothed moving average.
Overbought Level: Set the threshold for overbought conditions.
Middle Level: Set the threshold for middle conditions.
Oversold Level: Set the threshold for oversold conditions.
Color Settings: Customize the colors for overbought and oversold areas and their respective fill colors.
EMA and SMA Stacked IndicationEMA and SMA Stacked Indication
Are you looking for a powerful tool to help you identify bullish and bearish market trends with precision? Look no further! Our EMA and SMA Stacked Indication indicator is designed to enhance your trading strategy by providing clear visual signals based on the alignment of key moving averages.
Key Features:
Bullish and Bearish Stack Detection: Quickly identify market trends with our color-coded stacking system. Green dots indicate a bullish stack, while red dots signal a bearish stack.
Visual Clarity: Dots are plotted above and below the price to provide clear, easily interpretable signals without cluttering your chart.
ATR-Based Adjustments: Dots are positioned based on the Average True Range (ATR), ensuring they are visible and informative in all market conditions.
Seamless Integration: Overlay the indicator on any chart without disrupting your existing analysis.
How It Works:
Our indicator calculates four essential moving averages:
8-period EMA
21-period EMA
50-period SMA
200-period SMA
These averages are then analyzed to determine bullish or bearish stacking:When a bullish stack is detected, green dots are plotted above and below the price. Conversely, red dots appear when a bearish stack is identified. This visual representation helps you quickly grasp market conditions and make informed trading decisions.
Why Choose EMA and SMA Stacked Indication?
Enhance Your Strategy: Incorporate reliable moving average signals into your trading toolkit.
Simplify Analysis: Easily spot market trends and potential reversal points with our intuitive indicator.
Boost Confidence: Make more informed decisions backed by robust technical analysis.
Unlock the full potential of your trading with the EMA and SMA Stacked Indication. Start using it today and take your market analysis to the next level!
Kshitij Malve - Minervini Trend Criteria (MTC)Purpose:
This indicator is designed to assist traders in identifying stocks that potentially meet the bullish Stage 2 trend criteria outlined by renowned stock trader Mark Minervini. It analyzes price movement in relation to moving averages and calculates certain price thresholds to provide visual signals.
Key Features:
Minervini Stage 2 Focus: Specifically targets trend characteristics highlighted in Minervini's trading methodology.
Adjustable Moving Averages: The script includes inputs for 150-day, 200-day, and 50-day moving average lengths, allowing users to customize their analysis.
Visual Trend Criteria: Each core Stage 2 trend condition is plotted below the chart as green or red dots for quick visual assessment.
Stage 2 Uptrend Signal: When all key trend conditions are met, a purple up-arrow appears beneath the price chart.
Alerts: Customizable alerts can be set up to notify the user when all conditions are met, signaling a potential Stage 2 uptrend.
Conditions Evaluated:
Price Position: Current price is above the 50-day, 150-day, and 200-day simple moving averages.
Moving Average Alignment: 50-day MA is above the 150-day MA, which is above the 200-day MA.
Uptrending 200-day MA: The 200-day MA is demonstrating an upward trend over the specified period.
30% Above 52-Week Low: Current price is at least 30% higher than the 52-week low.
Within 25% of 52-Week High: Current price is no more than 25% below the 52-week high.
Important Notes:
This indicator does not directly plot lines for conditions 4 and 5 (52-week high/low comparisons). Consider incorporating these into your chart in some way for full technical analysis in line with the Minervini method.
For additional depth, study Mark Minervini's books to fully understand the context and strategies built around these criteria.
How to Use:
Add the "Kshitij Malve - Minervini Trend Criteria" indicator to a stock chart.
Observe the placement of colored dots below the chart. A series of green dots suggests the stock is within Minervini's Stage 2 criteria.
Look for the purple up-arrow signal for confirmation that all conditions are met.
Customize alerts if you would like real-time signals of potential Stage 2 uptrends.
FlexiMA Variance Tracker - Strategy [presentTrading]█ Introduction and How It Is Different
The FlexiMA Variance Tracker by PresentTrading introduces a novel approach to technical trading strategies. Unlike traditional methods, it calculates deviations between a chosen indicator source (such as price or average) and a moving average with a variable length. This flexibility is achieved through a unique combination of a starting factor and an increment factor, allowing the moving average to adapt dynamically within a specified range. This strategy provides a more responsive and nuanced view of market trends, setting it apart from standard trading methodologies.
BTC 8h L/S
Local
█ Strategy, How It Works: Detailed Explanation
The FlexiMA Variance Tracker, developed by PresentTrading, stands at the forefront of trading strategies, distinguished by its adaptive and multifaceted approach to market analysis. This strategy intricately weaves various technical elements to construct a comprehensive trading logic. Here's an in-depth professional breakdown:
🔶Foundation on Variable-Length Moving Averages:
Central to this strategy is the concept of variable-length Moving Averages (MAs). Unlike traditional MAs with a fixed period, this strategy dynamically adjusts the length of the MA based on a starting factor and an incremental factor. This approach allows the strategy to adapt to market volatility and trend strength more effectively.
Each MA iteration offers a distinct temporal perspective, capturing short-term price movements to long-term trends. This aggregation of various time frames provides a richer and more nuanced market analysis, essential for making informed trading decisions.
🔶Deviation Analysis and Normalization:
The strategy calculates deviations of the price (or the chosen indicator source) from each of these MAs. These deviations are pivotal in identifying the immediate market direction relative to the average trend captured by each MA.
To standardize these deviations for comparability, they undergo a normalization process. The choice of normalization method (Max-Min or Absolute Sum) can significantly influence the interpretation of market conditions, offering distinct insights into price movements and trend strength.
🔹Normalization: Absolute Sum
🔶Composite Oscillator Construction:
A composite oscillator is derived from the median of these normalized deviations. The median serves as a balanced and robust central trend indicator, minimizing the impact of outliers and market noise.
Additionally, the standard deviation of these deviations is computed, providing a measure of market volatility. This volatility indicator is crucial for assessing market risk and can guide traders in setting appropriate stop-loss and take-profit levels.
🔶Integration with SuperTrend Indicator:
The FlexiMA strategy integrates the SuperTrend indicator, renowned for its effectiveness in identifying trend direction and reversals. The SuperTrend's incorporation enhances the strategy's ability to filter out false signals and confirm genuine market trends.
* The SuperTrend Toolkit is made by @QuantiLuxe
This combination of the variable-length MA oscillator with the SuperTrend indicator forms a potent duo, offering traders a dual-confirmation mechanism for trade signals.
🔹Supertrend's incorporation
🔶Strategic Trade Signal Generation:
Trade signals are generated when there is a confluence between the composite oscillator and the SuperTrend indicator. For example, a long position signal might be considered when the oscillator suggests an uptrend, and the SuperTrend flips to bullish.
The strategy's parameters are fully customizable, enabling traders to tailor the signal generation process to their specific trading style, risk tolerance, and market conditions.
█ Usage
To effectively employ the FlexiMA Variance Tracker strategy:
Traders should set their desired trade direction and fine-tune the starting and increment factors according to their market analysis and risk tolerance.
Indicator Length: 5
Indicator Length: 40
The strategy is suitable for a wide range of markets and can be adapted to different time frames, making it a versatile tool for various trading scenarios.
█ Default Settings Impact on Performance: FlexiMA Variance Tracker
1. Trade Direction (Configurable: Long, Short, Both): Determines trade types. 'Long' for buying, 'Short' for selling, 'Both' adapts to market trends.
2. Indicator Source: HLC3: Balances market sentiment by considering high, low, and close, providing comprehensive period analysis.
4. Indicator Length (Default: 10): Baseline for moving averages. Shorter lengths increase responsiveness but add noise, while longer lengths favor trends.
5. Starting and Increment Factor (Default: 1.0): Adjusts MA lengths range. Higher values capture broad market dynamics, lower values focus analysis.
6. Normalization Method (Options: None, Max-Min, Absolute Sum): Standardizes deviations. 'None' for raw deviations, 'Max-Min' for relative scaling, 'Absolute Sum' emphasizes relative strength.
7. SuperTrend Settings (ATR Length: 10, Multiplier: 15.0): Influences indicator sensitivity. Short ATR or high multiplier for short-term, long ATR or low multiplier for long-term trends.
8. Additional Settings (Mesh Style, Color Customization): Enhances visual clarity. Mesh style for detailed deviation view, colors for quick market condition identification.
Heuristic Bg Color Hodl/swing/scalp [Ox_kali]The "Heuristic BG Color Hodl/Swing/Scalp " is a multi-faceted technical indicator designed to aid traders across varying investment strategies such as long-term holding (Hodl), swing trading, and scalping. Optimized to run on a range of timeframes from seconds to months. Built upon an intricate layering of moving averages, market oscillators. The indicator displays a color range from light green to deep red, based on market conditions. This tool aims to provide an analytical edge by visualizing market conditions in a straightforward manner. Incorporating both trend-following and oscillatory components both trend-following and oscillating components to furnish a more rounded view of the market. Note that this indicator is best used in conjunction with other forms of market analysis and should not be solely relied upon for making trading decisions.
Key Features:
Multiple Moving Averages: Utilizes Fast and Slow MAs to identify trend momentum.
Modified RSI and MFI: Incorporates RSI and MFI to gauge overbought and oversold conditions.
Stoch RSI Indicator: Used to provide additional confirmation for trading signals.
Dynamic Background Color: Highlights potential Buy and Sell zones using background color for easier visual interpretation.
Alert Conditions: Trigger customizable alerts for Buy and Sell zones.
Functionality Analysis:
The script allows you to select the type and period for Fast and Slow moving averages. It uses these MAs to calculate an underlying trend momentum, further refined by a user-defined MA.
The RSI and MFI are used to identify overbought and oversold conditions calculated and smoothed over a user-defined period. The Stoch RSI gives an additional layer of confirmation, allowing traders to identify more reliable trading signals.
The script's main visual feature is the background color, which changes based on potential Buy and Sell zones. It provides two layers for each, enabling traders to understand the strength of the signal. Notably, the indicator is particularly optimized for identifying Buy Zones and is more functional for detecting Sell Zones when applied to larger timeframes.
Trading Application:
The "Heuristic BG Color Hodl/Swing/Scalp" indicator can adapt to various trading styles, from long-term investment to short-term trading. When the background turns green, it signifies a potential Buy Zone, ideal for entering long positions. Conversely, a red background indicates a Sell Zone, suggesting it may be a good time to exit positions or go short.
Traders can also utilize the alert conditions set within the script to receive real-time notifications, making it easier to capitalize on potential market opportunities.
Please note that the "Heuristic BG Color Hodl/Swing/Scalp" by Ox_kali is intended for educational purposes only and does not constitute financial advice. This indicator is not a guarantee of future market performance and should be used alongside proper risk management strategies. Ensure you fully understand the methodology and limitations of this indicator before making any trading decisions. Past performance is not indicative of future results.
Machine Learning Momentum Index (MLMI) [Zeiierman]█ Overview
The Machine Learning Momentum Index (MLMI) represents the next step in oscillator trading. By blending traditional momentum analysis with machine learning, MLMI delivers a potent and dynamic tool that aligns with the complexities of modern financial landscapes. Offering traders an adaptive way to understand and act on market momentum and trends, this oscillator provides real-time insights into market momentum and prevailing trends.
█ How It Works:
Momentum Analysis: MLMI employs a dual-layer analysis, utilizing quick and slow weighted moving averages (WMA) of the Relative Strength Index (RSI) to gauge the market's momentum and direction.
Machine Learning Integration: Through the k-Nearest Neighbors (k-NN) algorithm, MLMI intelligently examines historical data to make more accurate momentum predictions, adapting to the intricate patterns of the market.
MLMI's precise calculation involves:
Weighted Moving Averages: Calculations of quick (5-period) and slow (20-period) WMAs of the RSI to track short-term and long-term momentum.
k-Nearest Neighbors Algorithm: Distances between current parameters and previous data are measured, and the nearest neighbors are used for predictive modeling.
Trend Analysis: Recognition of prevailing trends through the relationship between quick and slow-moving averages.
█ How to use
The Machine Learning Momentum Index (MLMI) can be utilized in much the same way as traditional trend and momentum oscillators, providing key insights into market direction and strength. What sets MLMI apart is its integration of artificial intelligence, allowing it to adapt dynamically to market changes and offer a more nuanced and responsive analysis.
Identifying Trend Direction and Strength: The MLMI serves as a tool to recognize market trends, signaling whether the momentum is upward or downward. It also provides insights into the intensity of the momentum, helping traders understand both the direction and strength of prevailing market trends.
Identifying Consolidation Areas: When the MLMI Prediction line and the WMA of the MLMI Prediction line become flat/oscillate around the mid-level, it's a strong sign that the market is in a consolidation phase. This insight from the MLMI allows traders to recognize periods of market indecision.
Recognizing Overbought or Oversold Conditions: By identifying levels where the market may be overbought or oversold, MLMI offers insights into potential price corrections or reversals.
█ Settings
Prediction Data (k)
This parameter controls the number of neighbors to consider while making a prediction using the k-Nearest Neighbors (k-NN) algorithm. By modifying the value of k, you can change how sensitive the prediction is to local fluctuations in the data.
A smaller value of k will make the prediction more sensitive to local variations and can lead to a more erratic prediction line.
A larger value of k will consider more neighbors, thus making the prediction more stable but potentially less responsive to sudden changes.
Trend length
This parameter controls the length of the trend used in computing the momentum. This length refers to the number of periods over which the momentum is calculated, affecting how quickly the indicator reacts to changes in the underlying price movements.
A shorter trend length (smaller momentumWindow) will make the indicator more responsive to short-term price changes, potentially generating more signals but at the risk of more false alarms.
A longer trend length (larger momentumWindow) will make the indicator smoother and less responsive to short-term noise, but it may lag in reacting to significant price changes.
Please note that the Machine Learning Momentum Index (MLMI) might not be effective on higher timeframes, such as daily or above. This limitation arises because there may not be enough data at these timeframes to provide accurate momentum and trend analysis. To overcome this challenge and make the most of what MLMI has to offer, it's recommended to use the indicator on lower timeframes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Hull Suite Oscillator - Normalized | IkkeOmarThis script is based off the Hull Suite by @InSilico.
I made this script to provide and calculate the Hull Moving Average (HMA) based on the chosen variation (HMA, TMA, or EMA) and length to then normalize the HMA values to a range of 0 to 100. The normalized values are further smoothed using an exponential moving average (EMA).
The smoothed oscillator is plotted as a line, where values above 80 are colored red, values below 20 are colored green, and values between 20 and 80 are colored blue. Additionally, there are horizontal dashed lines at the levels of 20 and 80 to serve as reference points.
Explanation for the code:
The script uses the close price of the asset as the source for calculations. The modeSwitch parameter allows selecting the type of Hull variation: Hma, Thma, or Ehma. The length parameter determines the calculation period for the Hull moving averages. The lengthMult parameter is used to adjust the length for higher timeframes. The oscSmooth parameter determines the lookback period for smoothing the oscillator.
There are three functions defined for calculating different types of Hull moving averages: HMA, EHMA, and THMA. These functions take the source and length as inputs and return the corresponding Hull moving average.
The Mode function acts as a switch and selects the appropriate Hull variation based on the modeSwitch parameter. It returns the chosen Hull moving average.
The script calculates the Hull moving averages using the selected mode, source, and length. The main Hull moving average is stored in the _hull variable, and aliases are created for the main Hull moving average (HULL), the main Hull value (MHULL), and the secondary Hull value (SHULL).
To create the normalized oscillator values, the script finds the highest and lowest values of the Hull moving average within the specified length. It then normalizes the Hull values to a range of 0 to 100 using a formula. This normalized oscillator represents the strength of the trend.
To smooth out the oscillator values, an exponential moving average is applied using the oscSmooth parameter.
The smoothed oscillator is plotted as a line chart. The line color is determined based on the oscillator value using conditional statements. If the oscillator value is above or equal to 80, the line color is set to red. If it is below or equal to 20, the color is green. Otherwise, it is blue. The linewidth is set to 2.
Additionally, two horizontal reference lines are plotted at levels 20 and 80 for visual reference. They are displayed in gray and dashed style.
T3 Super GuppyA Tillson T3 moving average implemented variation of the CM Super Guppy indicator by @FritzMurphy
The T3 moving average was developed by Tom Tilson which combines multiple EMAs into a single moving average. it is smoother and more responsive compared to traditional moving averages. The disadvantage is that it can overshoot price.
█ Description
T3 Super Guppy consists of 20 T3 moving averages:
• 7 fast T3 MAs
• 13 slow T3 MAs
Visuals:
• Compact view available for chart minimalists
• In compact view only 10 of the fastest T3 moving averages will be displayed
• Compact view will not affect how the colour scales with trend movement
• Ribbon transparency will automatically scale based on the display mode chosen
Colour Gradient
• The more T3 MAs that cross above or below their slower counterparts will result in how deep the chosen upTrend(Blue) or downTrend(Red) colour is displayed
• Helps to spot weakening trends or reversal signals when indicator colour starts converging into the opposite colour
• Single colour mode is available if you find the colour gradient distracting
█ Credits
@ChrisMoody original guppy idea:
@FritzMurphy super guppy format:
█ Examples
compact view:
full view:
3 EMA/SMA + Colored Candles[C2Trends]// Indicator Features:
// 1) 3 Exponential Moving Averages and 3 Simple Moving Averages.
// 2) Additional EMA input for colored candles(EMA is hidden from chart, input used for coloring of candles only)
// 3) Turn colored candles on/off from main input tab of indicator settings.
// 4) Turn SMA's and EMA's on/off from main input tab of indicator settings.
// 5) Select single color or 2 color EMA and SMA lines from main input tab of indicator settings.
// Indicator Notes:
// 1) 'Candle EMA' input is the trend lookback period for the price candle colors. When price is above desired Candle EMA, price candles will color green. When price is below the Candle EMA, price candles will color fuchsia.
// 2) If you are using another indicator that colors the price candles it may overlap the candle colors applied by this indicator. Trying hiding or removing other indicators to troubleshoot if having candle color issues.
// 3) Using 2-color price moving averages: when price is above an average the average will color green, when price is below an average the average will color fuchsia.
Half Causal EstimatorOverview
The Half Causal Estimator is a specialized filtering method that provides responsive averages of market variables (volume, true range, or price change) with significantly reduced time delay compared to traditional moving averages. It employs a hybrid approach that leverages both historical data and time-of-day patterns to create a timely representation of market activity while maintaining smooth output.
Core Concept
Traditional moving averages suffer from time lag, which can delay signals and reduce their effectiveness for real-time decision making. The Half Causal Estimator addresses this limitation by using a non-causal filtering method that incorporates recent historical data (the causal component) alongside expected future behavior based on time-of-day patterns (the non-causal component).
This dual approach allows the filter to respond more quickly to changing market conditions while maintaining smoothness. The name "Half Causal" refers to this hybrid methodology—half of the data window comes from actual historical observations, while the other half is derived from time-of-day patterns observed over multiple days. By incorporating these "future" values from past patterns, the estimator can reduce the inherent lag present in traditional moving averages.
How It Works
The indicator operates through several coordinated steps. First, it stores and organizes market data by specific times of day (minutes/hours). Then it builds a profile of typical behavior for each time period. For calculations, it creates a filtering window where half consists of recent actual data and half consists of expected future values based on historical time-of-day patterns. Finally, it applies a kernel-based smoothing function to weight the values in this composite window.
This approach is particularly effective because market variables like volume, true range, and price changes tend to follow recognizable intraday patterns (they are positive values without DC components). By leveraging these patterns, the indicator doesn't try to predict future values in the traditional sense, but rather incorporates the average historical behavior at those future times into the current estimate.
The benefit of using this "average future data" approach is that it counteracts the lag inherent in traditional moving averages. In a standard moving average, recent price action is underweighted because older data points hold equal influence. By incorporating time-of-day averages for future periods, the Half Causal Estimator essentially shifts the center of the filter window closer to the current bar, resulting in more timely outputs while maintaining smoothing benefits.
Understanding Kernel Smoothing
At the heart of the Half Causal Estimator is kernel smoothing, a statistical technique that creates weighted averages where points closer to the center receive higher weights. This approach offers several advantages over simple moving averages. Unlike simple moving averages that weight all points equally, kernel smoothing applies a mathematically defined weight distribution. The weighting function helps minimize the impact of outliers and random fluctuations. Additionally, by adjusting the kernel width parameter, users can fine-tune the balance between responsiveness and smoothness.
The indicator supports three kernel types. The Gaussian kernel uses a bell-shaped distribution that weights central points heavily while still considering distant points. The Epanechnikov kernel employs a parabolic function that provides efficient noise reduction with a finite support range. The Triangular kernel applies a linear weighting that decreases uniformly from center to edges. These kernel functions provide the mathematical foundation for how the filter processes the combined window of past and "future" data points.
Applicable Data Sources
The indicator can be applied to three different data sources: volume (the trading volume of the security), true range (expressed as a percentage, measuring volatility), and change (the absolute percentage change from one closing price to the next).
Each of these variables shares the characteristic of being consistently positive and exhibiting cyclical intraday patterns, making them ideal candidates for this filtering approach.
Practical Applications
The Half Causal Estimator excels in scenarios where timely information is crucial. It helps in identifying volume climaxes or diminishing volume trends earlier than conventional indicators. It can detect changes in volatility patterns with reduced lag. The indicator is also useful for recognizing shifts in price momentum before they become obvious in price action, and providing smoother data for algorithmic trading systems that require reduced noise without sacrificing timeliness.
When volatility or volume spikes occur, conventional moving averages typically lag behind, potentially causing missed opportunities or delayed responses. The Half Causal Estimator produces signals that align more closely with actual market turns.
Technical Implementation
The implementation of the Half Causal Estimator involves several technical components working together. Data collection and organization is the first step—the indicator maintains a data structure that organizes market data by specific times of day. This creates a historical record of how volume, true range, or price change typically behaves at each minute/hour of the trading day.
For each calculation, the indicator constructs a composite window consisting of recent actual data points from the current session (the causal half) and historical averages for upcoming time periods from previous sessions (the non-causal half). The selected kernel function is then applied to this composite window, creating a weighted average where points closer to the center receive higher weights according to the mathematical properties of the chosen kernel. Finally, the kernel weights are normalized to ensure the output maintains proper scaling regardless of the kernel type or width parameter.
This framework enables the indicator to leverage the predictable time-of-day components in market data without trying to predict specific future values. Instead, it uses average historical patterns to reduce lag while maintaining the statistical benefits of smoothing techniques.
Configuration Options
The indicator provides several customization options. The data period setting determines the number of days of observations to store (0 uses all available data). Filter length controls the number of historical data points for the filter (total window size is length × 2 - 1). Filter width adjusts the width of the kernel function. Users can also select between Gaussian, Epanechnikov, and Triangular kernel functions, and customize visual settings such as colors and line width.
These parameters allow for fine-tuning the balance between responsiveness and smoothness based on individual trading preferences and the specific characteristics of the traded instrument.
Limitations
The indicator requires minute-based intraday timeframes, securities with volume data (when using volume as the source), and sufficient historical data to establish time-of-day patterns.
Conclusion
The Half Causal Estimator represents an innovative approach to technical analysis that addresses one of the fundamental limitations of traditional indicators: time lag. By incorporating time-of-day patterns into its calculations, it provides a more timely representation of market variables while maintaining the noise-reduction benefits of smoothing. This makes it a valuable tool for traders who need to make decisions based on real-time information about volume, volatility, or price changes.
Uptrick: Time Based ReversionIntroduction
The Uptrick: Time Based Reversion indicator is designed to provide a comprehensive view of market momentum and potential trend shifts by combining multiple moving averages, a streak-based trend analysis system, and adaptive color visualization. It helps traders identify strong trends, spot potential reversals, and make more informed trading decisions.
Purpose
The primary goal of this indicator is to assist traders in distinguishing between sustained market movements and short-lived fluctuations. By evaluating how price behaves relative to its moving averages, and by measuring consecutive streaks above or below these averages, the indicator highlights areas where trends are likely to continue or lose momentum.
Overview
Uptrick: Time Based Reversion calculates one or more moving averages of price data and then tracks the number of consecutive bars (streaks) above or below these averages. This streak-based detection provides insight into whether a trend is gaining strength or nearing a potential reversal point. The indicator offers:
• Multiple moving average types (SMA, EMA, WMA)
• Optional second and third moving average layers for additional smoothing of first moving average
• A streak detection system to quantify trend intensity
• A dynamic color scheme that changes with streak strength
• Optional buy and sell signals for potential trade entries and exits
• A ribbon mode that applies moving averages to Open, High, Low, and Close prices for a more detailed visualization of overall trend alignment
Originality and Uniqueness
Unlike traditional moving average indicators, Uptrick: Time Based Reversion incorporates a streak measurement system to detect trend strength. This approach helps clarify whether a price movement is merely a quick fluctuation or part of a longer-lasting trend. Additionally, the optional ribbon mode extends this logic to Open, High, Low, and Close prices, creating a layered and intuitive visualization that shows complete trend alignment.
Inputs and Features
1. Enable Ribbon Mode
This input lets you activate or deactivate the ribbon display of multiple moving averages. When enabled, the script plots moving averages for the Open, High, Low, and Close prices and uses color fills to show whether these four data points are collectively above or below their respective moving averages.
2. Color Scheme Selection
Users can choose from several predefined color schemes, such as Default, Emerald, Crimson, Sapphire, Gold, Purple, Teal, Orange, Gray, Lime, or Aqua. Each scheme assigns distinct bullish, bearish and neutral colors..
3. Show Buy/Sell Signals
The indicator can display buy or sell signals based on its streak analysis logic. These signals appear as markers on the chart, indicating a “Safe Uptrend” (buy) or “Safe Downtrend” (sell).
4. Moving Average Types and Lengths
• First MA Type and Length: Choose SMA, EMA, or WMA along with a customizable period.
• Second and Third MA Types and Lengths: You can optionally stack additional moving averages for further smoothing, each with its own customizable type and period.
5. Streak Threshold Multiplier
This numeric input determines how strong a streak must be before the script considers it a “safe” trend. A higher multiplier requires a longer or more intense streak for a buy or sell signal.
6. Dynamic Transparency Calculation
The color intensity adapts to the streak’s strength. Longer streaks increase the transparency of the opposing color, making the current dominant color stand out. This feature ensures that a vigorous uptrend or downtrend is visually distinct from short-lived or weaker moves.
7. Ribbon Moving Averages
In ribbon mode, the script calculates moving averages for the Open, High, Low, and Close prices. Each of these is optionally smoothed again if the second and/or third moving average layers are active. The final result is a ribbon of moving averages that helps confirm whether the market is uniformly aligned above or below these key reference points.
Calculation Methodology
1. Initial Moving Average
The script calculates the first moving average (SMA, EMA, or WMA) of the closing price over a user-defined period.
2. Optional Secondary and Tertiary Averages
If selected, the script then applies a second and/or third smoothing step. Each of these steps can be a different type of moving average (SMA, EMA, or WMA) with its own period length.
3. Streak Detection
The indicator counts consecutive bars above or below the smoothed moving average. A running total (streakUp or streakDown) increments with every bar that remains above or below that average.
4. Reversion Intensity
The script compares the current streak value to its own average (calculated over the final chosen period). This ratio determines whether the streak is nearing a likely reversion or is strong enough to continue.
5. Color Assignment and Signals
The indicator calculates color transparency based on streak intensity. Buy and sell signals appear when the streak meets or exceeds the threshold multiplier, indicating a safe uptrend or downtrend.
Color Schemes and Visualization
This indicator offers multiple predefined color sets. Each scheme specifies a unique bullish color, bearish color and neutral color. The script automatically varies transparency to highlight strong trends and fade weaker ones, making it visually clear when a trend is intensifying or losing momentum.
Smoothing Techniques
By allowing up to three layers of moving average smoothing, the indicator accommodates different trading styles. A single layer provides faster reactions to market changes, while more layers reduce noise at the cost of slower responsiveness. Traders can choose the right balance between responsiveness and stability for their strategy, whether it is short-term scalping or long-term trend following.
Why It Combines Specific Smoothing Techniques
The Uptrick: Time Based Reversion indicator strategically combines specific smoothing techniques—SMA, EMA, and WMA—to leverage their complementary strengths. The SMA provides stable and consistent trend identification by equally weighting all data points, while the EMA emphasizes recent price movements, allowing quicker responses to market changes. WMA enhances sensitivity to recent price shifts, which helps in detecting subtle momentum changes early. By integrating these methods in layers, the indicator effectively balances responsiveness with stability, helping traders clearly identify genuine trend changes while filtering out short-term noise and false signals.
Ribbon Mode
If Open, High, Low, and Close prices remain above or below their respective moving averages consistently, the script colors the bars fully bullish or bearish. When the data points are mixed, a neutral color is applied. This mode provides a thorough perspective on whether the entire price range is aligned in one direction or showing conflicting signals.
Summary
Uptrick: Time Based Reversion combines multiple moving averages, streak detection, and dynamic color adjustments to help traders identify significant trends and potential reversal areas. Its flexibility allows it to be used either in a simpler form, with one moving average and streak analysis, or in a more advanced configuration with ribbon mode that charts multiple smoothed averages for a deeper understanding of price alignment. By adapting color intensities based on streak strength and providing optional buy/sell signals, this indicator delivers a clear and flexible tool suited to various trading strategies.
Disclaimer
This indicator is designed as an analysis aid and does not guarantee profitable trades. Past performance does not indicate future success, and market conditions can change unexpectedly. Users are advised to employ proper risk management and thoroughly evaluate trades before taking positions. Use this indicator as part of a broader strategy, not as a sole decision-making tool.
Trend ThermometerThis script, tailored for trading, allows traders to visualize trend penetration across multiple timeframes with a color-coded moving average sequence. The Trend Thermometer helps identify strong, sustained trends by displaying a progression of colors that indicate the trend's intensity across a series of moving averages, from shorter to longer timeframes.
Key Features:
Color Gradients(41 colors) for Trend Strength: The colors reflect the strength of the trend at each moving average level. Darker greens signify strong upward trends, while darker reds indicate strong downward trends. Lighter colors or mixed gradients suggest a weaker or transitional trend.
Multi-Timeframe Penetration: By observing color transitions across all moving averages, traders can see how trends penetrate from shorter to longer timeframes, providing insight into the trend's depth and potential longevity.
Slightly Exponential Distribution of Moving Averages: The script uses a series of moving averages that are spaced with a slight exponential distribution. This approach allows for closer analysis in the short-term ranges while maintaining visibility across longer timeframes, providing a balanced view of the trend’s strength across intraday periods.
Sequential Analysis: With the progressively spaced moving averages, traders can easily track how trends develop from short-term to long-term. Unified color shifts across these averages confirm the trend direction, while divergence (where shorter and longer averages display opposing trends) can signal consolidation or potential trend weakening.
Example Interpretation:
Bullish Penetration: When shorter moving averages (e.g., 8, 16, 24) turn green, and this color shift continues through medium to longer moving averages (up to 496), it indicates a strong, deepening bullish trend across intraday timeframes.
Bearish Penetration: If shorter averages turn red and the shift gradually extends to longer averages, this suggests a bearish trend that is gaining traction across multiple timeframes.
How to Use:
For intraday trading, watch for a consistent color shift across shorter to longer moving averages to confirm trend direction. A unified shift in color across at least half of the moving averages signals a robust trend, providing potential entry or exit points with greater accuracy.
This tool enhances intraday decision-making by offering a clear view of trend strength and penetration across slightly exponentially distributed moving averages, allowing traders to make informed choices based on the trend’s depth, consistency, and momentum across timeframes.
2 days ago
Release Notes
This script, tailored for trading, allows traders to visualize trend penetration across multiple timeframes with a color-coded moving average sequence. The Trend Thermometer helps identify strong, sustained trends by displaying a progression of colors that indicate the trend's intensity across a series of moving averages, from shorter to longer timeframes.
Key Features:
Color Gradients(41 colors) for Trend Strength: The colors reflect the strength of the trend at each moving average level. Darker greens signify strong upward trends, while darker reds indicate strong downward trends. Lighter colors or mixed gradients suggest a weaker or transitional trend.
Multi-Timeframe Penetration: By observing color transitions across all moving averages, traders can see how trends penetrate from shorter to longer timeframes, providing insight into the trend's depth and potential longevity.
Slightly Exponential Distribution of Moving Averages: The script uses a series of moving averages that are spaced with a slight exponential distribution. This approach allows for closer analysis in the short-term ranges while maintaining visibility across longer timeframes, providing a balanced view of the trend’s strength across intraday periods.
Sequential Analysis: With the progressively spaced moving averages, traders can easily track how trends develop from short-term to long-term. Unified color shifts across these averages confirm the trend direction, while divergence (where shorter and longer averages display opposing trends) can signal consolidation or potential trend weakening.
Example Interpretation:
Bullish Penetration: When shorter moving averages (e.g., 8, 16, 24) turn green, and this color shift continues through medium to longer moving averages (up to 496), it indicates a strong, deepening bullish trend across intraday timeframes.
Bearish Penetration: If shorter averages turn red and the shift gradually extends to longer averages, this suggests a bearish trend that is gaining traction across multiple timeframes.
How to Use:
For intraday trading, watch for a consistent color shift across shorter to longer moving averages to confirm trend direction. A unified shift in color across at least half of the moving averages signals a robust trend, providing potential entry or exit points with greater accuracy.
This tool enhances intraday decision-making by offering a clear view of trend strength and penetration across slightly exponentially distributed moving averages, allowing traders to make informed choices based on the trend’s depth, consistency, and momentum across timeframes.
(Envelopes)USS Enterprise1. This indicator is created for those who still believe in the functionality of moving averages. Indicator consists of several envelopes of moving averages and two separate averages. The selection of these moving averages is linked to Fibonacci theories and calculations.
2. The indicator shows moving averages (envelopes) of all market participants. From the smallest to the giants.
3. It should be noted that all averages are mainly calibrated to a 15-minute time frame. But I'm not saying that you can't use it on any TF. Because market is fractal.
Groups:
1. (YELLOW ENVELOPES) The first group are scalpers and big traders. Yellow envelope! This is the largest group of traders, but with the smallest capital on the market. Why did I choose this envelope? To show who is in control of the market. The average duration of holding the price of this envelope is 12-16 hours (in trend phase) and therefore it is suitable for intra-day trading. If the price closes below this envelope, we know that their strength was no longer sufficient. However, as long as these two yellow curves do not cross each other, we consider this group of traders to be still dominant/active and their weakening was only partial, for example, due to a pullback, or due to manipulation of the price of stronger players.
2. (LIGHT BLUE ENVELOPE) When I mentioned pullback. Understand it as the return of the price in the trend. But who is capable of these pullbacks in the trend? Our second group of traders. Institutions. (Light blue color). Only their amount of money can cause the price to return to their point of interest and that is the light blue envelope. The average ability to hold the trend of the institutions is something around 1-2 days. If the price closes with a slow decline/rise below this/above this envelope, we can expect that their strength is still large enough. However, if there are movements that seem to cut through this envelope, it is the first indication that the institutions are losing strength. If there is a crossover of any yellow average across both institutional ones, we can expect a much bigger pullback in the trend. This pullback is then again mainly under the control of the institutions (rejections from the light blue envelope.) But where can this pullback go? Another market participant will tell us that!
3. (DARK BLUE ENVELOPE) Market makers are another participant. Their task is to maintain balance on the market. This means that the market does not only go up or only down. That's what the envelope of market makers is for. This envelope is considered a trend defender. What makes it special. It can hold a trend even for days. We can consider the return to this envelope as a supply and demand strategy. In the trend, the price will come back here as a pullback and then rocket back into the original trend. I'll tell you what you probably guessed, yes, we are moving here at the EMA200 level. So if the institutional (light blue) traders lose their strength, believe me that the envelope of the market makers is a very likely stop! When does a trend change occur and not a pullback? If there is a crossing of the light blue average with the entire envelope of market makers. The next test from the other side of this envelope confirms the trend change.
4. Let's skip the black envelope for the moment.
5. (PURPLE ENVELOPE) Let's explain the purple envelope. It is the envelope of market makers and especially hedge funds. What do you think when the price closes below the EMA200 (originally a bull trend) and even tests it below? "We have a trend change now we definitely have a down trend!!!" Uhm. NOPE :D. That's their job. To show you what they want you to believe. What does this result in? Filling their large orders, which eventually means that you were caught and liquidated with your positions. By testing, you will find out how many times you thought there was a trend change, but after you see how the price reacts from the purple envelope, you will understand that until now you did not know at all when a general trend change occurs. When we talk about a trend change in the long term , occurs when the EMA200 (dark blue envelope) crosses this purple envelope. This purple envelope is able to keep the price trending for an average of 3 weeks.
Don't get caught that the trend change is when the price closes below the EMA200.Or "golden cross"
6. (BLACK ENVELOPE) Did we miss something though? So let's go back to the meaning of the black envelope. When you take a good look at the trend and notice all the envelopes lined up nicely and focus on the dark blue envelope and the purple envelope. Don't you feel like you're seeing Fibonacci's return? Or as if you see the price in the premium zone?.78%-88%. Yes, it's exactly this envelope. Sometimes market makers and funds are satisfied with the price in this envelope and are willing to continue buying or selling from this envelope. However, keep in mind, this can be a stop before testing the purple envelope - mostly the range is formed in this black envelope. Expect in such a case that they will test the purple envelope. Otherwise, take this envelope as a sign of a premium zone.
7. (ORANGE,TEAL and RED MA) The Orange,Teal and Red averages show a pure bank level. That is, our mentioned giants on the market. You will see for yourself on the market with what accuracy the banks return to these averages. You will see for yourself that trends really change only at these averages. You must have told yourself several times why and how patterns that resemble a letter are created in the market V or the letter A. Congratulations! Thanks to my indicator, you already know today! Because of these bank averages!!!
I wish you the best of luck with this indicator and hopefully it helps as many people as possible understand trends and how important simple lines can be! Which and how many envelopes or moving averages you will use is entirely up to you!
Warning: Everything published in this description or the functionality of this indicator serves only as educational content! Only YOU are responsible for all profits and losses!
Jobinsabu014This Pine Script code is for an advanced trading indicator that displays enhanced moving averages with buy and sell labels, trend probability, and support/resistance levels. Here’s a detailed description of its components and functionality:
### Description:
1. **Indicator Initialization**:
- The indicator is named "Enhanced Moving Averages with Buy/Sell Labels and Trend Probability" and is set to overlay on the chart.
2. **Input Parameters**:
- **Moving Averages**: Four different moving averages (short and long periods for default and enhanced) with customizable periods.
- **Probability Threshold**: Determines the threshold for trend probability.
- **Support/Resistance Lookback**: Number of bars to look back for calculating support and resistance levels.
- **Signals Valid From**: Timestamp from which the signals are considered valid.
3. **Moving Averages Calculation**:
- **Default Moving Averages**: Calculated using simple moving averages (SMA) for the specified periods.
- **Enhanced Moving Averages**: Calculated using SMAs for different specified periods.
4. **Plotting Moving Averages**:
- Plots the default and enhanced moving averages with different colors for distinction.
5. **Crossover Detection**:
- Detects when the short moving average crosses above or below the long moving average for default moving averages.
6. **Buy/Sell Signal Labels**:
- Adds "BUY" and "SELL" labels on the chart when crossovers are detected after the specified valid timestamp.
- Tracks entry prices for buy/sell signals and adds labels when the price moves +100 points.
7. **Trend Detection for Enhanced Indicator**:
- Detects uptrend or downtrend based on the enhanced moving averages.
- Calculates a simple probability of trend based on price movement and EMA.
- Determines buy and sell signals based on trend conditions and volume-based buy/sell pressure.
8. **Plot Buy/Sell Signals for Enhanced Indicator**:
- Plots buy/sell signals based on the enhanced conditions.
9. **Background Color for Trends**:
- Changes the background color to green for uptrend and red for downtrend.
10. **Trend Lines**:
- Draws imaginary trend lines for uptrend and downtrend based on enhanced moving averages.
11. **Support and Resistance Levels**:
- Calculates and plots support and resistance levels using the specified lookback period.
- Stores and plots previous support and resistance levels with dashed lines.
12. **Expected Trend Labels**:
- Adds labels indicating expected uptrend or downtrend based on buy/sell signals.
13. **Alerts**:
- Sets alert conditions for buy and sell signals, triggering alerts when these conditions are met.
14. **Demand and Supply Zones**:
- Draws and extends horizontal lines for demand (support) and supply (resistance) zones.
### Summary:
This script enhances traditional moving average crossovers by adding trend probability calculations, volume-based pressure, and support/resistance levels. It visualizes expected trends and provides comprehensive buy/sell signals with corresponding labels, background color changes, and alerts to help traders make informed decisions.
Moving Average Filters Add-on w/ Expanded Source Types [Loxx]Moving Average Filters Add-on w/ Expanded Source Types is a conglomeration of specialized and traditional moving averages that will be used in most of indicators that I publish moving forward. There are 39 moving averages included in this indicator as well as expanded source types including traditional Heiken Ashi and Better Heiken Ashi candles. You can read about the expanded source types clicking here . About half of these moving averages are closed source on other trading platforms. This indicator serves as a reference point for future public/private, open/closed source indicators that I publish to TradingView. Information about these moving averages was gleaned from various forex and trading forums and platforms as well as TASC publications and other assorted research publications.
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Included moving averages
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA, it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA.
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average (DEMA) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA. It's also considered a leading indicator compared to the EMA, and is best utilized whenever smoothness and speed of reaction to market changes are required.
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA (Simple Moving Average). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA.
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Hull Moving Average - HMA
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points.
IE/2 - Early T3 by Tim Tilson
The IE/2 is a Moving Average that uses Linear Regression slope in its calculation to help with smoothing. It's a worthy Moving Average on it's own, even though it is the precursor and very early version of the famous "T3 Indicator".
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA (Simple Moving Average) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and it's smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA (Least Squares Moving Average)
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA. Although it's similar to the Simple Moving Average, the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track price better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average. The Linear Weighted Moving Average calculates the average by assigning different weight to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrows price.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA.
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average (SMA), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen a an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA (Smoothed Moving Average). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a a Two pole Butterworth filter combined with a 2-bar SMA (Simple Moving Average) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA. They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
The TMA and Sine Weighted Moving Average Filter are almost identical at times.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, it's signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers.
Volume Weighted EMA - VEMA
Utilizing tick volume in MT4 (or real volume in MT5), this EMA will use the Volume reading in its decision to plot its moves. The more Volume it detects on a move, the more authority (confirmation) it has. And this EMA uses those Volume readings to plot its movements.
Studies show that tick volume and real volume have a very strong correlation, so using this filter in MT4 or MT5 produces very similar results and readings.
Zero Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers, as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA, this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
________________________________________________________________
What are Heiken Ashi "better" candles?
The "better formula" was proposed in an article/memo by BNP-Paribas (In Warrants & Zertifikate, No. 8, August 2004 (a monthly German magazine published by BNP Paribas, Frankfurt), there is an article by Sebastian Schmidt about further development (smoothing) of Heikin-Ashi chart.)
They proposed to use the following:
(Open+Close)/2+(((Close-Open)/( High-Low ))*ABS((Close-Open)/2))
instead of using :
haClose = (O+H+L+C)/4
According to that document the HA representation using their proposed formula is better than the traditional formula.
What are traditional Heiken-Ashi candles?
The Heikin-Ashi technique averages price data to create a Japanese candlestick chart that filters out market noise.
Heikin-Ashi charts, developed by Munehisa Homma in the 1700s, share some characteristics with standard candlestick charts but differ based on the values used to create each candle. Instead of using the open, high, low, and close like standard candlestick charts, the Heikin-Ashi technique uses a modified formula based on two-period averages. This gives the chart a smoother appearance, making it easier to spots trends and reversals, but also obscures gaps and some price data.
Expanded generic source types:
Close = close
Open = open
High = high
Low = low
Median = hl2
Typical = hlc3
Weighted = hlcc4
Average = ohlc4
Average Median Body = (open+close)/2
Trend Biased = (see code, too complex to explain here)
Trend Biased (extreme) = (see code, too complex to explain here)
Included:
-Toggle bar color on/off
-Toggle signal line on/off
Signal Hunter Pro - GKDXLSignal Hunter Pro - GKDXL combines four powerful technical indicators with trend strength filtering and volume confirmation to generate reliable BUY/SELL signals. This indicator is perfect for traders who want a systematic approach to market analysis without the noise of conflicting signals.
🔧 Core Features
📈 Multi-Indicator Signal System
Moving Averages: EMA 20, EMA 50, and SMA 200 for trend analysis
Bollinger Bands: Dynamic support/resistance with price momentum detection
RSI: Enhanced RSI logic with smoothing and multi-zone analysis
MACD: Traditional MACD with signal line crossovers and zero-line analysis
🎛️ Advanced Filtering System
ADX Trend Strength Filter: Only signals when trend strength exceeds threshold
Volume Confirmation: Ensures signals occur with adequate volume participation
Multi-Timeframe Logic: Works on any timeframe from 1m to 1D and beyond
🚨 Intelligent Signal Generation
Requires 3 out of 4 indicators to align for signal confirmation
Separate bullish and bearish signal conditions
Real-time signal strength scoring (1/4 to 4/4)
Built-in alert system for automated notifications
⚙️ Customizable Parameters
📊 Technical Settings
Moving Averages: Adjustable EMA and SMA periods
Bollinger Bands: Configurable length and multiplier
RSI: Customizable length, smoothing, and overbought/oversold levels
MACD: Flexible fast, slow, and signal line settings
🎯 Risk Management
Risk Percentage: Set your risk per trade (0.1% to 10%)
Reward Ratio: Configure risk-to-reward ratios (1:1 to 1:5)
ADX Threshold: Control minimum trend strength requirements
🖥️ Display Options
Indicator Visibility: Toggle individual indicators on/off
Information Table: Optional detailed status table (off by default)
Volume Analysis: Real-time volume vs. average comparison
🎨 Visual Elements
📈 Chart Indicators
EMA Lines: Blue (20) and Orange (50) exponential moving averages
SMA 200: Gray long-term trend line
Bollinger Bands: Upper/lower bands with semi-transparent fill
Clean Interface: Minimal visual clutter for clear analysis
📋 Information Table (Optional)
Real-time indicator status with ✓/✗/— symbols
Current signal strength and direction
ADX trend strength measurement
Volume confirmation status
No-signal reasons when conditions aren't met
🔔 Alert System
📢 Three Alert Types
BUY Signal: Triggered when 3+ indicators align bullishly
SELL Signal: Triggered when 3+ indicators align bearishly
General Alert: Any signal detection for broader monitoring
📱 Alert Messages
Clear, actionable alert text
Includes indicator name for easy identification
Compatible with webhook integrations
🎯 How It Works
📊 Signal Logic
Indicator Assessment: Each of the 4 indicators is evaluated as Bullish/Bearish/Neutral
Consensus Building: Counts aligned indicators (minimum 3 required)
Filter Application: Applies trend strength and volume filters
Signal Generation: Generates BUY/SELL when all conditions are met
🔍 Indicator States
Moving Averages: Price position, EMA alignment, and crossovers
Bollinger Bands: Price relative to bands and momentum shifts
RSI: Multi-zone analysis with momentum and crossover detection
MACD: Signal line crossovers and zero-line positioning
🎉 Why Choose Signal Hunter Pro?
✅ Multi-Indicator Confirmation reduces false signals
✅ Trend Strength Filtering improves win rate
✅ Volume Confirmation ensures market participation
✅ Customizable Parameters adapt to any trading style
✅ Clean Visual Design doesn't clutter your charts
✅ Professional Alert System for automated trading
✅ No Repainting - reliable historical signals
✅ Works on All Timeframes from scalping to investing
$TUBR: 7-25-99 Moving Average7, 25, and 99 Period Moving Averages
This indicator plots three moving averages: the 7-period, 25-period, and 99-period Simple Moving Averages (SMA). These moving averages are widely used to smooth out price action and help traders identify trends over different time frames. Let's break down the significance of these specific moving averages from both supply and demand perspectives and a price action perspective.
1. Supply and Demand Perspective:
- 7-period Moving Average (Short-Term) :
The 7-period moving average represents the short-term sentiment in the market. It captures the rapid fluctuations in price and is heavily influenced by recent supply and demand changes. Traders often look to the 7-period SMA for immediate price momentum, with price moving above or below this line signaling short-term strength or weakness.
- Bullish Supply/Demand : When price is above the 7-period SMA, it suggests that buyers are currently in control and demand is higher than supply. Conversely, price falling below this line indicates that supply is overpowering demand, leading to a short-term downtrend.
Is current price > average price in past 7 candles (depending on timeframe)? This will tell you how aggressive buyers are in short term.
- Key Supply/Demand Zones : The 7-period SMA often acts as dynamic support or resistance in a trending market, where traders might use it to enter or exit positions based on how price interacts with this level.
- 25-period Moving Average (Medium-Term) :
The 25-period SMA smooths out more of the noise compared to the 7-period, providing a more stable indication of intermediate trends. This moving average is often used to gauge the market's supply and demand balance over a broader timeframe than the short-term 7-period SMA.
- Supply/Demand Balance : The 25-period SMA reflects the medium-term equilibrium between supply and demand. A crossover between the price and the 25-period SMA may indicate a shift in this balance. When price sustains above the 25-period SMA, it shows that demand is strong enough to maintain an upward trend. Conversely, if the price stays below it, supply is likely exceeding demand.
Is current price > average price in past 25 candles (depending on timeframe)? This will tell you how aggressive buyers are in mid term.
- Momentum Shift : Crossovers between the 7-period and 25-period SMAs can indicate momentum shifts between short-term and medium-term demand. For example, if the 7-period crosses above the 25-period, it often signifies growing short-term demand relative to the medium-term trend, signaling potential buy opportunities. What this crossover means is that if 7MA > 25MA that means in past 7 candles average price is more than past 25 candles.
- 99-period Moving Average (Long-Term):
The 99-period SMA represents the long-term trend and reflects the market's supply and demand over an extended period. This moving average filters out short-term fluctuations and highlights the market's overall trajectory.
- Long-Term Supply/Demand Dynamics : The 99-period SMA is slower to react to changes in supply and demand, providing a more stable view of the market's overall trend. Price staying above this line shows sustained demand dominance, while price consistently staying below reflects ongoing supply pressure.
Is current price > average price in past 99 candles (depending on timeframe)? This will tell you how aggressive buyers are in long term.
- Market Trend Confirmation : When both the 7-period and 25-period SMAs are above the 99-period SMA, it signals a strong bullish trend with demand outweighing supply across all timeframes. If all three SMAs are below the 99-period SMA, it points to a bear market where supply is overpowering demand in both the short and long term.
2. Price Action Perspective :
- 7-period Moving Average (Short-Term Trends):
The 7-period moving average closely tracks price action, making it highly responsive to quick shifts in price. Traders often use it to confirm short-term reversals or continuations in price action. In an uptrend, price typically stays above the 7-period SMA, whereas in a downtrend, price stays below it.
- Short-Term Price Reversals : Crossovers between the price and the 7-period SMA often indicate short-term reversals. When price breaks above the 7-period SMA after staying below it, it suggests a potential bullish reversal. Conversely, a price breakdown below the 7-period SMA could signal a bearish reversal.
- 25-period Moving Average (Medium-Term Trends) :
The 25-period SMA helps identify the medium-term price action trend. It balances short-term volatility and longer-term stability, providing insight into the more persistent trend. Price pullbacks to the 25-period SMA during an uptrend can act as a buying opportunity for trend traders, while pullbacks during a downtrend may offer shorting opportunities.
- Pullback and Continuation: In trending markets, price often retraces to the 25-period SMA before continuing in the direction of the trend. For instance, if the price is in a bullish trend, traders may look for support at the 25-period SMA for potential continuation trades.
- 99-period Moving Average (Long-Term Trend and Market Sentiment ):
The 99-period SMA is the most critical for identifying the overall market trend. Price consistently trading above the 99-period SMA indicates long-term bullish momentum, while price staying below the 99-period SMA suggests bearish sentiment.
- Trend Confirmation : Price action above the 99-period SMA confirms long-term upward momentum, while price action below it confirms a downtrend. The space between the shorter moving averages (7 and 25) and the 99-period SMA gives a sense of the strength or weakness of the trend. Larger gaps between the 7 and 99 SMAs suggest strong bullish momentum, while close proximity indicates consolidation or potential reversals.
- Price Action in Trending Markets : Traders often use the 99-period SMA as a dynamic support/resistance level. In strong trends, price tends to stay on one side of the 99-period SMA for extended periods, with breaks above or below signaling major changes in market sentiment.
Why These Numbers Matter:
7-Period MA : The 7-period moving average is a popular choice among short-term traders who want to capture quick momentum changes. It helps visualize immediate market sentiment and is often used in conjunction with price action to time entries or exits.
- 25-Period MA: The 25-period MA is a key indicator for swing traders. It balances sensitivity and stability, providing a clearer picture of the intermediate trend. It helps traders stay in trades longer by filtering out short-term noise, while still being reactive enough to detect reversals.
- 99-Period MA : The 99-period moving average provides a broad view of the market's direction, filtering out much of the short- and medium-term noise. It is crucial for identifying long-term trends and assessing whether the market is bullish or bearish overall. It acts as a key reference point for longer-term trend followers, helping them stay with the broader market sentiment.
Conclusion:
From a supply and demand perspective, the 7, 25, and 99-period moving averages help traders visualize shifts in the balance between buyers and sellers over different time horizons. The price action interaction with these moving averages provides valuable insight into short-term momentum, intermediate trends, and long-term market sentiment. Using these three MAs together gives a more comprehensive understanding of market conditions, helping traders align their strategies with prevailing trends across various timeframes.
------------- RULE BASED SYSTEM ---------------
Overview of the Rule-Based System:
This system will use the following moving averages:
7-period MA: Represents short-term price action.
25-period MA: Represents medium-term price action.
99-period MA: Represents long-term price action.
1. Trend Identification Rules:
Bullish Trend:
The 7-period MA is above the 25-period MA, and the 25-period MA is above the 99-period MA.
This structure shows that short, medium, and long-term trends are aligned in an upward direction, indicating strong bullish momentum.
Bearish Trend:
The 7-period MA is below the 25-period MA, and the 25-period MA is below the 99-period MA.
This suggests that the market is in a downtrend, with bearish momentum dominating across timeframes.
Neutral/Consolidation:
The 7-period MA and 25-period MA are flat or crossing frequently with the 99-period MA, and they are close to each other.
This indicates a sideways or consolidating market where there’s no strong trend direction.
2. Entry Rules:
Bullish Entry (Buy Signals):
Primary Buy Signal:
The price crosses above the 7-period MA, AND the 7-period MA is above the 25-period MA, AND the 25-period MA is above the 99-period MA.
This indicates the start of a new upward trend, with alignment across the short, medium, and long-term trends.
Pullback Buy Signal (for trend continuation):
The price pulls back to the 25-period MA, and the 7-period MA remains above the 25-period MA.
This indica
tes that the pullback is a temporary correction in an uptrend, and buyers may re-enter the market as price approaches the 25-period MA.
You can further confirm the signal by waiting for price action (e.g., bullish candlestick patterns) at the 25-period MA level.
Breakout Buy Signal:
The price crosses above the 99-period MA, and the 7-period and 25-period MAs are also both above the 99-period MA.
This confirms a strong bullish breakout after consolidation or a long-term downtrend.
Bearish Entry (Sell Signals):
Primary Sell Signal:
The price crosses below the 7-period MA, AND the 7-period MA is below the 25-period MA, AND the 25-period MA is below the 99-period MA.
This indicates the start of a new downtrend with alignment across the short, medium, and long-term trends.
Pullback Sell Signal (for trend continuation):
The price pulls back to the 25-period MA, and the 7-period MA remains below the 25-period MA.
This indicates that the pullback is a temporary retracement in a downtrend, providing an opportunity to sell as price meets resistance at the 25-period MA.
Breakdown Sell Signal:
The price breaks below the 99-period MA, and the 7-period and 25-period MAs are also below the 99-period MA.
This confirms a strong bearish breakdown after consolidation or a long-term uptrend reversal.
3. Exit Rules:
Bullish Exit (for long positions):
Short-Term Exit:
The price closes below the 7-period MA, and the 7-period MA starts crossing below the 25-period MA.
This indicates weakening momentum in the uptrend, suggesting an exit from the long position.
Stop-Loss Trigger:
The price falls below the 99-period MA, signaling the breakdown of the long-term trend.
This can act as a final exit signal to minimize losses if the long-term uptrend is invalidated.
Bearish Exit (for short positions):
Short-Term Exit:
The price closes above the 7-period MA, and the 7-period MA starts crossing above the 25-period MA.
This indicates a potential weakening of the downtrend and signals an exit from the short position.
Stop-Loss Trigger:
The price breaks above the 99-period MA, invalidating the bearish trend.
This signals that the market may be reversing to the upside, and exiting short positions would be prudent.
MAC Investor V3.0 [VK]This indicator combines multiple functionalities to assist traders in making informed decisions. It primarily uses Heikin Ashi candles, Moving Averages, and a Price Action Channel (PAC) to provide signals for entering and exiting trades. Here's a detailed breakdown:
Inputs
MAC Length: Sets the length for the PAC calculation.
Use Heikin Ashi Candles: Option to use Heikin Ashi candles for calculations.
Show Coloured Bars around MAC: Option to color bars based on their relation to the PAC.
Show Long/Short Signals: Options to display long and short signals.
Show MAs? : Option to show moving averages on the chart.
Show MAs Trend at the Bottom?: Option to show trend signals at the bottom of the chart.
MA Lengths: Length settings for three different moving averages.
Change MA Color Based on Direction?: Option to change the color of moving averages based on trend direction.
MA Higher TimeFrame: Allows setting a higher timeframe for moving averages.
Show SL-TP Lines: Option to display Stop Loss and Take Profit lines.
SL/TP Percentages: Set the percentages for Stop Loss and three levels of Take Profit.
Calculations and Features
Heikin Ashi Candles: Calculations are based on Heikin Ashi candle data if selected.
Price Action Channel (PAC): Uses Exponential Moving Averages (EMA) of the high, low, and close to create a channel.
Bar Coloring: Colors the bars based on their position relative to the PAC.
Long and Short Signals: Uses crossovers of the close price and PAC upper/lower bands to generate signals.
Moving Averages (MA): Plots three moving averages and colors them based on their trend direction.
Overall Trend Indicators: Uses triangles at the bottom of the chart to show the overall trend of the MAs.
Stop Loss and Take Profit Levels: Calculates and plots these levels based on user-defined percentages from the entry price.
Alerts: Provides alerts for long and short signals.
Use Cases and How to Use
Identifying Trends: The PAC helps to identify the trend direction. If the closing price is above the PAC upper band, it suggests an uptrend; if below the lower band, it suggests a downtrend.
Entering Trades: Use the long and short signals to enter trades. A long signal is generated when the closing price crosses above the PAC upper band, and a short signal is generated when it crosses below the PAC lower band.
Exit Strategies: Utilize the Stop Loss (SL) and Take Profit (TP) levels to manage risk and lock in profits. These levels are automatically calculated based on the entry price and user-defined percentages.
Trend Confirmation with MAs: The moving averages provide additional confirmation of the trend. When all three MAs are trending in the same direction (e.g., all green for an uptrend), it adds confidence to the trade signal.
Overall Trend Indicators: The triangles at the bottom of the chart show the overall trend direction of the MAs:
Green Triangle: All three MAs are trending upwards, indicating a strong uptrend.
Red Triangle: All three MAs are trending downwards, indicating a strong downtrend.
Yellow Triangle: Mixed signals from the MAs, indicating no clear trend.
Bar Coloring for Quick Analysis: The colored bars give a quick visual cue about the market condition, aiding in faster decision-making.
Alerts: Set up alerts to get notified when a long or short signal is generated, allowing you to act promptly without constantly monitoring the chart.
Maximizing Profit
To maximize profit with this indicator:
Follow the Signals: Use the long and short signals to time your entries. Ensure you follow the trend indicated by the PAC and MAs.
Risk Management: Always set your Stop Loss and Take Profit levels to manage risk. This will help you cut losses early and secure profits.
Confirm with MAs: Look for confirmation from the moving averages. When all MAs align with the signal, it indicates a stronger trend.
Overall Trend Indicators: Pay attention to the triangles at the bottom for overall trend confirmation. Only enter trades when the overall trend is in your favor.
Heikin Ashi for Smoothing: Use Heikin Ashi candles for smoother trends and fewer false signals.
Backtesting: Test the indicator on historical data to understand its performance and adjust settings as necessary.
Adapt to Market Conditions: Adjust the lengths of PAC and MAs based on the market's volatility and timeframe you are trading on.
How to Use the Indicator
Add to Chart: Add the indicator to your TradingView chart.
Configure Settings: Customize the input settings to fit your trading strategy and timeframe.
Monitor Signals: Watch for long and short signals and observe the trend direction with the PAC and MAs.
Check Overall Trend: Look at the triangles at the bottom of the chart to see the overall trend direction of the MAs.
Set Alerts: Configure alerts to get notified of new signals.
Manage Trades: Use the SL and TP levels to manage your trades effectively.
[MAD] WaveBuilderThe WaveBuilder indicator is a powerful technical analysis tool that combines wave calculations, channel formation, and smoothing techniques to identify trends, reversals, and potential trading opportunities.
It provides users with customizable settings for different timeframes, smoothing averages, channel levels, and alert conditions, making it a comprehensive and versatile tool for analyzing market dynamics.
----------------------
Wave Settings:
The Wave Settings section in the Multitimeframe WaveTrend indicator allows you to configure parameters related to the wave calculations based on different timeframes and lengths. This section focuses on four different lengths. Here are the details of the Wave Settings (4 Lengths):
Timeframe 1 (TF1): This parameter allows you to select the first timeframe for the wave calculation. You can choose any valid timeframe.
Weight (F1): This setting represents the weight for Timeframe 1. It is a floating-point value that affects the impact of this timeframe in the wave calculation.
Multiplier 2 (TF2): This parameter specifies the multiplier for the second timeframe. It determines the ratio between Timeframe 2 and Timeframe 1.
Weight (F2): This setting represents the weight for Timeframe 2. It determines the influence of Timeframe 2 in the wave calculation.
Multiplier 3 (TF3): This parameter defines the multiplier for the third timeframe. It determines the ratio between Timeframe 3 and Timeframe 1.
Weight (F3): This setting represents the weight for Timeframe 3. It determines the impact of Timeframe 3 in the wave calculation.
Multiplier 4 (TF4): This parameter specifies the multiplier for the fourth timeframe. It determines the ratio between Timeframe 4 and Timeframe 1.
Weight (F4): This setting represents the weight for Timeframe 4. It determines the influence of Timeframe 4 in the wave calculation.
WaveBuilder Fast: This parameter sets the length of the fast wave average. It represents the number of bars considered in the calculation of the fast wave average.
WaveBuilder Slow: This parameter sets the length of the slow wave average. It represents the number of bars considered in the calculation of the slow wave average.
The Wave Settings allow you to configure different timeframes, multipliers, and weights for wave calculations. These settings provide flexibility in customizing the indicator's behavior based on your preferred trading strategy and market conditions.
----------------------
Counter Oscillator:
The Counter Oscillator section in the Multitimeframe WaveTrend indicator enables you to configure parameters related to a counter oscillator. This oscillator helps identify potential reversals or countertrend movements.
Here are the details of the Counter Oscillator settings:
Multiplier Counter (TF5): This parameter allows you to select the multiplier counter timeframe. It determines the ratio between the multiplier counter and the main timeframes.
Weight (F5): This setting represents the weight for the multiplier counter. It determines the influence of the multiplier counter in the counter oscillator calculation.
Length (will_length): This parameter sets the length or period of the counter oscillator. It represents the number of bars considered in the counter oscillator calculation.
The Counter Oscillator settings provide additional insights into the market by analyzing countertrend movements. By adjusting the multiplier counter and length parameters, you can customize the counter oscillator to suit your trading preferences.
----------------------
Wave Smoothing and Mixing:
The Wave Smoothing and Mixing section in the Multitimeframe WaveTrend indicator allows you to configure parameters related to the smoothing and mixing of the wave calculations. Here are the details of the Wave Smoothing and Mixing settings:
Average 1 Type: This parameter allows you to select the type of smoothing average for the first average. You have various options such as WMA, HMA, VWMA, LMA, RMA, SMA, EMA, and more.
Length 1: This setting determines the length or period of the first smoothing average. It represents the number of bars considered in the calculation.
Average 2 Type: This parameter allows you to select the type of smoothing average for the second average.
Length 2: This setting determines the length or period of the second smoothing average.
Mix Factor AVG1-AVG2: This parameter controls the mixing factor between the first and second smoothing averages. It affects the weighting or blending of the two averages.
POW - Factor: This parameter adjusts the power factor, which can compress or expand the resulting values. It allows you to fine-tune the output based on your preferences.
The Wave Smoothing and Mixing settings enable you to smooth the wave calculations and mix different averages to create a more refined and customized output. By selecting the desired smoothing types, adjusting the lengths, and modifying the mix factor and power factor, you can tailor the indicator to your specific trading style.
----------------------
Channel Levels and Alert Mode:
The Channel Levels and Alert Mode section in the Multitimeframe WaveTrend indicator allows you to configure parameters related to the channel levels and the alert mode. Here are the details of the Channel Levels and Alert Mode settings:
Channel Width: This parameter determines the width or range of the channel levels. It represents the distance between the upper and lower channel lines.
Channel Shift Up/Down: This setting allows you to shift the entire channel up or down. It represents the vertical offset of the channel lines.
Alert Mode (Alertmode): This parameter determines the type of alert triggered by the indicator based on the channel levels.
You have options such as Outside, CrossIn, CrossOut, ChangeDir-All, and ChangeDir-Outside.
Channel Levels: The upper and lower channel levels are calculated based on the channel width and offset. They provide visual boundaries for the price movement within the channel.
The Channel Levels and Alert Mode settings help define the channel levels and specify the conditions for generating alert notifications.
By adjusting the channel width, offset, and selecting the appropriate alert mode, you can customize the indicator's behavior according to your trading requirements.
----------------------
Dynamic Channel:
The Dynamic Channel section in the Multitimeframe WaveTrend indicator allows you to configure parameters related to the dynamic channel formation.
This feature helps create channels based on different smoothing averages.
Here are the details of the Dynamic Channel settings:
Channel Average 1 Type: This parameter allows you to select the type of smoothing average for the first channel average.
Length 1: This setting determines the length or period of the first channel average.
Channel Average 2 Type: This parameter allows you to select the type of smoothing average for the second channel average.
Length 2: This setting determines the length or period of the second channel average.
MA 1 / MA 2 Mix Factor: This parameter controls the mixing factor between the first and second channel averages. It affects the weighting or blending of the two averages.
Mixing Off Dynamic in Weight: This parameter allows you to mix off the dynamic in weight.
Smoothing Type: This parameter allows you to select the type of smoothing for the trend within the dynamic channel.
Smoothing Length: This setting determines the length or period of the trend smoothing within the dynamic channel.
The Dynamic Channel settings enable you to create channels based on different smoothing averages and adjust the weighting between them. Additionally, you can apply further smoothing to the trend within the dynamic channel. This feature helps identify trends and potential trade opportunities within the channel.
----------------------
Speed of Change Rate:
The Speed of Change Rate section in the Multitimeframe WaveTrend indicator allows you to configure parameters related to the rate of change in the indicator. Here are the details of the Speed of Change Rate settings:
Plot Speed (plot_speed): This setting determines whether to plot the speed of change on the chart.
Speed Scaling (change_factor): This parameter adjusts the scaling factor for the speed of change.
Speed Smoother (smoothtype_change): This parameter allows you to select the type of smoothing average for the speed of change calculation.
Speed Length (change_length): This setting determines the length or period of the speed of change calculation.
The Speed of Change Rate settings provide insights into the rate at which the indicator values are changing. By visualizing and analyzing the speed of change, you can identify potential acceleration or deceleration in the price movement.
----------------------
Signal Main Configuration:
The Signal Main Configuration section in the Multitimeframe WaveTrend indicator allows you to configure parameters related to the signal input and passthrough. Here are the details of the Signal Main Configuration settings:
Signal Type (inputtype): This parameter determines the type of signal input. You have options such as MultiBit and NoInput.
Select L1 Indicator Signal (inputModule): This parameter allows you to select the source of the L1 indicator signal. You can choose any valid input source, such as the closing price or another indicator.
Signal Passthrough (Passthrough): This setting enables or disables the passthrough of the signal. When enabled, the indicator passes the input signal to the output.
The Signal Main Configuration settings allow you to define the type of signal input and control whether to pass the signal through the indicator or not. This feature provides flexibility in integrating the indicator with other trading strategies or indicators.
----------------------
Multibit Modified Channel:
The Multibit Modified Channel section in the Multitimeframe WaveTrend indicator allows you to configure parameters related to the modified channel based on the multibit input. Here are the details of the Multibit Modified Channel settings:
Input Bull (CH_Trendup_in): This parameter allows you to specify the input channel for bullish signals.
Bull Offset (trendfactorbull): This setting determines the offset for the bullish signals in the modified channel.
Input Bear (CH_Trenddown_in): This parameter allows you to specify the input channel for bearish signals.
Bear Offset (trendfactorbaer): This setting determines the offset for the bearish signals in the modified channel.
The Multibit Modified Channel settings enable you to modify the channel based on the multibit input. By specifying the input channels for bullish and bearish signals and adjusting the respective offsets,
you can customize the channel representation based on your trading strategy.
Multibit Output:
The Multibit Output section in the Multitimeframe WaveBuilder indicator allows you to configure parameters related to the output of the multibit signals and alerts. Here are the details of the Multibit Output settings:
Output Bull (CH_Buy_out): This parameter specifies the output channel for bullish signals.
Output Bear (CH_Sell_out): This parameter specifies the output channel for bearish signals.
Show Alerts (showalerts): This setting determines whether to display alert notifications for the multibit signals.
The Multibit Output settings define the output channels for bullish and bearish signals and control the display of alert notifications. This allows you to visualize and receive alerts for the multibit signals generated by the indicator.
----------------
Here a overview from the settings
--------------------------------
The pipeline of the WaveBuilder can be understood in the following structured manner:
----------
Wave Calculation:
Wave calculation is performed using the input parameters, resulting in wave values.
The wave values are then averaged using Average 1 and Average 2, and the weighted average is obtained.
The weighted average is mixed with other factors to create a mixed value.
----------
Channel Formation:
The mixed value is multiplied by a weight to generate a dynamic part.
The dynamic part is combined with the static channel and the multibit modification to form a base value.
----------
Smoothing and Mixing:
The base value is averaged using Average 1 and Average 2, and the weighted average is calculated.
The mixed2 value is obtained by smoothing the weighted average.
The mixed2 value is further processed using power compression (POW) to refine the output.
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Plotting:
The final smoothed and processed values are plotted to visualize the indicator on the chart.
By following this pipeline, the WaveBuilder combines wave calculations, channel formation, smoothing techniques, and power compression to provide valuable insights into market trends and potential trading opportunities.
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Librarys used:
djmad/Signal_transcoder_library
djmad/MAD_MATH
djmad/Mad_Standardparts
Quansium Series A BacktestThis comes with preconfigured setups or strategies. Simply choose one from our list based on the timeframe it was made for. Leverage can be changed; to keep trading safe, a maximum of 2 is allowed. In our findings, this was able to trade crypto (specifically BTC ), MES (Micro E-mini S&P 500 Index Futures ), and stocks. It is important to know that setups A, B, C, and D use variable position sizing, and dynamic stop loss/trailing stop/take profit, these parameters are provided through the alerts. The rest of the strategies were created with a simpler approach in mind, just plainly entry/exits signals.
Quansium as a framework:
Price reformat: we take the price source (Open, Close, High, Low) and remove any noise that affects the accuracy of our signals.
Time awareness: we take several time periods of the data on the chart such as start, end, and whole. We use this to add more depth to our signals.
Position size: our backtest tries to recreate as much as the real world trades as possible so our position is determined by the current equity. We also use the volatility of the market to increase or decrease our exposure or risk.
Risk awareness: stop loss, take profit, trailing stop are the risk exits we use to provide our users some peace of mind. These parameters are totally dynamic and follow the same behavior of the market.
Signals filtering: to make almost non-existent any errors and increase the quality of our trades, our indicators go through multiple phases, this avoid double entries or early exits, and help maintain a record of what has transpired and what’s currently taking place.
Indicators: whenever we can we use custom code or our own functions instead of the defaults ones provided. This gives us total control of what we’re trying to achieve. In many cases we tend to combine several indicators’ logic into one creating a more personalized take on it.
Easiness: since we started our main goal has been to provide the easiest and fastest way to alerts’ creation. It has taken us years to reach this level where now we already provide a list of preset strategies so the user doesn’t have to spend much time tinkering with scripts and more on other matters, because we know life is more than just trading.
Raw signals: we provide the option to turn off as much of our advanced features such as stop loss, take profit, trailing stop, dynamic sizing, etc, etc for a simple approach. Trade signals still go through the signals filtering method mentioned above,
Timeframe pairing: we take trading very seriously, by no way we’ll want the user to lose money (although such thing is expected because past results aren’t an indicative of futures ones), through years of experience we have found what are usually common mistakes the user makes, this feature allows us to only activate the strategy if the right timeframe is chosen.
Trend filters: through the years we have improved the arts of the trend. We like to keep things simple but yet powerful. We observe the macro and micro trend of the security. This helps confirm we are entering at the desirable timing. We also incorporate volume and volatility into decision making, we simply programmed it to trade when these are increasing and higher than the average values observed in both the short and long term. Finally we take into account the strength of the pair to make our final choice of whether to enter or wait, and if anything flashes contrary movement then we cancel the upcoming signal and stop monitoring until the next one comes along.
Full automated risk: stop loss, take profit, and trailing stops usually are set in percentages, and optimized even more using the current market behavior to become more adaptive. But always remains some sort of fixation, so the user must choose a value somewhere. This is where our framework shines the most, as previously mentioned before when we take time into our calculations, we use several periods to observe performance and get values that keep our risk exits natural and closest to the flow of the market itself.
Setups:
A: Centered oscillator with the difference of several moving averages with more sensitive settings. Momentum focused.
B: Centered oscillator using simple moving averages. Trend-Following focused.
C: Centered oscillator using smoothed data with the help of faster moving averages. Trend-Following focused.
D: Centered oscillator with the difference of several moving averages with less sensitive settings. Trend-Following focused.
E: Centered oscillator with the difference of moving averages where the standard deviation is applied first. It uses less sensitive settings. Trend-Following focused.
F: Finds the relationship between multiple readings of the price’s relative strength to better pin-point downs and ups. Trend-Following focused.
G: Centered oscillator with the difference of moving averages where the standard deviation is applied first. It uses more sensitive settings. Momentum focused.
H: Multiple centered oscillators using various moving averages. Trend-Following focused.
I: Centered oscillator using simple moving averages. Momentum focused.
Note: The framework is composed of almost 1000 lines of code as compared to each indicator that makes up the setup which is around 10. The power from Quansium doesn't come from the strategies themselves but rather the overall system that turns simple signals into complex and advanced trades.
Strategy Tester:
Initial Capital: chosen value is $20,000, as an approximate to Bitcoin’s ATH (All-Time High). In previous iterations we noticed some trades won’t go through if the capital was less than the ATH.
Order Size: 100% of equity (although the script controls this, and this is of no regards to the results).
Pyramiding: 1, system doesn’t place multiple entries in a row, only one at a time.
Commission: This simulates order execution with custom trading fees. Commissions are turned off by default because this script works in various markets and each operates differently. In order to reach results that are close to real world conditions, it is imperative the user fills this based upon their broker or exchange data.
When we started, we were focused on finding the best indicator, or creating it ourselves. After years we came to realize that the secret is not in which indicator you use but the framework behind it. All strategies have bad, good, best, worst performance periods. The key of a good system is to help keep you safe when it’s down and maximize your potential when it’s up. We hope this material at the very minimum inspires you to keep going and not lose faith, because it is not the smartest who win but those who persevere.
Bar Balance [LucF]Bar Balance extracts the number of up, down and neutral intrabars contained in each chart bar, revealing information on the strength of price movement. It can display stacked columns representing raw up/down/neutral intrabar counts, or an up/down balance line which can be calculated and visualized in many different ways.
WARNING: This is an analysis tool that works on historical bars only. It does not show any realtime information, and thus cannot be used to issue alerts or for automated trading. When realtime bars elapse, the indicator will require a browser refresh, a change to its Inputs or to the chart's timeframe/symbol to recalculate and display information on those elapsed bars. Once a trader understands this, the indicator can be used advantageously to make discretionary trading decisions.
Traders used to work with my Delta Volume Columns Pro will feel right at home in this indicator's Inputs . It has lots of options, allowing it to be used in many different ways. If you value the bar balance information this indicator mines, I hope you will find the time required to master the use of Bar Balance well worth the investment.
█ OVERVIEW
The indicator has two modes: Columns and Line .
Columns
• In Columns mode you can display stacked Up/Down/Neutral columns.
• The "Up" section represents the count of intrabars where `close > open`, "Down" where `close < open` and "Neutral" where `close = open`.
• The Up section always appears above the centerline, the Down section below. The Neutral section overlaps the centerline, split halfway above and below it.
The Up and Down sections start where the Neutral section ends, when there is one.
• The Up and Down sections can be colored independently using 7 different methods.
• The signal line plotted in Line mode can also be displayed in Columns mode.
Line
• Displays a single balance line using a zero centerline.
• A variable number of independent methods can be used to calculate the line (6), determine its color (5), and color the fill (5).
You can thus evaluate the state of 3 different components with this single line.
• A "Divergence Levels" feature will use the line to automatically draw expanding levels on divergence events.
Features available in both modes
• The color of all components can be selected from 15 base colors, with 16 gradient levels used for each base color in the indicator's gradients.
• A zero line can show a 6-state aggregate value of the three main volume balance modes.
• The background can be colored using any of 5 different methods.
• Chart bars can be colored using 5 different methods.
• Divergence and large neutral count ratio events can be shown in either Columns or Line mode, calculated in one of 4 different methods.
• Markers on 6 different conditions can be displayed.
█ CONCEPTS
Intrabar inspection
Intrabar inspection means the indicator looks at lower timeframe bars ( intrabars ) making up a given chart bar to gather its information. If your chart is on a 1-hour timeframe and the intrabar resolution determined by the indicator is 5 minutes, then 12 intrabars will be analyzed for each chart bar and the count of up/down/neutral intrabars among those will be tallied.
Bar Balances and calculation methods
The indicator uses a variety of methods to evaluate bar balance and to derive other calculations from them:
1. Balance on Bar : Uses the relative importance of instant Up and Down counts on the bar.
2. Balance Averages : Uses the difference between the EMAs of Up and Down counts.
3. Balance Momentum : Starts by calculating, separately for both Up and Down counts, the difference between the same EMAs used in Balance Averages and an SMA of double the period used for the EMAs. These differences are then aggregated and finally, a bounded momentum of that aggregate is calculated using RSI.
4. Markers Bias : It sums the bull/bear occurrences of the four previous markers over a user-defined period (the default is 14).
5. Combined Balances : This is the aggregate of the instant bull/bear bias of the three main bar balances.
6. Dual Up/Down Averages : This is a display mode showing the EMA calculated for each of the Up and Down counts.
Interpretation of neutral intrabars
What do neutral intrabars mean? When price does not change during a bar, it can be because there is simply no interest in the market, or because of a perfect balance between buyers and sellers. The latter being more improbable, Bar Balance assumes that neutral bars reveal a lack of interest, which entails uncertainty. That is the reason why the option is provided to interpret ratios of neutral intrabars greater than 50% as divergences. It is also the rationale behind the option to dampen signal lines on the inverse ratio of neutral intrabars, so that zero intrabars do not affect the signal, and progressively larger proportions of neutral intrabars will reduce the signal's amplitude, as the balance calcs using the up/down counts lose significance. The impact of the dampening will vary with markets. Weaker markets such as cryptos will often contain greater numbers of neutral intrabars, so dampening the Line in that sector will have a greater impact than in more liquid markets.
█ FEATURES
1 — Columns
• While the size of the Up/Down columns always represents their respective importance on the bar, their coloring mode is independent. The default setup uses a standard coloring mode where the Up/Down columns over/under the zero line are always in the bull/bear color with a higher intensity for the winning side. Six other coloring modes allow you to pack more information in the columns. When choosing to color the top columns using a bull/bear gradient on Balance Averages, for example, you will end up with bull/bear colored tops. In order for the color of the bottom columns to continue to show the instant bar balance, you can then choose the "Up/Down Ratio on Bar — Dual Solid Colors" coloring mode to make those bars the color of the winning side for that bar.
• Line mode shows only the line, but Columns mode allows displaying the line along with it. If the scale of the line is different than that of the scale of the columns, the line will often appear flat. Traders may find even a flat line useful as its bull/bear colors will be easily distinguishable.
2 — Line
• The default setup for Line mode uses a calculation on "Balance Momentum", with a fill on the longer-term "Balance Averages" and a line color based on the "Markers Bias". With the background set on "Line vs Divergence Levels" and the zero line on the hard-coded "Combined Bar Balances", you have access to five distinct sources of information at a glance, to which you can add divergences, divergences levels and chart bar coloring. This provides powerful potential in displaying bar balance information.
• When no columns are displayed, Line mode can show the full scale of whichever line you choose to calculate because the columns' scale no longer interferes with the line's scale.
• Note that when "Balance on Bar" is selected, the Neutral count is also displayed as a ratio of the balance line. This is the only instance where the Neutral count is displayed in Line mode.
• The "Dual Up/Down Averages" is an exception as it displays two lines: one average for the Up counts and another for the Down counts. This mode will be most useful when Columns are also displayed, as it provides a reference for the top and bottom columns.
3 — Zero Line
The zero line can be colored using two methods, both based on the Combined Balances, i.e., the aggregate of the instant bull/bear bias of the three main bar balances.
• In "Six-state Dual Color Gradient" mode, a dot appears on every bar. Its color reflects the bull/bear state of the Combined Balances, and the dot's brightness reflects the tally of balance biases.
• In "Dual Solid Colors (All Bull/All Bear Only)" a dot only appears when all three balances are either bullish or bearish. The resulting pattern is identical to that of Marker 1.
4 — Divergences
• Divergences are displayed as a small circle at the top of the scale. Four different types of divergence events can be detected. Divergences occur whenever the bull/bear bias of the method used diverges with the bar's price direction.
• An option allows you to include in divergence events instances where the count of neutral intrabars exceeds 50% of the total intrabar count.
• The divergence levels are dynamic levels that automatically build from the line's values on divergence events. On consecutive divergences, the levels will expand, creating a channel. This implementation of the divergence levels corresponds to my view that divergences indicate anomalies, hesitations, points of uncertainty if you will. It excludes any association of a pre-determined bullish/bearish bias to divergences. Accordingly, the levels merely take note of divergence events and mark those points in time with levels. Traders then have a reference point from which they can evaluate further movement. The bull/bear/neutral colors used to plot the levels are also congruent with this view in that they are determined by price's position relative to the levels, which is how I think divergences can be put to the most effective use.
5 — Background
• The background can show a bull/bear gradient on four different calculations. You can adjust its brightness to make its visual importance proportional to how you use it in your analysis.
6 — Chart bars
• Chart bars can be colored using five different methods.
• You have the option of emptying the body of bars where volume does not increase, as does my TLD indicator, the idea behind this being that movement on bars where volume does not increase is less relevant.
7 — Intrabar Resolution
You can choose between three modes. Two of them are automatic and one is manual:
a) Fast, Longer history, Auto-Steps (~12 intrabars) : Optimized for speed and deeper history. Uses an average minimum of 12 intrabars.
b) More Precise, Shorter History Auto-Steps (~24 intrabars) : Uses finer intrabar resolution. It is slower and provides less history. Uses an average minimum of 24 intrabars.
c) Fixed : Uses the fixed resolution of your choice.
Auto-Steps calculations vary for 24/7 and conventional markets in order to achieve the proper target of minimum intrabars.
You can choose to view the intrabar resolution currently used to calculate delta volume. It is the default.
The proper selection of the intrabar resolution is important. It must achieve maximal granularity to produce precise results while not unduly slowing down calculations, or worse, causing runtime errors.
8 — Markers
Six markers are available:
1. Combined Balances Agreement : All three Bar Balances are either bullish or bearish.
2. Up or Down % Agrees With Bar : An up marker will appear when the percentage of up intrabars in an up chart bar is greater than the specified percentage. Conditions mirror to down bars.
3. Divergence confirmations By Price : One of the four types of balance calculations can be used to detect divergences with price. Confirmations occur when the bar following the divergence confirms the balance bias. Note that the divergence events used here do not include neutral intrabar events.
4. Balance Transitions : Bull/bear transitions of the selected balance.
5. Markers Bias Transitions : Bull/bear transitions of the Markers Bias.
6. Divergence Confirmations By Line : Marks points where the line first breaches a divergence level.
Markers appear when the condition is detected, without delay. Since nothing is plotted in realtime, markers do not appear on the realtime bar.
9 — Settings
• Two modes can be selected to dampen the line on the ratio of neutral intrabars.
• A distinct weight can be attributed to the count of the latter half of intrabars, on the assumption that later intrabars may be more important in determining the outcome of chart bars.
• Allows control over the periods of the different moving averages used in calculations.
• The default periods used for the various calculations define the following hierarchy from slow to fast:
Balance Averages: 50,
Balance Momentum: 20,
Dual Up/Down Averages: 20,
Marker Bias: 10.
█ LIMITATIONS
• This script uses a special characteristic of the `security()` function allowing the inspection of intrabars—which is not officially supported by TradingView.
• The method used does not work on the realtime bar—only on historical bars.
• The indicator only works on some chart resolutions: 3, 5, 10, 15 and 30 minutes, 1, 2, 4, 6, and 12 hours, 1 day, 1 week and 1 month. The script’s code can be modified to run on other resolutions, but chart resolutions must be divisible by the lower resolution used for intrabars and the stepping mechanism could require adaptation.
• When using the "Line vs Divergence Levels — Dual Color Gradient" color mode to fill the line, background or chart bars, keep in mind that a line calculation mode must be defined for it to work, as it determines gradients on the movement of the line relative to divergence levels. If the line is hidden, it will not work.
• When the difference between the chart’s resolution and the intrabar resolution is too great, runtime errors will occur. The Auto-Steps selection mechanisms should avoid this.
• Alerts do not work reliably when `security()` is used at intrabar resolutions. Accordingly, no alerts are configured in the indicator.
• The color model used in the indicator provides for fancy visuals that come at a price; when you change values in Inputs , it can take 20 seconds for the changes to materialize. Luckily, once your color setup is complete, the color model does not have a large performance impact, as in normal operation the `security()` calls will become the most important factor in determining response time. Also, once in a while a runtime error will occur when you change inputs. Just making another change will usually bring the indicator back up.
█ RAMBLINGS
Is this thing useful?
I'll let you decide. Bar Balance acts somewhat like an X-Ray on bars. The intrabars it analyzes are no secret; one can simply change the chart's resolution to see the same intrabars the indicator uses. What the indicator brings to traders is the precise count of up/down/neutral intrabars and, more importantly, the calculations it derives from them to present the information in a way that can make it easier to use in trading decisions.
How reliable is Bar Balance information?
By the same token that an up bar does not guarantee that more up bars will follow, future price movements cannot be inferred from the mere count of up/down/neutral intrabars. Price movement during any chart bar for which, let's say, 12 intrabars are analyzed, could be due to only one of those intrabars. One can thus easily see how only relying on bar balance information could be very misleading. The rationale behind Bar Balance is that when the information mined for multiple chart bars is aggregated, it can provide insight into the history behind chart bars, and thus some bias as to the strength of movements. An up chart bar where 11/12 intrabars are also up is assumed to be stronger than the same up bar where only 2/12 intrabars are up. This logic is not bulletproof, and sometimes Bar Balance will stray. Also, keep in mind that balance lines do not represent price momentum as RSI would. Bar Balance calculations have no idea where price is. Their perspective, like that of any historian, is very limited, constrained that it is to the narrow universe of up/down/neutral intrabar counts. You will thus see instances where price is moving up while Balance Momentum, for example, is moving down. When Bar Balance performs as intended, this indicates that the rally is weakening, which does necessarily imply that price will reverse. Occasionally, price will merrily continue to advance on weakening strength.
Divergences
Most of the divergence detection methods used here rely on a difference between the bias of a calculation involving a multi-bar average and a given bar's price direction. When using "Bar Balance on Bar" however, only the bar's balance and price movement are used. This is the default mode.
As usual, divergences are points of interest because they reveal imbalances, which may or may not become turning points. I do not share the overwhelming enthusiasm traders have for the purported ability of bullish/bearish divergences to indicate imminent reversals.
Superfluity
In "The Bed of Procrustes", Nassim Nicholas Taleb writes: To bankrupt a fool, give him information . Bar Balance can display lots of information. While learning to use a new indicator inevitably requires an adaptation period where we put it through its paces and try out all its options, once you have become used to Bar Balance and decide to adopt it, rigorously eliminate the components you don't use and configure the remaining ones so their visual prominence reflects their relative importance in your analysis. I tried to provide flexible options for traders to control this indicator's visuals for that exact reason—not for window dressing.
█ NOTES
For traders
• To avoid misleading traders who don't read script descriptions, the indicator shows nothing in the realtime bar.
• The Data Window shows key values for the indicator.
• All gradients used in this indicator determine their brightness intensities using advances/declines in the signal—not their relative position in a fixed scale.
• Note that because of the way gradients are optimized internally, changing their brightness will sometimes require bringing down the value a few steps before you see an impact.
• Because this indicator does not use volume, it will work on all markets.
For coders
• For those interested in gradients, this script uses an advanced version of the Advance/Decline gradient function from the PineCoders Color Gradient (16 colors) Framework . It allows more precise control over the range, steps and min/max values of the gradients.
• I use the PineCoders Coding Conventions for Pine to write my scripts.
• I used functions modified from the PineCoders MTF Selection Framework for the selection of timeframes.
█ THANKS TO:
— alexgrover who helped me think through the dampening method used to attenuate signal lines on high ratios of neutral intrabars.
— A guy called Kuan who commented on a Backtest Rookies presentation of their Volume Profile indicator . The technique I use to inspect intrabars is derived from Kuan's code.
— theheirophant , my partner in the exploration of the sometimes weird abysses of `security()`’s behavior at intrabar resolutions.
— midtownsk8rguy , my brilliant companion in mining the depths of Pine graphics. He is also the co-author of the PineCoders Color Gradient Frameworks .
