RSI DeviationAn oscillator which de-trends the Relative Strength Index. Rather, it takes a moving average of RSI and plots it's standard deviation from the MA, similar to a Bollinger %B oscillator. This seams to highlight short term peaks and troughs, Indicating oversold and overbought conditions respectively. It is intended to be used with a Dollar Cost Averaging strategy, but may also be useful for Swing Trading, or Scalping on lower timeframes.
When the line on the oscillator line crosses back into the channel, it signals a trade opportunity.
~ Crossing into the band from the bottom, indicates the end of an oversold condition, signaling a potential reversal. This would be a BUY signal.
~ Crossing into the band from the top, indicates the end of an overbought condition, signaling a potential reversal. This would be a SELL signal.
For ease of use, I've made the oscillator highlight the main chart when Overbought/Oversold conditions are occurring, and place fractals upon reversion to the Band. These repaint as they are calculated at close. The earliest trade would occur upon open of the following day.
I have set the default St. Deviation to be 2, but in my testing I have found 1.5 to be quite reliable. By decreasing the St. Deviation you will increase trade frequency, to a point, at the expense of efficiency.
Cheers
DJSnoWMan06
센터드 오실레이터
Non-Sinusoidal Multi-Layered Moving Average OscillatorThis indicator utilizes multiple moving averages (MAs) of different lengths their difference and its rate of change to provide a comprehensive view of both short-term and long-term market trends. The output signal is characterized by its non-sinusoidal nature, offering distinct advantages in trend analysis and market forecasting.
Combining the difference between two moving averages with the ROC allows to assess not only the direction and strength of the trend but also the momentum behind it. Transforming these signal in to non-sinusoidal output enhances its utility.
The indicator allows traders to select any one or more of seven moving average options. Larger timeframes (e.g., MA89/MA144) provide a broader identification of the overall trend, helping to understand the general market direction. Smaller timeframes (e.g., MA5/MA8) are more sensitive to price changes and can indicate better entry and exit points, aiding in the identification of retracements and pullbacks. By combining multiple timeframes, traders can get a comprehensive view of the market, enabling more precise and informed trading decisions.
Key Features:
Multiple Moving Averages:
The indicator calculates several exponential moving averages (EMAs) based on different lengths: MA5, MA8, MA13, MA21, MA34, MA55, MA89, and MA144.
These MAs are further smoothed using a secondary exponential moving average, with the smoothing length customizable by the user.
Percentage Differences:
The indicator computes the percentage differences between successive MAs (e.g., (MA5 - MA8) / MA8 * 100). These differences highlight the relative movement of prices over different periods, providing insights into market momentum and trend strength.
Short-term MA differences (e.g., MA5/MA8) are more sensitive to recent price changes, making them useful for detecting quick market movements.
Long-term MA differences (e.g., MA89/MA144) smooth out short-term fluctuations, helping to identify major trends.
Rate of Change (ROC):
The indicator applies the Rate of Change (ROC) to the percentage differences of the MAs. ROC measures the speed at which the percentage differences are changing over time, providing an additional layer of trend analysis.
ROC helps in understanding the acceleration or deceleration of market trends, indicating the strength and potential reversals.
Transformations:
The percentage differences undergo a series of mathematical transformations (either inverse hyperbolic sine transformation or inverse fisher transformation) to refine the signal and enhance its interpretability. These transformations include adjustments to stabilize the values and highlight significant movements.
checkbox allows users to select which mathematical transformations to use.
Non-Sinusoidal Nature:
The output signal of this indicator is non-sinusoidal, characterized by abrupt changes and distinct patterns rather than smooth, wave-like oscillations.
The non-sinusoidal signal provides clearer demarcations of trend changes and is more responsive to sudden market shifts.
This nature reduces the lag typically associated with sinusoidal indicators, allowing for more timely and accurate trading decisions.
Customizable Options:
Users can select which MA pairs to include in the analysis using checkboxes. This flexibility allows the indicator to adapt to different trading strategies, whether focused on short-term movements or long-term trends.
Visual Representation:
The indicator plots the transformed values on a separate panel, making it easy for traders to visualize the trends and potential entry or exit points.
Usage Scenarios:
Short-Term Trading: By focusing on shorter MAs (e.g., MA5/MA8), traders can capture quick market movements and identify short-term trends.
Long-Term Analysis: Utilizing longer MAs (e.g., MA89/MA144) helps in identifying major market trends.
Combination of MAs: The ability to mix different MA lengths provides a balanced view, helping traders make decisions based on both immediate price actions and overall market direction.
Practical Benefits:
Early Signal Detection: The sensitivity of short-term MAs provides early signals for potential trend changes, assisting traders in timely decision-making.
Trend Confirmation: Long-term MAs offer stable trend confirmation, reducing the likelihood of false signals in volatile markets.
Noise Reduction: The mathematical transformations and ROC applied to the percentage differences help in filtering out market noise, focusing on meaningful price movements.
Improved Responsiveness: The non-sinusoidal nature of the signal allows the indicator to react more quickly to market changes, providing more accurate and timely trading signals.
Clearer Trend Demarcations: Non-sinusoidal signals make it easier to identify distinct phases of market trends, aiding in better interpretation and decision-making.
Glitch IndexGlitch Index is an oscillator from an unknown origin that is discovered in 2013 as a lua indicator taken from MetaStock days and we are not really sure how far back the original idea goes.
How it Works?
As I found this indicator and looking at it's code in different platform I can see it comes back from a basic idea of getting a price value, calculating it's smoothed average with a set multiplier and getting the difference then presenting it on a simplified scale. It appears to be another interpretation of figuring out price acceleration and velocity. The main logic is calculated as below:
price = priceSet(priceType)
_ma = getAverageName(price, MaMethod, MaPeriod)
rocma = ((_ma - _ma ) * 0.1) + 1
maMul = _ma * rocma
diff = price - maMul
gli_ind = (diff / price) * -10
How to Use?
Glitch Index can be used based on different implementations and along with your already existing trading system as a confirmation. Yoıu can use it as a Long signal when the histogram crosses inner levels or you can use it as an overbough and oversold signals when the histogram crosses above outter levels and gets back in the range between outter and inner levels.
You can customise the settings and set your prefered inner and outter levels in indicator settings along with gradient or static based coloring and modify the code as you see fit. The coloring code is set below:
gli_col = gli_ind > outterLevel ? color.green : gli_ind < -outterLevel ? color.red : gli_ind > innerLevel ? color.rgb(106, 185, 109, 57) : gli_ind < -innerLevel ? color.rgb(233, 111, 111, 40) : color.new(color.yellow, 60)
gradcol = color.from_gradient(gli_ind, -outterLevel, outterLevel, color.red, color.green)
colorSelect = colorType == "Gradient" ? gradcol : gli_col
KNN OscillatorOverview
The KNN Oscillator is an advanced technical analysis tool designed to help traders identify potential trend reversals and market momentum. Using the K-Nearest Neighbors (KNN) algorithm, this oscillator normalizes KNN values to create a dynamic and responsive indicator. The oscillator line changes color to reflect the market sentiment, providing clear visual cues for trading decisions.
Key Features
Dynamic Color Oscillator: The line changes color based on the oscillator value – green for positive, red for negative, and grey for neutral.
Advanced KNN Algorithm: Utilizes the K-Nearest Neighbors algorithm for precise trend detection.
Normalized Values: Ensures the oscillator values are normalized to align with the stock price range, making it applicable to various assets.
Easy Integration: Can be easily added to any TradingView chart for enhanced analysis.
How It Works
The KNN Oscillator leverages the K-Nearest Neighbors algorithm to calculate the average distance of the nearest neighbors over a specified period. These values are then normalized to match the stock price range, ensuring they are comparable across different assets. The oscillator value is derived by taking the difference between the normalized KNN values and the source price. The line's color changes dynamically to provide an immediate visual indication of the market's state:
Green: Positive values indicate upward momentum.
Red: Negative values indicate downward momentum.
Grey: Neutral values indicate a stable or consolidating market.
Usage Instructions
Trend Reversal Detection: Use the color changes to identify potential trend reversals. A shift from red to green suggests a bullish reversal, while a shift from green to red indicates a bearish reversal.
Momentum Analysis: The oscillator's value and color help gauge market momentum. Strong positive values (green) indicate strong upward momentum, while strong negative values (red) indicate strong downward momentum.
Market Sentiment: The dynamic color changes provide an easy-to-understand visual representation of market sentiment, helping traders make informed decisions quickly.
Confirmation Tool: Use the KNN Oscillator in conjunction with other technical indicators to confirm signals and improve the accuracy of your trades.
Scalability: Applicable to various timeframes and asset classes, making it a versatile tool for all types of traders.
MACD Highlight Zones for PrimetimeUse the MACD Highlight Zones to easily spot changes in market momentum and make more informed trading decisions.
The MACD Highlight Zones script visually enhances your chart by highlighting different zones based on the MACD's relationship to the zero line and its signal line. This script helps traders quickly identify the market's momentum and potential reversal points.
Features:
🟢 Green Background: Indicates the MACD line is above 0, signaling bullish momentum.
🟡 Yellow Background: Indicates the MACD line crosses the signal line, suggesting a potential momentum shift.
🔴 Red Background: Indicates the MACD line is below 0, signaling bearish momentum.
MACD BB v2.00 Indicator CryptoPotato748The MACD BB v2.00 CryptoPotato748 is a custom technical analysis indicator for TradingView that combines the Moving Average Convergence Divergence (MACD) with Bollinger Bands to provide a powerful tool for identifying trend strength and potential trading signals. This indicator is designed to automatically adapt its parameters based on the selected time frame, making it versatile and suitable for various trading strategies and time horizons.
Features
MACD Calculation:
The MACD line is calculated using the difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
The Signal line is the 9-period EMA of the MACD line.
These parameters automatically adjust based on the selected time frame to optimize performance.
Bollinger Bands:
Bollinger Bands are calculated based on the MACD line to identify overbought and oversold conditions.
The bands consist of a 20-period Simple Moving Average (SMA) of the MACD line, with upper and lower bands set 2 standard deviations away.
These parameters also adjust based on the selected time frame for better alignment with market conditions.
Adaptive Time Frames:
The indicator automatically adjusts its MACD and Bollinger Bands parameters based on the selected chart time frame, including 1 minute, 3 minutes, 5 minutes, 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 12 hours, 1 day, 3 days, 1 week, and 1 month.
This ensures the indicator remains effective across various time frames without manual reconfiguration.
Visual Elements:
The upper and lower Bollinger Bands are plotted in gray, with a blue fill between them for easy visualization.
The MACD line is plotted with circle markers, colored lime when above the upper band and red when below the lower band.
A zero line is plotted in orange for reference.
Bar colors change to yellow when the MACD line is above the upper band (indicating a potential buy signal) and aqua when below the lower band (indicating a potential sell signal).
How to Use
Adding to Chart:
Copy and paste the script into the Pine Editor on TradingView.
Click "Add to Chart" to see the indicator in action.
Interpreting Signals:
MACD Above Upper Band (Lime): Indicates strong bullish momentum, potential buy signal.
MACD Below Lower Band (Red): Indicates strong bearish momentum, potential sell signal.
Yellow Bars: Suggest a potential buy condition.
Aqua Bars: Suggest a potential sell condition.
Adaptive Parameters:
The indicator automatically adjusts its parameters based on the selected time frame, ensuring optimal performance across different trading environments.
LBR-S310ROC @shrilssOriginally made by Linda Raschke, The S310ROC Indicator combines the Rate of Change (ROC) indicator with the 3-10 Oscillator (Modified MACD) and plots to capture rapid price movements and gauge market momentum.
- Rate of Change (ROC): This component of the indicator measures the percentage change in price over a specified short interval, which can be set by the user (default is 2 days). It is calculated by subtracting the closing price from 'X' days ago from the current close.
- 3-10 Oscillator (MACD; 3,10,16): This is a specialized version of the Moving Average Convergence Divergence (MACD) but uses simple moving averages instead of exponential. Using a fast moving average of 3 days and a slow moving average of 10 days with a smoothing period of 16.
- ROC Dots: A great feature based on the oscillator's readings. Dots are displayed directly on the oscillator or the price chart to provide visual momentum cues:
- Aqua Dots: Appear when all lines (ROC, MACD, Slowline) are sloping downwards, indicating bearish momentum and potentially signaling a sell opportunity.
- White Dots: Appear when all lines are sloping upwards, suggesting bullish momentum and possibly a buy signal.
Linear Regression Oscillator [ChartPrime]Linear Regression Oscillator Indicator
Overview:
The Linear Regression Oscillator is a custom TradingView indicator designed to provide insights into potential mean reversion and trend conditions. By calculating a linear regression on the closing prices over a user-defined period, this oscillator helps identify overbought and oversold levels and highlights trend changes. The indicator also offers visual cues and color-coded price bars to aid in quick decision-making.
Key Features:
◆ Customizable Look-Back Period:
Input: Length
Default: 20
Description: Determines the period over which the linear regression is calculated. A longer period smooths the oscillator but may lag, while a shorter period is more responsive but may be noisier.
◆ Overbought and Oversold Thresholds:
Inputs: Upper Threshold and Lower Threshold
Default: 1.5 and -1.5 respectively
Description: Define the upper and lower bounds for identifying overbought and oversold conditions. Values outside these thresholds suggest potential reversals.
◆ Candlestick Color Plotting:
Input: Plot Bar Color
Default: false
Description: Option to color the price bars based on the oscillator's value, providing a visual representation of market conditions. Bars turn cyan for positive oscillator values and blue for negative.
◆ Mean Reversion and Trend Signals:
Visual markers and labels indicate when the oscillator suggests mean reversion or trend changes, aiding in identifying key market turning points.
◆ Invalidation Levels:
Tracks the highest and lowest prices over a recent period to set levels where the current trend signal would be considered invalidated.
◆ Gradient Color Coding:
Utilizes gradient color coding to enhance the visualization of oscillator values, making it easier to interpret overbought and oversold conditions.
◆ Usage Notes:
Setting the Look-Back Period:
Adjust the "Length" input based on the timeframe and the type of trading you are conducting. Shorter periods are more suited for intraday trading, while longer periods can be used for swing trading.
Interpreting Thresholds:
Use the upper and lower threshold inputs to fine-tune the sensitivity of the overbought and oversold signals. Higher absolute values reduce the number of signals but increase their reliability.
Candlestick Coloring:
Enabling the "Plot Bar Color" option can help quickly identify the current state of the oscillator in relation to the zero line. This visual aid can be particularly useful in fast-moving markets.
Mean Reversion and Trend Signals:
Pay attention to the symbols and labels on the chart indicating mean reversion and trend changes. These signals are designed to highlight potential entry and exit points.
Invalidation Levels:
Use the plotted invalidation levels as stop-loss or signal invalidation points. If the price moves beyond these levels, the current trend signal is likely invalid.
This indicator helps traders identify overbought and oversold conditions, potential mean reversions, and trend changes based on the linear regression of the closing prices over a specified look-back period.
Price Reversal Probability + Price Forecast [TradeDots]The TradeDots Price Reversal Probability + Price Forecast Indicator helps traders discern market direction and identify potential trading opportunities.
📝 HOW IT WORKS
The indicator provides two types of reversal signals:
Bullish Reversal: Marked with a green label, indicating an expected upward market reversal.
Bearish Reversal: Marked with a red label, indicating an expected downward market reversal.
⭐️ Computation
This tool identifies significant reversal patterns using a mathematical model on a designated window of candlesticks to calculate price action changes. It incorporates candlestick data and price indicators, such as the Open, Close, High, Low of candlesticks and Average True Range (ATR), to detect similar occurrences in real-time.
Potential market turning points are marked with reversal labels and percentage changes , calculated using pivot high or low price data from the last reversal patterns of the opposite side.
For example, a green label on the chart indicates a bullish reversal pattern, showing the market is expected to reverse upward. However, signals are based on historical price actions and are not 100% accurate. If the price breaks down from the bullish reversal pivot low, the original signal will turn half transparent until the next reversal pattern is detected.
The algorithm groups consecutive bullish reversal patterns until a bearish reversal pattern appears. The last bullish label occurrence indicates the maximum number of bullish patterns required to confirm a reversal in the group. This information is stored to apply Bayesian statistical models and probability models to generate market insights.
⭐️ Statistical Analysis
Reversal signals are categorized into bullish and bearish groups, with each group storing consecutive reversal signals.
In the indicator table, each new reversal is labeled sequentially (e.g., "🟢 #1" for the first bullish reversal after a bearish signal). The number increases for each new signal on the same side and resets when a reversal signal on the opposite side appears.
The indicator provides two forecasts: the probability of reversal and the expected price change if the pattern is successful or unsuccessful.
⭐️ Probability of Reversal
By counting the number of consecutive reversal patterns on one side before a reversal pattern on the opposite side appears, we can calculate the probability of reversal of each signal throughout the entire price action history.
Using Bayes’ Theorem, the probability increases with each consecutive pattern. The values are displayed in the first two columns of the indicator table, with the current condition highlighted in orange.
⭐️ Price Forecast
The price forecast uses the pivot point of the last reversal pattern of the opposite side as a reference for calculating the percentage change.
For example, for a group of bullish patterns, the pivot high of the most recent bearish pattern is taken. A percentage is calculated with the pivot low of all bullish patterns in the same group. Repeating this model throughout the entire historical price action patterns gives the average price percentage difference between all bearish and bullish patterns.
Whenever a new reversal pattern is detected, a price can be forecasted using the percentage difference from the statistical model. The target price is calculated and displayed in the third and fourth columns of the indicator table.
Assisting Traders To Make Data-Informed Trading Decisions
All included features in this indicator:
Labeling of bullish and bearish reversal patterns
Success probability of each reversal pattern
Price targets of each reversal pattern
Visual aid for pattern confirmation
More (check the changelog below for current features)
🛠️ HOW TO USE
⭐️ Reversal Signals
There are two types of reversal signals identified by the algorithm that detects reversal patterns using price action analysis with candlestick data and price indicators. When the price breaks out from the labeled pivot, the label will turn half transparent.
Bullish reversal signals: Labeled in green. The number represents the price of the candlestick "low," and the percentage value indicates the price difference from the previous bearish reversal pattern's candlestick "high."
Bearish reversal signals: Labeled in red. The number represents the price of the candlestick "high," and the percentage value indicates the price difference from the previous bullish reversal pattern's candlestick "low."
⭐️ Probability Table
The probability table shows the likelihood of reversal for each number of occurrences of bullish and bearish reversal signals, displayed in the first two columns.
It also shows the target prices for both bullish and bearish conditions for each number of reversal patterns.
⭐️ Price Targets
By combining the probability of reversal and the price forecast, price targets for new reversal patterns are calculated. These insights help traders align their strategies with price action analysis and statistics by simply observing the candlestick chart in real-time.
Bullish Price Target: The average percentage price and probability that the next bearish reversal signal might hit.
Bearish Price Target: The average percentage price and probability that the next bullish reversal signal might hit.
⭐️ Market Trend Panel
The market trend panel is a small table that indicates the market trend using a 200 Exponential Moving Average (EMA) alongside reversal signals. A bullish reversal pattern above the moving average indicates a "bullish" market, while a bearish reversal pattern below it indicates a "bearish" market. If the price fluctuates around the moving average, it is identified as "choppy."
The panel also shows the risk and reward for each trade by taking the closing bullish and bearish targets from the most recent reversal pattern's price reference. Lastly, it displays the probability of reversal, consistent with the number highlighted in the probability table.
⭐️ Other Visual Aid
Other visual aids visualize the market trend and potential direction for users on the candlestick chart.
Background colors reflect the current market trend (green = bullish, red = bearish, blue = choppy).
A white plotted line represents the moving average for categorizing market trends.
❗️LIMITATIONS
Price targets represent only the mean of percentage differences. Therefore, the price could reverse before hitting either side of the price target.
When the market is in extreme price action or a new market pattern, the price targets may not be forecasted accurately and might move out of the model's range.
This model works best for assets with less price variation and a near-Gaussian distribution in returns. It may be less accurate for assets with random price movements.
CONCLUSION
This indicator uses fundamental statistics and mathematical models to generate reversal probabilities and price forecasts. It does not have the ability to predict the future with certainty. Traders should combine this indicator with other confirmation strategies to make informed investment decisions.
See Author's instructions below to get instant access to this indicator.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
NOTES*
Calculations are based on historical data and do not guarantee future results.
Reversals exceeding ten consecutive occurrences are rare (likely <1% of total occurrences).
Users SHOULD NOT blindly follow the price targets as their trading strategy.
If you encounter a timeout with this indicator, reapply it to your chart.
Multi Timeframe Moving Average Convergence Divergence {DCAquant}Overview
The MTF MACD indicator provides a unique view of MACD (Moving Average Convergence Divergence) and Signal Line dynamics across various timeframes. It calculates the MACD and Signal Line for each selected timeframe and aggregates them for analysis.
Key Features
MACD Calculation
Utilizes standard MACD calculations based on user-defined parameters like fast length, slow length, and signal smoothing.
Determines the difference between the MACD and Signal Line to identify convergence or divergence.
Multiple Timeframe Analysis
Allows users to select up to six different timeframes for analysis, ranging from minutes to days, providing a holistic view of market trends.
Calculates MACD and Signal Line for each timeframe independently.
Aggregated Analysis
Combines MACD and Signal Line values from multiple timeframes to derive a consolidated view.
Optionally applies moving average smoothing to aggregated MACD and Signal Line values for better clarity.
Position Identification
Determines the trading position (Long, Short, or Neutral) based on the relationship between MACD and Signal Line.
Considers the proximity of MACD and Signal Line to identify potential trading opportunities.
Visual Representation
Plots MACD and Signal Line on the price chart for visual analysis.
Utilizes color-coded backgrounds to indicate trading conditions (Long, Short, or Neutral) for quick interpretation.
Dynamic Table Display
Displays trading position alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table.
Offers flexibility in table placement and size for user preference.
How to Use
Parameter Configuration
Adjust parameters like fast length, slow length, and signal smoothing to fine-tune MACD calculations.
Select desired timeframes for analysis based on trading preferences and market conditions.
Interpretation
Monitor the relationship between MACD and Signal Line on the price chart.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable insights.
Decision Making
Consider entering Long positions when MACD is above the Signal Line and vice versa for Short positions.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management
Combine MTF MACD analysis with risk management strategies to optimize trade entries and exits.
Set stop-loss and take-profit levels based on individual risk tolerance and market conditions.
Conclusion
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator offers a robust framework for traders to analyze market trends across multiple timeframes efficiently. By combining MACD insights from various time horizons and presenting them in a clear and actionable format, it empowers traders to make informed decisions and enhance their trading strategies.
Disclaimer
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator provided here is intended for educational and informational purposes only. Trading in financial markets involves risk, and past performance is not indicative of future results. The use of this indicator does not guarantee profits or prevent losses.
Please be aware that trading decisions should be made based on your own analysis, risk tolerance, and financial situation. It is essential to conduct thorough research and seek advice from qualified financial professionals before engaging in any trading activity.
The MTF MACD indicator is a tool designed to assist traders in analyzing market trends and identifying potential trading opportunities. However, it is not a substitute for sound judgment and prudent risk management.
By using this indicator, you acknowledge that you are solely responsible for your trading decisions, and you agree to indemnify and hold harmless the developer and distributor of this indicator from any losses, damages, or liabilities arising from its use.
Trading in financial markets carries inherent risks, and you should only trade with capital that you can afford to lose. Exercise caution and discretion when implementing trading strategies, and consider seeking independent financial advice if necessary.
Median Momentum with Buy/Sell Signals and Bar ColorMomentum Calculation:
Momentum is calculated as the difference between the current close price and the close price momentum_length periods ago: momentum = close - close .
Highest and Lowest Momentum:
The highest and lowest momentum values over the specified length are calculated.
Median Momentum:
The median momentum is calculated as the average of the highest and lowest momentum values.
Color Setting:
medianColor is set based on whether the momentum is above, below, or equal to the median momentum.
barColor is set similarly for bar coloring.
Plotting:
The script plots the median momentum and the actual momentum values.
Buy and sell signals are generated when momentum crosses over or under the median momentum.
The script also plots the buy and sell signals with arrows on the chart.
Velocity And Acceleration with Strategy: Traders Magazine◙ OVERVIEW
Hi, Ivestors and Traders... This Indicator, the focus is Scott Cong's article in the Stocks & Commodities September issue, “VAcc: A Momentum Indicator Based On Velocity And Acceleration”. I have also added a trading strategy for you to benefit from this indicator. First of all, let's look at what the indicator offers us and what its logic is. First, let's focus on the logic of the strategy.
◙ CONCEPTS
Here is a new indicator based on some simple physics concepts that is easy to use, responsive and precise. Learn how to calculate and use it.
The field of physics gives us some important principles that are highly applicable to analyzing the markets. In this indicator, I will present a momentum indicator. Scott Cong developed based on the concepts of velocity and acceleration this indicator. Of the many characteristics of price that traders and analysts often study, rate and rate of change are useful ones. In other words, it’s helpful to know: How fast is price moving, and is it speeding up or slowing down? How is price changing from one period to the next? The indicator I’m introducing here is calculated using the current bar (C) and every bar of a lookback period from the current bar. He named the indicator the VAcc since it’s based on the average of velocity line (av) and acceleration line (Acc) over the lookback period. For longer periods, the VAcc behaves the same way as the MACD, only it’s simpler, more responsive, and more precise. Interestingly, for shorter periods, VAcc exhibits characteristics of an oscillator, such as the stochastics oscillator.
◙ CALCULATION
The calculation of VAcc involves the following steps:
1. Relatively weighted average where the nearer price has the largest influence.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. The Velocity Average is smoothed with an exponential moving average. Now it get:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Similarly, accelerations for each bar within the lookback period and scale factor are calculated as:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEGY
In fact, Scott probably preferred to use it in periods 9 and 26 because it was similar to Macd and used the ratio of 0.5. However, I preferred to use the 8 and 21 periods to provide signals closer to the stochastic oscillator in the short term and used the 0.382 ratio. The logic of the strategy is this
Long Strategy → acc(Acceleration Line) > 0.1 and av(Velocity Average Line) > 0.1(Long Factor)
Short strategy → acc(Acceleration Line) < -0.1 and av(Velocity Average Line) < -0.1(Long Factor)
Here, you can change the Short Factor and Long Factor as you wish and produce more meaningful results that are closer to your own strategy.
I hope you benefits...
◙ GENEL BAKIŞ
Merhaba Yatırımcılar ve Yatırımcılar... Bu Gösterge, Scott Cong'un Stocks & Emtia Eylül sayısındaki “VAcc: Hız ve İvmeye Dayalı Bir Momentum Göstergesi” başlıklı makalesine odaklanmaktadır. Bu göstergeden faydalanabilmeniz için bir ticaret stratejisi de ekledim. Öncelikle göstergenin bize neler sunduğuna ve mantığının ne olduğuna bakalım. Öncelikle stratejinin mantığına odaklanalım.
◙ KAVRAMLAR
İşte kullanımı kolay, duyarlı ve kesin bazı basit fizik kavramlarına dayanan yeni bir gösterge. Nasıl hesaplanacağını ve kullanılacağını öğrenin.
Fizik alanı bize piyasaları analiz etmede son derece uygulanabilir bazı önemli ilkeler verir. Bu göstergede bir momentum göstergesi sunacağım. Scott Cong bu göstergeyi hız ve ivme kavramlarına dayanarak geliştirdi. Yatırımcıların ve analistlerin sıklıkla incelediği fiyatın pek çok özelliği arasında değişim oranı ve oranı yararlı olanlardır. Başka bir deyişle şunu bilmek faydalı olacaktır: Fiyat ne kadar hızlı hareket ediyor ve hızlanıyor mu, yavaşlıyor mu? Fiyatlar bir dönemden diğerine nasıl değişiyor? Burada tanıtacağım gösterge, mevcut çubuk (C) ve mevcut çubuktan bir yeniden inceleme döneminin her çubuğu kullanılarak hesaplanır. Göstergeye, yeniden inceleme dönemi boyunca hız çizgisinin (av) ve ivme çizgisinin (Acc) ortalamasına dayandığı için VAcc adını verdi. Daha uzun süreler boyunca VACc, MACD ile aynı şekilde davranır, yalnızca daha basit, daha duyarlı ve daha hassastır. İlginç bir şekilde, daha kısa süreler için VAcc, stokastik osilatör gibi bir osilatörün özelliklerini sergiliyor.
◙ HESAPLAMA
VAcc'nin hesaplanması aşağıdaki adımları içerir:
1. Yakın zamandaki fiyatın en büyük etkiye sahip olduğu göreceli ağırlıklı ortalamayı hesaplatıyoruz.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. Hız Ortalamasına üstel hareketli ortalamayla düzleştirme uygulanır. Şimdi bu şekilde aşağıdaki kod ile bunu şöyle elde ediyoruz:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Benzer şekilde, yeniden inceleme süresi ve ölçek faktörü içindeki her bir çubuk için fiyattaki ivmelenler yada momentum şu şekilde hesaplanır:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEJİ
Aslında Scott muhtemelen Macd'e benzediği ve 0,5 oranını kullandığı için 9. ve 26. periyotlarda kullanmayı tercih etmişti. Ancak kısa vadede stokastik osilatöre daha yakın sinyaller sağlamak için 8 ve 21 periyotlarını kullanmayı tercih ettim ve 0,382 oranını kullandım. Stratejinin mantığı şu
Uzun Strateji → acc(İvme Çizgisi) > 0,1 ve av(Hız Ortalama Çizgisi) > 0,1(Uzun Faktör)
Kısa strateji → acc(İvme Çizgisi) < -0,1 ve av(Hız Ortalama Çizgisi) < -0,1(Uzun Faktör)
Burada Kısa Faktör ve Uzun Faktör' ü dilediğiniz gibi değiştirip, kendi stratejinize daha yakın, daha anlamlı sonuçlar üretebilirsiniz.
umarım faydasını görürsün...
ADX-DI - Made EasyThis indicator is a visually improved version of ADX. It makes it much easier to see what's happening by simplifying those confusing, intersecting lines. With this, you can detect the ADX direction more clearly. All the features are also explained in the tooltips of the input fields. Some extra features are included, such as average top and bottom calculation and divergences.
Please note that the divergences on ADX are just experimental and are based on calculations, so there is no guarantee the direction will change.
MMI (Multi.Index.Indicator)Multi-Index Momentum Indicator (MMI)
The Multi-Index Momentum Indicator (MMI) is a custom TradingView Pine Script indicator designed to calculate and display the momentum difference between the base and quote indexes of various currency pairs. This indicator helps traders identify the relative strength or weakness of a currency pair by comparing the momentum of its base and quote indexes.
Features:
Currency Pair Detection: The indicator automatically detects the currency pair of the current chart and selects the appropriate base and quote indexes for that pair.
Index Data Retrieval: It fetches the closing prices of the base and quote indexes for the specified timeframe.
Momentum Calculation:
The indicator calculates the 14-period momentum for both the base and quote indexes and then computes the momentum difference.
Visual Representation: The momentum difference is plotted on the chart as a colored line. If the momentum difference is positive, the line is green; if negative, the line is red.
Data Availability Check:
The script checks if the index data is available. If any index data is missing, the script displays a red label on the chart indicating which index data is missing.
Zero Line: A horizontal line at the zero level is plotted for reference.
Supported Currency Pairs and Their Indexes:
USDJPY: Base Index - DXY, Quote Index - JPYX
EURUSD: Base Index - EXY, Quote Index - DXY
GBPUSD: Base Index - BXY, Quote Index - DXY
AUDUSD: Base Index - AXY, Quote Index - DXY
USDCHF: Base Index - DXY, Quote Index - SXY
USDCAD: Base Index - DXY, Quote Index - CXY
GBPJPY: Base Index - BXY, Quote Index - JPYX
CME Gap Oscillator [CryptoSea]Introducing the CME Gap Oscillator , a pioneering tool designed to illuminate the significance of market gaps through the lens of the Chicago Mercantile Exchange (CME). By leveraging gap sizes in relation to the Average True Range (ATR), this indicator offers a unique perspective on market dynamics, particularly around the critical weekly close periods.
Key Features
Gap Measurement : At its core, the CME Oscillator quantifies the size of weekend gaps in the context of the market's volatility, using the ATR to standardize this measurement.
Dynamic Levels : Incorporating a dynamic extreme level calculation, the tool adapts to current market conditions, providing real-time insights into significant gap sizes and their implications.
Band Analysis : Through the introduction of upper and lower bands, based on standard deviations, traders can visually assess the oscillator's position relative to typical market ranges.
Enhanced Insights : A built-in table tracks the frequency of the oscillator's breaches beyond these bands within the latest CME week, offering a snapshot of recent market extremities.
Settings & Customisation
ATR-Based Measurement : Choose to measure gap sizes directly or in terms of ATR for a volatility-adjusted view.
Band Period Adjustability : Tailor the oscillator's sensitivity by modifying the band calculation period.
Dynamic Level Multipliers : Adjust the multiplier for dynamic levels to suit your analysis needs.
Visual Preferences : Customise the oscillator, bands, and table visuals, including color schemes and line styles.
In the example below, it demonstrates that the CME will want to return to the 0 value, this would be considered a reset or gap fill.
Application & Strategy
Deploy the CME Oscillator to enhance your market analysis
Market Sentiment : Gauge weekend market sentiment shifts through gap analysis, refining your strategy for the week ahead.
Volatility Insights : Use the oscillator's ATR-based measurements to understand the volatility context of gaps, aiding in risk management.
Trend Identification : Identify potential trend continuations or reversals based on the frequency and magnitude of gaps exceeding dynamic levels.
The CME Oscillator stands out as a strategic tool for traders focusing on gap analysis and volatility assessment. By offering a detailed breakdown of market gaps in relation to volatility, it empowers users with actionable insights, enabling more informed trading decisions across a range of markets and timeframes.
Price Ratio Indicator [ChartPrime]The Price Ratio Indicator is a versatile tool designed to analyze the relationship between the price of an asset and its moving average. It helps traders identify overbought and oversold conditions in the market, as well as potential trend reversals.
◈ User Inputs:
MA Length: Specifies the length of the moving average used in the calculation.
MA Type Fast: Allows users to choose from various types of moving averages such as Exponential Moving Average (EMA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Relative Moving Average (RMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Zero-Lag Exponential Moving Average (ZLEMA), and Hull Moving Average (HMA).
Upper Level and Lower Level: Define the threshold levels for identifying overbought and oversold conditions.
Signal Line Length: Determines the length of the signal line used for smoothing the indicator's values.
◈ Indicator Calculation:
The indicator calculates the ratio between the price of the asset and the selected moving average, subtracts 1 from the ratio, and then smooths the result using the chosen signal line length.
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
//@ Moving Average's Function
ma(src, ma_period, ma_type) =>
ma =
ma_type == 'EMA' ? ta.ema(src, ma_period) :
ma_type == 'SMA' ? ta.sma(src, ma_period) :
ma_type == 'WMA' ? ta.wma(src, ma_period) :
ma_type == 'VWMA' ? ta.vwma(src, ma_period) :
ma_type == 'RMA' ? ta.rma(src, ma_period) :
ma_type == 'DEMA' ? ta.ema(ta.ema(src, ma_period), ma_period) :
ma_type == 'TEMA' ? ta.ema(ta.ema(ta.ema(src, ma_period), ma_period), ma_period) :
ma_type == 'ZLEMA' ? ta.ema(src + src - src , ma_period) :
ma_type == 'HMA' ? ta.hma(src, ma_period)
: na
ma
//@ Smooth of Source
src = math.sum(source, 5)/5
//@ Ratio Price / MA's
p_ratio = src / ma(src, ma_period, ma_type) - 1
◈ Visualization:
The main plot displays the price ratio, with color gradients indicating the strength and direction of the ratio.
The bar color changes dynamically based on the ratio, providing a visual representation of market conditions.
Invisible Horizontal lines indicate the upper and lower threshold levels for overbought and oversold conditions.
A signal line, smoothed using the specified length, helps identify trends and potential reversal points.
High and low value regions are filled with color gradients, enhancing visualization of extreme price movements.
MA type HMA gives faster changes of the indicator (Each MA has its own specifics):
MA type TEMA:
◈ Additional Features:
A symbol displayed at the bottom right corner of the chart provides a quick visual reference to the current state of the indicator, with color intensity indicating the strength of the ratio.
Overall, the Price Ratio Indicator offers traders valuable insights into price dynamics and helps them make informed trading decisions based on the relationship between price and moving averages. Adjusting the input parameters allows for customization according to individual trading preferences and market conditions.
WaveTrend Oscillator PlusThe WaveTrend based on “Enhanced WaveTrend” of EliCobra. The WaveTrend Oscillator is a popular technical analysis tool used to identify overbought and oversold conditions in the market and generate trading signals. This indicator introduces additional features for improved analysis and comparison across assets.
WaveTrend:
The original WaveTrend indicator calculates two lines based on exponential moving averages and their relationship to the asset's price. The first line measures the distance between the asset's price and its EMA, while the second line smooths the first line over a specific period. The result is divided by 0.015 multiplied by the smoothed difference ('d' for reference). The indicator aims to identify overbought and oversold conditions by analyzing the relationship between the two lines.
In the original formula, the rudimentary estimation factor 0.015 times 'd' fails to accomodate for approximately a quarter of the data, preventing the indicator from reaching the traditional stationary levels of +-100. This limitation renders the indicator quantitatively biased, as it relies on the user's subjective adjustment of the levels. The enhanced version replaces this factor with the standard deviation of the asset's price, resulting in improved estimation accuracy and provides a more dynamic and robust outcome, we thereafter multiply the result by 100 to achieve a more traditional oscillation.
Enhancements and Features:
Dynamic Estimation: The original indicator uses an arbitrary estimation factor, while the enhanced version replaces it with the standard deviation of the asset's price. This modification provides a more dynamic and accurate estimation, adapting to the specific price characteristics of each asset.
Stationary Support and Resistance Levels: The enhanced version provides stationary key support and resistance levels that range from -150 to 150. These levels are determined based on the analysis of the indicator's data and encompass more than 95% of the indicator's values. These levels offer important reference points for traders to identify potential price reversals or significant price movements.
Comparison Across Assets: The enhanced version allows for better comparison and analysis across different assets. By incorporating the standard deviation of the asset's price, the indicator provides a more consistent and comparable interpretation of the market conditions across multiple assets.
Z-Score Analysis:
The Z-Score is a statistical measurement that quantifies how far a particular data point deviates from the mean in terms of standard deviations. In the enhanced version, the calculation involves determining the basis (mean) and deviation (standard deviation) of the asset's price to calculate its Z-Score, thereafter applying a smoothing technique to generate the final WaveTrend value.
Utility:
The offers traders and investors valuable insights into overbought and oversold conditions in the market. By analyzing the indicator's values and referencing the stationary support and resistance levels, traders can identify potential trend reversals, evaluate market strength, and make better informed analysis.
The following indicators were added:
⎆⎆ Squeeze Momentum Indicator
⎆⎆ Elliott Wave Oscillator
⎆⎆ Expert Trend Locator
Multiple Non-Linear Regression [ChartPrime]This Pine Script indicator is designed to perform multiple non-linear regression analysis using four independent variables: close, open, high, and low prices. Here's a breakdown of its components and functionalities:
Inputs:
Users can adjust several parameters:
Normalization Data Length: Length of data used for normalization.
Learning Rate: Rate at which the algorithm learns from errors.
Smooth?: Option to smooth the output.
Smooth Length: Length of smoothing if enabled.
Define start coefficients: Initial coefficients for the regression equation.
Data Normalization:
The script normalizes input data to a range between 0 and 1 using the highest and lowest values within a specified length.
Non-linear Regression:
It calculates the regression equation using the input coefficients and normalized data. The equation used is a weighted sum of the independent variables, with coefficients adjusted iteratively using gradient descent to minimize errors.
Error Calculation:
The script computes the error between the actual and predicted values.
Gradient Descent: The coefficients are updated iteratively using gradient descent to minimize the error.
// Compute the predicted values using the non-linear regression function
predictedValues = nonLinearRegression(x_1, x_2, x_3, x_4, b1, b2, b3, b4)
// Compute the error
error = errorModule(initial_val, predictedValues)
// Update the coefficients using gradient descent
b1 := b1 - (learningRate * (error * x_1))
b2 := b2 - (learningRate * (error * x_2))
b3 := b3 - (learningRate * (error * x_3))
b4 := b4 - (learningRate * (error * x_4))
Visualization:
Plotting of normalized input data (close, open, high, low).
The indicator provides visualization of normalized data values (close, open, high, low) in the form of circular markers on the chart, allowing users to easily observe the relative positions of these values in relation to each other and the regression line.
Plotting of the regression line.
Color gradient on the regression line based on its value and bar colors.
Display of normalized input data and predicted value in a table.
Signals for crossovers with a midline (0.5).
Interpretation:
Users can interpret the regression line and its crossovers with the midline (0.5) as signals for potential buy or sell opportunities.
This indicator helps users analyze the relationship between multiple variables and make trading decisions based on the regression analysis. Adjusting the coefficients and parameters can fine-tune the model's performance according to specific market conditions.
Multiple Indicators Screener v2After taking the approval of Mr. QuantNomad
Multiple Indicators Screener by QuantNomad
New lists have been modified and added
Built-in indicators:
RSI (Relative Strength Index): Provides trading opportunities based on overbought or oversold market conditions.
MFI (Cash Flow Index): Measures the flow of cash into or from assets, which helps in identifying buying and selling areas.
Williams Percent Range (WPR): Measures how high or low the price has been in the last time period, giving signals of periods of saturation.
Supertrend: Used to determine market direction and potential entry and exit locations.
Volume Change Percentage: Provides an analysis of the volume change percentage, which helps in identifying demand and supply changes for assets.
How to use:
Users can choose which symbols they want to monitor and analyze using a variety of built-in indicators.
The indicator provides visual signals that help traders identify potential trading opportunities based on the selected settings.
RSI in purple = buy weak liquidity (safe entry).
MFI in yellow = Liquidity
WPR in blue = RSI, MFI and WPR in oversold areas for all.
Allows users to customize the display locations and appearance of the cursor to their personal preferences.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
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فاحص لمؤشرات متعددة مع مخرجات جدول شاملة لتسهيل مراقبة الكثير من العملات تصل الى 99 في وقت واحد
بختصر الشرح
ظهور اللون البنفسجي يعني كمية الشراء ضعف السيولة .
ظهور اللون الازرق جميع المؤشرات وصلة الى مرحلة التشبع البيعي ( دخول آمن )
ظهور اللون الاصفر يعني السيولة ضعفين الشراء ( عكس اتجاه قريب ) == ركزو على هاللون خصوصا مع عملات الخفيفة
Kalman Volume Filter [ChartPrime]The "Kalman Volume Filter" , aims to provide insights into market volume dynamics by filtering out noise and identifying potential overbought or oversold conditions. Let's break down its components and functionality:
Settings:
Users can adjust various parameters to customize the indicator according to their preferences:
Volume Length: Defines the length of the volume period used in calculations.
Stabilization Coefficient (k): Determines the level of noise reduction in the signals.
Signal Line Length: Sets the length of the signal line used for identifying trends.
Overbought & Oversold Zone Level: Specifies the threshold levels for identifying overbought and oversold conditions.
Source: Allows users to select the price source for volume calculations.
Volume Zone Oscillator (VZO):
Calculates a volume-based oscillator indicating the direction and intensity of volume movements.
Utilizes a volume direction measurement over a specified period to compute the oscillator value.
Normalizes the oscillator value to improve comparability across different securities or timeframes.
// VOLUME ZONE OSCILLATOR
VZO(get_src, length) =>
Volume_Direction = get_src > get_src ? volume : -volume
VZO_volume = ta.hma(Volume_Direction, length)
Total_volume = ta.hma(volume, length)
VZO = VZO_volume / (Total_volume)
VZO := (VZO - 0) / ta.stdev(VZO, 200)
VZO
Kalman Filter:
Applies a Kalman filter to smooth out the VZO values and reduce noise.
Utilizes a stabilization coefficient (k) to control the degree of smoothing.
Generates a filtered output representing the underlying volume trend.
// KALMAN FILTER
series float M_n = 0.0 // - the resulting value of the current calculation
series float A_n = VZO // - the initial value of the current measurement
series float M_n_1 = nz(M_n ) // - the resulting value of the previous calculation
float k = input.float(0.06) // - stabilization coefficient
// Kalman Filter Formula
kalm(k)=>
k * A_n + (1 - k) * M_n_1
Volume Visualization:
Displays the volume histogram, with color intensity indicating the strength of volume movements.
Adjusts bar colors based on volume bursts to highlight significant changes in volume.
Overbought and Oversold Zones:
Marks overbought and oversold levels on the chart to assist in identifying potential reversal points.
Plotting:
Plots the Kalman Volume Filter line and a signal line for visual analysis.
Utilizes different colors and fills to distinguish between rising and falling trends.
Highlights specific events such as local buy or sell signals, as well as overbought or oversold conditions.
This indicator provides traders with a comprehensive view of volume dynamics, trend direction, and potential market turning points, aiding in informed decision-making during trading activities.
VWAP DivergenceThe "VWAP Divergence" indicator leverages the VWAP Rolling indicator available in TradingView's library to analyze price and volume dynamics. This custom indicator calculates a rolling VWAP (Volume Weighted Average Price) and compares it with a Simple Moving Average (SMA) over a specified historical period.
Advantages:
1. Accurate VWAP Calculation: The VWAP Rolling indicator computes a VWAP that dynamically adjusts based on recent price and volume data. VWAP is a vital metric used by traders to understand the average price at which a security has traded, factoring in volume.
2. SMA Comparison: By contrasting the rolling VWAP from the VWAP Rolling indicator with an SMA of the same length, the indicator highlights potential divergences. This comparison can reveal shifts in market sentiment.
3. Divergence Identification: The primary purpose of this indicator is to detect divergences between the rolling VWAP from VWAP Rolling and the SMA. Divergence occurs when the rolling VWAP significantly differs from the SMA, indicating potential changes in market dynamics.
Interpretation:
1. Positive Oscillator Values: A positive oscillator (difference between rolling VWAP and SMA) suggests that the rolling VWAP, derived from the VWAP Rolling indicator, is above the SMA. This could indicate strong buying interest or accumulation.
2. Negative Oscillator Values: Conversely, a negative oscillator value indicates that the rolling VWAP is below the SMA. This might signal selling pressure or distribution.
3. Divergence Signals: Significant divergences between the rolling VWAP (from VWAP Rolling) and SMA can indicate shifts in market sentiment. For instance, a rising rolling VWAP diverging upwards from the SMA might suggest increasing bullish sentiment.
4. Confirmation with Price Movements: Traders often use these divergences alongside price action to confirm potential trend reversals or continuations.
Implementation:
1. Length Parameter: Adjust the Length input to modify the lookback period for computing both the rolling VWAP from VWAP Rolling and the SMA. A longer period provides a broader view of market sentiment, while a shorter period is more sensitive to recent price movements.
2. Visualization: The indicator plots the VWAP SMA Oscillator, which visually represents the difference (oscillator) between the rolling VWAP (from VWAP Rolling) and SMA over time.
3. Zero Line: The zero line (gray line) serves as a reference point. Oscillator values crossing above or below this line can be interpreted as bullish or bearish signals, respectively.
4. Contextual Analysis: Interpret signals from this indicator in conjunction with broader market conditions and other technical indicators to make informed trading decisions.
This indicator, utilizing the VWAP Rolling component, is valuable for traders seeking insights into the relationship between volume-weighted price levels and traditional moving averages, aiding in the identification of potential trading opportunities based on market dynamics.
MACD 4C with DivergenceMACD 4C Indicator with Divergence
This indicator, named MACD 4C, enhances the traditional MACD (Moving Average Convergence Divergence) by providing a visually intuitive representation with four distinct colors for the histogram bars. It offers a clear interpretation of market momentum and potential trend reversals.
Key Features:
Customizable Parameters: Users can adjust the fast and slow moving average periods along with the signal smoothing parameter to tailor the indicator to their preferred trading style and market conditions.
Four-color Histogram: The histogram bars are color-coded for easy interpretation. Lime and green bars indicate increasing bullish momentum, while maroon and red bars signify increasing bearish momentum.
Bullish and Bearish Divergence Detection: The indicator identifies bullish and bearish divergences between the MACD histogram and price action. Bullish divergence occurs when the price makes a lower low while the MACD histogram forms a higher low, indicating potential bullish reversal. Conversely, bearish divergence occurs when the price makes a higher high while the MACD histogram forms a lower high, suggesting a potential bearish reversal.
How to Use:
Trend Confirmation: Monitor the color of the histogram bars. A series of green (or lime) bars suggests a strengthening bullish trend, while a series of red (or maroon) bars indicates a strengthening bearish trend.
Divergence Identification: Watch for divergences between the MACD histogram and price action. Bullish divergence may signal a potential bullish reversal, while bearish divergence may indicate a potential bearish reversal. These signals can be used in conjunction with other technical analysis tools to confirm trade entries and exits.
The MACD 4C indicator was developed by user vkno422 You can find the original author and their work on their TradingView profile: www.tradingview.com
RSI and MACD Composite ScoreComponents of the Indicator
RSI Settings:
The RSI is set with a length parameter, which can be adjusted by the user but defaults to 14. This measures the speed and change of price movements.
MACD Settings:
The MACD is composed of two lines: the MACD line and the signal line, which are calculated from exponential moving averages (EMAs) of different lengths (fast and slow). The default settings are 9 for the fast length, 26 for the slow length, and 3 for the signal length.
The MACD histogram, which is the difference between the MACD line and the signal line, is also calculated.
Normalization and Combination
RSI Normalization : The RSI values are normalized around 0 by subtracting 50 from the RSI and then dividing by 50. This scaling adjusts the RSI to fluctuate around 0, where positive values indicate strength and negative values indicate weakness relative to the median RSI value of 50.
MACD Normalization : The MACD histogram is normalized by dividing it by the highest absolute value of the histogram over the slow length period. This adjustment scales the MACD histogram to fall between -1 and 1, making it comparable in magnitude to the normalized RSI.
Composite Score Calculation
The composite score is simply the sum of the normalized RSI and the normalized MACD histogram. This results in a combined score that reflects both momentum (from RSI) and trend (from MACD), providing a multifaceted view of market dynamics.
Visualization
The composite score is plotted as an oscillator, with a horizontal zero line that helps identify when the score shifts from positive to negative or vice versa.
The background color changes based on the trend: green if the composite score is above zero (bullish trend) and red if below zero (bearish trend).
