MA Optimizer Simplified [CHE]Introduction:
The MA Optimizer Simplified is a powerful tool for traders and analysts who want to compare and optimize various moving averages (MA). This tool is specifically designed to identify the best or worst performers among a variety of moving averages based on their cumulative performance.
Features and Benefits:
1. Versatility:
- Supports multiple types of moving averages, including:
- Simple Moving Average (SMA): A basic MA calculated by averaging the closing prices over a specified period.
- Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to new information.
- Weighted Moving Average (WMA): Assigns more weight to recent data, but in a linear fashion.
- Volume-Weighted Moving Average (VWMA): Averages prices based on volume, giving more importance to periods with higher trading volume.
- Hull Moving Average (HMA): Designed to reduce lag while improving smoothness.
- Smoothed Moving Average (SMMA or RMA): Averages prices over a longer period, providing a smoother line.
- Bollinger Bands: Uses SMA as a basis and adds upper and lower bands based on standard deviations.
- T3: A smoother and less lagging MA that reduces market noise.
- Allows users to easily switch between MA types and test different periods.
2. Performance Evaluation:
- Calculates the cumulative performance of up to ten different MAs.
- Automatically identifies the best or worst performer based on user selection (Best or Worst).
3. Crossover Detection:
- Detects crossovers of prices and MAs to measure performance.
- Provides clear visual signals when the price crosses a moving average.
4. Visual Representation:
- Plots the best MA indicator on the chart, dynamically changing its color based on price movement relative to the MA.
- Table functionality to display the performance of each MA, including the length and achieved performance in percentage.
5. Customizable Settings:
- Customizable settings for table size and position as well as colors for better visualization and user-friendliness.
- Flexibility in selecting the number of candles that must be above or below the MA before a signal is triggered.
Special Features:
1. T3 Indicator:
- The T3 indicator provides a smoother representation and reduces market noise, leading to more precise signals.
2. Crossover and Crossunder Logic:
- The script includes advanced logic for detecting crossover and crossunder events to identify accurate entry points.
3. Dynamic Color Change:
- The best MA indicator changes color based on the number of candles above or below the MA, helping to quickly recognize market sentiment.
4. Comprehensive Performance Analysis:
- The calculation of cumulative performance for each MA allows for detailed analysis and helps identify the most effective trading strategies.
Conclusion:
The MA Optimizer Simplified is an essential tool for any trader looking to analyze and optimize the performance of various moving averages. With its versatile features and user-friendly settings, it offers a comprehensive and efficient solution for technical analysis.
Best regards, Chervolino
Search in scripts for "Exponential Moving Average"
Simple Bollinger Bands + 3 EMAWe know that the number of indicators that we can use is limited, that is why with this indicator the Bollinger Bands + 3 EMAs join and be able to use 4 indicators in 1.
Bollinger Bands (BB)
Bollinger Bands (BB) are a widely popular technical analysis instrument created by John Bollinger in the early 1980’s. Bollinger Bands consist of a band of three lines which are plotted in relation to security prices. The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader; however a 20 day moving average is by far the most popular). The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price. Typically the Upper and Lower Bands are set to two standard deviations away from the SMA (The Middle Line); however the number of standard deviations can also be adjusted by the trader.
Exponential Moving Average (EMA)
Moving averages visualize the average price of a financial instrument over a specified period of time. However, there are a few different types of moving averages. They typically differ in the way that different data points are weighted or given significance. An Exponential Moving Average (EMA) is very similar to (and is a type of) a weighted moving average. The major difference with the EMA is that old data points never leave the average. To clarify, old data points retain a multiplier (albeit declining to almost nothing) even if they are outside of the selected data series length.
The 3 EMAs that the Script has, are configured as follows:
Fast EMA (purple) 10 periods.
Slow EMA (blue) 55 periods.
Big EMA (olive) 200 periods.
However, you can configure each one with the color and the number of periods you want.
There are other indicators in the Public Library that have similar functions to this Script, but they all do it in a more complex and less friendly way when configuring it, for this reason we wanted to keep this Script as simple as possible.
ATR and Moving AverageUsing ATR and Moving Average: A Technical Analysis Strategy
The Average True Range (ATR) and the Moving Average are two important technical analysis tools that can be used together to identify trading opportunities in the market. In this article, we will explore how to use these two tools and how the crossover between them can indicate changes in the market.
What is ATR?
The Average True Range (ATR) is a measure of the volatility of an asset, which calculates the average true range of an asset over a period of time. The true range is the difference between the closing price and the opening price of an asset, or the difference between the closing price and the highest or lowest price of the day. ATR is an important measure of volatility, as it helps to identify the magnitude of price fluctuations of an asset.
What is Moving Average?
The Moving Average is a technical analysis tool that calculates the average price of an asset over a period of time. The Moving Average can be used to identify trends and price patterns, and is an important tool for traders. There are different types of Moving Averages, including the Simple Moving Average (SMA), the Exponential Moving Average (EMA), and the Weighted Moving Average (WMA).
Crossover between ATR and Moving Average
The crossover between ATR and Moving Average can be an important indicator of changes in the market. When ATR crosses above the Moving Average, it may indicate that the volatility of the asset is increasing and that the price may be about to rise. This occurs because ATR is increasing, which means that the true range of the asset is increasing, and the Moving Average is being surpassed, which means that the price is rising.
On the other hand, when ATR crosses below the Moving Average, it may indicate that the volatility of the asset is decreasing and that the price may be about to fall. This occurs because ATR is decreasing, which means that the true range of the asset is decreasing, and the Moving Average is being surpassed, which means that the price is falling.
Trading Strategies
There are several trading strategies that can be used with the crossover between ATR and Moving Average. Some of these strategies include:
Buying when ATR crosses above the Moving Average, with the expectation that the price will rise.
Selling when ATR crosses below the Moving Average, with the expectation that the price will fall.
Using the crossover between ATR and Moving Average as a filter for other trading strategies, such as trend analysis or pattern recognition.
In summary, the crossover between ATR and Moving Average can be an important indicator of changes in the market, and can be used as a technical analysis tool to identify trading opportunities. However, it is important to remember that no trading strategy is foolproof, and that it is always important to use a disciplined approach and manage risk adequately.
Stochastic Fusion Elite [trade_lexx]📈 Stochastic Fusion Elite is your reliable trading assistant!
📊 What is Stochastic Fusion Elite ?
Stochastic Fusion Elite is a trading indicator based on a stochastic oscillator. It analyzes the rate of price change and generates buy or sell signals based on various technical analysis methods.
💡 The main components of the indicator
📊 Stochastic oscillator (K and D)
Stochastic shows the position of the current price relative to the price range for a certain period. Values above 80 indicate overbought (an early sale is possible), and values below 20 indicate oversold (an early purchase is possible).
📈 Moving Averages (MA)
The indicator uses 10 different types of moving averages to smooth stochastic lines.:
- SMA: Simple moving average
- EMA: Exponential moving average
- WMA: Weighted moving average
- HMA: Moving Average Scale
- KAMA: Kaufman Adaptive Moving Average
- VWMA: Volume-weighted moving average
- ALMA: Arnaud Legoux Moving Average
- TEMA: Triple exponential moving average
- ZLEMA: zero delay exponential moving average
- DEMA: Double exponential moving average
The choice of the type of moving average affects the speed of the indicator's response to market changes.
🎯 Bollinger Bands (BB)
Bands around the moving average that widen and narrow depending on volatility. They help determine when the stochastic is out of the normal range.
🔄 Divergences
Divergences show discrepancies between price and stochastic:
- Bullish divergence: price is falling and stochastic is rising — an upward reversal is possible
- Bearish divergence: the price is rising, and stochastic is falling — a downward reversal is possible
🔍 Indicator signals
1️⃣ KD signals (K and D stochastic lines)
- Buy signal:
- What happens: the %K line crosses the %D line from bottom to top
- What does it look like: a green triangle with the label "KD" under the chart and the label "Buy" below the bar
- What does this mean: the price is gaining an upward momentum, growth is possible
- Sell signal:
- What happens: the %K line crosses the %D line from top to bottom
- What it looks like: a red triangle with the label "KD" above the chart and the label "Sell" above the bar
- What does this mean: the price is losing its upward momentum, possibly falling
2️⃣ Moving Average Signals (MA)
- Buy Signal:
- What happens: stochastic crosses the moving average from bottom to top
- What it looks like: a green triangle with the label "MA" under the chart and the label "Buy" below the bar
- What does this mean: stochastic is starting to accelerate upward, price growth is possible
- Sell signal:
- What happens: stochastic crosses the moving average from top to bottom
- What it looks like: a red triangle with the label "MA" above the chart and the label "Sell" above the bar
- What does this mean: stochastic is starting to accelerate downwards, a price drop is possible
3️⃣ Bollinger Band Signals (BB)
- Buy signal:
- What happens: stochastic crosses the lower Bollinger band from bottom to top
- What it looks like: a green triangle with the label "BB" under the chart and the label "Buy" below the bar
- What does this mean: stochastic was too low and is now starting to recover
- Sell signal:
- What happens: Stochastic crosses the upper Bollinger band from top to bottom
- What it looks like: a red triangle with a "BB" label above the chart and a "Sell" label above the bar
- What does this mean: stochastic was too high and is now starting to decline
4️⃣ Divergence Signals (Div)
- Buy Signal (Bullish Divergence):
- What's happening: the price is falling, and stochastic is forming higher lows
- What it looks like: a green triangle with a "Div" label under the chart and a "Buy" label below the bar
- What does this mean: despite the falling price, the momentum is already changing in an upward direction
- Sell signal (bearish divergence):
- What's going on: the price is rising, and stochastic is forming lower highs
- What it looks like: a red triangle with a "Div" label above the chart and a "Sell" label above the bar
- What does this mean: despite the price increase, the momentum is already weakening
🛠️ Filters to filter out false signals
1️⃣ Minimum distance between the signals
- What it does: sets the minimum number of candles between signals
- Why it is needed: prevents signals from being too frequent during strong market fluctuations
- How to set it up: Set the number from 0 and above (default: 5)
2️⃣ "Waiting for the opposite signal" mode
- What it does: waits for a signal in the opposite direction before generating a new signal
- Why you need it: it helps you not to miss important trend reversals
- How to set up: just turn the function on or off
3️⃣ Filter by stochastic levels
- What it does: generates signals only when the stochastic is in the specified ranges
- Why it is needed: it helps to catch the moments when the market is oversold or overbought
- How to set up:
- For buy signals: set a range for oversold (for example, 1-20)
- For sell signals: set a range for overbought (for example, 80-100)
4️⃣ MFI filter
- What it does: additionally checks the values of the cash flow index (MFI)
- Why it is needed: confirms stochastic signals with cash flow data
- How to set it up:
- For buy signals: set the range for oversold MFI (for example, 1-25)
- For sell signals: set the range for overbought MFI (for example, 75-100)
5️⃣ The RSI filter
- What it does: additionally checks the RSI values to confirm the signals
- Why it is needed: adds additional confirmation from another popular indicator
- How to set up:
- For buy signals: set the range for oversold MFI (for example, 1-30)
- For sell signals: set the range for overbought MFI (for example, 70-100)
🔄 Signal combination modes
1️⃣ Normal mode
- How it works: all signals (KD, MA, BB, Div) work independently of each other
- When to use it: for general market analysis or when learning how to work with the indicator
2️⃣ "AND" Mode ("AND Mode")
- How it works: the alarm appears only when several conditions are triggered simultaneously
- Combination options:
- KD+MA: signals from the KD and moving average lines
- KD+BB: signals from KD lines and Bollinger bands
- KD+Div: signals from the KD and divergence lines
- KD+MA+BB: three signals simultaneously
- KD+MA+Div: three signals at the same time
- KD+BB+Div: three signals at the same time
- KD+MA+BB+Div: all four signals at the same time
- When to use: for more reliable but rare signals
🔌 Connecting to trading strategies
The indicator can be connected to your trading strategies using 6 different channels.:
1. Connector KD signals: connects only the signals from the intersection of lines K and D
2. Connector MA signals: connects only signals from moving averages
3. Connector BB signal: connects only the signals from the Bollinger bands
4. Connector divergence signals: connects only divergence signals
5. Combined Connector: connects any signals
6. Connector for "And" mode: connects only combined signals
🔔 Setting up alerts
The indicator can send alerts when alarms appear.:
- Alerts for KD: when the %K line crosses the %D line
- Alerts for MA: when stochastic crosses the moving average
- Alerts for BB: when stochastic crosses the Bollinger bands
- Divergence alerts: when a divergence is detected
- Combined alerts: for all types of alarms
- Alerts for "And" mode: for combined signals
🎭 What does the indicator look like on the chart ?
- Main lines K and D: blue and orange lines
- Overbought/oversold levels: horizontal lines at levels 20 and 80
- Middle line: dotted line at level 50
- Stochastic Moving Average: yellow line
- Bollinger bands: green lines around the moving average
- Signals: green and red triangles with corresponding labels
📚 How to start using Stochastic Fusion Elite
1️⃣ Initial setup
- Add an indicator to your chart
- Select the types of signals you want to use (KD, MA, BB, Div)
- Adjust the period and smoothing for the K and D lines
2️⃣ Filter settings
- Set the distance between the signals to get rid of unnecessary noise
- Adjust stochastic, MFI and RSI levels depending on the volatility of your asset
- If you need more reliable signals, turn on the "Waiting for the opposite signal" mode.
3️⃣ Operation mode selection
- First, use the standard mode to see all possible signals.
- When you get comfortable, try the "And" mode for rarer signals.
4️⃣ Setting up Alerts
- Select the types of signals you want to be notified about
- Set up alerts for these types of signals
5️⃣ Verification and adaptation
- Check the operation of the indicator on historical data
- Adjust the parameters for a specific asset
- Adapt the settings to your trading style
🌟 Usage examples
For trend trading
- Use the KD and MA signals in the direction of the main trend
- Set the distance between the signals
- Set stricter levels for filters
For trading in a sideways range
- Use BB signals to detect bounces from the range boundaries
- Use a stochastic level filter to confirm overbought/oversold conditions
- Adjust the Bollinger bands according to the width of the range
To determine the pivot points
- Pay attention to the divergence signals
- Set the distance between the signals
- Check the MFI and RSI filters for additional confirmation
Cross Alert with Configurable Rectangles**Description:**
This TradingView script, **"Cross Alert with Configurable Rectangles"**, is a technical analysis tool designed to help traders visualize and analyze market trends effectively. It combines configurable moving averages with customizable timeframe-based rectangles for highlighting price ranges.
### Features:
1. **Moving Averages:**
- Calculates and plots an Exponential Moving Average (EMA) and a Simple Moving Average (SMA) based on user-defined lengths.
- Provides both short and long moving averages to identify potential trend reversals or confirmations.
2. **Customizable Timeframe Rectangles:**
- Dynamically draws rectangles around price action based on user-selected timeframes: **Hourly (60 minutes), Daily, Weekly, or Monthly.**
- Automatically updates the rectangles to reflect high and low price levels within the selected timeframe.
- Customizable rectangle color and transparency for better chart visibility.
3. **Dynamic Line Projections:**
- Projects the trend of the long and short moving averages forward in time to help anticipate price movements.
### Use Case:
This script is ideal for traders who want to:
- Identify key support and resistance levels within different timeframes.
- Analyze price behavior relative to moving averages.
- Spot potential trend changes by observing price interaction with the moving averages and timeframe rectangles.
The script is fully configurable, allowing traders to adapt it to their trading strategy and preferences.
[blackcat] L1 Banker Move█ OVERVIEW
The Pine Script is an indicator designed to analyze market signals for institutional and short-term investors. It calculates and plots three main signals: Institutional Signal, Institutional Build, and Short-Term Investor Signal. The script uses a combination of price, volume, and moving average data to generate these signals, which can help traders identify potential buying or selling opportunities.
█ LOGICAL FRAMEWORK
The script is structured into several main sections:
1 — Input Parameters
The script does not explicitly define any input parameters, relying on default values for calculations.
2 — Custom Functions
• reference_value(values, length) : Retrieves the first non-NA value from a specified number of past values.
• calculate_institutional_and_short_term_signals(low, close, open, volume) : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
3 — Calculations
• Price and Volume Metrics: The script calculates various smoothed price changes, lowest and highest values over different periods, and volume-weighted prices.
• Moving Averages: It computes simple moving averages (SMA) and exponential moving averages (EMA) for different periods.
• RSI Calculation: The script calculates a custom RSI for different periods.
• Signal Generation: It generates the institutional and short-term investor signals based on the calculated metrics.
4 — Plotting
The script plots the three main signals on the chart using the plot function.
The flow of data and logic is as follows:
• The reference_value function is used to find reference values for calculations.
• The calculate_institutional_and_short_term_signals function performs the core calculations and returns the institutional and short-term investor signals.
• The main script calls this function and plots the results.
█ CUSTOM FUNCTIONS
1 — reference_value(values, length)
• Purpose : Retrieves the first non-NA value from a specified number of past values.
• Parameters :
• values: An array of values.
• length: The number of past values to consider.
• Return Value : The first non-NA value found or na if no valid value is found.
• Functionality : Iterates through the specified number of past values and returns the first non-NA value.
2 — calculate_institutional_and_short_term_signals(low, close, open, volume)
• Purpose : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
• Parameters :
• low: Low price series.
• close: Close price series.
• open: Open price series.
• volume: Volume series.
• Return Values :
• institutional_signal: The institutional signal.
• institutional_build: The institutional build signal.
• short_term_investor_signal: The short-term investor signal.
• Functionality :
• Computes various price and volume metrics.
• Calculates moving averages and volume-weighted prices.
• Generates the institutional and short-term investor signals based on these metrics.
█ KEY POINTS AND TECHNIQUES
1 — Advanced Pine Script Features
• Custom Functions: The script defines and uses custom functions to encapsulate complex logic.
• Conditional Statements: Extensive use of iff and if statements to control the flow of calculations.
• Looping Constructs: The for loop in reference_value function to iterate through past values.
• Exponential Moving Averages (EMA): Used to smooth out price and signal changes.
• Volume-Weighted Price (VWP): Calculated to factor in volume in price analysis.
• Custom RSI Calculation: A custom RSI formula is used, which differs from the standard RSI calculation.
2 — Optimization Techniques
• Efficient Data Handling: The reference_value function efficiently finds the first non-NA value without unnecessary computations.
• Smoothed Signals: Using EMAs to smooth out noisy signals for better trend identification.
3 — Unique Approaches
• Combination of Metrics: The script combines multiple metrics (price, volume, moving averages, and custom RSI) to generate comprehensive signals.
• Institutional Build Signal: A unique approach to detect institutional activity by comparing current price levels with historical lows and smoothed price changes.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
1 — Potential Modifications
• Input Parameters: Add input parameters to allow users to customize the lengths and thresholds used in the calculations.
• Strategy Version: Convert the indicator into a strategy by adding buy/sell signals based on the generated signals.
• Additional Indicators: Integrate other technical indicators (e.g., MACD, Bollinger Bands) to enhance the signal generation process.
2 — Similar Trading Scenarios
• Institutional Activity Analysis: Use similar techniques to analyze institutional activity in other markets or assets.
• Volume Analysis: Apply the volume-weighted price and volume analysis to identify significant price movements.
• Multi-Timeframe Analysis: Extend the script to analyze signals across multiple timeframes for a more robust trading strategy.
3 — Related Pine Script Concepts
• Pine Script Functions: Understanding how to define and use custom functions effectively.
• Conditional Logic: Mastering the use of iff and if statements for complex logic.
• Looping Constructs: Familiarity with for loops for iterating through data.
• Moving Averages: Knowledge of different types of moving averages and their applications.
• Volume Analysis: Techniques for incorporating volume data into price analysis.
Atlantean Bitcoin Weekly Market Condition - Top/Bottom BTC Overview:
The "Atlantean Bitcoin Weekly Market Condition Detector - Top/Bottom BTC" is a specialized TradingView indicator designed to identify significant turning points in the Bitcoin market on a weekly basis. By analyzing long-term and short-term moving averages across two distinct resolutions, this indicator provides traders with valuable insights into potential market bottoms and tops, as well as the initiation of bull markets.
Key Features:
Market Bottom Detection: The script uses a combination of a simple moving average (SMA) and an exponential moving average (EMA) calculated over long and short periods to identify potential market bottoms. When these conditions are met, the script signals a "Market Bottom" label on the chart, indicating a possible buying opportunity.
Bull Market Start Indicator: When the short-term EMA crosses above the long-term SMA, it signals the beginning of a bull market. This is marked by a "Bull Market Start" label on the chart, helping traders to prepare for potential market upswings.
Market Top Detection: The script identifies potential market tops by analyzing the crossunder of long and short-term moving averages. A "Market Top" label is plotted, suggesting a potential selling point.
Customizable Moving Averages Display: Users can choose to display the moving averages used for detecting market tops and bottoms, providing additional insights into market conditions.
How It Works: The indicator operates by monitoring the interactions between the specified moving averages:
Market Bottom: Detected when the long-term SMA (adjusted by a factor of 0.745) crosses over the short-term EMA.
Bull Market Start: Detected when the short-term EMA crosses above the long-term SMA.
Market Top: Detected when the long-term SMA (adjusted by a factor of 2) crosses under the short-term SMA.
These conditions are highlighted on the chart, allowing traders to visualize significant market events and make informed decisions.
Intended Use: This indicator is best used on weekly Bitcoin charts. It’s designed to provide long-term market insights rather than short-term trading signals. Traders can use this tool to identify strategic entry and exit points during major market cycles. The optional display of moving averages can further enhance understanding of market dynamics.
Originality and Utility: Unlike many other indicators, this script not only highlights traditional market tops and bottoms but also identifies the aggressive start of bull markets, offering a comprehensive view of market conditions. The unique combination of adjusted moving averages makes this script a valuable tool for long-term Bitcoin traders.
Disclaimer: The signals provided by this indicator are based on historical data and mathematical calculations. They do not guarantee future market performance. Traders should use this tool as part of a broader trading strategy and consider other factors before making trading decisions. Not financial advice.
Happy Trading!
By Atlantean
Alpha-Sutte Multi-Price Indicator [CHE] Overview
The AlphaSutte MultiPrice Indicator is a powerful tool for forecasting market movements and generating trading signals. At its core is the AlphaSutte Model, which stands out for its innovative approach to predicting future price movements.
Inspired by the () on TradingView, this indicator enhances the original concept by integrating it with the T3 smoothing technique to improve trend identification and signal reliability.
The AlphaSutte Model
The AlphaSutte Model is a mathematical method for forecasting prices based on the analysis of historical price data. It is applied to various price components such as High, Low, Open, and Close. The model predicts future values using differences and weighted averages of previous periods. Here are the key steps and components of the AlphaSutte Model:
1. Data Extraction:
The model extracts historical values at specified intervals. For example, it uses the values from the last four periods for calculations.
2. Difference Calculations:
Differences between successive historical values are calculated:
Delta_x: Difference between the first and fourth values.
Delta_y: Difference between the second and first values.
Delta_z: Difference between the third and second values.
3. Weighted Average Calculation:
These differences are then integrated into a weighted average to forecast the future value:
The weighted average combines the historical values and their differences to calculate the forecasted value, referred to as a_t.
4. Application to Price Components:
The AlphaSutte Model can be applied to various price components:
High: Forecasting the future high price.
Low: Forecasting the future low price.
Open: Forecasting the future opening price.
Close: Forecasting the future closing price.
5. Averaging AlphaSutte Values:
If multiple price components are used for calculation, an average of the AlphaSutte values is computed. This average serves as the basis for generating trading signals.
Trading Signals and Directional Change
The AlphaSutte Model is used to generate long and short trading signals. These signals are confirmed by the directional change of the T3 Indicator to enhance reliability:
Long Signals:
A long signal is generated when the average value of the AlphaSutte Model is positive, and the T3 indicator previously showed a downtrend.
These signals are displayed with green labels and lines on the chart.
Short Signals:
A short signal is generated when the average value of the AlphaSutte Model is negative, and the T3 indicator previously showed an uptrend.
These signals are displayed with red labels and lines on the chart.
StepbyStep Explanation of the Script
The AlphaSutte MultiPrice Indicator script in TradingView is designed to provide comprehensive market trend analysis and trading signal generation. Here is a stepbystep explanation of how the script operates:
1. Input Parameters:
The script begins by defining several input parameters for the T3 indicator and AlphaSutte Model, including:
`t3Length`: The length of the T3 moving average.
`t3VolumeFactor`: The volume factor used in T3 smoothing.
Boolean inputs to determine which price components (High, Low, Open, Close) should use the AlphaSutte Model.
`numLastLabels`: The number of last labels to display for recent signals.
2. T3 Smoothing Function:
The `t3Smoothing` function calculates the T3 smoothed value for the specified source price using a series of exponential moving averages (EMAs):
It calculates six sequential EMAs of the source price.
It then combines these EMAs using specific coefficients to obtain the T3 value.
3. AlphaSutte Calculation Function:
The `get_alpha_sutte` function forecasts future values based on historical price data:
It extracts historical price values at specific intervals.
It calculates the differences (deltas) between these values.
It computes a weighted average of these deltas to obtain the AlphaSutte value.
4. Calculating AlphaSutte Components:
The script calculates the AlphaSutte values for the selected price components (High, Low, Open, Close) based on user input.
It then averages these values if multiple components are selected.
5. Generating Long and Short Conditions:
The script defines conditions for generating long and short signals based on the AlphaSutte average:
`long_condition`: True if the AlphaSutte average is positive.
`short_condition`: True if the AlphaSutte average is negative.
6. Tracking T3 Trend Direction:
The script updates state variables to track whether the T3 line is in an uptrend or downtrend:
`t3_uptrend`: True if the T3 value is higher than the previous T3 value.
`t3_downtrend`: True if the T3 value is lower than the previous T3 value.
7. Generating and Managing Labels and Lines:
The script generates labels and lines on the chart to visualize long and short signals:
For long signals, green labels and lines are created when the long condition is met, and the T3 was previously in a downtrend.
For short signals, red labels and lines are created when the short condition is met, and the T3 was previously in an uptrend.
Old labels and lines are deleted to keep the chart clean and relevant.
8. Updating Lines to Current Candle:
The script dynamically updates the end points of the lines to the current candle to reflect the latest market data.
9. Highlighting Movements:
The script optionally highlights the T3 line based on its direction to visually emphasize the trend:
Green for an uptrend and red for a downtrend.
10. Plotting the T3 Line:
Finally, the T3 line is plotted on the chart with the specified color and line width to provide a clear visualization of the trend.
Conclusion
The primary focus of the AlphaSutte MultiPrice Indicator is on the forecasting capabilities of the AlphaSutte Model. This model's forecasts are the most critical part of the indicator, providing the essential signals for potential market movements. The T3 indicator serves as a confirmation tool, validating these forecasts by indicating the direction of the trend. This combination enhances the reliability of the trading signals, making the AlphaSutte MultiPrice Indicator a valuable asset for traders looking to make informed decisions based on robust market analysis.
Best regards Chervolino
Leading T3Hello Fellas,
Here, I applied a special technique of John F. Ehlers to make lagging indicators leading. The T3 itself is usually not realling the classic lagging indicator, so it is not really needed, but I still publish this indicator to demonstrate this technique of Ehlers applied on a simple indicator.
The indicator does not repaint.
In the following picture you can see a comparison of normal T3 (purple) compared to a 2-bar "leading" T3 (gradient):
The range of the gradient is:
Bottom Value: the lowest slope of the last 100 bars -> green
Top Value: the highest slope of the last 100 bars -> purple
Ehlers Special Technique
John Ehlers did develop methods to make lagging indicators leading or predictive. One of these methods is the Predictive Moving Average, which he introduced in his book “Rocket Science for Traders”. The concept is to take a difference of a lagging line from the original function to produce a leading function.
The idea is to extend this concept to moving averages. If you take a 7-bar Weighted Moving Average (WMA) of prices, that average lags the prices by 2 bars. If you take a 7-bar WMA of the first average, this second average is delayed another 2 bars. If you take the difference between the two averages and add that difference to the first average, the result should be a smoothed line of the original price function with no lag.
T3
To compute the T3 moving average, it involves a triple smoothing process using exponential moving averages. Here's how it works:
Calculate the first exponential moving average (EMA1) of the price data over a specific period 'n.'
Calculate the second exponential moving average (EMA2) of EMA1 using the same period 'n.'
Calculate the third exponential moving average (EMA3) of EMA2 using the same period 'n.'
The formula for the T3 moving average is as follows:
T3 = 3 * (EMA1) - 3 * (EMA2) + (EMA3)
By applying this triple smoothing process, the T3 moving average is intended to offer reduced noise and improved responsiveness to price trends. It achieves this by incorporating multiple time frames of the exponential moving averages, resulting in a more accurate representation of the underlying price action.
Thanks for checking this out and give a boost, if you enjoyed the content.
Best regards,
simwai
---
Credits to @loxx
[AIO] Multi Collection Moving Averages 140 MA TypesAll In One Multi Collection Moving Averages.
Since signing up 2 years ago, I have been collecting various Сollections.
I decided to get it into a decent shape and make it one of the biggest collections on TV, and maybe the entire internet.
And now I'm sharing my collection with you.
140 Different Types of Moving Averages are waiting for you.
Specifically :
"
AARMA | Adaptive Autonomous Recursive Moving Average
ADMA | Adjusted Moving Average
ADXMA | Average Directional Moving Average
ADXVMA | Average Directional Volatility Moving Average
AHMA | Ahrens Moving Average
ALF | Ehler Adaptive Laguerre Filter
ALMA | Arnaud Legoux Moving Average
ALSMA | Adaptive Least Squares
ALXMA | Alexander Moving Average
AMA | Adaptive Moving Average
ARI | Unknown
ARSI | Adaptive RSI Moving Average
AUF | Auto Filter
AUTL | Auto-Line
BAMA | Bryant Adaptive Moving Average
BFMA | Blackman Filter Moving Average
CMA | Corrected Moving Average
CORMA | Correlation Moving Average
COVEMA | Coefficient of Variation Weighted Exponential Moving Average
COVNA | Coefficient of Variation Weighted Moving Average
CTI | Coral Trend Indicator
DEC | Ehlers Simple Decycler
DEMA | Double EMA Moving Average
DEVS | Ehlers - Deviation Scaled Moving Average
DONEMA | Donchian Extremum Moving Average
DONMA | Donchian Moving Average
DSEMA | Double Smoothed Exponential Moving Average
DSWF | Damped Sine Wave Weighted Filter
DWMA | Double Weighted Moving Average
E2PBF | Ehlers 2-Pole Butterworth Filter
E2SSF | Ehlers 2-Pole Super Smoother Filter
E3PBF | Ehlers 3-Pole Butterworth Filter
E3SSF | Ehlers 3-Pole Super Smoother Filter
EDMA | Exponentially Deviating Moving Average (MZ EDMA)
EDSMA | Ehlers Dynamic Smoothed Moving Average
EEO | Ehlers Modified Elliptic Filter Optimum
EFRAMA | Ehlers Modified Fractal Adaptive Moving Average
EHMA | Exponential Hull Moving Average
EIT | Ehlers Instantaneous Trendline
ELF | Ehler Laguerre filter
EMA | Exponential Moving Average
EMARSI | EMARSI
EPF | Edge Preserving Filter
EPMA | End Point Moving Average
EREA | Ehlers Reverse Exponential Moving Average
ESSF | Ehlers Super Smoother Filter 2-pole
ETMA | Exponential Triangular Moving Average
EVMA | Elastic Volume Weighted Moving Average
FAMA | Following Adaptive Moving Average
FEMA | Fast Exponential Moving Average
FIBWMA | Fibonacci Weighted Moving Average
FLSMA | Fisher Least Squares Moving Average
FRAMA | Ehlers - Fractal Adaptive Moving Average
FX | Fibonacci X Level
GAUS | Ehlers - Gaussian Filter
GHL | Gann High Low
GMA | Gaussian Moving Average
GMMA | Geometric Mean Moving Average
HCF | Hybrid Convolution Filter
HEMA | Holt Exponential Moving Average
HKAMA | Hilbert based Kaufman Adaptive Moving Average
HMA | Harmonic Moving Average
HSMA | Hirashima Sugita Moving Average
HULL | Hull Moving Average
HULLT | Hull Triple Moving Average
HWMA | Henderson Weighted Moving Average
IE2 | Early T3 by Tim Tilson
IIRF | Infinite Impulse Response Filter
ILRS | Integral of Linear Regression Slope
JMA | Jurik Moving Average
KA | Unknown
KAMA | Kaufman Adaptive Moving Average & Apirine Adaptive MA
KIJUN | KIJUN
KIJUN2 | Kijun v2
LAG | Ehlers - Laguerre Filter
LCLSMA | 1LC-LSMA (1 line code lsma with 3 functions)
LEMA | Leader Exponential Moving Average
LLMA | Low-Lag Moving Average
LMA | Leo Moving Average
LP | Unknown
LRL | Linear Regression Line
LSMA | Least Squares Moving Average / Linear Regression Curve
LTB | Unknown
LWMA | Linear Weighted Moving Average
MAMA | MAMA - MESA Adaptive Moving Average
MAVW | Mavilim Weighted Moving Average
MCGD | McGinley Dynamic Moving Average
MF | Modular Filter
MID | Median Moving Average / Percentile Nearest Rank
MNMA | McNicholl Moving Average
MTMA | Unknown
MVSMA | Minimum Variance SMA
NLMA | Non-lag Moving Average
NWMA | Dürschner 3rd Generation Moving Average (New WMA)
PKF | Parametric Kalman Filter
PWMA | Parabolic Weighted Moving Average
QEMA | Quadruple Exponential Moving Average
QMA | Quick Moving Average
REMA | Regularized Exponential Moving Average
REPMA | Repulsion Moving Average
RGEMA | Range Exponential Moving Average
RMA | Welles Wilders Smoothing Moving Average
RMF | Recursive Median Filter
RMTA | Recursive Moving Trend Average
RSMA | Relative Strength Moving Average - based on RSI
RSRMA | Right Sided Ricker MA
RWMA | Regressively Weighted Moving Average
SAMA | Slope Adaptive Moving Average
SFMA | Smoother Filter Moving Average
SMA | Simple Moving Average
SSB | Senkou Span B
SSF | Ehlers - Super Smoother Filter P2
SSMA | Super Smooth Moving Average
STMA | Unknown
SWMA | Self-Weighted Moving Average
SW_MA | Sine-Weighted Moving Average
TEMA | Triple Exponential Moving Average
THMA | Triple Exponential Hull Moving Average
TL | Unknown
TMA | Triangular Moving Average
TPBF | Three-pole Ehlers Butterworth
TRAMA | Trend Regularity Adaptive Moving Average
TSF | True Strength Force
TT3 | Tilson (3rd Degree) Moving Average
VAMA | Volatility Adjusted Moving Average
VAMAF | Volume Adjusted Moving Average Function
VAR | Vector Autoregression Moving Average
VBMA | Variable Moving Average
VHMA | Vertical Horizontal Moving Average
VIDYA | Variable Index Dynamic Average
VMA | Volume Moving Average
VSO | Unknown
VWMA | Volume Weighted Moving Average
WCD | Unknown
WMA | Weighted Moving Average
XEMA | Optimized Exponential Moving Average
ZEMA | Zero Lag Moving Average
ZLDEMA | Zero-Lag Double Exponential Moving Average
ZLEMA | Ehlers - Zero Lag Exponential Moving Average
ZLTEMA | Zero-Lag Triple Exponential Moving Average
ZSMA | Zero-Lag Simple Moving Average
"
Don't forget that you can use any Moving Average not only for the chart but also for any of your indicators without affecting the code as in my example.
But remember that some MAs are not designed to work with anything other than a chart.
All MA and Code lists are sorted strictly alphabetically by short name (A-Z).
Each MA has its own number (ID) by which you can display the Moving Average you need.
Next to the ID selection there are tooltips with short names and their numbers. Use them.
The panel below will help you to read the Name of the selected MA.
Because of the size of the collection I think this is the optimal and most convenient use. Correct me if this is not the case.
Unknown - Some MAs I collected so long ago that I lost the full real name and couldn't find the authors. If you recognize them, please let me know.
I have deliberately simplified all MAs to input just Source and Length.
Because the collection is so large, it would be quite inconvenient and difficult to customize all MA functions (multipliers, offset, etc.).
If you need or like any MA you will still have to take it from my collection for your code.
I tried to leave the basic MA settings inside function in first strings.
I have tried to list most of the authors, but since the bulk of the collection was created a long time ago and was not intended for public publication I could not find all of them.
Some of the features were created from scratch or may have been slightly modified, so please be careful.
If you would like to improve this collection, please write to me in PM.
Also Credits, Likes, Awards, Loves and Thanks to :
@alexgrover
@allanster
@andre_007
@auroagwei
@blackcat1402
@bsharpe
@cheatcountry
@CrackingCryptocurrency
@Duyck
@ErwinBeckers
@everget
@glaz
@gotbeatz26107
@HPotter
@io72signals
@JacobAmos
@JoshuaMcGowan
@KivancOzbilgic
@LazyBear
@loxx
@LuxAlgo
@MightyZinger
@nemozny
@NGBaltic
@peacefulLizard50262
@RicardoSantos
@StalexBot
@ThiagoSchmitz
@TradingView
— 𝐀𝐧𝐝 𝐎𝐭𝐡𝐞𝐫𝐬 !
So just a Big Thank You to everyone who has ever and anywhere shared their codes.
JC MAs: SMA, WMA, EMA, DEMA, TEMA, ALMA, Hull, Kaufman, FractalThe best collection of moving averages anywhere. I know, because I searched, couldn't find the right collection, and so wrote it myself!
-------------------------------------------------------------------------------
Notable features that either aren't found anywhere else...or at least in one place:
-------------------------------------------------------------------------------
• The "Triple Exponential Moving Average", is actually that mathematically - rather than "three seperate EMA graphs", as is commonly found on Trading View.
• Includes exotic moving averages: Hull Moving Average (HMA), Kaufman's Adaptive Moving Average (KAMA), and Fractal Apaptive Moving Average (FrAMA).
• Each moving average has its own user-definable averaging length in DAYS, rather than an abstract "length". This is respected even for different graphing resolutions, and different chart views - even for the more exotic MAs.
• Days can be fractional.
• A master time resolution ("Timeframe") is also user-definable. And unlike most other moving average charts, this won't affect the internal "length" variable (specified days are still respected), it only changes the graphing resolution. You can also specify to use chart's resolution - which, as you know, is not very useful for moving averages - yet so many moving average scripts on Trading View don't let you specify otherwise.
• If every CPU cycle counts, you can set "days" to 0 to prevent a particular unneeded moving average from being calculated at all.
• Includes a custom moving average that is unique, if you're looking for a tiny edge in TA to beat everyone else looking at the same stuff: a customizable weighted blend of SMA, TEMA, HMA, KAMA, and FrMA. (Note: The weights for these blends don't have to add up to 100, they will self-level no matter what they add up to.)
• By default, the averages are color-coded according to rainbow order of light spectrum frequency, relative to approximate responsiveness to current price: Red (SMA) is the laziest, violet (FrAMA) is the most hyper, and green is in the middle.
-------------------------------------------------------------------------------
Contains the following moving averages, in order of responsiveness:
-------------------------------------------------------------------------------
• Simple Moving Average (SMA)
• Arnaud Legoux Moving Average (ALMA)
• Exponential Moving Average (EMA)
• Weighted Moving Average (WMA)
• Blend average of SMA and TEMA (JCBMA)
• Double Exponential Moving Average (DEMA)
• Triple Exponential Moving Average (TEMA)
• Hull Moving Average (HMA)
• Kaufman's Adaptive Moving Average (KAMA)
• Fractal Apaptive Moving Average (FrAMA)
Note: There are a few extreme edge cases where the graphs won't render, which are obvious. (Because they won't render.) In which case, all you need to do is choose a more sane master resolution ("Timeframe") relative to the timeframe of the chart. This is more about the limits of Trading View, than specific script bugs.
-------------------------------------------------------------------------------
Includes reworked code snippets
-------------------------------------------------------------------------------
• "Kaufman Moving Average Adaptive (KAMA)" by HPotter
• "FRAMA (Ehlers true modified calculation)" by nemozny
• Which in turn was based on "Fractal Adaptive Moving Average (real one)" by Shizaru
T3 [DCAUT]█ T3
📊 INDICATOR OVERVIEW
The T3 Moving Average is a smoothing indicator developed by Tim Tillson and published in Technical Analysis of Stocks & Commodities magazine (January 1998). The algorithm applies Generalized DEMA (Double Exponential Moving Average) recursively three times, creating a six-pole filtering effect that aims to balance noise reduction with responsiveness while minimizing lag relative to price changes.
📐 MATHEMATICAL FOUNDATION
Generalized DEMA (GD) Function:
The core building block is the Generalized DEMA function, which combines two exponential moving averages with weights controlled by the volume factor:
GD(input, v) = EMA(input) × (1 + v) - EMA(EMA(input)) × v
Where v is the volume factor parameter (default 0.7). This weighted combination reduces lag while maintaining smoothness by extrapolating beyond the first EMA using the double-smoothed EMA as a reference.
T3 Calculation Process:
T3 applies the GD function three times recursively:
T3 = GD(GD(GD(Price, v), v), v)
This triple nesting creates a six-pole smoothing effect (each GD applies two EMA operations, resulting in 2 × 3 = 6 total EMA calculations). The cascading refinement progressively filters noise while preserving trend information.
Step-by-Step Breakdown:
First GD application: GD1 = EMA(Price) × (1 + v) - EMA(EMA(Price)) × v - Creates initial smoothed series with lag reduction
Second GD application: GD2 = EMA(GD1) × (1 + v) - EMA(EMA(GD1)) × v - Further refines the smoothing while maintaining responsiveness
Third GD application: T3 = EMA(GD2) × (1 + v) - EMA(EMA(GD2)) × v - Final refinement produces the T3 output
Volume Factor Impact:
The volume factor (v) is the key parameter controlling the balance between smoothness and responsiveness. Tim Tillson recommended v = 0.7 as the optimal default value.
Lower volume factors (v closer to 0.0): Increase the extrapolation effect, making T3 more responsive to price changes but potentially more sensitive to noise.
Higher volume factors (v closer to 1.0): Reduce the extrapolation effect, producing smoother output with less sensitivity to short-term fluctuations but slightly more lag.
The recursive application of the volume factor through three GD stages creates a nonlinear filtering effect that achieves superior lag reduction compared to traditional moving averages of equivalent smoothness.
📊 SIGNAL INTERPRETATION
Trend Direction Signals:
Green Line (T3 Rising): Smoothed trend line is rising, may indicate uptrend, consider bullish opportunities when confirmed by other factors
Red Line (T3 Falling): Smoothed trend line is falling, may indicate downtrend, consider bearish opportunities when confirmed by other factors
Gray Line (T3 Flat): Smoothed trend line is flat, indicates unclear trend or consolidation phase
Price Crossover Signals:
Price Crosses Above T3: Price breaks above smoothed trend line, may be bullish signal, requires confirmation from other indicators
Price Crosses Below T3: Price breaks below smoothed trend line, may be bearish signal, requires confirmation from other indicators
Price Position Relative to T3: Price sustained above T3 may indicate uptrend, sustained below may indicate downtrend
Supporting Analysis Signals:
T3 Slope Angle: Steeper slopes indicate stronger trend momentum, flatter slopes suggest weakening trends
Price Deviation: Significant price separation from T3 may indicate overextension, watch for pullback or reversal
Dynamic Support/Resistance: T3 line can serve as dynamic support (in uptrends) or resistance (in downtrends) reference
🎯 STRATEGIC APPLICATIONS
Common Usage Patterns:
The T3 Moving Average can be incorporated into trading analysis in various ways. These represent common approaches used by market participants, though effectiveness varies by market conditions and requires individual testing:
Trend Filtering:
T3 can be used as a trend filter by observing the relationship between price and the T3 line. The color-coded slope (green for rising, red for falling, gray for sideways) provides visual feedback about the current trend direction of the smoothed series.
Price Crossover Analysis:
Some traders monitor crossovers between price and the T3 line as potential indication points. When price crosses the T3 line, it may suggest a change in the relationship between current price action and the smoothed trend.
Multi-Timeframe Observation:
T3 can be applied to multiple timeframes simultaneously. Observing alignment or divergence between different timeframe T3 indicators may provide context about trend consistency across time scales.
Dynamic Reference Level:
The T3 line can serve as a dynamic reference level for price action analysis. Price distance from T3, price reactions when approaching T3, and the behavior of price relative to the T3 line can all be incorporated into market analysis frameworks.
Application Considerations:
Any trading application should be thoroughly tested on historical data before implementation
T3 performance characteristics vary across different market conditions and asset types
The indicator provides smoothed trend information but does not predict future price movements
Combining T3 with other analytical tools and market context improves analysis quality
Risk management practices remain essential regardless of the analytical approach used
📋 DETAILED PARAMETER CONFIGURATION
Source Selection:
Close Price (Default): Standard choice for end-of-period trend analysis, reduces intrabar noise
HL2 (High+Low)/2: Provides balanced view of price action, considers full bar range
HLC3 or OHLC4: Incorporates more price information, may provide smoother results
Selection Impact: Different sources affect signal timing and smoothness characteristics
Length Configuration:
Shorter periods: More responsive, faster reaction, frequent signals, but higher false signal risk in choppy markets
Longer periods: Smoother output, fewer signals, better for long-term trends, but slower response
Default 14 periods is a common baseline, but optimal length varies by asset, timeframe, and market conditions
Parameter selection should be determined through backtesting rather than general recommendations
Volume Factor Configuration:
Lower values (closer to 0.0): Increase responsiveness but also noise sensitivity
Higher values (closer to 1.0): Increase smoothness but slightly more lag
Default 0.7 (Tim Tillson's recommendation) provides good balance for most applications
Optimal value depends on signal frequency versus reliability preference, test for specific use case
Parameter Optimization Approach:
There are no universal "best" parameter values - optimal settings depend on the specific asset, timeframe, market regime, and trading strategy
Start with default values (Length: 14, Volume Factor: 0.7) and adjust based on observed performance in your target market
Conduct systematic backtesting across different market conditions to evaluate parameter sensitivity
Consider that parameters optimized for historical data may not perform identically in future market conditions
Monitor performance and be prepared to adjust parameters as market characteristics evolve
📈 DESIGN FEATURES & MARKET ADAPTATION
Algorithm Design Features:
Simple Moving Average (SMA): Equal weighting across lookback period
Exponential Moving Average (EMA): Exponentially decreasing weights on historical prices
T3 Moving Average: Recursive Generalized DEMA with adjustable volume factor
Market Condition Adaptation:
Trending markets: Smoothed indicators generally align more closely with sustained directional movement
Ranging markets: All moving averages may generate more crossover signals during non-trending periods
Volatile conditions: Higher smoothing parameters reduce short-term sensitivity but increase lag
Indicator behavior relative to market conditions should be evaluated for specific applications
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. The T3 Moving Average has limitations and should not be used as the sole basis for trading decisions. Like all trend-following indicators, its performance varies with market conditions, and past signal characteristics do not guarantee future results.
Key Points:
T3 is a lagging indicator that responds to price changes rather than predicting future movements
Signals should be confirmed with other technical tools and market context
Parameters should be optimized for specific market and timeframe
Risk management and position sizing are essential
Market regime changes can affect indicator effectiveness
Test strategies thoroughly on historical data before live implementation
Consider broader market context and fundamental factors
On-Chain Signals [LuxAlgo]The On-Chain Signals indicator uses fundamental blockchain metrics to provide traders with an objective technical view of their favorite cryptocurrencies.
It uses IntoTheBlock datasets integrated within TradingView to generate four key signals: Net Network Growth, In the Money, Concentration, and Large Transactions.
Together, these four signals provide traders with an overall directional bias of the market. All of the data can be visualized as a gauge, table, historical plot, or average.
🔶 USAGE
The main goal of this tool is to provide an overall directional bias based on four blockchain signals, each with three possible biases: bearish, neutral, or bullish. The thresholds for each signal bias can be adjusted on the settings panel.
These signals are based on IntoTheBlock's On-Chain Signals.
Net network growth: Change in the total number of addresses over the last seven periods; i.e., how many new addresses are being created.
In the Money: Change in the seven-period moving average of the total supply in the money. This shows how many addresses are profitable.
Concentration: Change in the aggregate addresses of whales and investors from the previous period. These are addresses holding at least 0.1% of the supply. This shows how many addresses are in the hands of a few.
Large Transactions: Changes in the number of transactions over $100,000. This metric tracks convergence or divergence from the 21- and 30-day EMAs and indicates the momentum of large transactions.
All of these signals together form the blockchain's overall directional bias.
Bearish: The number of bearish individual signals is greater than the number of bullish individual signals.
Neutral: The number of bearish individual signals is equal to the number of bullish individual signals.
Bullish: The number of bullish individual signals is greater than the number of bearish individual signals.
If the overall directional bias is bullish, we can expect the price of the observed cryptocurrency to increase. If the bias is bearish, we can expect the price to decrease. If the signal is neutral, the price may be more likely to stay the same.
Traders should be aware of two things. First, the signals provide optimal results when the chart is set to the daily timeframe. Second, the tool uses IntoTheBlock data, which is available on TradingView. Therefore, some cryptocurrencies may not be available.
🔹 Display Mode
Traders have three different display modes at their disposal. These modes can be easily selected from the settings panel. The gauge is set by default.
🔹 Gauge
The gauge will appear in the center of the visible space. Traders can adjust its size using the Scale parameter in the Settings panel. They can also give it a curved effect.
The number of bars displayed directly affects the gauge's resolution: More bars result in better resolution.
The chart above shows the effect that different scale configurations have on the gauge.
🔹 Historical Data
The chart above shows the historical data for each of the four signals.
Traders can use this mode to adjust the thresholds for each signal on the settings panel to fit the behavior of each cryptocurrency. They can also analyze how each metric impacts price behavior over time.
🔹 Average
This display mode provides an easy way to see the overall bias of past prices in order to analyze price behavior in relation to the underlying blockchain's directional bias.
The average is calculated by taking the values of the overall bias as -1 for bearish, 0 for neutral, and +1 for bullish, and then applying a triangular moving average over 20 periods by default. Simple and exponential moving averages are available, and traders can select the period length from the settings panel.
🔶 DETAILS
The four signals are based on IntoTheBlock's On-Chain Signals. We gather the data, manipulate it, and build the signals depending on each threshold.
Net network growth
float netNetworkGrowthData = customData('_TOTALADDRESSES')
float netNetworkGrowth = 100*(netNetworkGrowthData /netNetworkGrowthData - 1)
In the Money
float inTheMoneyData = customData('_INOUTMONEYIN')
float averageBalance = customData('_AVGBALANCE')
float inTheMoneyBalance = inTheMoneyData*averageBalance
float sma = ta.sma(inTheMoneyBalance,7)
float inTheMoney = ta.roc(sma,1)
Concentration
float whalesData = customData('_WHALESPERCENTAGE')
float inverstorsData = customData('_INVESTORSPERCENTAGE')
float bigHands = whalesData+inverstorsData
float concentration = ta.change(bigHands )*100
Large Transactions
float largeTransacionsData = customData('_LARGETXCOUNT')
float largeTX21 = ta.ema(largeTransacionsData,21)
float largeTX30 = ta.ema(largeTransacionsData,30)
float largeTransacions = ((largeTX21 - largeTX30)/largeTX30)*100
🔶 SETTINGS
Display mode: Select between gauge, historical data and average.
Average: Select a smoothing method and length period.
🔹 Thresholds
Net Network Growth : Bullish and bearish thresholds for this signal.
In The Money : Bullish and bearish thresholds for this signal.
Concentration : Bullish and bearish thresholds for this signal.
Transactions : Bullish and bearish thresholds for this signal.
🔹 Dashboard
Dashboard : Enable/disable dashboard display
Position : Select dashboard location
Size : Select dashboard size
🔹 Gauge
Scale : Select the size of the gauge
Curved : Enable/disable curved mode
Select Gauge colors for bearish, neutral and bullish bias
🔹 Style
Net Network Growth : Enable/disable historical plot and choose color
In The Money : Enable/disable historical plot and choose color
Concentration : Enable/disable historical plot and choose color
Large Transacions : Enable/disable historical plot and choose color
Heikinisi Candle (With MA + Smoothing + Buy/Sell with Cooldown)This custom Heikinisi Candle (With MA + Smoothing + Buy/Sell with Cooldown) indicator combines the advantages of Heikin-Ashi candles with the flexibility of multiple moving averages and smoothing options. The built-in buy/sell signals with cooldown functionality help traders avoid overtrading while capturing trend reversals and momentum shifts. Whether you're a day trader, swing trader, or long-term investor, this indicator offers powerful tools for analyzing price action and making informed trading decisions.
Note: Disable the regular candle to get better visualization.
Key Features:
Custom Heikin-Ashi Candles:
The core feature of this script is the Heikin-Ashi candles, which are known for smoothing price action and helping traders identify market trends more clearly.
Unlike traditional Heikin-Ashi, this version adjusts the Heikin-Ashi close based on specific price action patterns, including rejection signals and engulfing patterns.
The custom Heikin-Ashi open also incorporates momentum, adjusting dynamically based on recent price changes.
Price Action Measurements:
The indicator measures key price action components, including:
Body: The absolute difference between the open and close.
Candle Range: The total range from high to low.
Upper Wick: The distance from the highest price to the maximum of open or close.
Lower Wick: The distance from the lowest price to the minimum of open or close.
These measurements help detect bullish and bearish conditions, as well as price rejection signals.
Buy/Sell Signal Logic:
Buy Signal: Triggered when the Heikin-Ashi close is above the chosen moving average (MA1), with a cooldown period to avoid too frequent signals.
Sell Signal: Triggered when the Heikin-Ashi close falls below the MA1 after a buy signal has already been issued.
The cooldown period ensures that buy and sell signals are spaced apart by a specific number of bars, preventing excessive signal generation during periods of price consolidation.
Multiple Moving Averages (MA):
This script supports up to three customizable moving averages (MA1, MA2, MA3), each of which can be set to different types and lengths, including:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Volume Weighted Moving Price (VWMP)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Users can adjust the length and type of each MA for tailored analysis.
Smoothing Options for MAs:
Users can smooth the output of MAs using various types of smoothing algorithms (SMA, EMA, LSMA, WMA, Gaussian) and a customizable length. This helps to reduce noise in the moving average lines and provides clearer signals.
Gaussian Filter (Advanced Smoothing):
A Gaussian Filter is available as a smoothing option for MAs. This filter reduces noise and makes the moving averages smoother, which can be particularly helpful in volatile or choppy markets.
Alerts and Visualization:
The script allows users to plot buy and sell signals on the chart with distinctive markers. A Buy Signal is shown below the bar with a lime green marker and text "Buy," while a Sell Signal is shown above the bar with a red marker and text "Sell."
Traders can also set up alerts based on the buy/sell signals to get notified in real time.
Indicator Configuration:
Heikin-Ashi Candle Configuration:
Automatically adjusts Heikin-Ashi candles based on rejection signals, engulfing patterns, and momentum. It uses custom formulas for the Heikin-Ashi open and close, making it more sensitive to price action than standard Heikin-Ashi candles.
Moving Averages (MA) Configuration:
You can select from multiple moving average types and lengths (MA1, MA2, MA3) for trend-following analysis.
Choose between SMA, EMA, WMA, VWMA, VWMP, LSMA, HMA, DEMA, and TEMA.
Smoothing Options:
Enable or disable smoothing for the moving averages.
Select from different smoothing types, including SMA, EMA, RMA, WMA, LSMA, and Gaussian.
Cooldown Period:
Control the number of bars that must pass before a new buy/sell signal is triggered. This cooldown period helps prevent excessive trading signals in quick succession.
How to Use:
Analyze Price Action with Heikin-Ashi Candles:
The custom Heikin-Ashi candles are ideal for spotting market trends, reversals, and price rejection. Use the candle patterns to gauge the market sentiment.
Use MAs for Trend Confirmation:
The moving averages (MA1, MA2, MA3) can help identify the prevailing trend. A price above a rising MA indicates an uptrend, while a price below a falling MA suggests a downtrend.
Trigger Buy and Sell Signals:
When the Heikin-Ashi close crosses above MA1, a buy signal is triggered.
When the Heikin-Ashi close crosses below MA1 after a buy signal, a sell signal is triggered.
The cooldown period ensures that signals are spaced out, preventing overtrading.
Use Smoothing for Clearer Signals:
If you are trading in a volatile market, you can use the smoothing options to make the MAs smoother and reduce noise.
Timeframe-Based Dynamic MA [odnac]
This code is a Timeframe-Based Dynamic MA indicator, written in Pine Script, that dynamically calculates and displays the Simple Moving Average (SMA), Exponential Moving Average (EMA), and Volume Weighted Moving Average (VWMA) based on a 24-hour period, according to the selected timeframe. It automatically adjusts the length of the moving averages for each timeframe, showing the appropriate value optimized for that specific timeframe.
Code Explanation:
Settings:
inputLength: A user input that allows setting the base time (24 hours by default). This value determines the reference for calculating the length of the moving averages according to the timeframe.
transp: A setting for the transparency of the moving average lines. It can accept values from 0 to 100 (0 is opaque, 100 is fully transparent).
Timeframe-Based Moving Average Calculation:
The length variable is dynamically calculated based on the current chart's timeframe.
For shorter timeframes like 1-minute, 2-minute, 3-minute, 5-minute, 10-minute, 15-minute, 30-minute, and 45-minute, the length is calculated by multiplying 60 / selected timeframe to obtain the moving average length based on a 24-hour period.
For longer timeframes like 1 hour, 4 hours, and 1 day, fixed values are used to set the moving average length.
Moving Average Calculation:
sma, ema, vwma: These are the Simple Moving Average, Exponential Moving Average, and Volume Weighted Moving Average calculated based on the length.
else_sma, else_ema, else_vwma: These represent the moving averages fetched from the 1-hour chart. For timeframes that are not calculated directly, the values are taken from the 1-hour chart.
Displaying the Moving Averages:
The moving averages are plotted according to the length calculated for the current timeframe.
If the length for the current timeframe is valid, the corresponding SMA, EMA, and VWMA values are displayed. Otherwise, the values fetched from the 1-hour chart are used.
The moving averages are displayed with the transparency (transp) value set by the user, controlling their opacity on the chart.
How to Use:
Base Time: The user sets a base time. For example, setting inputLength to 24 will calculate the moving average length based on a 24-hour period, which will be dynamically adjusted and displayed according to the selected timeframe.
Transparency Setting: The transparency of the moving average lines can be adjusted using the transp value.
Supported Timeframes:
For shorter timeframes (1-minute, 2-minute, 3-minute, 5-minute, 10-minute, 15-minute, 30-minute, 45-minute), the moving average lengths are dynamically calculated and displayed.
For longer timeframes (1 hour, 4 hours, 1 day), fixed length values are used.
This indicator allows you to dynamically calculate daily moving averages across different timeframes and visually check which moving average is the most appropriate for the selected timeframe.
Multi-Chart Widget [LuxAlgo]The Multi-Chart Widget tool is a comprehensive solution crafted for traders and investors looking to analyze multiple financial instruments simultaneously. With the capability to showcase up to three additional charts, users can customize each chart by selecting different financial instruments, and timeframes.
Users can add various widely used technical indicators to the charts such as the relative strength index, Supertrend, moving averages, Bollinger Bands...etc.
🔶 USAGE
The tool offers traders and investors a comprehensive view of multiple charts simultaneously. By displaying up to three additional charts alongside the primary chart, users can analyze assets across different timeframes, compare their performance, and make informed decisions.
Users have the flexibility to choose from various customizable chart types, including the recently added "Volume Candles" option.
This tool allows adding to the chart some of the most widely used technical indicators, such as the Supertrend, Bollinger Bands, and various moving averages.
In addition to the charting capabilities, the tool also features a dynamic statistic panel that provides essential metrics and key insights into the selected assets. Users can track performance indicators such as relative strength, trend, and volatility, enabling them to identify trends, patterns, and trading opportunities efficiently.
🔶 DETAILS
A brief overview of the indicators featured in the statistic panel is given in the sub-section below:
🔹Dual Supertrend
The Dual Supertrend is a modified version of the Supertrend indicator, which is based on the concept of trend following. It generates buy or sell signals by analyzing the asset's price movement. The Dual Supertrend incorporates two Supertrend indicators with different parameters to provide potentially more accurate signals. It helps traders identify trend reversals and establish trend direction in a more responsive manner compared to a single Supertrend.
🔹Relative Strength Index
The Relative Strength Index is a momentum oscillator that measures the speed and change of price movements. RSI oscillates between 0 and 100 and is typically used to identify overbought or oversold conditions in a market. Traditionally, RSI values above 70 are considered overbought, suggesting that the asset may be due for a reversal or correction, while RSI values below 30 are considered oversold, indicating potential buying opportunities.
🔹Volatility
Volatility in trading refers to the degree of variation or fluctuation in the price of a financial instrument, such as a stock, currency pair, or commodity, over a certain period of time. It is a measure of the speed and magnitude of price changes and reflects the level of uncertainty or risk in the market. High volatility implies that prices are experiencing rapid and significant movements, while low volatility suggests that prices are relatively stable and are not changing much. Traders often use volatility as an indicator to assess the potential risk and return of an investment and to make informed decisions about when to enter or exit trades.
🔹R-Squared (R²)
R-squared, also known as the coefficient of determination, is a statistical measure that indicates the proportion of the variance in the dependent variable that is predictable from the independent variable(s). In other words, it quantifies the goodness of fit of a regression model to the observed data. R-squared values range from %0 to %100, with higher values indicating a better fit of the model to the data. An R-squared of 100% means that all movements of a security are completely explained by movements in the index, while an R-squared value of %0 indicates that the model does not explain any of the variability in the dependent variable.
In simpler terms, in investing, a high R-squared, from 85% to 100%, indicates that the stock’s or fund’s performance moves relatively in line with the index. Conversely, a low R-squared (around 70% or less) indicates that the fund's performance tends to deviate significantly from the movements of the index.
🔶 SETTINGS
🔹Mini Chart(s) Generic Settings
Mini Charts Separator: This option toggles the visibility of the separator lines.
Number Of Bars: Specifies the number of bars to be displayed for each mini chart.
Horizontal Offset: Determines the distance at which the mini charts will be displayed from the primary chart.
🔹Mini Chart Settings: Top - Middle - Bottom
Mini Chart Top/Middle/Bottom: Toggle the visibility of the selected mini chart.
Symbol: Choose the financial instrument to be displayed in the mini chart. If left as an empty string, it will default to the current chart instrument.
Timeframe: This option determines the timeframe used for calculating the mini charts. If a timeframe lower than the chart's timeframe is selected, the calculations will be based on the chart's timeframe.
Chart Type: Selection from various chart types for the mini charts, including candles, volume candles, line, area, columns, high-low, and Heikin Ashi.
Chart Size: Determines the size of the mini chart.
Technical Indicator: Selection from various technical indicators to be displayed on top of the mini charts.
Note : Chart sizing is relative to other mini charts. For example, If all the mini charts are sized to x5 relative to each other, the result will be the same as if they were all sized as x1. This is because the relative proportions between the mini charts remain consistent regardless of their absolute sizes. Therefore, their positions and sizes relative to each other remain unchanged, resulting in the same visual representation despite the differences in absolute scale.
🔹Supertrend Settings
ATR Length: is the lookback length for the ATR calculation.
Factor: is what the ATR is multiplied by to offset the bands from price.
Color: color customization option.
🔹Moving Average Settings
Type: is the type of the moving average, available types of moving averages include SMA (Simple Moving Average), EMA (Exponential Moving Average), RMA (Root Mean Square Moving Average), HMA (Hull Moving Average), WMA (Weighted Moving Average), and VWMA (Volume Weighted Moving Average).
Source: Determines what data from each bar will be used in calculations.
Length: The time period to be used in calculating the Moving Average.
Color: Color customization option.
🔹Bollinger Bands Settings
Basis Type: Determines the type of Moving Average that is applied to the basis plot line.
Source: Determines what data from each bar will be used in calculations.
Length: The time period to be used in calculating the Moving Average which creates the base for the Upper and Lower Bands.
StdDev: The number of Standard Deviations away from the Moving Average that the Upper and Lower Bands should be.
Color: Color customization options for basis, upper and lower bands.
🔹Mini Chart(s) Panel Settings
Mini Chart(s) Panel: Controls the visibility of the panel containing the mini charts.
Dual Supertrend: Toggles the display of the evaluated dual super trend, based on the super trend settings provided below the option. The definitions for the options are the same as stated above for the super trend.
Relative Strength Index: Toggles the display of the evaluated RSI, based on the source and length settings provided below the option.
Volatility: Toggles the display of the calculated Volatility, based on the length settings provided below the option.
R-Squared: Toggles the display of the calculated R-Squared (R²), based on the length settings provided below the option.
🔶 LIMITATIONS
The tool allows users to display mini charts featuring various types of instruments alongside the primary chart instrument. However, there's a limitation: the selected primary chart instrument must have an ACTIVE market status. Alternatively, if the primary chart instrument is not active, the mini chart instruments must belong to the same exchange and have the same type as the primary chart instrument.
[blackcat] L2 Twisted Pair IndicatorOn the grand stage of the financial market, every trader is looking for a partner who can lead them to dance the tango well. The "Twisted Pair" indicator is that partner who dances gracefully in the market fluctuations. It weaves the rhythm of the market with two lines, helping traders to find the rhythm in the market's dance floor.
Imagine when the market is as calm as water, the "Twisted Pair" is like two ribbons tightly intertwined. They almost overlap on the chart, as if whispering: "Now, let's enjoy these quiet dance steps." This is the market consolidation period, the price fluctuation is not significant, traders can relax and slowly savor every detail of the market.
Now, let's describe the market logic of this code in natural language:
- **HJ_1**: This is the foundation of the market dance steps, by calculating the average price and trading volume, setting the tone for the market rhythm.
- **HJ_2** and **HJ_3**: These two lines are the arms of the dance partner, they help traders identify the long-term trend of the market through smoothing.
- **HJ_4**: This is a magnifying glass for market sentiment, it reveals the tension and excitement of the market by calculating the short-term deviation of the price.
- **A7** and **A9**: These two lines are the guide to the dance steps, they separate when the market volatility increases, guiding the traders in the right direction.
- **WATCH**: This is the signal light of the dance, when the two lines overlap, the market is calm; when they separate, the market is active.
The "Twisted Pair" indicator is like a carefully choreographed dance, it allows traders to find their own rhythm in the market dance floor, whether in a calm slow dance or a passionate tango. Remember, the market is always changing, and the "Twisted Pair" is the perfect dance partner that can lead you to dance out brilliant steps.
The script of this "Twisted Pair" uses three different types of moving averages: EMA (Exponential Moving Average), DEMA (Double EMA), and TEMA (Triple EMA). These types can be selected by the user through exchange input.
Here are the main functions of this code:
1. Defined the DEMA and TEMA functions: These two functions are used to calculate the corresponding moving averages. EMA is the exponential moving average, which is a special type of moving average that gives more weight to recent data. In the first paragraph, ema1 is the EMA of "length", and ema2 is the EMA of ema1. DEMA is 2 times of ema1 minus ema2.
2. Let users choose to use EMA, DEMA or TEMA: This part of the code provides an option for users to choose which type of moving average they want to use.
3. Defined an algorithm called "Twisted Pair algorithm": This part of the code defines a complex algorithm to calculate a value called "HJ". This algorithm involves various complex calculations and applications of EMA, DEMA, TEMA.
4. Plotting charts: The following code is used to plot charts on Tradingview. It uses the plot function to draw lines, the plotcandle function to draw candle (K-line) charts, and yellow and red to represent different conditions.
5. Specify colors: The last two lines of code use yellow and red K-line charts to represent the conditions of HJ_7. If the conditions of HJ_7 are met, the color of the K-line chart will change to the corresponding color.
Blockunity Excess Index (BEI)Identify excess zones resulting in market reversals by visualizing price deviations from an average.
The Excess Index (BEI) is designed to identify excess zones resulting in reversals, based on price deviations from a moving average. This moving average is fully customizable (type, period to be taken into account, etc.). This indicator also multiplies the moving average with a configurable coefficient, to give dynamic support and resistance levels. Finally, the BEI also provides reversal signals to alert you to any risk of trend change, on any asset.
The Idea
The goal is to provide the community with a visual and customizable tool for analyzing large price deviations from an average.
How to Use
Very simple to use, this indicator plots colored zones according to the price's deviation from the moving average. Moving average extensions also provide dynamic support and resistance. Finally, signals alert you to potential reversal points.
Elements
The Moving Average
The Moving Average, which defaults to a gray line over 200 periods, serves as a stable reference point. It is accompanied by an Index, whose color varies from yellow to orange to red, offering an overview of market conditions.
Extensions
These dynamic lines can be used to determine effective supports and resistances.
Signals
Green and red triangles serve as clear indicators for buy and sell signals.
Settings
Mainly, the type of moving average is configurable. The default is an SMA.
A Simple Moving Average (SMA) calculates the average of a selected range of prices by the number of periods in that range.
But you can also, for example, switch the mode to EMA.
The Exponential Moving Average (EMA) is a moving average that places a greater weight and significance on the most recent data points:
You also have WMA.
A Weighted Moving Average (WMA) gives more weight on recent data and less on past data:
And finally, the possibility of having a PCMA.
PCMA takes into account the highest and lowest points in the lookback period and divides this by two to obtain an average:
You can change other parameters such as lookback periods, as well as the coefficient used to define extension lines.
You can refer to the tooltips directly in the indicator parameters.
For those who prefer a minimalist display, you can activate a "Bar Color" in the settings (You must also uncheck "Borders" and "Wick" in your Chart Settings), and deactivate all other elements as you wish:
Finally, you can customize all the different colors, as well as the parameters of the table that indicates the Index value and the asset trend.
How it Works
The Index is calculated using the following method:
abs_distance = math.abs(close - base_ma)
bei = (abs_distance - ta.lowest(abs_distance, lookback_norm)) / (ta.highest(abs_distance, lookback_norm) - ta.lowest(abs_distance, lookback_norm)) * 100
Signals are triggered according to the following conditions:
A Long (buy) signal is triggered when the Index falls below 100, when the closing price is lower than 5 periods ago, and when the price is under the moving average.
A Short (sell) signal is triggered when the Index falls below 100, when the closing price is greater than 5 periods ago, and when the price is above the moving average.
TOMMAR#TOMMAR #MultiMovingAverages #MMAR
Dear fellow traders, this is Tommy, and today I'd like to introduce you to the Multi-Moving Averages Ribbon (MMAR) indicator, which I believe to be one of the best MMAR indicators available on TradingView. Moving Averages is a popular technical analysis tool used to smooth out price data by creating an average of past price data points over a specified time period. They can be used to identify trends and provide a clearer view of price action, as well as generate buy and sell signals by observing crossovers between different moving average lines.
In the MMAR indicator, we have incorporated 12 different types of Moving Averages, including Simple Moving Averages (SMA), Exponential Moving Averages (EMA), Weighted Moving Averages (WMA), Hull Moving Averages (HMA), and Smoothed Moving Averages (SMMA), among others. This allows traders to choose the optimal type for their preferred trading commodities.
One common technique in technical analysis is using multiple Moving Averages with varying lengths, which provides a more comprehensive view of price action. By analyzing multiple Moving Averages with different timeframes, traders can better understand both short- and long-term trends and make more informed trading decisions. Some of the well-known combinations of multiple moving averages used by traders are (5, 9, 14, 21, 45), (6, 11, 16, 22, 51), [8, 13, 21, 55), (50, 100, 200), and (60, 120, 240).
Another way to gauge the strength of the market trend is to look for the arrangement of the Moving Averages. If they are in a sequential order, with the shortest on top and the longest on the bottom, it is most likely a bullish trend. On the other hand, if they are arranged in reverse order, with the shortest on the bottom and the longest on top, it is most likely a bearish trend. The 'Trend Light' in the indicator settings will automatically signal when the Moving Averages are in either an orderly or reverse arrangement.
Lastly, I have added a useful feature to the indicator: the 'MA Projection'. This feature projects and forecasts the Moving Averages in the future, allowing traders to easily identify confluence zones in future candlesticks. Please note that the projection levels may change in the case of extreme price action that significantly affects the Moving Averages.
This is free so any Tradingview users can use this indicator. Just search TOMMAR in the indicator section located on top of the chart.
#TOMMAR #MultiMovingAverages #MMAR
안녕하세요 트레이더 여러분, 토미입니다. 오늘 여러분들에게 소개드릴 지표는 다양한 길이의 이동평균선 조합을 사용할 수 있는 MMAR (Multiple Moving Averages Ribbon)입니다. 아마 제가 만든 MMAR 지표가 트레이딩뷰에서 가장 쓸만할 겁니다. 이동평균선, 줄여서 이평선은 말 그대로 특정 기간 범위 내의 주가들을 평균한 값들로 이루어진 선입니다. 제가 이평선 관련된 강의 자료는 예전에 올려드린 바 있으니 더 자세한 내용이 궁금하신 분들은 아래 링크/이미지 클릭하시길 바랍니다.
본 지표는 Simple Moving Averages (SMA), Exponential Moving Averages (EMA), Weighted Moving Averages (WMA), Hull Moving Averages (HMA), 그리고 Smoothed Moving Averages (SMMA) 등을 포함해 총 12개 종류의 이평선 지표를 사용할 수 있습니다. 또한 각 이평선의 길이들도 하나하나 일일이 설정하실 수 있습니다. 예를 들어 요즘에 자주 보이는 이평선들의 조합이 , , , , 그리고 등등이 존재하는데 여러분의 취향에 맞게 설정하여 사용하시면 됩니다.
몇 가지 주요 기능에 대해서 설명 드리겠습니다. 설정에서 ‘Trend Light’를 키면 이평선들의 정배열 혹은 역배열 여부를 쉽게 볼 수 있습니다. 이평선이 정배열일때는 맨 아래의 이평선에 초록불이, 역배열일때는 맨 위의 이평선에 빨간불이 켜지며 둘 다 아닐 땐 아무 불도 켜지지 않습니다. 또한 ‘MA Projection’을 키면 이평선들의 미래 예측 값들을 확장해줍니다. 당연히 가격 변동이 갑자기 크게 나오면 이평선 예측 확장 레벨들이 확 바뀌겠죠.
지표창에 TOMMAR 검색하시거나 아래 즐겨찾기 인디케이터에 넣기 클릭하시면 누구나 사용하실 수 있습니다~ 여러분의 구독, 좋아요, 댓글은 저에게 큰 힘이 됩니다.
Step Generalized Double DEMA (ATR based) [Loxx]Step Generalized Double DEMA (ATR based) works like a T3 moving average but is less smooth. This is on purpose to catch more signals. The addition of ATR stepped filtering reduces noise while maintaining signal integrity. This one comes via Mr. Tools.
Theory:
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages". The way to calculate is the following :
The Double Exponential Moving Average calculations are based combinations of a single EMA and double EMA into a new EMA:
1. Calculate EMA
2. Calculate Smoothed EMA by applying EMA with the same period to the EMA calculated in the first step
3. Calculate DEMA
DEMA = (2 * EMA) - (Smoothed EMA)
This version:
For our purposes here, we are using Tim Tillson's (the inventor of T3) work, specifically, we are using the GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that "middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Usage:
You can use it as any regular average or you can use the color change of the indicator as a signal.
Included
Alerts
Signals
Bar coloring
Loxx's Expanded Source Types
Coloured MA R3-16 by JustUncleLThis indicator is an implementation of the coloured trend Moving Average, that includes some unique features. The Moving Average plot is coloured relative to it's direction and optionally display coloured Trend Bars using the standard 2-tone colours, or Grab candle style 4-tone colours.
Options:
1) Anchor Time Frame to a Highter Time frame, eg. set anchor to 1440 and length set to 8, the script will re-size the MA length needed to display on the current TF, say 60.
2) You can select between 11 different types of moving averages, each MA line can be a different type:
SMA = Simple Moving Average.
EMA = Exponential Moving Average.
WMA = Weighted Moving Average
VWMA = Volume Weighted Moving Average
SMMA = Smoothed Simple Moving Average.
DEMA = Double Exponential Moving Average
TEMA = Triple Exponential Moving Average.
HullMA = Hull Moving Average
SSMA = Ehlers Super Smoother Moving average
ZEMA = Near Zero Lag Exponential Moving Average.
TMA = Triangular (smoothed) Simple Moving Average.
3) Option to display coloured Candles around the Ribbon, the colouring -
Standard candle colours:
Lime = candle closed above Ribbon.
Red = candle closed below Ribbon.
The Grab candles scheme:
Lime = Bull candle closed above Ribbon.
Green = Bear candle closed above Ribbon.
Red = Bull candle closed below Ribbon.
DarkRed = Bear candle closed below Ribbon.
Dominant DATR [CHE] Dominant DATR — Directional ATR stream with dominant-side EMA, bands, labels, and alerts
Summary
Dominant DATR builds two directional volatility streams from the true range, assigns each bar’s range to the up or down side based on the sign of the close-to-close move, and then tracks the dominant side through an exponential average. A rolling band around the dominant stream defines recent extremes, while optional gradient coloring reflects relative magnitude. Swing-based labels mark new higher highs or lower lows on the dominant stream, and alerts can be enabled for swings, zero-line crossings, and band breakouts. The result is a compact pane that highlights regime bias and intensity without relying on price overlays.
Motivation: Why this design?
Conventional ATR treats all range as symmetric, which can mask directional pressure, cause late regime shifts, and produce frequent false flips during noisy phases. This design separates the range into up and down contributions, then emphasizes whichever side is stronger. A single smoothed dominant stream clarifies bias, while the band and swing markers help distinguish continuation from exhaustion. Optional normalization by close makes the metric comparable across instruments with different price scales.
What’s different vs. standard approaches?
Reference baseline: Classic ATR or a basic EMA of price.
Architecture differences:
Directional weighting of range using positive and negative close-to-close moves.
Separate moving averages for up and down contributions combined into one dominant stream.
Rolling highest and lowest of the dominant stream to form a band.
Optional normalization by close, window-based scaling for color intensity, and gamma adjustment for visual contrast.
Event logic for swing highs and lows on the dominant stream, with label buffering and pruning.
Configurable alerts for swings, zero-line crossings, and band breakouts.
Practical effect: You see when volatility is concentrated on one side, how strong that bias currently is, and when the dominant stream pushes through or fails at its recent envelope.
How it works (technical)
Each bar’s move is split into an up component and a down component based on whether the close increased or decreased relative to the prior close. The bar’s true range is proportionally assigned to up or down using those components as weights.
Each side is smoothed with a Wilder-style moving average. The dominant stream is the side with the larger value, recorded as positive for up dominance and negative for down dominance.
The dominant stream is then smoothed with an exponential moving average to reduce noise and provide a responsive yet stable signal line.
A rolling window tracks the highest and lowest values of the dominant EMA to form an envelope. Crossings of these bounds indicate unusual strength or weakness relative to recent history.
For visualization, the absolute value of the dominant EMA is scaled over a lookback window and passed through a gamma curve to modulate gradient intensity. Colors are chosen separately for up and down regimes.
Swing events are detected by comparing the dominant EMA to its recent extremes over a short lookback. Labels are placed when a prior bar set an extreme and the current bar confirms it. A managed array prunes older labels when the user-defined maximum is exceeded.
Alerts mirror these events and also include zero-line crossings and band breakouts. The script does not force closed-bar confirmation; users should configure alert execution timing to suit their workflow.
There are no higher-timeframe requests and no security calls. State is limited to simple arrays for labels and persistent color parameters.
Parameter Guide
Parameter — Effect — Default — Trade-offs/Tips
ATR Length — Smoothing of directional true range streams — fourteen — Longer reduces noise and may delay regime shifts; shorter increases responsiveness.
EMA Length — Smoothing of the dominant stream — twenty-five — Lower values react faster; higher values reduce whipsaw.
Band Length — Window for recent highs and lows of the dominant stream — ten — Short windows flag frequent breakouts; long windows emphasize only exceptional moves.
Normalize by Close — Divide by close price to produce a percent-like scale — false — Useful across assets with very different price levels.
Enable gradient color — Turn on magnitude-based coloring — true — Visual aid only; can be disabled for simplicity.
Gradient window — Lookback used to scale color intensity — one hundred — Larger windows stabilize the color scale.
Gamma (lines) — Adjust gradient intensity curve — zero point eight — Lower values compress variation; higher values expand it.
Gradient transparency — Transparency for gradient plots — zero, between zero and ninety — Higher values mute colors.
Up dark / Up neon — Base and peak colors for up dominance — green tones — Styling only.
Down dark / Down neon — Base and peak colors for down dominance — red tones — Styling only.
Show zero line / Background tint — Visual references for regime — true and false — Background tint can help quick scanning.
Swing length — Bars used to detect swing highs or lows — two — Larger values demand more structure.
Show labels / Max labels / Label offset — Label visibility, cap, and vertical offset — true, two hundred, zero — Increase cap with care to avoid clutter.
Alerts: HH/LL, Zero Cross, Band Break — Toggle alert rules — true, false, false — Enable only what you need.
Reading & Interpretation
The dominant EMA above zero indicates up-side dominance; below zero indicates down-side dominance.
Band lines show recent extremes of the dominant EMA; pushes through the band suggest unusual momentum on the dominant side.
Gradient intensity reflects local magnitude of dominance relative to the chosen window.
HH/LL labels appear when the dominant stream prints a new local extreme in the current regime and that extreme is confirmed on the next bar.
Zero-line crosses suggest regime flips; combine with structure or filters to reduce noise.
Practical Workflows & Combinations
Trend following: Consider entries when the dominant EMA is on the regime side and expands away from zero. Band breakouts add confirmation; structure such as higher highs or lower lows in price can filter signals.
Exits and stops: Tighten exits when the dominant stream stalls near the band or fades toward zero. Opposite swing labels can serve as early caution.
Multi-asset and multi-timeframe: Works across liquid assets and common timeframes. For lower noise instruments, reduce smoothing slightly; for high noise, increase lengths and swing length.
Behavior, Constraints & Performance
Repaint and confirmation: No security calls and no future-looking references. Swing labels confirm one bar later by design. Real-time crosses can change intra-bar; use bar-close alerts if needed.
Resources: `max_bars_back` is two thousand. The script uses an array for labels with pruning, gradient color computations, and a simple while loop that runs only when the label cap is exceeded.
Known limits: The EMA can lag at sharp turns. Normalization by close changes scale and may affect thresholds. Extremely gappy data can produce abrupt shifts in the dominant side.
Sensible Defaults & Quick Tuning
Starting point: ATR Length fourteen, EMA Length twenty-five, Band Length ten, Swing Length two, gradient enabled.
Too many flips: Increase EMA Length and swing length, or enable only swing alerts.
Too sluggish: Decrease EMA Length and Band Length.
Inconsistent scales across symbols: Enable Normalize by Close.
Visual clutter: Disable gradient or reduce label cap.
What this indicator is—and isn’t
This is a volatility-bias visualization and signal layer that highlights directional pressure and intensity. It is not a complete trading system and does not produce position sizing or risk management. Use it with market structure, context, and independent risk controls.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Multi Moving Average with CustomizationCore Functionality
The indicator allows you to display up to 5 different moving averages on your chart simultaneously.
Each moving average can be fully customized with its own settings.
You can choose between
1. Simple Moving Average (SMA),
2. Exponential Moving Average (EMA)
3. Weighted Moving Average (WMA) types
Multi-Timeframe Support
One standout feature is the ability to display higher timeframe moving averages on lower timeframe charts.
For example, you can show a 200 EMA from the daily chart while viewing a 15-minute chart.
Advanced Visualization Features
The indicator includes several visualization enhancements:
1. MA Cloud - Creates a filled area between any two selected moving averages. The cloud automatically changes color based on which MA is on top - typically green when the faster MA is above (bullish) and red when below (bearish).
2. Golden/Death Cross Detection - Automatically detects and marks important MA crossover events:
* Golden Cross: When a shorter-term MA crosses above a longer-term MA (bullish signal)
* Death Cross: When a shorter-term MA crosses below a longer-term MA (bearish signal)
3. Trend Background - Colors the entire chart background based on whether price is above or below a specified MA, giving a clear visual indicator of the overall trend.
Alert System
The indicator can generate alerts when price crosses above or below any selected moving average. This feature is useful for automated trading signals or notifications, and can be configured to trigger once per bar.
Flexible Architecture
The code uses several programming techniques to maximize flexibility:
* Switch statements for selecting MA types and cloud values
* Conditional logic throughout the code
* Function abstraction for calculating MAs and handling multi-timeframe display
* String identifiers to select which MAs to use for cloud visualization
Unique Technical Aspects
1. The multi-timeframe plotting function solves the common problem of higher timeframe MAs looking distorted on lower timeframe charts.
2. The cloud feature uses string identifiers to select which MAs to use, allowing for any combination.
3. The indicator employs smart conditional logic to handle complex decision trees efficiently.
4. Every visual aspect (colors, line widths, display conditions) is customizable through the settings.
This indicator combines multiple technical analysis tools into a single, highly configurable package that can adapt to different trading styles and timeframes.
Its ability to correctly display higher timeframe MAs on lower timeframe charts makes it particularly valuable for traders who analyze multiple timeframes simultaneously.
