RSI Difference (Fast and Slow)Introduction
Oscillators like the RSI are fundamental tools for identifying trends in financial markets. Their ability to measure price momentum allows traders to detect overbought, oversold levels, and divergences, anticipating trend changes. Are there ways to improve the use of traditional RSI? How can we obtain more detailed information about current trends? This indicator answers these questions by expanding the functionalities of the traditional RSI and offering an additional tool for analysis.
How does it work?
This indicator provides a framework for trend analysis based on the following setup:
Fast RSI
Slow RSI
SMA of the fast RSI
SMA of the slow RSI
Histogram
Custom Indicator Settings
My preferred configuration is based on the 13 and 55 moving averages. The rest of the setup is as follows:
I typically use the 13 and 55 moving averages to configure both the RSI and short- and long-term moving averages.
Interpretation and Signals: Including a Long-Period RSI
Including a long-period RSI helps identify key patterns in market behavior. Crossovers between the two can be used to establish entry patterns:
If the fast RSI crosses above the slow RSI, this could indicate a long-entry pattern.
If the fast RSI crosses below the slow RSI, this could indicate a short-entry pattern.
Interpretation and Signals: Including Moving Averages
Including moving averages for both the short- and long-period RSI can help identify the base trend of the movement and, consequently:
Avoid false signals.
Trade in favor of the trend.
A simple way to start working with these is to use the crossover of the moving averages to identify the current trend:
If the short-period SMA is above the long-period SMA, the trend is bullish.
If the short-period SMA is below the long-period SMA, the trend is bearish.
Interpretation and Signals: The Histogram
The histogram represents the difference between the moving averages. If the histogram is positive, the short average is above the long average. If the histogram is below zero, the short average is below the long average. Divergences with price provide signals of potential exhaustion in the movement, indicating a possible reversal.
Indicator Details
This indicator builds upon the traditional RSI by integrating additional features that enhance its utility for traders. Here’s how each component is calculated and how they contribute to the originality of the script:
Fast RSI and Slow RSI: The fast RSI is calculated using a shorter lookback period, allowing it to capture rapid changes in momentum. The slow RSI uses a longer period to smooth out fluctuations and provide a broader view of the trend. These two RSIs work together to identify significant momentum shifts.
SMA of RSI values: The simple moving averages (SMA) of the fast and slow RSI help filter out noise and provide clear crossover signals. The SMAs are calculated using standard formulas but applied to the RSI values rather than price data, which adds a layer of insight into momentum trends.
Histogram calculation: The histogram represents the difference between the SMA of the fast RSI and the SMA of the slow RSI. This value gives a visual representation of the convergence or divergence of momentum. When the histogram crosses zero, it signifies a potential shift in the underlying trend.
This indicator combines multiple layers of analysis: fast and slow momentum, trend confirmation through SMAs, and divergence detection via the histogram. This multi-dimensional approach provides traders with a more comprehensive tool for trend analysis and decision-making.
Conclusion
This article has explored how to use this indicator to identify trends, leverage entry patterns, and analyze divergences by combining the fast RSI, slow RSI, their moving averages, and a histogram. Additionally, I’ve detailed how I usually interpret this indicator:
Identifying RSI patterns to anticipate momentum changes.
Using SMAs to confirm base trends.
Leveraging the histogram to detect divergences and potential price reversals.
Cari dalam skrip untuk "moving averages"
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.
CT Moving Average Crossover IndicatorMoving Average Crossover Indicator
Here I present a moving average indicator with 9 user definable moving averages from which up to 5 pairs can be selected to show what prices would need to be closed at on the current bar to cross each individual pair.
I have put much emphasis here on simplicity of setting the parameters of the moving averages, selecting the crossover pairs and on the clarity of the displayed information in the optional “Moving Average Crossover Level” Information Box.
What Is a Moving Average (MA)?
According to Investopedia - “In statistics, a moving average is a calculation used to analyze data points by creating a series of averages of different subsets of the full data set.
In finance, a moving average (MA) is a stock indicator that is commonly used in technical analysis. The reason for calculating the moving average of a stock is to help smooth out the price data by creating a constantly updated average price.
By calculating the moving average, the impacts of random, short-term fluctuations on the price of a stock over a specified time-frame are mitigated.”
The user can set the color, type (SMA/EMA) and length of each of the 9 moving averages.
Then the user may choose 5 pairs of moving averages from the set of 9.
The script will then calculate the price needed to be crossed by the close of the current bar in order to crossover each of the user defined pairs and outputs the results as optional lineplots and/or an Infobox which shows the relevant information in a very clear way.
The user may switch the moving averages, crossover lineplots and infobox on and off easily with one click boxes in the settings menu.
The number of decimal places shown in the Infobox can be altered in the settings menu.
If the price required to cross a pair of moving averages is zero or less, the crossover level will display “Impossible” and the plots will plot at zero. (this helps ameliorate chart auto-focus issues)
Quoting a variety of online resources …….
Understanding Moving Averages (MA)
Moving averages are a simple, technical analysis tool. Moving averages are usually calculated to identify the trend direction of a stock or to determine its support and resistance levels. It is a trend-following—or lagging—indicator because it is based on past prices.
The longer the time period for the moving average, the greater the lag. So, a 200-day moving average will have a much greater degree of lag than a 20-day MA because it contains prices for the past 200 days. The 50-day and 200-day moving average figures for stocks are widely followed by investors and traders and are considered to be important trading signals.
Moving averages are a totally customizable indicator, which means that an investor can freely choose whatever time frame they want when calculating an average. The most common time periods used in moving averages are 15, 20, 30, 50, 100, and 200 days. The shorter the time span used to create the average, the more sensitive it will be to price changes. The longer the time span, the less sensitive the average will be.
Investors may choose different time periods of varying lengths to calculate moving averages based on their trading objectives. Shorter moving averages are typically used for short-term trading, while longer-term moving averages are more suited for long-term investors.
There is no correct time frame to use when setting up your moving averages. The best way to figure out which one works best for you is to experiment with a number of different time periods until you find one that fits your strategy.
Predicting trends in the stock market is no simple process. While it is impossible to predict the future movement of a specific stock, using technical analysis and research can help you make better predictions.
A rising moving average indicates that the security is in an uptrend, while a declining moving average indicates that it is in a downtrend. Similarly, upward momentum is confirmed with a bullish crossover, which occurs when a short-term moving average crosses above a longer-term moving average. Conversely, downward momentum is confirmed with a bearish crossover, which occurs when a short-term moving average crosses below a longer-term moving average.
Types of Moving Averages
Simple Moving Average (SMA)
The simplest form of a moving average, known as a simple moving average (SMA), is calculated by taking the arithmetic mean of a given set of values. In other words, a set of numbers–or prices in the case of financial instruments–are added together and then divided by the number of prices in the set.
Exponential Moving Average (EMA)
The exponential moving average is a type of moving average that gives more weight to recent prices in an attempt to make it more responsive to new information.
To calculate an EMA, you must first compute the simple moving average (SMA) over a particular time period. Next, you must calculate the multiplier for weighting the EMA (referred to as the "smoothing factor"), which typically follows the formula: 2/(selected time period + 1). So, for a 20-day moving average, the multiplier would be 2/(20+1)= 0.0952. Then you use the smoothing factor combined with the previous EMA to arrive at the current value.
The EMA thus gives a higher weighting to recent prices, while the SMA assigns equal weighting to all values.
Signal Hunter Pro - GKDXLSignal Hunter Pro - GKDXL combines four powerful technical indicators with trend strength filtering and volume confirmation to generate reliable BUY/SELL signals. This indicator is perfect for traders who want a systematic approach to market analysis without the noise of conflicting signals.
🔧 Core Features
📈 Multi-Indicator Signal System
Moving Averages: EMA 20, EMA 50, and SMA 200 for trend analysis
Bollinger Bands: Dynamic support/resistance with price momentum detection
RSI: Enhanced RSI logic with smoothing and multi-zone analysis
MACD: Traditional MACD with signal line crossovers and zero-line analysis
🎛️ Advanced Filtering System
ADX Trend Strength Filter: Only signals when trend strength exceeds threshold
Volume Confirmation: Ensures signals occur with adequate volume participation
Multi-Timeframe Logic: Works on any timeframe from 1m to 1D and beyond
🚨 Intelligent Signal Generation
Requires 3 out of 4 indicators to align for signal confirmation
Separate bullish and bearish signal conditions
Real-time signal strength scoring (1/4 to 4/4)
Built-in alert system for automated notifications
⚙️ Customizable Parameters
📊 Technical Settings
Moving Averages: Adjustable EMA and SMA periods
Bollinger Bands: Configurable length and multiplier
RSI: Customizable length, smoothing, and overbought/oversold levels
MACD: Flexible fast, slow, and signal line settings
🎯 Risk Management
Risk Percentage: Set your risk per trade (0.1% to 10%)
Reward Ratio: Configure risk-to-reward ratios (1:1 to 1:5)
ADX Threshold: Control minimum trend strength requirements
🖥️ Display Options
Indicator Visibility: Toggle individual indicators on/off
Information Table: Optional detailed status table (off by default)
Volume Analysis: Real-time volume vs. average comparison
🎨 Visual Elements
📈 Chart Indicators
EMA Lines: Blue (20) and Orange (50) exponential moving averages
SMA 200: Gray long-term trend line
Bollinger Bands: Upper/lower bands with semi-transparent fill
Clean Interface: Minimal visual clutter for clear analysis
📋 Information Table (Optional)
Real-time indicator status with ✓/✗/— symbols
Current signal strength and direction
ADX trend strength measurement
Volume confirmation status
No-signal reasons when conditions aren't met
🔔 Alert System
📢 Three Alert Types
BUY Signal: Triggered when 3+ indicators align bullishly
SELL Signal: Triggered when 3+ indicators align bearishly
General Alert: Any signal detection for broader monitoring
📱 Alert Messages
Clear, actionable alert text
Includes indicator name for easy identification
Compatible with webhook integrations
🎯 How It Works
📊 Signal Logic
Indicator Assessment: Each of the 4 indicators is evaluated as Bullish/Bearish/Neutral
Consensus Building: Counts aligned indicators (minimum 3 required)
Filter Application: Applies trend strength and volume filters
Signal Generation: Generates BUY/SELL when all conditions are met
🔍 Indicator States
Moving Averages: Price position, EMA alignment, and crossovers
Bollinger Bands: Price relative to bands and momentum shifts
RSI: Multi-zone analysis with momentum and crossover detection
MACD: Signal line crossovers and zero-line positioning
🎉 Why Choose Signal Hunter Pro?
✅ Multi-Indicator Confirmation reduces false signals
✅ Trend Strength Filtering improves win rate
✅ Volume Confirmation ensures market participation
✅ Customizable Parameters adapt to any trading style
✅ Clean Visual Design doesn't clutter your charts
✅ Professional Alert System for automated trading
✅ No Repainting - reliable historical signals
✅ Works on All Timeframes from scalping to investing
Enhanced Market Analyzer with Adaptive Cognitive LearningThe "Enhanced Market Analyzer with Advanced Features and Adaptive Cognitive Learning" is an advanced, multi-dimensional trading indicator that leverages sophisticated algorithms to analyze market trends and generate predictive trading signals. This indicator is designed to merge traditional technical analysis with modern machine learning techniques, incorporating features such as adaptive learning, Monte Carlo simulations, and probabilistic modeling. It is ideal for traders who seek deeper market insights, adaptive strategies, and reliable buy/sell signals.
Key Features:
Adaptive Cognitive Learning:
Utilizes Monte Carlo simulations, reinforcement learning, and memory feedback to adapt to changing market conditions.
Adjusts the weighting and learning rate of signals dynamically to optimize predictions based on historical and real-time data.
Hybrid Technical Indicators:
Custom RSI Calculation: An RSI that adapts its length based on recursive learning and error adjustments, making it responsive to varying market conditions.
VIDYA with CMO Smoothing: An advanced moving average that incorporates Chander Momentum Oscillator for adaptive smoothing.
Hamming Windowed VWMA: A volume-weighted moving average that applies a Hamming window for smoother calculations.
FRAMA: A fractal adaptive moving average that responds dynamically to price movements.
Advanced Statistical Analysis:
Skewness and Kurtosis: Provides insights into the distribution and potential risk of market trends.
Z-Score Calculations: Identifies extreme market conditions and adjusts trading thresholds dynamically.
Probabilistic Monte Carlo Simulation:
Runs thousands of simulations to assess potential price movements based on momentum, volatility, and volume factors.
Integrates the results into a probabilistic signal that informs trading decisions.
Feature Extraction:
Calculates a variety of market metrics, including price change, momentum, volatility, volume change, and ATR.
Normalizes and adapts these features for use in machine learning algorithms, enhancing signal accuracy.
Ensemble Learning:
Combines signals from different technical indicators, such as RSI, MACD, Bollinger Bands, Stochastic Oscillator, and statistical features.
Weights each signal based on cumulative performance and learning feedback to create a robust ensemble signal.
Recursive Memory and Feedback:
Stores and averages past RSI calculations in a memory array to provide historical context and improve future predictions.
Adaptive memory factor adjusts the influence of past data based on current market conditions.
Multi-Factor Dynamic Length Calculation:
Determines the length of moving averages based on volume, volatility, momentum, and rate of change (ROC).
Adapts to various market conditions, ensuring that the indicator is responsive to both high and low volatility environments.
Adaptive Learning Rate:
The learning rate can be adjusted based on market volatility, allowing the system to adapt its speed of learning and sensitivity to changes.
Enhances the system's ability to react to different market regimes.
Monte Carlo Simulation Engine:
Simulates thousands of random outcomes to model potential future price movements.
Weights and aggregates these simulations to produce a final probabilistic signal, providing a comprehensive risk assessment.
RSI with Dynamic Adjustments:
The initial RSI length is adjusted recursively based on calculated errors between true RSI and predicted RSI.
The adaptive RSI calculation ensures that the indicator remains effective across various market phases.
Hybrid Moving Averages:
Short-Term and Long-Term Averages: Combines FRAMA, VIDYA, and Hamming VWMA with specific weights for a unique hybrid moving average.
Weighted Gradient: Applies a color gradient to indicate trend strength and direction, improving visual clarity.
Signal Generation:
Generates buy and sell signals based on the ensemble model and multi-factor analysis.
Uses percentile-based thresholds to determine overbought and oversold conditions, factoring in historical data for context.
Optional settings to enable adaptation to volume and volatility, ensuring the indicator remains effective under different market conditions.
Monte Carlo and Learning Parameters:
Users can customize the number of Monte Carlo simulations, learning rate, memory factor, and reward decay for tailored performance.
Applications:
Scalping and Day Trading:
The fast response of the adaptive RSI and ensemble learning model makes this indicator suitable for short-term trading strategies.
Swing Trading:
The combination of long-term moving averages and probabilistic models provides reliable signals for medium-term trends.
Volatility Analysis:
The ATR, Bollinger Bands, and adaptive moving averages offer insights into market volatility, helping traders adjust their strategies accordingly.
Distance From moving averageDistance From Moving Average is designed to help traders visualize the deviation of the current price from a specified moving average. Users can select from four different types of moving averages: Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), and Hull Moving Average (HMA).
Key Features:
User-Friendly Input Options:
Choose the type of moving average from a dropdown menu.
Set the length of the moving average, with a default value of 200.
Custom Moving Average Calculations:
The script computes the selected moving average using the appropriate mathematical formula, allowing for versatile analysis based on individual trading strategies.
Distance Calculation:
The indicator calculates the distance between the current price and the chosen moving average, providing insight into market momentum. A positive value indicates that the price is above the moving average, while a negative value shows it is below.
Visual Representation:
The distance is plotted on the chart, with color coding:
Lime: Indicates that the price is above the moving average (bullish sentiment).
Red: Indicates that the price is below the moving average (bearish sentiment).
Customization:
Users can further customize the appearance of the plotted line, enhancing clarity and visibility on the chart.
This indicator is particularly useful for traders looking to gauge market conditions and make informed decisions based on the relationship between current prices and key moving averages.
Bull Bear Power With EMA FilterDescription of Indicator:
This Pine Script indicator colors price bars based on the open price in relation to custom moving averages (EMA/SMA), Bull/Bear Power (BBPower), and an optional VWAP filter. The bar colors help identify bullish and bearish conditions with added visual cues for price positioning relative to VWAP.
Key Features:
Customizable Moving Averages (EMA/SMA):
The user can select between EMA or SMA for both short-term and long-term moving averages.
Default moving averages are set to 5 (short-term) and 9 (long-term) but can be adjusted by the user.
Bullish Condition (Blue or Purple Bars):
A bar is colored blue if the following conditions are met:
The open price is above both the short-term and long-term moving averages.
The short-term moving average (MA 1) is above the long-term moving average (MA 2).
BBPower (open price minus the 13-period EMA) is positive, indicating bullish strength.
If the VWAP filter is enabled and the price opens below VWAP, the bullish bars will turn purple.
Bearish Condition (Yellow or Orange Bars):
A bar is colored yellow if the following conditions are met:
The open price is below both the short-term and long-term moving averages.
The short-term moving average (MA 1) is below the long-term moving average (MA 2).
BBPower is negative or zero, indicating bearish market conditions.
If the VWAP filter is enabled and the price opens above VWAP, the bearish bars will turn orange.
VWAP Filter (Optional):
An optional filter allows the user to add VWAP (Volume-Weighted Average Price) to the bar coloring logic.
When the VWAP filter is enabled, it provides additional information about price positioning relative to VWAP, turning bullish bars purple and bearish bars orange depending on whether the price opens above or below VWAP.
Usage:
Bullish Trend: Look for blue or purple bars to identify potential bullish momentum.
Bearish Trend: Look for yellow or orange bars to spot bearish conditions in the market.
The indicator allows users to customize the length and type of moving averages (EMA or SMA), as well as decide whether to apply the VWAP filter.
This indicator provides traders with clear visual signals to quickly assess the strength of bullish or bearish conditions based on the price's position relative to custom moving averages, BBPower, and VWAP, helping with trend identification and potential trade setups.
MTF HalfTrendIntroduction
A half-trend indicator is a technical analysis tool that uses moving averages and price data to find potential trend reversal and entry points in the form of graphical arrows showing market turning points.
The salient features of this indicator are:
- It uses the phenomenon of moving averages.
- It is a momentum indicator.
- It can indicate a trend change.
- It is capable of detecting a bullish or bearish trend reversal.
- It can signal to sell/buy.
- It is a real-time indicator.
Multi-Timeframe Application
A standout feature is its flexibility across timeframes. Traders have the liberty to choose any timeframe on the chart, enhancing the tool's versatility and making it suitable for both short-term and long-term analyses.
Principle of the Half Trend indicator
This indicator is based on the moving averages. The moving average is the average of the fluctuation or change in the price of an asset. These averages are taken for a time interval.
So, a half-trend indicator takes the moving averages phenomenon as its principle for working. The most commonly used moving averages in a half trend indicator are:
- Relative strength index (RSI)
- EMA (estimated moving average)
Components of a Half Trend indicator
There are two main components of a half trend indicator:
- Half trend line
- Arrows
- ATR lines
Half trend line
Half trend line represents this indicator on a candlestick chart. This line shows the trend of a chart in real-time. A half-trend line is based on the moving averages.
There are two further components of a half-trend line:
- Redline
- Blue line
A red line represents a bearish trend. When the half-trend line turns red, a trend is facing a dip. It is time for the bears to take control of the market. A bearish control of the market represents the domination of sellers in the market.
On the other hand, the blue line represents the bullish nature of the market. It tells a trader that the bullish sentiment of the market is prevailing. A bullish market means the number of buyers is significantly greater than the number of sellers.
Moreover, a trader can change these colors to his choice by customization.
Arrows
There are two types of arrows in this indicator which help a trader with the entry and exit points. These arrows are,
- Blue arrow
- Red arrow
A blue arrow signals a buying trade; on the other hand, a red arrow tells a trader about the selling of the assets. These arrows work with the moving average line to formulate a trading strategy.
The color of these arrows is changed if a trader desires so.
ATR lines
The ATR blue and red lines represent the Average True Range of the Half trend line. They may be used as stop loss or take profit levels.
Pros and Cons
Pros
- It is a very easy to eyes indicator.
- This is a very useful friendly indicator.
- It provides sufficient information to beginner traders.
- It provides sufficient information for entry points in a trade.
- A half-trend indicator provides a good exit strategy for a trader.
- It provides information about market reversals.
- It helps a trader to find a bullish and bearish sentiment in the market.
Cons
- It is a real-time indicator. So, it can lag.
- The lagging of this indicator can lead to miss opportunities.
- The most advanced and professional traders may not rely on this indicator for crucial trading decisions.
- The lagging of this indicator can predict false reversals of the market.
- It can create false signals.
- It requires the confluence of the other technical tools for a better success ratio.
Settings for Half Trend indicator
The default settings for half trend indicator are:
Amplitude = 2
Channel deviation = 2
Different markets or financial instruments may require different settings for optimal execution.
Amplitude: The degree that the Half trend line takes the internal variables into consideration. The higher the number, the fewer trades. The default value is 2.
Channel deviation: The ATR value calculation from the Half trend line. The default value is 2.
Trading strategy
It is an effective indicator in terms of strategy formation for a trading setup. The new and beginner trades can take benefit from this indicator for the formulation of a good trading setup. This indicator also helps seasoned and professional traders formulate a good trading setup with other technical tools.
The trading strategy involving a half-trend indicator is divided into three parts:
- Entry and exit
- Risk management
- Take profit
Entry and exit
It is an effective indicator that provides sufficient information about the entry and exit points in a trading setup. The profit of a trader is directly proportional to the appropriate entry and exit points. So, it is a crucial step in any trading setup.
The blue and red arrows provide information about the entry and exit points in a trading setup. Furthermore, the entry and exit for the bullish and bearish setups are as follows.
Entry and exit for a bullish setup
If a blue arrow appears under the half-trend line, it means the bullish sentiment of the market is getting stronger in the future. So, it is a signal for entry in a bullish setup.
As the red arrow appears on the chart, it is a signal to exit your trade. The red arrow represents a reversal in the market, so it is a good opportunity to close your trade in a bullish setup.
Entry and exit for a bearish setup
Suppose a red arrow appears above the red moving average line. It is a good opportunity to enter a trade in a bearish setup. The red line represents that sooner the sellers are going to take control and the value of the asset is about to face a dip. So it is the best time to make your move.
As the opposite arrow appears in the chart, it is time to exit from a bearish trade setup.
Re-entering a position
Bullish setup
- The half-trend line is blue.
- At least one candle closes below the blue half-trend line.
- Enter on the candle that closes above the blue half-trend line.
Bearish setup
- The half-trend line is red.
- At least one candle closes above the red half-trend line.
- Enter on the candle that closes below the red half-trend line.
Risk management
Risk management is an integral part of a trading setup. It is an important step to protect your potential profits and losses.
When trading in a bullish market, place the stop loss at the prior swing low. It will help you to cut your losses in case the prices move to the lower end.
In the case of a bearish market, place your stop loss above the prior swing high.
A trader may trail the stop loss using the ATR lines.
The new trader often makes mistakes in the placement of the stop loss. If you don’t place the stop loss at an appropriate point. It can drain your bank account and ruin your trading experience. Is is recommended not to risk more than 2% of your trading account, per trade.
Take profit
The blue ATR line may be used as one take profit level on a bullish setup followed by the previous swing high. The signal reversal would indicate the final take profit and closing of any position.
The red ATR line may be used as one take profit level on a bearish setup followed by the previous swing low. The signal reversal would indicate the final take profit and closing of any position.
Conclusion
A half trend indicator is a decent indicator that can transform your trading experience. It is a dual indicator that is based on the moving averages as well as helps you to form a trading strategy. If you are a new trader, this indicator can help you to learn and flourish in the trading universe. If you are a seasoned trader, I recommend you use this indicator with other technical analysis tools to enhance your success ratio.
All credits go to:
- @everget the original creator of this indicator (I just added the MTF capability).
- Ali Muhammad original author of much of the description used.
Moving Average Rainbow (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses 12 moving averages (default EMA) to identify trends and generate trading signals opening positions.
Allowing to select the type of moving average and length to be used.
The conditions includes relationship between moving averages, the position of the current price relative to the moving averages, and the occurrence of certain price patterns.
Calculation
The mean moving averages is calculated by adding all the 12 moving averages and dividing by 12, the value is used to help to identify trend and possible condition to open position.
The 12 moving averages is spliced by 3 ranges, initial range (moving average lines 1 to 4), middle range (moving average lines 5 to 8) and end range (moving average lines 9 to 12). These ranges helps to identify potential trend and market turn over.
The moving average touch price is a relationship between the low price (uptrend) or high price (downtrend) with the moving average lines, it identifies where the price (low/high) has reached the the moving average line. Fetching the value to help for opening position, set stop loss and take profit.
Since the stop loss is based and set from the previous moving average touch price value, when position is about to be open and setting the stop loss value, there is a verification to check both current and previous moving average touch price to recalculate the stop loss value.
The turnover trend checks for a possible market turnover event, setting up a new profit target, this setting when enabled is to be helpful when a turnover occurs against the position to exit position with some profit based on highest high price if long or lowest low price if short.
The turnover signal is similar to turnover trend. The difference is that when this setting is enabled and it triggers, it simply exit the current position and opens up a reverse position, long goes short and short goes long. And there is an complement optional that checks current price exit profitable.
Entry Position
Long Position:
Price is higher than the mean moving averages. Meaning possible uptrend.
The lines of the middle range from the moving averages are in increasing order. Meaning possible uptrend.
The current high pierced up previous high.
Fetch the previous value of the moving average touch price. Meaning the low price has touched one of the moving average lines, which that value is conditioning to open position.
Short Position:
Price is lower than the mean moving averages. Meaning possible downtrend.
The lines of the middle range from the moving averages are in decreasing order. Meaning possible downtrend.
The current low pierced down previous low.
Fetch the previous value of the moving average touch price. Meaning the high price has touched one of the moving average lines, which that value is conditioning to open position.
Risk Management
Stop Loss:
The stop loss is based from the previous moving average touch price value, high price for short and low price for long or occurs an verification to check for both current and previous moving average touch price value and a recalculation is done to set the stop loss.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Turnover Trend
Long Position:
The moving averages initial range lines signals a possible market turnover. Meaning long might be going short.
Fetches the highest high hit since the opening of the position, setting that value to the new profit target.
Short Position:
The moving averages initial range lines signals a possible market turnover. Meaning short might be going long.
Fetches the lowest low hit since the opening of the position, setting that value to the new profit target.
Zero Lag Moving Average with Gaussian weightsIntroduction
The Zero Lag Moving Average (ZLMA) is a powerful technical indicator that aims to eliminate the lag inherent in traditional moving averages. This post provides a comprehensive exploration of the ZLMA with Gaussian Weights (GWMA) indicator, discussing the concepts, the calculations, and its application in trading.
Concepts
Zero Lag Moving Average (ZLMA): A ZLMA is an advanced moving average designed to reduce the lag in price movements associated with conventional moving averages. This reduction in lag enables traders to make more informed decisions based on the most recent price data.
Gaussian Weights: Gaussian weights are derived from the Gaussian function, which is a mathematical function used to calculate probabilities in a normal distribution. The Gaussian function is smooth, symmetric, and has a bell-shaped curve. In this context, Gaussian weights are used to calculate the weighted average of a series of data points.
Why Gaussian Weights are Beneficial
Gaussian Weights offer several advantages in comparison to traditional moving averages. One of the main reasons for using Gaussian Weights is to address the issue of lag, which is commonly associated with simple and exponential moving averages. By reducing lag, traders can make more informed decisions based on up-to-date information.
Another advantage of Gaussian Weights is their mathematical foundation, which is rooted in the Gaussian function. This function describes the normal distribution in probability theory and statistics. The smooth and symmetric bell-shaped curve of Gaussian Weights enables a more refined approach to handling data points, resulting in a more responsive and accurate moving average.
While exponential moving averages (EMAs) also assign more weight to recent data points, they can still exhibit some lag. Gaussian Weights, on the other hand, offer a smoother and more adaptive solution to different market conditions. By adjusting the smoothing period, traders can tailor the Gaussian Weights to their specific needs, making them a versatile tool for various trading strategies.
In summary, Gaussian Weights provide a valuable alternative to traditional moving averages due to their ability to reduce lag, their strong mathematical foundation, and their adaptability to different market conditions. These benefits make Gaussian Weights a worthwhile consideration for traders looking to enhance their trading strategies.
Calculations
The ZLMA with GWMA consists of two main calculations:
Gaussian Weight Calculation: The Gaussian weight for a given 'k' and 'smooth_per' is calculated using the standard deviation (sigma) and the exponent part of the Gaussian function.
Zero-Lag GWMA Calculation: The zero-lag GWMA is calculated using a source buffer, a Gaussian weighted moving average (gwma1), and an output array. The source buffer stores the input data, the gwma1 array stores the first Gaussian weighted moving average, and the output array stores the final zero-lag moving average.
Application in Trading
The ZLMA with GWMA indicator can be used to identify trends and potential entry/exit points in trading:
Trend Identification: When the ZLMA is above the price, it indicates a bearish trend, and when it is below the price, it indicates a bullish trend.
Entry/Exit Points: Traders can use crossovers between the ZLMA and price to identify potential entry and exit points. A long position could be taken when the price crosses above the ZLMA, and a short position could be taken when the price crosses below the ZLMA.
Conclusion
The Zero Lag Moving Average with Gaussian Weights is a powerful and versatile indicator that can be used in various trading strategies. By minimizing the lag associated with traditional moving averages, the ZLMA with GWMA provides traders with more accurate and timely information about price trends and potential trade opportunities.
+ Awesome OscillatorHi again. I have another indicator that I think is pretty neat.
I had the idea of creating an Awesome Oscillator for my Ultimate MA, just to see what kind of signals it might produce. If you're not familiar with my UMA you should go take a look at it, but essentially it is just an average of eight different length MAs, and if you're not familiar with the Awesome Oscillator, it is simply a comparison of the gap between two different moving averages (traditionally a 5 and 34 SMA) plotted as a histogram below the price chart. The two UMAs I was comparing in this version of the AO were the Hull and Simple. It looked okay, but I thought due to the nature of the movements of these MAs, that it was necessary to add something to this indicator in order to validate its creation and make it truly useful
I came to the idea of simply comparing the closing price of the asset on the chart to both the Awesome Oscillator moving averages. What this effectively does is gives you a representation of the moving averages on the chart (assuming you are using those same MAs) as an oscillator below the chart, enabling you to remove the moving averages from your price chart (obviously if you so choose). For me, I like this because fewer things on the chart makes it easier for me to see the price action and structure of the market clearly, or add something like a tWAP or two.
So, like, "how exactly would I use this indicator?"" you're probably asking.
First off: the Awesome Oscillator. By default it is a faintly shaded area, and is the least obvious part of the indicator.
Second: the plotted line. This is what I call the baseline (if you're familiar with NNFX, then you know what this is). It's basically your bias moving average (this means it defines, based on its lookback or length, whether momentum is bullish, bearish or ranging). In the case of the oscillator though, the ZERO line represents the baseline, and the oscillating line represents price in relation to it. If the line is above the zero line then price is above the moving average, and vice versa if it's below. The farther from the center line the baseline price is the greater the volatility,
Third: the histogram. This is the faster moving average, and same rules apply to it as your baseline. You can think of your fast moving average as a trade entry trigger, or an exit. It shows more immediate momentum shifts.
What's interesting about the relationships of all three of these things is that you don't actually NEED all three displayed. Because the Awesome Oscillator is a relation of your two moving averages, and the baseline and histogram are representational of the price relative to those two moving averages, you will notice that when the histogram (fast MA) flips up or down is the same exact time that the baseline price dips into the AO. The AO is effectively a moving average on that. So you can run this with just the AO and Baseline, or just the Baseline and fast MA histogram. To get started, I might recommend keeping your moving averages that you use on the chart just so you can see how this indicator works.
Both the fast MA and Baseline will show nice divergences (divergence indicator is added if you want to use it). And I've added Donchian Channels as upper and lower bounds that act neatly as support or resistance (especially effective if you're using my UMA with Bollinger Bands, or Magic Carpet Bands).
I've also done the usual colored candles thing, which gives you another great reason to get the moving averages off your chart. There are of course alerts for conditions that one might need to be alerted to as well.
Below are some images of different ways you might set these up using the default moving average/baseline settings. In all of these I've left the moving averages on the price chart (with the addition of a 233 SMA) so you can see the relationship between the indicators.
Right here is the indicator set up with just the awesome oscillator and baseline price. Gives a cleaner overall look. You can see that every time the baseline crosses the awesome oscillator is when price crosses the 8 SMA. Candle colors are based on if candle closes above baseline or below.
This is the indicator set up without the awesome oscillator. Here you can see candle closes over the 8 SMA (fast moving average) are shown by the histogram. Candle coloring is still the same as the above image.
This image looks identical to the first, except that the candle coloring is different. This time it is based on the 8 SMA (same as the baseline entering the awesome oscillator).
And the final example image. This one depicts the awesome oscillator and the fast moving average histogram. Candle coloring is based on the awesome oscillator. This can be a great way to visualize momentum because the awesome oscillator is depicting the crossing of the moving averages. A lot of people poo-poo moving average crosses, but I'd say they're wrong. Well, they're right and wrong. Depends on the MAs you're using. The power in moving average crosses is in their ability to show bullish or bearish momentum (or ranging behavior if they continually cross over each other). If you're using slow moving averages, then crosses are often very late (hence so many people who don't know saying, "but moving average crosses are too laggy". Here you might try changing these and having the baseline be faster than the UMA, and actually plot on chart the UMA (or some other moving average). These are just some thoughts.
Anyway, I hope this indicator proves useful to you all. I think for anyone looking to look at price action a bit more, but is used to using moving averages, this could be a really useful indicator. Most oscillating indicators (if not all) are built around moving averages, but they're never explained in such a way as I'm explaining how this one works (I don't think). I think knowing this could help many traders come to a deeper understanding of what the indicator they're using is actually doing.
On Chart Anticipated Moving Average Crossover IndicatorIntroducing the on chart moving average crossover indicator.
This is my On Chart Pinescript implementation of the Anticipated Simple Moving Average Crossover idea.
This indicator plots 6 user defined moving averages.
It also plots the 5 price levels required on the next close to cross a user selected moving average with the 5 other user defined moving averages
It also gives signals of anticipated moving average crosses as arrows on chart and also as tradingview alerts with a very high degree of accuracy
Much respect to the creator of the original idea Mr. Dimitris Tsokakis
Moving Averages
A moving average simplifies price data by smoothing it out by averaging closing prices and creating one flowing line which makes seeing the trend easier.
Moving averages can work well in strong trending conditions, but poorly in choppy or ranging conditions.
Adjusting the time frame can remedy this problem temporarily, although at some point, these issues are likely to occur regardless of the time frame chosen for the moving average(s).
While Exponential moving averages react quicker to price changes than simple moving averages. In some cases, this may be good, and in others, it may cause false signals.
Moving averages with a shorter look back period (20 days, for example) will also respond quicker to price changes than an average with a longer look back period (200 days).
Trading Strategies — Moving Average Crossovers
Moving average crossovers are a popular strategy for both entries and exits. MAs can also highlight areas of potential support or resistance.
The first type is a price crossover, which is when the price crosses above or below a moving average to signal a potential change in trend.
Another strategy is to apply two moving averages to a chart: one longer and one shorter.
When the shorter-term MA crosses above the longer-term MA, it's a buy signal, as it indicates that the trend is shifting up. This is known as a "golden cross."
Meanwhile, when the shorter-term MA crosses below the longer-term MA, it's a sell signal, as it indicates that the trend is shifting down. This is known as a "dead/death cross."
MA and MA Cross Strategy Disadvantages
Moving averages are calculated based on historical data, and while this may appear predictive nothing about the calculation is predictive in nature.
Moving averages are always based on historical data and simply show the average price over a certain time period.
Therefore, results using moving averages can be quite random.
At times, the market seems to respect MA support/resistance and trade signals, and at other times, it shows these indicators no respect.
One major problem is that, if the price action becomes choppy, the price may swing back and forth, generating multiple trend reversal or trade signals.
When this occurs, it's best to step aside or utilize another indicator to help clarify the trend.
The same thing can occur with MA crossovers when the MAs get "tangled up" for a period of time during periods of consolidation, triggering multiple losing trades.
Ensure you use a robust risk management system to avoid getting "Chopped Up" or "Whip Sawed" during these periods.
Market Analysis Assistant This indicator uniquely maps and interprets key market conditions using Moving Averages, MACD, RSI, and Bollinger Bands. Unlike traditional indicators that only display visual signals, this tool provides written analysis directly on your chart as soon as specific conditions are met. This feature makes it easier to understand the market’s current state and anticipate potential moves.
Why Moving Averages? Moving Averages are essential for identifying the overall trend of the market. By analyzing the 200, 20, and 9-period Moving Averages, this indicator helps traders quickly determine whether the market is in an uptrend, downtrend, or sideways phase. The integration of multiple averages offers a comprehensive view, allowing for more accurate trend identification.
Why MACD? The MACD is a powerful tool for spotting trend reversals and momentum shifts. By monitoring MACD crossovers, divergences, and the position of the MACD line relative to the zero line, this indicator helps you identify potential changes in the trend direction before they fully develop, giving you a critical edge.
Why RSI? RSI is crucial for understanding the market's overbought and oversold conditions. By tracking RSI levels and its crossover with its moving average, this indicator provides early warnings for potential trend reversals or continuations, helping you time your entries and exits more effectively.
Why Bollinger Bands? Bollinger Bands are used to measure market volatility and identify breakout opportunities. By analyzing the price’s relationship with the upper and lower bands, this indicator helps traders spot potential overbought or oversold conditions, as well as possible breakout scenarios, offering a clear view of market dynamics.
Trend Identification (getTrend()): Detects whether the market is in an uptrend, downtrend, or sideways phase by analyzing the position of the price relative to the 200, 20, and 9-period moving averages.
MACD Analysis (analyzeMACD()): Identifies potential trend reversals or continuations through MACD divergence, crossovers, and the MACD signal line's position relative to the zero line.
RSI Monitoring (analyzeRSI()): Detects overbought and oversold conditions and anticipates trend continuation or corrections based on RSI crossings with its moving average.
Trap Zone Detection (analyzeTrapZone()): Highlights areas of potential price consolidation between the 20 and 200-period moving averages, indicating possible breakouts.
Bollinger Bands Analysis (analyzeBollingerBands()): Analyzes the price’s relationship with Bollinger Bands to identify overbought/oversold conditions, breakouts, and potential trend continuations or correction.
Fibonacci retracement will also check the moment the price tests a monthly or daily weekly Fibonacci retracement
What Makes This Indicator Unique?
This indicator stands out by transforming complex technical analysis into clear, written insights directly on your chart. As soon as specific conditions are met—such as a MACD crossover or an RSI overbought/oversold level—this tool immediately displays a written summary of the event, helping traders to quickly understand and act on market developments.
How to Use My Indicator:
The indicator is designed to provide detailed, real-time market condition analysis using Moving Averages, MACD, RSI, and Bollinger Bands. When certain market conditions are met, such as the price testing a specific moving average or the MACD indicating a potential reversal, the indicator displays this information in written form directly on the chart, in both English and Portuguese.
How to Interpret the Displayed Information:
The information displayed by the indicator can be used for:
Identifying Support and Resistance: The indicator can help identify when the price is testing an important support or resistance level, such as a moving average or a Fibonacci level, allowing the user to decide whether to enter or exit a position.
Trend Detection: If the indicator shows that the price is above the 200, 20, and 9-period moving averages, this may be a sign of an uptrend, indicating that the user should consider maintaining or opening buy positions.
Correction Signals: When the MACD indicates a potential correction, the user may decide to protect their profits by adjusting stops or even exiting the position to avoid losses.
Identifying Overbought/Oversold Conditions: Based on the RSI, the indicator can alert to overbought or oversold conditions, helping the user avoid entering a trade at an unfavorable time.
Example of Use:
the indicator shows several important pieces of information, such as:
"US100 Price is at the 50.0% Fibonacci level (Last Monthly)."
This suggests that the price is testing a significant Fibonacci level, which could be a point of reversal or continuation. A trader can use this information to adjust their entry or exit strategy.
"DXY RSI below 30: Indication of oversold condition"
This indicates that the DXY is in an oversold condition, which might suggest an upcoming bullish reversal. A trader could consider this when trading DXY-related assets.
"Bullish Trend: Price is above the 200, 20, and 9-period moving averages."
This confirms an uptrend, giving the user more confidence to hold long positions.
Availability:
This indicator is available in two languages: English and Portuguese. It is ideal for traders who prefer analysis in English as well as those who prefer it in Portuguese, making it a versatile and accessible tool for traders from different backgrounds
Este indicador mapeia e interpreta de forma única as principais condições de mercado utilizando Médias Móveis, MACD, RSI e Bandas de Bollinger. Ao contrário dos indicadores tradicionais que apenas exibem sinais visuais, esta ferramenta oferece uma análise escrita diretamente no seu gráfico assim que determinadas condições são atendidas. Isso facilita o entendimento do estado atual do mercado e a antecipação de possíveis movimentos.
Por que Médias Móveis? As Médias Móveis são essenciais para identificar a tendência geral do mercado. Ao analisar as Médias Móveis de 200, 20 e 9 períodos, este indicador ajuda os traders a determinarem rapidamente se o mercado está em tendência de alta, baixa ou em fase lateral. A integração de múltiplas médias oferece uma visão abrangente, permitindo uma identificação mais precisa das tendências.
Por que MACD? O MACD é uma ferramenta poderosa para identificar reversões de tendência e mudanças de momentum. Monitorando os cruzamentos do MACD, divergências e a posição da linha MACD em relação à linha zero, este indicador ajuda você a identificar possíveis mudanças na direção da tendência antes que elas se desenvolvam completamente, dando-lhe uma vantagem crítica.
Por que RSI? O RSI é crucial para entender as condições de sobrecompra e sobrevenda do mercado. Acompanhando os níveis do RSI e seu cruzamento com sua média móvel, este indicador fornece avisos antecipados para possíveis reversões ou continuações de tendência, ajudando você a cronometrar suas entradas e saídas de forma mais eficaz.
Por que Bandas de Bollinger? As Bandas de Bollinger são usadas para medir a volatilidade do mercado e identificar oportunidades de rompimento. Ao analisar a relação do preço com as bandas superior e inferior, este indicador ajuda os traders a identificar condições de sobrecompra ou sobrevenda, bem como possíveis cenários de rompimento, oferecendo uma visão clara da dinâmica do mercado.
Identificação de Tendências (getTrend()): Detecta se o mercado está em tendência de alta, baixa ou em fase lateral, analisando a posição do preço em relação às médias móveis de 200, 20 e 9 períodos.
Análise de MACD (analyzeMACD()): Identifica possíveis reversões ou continuações de tendência através de divergências do MACD, cruzamentos, e a posição da linha de sinal do MACD em relação à linha zero.
Monitoramento do RSI (analyzeRSI()): Detecta condições de sobrecompra e sobrevenda e antecipa a continuação da tendência ou correções com base nos cruzamentos do RSI com sua média móvel.
Detecção de Zona de Armadilha (analyzeTrapZone()): Destaca áreas de possível consolidação de preços entre as médias móveis de 20 e 200 períodos, indicando possíveis rompimentos.
Análise das Bandas de Bollinger (analyzeBollingerBands()): Analisa a relação do preço com as Bandas de Bollinger para identificar condições de sobrecompra/sobrevenda, rompimentos e possíveis continuações de tendência ou correção.
A retração de Fibonacci também verificará o momento em que o preço testa uma retração de Fibonacci semanal mensal ou diária
O que Torna Este Indicador Único?
Este indicador se destaca por transformar análises técnicas complexas em insights escritos claros diretamente no seu gráfico. Assim que condições específicas são atendidas—como um cruzamento do MACD ou um nível de sobrecompra/sobrevenda do RSI—esta ferramenta exibe imediatamente um resumo escrito do evento, ajudando os traders a entenderem e agirem rapidamente sobre as mudanças do mercado.
Como Utilizar o Meu Indicador:
O indicador foi desenvolvido para oferecer uma análise detalhada e em tempo real das condições de mercado, utilizando os conceitos de Médias Móveis, MACD, RSI e Bandas de Bollinger. Quando certas condições de mercado são atingidas, como o preço testando uma média móvel específica ou o MACD indicando uma possível reversão, o indicador exibe essas informações de forma escrita diretamente no gráfico, em inglês e português.
Como Interpretar as Informações Exibidas:
As informações exibidas pelo indicador podem ser usadas para:
Identificação de Suportes e Resistências: O indicador pode ajudar a identificar quando o preço está testando um nível de suporte ou resistência importante, como uma média móvel ou um nível de Fibonacci, permitindo ao usuário decidir se deve entrar ou sair de uma posição.
Detecção de Tendências: Se o indicador mostra que o preço está acima das médias móveis de 200, 20 e 9 períodos, isso pode ser um sinal de uma tendência de alta, indicando que o usuário deve considerar manter ou abrir posições de compra.
Sinais de Correção: Quando o MACD indica uma possível correção, o usuário pode decidir proteger seus lucros ajustando os stops ou até mesmo saindo da posição para evitar perdas.
Identificação de Condições de Sobrecompra/Sobrevenda: Com base no RSI, o indicador pode alertar sobre condições de sobrecompra ou sobrevenda, ajudando o usuário a evitar entrar em uma operação em um momento desfavorável.
Exemplo de Utilização:
o indicador mostra várias informações importantes, como:
"O preço do US100 está no nível de Fibonacci de 50,0% (mês passado)."
Isso sugere que o preço está testando um nível significativo de Fibonacci, o que pode ser um ponto de reversão ou continuação. Um trader pode usar essa informação para ajustar sua estratégia de entrada ou saída.
DXY RSI abaixo de 30: Indicação de condição de sobrevenda"
Isso indica que o DXY está em uma condição de sobrevenda, o que pode sugerir uma reversão de alta em breve. Um trader pode considerar isso ao fazer operações relacionadas ao DXY.
"Tendência de alta: o preço está acima das médias móveis de 200, 20 e 9 períodos."
Isso confirma uma tendência de alta, dando ao usuário mais confiança para manter posições longas.
Disponibilidade:
Este indicador está disponível em dois idiomas: inglês e português. Ele é ideal tanto para traders que preferem análises em inglês quanto para aqueles que preferem em português. Isso o torna uma ferramenta versátil e acessível para traders de diferentes origens.
Trend_Trader_WMA (Momentum)<---> Caution! This is first test version of indicator. I am ready to get more ideas+feedback to develop it more. <--->
The "Momentum_Trader_WMA" indicator is a versatile technical analysis tool designed to help traders identify potential trend changes and momentum shifts in the market. It combines multiple indicators and moving averages to provide a comprehensive view of price action and momentum.
Key Features:
Weighted Moving Averages (WMAs): The indicator calculates two different WMAs with user-defined lengths, providing a smoothed representation of price data.
Average True Range (ATR) Bands: ATR is used to calculate dynamic bands around the WMA Average. These bands can help traders gauge market volatility and potential breakout points. The color of the ATR bands can be seen as an early signal of trends or the continuation of current trends.
Commodity Channel Index (CCI): CCI is a momentum oscillator that measures the relative strength of price changes. The indicator calculates CCI values based on a user-defined period.
Exponential Moving Average (EMA) of CCI: An EMA of CCI is plotted to help identify trends and momentum shifts.
Color-Coded Bands: The ATR bands change colors based on CCI conditions, providing visual cues for potential trading opportunities. When ATR bands transition from narrow (indicating low volatility) to wide (indicating increased volatility), it can be seen as an early signal of a potential trend change or the continuation of the current trend.
Buy and Sell Signals: The indicator generates buy and sell signals based on crossovers of WMAs and CCI thresholds, making it easier for traders to identify entry and exit points.
Customizable Moving Averages: Traders can enable or disable different moving averages (e.g., SMA, EMA, WMA, RMA, VWMA, HMA) with various periods and colors to adapt the indicator to their trading preferences.
CCI Dot Alerts: Dots are displayed at the bottom of the chart based on CCI values, helping traders spot extreme CCI conditions.
How to Use:
Trend Identification: The WMAs and ATR bands can help identify the current trend direction and its strength. When the WMAs are in an uptrend (green) and the ATR bands widen, it may indicate a strong bullish trend. Conversely, when the WMAs are in a downtrend (red) and the ATR bands narrow, it may suggest a weakening bearish trend.
Momentum Confirmation: The CCI and its EMA provide insights into market momentum. Look for CCI crossovers above 100 for potential bullish momentum and below -100 for potential bearish momentum.
Buy and Sell Signals: Pay attention to the buy and sell signals generated by the indicator. Buy when the WMAs cross over and CCI crosses above 100. Sell when the WMAs cross under and CCI crosses below -100.
ATR Bands as Early Signals: The color changes in the ATR bands can be seen as early signals of trends or the continuation of current trends. Wide ATR bands may indicate increased volatility and potential trend changes, while narrow ATR bands suggest reduced volatility and potential trend continuation.
Moving Averages: Customize the indicator by enabling or disabling specific moving averages according to your preferred trading strategy.
CCI Dots: Use the CCI dots to identify extreme CCI conditions, which may indicate overbought or oversold market conditions.
PS:
Recommended to use Indicator with price action conecpts(eg. support and resistance) as they play important role in any market.
Buy and sell signals are not really accurate. I would personally look for trend shift in WMA middle line and confirmation from CCI dots at bottom. For example. If middle line turns green and within recent 3-4 candles (or next 3-4 candles) dots tunrns green also, that means momentum has been rised in the direction of bulls.
pls, take s/r concepts first when working. I am thinking to add more precise buy sell signal method to make it easier to trade.
Good luck with your trades :)
Alxuse Supertrend 4EMA Buy and Sell for tutorialAll abilities of Supertrend, moreover :
Drawing 4 EMA band & the ability to change values, change colors, turn on/off show.
Sends Signal Sell and Buy in multi timeframe.
The ability used in the alert section and create customized alerts.
To receive valid alerts the replay section , the timeframe of the chart must be the same as the timeframe of the indicator.
Supertrend with a simple EMA Filter can improve the performance of the signals during a strong trend.
For detecting the continuation of the downward and upward trend we can use 4 EMA colors.
In the upward trend , the EMA lines are in order of green, blue, red, yellow from bottom to top.
In the downward trend, the EMA lines are in order of yellow, red, blue, green from bottom to top.
How it works:
x1 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA3, MA4)
x2 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA2, MA3)
x3 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA1, MA2)
y1 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA3, MA4)
y2 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA2, MA3)
y3 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA1, MA2)
Red triangle = x1 or x2 or x3
Green triangle = y1 or y2 or y3
Long = BUY signal and followed by a Green triangle
Exit Long = SELL signal
Short = SELL signal and followed by a Red triangle
Exit Short = BUY signal
It is also possible to get help from the Stochastic RSI and MACD indicators for confirmation.
For receiving a signal with these two conditions or more conditions, i am making a video tutorial that I will release soon.
Supertrend
Definition
Supertrend is a trend-following indicator based on Average True Range (ATR). The calculation of its single line combines trend detection and volatility. It can be used to detect changes in trend direction and to position stops.
The basics
The Supertrend is a trend-following indicator. It is overlaid on the main chart and their plots indicate the current trend. A Supertrend can be used with varying periods (daily, weekly, intraday etc.) and on varying instruments.
The Supertrend has several inputs that you can adjust to match your trading strategy. Adjusting these settings allows you to make the indicator more or less sensitive to price changes.
For the Supertrend inputs, you can adjust atrLength and multiplier:
the atrLength setting is the lookback length for the ATR calculation;
multiplier is what the ATR is multiplied by to offset the bands from price.
When the price falls below the indicator curve, it turns red and indicates a downtrend. Conversely, when the price rises above the curve, the indicator turns green and indicates an uptrend. After each close above or below Supertrend, a new trend appears.
Summary
The Supertrend helps you make the right trading decisions. However, there are times when it generates false signals. Therefore, it is best to use the right combination of several indicators. Like any other indicator, Supertrend works best when used with other indicators such as MACD, Parabolic SAR, or RSI.
Exponential Moving Average
Definition
The Exponential Moving Average (EMA) is a specific type of moving average that points towards the importance of the most recent data and information from the market. The Exponential Moving Average is just like it’s name says - it’s exponential, weighting the most recent prices more than the less recent prices. The EMA can be compared and contrasted with the simple moving average.
Similar to other moving averages, the EMA is a technical indicator that produces buy and sell signals based on data that shows evidence of divergence and crossovers from general and historical averages. Additionally, the EMA tries to amplify the importance that the most recent data points play in a calculation.
It is common to use more than one EMA length at once, to provide more in-depth and focused data. For example, by choosing 10-day and 200-day moving averages, a trader is able to determine more from the results in a long-term trade, than a trader who is only analyzing one EMA length.
It’s best to use the EMA when for trending markets, as it shows uptrends and downtrends when a market is strong and weak, respectively. An experienced trader will know to look both at the line the EMA projects, as well as the rate of change that comes from each bar as it moves to the next data point. Analyzing these points and data streams correctly will help the trader determine when they should buy, sell, or switch investments from bearish to bullish or vice versa.
Short-term averages, on the other hand, is a different story when analyzing Exponential Moving Average data. It is most common for traders to quote and utilize 12- and 26-day EMAs in the short-term. This is because they are used to create specific indicators. Look into Moving Average Convergence Divergence (MACD) for more information. Similarly, the 50- and 200-day moving averages are most common for analyzing long-term trends.
Moving averages can be very useful for traders using technical analysis for profit. It is important to identify and realize, however, their shortcomings, as all moving averages tend to suffer from recurring lag. It is difficult to modify the moving average to work in your favor at times, often having the preferred time to enter or exit the market pass before the moving average even shows changes in the trend or price movement for that matter.
All of this is true, however, the EMA strives to make this easier for traders. The EMA is unique because it places more emphasis on the most recent data. Therefore, price movement and trend reversals or changes are closely monitored, allowing for the EMA to react quicker than other moving averages.
Limitations
Although using the Exponential Moving Average has a lot of advantages when analyzing market trends, it is also uncertain whether or not the use of most recent data points truly affects technical and market analysis. In addition, the EMA relies on historical data as its basis for operating and because news, events, and other information can change rapidly the indicator can misinterpret this information by weighting the current prices higher than when the event actually occurred.
Summary
The Exponential Moving Average (EMA) is a moving average and technical indicator that reflects and projects the most recent data and information from the market to a trader and relies on a base of historical data. It is one of many different types of moving averages and has an easily calculable formula.
The added features to the indicator are made for training, it is advisable to use it with caution in tradings.
Adaptive MA-Bollinger HistogramVisualize two of your favorite moving averages in a fun new way.
This script calculates the distance (or difference) between the price and two moving averages of your choosing and then creates two histograms.
The two histograms are plotted inversely, so if the price is over both moving averages, one will be positive above the centerline while the other still positive will be below the centerline.
(In a future update you will have the option to have them both positive at the same time)
Next, what it does is apply Bollinger Bands (optional) to each of the histograms.
This creates a very interesting effect that can highlight areas of interest you may miss with other indicators.
You have plenty of options for coloring, the type of moving average, Bollinger Band length, and toggling features on and off.
Give it a few minutes of your time to study, and see what information you can learn from watching this indicator by comparing it with the chart.
Here is a full user guide:
Adaptive MA-Bollinger Histogram Indicator User Guide
Welcome to the user guide for the **Adaptive MA-Bollinger Histogram** indicator. This custom indicator is designed to help traders analyze trends and potential reversals in a financial instrument's price movements. The indicator combines two Moving Averages (MA) and Bollinger Bands to provide valuable insights into market conditions.
### Indicator Overview
The Adaptive MA-Bollinger Histogram indicator comprises the following components:
1. **Moving Averages (MA1 and MA2):** The indicator uses two moving averages, namely MA1 and MA2, to track different time periods. MA1 has a user-defined length (default: 50) and MA2 has a longer user-defined length (default: 100). These moving averages can be calculated using different methods such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), or Smoothed Moving Average (RMA).
2. **Histograms:** The indicator displays histograms based on the differences between the price source and the respective moving averages. Positive values of the histogram for MA1 are plotted in one color (default: green), while negative values are plotted in another color (default: red). Similarly, positive values of the histogram for MA2 are plotted in one color (default: blue), while negative values are plotted in another color (default: yellow). It's important to note that the histogram for MA1 is plotted positively, while the histogram for MA2 is plotted inversely.
3. **Bollinger Bands:** The indicator also features Bollinger Bands calculated based on the differences between the price source and the respective moving averages (dist1 and dist2). Bollinger Bands consist of three lines: the middle band, upper band, and lower band. These bands help visualize the potential volatility and overbought/oversold levels of the instrument's price.
### Understanding the Indicator
- **Histograms:** The histograms highlight the divergence between the price and the two moving averages. When the histogram for MA1 is positive, it indicates that the price is above the MA1. Conversely, when the histogram for MA1 is negative, it suggests that the price is below the MA1. Similarly, the histogram for MA2 is plotted inversely.
- **Bollinger Bands:** The Bollinger Bands consist of three lines. The middle band represents the moving average (MA1 or MA2), while the upper and lower bands are calculated based on the standard deviation of the differences between the price source and the moving average. The bands expand during periods of higher volatility and contract during periods of lower volatility.
### Possible Trading Ideas
1. **Trend Confirmation:** When the histograms for both MA1 and MA2 are consistently positive, it may indicate a strong bullish trend. Conversely, when both histograms are consistently negative, it may suggest a strong bearish trend.
2. **Divergence:** Divergence between price and the histograms could signal potential reversals. For example, if the price is making new highs while the histogram is declining, it might indicate a bearish divergence and a possible upcoming trend reversal.
3. **Bollinger Bands Squeeze:** A narrowing of the Bollinger Bands indicates lower volatility and often precedes a significant price movement. Traders might consider a potential breakout trade when the bands start to expand again.
4. **Overbought/Oversold Levels:** Prices touching or exceeding the upper Bollinger Band could suggest overbought conditions, while prices touching or falling below the lower Bollinger Band could indicate oversold conditions. Traders might look for reversals or corrections in such scenarios.
### Customization
- You can adjust the parameters such as MA lengths, Bollinger Bands length, width, and colors to suit your preferences and trading strategy.
### Conclusion
The **Adaptive MA-Bollinger Histogram** indicator provides a comprehensive view of price trends, divergences, and potential reversal points. Traders can use the information from this indicator to make informed decisions in their trading strategies. However, like any technical tool, it's recommended to combine this indicator with other forms of analysis and risk management techniques for optimal results.
HTF Trend Filter - Dynamic SmoothingSummary of the HTF Trend Filter
The Higher Time Frame (HTF) Trend Filter is a cutting-edge tool crafted for traders who want to scan moving average trend lines time efficiently. At its core, it harnesses the power of dynamic smoothing to present a sleek moving average line regardless of the time frame you’re on. Here's a glimpse of the advantages you unlock with the HTF trend filter:
Dynamic Smoother: Ever been irked by jagged lines on your chart? With the dynamic smoother, those days are gone. The smoother streamlines HTF moving average line on your current lower time frame chart.
Time Efficiency: Time is of the essence in trading. With this tool, you can nimbly toggle between time charts without the hassle of readjusting input parameters, ensuring your screening process remains unhindered.
Features of the Script
Variety of Moving Averages: The script caters to different trading styles by offering a plethora of moving average types, ranging from the classic SMA and EMA to the innovative Hull and McGinley Dynamic MAs.
Dynamic Smoothing: This is the script's pièce de résistance. The dynamic smoothing factor is ingeniously derived by taking the ratio of minutes of the higher time frame to the current time frame. This ensures the moving average remains fluid and consistent across different time frames, eliminating the common pitfalls of jagged moving averages.
Reversal Indicators: It includes a reversal indicator. Green circles pinpoint the start of a potential uptrend, while red ones signify a potential downtrend.
Customizable Alerts: To ensure you never miss a beat, the script is equipped with customizable alert conditions.
Trading Idea
The essence of trading lies in confirming assumptions and validating trends. The HTF Trend Dynamic Smoother positions itself as a potential game-changer in this domain. One could consider using the HTF trend dynamic smoother as a supplementary confirmation tool alongside other primary indicators. For instance, if you're plotting a moving average on a lower time frame, toggling the HTF smoother can offer a broader perspective of the trend from a higher time frame. By ensuring alignment between these perspectives, you could potentially trade with increased confidence, reinforcing your lower time frame strategies with higher time frame confirmations. It's worth noting, however, that while this method can offer additional layers of information and validation, it doesn't replace due diligence. Every trade decision should be the culmination of thorough analysis, and no tool should be solely relied upon for decision-making.
Limitations
While the HTF Trend Filter is an exceptional tool, like all tools, it has its constraints. Lower Time Frame Dependency: For the indicator to function optimally, it's paramount to ensure that the time frame open is always lower (or equal) than the one selected in the input parameters. This limitation is crucial to remember as the dynamic smoother's accuracy hinges on this condition.
In conclusion, the HTF Trend Filter - Dynamic Smoothing is a remarkable blend of innovation and efficiency, tailored for traders who demand fast screening of higher time frame MA trends. Due to it simplistic design it gives a user-friendly experience. However, always remember the golden rule of trading: utilize tools as part of a comprehensive strategy, never in isolation.
R-squared Adaptive T3 [Loxx]R-squared Adaptive T3 is an R-squared adaptive version of Tilson's T3 moving average. This adaptivity was originally proposed by mladen on various forex forums. This is considered experimental but shows how to use r-squared adapting methods to moving averages. In theory, the T3 is a six-pole non-linear Kalman filter.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis. Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD, Momentum, Relative Strength Index) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA (simple moving average) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA(n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA.
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE/2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE/2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE/2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA, popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE/2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA(3) has lag 1, and EMA(11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA(3) through itself 5 times than if I just take EMA(11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA(3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA(7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA(n) = EMA(n) + EMA(time series - EMA(n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA. The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA(n) + EMA(time series - EMA(n))*.7;
This is algebraically the same as:
EMA(n)*1.7-EMA(EMA(n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD(n,v) = EMA(n)*(1+v)-EMA(EMA(n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA, and when v=1, GD is DEMA. In between, GD is a cooler DEMA. By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD(GD(GD(n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA(n)) to correct themselves. In Technical Analysis, these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Overlay Indicators (EMAs, SMAs, Ichimoku & Bollinger Bands)This is a combination of popular overlay indicators that are used for dynamic support and resistance, trade targets and trend strength.
Included are:
-> 6 Exponential Moving Averages
-> 6 Simple Moving Averages
-> Ichimoku Cloud
-> Bollinger Bands
-> There is also a weekend background marker ideal for cryptocurrency trading
Using all these indicators in conjunction with each other provide great confluence and confidence in trades and price targets.
An explanation of each indicator is listed below.
What Is an Exponential Moving Average (EMA)?
"An exponential moving average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average (SMA), which applies an equal weight to all observations in the period.
What Does the Exponential Moving Average Tell You?
The 12- and 26-day exponential moving averages (EMAs) are often the most quoted and analyzed short-term averages. The 12- and 26-day are used to create indicators like the moving average convergence divergence (MACD) and the percentage price oscillator (PPO). In general, the 50- and 200-day EMAs are used as indicators for long-term trends. When a stock price crosses its 200-day moving average, it is a technical signal that a reversal has occurred.
Traders who employ technical analysis find moving averages very useful and insightful when applied correctly. However, they also realize that these signals can create havoc when used improperly or misinterpreted. All the moving averages commonly used in technical analysis are, by their very nature, lagging indicators."
Source: www.investopedia.com
Popular EMA lookback periods include fibonacci numbers and round numbers such as the 100 or 200. The default values of the EMAs in this indicator are the most widely used, specifically for cryptocurrency but they also work very well with traditional.
EMAs are normally used in conjunction with Simple Moving Averages.
" What Is Simple Moving Average (SMA)?
A simple moving average (SMA) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range.
Simple Moving Average vs. Exponential Moving Average
The major difference between an exponential moving average (EMA) and a simple moving average is the sensitivity each one shows to changes in the data used in its calculation. More specifically, the EMA gives a higher weighting to recent prices, while the SMA assigns an equal weighting to all values."
Source: www.investopedia.com
In this indicator, I've included 6 popular moving averages that are commonly used. Most traders will find specific settings for their own personal trading style.
Along with the EMA and SMA, another indicator that is good for finding confluence between these two is the Ichimoku Cloud.
" What is the Ichimoku Cloud?
The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on the chart. It also uses these figures to compute a "cloud" which attempts to forecast where the price may find support or resistance in the future.
The Ichimoku cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s.1 It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals."
More info can be seen here: www.investopedia.com
I have changed the default settings on the Ichimoku to suit cryptocurrency trading (as cryptocurrency is usually fast and thus require slightly longer lookbacks) to 20 60 120 30.
Along with the Ichimoku, I like to use Bollinger Bands to not only find confluence for support and resistance but for price discovery targets and trend strength.
" What Is a Bollinger Band®?
A Bollinger Band® is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a security's price, but which can be adjusted to user preferences.
Bollinger Bands® were developed and copyrighted by famous technical trader John Bollinger, designed to discover opportunities that give investors a higher probability of properly identifying when an asset is oversold or overbought."
This article goes into great detail of the complexities of using the Bollinger band and how to use it.
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This indicator combines all these powerful indicators into one so that it is easier to input different settings, turn specific tools on or off and can be easily customised.
Bar Balance [LucF]Bar Balance extracts the number of up, down and neutral intrabars contained in each chart bar, revealing information on the strength of price movement. It can display stacked columns representing raw up/down/neutral intrabar counts, or an up/down balance line which can be calculated and visualized in many different ways.
WARNING: This is an analysis tool that works on historical bars only. It does not show any realtime information, and thus cannot be used to issue alerts or for automated trading. When realtime bars elapse, the indicator will require a browser refresh, a change to its Inputs or to the chart's timeframe/symbol to recalculate and display information on those elapsed bars. Once a trader understands this, the indicator can be used advantageously to make discretionary trading decisions.
Traders used to work with my Delta Volume Columns Pro will feel right at home in this indicator's Inputs . It has lots of options, allowing it to be used in many different ways. If you value the bar balance information this indicator mines, I hope you will find the time required to master the use of Bar Balance well worth the investment.
█ OVERVIEW
The indicator has two modes: Columns and Line .
Columns
• In Columns mode you can display stacked Up/Down/Neutral columns.
• The "Up" section represents the count of intrabars where `close > open`, "Down" where `close < open` and "Neutral" where `close = open`.
• The Up section always appears above the centerline, the Down section below. The Neutral section overlaps the centerline, split halfway above and below it.
The Up and Down sections start where the Neutral section ends, when there is one.
• The Up and Down sections can be colored independently using 7 different methods.
• The signal line plotted in Line mode can also be displayed in Columns mode.
Line
• Displays a single balance line using a zero centerline.
• A variable number of independent methods can be used to calculate the line (6), determine its color (5), and color the fill (5).
You can thus evaluate the state of 3 different components with this single line.
• A "Divergence Levels" feature will use the line to automatically draw expanding levels on divergence events.
Features available in both modes
• The color of all components can be selected from 15 base colors, with 16 gradient levels used for each base color in the indicator's gradients.
• A zero line can show a 6-state aggregate value of the three main volume balance modes.
• The background can be colored using any of 5 different methods.
• Chart bars can be colored using 5 different methods.
• Divergence and large neutral count ratio events can be shown in either Columns or Line mode, calculated in one of 4 different methods.
• Markers on 6 different conditions can be displayed.
█ CONCEPTS
Intrabar inspection
Intrabar inspection means the indicator looks at lower timeframe bars ( intrabars ) making up a given chart bar to gather its information. If your chart is on a 1-hour timeframe and the intrabar resolution determined by the indicator is 5 minutes, then 12 intrabars will be analyzed for each chart bar and the count of up/down/neutral intrabars among those will be tallied.
Bar Balances and calculation methods
The indicator uses a variety of methods to evaluate bar balance and to derive other calculations from them:
1. Balance on Bar : Uses the relative importance of instant Up and Down counts on the bar.
2. Balance Averages : Uses the difference between the EMAs of Up and Down counts.
3. Balance Momentum : Starts by calculating, separately for both Up and Down counts, the difference between the same EMAs used in Balance Averages and an SMA of double the period used for the EMAs. These differences are then aggregated and finally, a bounded momentum of that aggregate is calculated using RSI.
4. Markers Bias : It sums the bull/bear occurrences of the four previous markers over a user-defined period (the default is 14).
5. Combined Balances : This is the aggregate of the instant bull/bear bias of the three main bar balances.
6. Dual Up/Down Averages : This is a display mode showing the EMA calculated for each of the Up and Down counts.
Interpretation of neutral intrabars
What do neutral intrabars mean? When price does not change during a bar, it can be because there is simply no interest in the market, or because of a perfect balance between buyers and sellers. The latter being more improbable, Bar Balance assumes that neutral bars reveal a lack of interest, which entails uncertainty. That is the reason why the option is provided to interpret ratios of neutral intrabars greater than 50% as divergences. It is also the rationale behind the option to dampen signal lines on the inverse ratio of neutral intrabars, so that zero intrabars do not affect the signal, and progressively larger proportions of neutral intrabars will reduce the signal's amplitude, as the balance calcs using the up/down counts lose significance. The impact of the dampening will vary with markets. Weaker markets such as cryptos will often contain greater numbers of neutral intrabars, so dampening the Line in that sector will have a greater impact than in more liquid markets.
█ FEATURES
1 — Columns
• While the size of the Up/Down columns always represents their respective importance on the bar, their coloring mode is independent. The default setup uses a standard coloring mode where the Up/Down columns over/under the zero line are always in the bull/bear color with a higher intensity for the winning side. Six other coloring modes allow you to pack more information in the columns. When choosing to color the top columns using a bull/bear gradient on Balance Averages, for example, you will end up with bull/bear colored tops. In order for the color of the bottom columns to continue to show the instant bar balance, you can then choose the "Up/Down Ratio on Bar — Dual Solid Colors" coloring mode to make those bars the color of the winning side for that bar.
• Line mode shows only the line, but Columns mode allows displaying the line along with it. If the scale of the line is different than that of the scale of the columns, the line will often appear flat. Traders may find even a flat line useful as its bull/bear colors will be easily distinguishable.
2 — Line
• The default setup for Line mode uses a calculation on "Balance Momentum", with a fill on the longer-term "Balance Averages" and a line color based on the "Markers Bias". With the background set on "Line vs Divergence Levels" and the zero line on the hard-coded "Combined Bar Balances", you have access to five distinct sources of information at a glance, to which you can add divergences, divergences levels and chart bar coloring. This provides powerful potential in displaying bar balance information.
• When no columns are displayed, Line mode can show the full scale of whichever line you choose to calculate because the columns' scale no longer interferes with the line's scale.
• Note that when "Balance on Bar" is selected, the Neutral count is also displayed as a ratio of the balance line. This is the only instance where the Neutral count is displayed in Line mode.
• The "Dual Up/Down Averages" is an exception as it displays two lines: one average for the Up counts and another for the Down counts. This mode will be most useful when Columns are also displayed, as it provides a reference for the top and bottom columns.
3 — Zero Line
The zero line can be colored using two methods, both based on the Combined Balances, i.e., the aggregate of the instant bull/bear bias of the three main bar balances.
• In "Six-state Dual Color Gradient" mode, a dot appears on every bar. Its color reflects the bull/bear state of the Combined Balances, and the dot's brightness reflects the tally of balance biases.
• In "Dual Solid Colors (All Bull/All Bear Only)" a dot only appears when all three balances are either bullish or bearish. The resulting pattern is identical to that of Marker 1.
4 — Divergences
• Divergences are displayed as a small circle at the top of the scale. Four different types of divergence events can be detected. Divergences occur whenever the bull/bear bias of the method used diverges with the bar's price direction.
• An option allows you to include in divergence events instances where the count of neutral intrabars exceeds 50% of the total intrabar count.
• The divergence levels are dynamic levels that automatically build from the line's values on divergence events. On consecutive divergences, the levels will expand, creating a channel. This implementation of the divergence levels corresponds to my view that divergences indicate anomalies, hesitations, points of uncertainty if you will. It excludes any association of a pre-determined bullish/bearish bias to divergences. Accordingly, the levels merely take note of divergence events and mark those points in time with levels. Traders then have a reference point from which they can evaluate further movement. The bull/bear/neutral colors used to plot the levels are also congruent with this view in that they are determined by price's position relative to the levels, which is how I think divergences can be put to the most effective use.
5 — Background
• The background can show a bull/bear gradient on four different calculations. You can adjust its brightness to make its visual importance proportional to how you use it in your analysis.
6 — Chart bars
• Chart bars can be colored using five different methods.
• You have the option of emptying the body of bars where volume does not increase, as does my TLD indicator, the idea behind this being that movement on bars where volume does not increase is less relevant.
7 — Intrabar Resolution
You can choose between three modes. Two of them are automatic and one is manual:
a) Fast, Longer history, Auto-Steps (~12 intrabars) : Optimized for speed and deeper history. Uses an average minimum of 12 intrabars.
b) More Precise, Shorter History Auto-Steps (~24 intrabars) : Uses finer intrabar resolution. It is slower and provides less history. Uses an average minimum of 24 intrabars.
c) Fixed : Uses the fixed resolution of your choice.
Auto-Steps calculations vary for 24/7 and conventional markets in order to achieve the proper target of minimum intrabars.
You can choose to view the intrabar resolution currently used to calculate delta volume. It is the default.
The proper selection of the intrabar resolution is important. It must achieve maximal granularity to produce precise results while not unduly slowing down calculations, or worse, causing runtime errors.
8 — Markers
Six markers are available:
1. Combined Balances Agreement : All three Bar Balances are either bullish or bearish.
2. Up or Down % Agrees With Bar : An up marker will appear when the percentage of up intrabars in an up chart bar is greater than the specified percentage. Conditions mirror to down bars.
3. Divergence confirmations By Price : One of the four types of balance calculations can be used to detect divergences with price. Confirmations occur when the bar following the divergence confirms the balance bias. Note that the divergence events used here do not include neutral intrabar events.
4. Balance Transitions : Bull/bear transitions of the selected balance.
5. Markers Bias Transitions : Bull/bear transitions of the Markers Bias.
6. Divergence Confirmations By Line : Marks points where the line first breaches a divergence level.
Markers appear when the condition is detected, without delay. Since nothing is plotted in realtime, markers do not appear on the realtime bar.
9 — Settings
• Two modes can be selected to dampen the line on the ratio of neutral intrabars.
• A distinct weight can be attributed to the count of the latter half of intrabars, on the assumption that later intrabars may be more important in determining the outcome of chart bars.
• Allows control over the periods of the different moving averages used in calculations.
• The default periods used for the various calculations define the following hierarchy from slow to fast:
Balance Averages: 50,
Balance Momentum: 20,
Dual Up/Down Averages: 20,
Marker Bias: 10.
█ LIMITATIONS
• This script uses a special characteristic of the `security()` function allowing the inspection of intrabars—which is not officially supported by TradingView.
• The method used does not work on the realtime bar—only on historical bars.
• The indicator only works on some chart resolutions: 3, 5, 10, 15 and 30 minutes, 1, 2, 4, 6, and 12 hours, 1 day, 1 week and 1 month. The script’s code can be modified to run on other resolutions, but chart resolutions must be divisible by the lower resolution used for intrabars and the stepping mechanism could require adaptation.
• When using the "Line vs Divergence Levels — Dual Color Gradient" color mode to fill the line, background or chart bars, keep in mind that a line calculation mode must be defined for it to work, as it determines gradients on the movement of the line relative to divergence levels. If the line is hidden, it will not work.
• When the difference between the chart’s resolution and the intrabar resolution is too great, runtime errors will occur. The Auto-Steps selection mechanisms should avoid this.
• Alerts do not work reliably when `security()` is used at intrabar resolutions. Accordingly, no alerts are configured in the indicator.
• The color model used in the indicator provides for fancy visuals that come at a price; when you change values in Inputs , it can take 20 seconds for the changes to materialize. Luckily, once your color setup is complete, the color model does not have a large performance impact, as in normal operation the `security()` calls will become the most important factor in determining response time. Also, once in a while a runtime error will occur when you change inputs. Just making another change will usually bring the indicator back up.
█ RAMBLINGS
Is this thing useful?
I'll let you decide. Bar Balance acts somewhat like an X-Ray on bars. The intrabars it analyzes are no secret; one can simply change the chart's resolution to see the same intrabars the indicator uses. What the indicator brings to traders is the precise count of up/down/neutral intrabars and, more importantly, the calculations it derives from them to present the information in a way that can make it easier to use in trading decisions.
How reliable is Bar Balance information?
By the same token that an up bar does not guarantee that more up bars will follow, future price movements cannot be inferred from the mere count of up/down/neutral intrabars. Price movement during any chart bar for which, let's say, 12 intrabars are analyzed, could be due to only one of those intrabars. One can thus easily see how only relying on bar balance information could be very misleading. The rationale behind Bar Balance is that when the information mined for multiple chart bars is aggregated, it can provide insight into the history behind chart bars, and thus some bias as to the strength of movements. An up chart bar where 11/12 intrabars are also up is assumed to be stronger than the same up bar where only 2/12 intrabars are up. This logic is not bulletproof, and sometimes Bar Balance will stray. Also, keep in mind that balance lines do not represent price momentum as RSI would. Bar Balance calculations have no idea where price is. Their perspective, like that of any historian, is very limited, constrained that it is to the narrow universe of up/down/neutral intrabar counts. You will thus see instances where price is moving up while Balance Momentum, for example, is moving down. When Bar Balance performs as intended, this indicates that the rally is weakening, which does necessarily imply that price will reverse. Occasionally, price will merrily continue to advance on weakening strength.
Divergences
Most of the divergence detection methods used here rely on a difference between the bias of a calculation involving a multi-bar average and a given bar's price direction. When using "Bar Balance on Bar" however, only the bar's balance and price movement are used. This is the default mode.
As usual, divergences are points of interest because they reveal imbalances, which may or may not become turning points. I do not share the overwhelming enthusiasm traders have for the purported ability of bullish/bearish divergences to indicate imminent reversals.
Superfluity
In "The Bed of Procrustes", Nassim Nicholas Taleb writes: To bankrupt a fool, give him information . Bar Balance can display lots of information. While learning to use a new indicator inevitably requires an adaptation period where we put it through its paces and try out all its options, once you have become used to Bar Balance and decide to adopt it, rigorously eliminate the components you don't use and configure the remaining ones so their visual prominence reflects their relative importance in your analysis. I tried to provide flexible options for traders to control this indicator's visuals for that exact reason—not for window dressing.
█ NOTES
For traders
• To avoid misleading traders who don't read script descriptions, the indicator shows nothing in the realtime bar.
• The Data Window shows key values for the indicator.
• All gradients used in this indicator determine their brightness intensities using advances/declines in the signal—not their relative position in a fixed scale.
• Note that because of the way gradients are optimized internally, changing their brightness will sometimes require bringing down the value a few steps before you see an impact.
• Because this indicator does not use volume, it will work on all markets.
For coders
• For those interested in gradients, this script uses an advanced version of the Advance/Decline gradient function from the PineCoders Color Gradient (16 colors) Framework . It allows more precise control over the range, steps and min/max values of the gradients.
• I use the PineCoders Coding Conventions for Pine to write my scripts.
• I used functions modified from the PineCoders MTF Selection Framework for the selection of timeframes.
█ THANKS TO:
— alexgrover who helped me think through the dampening method used to attenuate signal lines on high ratios of neutral intrabars.
— A guy called Kuan who commented on a Backtest Rookies presentation of their Volume Profile indicator . The technique I use to inspect intrabars is derived from Kuan's code.
— theheirophant , my partner in the exploration of the sometimes weird abysses of `security()`’s behavior at intrabar resolutions.
— midtownsk8rguy , my brilliant companion in mining the depths of Pine graphics. He is also the co-author of the PineCoders Color Gradient Frameworks .
[blackcat] L3 Dynamic CrossOVERVIEW
The L3 Dynamic Cross indicator is a powerful tool designed to assist traders in identifying potential buy and sell opportunities through the use of dynamic moving averages. This versatile script offers a wide range of customizable options, allowing users to tailor the moving averages to their specific needs and preferences. By providing clear visual cues and generating precise crossover signals, it helps traders make informed decisions about market trends and potential entry/exit points 📈💹.
FEATURES
Multiple Moving Average Types:
Simple Moving Average (SMA): Provides a straightforward average of prices over a specified period.
Exponential Moving Average (EMA): Gives more weight to recent prices, making it responsive to new information.
Weighted Moving Average (WMA): Assigns weights to all prices within the look-back period, giving more importance to recent prices.
Volume Weighted Moving Average (VWMA): Incorporates volume data to provide a more accurate representation of price movements.
Smoothed Moving Average (SMMA): Averages out fluctuations to create a smoother trend line.
Double Exponential Moving Average (DEMA): Reduces lag by applying two layers of exponential smoothing.
Triple Exponential Moving Average (TEMA): Further reduces lag with three layers of exponential smoothing.
Hull Moving Average (HullMA): Combines weighted moving averages to minimize lag and noise.
Super Smoother Moving Average (SSMA): Uses a sophisticated algorithm to smooth out price data while preserving trend direction.
Zero-Lag Exponential Moving Average (ZEMA): Eliminates lag entirely by adjusting the calculation method.
Triangular Moving Average (TMA): Applies a double smoothing process to reduce volatility and enhance trend identification.
Customizable Parameters:
Length: Adjust the period for both fast and slow moving averages to match your trading style.
Source: Select different price sources such as close, open, high, or low for more nuanced analysis.
Visual Representation:
Fast MA: Displayed as a green line representing shorter-term trends.
Slow MA: Shown as a red line indicating longer-term trends.
Crossover Signals:
Generate buy ('BUY') and sell ('SELL') labels based on crossover events between the fast and slow moving averages 🏷️.
Clear visual cues help traders quickly identify potential entry and exit points.
Alert Functionality:
Receive real-time notifications when crossover conditions are met, ensuring timely action 🔔.
Customizable alert messages for personalized trading strategies.
Advanced Trade Management:
Support for pyramiding levels allows traders to manage multiple positions effectively.
Fine-tune your risk management by setting the number of allowed trades per signal.
HOW TO USE
Adding the Indicator:
Open your TradingView chart and go to the indicators list.
Search for L3 Dynamic Cross and add it to your chart.
Configuring Settings:
Choose your desired Moving Average Type from the dropdown menu.
Adjust the Fast MA Length and Slow MA Length according to your trading timeframe.
Select appropriate Price Sources for both fast and slow moving averages.
Monitoring Signals:
Observe the plotted lines on the chart to track short-term and long-term trends.
Look for buy and sell labels that indicate potential trade opportunities.
Setting Up Alerts:
Enable alerts based on crossover conditions to receive instant notifications.
Customize alert messages to suit your trading plan.
Managing Positions:
Utilize the pyramiding feature to handle multiple entries and exits efficiently.
Keep track of your position sizes relative to the defined pyramiding levels.
Combining with Other Tools:
Integrate this indicator with other technical analysis tools for confirmation.
Use additional filters like volume, RSI, or MACD to enhance decision-making accuracy.
LIMITATIONS
Market Conditions: The effectiveness of the indicator may vary in highly volatile or sideways markets. Be cautious during periods of low liquidity or sudden price spikes 🌪️.
Parameter Sensitivity: Different moving average types and lengths can produce varying results. Experiment with settings to find what works best for your asset class and timeframe.
False Signals: Like any technical indicator, false signals can occur. Always confirm signals with other forms of analysis before executing trades.
NOTES
Historical Data: Ensure you have enough historical data loaded into your chart for accurate moving average calculations.
Backtesting: Thoroughly backtest the indicator on various assets and timeframes using demo accounts before deploying it in live trading environments 🔍.
Customization: Feel free to adjust colors, line widths, and label styles to better fit your chart aesthetics and personal preferences.
EXAMPLE STRATEGIES
Trend Following: Use the indicator to ride trends by entering positions when the fast MA crosses above/below the slow MA and exiting when the opposite occurs.
Mean Reversion: Identify overbought/oversold conditions by combining the indicator with oscillators like RSI or Stochastic. Enter counter-trend positions when the moving averages diverge significantly from the mean.
Scalping: Apply tight moving average settings to capture small, quick profits in intraday trading. Combine with volume indicators to filter out weak signals.
[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.
Universal MA Trend(Republishing in Open source)
Hello traders,
Many existing moving average indicators have not been satisfactory in terms of the number, types, and length adjustments of moving averages.
Feeling the inconvenience, I created a moving average indicator and collected numerous famous moving averages.
Fortunately, there was a PineCoder "andre_007" who had already compiled various Moving Averages,
so I was able to find a new Moving Average and combine it with the indicator. Here is the link below
Among these, for the JMA, which has not been publicly disclosed, I utilized the source code from TradingView Wizard everget:
For VIDYA, I also used everget's source code:
And also MAMA / FAMA Coded from Pinescript Wizard everget :
Ehlers MESA Adaptive Moving Averages (MAMA & FAMA)
For Frama, I used the code from nemozny's source code :
Thanks to all these Pinecoders.
---
By using these excellent moving averages together, I found that the simultaneous Up/Down changes of various moving averages with different characteristics tend to be maintained for quite a long time.
Therefore, this indicator not only collects various moving averages but also displays areas with simultaneous trends as background.
An example can be found here:
Furthermore, to prevent the up/down changes of the moving averages due to factors like whipsaws, a smoothing filter has been introduced.
And Also, Alert is able when trend changes.
---
(오픈소스화 후 재발행)
안녕하세요 트레이더여러분.
기존의 이동평균선 지표들은, 이동평균선의 갯수, 종류, 길이조절 등에서 만족스럽지 못한 점들이 많았습니다.
불편함을 느끼고 직접 이동평균선 지표를 만들면서, 유명한 수 많은 이동평균선들을 모았습니다.
그리고 이미 이러한 수많은 이동평균선을 손수 모아서 정리해주신 고마우신 파인코더(andere_007 님)가 있어서, 그 분의 코드를 많이 이용했습니다. 링크는 아래와 같습니다.
이 중 소스가 공개되지 않은 이동평균선 중 JMA는 트레이딩뷰 위자드이신 everget의 소스코드를 이용했습니다.
VIDYA 역시 everget의 소스코드를 이용했습니다.
MAMA와 FAMA의 코드 역시 everget님의 코드를 가져왔습니다.
Ehlers MESA Adaptive Moving Averages (MAMA & FAMA)
Frama는 nemozny님의 코드를 이용했습니다.
의 코드를 이용했습니다.
이 자리를 빌어 위의 파인코더님들께 감사의 말씀을 전합니다.
---
이러한 좋은 이동평균선을 모아서 사용해보니, 다양한 특성을 갖고 있는 이동평균선의 동시적인 Up/Down 변화는 꽤 오랫동안 유지된다는 점을 발견했습니다.
그래서 이 지표는, 위의 여러가지 이동평균선을 모아놓은 것 뿐만 아니라,
그것에서 동시적인 트랜드가 나오는 곳을 배경화면으로 표시해두었습니다.
예시는 다음과 같습니다.
나아가 휩쏘 등으로 이동평균선의 up/down이 바뀌는 것을 막고자, Smoothing 필터도 도입했습니다.
또한 트랜드가 바뀔 때 얼러트가 울리도록, 얼러트 기능을 설정해놓을 수 있게 해놓았으며, 현재 이동평균선과 상태를 보기 쉽도록 테이블을 만들어놓았습니다.
