Display MB on BarsDescription
The "Display MB on Bars" Pine Script indicator is designed to visually represent Market Breadth values and R4.5 scores on trading charts. This script enables traders to highlight and analyze key market behavior using pre-defined thresholds for MB scores and dynamically calculated R4.5 values. Additionally, it includes a moving average status table to assess price levels relative to the 10-day and 20-day moving averages.
Features:
1. COB Date Matching: Displays data corresponding to specific "COB dates" provided by the user.
2. MB Value Visualization:
o Highlights bars with a background color based on MB values:
Red if MB ≤ MB_Red (default: -1).
Green if MB ≥ MB_Green (default: 3).
3. R4.5 Scores Display:
o Creates a label on the chart with the MB and R4.5 values when conditions are met (e.g., R4.5 > 200 or specific MB thresholds).
4. Index Moving Average Comparison:
o Calculates 10-day and 20-day moving averages for the selected symbol (default: NSE:NIFTYMIDSML400).
o Shows the price position relative to these moving averages in a table.
How to Use:
1. Configure Inputs:
o COB Dates: Enter a comma-separated list of dates in the format DD-MM-YYYY.
o MB Values: Provide the corresponding MB scores for the COB dates.
o R4.5 Values: Provide the R4.5 scores for the COB dates.
o Set the thresholds for MB values (MB Red<= and MB Green>=).
o Toggle features like MB, RS (R4.5), and the moving average status table.
2. Interpret the Output:
o Observe background colors on the bars:
Red: Indicates MB is less than or equal to the lower threshold.
Green: Indicates MB exceeds the upper threshold.
o Check labels above bars for R4.5 and MB values when conditions are met.
o Refer to the status table on the top-right corner to understand price positions relative to 10-day and 20-day moving averages.
This script is especially useful for traders seeking insights into custom metrics like MB and R4.5, enabling quick identification of key patterns and trends in the market.
Cerca negli script per "averages"
2 MA Simplified Sideways Candle ColorsHow to Use the Indicator: A Simple Guide
This custom indicator colors candlesticks to help you quickly identify market conditions based on two moving averages (9-period and 21-period). Here’s how to get started:
Add the Indicator to Your Chart:
Copy the provided Pine Script code.
Open TradingView and navigate to the Pine Editor.
Paste the code into a new script, save it, and then add the indicator to your chart.
Understand the Candlestick Colors:
Green Candles (Bullish):
Indicates a bullish market when the price is above the 9-period SMA and the 9 SMA is above the 21 SMA.
Red Candles (Bearish):
Indicates a bearish market when the price is below the 21-period SMA and the 9 SMA is below the 21 SMA.
Yellow Candles (Sideways):
Indicates a sideways (neutral) market when:
Condition 1: Price is below the 9 SMA but above the 21 SMA, with the 9 SMA above the 21 SMA, or
Condition 2: The 9 SMA is below the 21 SMA, and the price lies between them.
White Candles (No Clear Signal):
Used when none of the above conditions apply.
Interpreting the Signals:
When you see green candles, the market is showing bullish momentum.
When you see red candles, bearish pressure is dominant.
Yellow candles suggest the market is moving sideways without a strong trend.
White candles mean that none of the specific conditions (bullish, bearish, or sideways) are currently met.
Chart Reference:
The script also plots two moving averages on your chart (a blue line for the 9-period SMA and an orange line for the 21-period SMA). These lines help visualize how price interacts with these averages.
Using the Indicator in Practice:
Once added to your chart, monitor the color of the candlesticks:
Green signals may be opportunities to consider long positions.
Red signals may indicate a good time to consider short positions or tighten stops.
Yellow signals suggest caution as the market isn’t trending strongly.
White candles indicate no strong signal, so it might be a period of consolidation or indecision.
This simple visual cue system allows you to quickly assess market sentiment and make more informed trading decisions based on the relationship between price and the two moving averages.
Volume Weighted Jurik Moving AverageThe Jurik Moving Average (JMA) is a smoothing indicator that is designed to improve upon traditional moving averages by reducing lag while enhancing responsiveness to price movements. It was created by Jurik Research and is often used to track trends with greater accuracy and minimal delay. The JMA is based on a combination of **exponential smoothing** and **phase adjustments**, making it more adaptable to varying market conditions compared to standard moving averages like SMA (Simple Moving Average) or EMA (Exponential Moving Average).
The core advantage of the JMA lies in its ability to adjust to price changes without excessively lagging, which is a common issue with traditional moving averages. It incorporates a **phase parameter** that can be adjusted to smooth out the signal further or make it more responsive to recent price action. This phase adjustment allows traders to fine-tune the JMA's sensitivity to the market, optimizing it for different timeframes and trading strategies.
How JMA Works and Benefits of Adding Volume Weight
The JMA works by applying a **smoothing process** to price data while allowing for adjustments through its phase and power parameters. These parameters help control the degree of smoothness and responsiveness. The result is a curve that follows price trends closely but with less lag than traditional moving averages.
Adding **volume weighting** to the JMA enhances its ability to reflect market activity more accurately. Just like the **Volume-Weighted Moving Average (VWMA)**, volume-weighting adjusts the moving average based on the strength of trading volume, meaning that price movements with higher volume will have a greater influence on the JMA. This can help traders identify trends that are supported by significant market participation, making the moving average more reliable.
The benefit of a volume-weighted JMA is that it responds more effectively to price movements that occur during periods of high trading volume, which are often considered more significant. This can help traders avoid false signals that may occur during low-volume periods when price changes may not reflect true market sentiment. By incorporating volume into the calculation, the JMA becomes more aligned with real market conditions, enhancing its effectiveness for trend identification and decision-making.
Adaptive Fibonacci Trend Ribbon[FibonacciFlux]Adaptive Fibonacci Trend Ribbon (FibonacciFlux)
Overview
The Adaptive Fibonacci Trend Ribbon is a versatile technical analysis tool designed for traders who want to leverage the power of multiple moving averages while integrating Fibonacci numbers. This indicator provides a dynamic visual representation of market trends, enhancing decision-making processes in trading.
Key Features
1. Multi-Moving Averages
- The indicator calculates eight different moving averages based on user-defined periods, including Fibonacci numbers such as 5, 8, 13, 21, 34, 55, 89, and 144.
- Traders can choose from various moving average types, including EMA, HMA, WMA, VWMA, ALMA, SMA, RMA, and TMA , allowing for tailored analysis based on market conditions.
2. Trend Detection
- Each moving average is color-coded based on its trend direction, with green indicating an upward trend and red indicating a downward trend.
- This visual clarity helps traders quickly assess market sentiment and make informed decisions.
3. Fill Areas for Enhanced Insight
- The indicator features fill areas between the moving averages, which dynamically change color according to their relative positions.
- This provides a clear visual cue of trend strength and potential reversal points, allowing traders to identify key areas of interest.
4. Customizable Inputs
- Users can easily adjust the source data, moving average lengths, and ALMA parameters (offset and sigma) to fit their trading strategies.
- This flexibility ensures that traders can adapt the tool to various market conditions and personal preferences.
Insights and Applications
1. Fibonacci Integration
- By incorporating Fibonacci numbers into the moving average periods, this indicator allows traders to align their strategies with key levels of support and resistance.
- This can enhance the accuracy of entry and exit points, particularly in trending markets.
2. Trend Continuation and Reversal Analysis
- The adaptive nature of the moving averages provides insights into potential trend continuations or reversals.
- Traders can use the indicator to identify when to enter or exit positions based on the interaction between the moving averages.
3. Visual Clarity for Quick Decisions
- The color-coded moving averages and fill areas offer immediate visual feedback on market conditions, helping traders react swiftly to changing dynamics.
- This is especially useful in fast-moving markets where timely decisions are critical.
Conclusion
The Adaptive Fibonacci Trend Ribbon is an essential tool for traders looking to enhance their technical analysis capabilities. By combining multiple moving averages with Fibonacci integration and dynamic visual cues, this indicator offers a robust framework for understanding market trends. Its flexibility and clarity make it an invaluable asset for both novice and experienced traders alike.
Open Source Contribution
This indicator is open source, inviting contributions and improvements from the trading community. Feel free to fork, enhance, and share your insights with the world, helping to foster a collaborative environment for traders everywhere.
WPR Volume Candle [Atareum]AWPRVC (Atareum WPR Volume Candles) is clearly an awesome indicator produced by AtareumFX that is based on William’s Percent Range concepts by combination with volume. This is a new approach of volume candles that is combined with R% concepts and creates such a powerful tool to trace the market and assists traders to make better decisions surly and so much accurate. You can find this new indicator more useful because it has all benefits and advantages of William’s R% and cover its disadvantages. Also it is more powerful because of using volume in its calculations and generate a new candles which is more reliable and trustworthy.
Concept:
Using William’s Percent leading periods and calculations on redesigning new candles in combination with volume, that makes unique reform candles, but these new candles with their new cloud system clearly response to any reasonable price movement with so much information.
As you know if use R% there are some misleading fake signals generate by oscillator, also it could not show any sign of price moving trend which is almost confusing for beginners or even a pro trader! And finally this oscillator is so sensitive to price change that is so creepy to use for most of traders.
This new AWPRVC solve the problem and make all of them handy and useful for you.
The cloud system which is designed in AWPRVC shows the price trend moving from Bearish Zone (-100 to -50 percent) to Bullish Zone (-50 to 0 percent). You can trust the lead moving forward of the clouds in two separate Top and Bottom (Bull and Bear) lines which solely determine the trend and power of price moving. When clouds are close to each other means we continue the trend and when they get far away from each other means we will face powerful trend in near future. If they are in Bearish Zone we continue the selling pressure and vice versa. Following picture shows good sample of Long and Short positions in compare with so many fake signals generated on original R%.
Besides the cloud system of AWPRVC which is clearly show the price trend and it is completely enough for being sure about price moving trend, you can use moving average which is designated in it to confirm the price trend, also.
Also you can see this new AWPRVC candle by using volume within its conformation, make reasonable price candles which is no so sensitive and so creepy and make your decisions come true in peace and clear sense of market moves. You can see following picture which is showing although the real price candles are so unclear and nonsense of making decision but the AWPRVC candles lead you to make true and trustable position.
As you see this new combination of Williams R% oscillator with volume and also generating a perfect new cloud system will clearly help traders even pro to trust the signals and understand whole market movement better and all of original problems of R% solved and even make a most powerful, trustworthy and useful new indicator.
Parameters:
Section 1 : Candle colour setting for flourishing just as you desire !
Section 2 : Defining Periods of R% and source of candle data in combination with determining the smoothing type of moving averages and signal period.
Section 3 : Select using Standard candles alongside with redesigned cloud calculation type and three additional moving averages which can plot on each newly generated candles and standard candles on a chart with the type mode defined in the previous section.
Note: if you want to omit any or all of these moving averages, you can use 0 in period, instead of selecting "None" in the plot moving option!
Usage :
Overall:
Regardless of the additional moving averages which will lead to so many situations of market according to their types and designs, that is four different period for new redesign AWPRVC and three period for standard chart. You can easily select periods and type for these moving averages. Also, do not forget that signal moving averages is shown only on AWPRVC chart and have two different colour for upward and downward trends. Other moving averages are plot by just one single colour.
Cloud levels are so important because AWPRVC candles show respect to them and when they break the clouds upward or downward it is surly beginning of a trend. Do not forget we have 5 levels for tracing new AWPRVC candles move as follows : Ready for Short \ Long, Surly Short \ Long and Turn Trend which is in middle range of movement percent. Each level clearly shows what it means by its name.
Support and Resistance:
Any consolidation of AWPRVC candles in Ready for Short or Long Zones means the support or resistance level due to its nature, but important thing is how long the candles lasts in there or how many times repeated in the same level in AWPRVC chart zone in future.
For plotting the support or resistance you should trace range of AWPRVC candles consolidated and plot zone in standard chart candles just like following picture.
Divergence:
When standard price candles move downward but we see upward trend in clouds of AWPRVC candles that means we should face Bullish Trend because of the divergence and vice versa. You can see perfect example in following picture.
Signal:
Alert of Long :
Bullish candle cross both cloud down and up level simultaneously.
Confirmed Long :
AWPRVC candles cross up turn trend level and pullback to cloud up level.
Take profit of Long:
Any cross down of the AWPRVC candles from surly short level of chart.
Alert of Short :
Bearish candle cross both cloud up and down level simultaneously.
Confirmed Short :
AWPRVC candles cross down turn trend level and pullback to cloud down level.
Take profit of Short:
Any cross up of the AWPRVC candles from surly long level of chart.
Notes:
Use moving averages cross of standard chart candles as lead to be in positions more as they are good representative of trend.
As long as AWPRVC candles or Cloud levels are in Bullish Zone, you can stay in Long positions.
Cloud level thickness means the power of trend and can be use as confirmation of powerful trend, so when cloud levels tight or going to cross each other it means the trend is going to be reversed.
It is the result of many years of experience in markets and there are so many details about this AWPRVC chart which I am in the experiment phase to publish in the future, so please help me with your ideas and do not hesitate to comment and inform me any suggestions or criticism.
Atareum Volume Ichimuku CandleAVIC (Atareum Volume Ichimoku Candles) is clearly an awesome indicator that is based on Ichimoku concepts by combination with volume. This is a new approach of volume candles that is combined with Ichimoku concepts and creates such a powerful tool to trace the market and assists traders to make better decisions, truly.
Concept:
Using Ichimoku leading periods and calculations on redesigning new candles in combination with volume, that makes unique reform candles on Tenkansen movement, but these new candles clearly omit noises in combination with volume, and then the new redesigned system of cloud calculations builds, new series of data for Senko Span A and Senko Span B which is so odd in first view, because they will barely ever cross each other, but they show very more informative and useful.
Parameters:
Section 1 : Candle colour setting for flourishing just as you desire !
Section 2 : Defining Periods of standard Ichimoku and source of candle data in combination with determining the smoothing type of moving averages and signal period.
Section 3 : Select using Heikin Ashi based candles alongside with redesigned cloud calculation type and three additional moving averages which can plot on each newly generated candles and standard candles on a chart with the type mode defined in the previous section.
Note: if you want to omit any or all of these moving averages, you can use 0 in period, instead of selecting "None" in the plot moving option!
Usage :
Overall:
Regardless of the additional moving averages which will lead to so many situations of market according to their types and designs, that is four different period for new redesign AVIC and three period for standard chart. You can easily select periods and type for these moving averages. Also, do not forget that signal moving averages is shown only on AVIC chart and have two different colour for upward and downward trends. Other moving averages are plot by just one single colour.
Cloud levels are so important because AVIC candles show respect to them and when they break the clouds upward or downward it's surly beginning of a trend that is may last long. Also when cloud levels flatten, it is determining a support or resistance according to up cloud or down cloud nature and as long as they will continue or repeated periodically on same level of AVIC chart, it will implement their weakness or strength.
Support and Resistance:
Any flattens of cloud up or down level means the support or resistance level due to its nature, but important thing is how long the cloud lasts flatten or how many times repeated in the same level in AVIC chart.
For plotting the support or resistance you should trace first candle of start of flattens in standard chart just like following picture.
Divergence:
All Higher high or Lower low of standard chart has its reflect in AVIC chart but there is secret in it, It is named divergence. When standard chart price candles generating lower low but the AVIC chart candles do not cross the bottom, it means we will spike high as soon as AVIC candle chart complete its divergence. You can see perfect example in following picture.
Cloud level Ends
When cloud down level become flattens and cloud up level start a bull run it means we will face a great up trend movement but as soon as cloud down level starts to move up it mean we are going to finish the bull run and maybe it goes with consolidation phase or reversal phase. This reaction is exactly happen in vice versa for bear run trend. You can see both examples in following pictures.
Note: if we face end of bull run and cloud down level make a U turn shape upside down it means we will have reversal phase even not too long but it is sharp and fast reversal. If cloud down level just turn right slightly, it means we should have consolidation phase, mostly or we can continue the last trend slightly. All these situations can happen in vice versa bear run. You can see example in following picture.
Signals:
Long but risky:
You can go long when AVIC candles are green and be in position as long as they are not change in colour.
Long and safe :
You can go long when AVIC candles cross up cloud down level and be in position as long as AVIC candles cross down cloud up level.
Long and sure:
You can go long when AVIC candles cross up cloud up level and be in position as long as AVIC candles cross down cloud down level.
Short but risky:
You can go short when AVIC candles are red and be in position as long as they are not change in colour.
Short and safe :
You can go short when AVIC candles cross down cloud up level and be in position as long as AVIC candles cross up cloud down level.
Short and sure:
You can go short when AVIC candles cross down cloud down level and be in position as long as AVIC candles cross up cloud up level.
Notice : Candles with large body are so strong but if a body candle is weak or flatten it may a signal of changing colour and direction, especially when using Heikin Ashi type.
It is the result of many years of experience in markets and there are so many details about this AVIC chart which I am in the experiment phase to publish in the future, so please help me with your ideas and do not hesitate to comment and inform me any suggestions or criticism.
Uptrick: RSI Histogram
1. **Introduction to the RSI and Moving Averages**
2. **Detailed Breakdown of the Uptrick: RSI Histogram**
3. **Calculation and Formula**
4. **Visual Representation**
5. **Customization and User Settings**
6. **Trading Strategies and Applications**
7. **Risk Management**
8. **Case Studies and Examples**
9. **Comparison with Other Indicators**
10. **Advanced Usage and Tips**
---
## 1. Introduction to the RSI and Moving Averages
### **1.1 Relative Strength Index (RSI)**
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder and introduced in his 1978 book "New Concepts in Technical Trading Systems." It is widely used in technical analysis to measure the speed and change of price movements.
**Purpose of RSI:**
- **Identify Overbought/Oversold Conditions:** RSI values range from 0 to 100. Traditionally, values above 70 are considered overbought, while values below 30 are considered oversold. These thresholds help traders identify potential reversal points in the market.
- **Trend Strength Measurement:** RSI also indicates the strength of a trend. High RSI values suggest strong bullish momentum, while low values indicate bearish momentum.
**Calculation of RSI:**
1. **Calculate the Average Gain and Loss:** Over a specified period (e.g., 14 days), calculate the average gain and loss.
2. **Compute the Relative Strength (RS):** RS is the ratio of average gain to average loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS))
### **1.2 Moving Averages (MA)**
Moving Averages are used to smooth out price data and identify trends by filtering out short-term fluctuations. Two common types are:
**Simple Moving Average (SMA):** The average of prices over a specified number of periods.
**Exponential Moving Average (EMA):** A type of moving average that gives more weight to recent prices, making it more responsive to recent price changes.
**Smoothed Moving Average (SMA):** Used to reduce the impact of volatility and provide a clearer view of the underlying trend. The RMA, or Running Moving Average, used in the USH script is similar to an EMA but based on the average of RSI values.
## 2. Detailed Breakdown of the Uptrick: RSI Histogram
### **2.1 Indicator Overview**
The Uptrick: RSI Histogram (USH) is a technical analysis tool that combines the RSI with a moving average to create a histogram that reflects momentum and trend strength.
**Key Components:**
- **RSI Calculation:** Determines the relative strength of price movements.
- **Moving Average Application:** Smooths the RSI values to provide a clearer trend indication.
- **Histogram Plotting:** Visualizes the deviation of the smoothed RSI from a neutral level.
### **2.2 Indicator Purpose**
The primary purpose of the USH is to provide a clear visual representation of the market's momentum and trend strength. It helps traders identify:
- **Bullish and Bearish Trends:** By showing how far the smoothed RSI is from the neutral 50 level.
- **Potential Reversal Points:** By highlighting changes in momentum.
### **2.3 Indicator Design**
**RSI Moving Average (RSI MA):** The RSI MA is a smoothed version of the RSI, calculated using a running moving average. This smooths out short-term fluctuations and provides a clearer indication of the underlying trend.
**Histogram Calculation:**
- **Neutral Level:** The histogram is plotted relative to the neutral level of 50. This level represents a balanced market where neither bulls nor bears have dominance.
- **Histogram Values:** The histogram bars show the difference between the RSI MA and the neutral level. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
## 3. Calculation and Formula
### **3.1 RSI Calculation**
The RSI calculation involves:
1. **Average Gain and Loss:** Calculated over the specified length (e.g., 14 periods).
2. **Relative Strength (RS):** RS = Average Gain / Average Loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS)).
### **3.2 Moving Average Calculation**
For the USH indicator, the RSI is smoothed using a running moving average (RMA). The RMA formula is similar to that of the EMA but is based on averaging RSI values over the specified length.
### **3.3 Histogram Calculation**
The histogram value is calculated as:
- **Histogram Value = RSI MA - 50**
**Plotting the Histogram:**
- **Positive Histogram Values:** Indicate that the RSI MA is above the neutral level, suggesting bullish momentum.
- **Negative Histogram Values:** Indicate that the RSI MA is below the neutral level, suggesting bearish momentum.
## 4. Visual Representation
### **4.1 Histogram Bars**
The histogram is plotted as bars on the chart:
- **Bullish Bars:** Colored green when the RSI MA is above 50.
- **Bearish Bars:** Colored red when the RSI MA is below 50.
### **4.2 Customization Options**
Traders can customize:
- **RSI Length:** Adjust the length of the RSI calculation to match their trading style.
- **Bull and Bear Colors:** Choose colors for histogram bars to enhance visual clarity.
### **4.3 Interpretation**
**Bullish Signal:** A histogram bar that moves from red to green indicates a potential shift to a bullish trend.
**Bearish Signal:** A histogram bar that moves from green to red indicates a potential shift to a bearish trend.
## 5. Customization and User Settings
### **5.1 Adjusting RSI Length**
The length parameter determines the number of periods over which the RSI is calculated and smoothed. Shorter lengths make the RSI more sensitive to price changes, while longer lengths provide a smoother view of trends.
### **5.2 Color Settings**
Traders can adjust:
- **Bull Color:** Color of histogram bars indicating bullish momentum.
- **Bear Color:** Color of histogram bars indicating bearish momentum.
**Customization Benefits:**
- **Visual Clarity:** Traders can choose colors that stand out against their chart’s background.
- **Personal Preference:** Adjust settings to match individual trading styles and preferences.
## 6. Trading Strategies and Applications
### **6.1 Trend Following**
**Identifying Entry Points:**
- **Bullish Entry:** When the histogram changes from red to green, it signals a potential entry point for long positions.
- **Bearish Entry:** When the histogram changes from green to red, it signals a potential entry point for short positions.
**Trend Confirmation:** The histogram helps confirm the strength of a trend. Strong, consistent green bars indicate robust bullish momentum, while strong, consistent red bars indicate robust bearish momentum.
### **6.2 Swing Trading**
**Momentum Analysis:**
- **Entry Signals:** Look for significant shifts in the histogram to time entries. A shift from bearish to bullish (red to green) indicates potential for upward movement.
- **Exit Signals:** A shift from bullish to bearish (green to red) suggests a potential weakening of the trend, signaling an exit or reversal point.
### **6.3 Range Trading**
**Market Conditions:**
- **Consolidation:** The histogram close to zero suggests a range-bound market. Traders can use this information to identify support and resistance levels.
- **Breakout Potential:** A significant move away from the neutral level may indicate a potential breakout from the range.
### **6.4 Risk Management**
**Stop-Loss Placement:**
- **Bullish Positions:** Place stop-loss orders below recent support levels when the histogram is green.
- **Bearish Positions:** Place stop-loss orders above recent resistance levels when the histogram is red.
**Position Sizing:** Adjust position sizes based on the strength of the histogram signals. Strong trends (indicated by larger histogram bars) may warrant larger positions, while weaker signals suggest smaller positions.
## 7. Risk Management
### **7.1 Importance of Risk Management**
Effective risk management is crucial for long-term trading success. It involves protecting capital, managing losses, and optimizing trade setups.
### **7.2 Using USH for Risk Management**
**Stop-Loss and Take-Profit Levels:**
- **Stop-Loss Orders:** Use the histogram to set stop-loss levels based on trend strength. For instance, place stops below support levels in bullish trends and above resistance levels in bearish trends.
- **Take-Profit Targets:** Adjust take-profit levels based on histogram changes. For example, lock in profits as the histogram starts to shift from green to red.
**Position Sizing:**
- **Trend Strength:** Scale position sizes based on the strength of histogram signals. Larger histogram bars indicate stronger trends, which may justify larger positions.
- **Volatility:** Consider market volatility and adjust position sizes to mitigate risk.
## 8. Case Studies and Examples
### **8.1 Example 1: Bullish Trend**
**Scenario:** A trader notices a transition from red to green histogram bars.
**Analysis:**
- **Entry Point:** The transition indicates a potential bullish trend. The trader decides to enter a long position.
- **Stop-Loss:** Set stop-loss below recent support levels.
- **Take-Profit:** Consider taking profits as the histogram moves back towards zero or turns red.
**Outcome:** The bullish trend continues, and the histogram remains green, providing a profitable trade setup.
### **8.2 Example 2: Bearish Trend**
**Scenario:** A trader observes a transition from green to red histogram bars.
**Analysis:**
- **Entry Point:** The transition suggests a potential
bearish trend. The trader decides to enter a short position.
- **Stop-Loss:** Set stop-loss above recent resistance levels.
- **Take-Profit:** Consider taking profits as the histogram approaches zero or shifts to green.
**Outcome:** The bearish trend continues, and the histogram remains red, resulting in a successful trade.
## 9. Comparison with Other Indicators
### **9.1 RSI vs. USH**
**RSI:** Measures momentum and identifies overbought/oversold conditions.
**USH:** Builds on RSI by incorporating a moving average and histogram to provide a clearer view of trend strength and momentum.
### **9.2 RSI vs. MACD**
**MACD (Moving Average Convergence Divergence):** A trend-following momentum indicator that uses moving averages to identify changes in trend direction.
**Comparison:**
- **USH:** Provides a smoothed RSI perspective and visual histogram for trend strength.
- **MACD:** Offers signals based on the convergence and divergence of moving averages.
### **9.3 RSI vs. Stochastic Oscillator**
**Stochastic Oscillator:** Measures the level of the closing price relative to the high-low range over a specified period.
**Comparison:**
- **USH:** Focuses on smoothed RSI values and histogram representation.
- **Stochastic Oscillator:** Provides overbought/oversold signals and potential reversals based on price levels.
## 10. Advanced Usage and Tips
### **10.1 Combining Indicators**
**Multi-Indicator Strategies:** Combine the USH with other technical indicators (e.g., Moving Averages, Bollinger Bands) for a comprehensive trading strategy.
**Confirmation Signals:** Use the USH to confirm signals from other indicators. For instance, a bullish histogram combined with a moving average crossover may provide a stronger buy signal.
### **10.2 Customization Tips**
**Adjust RSI Length:** Experiment with different RSI lengths to match various market conditions and trading styles.
**Color Preferences:** Choose histogram colors that enhance visibility and align with personal preferences.
### **10.3 Continuous Learning**
**Backtesting:** Regularly backtest the USH with historical data to refine strategies and improve accuracy.
**Education:** Stay updated with trading education and adapt strategies based on market changes and personal experiences.
Leading T3Hello Fellas,
Here, I applied a special technique of John F. Ehlers to make lagging indicators leading. The T3 itself is usually not realling the classic lagging indicator, so it is not really needed, but I still publish this indicator to demonstrate this technique of Ehlers applied on a simple indicator.
The indicator does not repaint.
In the following picture you can see a comparison of normal T3 (purple) compared to a 2-bar "leading" T3 (gradient):
The range of the gradient is:
Bottom Value: the lowest slope of the last 100 bars -> green
Top Value: the highest slope of the last 100 bars -> purple
Ehlers Special Technique
John Ehlers did develop methods to make lagging indicators leading or predictive. One of these methods is the Predictive Moving Average, which he introduced in his book “Rocket Science for Traders”. The concept is to take a difference of a lagging line from the original function to produce a leading function.
The idea is to extend this concept to moving averages. If you take a 7-bar Weighted Moving Average (WMA) of prices, that average lags the prices by 2 bars. If you take a 7-bar WMA of the first average, this second average is delayed another 2 bars. If you take the difference between the two averages and add that difference to the first average, the result should be a smoothed line of the original price function with no lag.
T3
To compute the T3 moving average, it involves a triple smoothing process using exponential moving averages. Here's how it works:
Calculate the first exponential moving average (EMA1) of the price data over a specific period 'n.'
Calculate the second exponential moving average (EMA2) of EMA1 using the same period 'n.'
Calculate the third exponential moving average (EMA3) of EMA2 using the same period 'n.'
The formula for the T3 moving average is as follows:
T3 = 3 * (EMA1) - 3 * (EMA2) + (EMA3)
By applying this triple smoothing process, the T3 moving average is intended to offer reduced noise and improved responsiveness to price trends. It achieves this by incorporating multiple time frames of the exponential moving averages, resulting in a more accurate representation of the underlying price action.
Thanks for checking this out and give a boost, if you enjoyed the content.
Best regards,
simwai
---
Credits to @loxx
Fib TSIFib TSI = Fibonacci True Strength Index
The Fib TSI indicator uses Fibonacci numbers input for the True Strength Index moving averages. Then it is converted into a stochastic 0-100 scale.
The Fibonacci sequence is the series of numbers where each number is the sum of the two preceding numbers. 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610...
TSI uses moving averages of the underlying momentum of a financial instrument.
Stochastic is calculated by a formula of high and low over a length of time on a scale of 0-100.
How to use Fib TSI:
100 = overbought
0 = oversold
Rising = bullish
Falling = bearish
crossover 50 = bullish
crossunder 50 = bearish
The default input settings are:
2 = Stoch D smoothing
3 = TSI signal
TSI uses 2 moving averages compared with each other.
5 = TSI fastest
TSI uses 2 moving averages compared with each other.
Default value is 3/5.
color = white
8 = TSI fast
TSI uses 2 moving averages compared with each other.
Default value is 5/8.
color = blue
13 = TSI mid
TSI uses 2 moving averages compared with each other.
Default value is 8/13.
color = orange
21 = TSI slow
TSI uses 2 moving averages compared with each other.
Default value is 13/21.
color = purple
34 = TSI slowest
TSI uses 2 moving averages compared with each other.
Default value is 21/34.
color = yellow
55 = Stoch K length
All total / 5 = All TSI
color rising above 50 = bright green
color falling above 50 = mint green
color falling below 50 = bright red
color rising below 50 = pink
Up bullish reversal = green arrow up
bullish trend = green dots
Down bearish reversal = red arrow down
bearish trend = red dots
Horizontal lines:
100
75
50
25
0
2 different visual options example snapshot:
Extended Moving Average (MA) LibraryThis Extended Moving Average Library is a sophisticated and comprehensive tool for traders seeking to expand their arsenal of moving averages for more nuanced and detailed technical analysis.
The library contains various types of moving averages, each with two versions - one that accepts a simple constant length parameter and another that accepts a series or changing length parameter.
This makes the library highly versatile and suitable for a wide range of strategies and trading styles.
Moving Averages Included:
Simple Moving Average (SMA): This is the most basic type of moving average. It calculates the average of a selected range of prices, typically closing prices, by the number of periods in that range.
Exponential Moving Average (EMA): This type of moving average gives more weight to the latest data and is thus more responsive to new price information. This can help traders to react faster to recent price changes.
Double Exponential Moving Average (DEMA): This is a composite of a single exponential moving average, a double exponential moving average, and an exponential moving average of a triple exponential moving average. It aims to eliminate lag, which is a key drawback of using moving averages.
Jurik Moving Average (JMA): This is a versatile and responsive moving average that can be adjusted for market speed. It is designed to stay balanced and responsive, regardless of how long or short it is.
Kaufman's Adaptive Moving Average (KAMA): This moving average is designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Smoothed Moving Average (SMMA): This type of moving average applies equal weighting to all observations and smooths out the data.
Triangular Moving Average (TMA): This is a double smoothed simple moving average, calculated by averaging the simple moving averages of a dataset.
True Strength Force (TSF): This is a moving average of the linear regression line, a statistical tool used to predict future values from past values.
Volume Moving Average (VMA): This is a simple moving average of a volume, which can help to identify trends in volume.
Volume Adjusted Moving Average (VAMA): This moving average adjusts for volume and can be more responsive to volume changes.
Zero Lag Exponential Moving Average (ZLEMA): This type of moving average aims to eliminate the lag in traditional EMAs, making it more responsive to recent price changes.
Selector: The selector function allows users to easily select and apply any of the moving averages included in the library inside their strategy.
This library provides a broad selection of moving averages to choose from, allowing you to experiment with different types and find the one that best suits your trading strategy.
By providing both simple and series versions for each moving average, this library offers great flexibility, enabling users to pass both constant and changing length parameters as needed.
Munich GuppyWELCOME to the Munich Guppy!
This is a simple moving average indicator that will help you determine the trend of your chart using historical moving averages.
The indicator consists of 3 EMA's and one ALMA moving average. Using these 4 moving averages I have programmed the relationship between the moving averages to color the background of your chart.
If your background is red, this means that the alma moving average has fallen below the EMA's (EMA1 and EMA 2) as well as (EMA 1 and EMA 2) are postured in a down trending/up trending fashion
For example, the 21EMA is greater than the 55EMA, this signals that the chart has been outperforming its intermediate averages. Now if the ALMA is below both the 21ema and 55ema, in this instance, your chart background will become green.
The ALMA has color options '+CoC' and '-Coc', this simply means if the candle closes below the alma, it will turn red, if closure above it will turn green.
EMA 3 which is default set to 200, has no affect on the color of the background.
Now I hope I have thoroughly explained the simplicity of this indicator, if you have any questions leave them below or private message me for any other requests,
Good Trading!
-CheatCode1
CCMA - Count Condition MA (560 Indicators In One) Do you like using moving averages?
Why do you think a pair of moving averages on a chart will help you?
What is the probability that once two moving averages have crossed, you will successfully enter the trade?
So why not use 100+ moving averages at once to increase the probability of a successful trade?
And all this can be seen in a single oscillator as a histogram!
I want to introduce you to a system that takes into account 560 moving averages movements. And that's just for a second, 560 potential indicators.
Specifically:
- 22 types of MA (EMA, SMA, RMA and others).
- 176 moving averages.
- 310 crossover checks.
- 252 checks of trend following.
The indicator makes the most of the opportunities provided by television. Therefore, it can take a long time to load it.
How does it work ?
In general, the indicator counts the number of fulfilled conditions.
It checks if MA #1 and MA #2 have crossed. If so, it adds +1 to the statistics. It also checks if price is above or below the moving average. There are a total of 560 such checks. (This is about the maximum the TV allowed me).
The default is 8 lengths of moving averages, I took the Fibonacci numbers thinking they were the optimal solution. You can take any of your favorites.
If the "Ratio MOD" feature is on. Then you can see how many MAs are showing signals to enter a long or short position.
You can also see the indication at the bottom as dots. They show which signals are longer/shorter. If the number of signals is the same, the dot will be yellow. The first line of dots counts the number of crossings. The second line counts the number of crossovers + checks whether the price is above or below the average slippage.
If the "Differ MOD" function is enabled. Then you can see the difference between long and short signals. With the same indication as in RATIO MOD.
If "Show all" is on, then the bar graph shows all 560 accounting options. If it is off, only the number of crossovers is displayed. (This does not apply to the display as points)
If the script shows an error, try to change the timeframe and go back. Or add it again.
You can also disable the histogram in the stats settings and leave only the points that help in determining the trend.
AMACD - All Moving Average Convergence DivergenceThis indicator displays the Moving Average Convergane and Divergence ( MACD ) of individually configured Fast, Slow and Signal Moving Averages. Buy and sell alerts can be set based on moving average crossovers, consecutive convergence/divergence of the moving averages, and directional changes in the histogram moving averages.
The Fast, Slow and Signal Moving Averages can be set to:
Exponential Moving Average ( EMA )
Volume-Weighted Moving Average ( VWMA )
Simple Moving Average ( SMA )
Weighted Moving Average ( WMA )
Hull Moving Average ( HMA )
Exponentially Weighted Moving Average (RMA) ( SMMA )
Symmetrically Weighted Moving Average ( SWMA )
Arnaud Legoux Moving Average ( ALMA )
Double EMA ( DEMA )
Double SMA (DSMA)
Double WMA (DWMA)
Double RMA ( DRMA )
Triple EMA ( TEMA )
Triple SMA (TSMA)
Triple WMA (TWMA)
Triple RMA (TRMA)
Linear regression curve Moving Average ( LSMA )
Variable Index Dynamic Average ( VIDYA )
Fractal Adaptive Moving Average ( FRAMA )
If you have a strategy that can buy based on External Indicators use 'Backtest Signal' which returns a 1 for a Buy and a 2 for a sell.
'Backtest Signal' is plotted to display.none, so change the Style Settings for the chart if you need to see it for testing.
Keltner Channel With User Selectable Moving AvgKeltner Channel with user options to calculate the moving average basis and envelopes from a variety of different moving averages.
The user selects their choice of moving average, and the envelopes automatically adjust. The user may select a MA that reacts faster to volatility or slower/smoother.
Added additional options to color the envelopes or basis based on the current trend and alternate candle colors for envelope touches. The script has a rainbow gradient by default based on RSI.
Options (generally from slower/smoother to faster/more responsive to volatility):
SMMA,
SMA,
Donchian, (Note: Selecting Donchian will just convert this indicator to a regular Donchian Channel)
Tillson T3,
EMA,
VWMA,
WMA,
EHMA,
ALMA,
LSMA,
HMA,
TEMA
Value Added:
Allows Keltner Channel to be calculated from a variety of moving averages other than EMA/SMA, including ones that are well liked by traders such as Tillson T3, ALMA, Hull MA, and TEMA.
Glossary:
The Hull Moving Average ( HMA ), developed by Alan Hull, is an extremely fast and smooth moving average . In fact, the HMA almost eliminates lag altogether and manages to improve smoothing at the same time.
The Exponential Hull Moving Average is similar to the standard Hull MA, but with superior smoothing. The standard Hull Moving Average is derived from the weighted moving average ( WMA ). As other moving average built from weighted moving averages it has a tendency to exaggerate price movement.
Weighted Moving Average: A Weighted Moving Average ( WMA ) is similar to the simple moving average ( SMA ), except the WMA adds significance to more recent data points.
Arnaud Legoux Moving Average: ALMA removes small price fluctuations and enhances the trend by applying a moving average twice, once from left to right, and once from right to left. At the end of this process the phase shift (price lag) commonly associated with moving averages is significantly reduced. Zero-phase digital filtering reduces noise in the signal. Conventional filtering reduces noise in the signal, but adds a delay.
Least Squares: Based on sum of least squares method to find a straight line that best fits data for the selected period. The end point of the line is plotted and the process is repeated on each succeeding period.
Triple EMA (TEMA) : The triple exponential moving average (TEMA) was designed to smooth price fluctuations, thereby making it easier to identify trends without the lag associated with traditional moving averages (MA). It does this by taking multiple exponential moving averages (EMA) of the original EMA and subtracting out some of the lag.
Running (SMoothed) Moving Average: A Modified Moving Average (MMA) (otherwise known as the Running Moving Average (RMA), or SMoothed Moving Average (SMMA)) is an indicator that shows the average value of a security's price over a period of time. It works very similar to the Exponential Moving Average, they are equivalent but for different periods (e.g., the MMA value for a 14-day period will be the same as EMA-value for a 27-days period).
Volume-Weighted Moving Average: The Volume-weighted Moving Average (VWMA) emphasizes volume by weighing prices based on the amount of trading activity in a given period of time. Users can set the length, the source and an offset. Prices with heavy trading activity get more weight than prices with light trading activity.
Tillson T3: The Tillson moving average a.k.a. the Tillson T3 indicator is one of the smoothest moving averages and is both composite and adaptive.
Adjustable MA & Alternating Extremities [LuxAlgo]Returns a moving average allowing the user to control the amount of lag as well as the amplitude of its overshoots thanks to a parametric kernel. The indicator displays alternating extremities and aims to provide potential points where price might reverse.
Due to user requests, we added the option to display the moving average as candles instead of a solid line.
Settings
Length: MA period, refers to the number of most recent data points to use for its calculation.
Mult: Multiplicative factor for each extremity.
As Smoothed Candles: Allows the user to show the MA as a series of candles instead of a solid line.
Show Alternating Extremities : Determines whether to display the alternating extremities or not.
Lag: Controls the amount of lag of the MA, with higher values returning a MA with more lag.
Overshoot: Controls the amplitude of the overshoots returned by the MA, with higher values increasing the amplitude of the overshoots.
Usage
Moving averages using parametric kernels allows users to have more control over characteristics such as lag or smoothness; this can greatly benefit the analyst. A moving average with reduced lag can be used as a leading moving average in a MA crossover system, while lag will benefit moving averages used as slow MA in a crossover system.
Increasing 'Lag' will increase smoothness while increasing 'overshoot' will reduce lag.
The following indicator puts more emphasis on its alternating extremities, an upper extremity will be shown once the high price crosses the upper extremity, while a low extremity will be shown once the low price crosses the lower extremity. These can be interpreted like extremities of a band indicator.
The MA using a length value of 200 with a multiplicative factor of 1.
In general, extremities will effectively return points where price might potentially bounce in ranging markets while closing prices under trending markets will often be found above an upper extremity and under a lower extremity.
Reducing the lag of the moving average allows the user to obtain a more timely estimate of the underlying trend in the price, with a better fit overall. This allows the user to obtain potentially pertinent extremities where price might reverse upon a break, even under trending markets.
In the above chart, the price initially breaks the upper extremity, however, we can observe that the upper extremity eventually reaches back the price, goes above it, provides a resistance, and effectively indicates a reversal.
Users can plot candles from the moving average, these are fairly similar to heikin-ashi candles in the sense that CandleOpen(t) ≠ CandleClose(t-1) , each point of the candle is calculated as follows for our indicator:
Open = Average between MA(t-1) and MA(t-2)
High = MA using the high price as input
Low = MA using the low price as input
Close = MA using the closing price as input
Details
Lag is defined as the effect of moving averages to reflect past price variations instead of new ones, lag can be observed by the user and is the main cause of false signals. Lag is proportional to the degree of filtering returned by the moving average.
Overshooting is a common effect encountered in non-lagging moving averages, and is defined as the tendency of a moving average to exceed a maximum level (or minimum level, which can be defined as undershooting )
MA and rolling maximum/minimum, both using a length of 50 bars. While we can think of lag as a cost of smoothness, we can think of overshooting as a cost for reduced lag on some occasions.
Explaining the kernel design behind our moving average requires understanding of the logic behind lag reduction in moving averages. This can prove to be complex for non informed users, but let's just focus on the simpler part; moving averages can be defined as a weighted sum between past prices and a set of coefficients (kernel).
MA(t) = b(0)C(t) + b(1)C(t-1) + b(2)C(t-2) + ... + b(n-1)C(t-n-1)
Where n is the period of the moving average. Lag is (non optimally) reduced by "underweighting" past prices - that is multiplying them by negative numbers.
The kernel used in our moving average is based on a modified sinewave. A weighted sum making use of a sinewave as a kernel would return an oscillator centered at 0. We can divide this sinewave by an increasing linear function in order to obtain a kernel allowing us to obtain a low lag moving average instead of a centered oscillator. This is the main idea in the design of the kernel used by our moving average.
The kernel equation of our moving average is:
sin(2πx^α)(1 - x^β)
With 1>x>0 , and where α controls the lag, while β controls the overshoot amplitude.
Using this equation we can obtain the following kernels:
Here only α is changed, while β is equal to 1. Values to the left would represent the coefficients for the most recent prices. Notice how the most significant coefficients are given to the oldest prices in the case where α increases.
Higher overshoot would require more negative values, this is controlled by β
Here only β is changed, while α is equal to 1. Notice how higher values return lower negative coefficients. This effectively increases the overshoots amplitude in our moving average. We can decrease α in order for these negative coefficients to underweight more recent values.
Using α = 0 allows us to simplify the kernel equation to:
1 - x^β
Using this kernel we can obtain more classical moving averages, this can be seen from the following results:
Using β = 1 allows us to obtain a linearly decreasing kernel (the one of a WMA), while increasing allows the kernel to converge toward a rectangular kernel (the one of SMA).
Multi Moving Average Crossing (by Coinrule)Moving Averages are among the most common trading indicators. They are straightforward to interpret and effective to use.
One of the limitations of using moving averages is they can provide buy and sell signals with a relatively high lag , making it very difficult to spot the lows and tops of the trend.
Moving averages calculated with a low number of periods like the MA9 (the average of the previous nine price periods) react very fast to price moves providing prompt signals. On the other side, more signals may end up with more false-signals and more trades in a loss.
On the contrary, moving averages calculated with a higher number of periods like the MA100 (which considers the previous one hundred price periods) give more reliable signals, but with a delay.
A system catching the crossing of the MA50 over the MA100 is a good compromise for successful long-term strategies. It provides, on average, reliable buy signals.
The Multi Moving Average Crossing Strategy tries to optimize the exit without waiting for the same opposite crossing (MA50 below MA100). It uses the MA9 crossing below the MA50, instead, to spot a better time for selling.
The setup is as follows.
BUY when the Moving Average 50 crosses above the Moving Average 100
SELL when the Moving Average 9 crosses below the Moving Average 50
The higher is the time frame to calculate the Moving Averages, the better is the overall performance of the strategy. The 4-hour (or 6-hour) time frame seems to be the best, even if it results in fewer trades. If you want to trade more still with good results, the 1-hour time is a good compromise.
Advantages of the strategy
This strategy seeks to catch those that are more likely relevant uptrends and close the trade relatively quickly. More trades mean more opportunities. This is especially effective if you run the strategy on all the available coins on the market, as you could do with Coinrule.
Generally, a Multi Moving Averages approach beats the classic crossing strategy involving only two Moving Averages. We backtested a sample of twenty trading pairs to assess the benefits empirically.
The results show that the Multi Moving Average Strategy
outperforms 13 out of 20 times
has 95% higher average return
has 67% higher median return
The strategy assumes each order to trade 30% of the available capital and opens a trade at a time. A trading fee of 0.1% is taken into account.
Price Distance to its MA by DGTPrices high above the moving average (MA) or low below it are likely to be remedied in the future by a reverse price movement as stated in an Article by Denis Alajbeg, Zoran Bubas and Dina Vasic published in International Journal of Economics, Commerce and Management
Here comes a study to indicate the idea of this article, Price Distance to its Moving Averages (P/MA Ratio)
The analysis expressed in the paper indicates that there is a connection between the distance of the prices to moving averages and subsequent returns : portfolios of stocks with lower prices to moving averages generally outperformed portfolios of stocks with higher prices to moving averages. This “overextended” effect is more pronounced when using shorter moving averages of 20 and 50 days, and is especially strong in short-term holding periods like one and two weeks. The highest annual returns are recorded when buying in the range of 0-5% below shorter moving averages of 20/50 days, and 0-10% below longer moving averages of 100/200 days. However, buying very far below almost all moving averages on almost all holding periods produces the lowest returns.
The concept of this study recognizes three different modes of action.
In a clearly established upward trend traders should be buying when prices are near or below the MA line and selling when prices move too far above the MA.
Conversely, in downward trend stocks should be shorted when reaching or going above the moving average and covered when they drop too far below the MA line.
In a sideways movement traders are advised to buy if the price is too low below the moving average and sell when it goes too far above it
Short-term traders can expect to outperform in a one or two week time window if buying stocks with lower prices compared to their 20 and 50 SMA/EMA, one to two-week holding periods is quite high, ranging from 72,09% to 90,61% for the SMA(20, 50) and 85,03% to 87,5% for the EMA(20, 50). The best results for the SMA 20 and 50, on average, are concentrated in the region of 0-5% below the MA for the majority of holding periods. Buying very far below almost all MA in almost all holding periods turns out to be the worst possible option
Candle patterns, momentum could be used in conjunction with this indicator for better results. Try Colored DMI and Ichimoku colored SuperTrend by DGT
Shapeshifting Moving Average - Switching From Low-Lag To SmoothThe term "shapeshifting" is more appropriate when used with something with a shape that isn't supposed to change, this is not the case of a moving average whose shape can be altered by the length setting or even by an external factor in the case of adaptive moving averages, but i'll stick with it since it describe the purpose of the proposed moving average pretty well.
In the case of moving averages based on convolution, their properties are fully described by the moving average kernel ( set of weights ), smooth moving averages tend to have a symmetrical bell shaped kernel, while low lag moving averages have negative weights. One of the few moving averages that would let the user alter the shape of its kernel is the Arnaud Legoux moving average, which convolve the input signal with a parametric gaussian function in which the center and width can be changed by the user, however this moving average is not a low-lagging one, as the weights don't include negative values.
Other moving averages where the user can change the kernel from user settings where already presented, i posted a lot of them, but they only focused on letting the user decrease or increase the lag of the moving average, and didn't included specific parameters controlling its smoothness. This is why the shapeshifting moving average is proposed, this parametric moving average will let the user switch from a smooth moving average to a low-lagging one while controlling the amount of lag of the moving average.
Settings/Kernel Interaction
Note that it could be possible to design a specific kernel function in order to provide a more efficient approach to today goal, but the original indicator was a simple low-lag moving average based on a modification of the second derivative of the arc tangent function and because i judged the indicator a bit boring i decided to include this parametric particularity.
As said the moving average "kernel", who refer to the set of weights used by the moving average, is based on a modification of the second derivative of the arc tangent function, the arc tangent function has a "S" shaped curve, "S" shaped functions are called sigmoid functions, the first derivative of a sigmoid function is bell shaped, which is extremely nice in order to design smooth moving averages, the second derivative of a sigmoid function produce a "sinusoid" like shape ( i don't have english words to describe such shape, let me know if you have an idea ) and is great to design bandpass filters.
We modify this 2nd derivative in order to have a decreasing function with negative values near the end, and we end up with:
The function is parametric, and the user can change it ( thus changing the properties of the moving average ) by using the settings, for example an higher power value would reduce the lag of the moving average while increasing overshoots. When power < 3 the moving average can act as a slow moving average in a moving average crossover system, as weights would not include negative values.
Here power = 0 and length = 50. The shapeshifting moving average can approximate a simple moving average with very low power values, as this would make the kernel approximate a rectangular function, however this is only a curiosity and not something you should do.
As A Smooth Moving Average
“So smooth, and so tranquil. It doesn't get any quieter than this”
A smooth moving average kernel should be : symmetrical, not to width and not to sharp, bell shaped curve are often appropriates, the proposed moving average kernel can be symmetrical and can return extremely smooth results. I will use the Blackman filter as comparison.
The smooth version of the moving average can be used when the "smooth" setting is selected. Here power can only be an even number, if power is odd, power will be equal to the nearest lowest even number. When power = 0, the kernel is simply a parabola:
More smoothness can be achieved by using power = 2
In red the shapeshifting moving average, in green a Blackman filter of both length = 100. Higher values of power will create lower negative values near the border of the kernel shape, this often allow to retain information about the peaks and valleys in the input signal. Power = 6 approximate the Blackman filter pretty well.
Conclusion
A moving average using a modification of the 2nd derivative of the arc tangent function as kernel has been presented, the kernel is parametric and allow the user to switch from a low-lag moving average where the lag can be increased/decreased to a really smooth moving average.
As you can see once you get familiar with a function shape, you can know what would be the characteristics of a moving average using it as kernel, this is where you start getting intimate with moving averages.
On a side note, have you noticed that the views counter in posted ideas/indicators has been removed ? This is truly a marvelous idea don't you think ?
Thanks for reading !
Moving Average Heatmap Visualization7 different types of moving averages (5 different lengths of each) compared to a base moving average. Base moving average can be configured to be a slew of different types of moving averages (credit to @mortdiggiddy for the code) and have a custom length.
Red = base moving average is over other moving average (bearish)
Green = base moving average is under other moving average (bullish)
lengths for the different MAs are just fibonacci numbers due to lack of creativity.
First 5 moving averages are Simple moving average the next 5 are Exponential moving averages and after that it is weighted moving averages, volume weighted moving average (VWAP), Exponential volume weighted moving average (thanks again @mortdiggiddy ), hull moving averages and lastly zero lag moving averages.
The indicator might lag your chart out a bit so be ready for that.
Have fun!
Trend is your friendThis indicator evaluates the trend based on crosses of two McGinley moving averages. It paints candles accordingly (it does not repaint), so you can see what the indicator is saying more clearly and stay in your trade until you see a period of consolidation or a reversal. You can control how far away those moving averages need to be for you to consider it a trend. If this distance is not met candles color is not changed and it shows you that the market is in a period of consolidation. I also added visualization of RSI, so you can have an easier time finding appropriate profit targets. For stop loss I would recommend placing it a couple points above or below the previous high / low that is located above / below you final target for entry. You can also use a certain percentage that works for you. I tried adding a stop loss based on ATR, but I did not like the results. Using market structure is a better choice in my opinion.
Here is a basic trading strategy for the default settings:
Wait for the indicator to start printing a series of green or red candles. After that you can enter a long or a short around moving averages. Another valid place to entry is the specific RSI zone. If we are in an uptrend buying when RSI is oversold can be beneficial as you expect market to recover. I do not recommend changing RSI from 14. Vice versa for the downtrend. It gives you an edge as you know at what price RSI will be oversold and allows you to place trades in advance. Pretty neat! You need to realize that no indicator or strategy can give you an exact entry. There will always be some margin of error. What I wanted to say is that if there is a strong trend up and you buy around your key moving averages and when RSI is oversold you entered in good places and there is a pretty good chance you will make money.
Time frame settings:
If you want to use tighter stop losses I would recommend sticking to 15m. Do not go lower. It is not worth the stress. 1h and 4h seems to be very good as well, but expect your stop losses to be wider. What I personally tend to do is display 15m, 30m and 1h and compare it. Think of it as a short, mid and long term. That way you can see things little bit better.
Examples:
1H chart BTC
4h chart EUR / USD
1D chart NASDAQ
15m chart BTC (Daytrading)
That last chart shows that even if you were longing while the trend was about to change you still had a good chance to close it with a little profit and switch to short easily. The default settings is what has worked the best for me. Feel free to change them as you see fit and do not forget to let me know if you find something that works better :)
Notes:
Either disable wick display or change it to a neutral color like gray for both green and red candles. Unfortunately pine script does not allow wick painting, so if you have red / green wicks it will look terrible. If RSI visualization makes your candles look too small you can go to settings and disable the display of individual RSI levels. You will still be able to see the zones, but the scale won't be affected.
Percentage Price Oscillator (PPO)The Percentage Price Oscillator (PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. As with its cousin, MACD, the Percentage Price Oscillator is shown with a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers, and divergences. First, PPO readings are not subject to the price level of the security. Second, PPO readings for different securities can be compared, even when there are large differences in the price.
Calculations
PPO: {(12-day EMA - 26-day EMA)/26-day EMA} x 100
Signal Line: 9-day EMA of PPO
PPO Histogram: PPO - Signal Line
While MACD measures the absolute difference between two moving averages, PPO makes this a relative value by dividing the difference by the slower moving average (26-day EMA). PPO is simply the MACD value divided by the longer moving average. The result is multiplied by 100 to move the decimal place two spots.
Interpretation
As with MACD, the PPO reflects the convergence and divergence of two moving averages. PPO is positive when the shorter moving average is above the longer moving average. The indicator moves further into positive territory as the shorter moving average distances itself from the longer moving average. This reflects strong upside momentum. The PPO is negative when the shorter moving average is below the longer moving average. Negative readings grow when the shorter moving average distances itself from the longer moving average (goes further negative). This reflects strong downside momentum. The histogram represents the difference between PPO and its 9-day EMA, the signal line. The histogram is positive when PPO is above its 9-day EMA and negative when PPO is below its 9-day EMA. The PPO-Histogram can be used to anticipate signal line crossovers in the PPO.
MACD, PPO and Price
MACD levels are affected by the price of a security. A high-priced security will have higher or lower MACD values than a low-priced security, even if volatility is basically equal. This is because MACD is based on the absolute difference in the two moving averages. Because MACD is based on absolute levels, large price changes can affect MACD levels over an extended period of time. If a stock advances from 20 to 100, its MACD levels will be considerably smaller around 20 than around 100. The PPO solves this problem by showing MACD values in percentage terms.
Conclusions
The Percentage Price Oscillator (PPO) generates the same signals as the MACD, but provides an added dimension as a percentage version of MACD. The PPO levels of the Dow Industrials (price > 20K) can be compared against the PPO levels of IBM (price < 200) because the PPO “levels” the playing field. In addition, PPO levels in one security can be compared over extended periods of time, even if the price has doubled or tripled. This is not the case for the MACD.
Limitations
Despite its advantages, the PPO is still not the best oscillator to identify overbought or oversold conditions because movements are unlimited (in theory). Levels for RSI and the Stochastic Oscillator are limited and this makes them better suited to identify overbought and oversold levels.
Source: Stockcharts
Hyper Insight MA Strategy [Universal]Hyper Insight MA Strategy ** is a comprehensive trend-following engine designed for traders who require precision and flexibility. Unlike standard indicators that lock you into a single calculation method, this strategy serves as a "Universal Adapter," allowing you to **Mix & Match 13 different Moving Average types** for both the Fast and Slow trend lines independently.
Whether you need the smoothness of T3, the responsiveness of HMA, or the classic reliability of SMA, this script enables you to backtest thousands of combinations to find the perfect edge for your specific asset class.
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🔬 Deep Dive: Calculation Logic of Included MAs
This strategy includes 13 distinct calculation methods. Understanding the math behind them will help you choose the right tool for your specific market conditions.
#### 1. Standard Averages
* **SMA (Simple Moving Average):** The unweighted mean of the previous $n$ data points.
* *Logic:* Treats every price point in the period with equal importance. Good for identifying long-term macro trends but reacts slowly to recent volatility.
* **WMA (Weighted Moving Average):** A linear weighted average.
* *Logic:* Assigns heavier weight to current data linearly (e.g., $1, 2, 3... n$). It reacts faster than SMA but is still relatively smooth.
* **SWMA (Symmetrically Weighted Moving Average):**
* *Logic:* Uses a fixed-length window (usually 4 bars) with symmetrical weights $ $. It prioritizes the center of the recent data window.
#### 2. Exponential & Lag-Reducing Averages
* **EMA (Exponential Moving Average):**
* *Logic:* Applies an exponential decay weighting factor. Recent prices have significantly more impact on the average than older prices, reducing lag compared to SMA.
* **RMA (Running Moving Average):** Also known as Wilder's Smoothing (used in RSI).
* *Logic:* It is essentially an EMA but with a slower alpha weight of $1/length$. It provides a very smooth, stable line that filters out noise effectively.
* **DEMA (Double Exponential Moving Average):**
* *Logic:* Calculated as $2 \times EMA - EMA(EMA)$. By subtracting the "lag" (the smoothed EMA) from the original EMA, DEMA provides a much faster reaction to price changes with less noise than a standard EMA.
* **TEMA (Triple Exponential Moving Average):**
* *Logic:* Calculated as $3 \times EMA - 3 \times EMA(EMA) + EMA(EMA(EMA))$. This effectively eliminates the lag inherent in single and double EMAs, making it an extremely fast-tracking indicator for scalping.
#### 3. Advanced & Adaptive Averages
* **HMA (Hull Moving Average):**
* *Logic:* A composite formula involving Weighted Moving Averages: ASX:WMA (2 \times Integer(n/2)) - WMA(n)$. The result is then smoothed by a $\sqrt{n}$ WMA.
* *Effect:* It eliminates lag almost entirely while managing to improve curve smoothness, solving the traditional trade-off between speed and noise.
* **ZLEMA (Zero Lag Exponential Moving Average):**
* *Logic:* This calculation attempts to remove lag by modifying the data source before smoothing. It calculates a "lag" value $(length-1)/2$ and applies an EMA to the data: $Source + (Source - Source )$. This creates a projection effect that tracks price tightly.
* **T3 (Tillson T3 Moving Average):**
* *Logic:* A complex smoothing technique that runs an EMA through a filter multiple times using a "Volume Factor" (set to 0.7 in this script).
* *Effect:* It produces a curve that is incredibly smooth and free of "overshoot," making it excellent for filtering out market chop.
* **ALMA (Arnaud Legoux Moving Average):**
* *Logic:* Uses a Gaussian distribution (bell curve) to assign weights. It allows the user to offset the moving average (moving the peak of the weight) to align it perfectly with the price, balancing smoothness and responsiveness.
* **LSMA (Least Squares Moving Average):**
* *Logic:* Calculates the endpoint of a Linear Regression line for the lookback period. It essentially guesses where the price "should" be based on the best-fit line of the recent trend.
* **VWMA (Volume Weighted Moving Average):**
* *Logic:* Weights the closing price by the volume of that bar.
* *Effect:* Prices on high volume days pull the MA harder than prices on low volume days. This is excellent for validating true trend strength (i.e., a breakout on high volume will move the VWMA significantly).
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### 🛠 Features & Settings
* **Universal Switching:** Change the `Fast MA` and `Slow MA` types instantly via the settings menu.
* **Trend Cloud:** A dynamic background fill (Green/Red) highlights the crossover zone for immediate visual trend identification.
* **Strategy Mode:** Built-in Backtesting logic triggers `LONG` entries when Fast MA crosses over Slow MA, and `EXIT` when Fast MA crosses under.
### ⚠️ Disclaimer
This script is intended for educational and research purposes. The wide variety of MA combinations can produce vastly different results. Past performance is not indicative of future results. Please use proper risk management.
EMAs Bullish/Bearish Confluence [Trend Bias]EMA Confluence Zones
This indicator is designed to simplify trend identification by visually highlighting "Confluence Zones" —areas where short-term, medium-term, and long-term momentum are fully aligned.
While traders can manually add three Moving Averages to a chart, identifying the exact moment all three align (the "Perfect Stack") can be visually difficult during live trading. This script automates that process, converting complex line crosses into simple background color zones and providing actionable alerts for the exact moment a trend alignment begins.
🛠 How It Works
The script utilizes three customizable Exponential Moving Averages (EMAs) to detect the market bias:
Short EMA: Represents immediate price action/momentum.
Medium EMA: Represents the intermediate trend.
Long EMA: Represents the major trend baseline.
Calculations & Logic
The indicator checks for a specific hierarchical alignment (Stacking) of these averages:
1. 🟢 Bullish Confluence (Buy Zone):** Returns true when `Short > Medium` AND `Medium >Long`. This confirms that momentum is rising across all three monitored timeframes.
2. 🔴 Bearish Confluence (Sell Zone):** Returns true when `Short < Medium` AND `Medium < Long`. This confirms that momentum is falling across all three monitored timeframes.
3. ⚪ Neutral (No Color): Any other state indicates a choppy or consolidating market where the EMAs are intertwined.
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🚀 Key Features
*Visual Bias Confirmation: The background highlights Green (Bullish) or Red (Bearish) only when the "Perfect Stack" conditions are met.
Trend Start Alerts: Unlike standard EMA cross alerts, this script includes custom alert conditions that trigger only on the first bar where the confluence becomes valid. This prevents spam alerts during a prolonged trend.
Full Customization: Users can adjust the lengths of all three EMAs to fit specific strategies (e.g., Scalping vs. Swing Trading).
Clean Chart Mode: Includes options to hide the EMA lines entirely and rely solely on the background color for a minimalist "Naked Trading" setup.
🎯 How to Use
1. Trend Filter: Use the background color to determine your directional bias. If the background is Green, look only for Long setups on lower timeframes. If Red, look only for Short setups.
2. Breakout Confirmation: If price breaks a key level, wait for the background color to flip. This confirms that the Moving Averages have caught up to the move, validating the breakout strength.
3. Exit Signal: If you are in a trend trade and the background color disappears (turns transparent), it indicates the trend momentum is fading and the EMAs are beginning to cross/compress.
⚙️ Settings
EMA Lengths: Default is 20, 50, 100. These can be changed to common combinations like (9, 21, 55) or (50, 100, 200).
Visuals: Toggle lines or background colors on/off and adjust transparency to keep your chart readable.
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Disclaimer: This script is for informational purposes only. Past performance of a trend following method does not guarantee future results. Always use proper risk management.
