Ultra Moving AverageThe Ultra Moving Average is a versatile technical indicator that combines various types of moving averages to analyze trends, providing multi-timeframe insights for traders. It offers four customizable moving averages and a trend strength table for enhanced decision-making.
Introduction
The Ultra Moving Average indicator is a powerful tool designed to help traders track market trends by offering a combination of four distinct moving averages. With flexible customization options, users can apply different types of moving averages like SMA, EMA, TEMA, and many more, across various timeframes. Additionally, it provides trend strength analysis through an intuitive visual table, helping traders quickly identify market conditions.
Detailed Description
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Moving Averages
Each of the four moving averages is independently configurable. You can select the timeframe, type, length, color, and width to match your trading strategy.
The types of moving averages range from traditional ones like the Simple Moving Average (SMA) to advanced ones like the Double Expotential Moving Average (DEMA) or the Triple Exponential Moving Average (TEMA) or the Recursive Moving Average (RMA) or the Weigthend Moving Average (WMA) or the Volume Weigthend Moving Average (VWMA) or Hull Moving Average (HMA).
Very Special ones are the Triple Weigthend Moving Average (TWMA) wich created RedKTrader .
I created the Multi Weigthend Moving Average (MWMA) wich is a simple signal line to the TWMA.
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Trend Visualization
The indicator uses color-coding to visually represent whether the price is in an uptrend or downtrend. Bullish trends are highlighted in one color, while bearish trends appear in another, making it easy to interpret.
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Trend Strength Table
One of the unique features of the Ultra Moving Average is the trend strength table at the bottom of the chart. This table breaks down the strength of the fast, mid, and slow moving averages, displaying them as percentages. It also shows the overall "trend power," which helps assess how strong or weak the current trend is.
You have the option to calculate trends using live data or the previous bar's data, offering flexibility in how the indicator reacts to market changes. This can help traders make more responsive decisions based on real-time trends.
The table displays trend strength across three timeframes Fast, Mid, and Slow by calculating the percentage difference between the price and each of the moving averages (MA1, MA3, MA4).
The Power row shows the average of these percentages, representing overall trend strength.
The percentages are calculated relative to their maximum values in history (limited by TradingView subscription), providing insight into the trend's strength for each timeframe.
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Overall, the Ultra Moving Average indicator is a comprehensive tool that combines multiple moving average types and advanced trend analysis, helping traders identify market direction and strength at a glance. With its intuitive visualization and flexible settings, it's suited for both beginner and experienced traders.
Special Thanks
I use the TWMA-Function created from RedKTrader to smooth the values.
Special thanks to him for creating and sharing this function!
Médias Móveis
Multiple Bollinger Bands + Volatility [AlgoTraderPro]This indicator helps traders visualize price ranges and volatility changes. Designed to assist in identifying potential consolidation zones, the indicator uses multiple layers of Bollinger Bands combined with volatility-based shading. This can help traders spot periods of reduced price movement, which are often followed by breakouts or trend reversals.
█ FEATURES
Multiple Bollinger Bands: Displays up to seven bands with customizable standard deviations, providing a layered view of price range activity.
Volatility Measurement: Tracks changes in Bollinger Band width to display volatility percentage and direction (increasing, decreasing, or neutral).
Volatility Shading: Uses color-coded shading between the outermost bands to indicate changes in volatility, helping to visualize potential consolidation zones.
Customizable Inputs: Modify lookback periods, moving average lengths, and standard deviations for each band to tailor the analysis to your strategy.
Volatility Table: Displays a table on the chart showing real-time volatility data and direction for quick reference.
█ HOW TO USE
Add the Indicator: Apply it to your TradingView chart.
Adjust Settings: Customize the Bollinger Bands’ parameters to suit your trading timeframe and strategy.
Analyze Consolidation Zones: Use the multiple bands and volatility shading to identify areas of reduced price activity, signaling potential breakouts.
Monitor Volatility: Refer to the volatility table to track real-time shifts in market volatility.
Use in Different Markets: Adapt the settings for various assets and timeframes to assess market conditions effectively.
█ NOTES
• The indicator is useful in consolidating markets where price movement is limited, offering insights into potential breakout areas.
• Adjust the settings based on asset and market conditions for optimal results.
Varanormal Mac N Cheez Strategy v1Mac N Cheez Strategy (Set a $200 Take profit Manually)
It's super cheesy. Strategy does the following:
Here's a detailed explanation of what the entire script does, including its key components, functionality, and purpose.
1. Strategy Setup and Input Parameters:
Strategy Name: The script is named "NQ Futures $200/day Strategy" and is set as an overlay, meaning all elements (like moving averages and signals) are plotted on the price chart.
Input Parameters:
fastLength: This sets the length of the fast moving average. The user can adjust this value, and it defaults to 9.
slowLength: This sets the length of the slow moving average. The user can adjust this value, and it defaults to 21.
dailyTarget: The daily profit target, which defaults to $200. If set to 0, this disables the daily profit target.
stopLossAmount: The fixed stop-loss amount per trade, defaulting to $100. This value is used to calculate how much you're willing to lose on a single trade.
trailOffset: This value sets the distance for a trailing stop. It helps protect profits by automatically adjusting the stop-loss as the price moves in your favor.
2. Calculating the Moving Averages:
fastMA: The fast moving average is calculated using the ta.sma() function on the close price with a period length of fastLength. The ta.sma() function calculates the simple moving average.
slowMA: The slow moving average is also calculated using ta.sma() but with the slowLength period.
These moving averages are used to determine trend direction and identify entry points.
3. Buy and Sell Signal Conditions:
longCondition: This is the buy condition. It occurs when the fast moving average crosses above the slow moving average. The script uses ta.crossover() to detect this crossover event.
shortCondition: This is the sell condition. It occurs when the fast moving average crosses below the slow moving average. The script uses ta.crossunder() to detect this crossunder event.
4. Executing Buy and Sell Orders:
Buy Orders: When the longCondition is true (i.e., fast MA crosses above slow MA), the script enters a long position using strategy.entry("Buy", strategy.long).
Sell Orders: When the shortCondition is true (i.e., fast MA crosses below slow MA), the script enters a short position using strategy.entry("Sell", strategy.short).
5. Setting Stop Loss and Trailing Stop:
Stop-Loss for Long Positions: The stop-loss is calculated as the entry price minus the stopLossAmount. If the price falls below this level, the trade is exited automatically.
Stop-Loss for Short Positions: The stop-loss is calculated as the entry price plus the stopLossAmount. If the price rises above this level, the short trade is exited.
Trailing Stop: The trail_offset dynamically adjusts the stop-loss as the price moves in favor of the trade, locking in profits while still allowing room for market fluctuations.
6. Conditional Daily Profit Target:
The script includes a daily profit target that automatically closes all trades once the total profit for the day reaches or exceeds the dailyTarget.
Conditional Logic:
If the dailyTarget is greater than 0, the strategy checks whether the strategy.netprofit (total profit for the day) has reached or exceeded the target.
If the strategy.netprofit >= dailyTarget, the script calls strategy.close_all(), closing all open trades for the day and stopping further trading.
If dailyTarget is set to 0, this logic is skipped, and the script continues trading without a daily profit target.
7. Plotting Moving Averages:
plot(fastMA): This plots the fast moving average as a blue line on the price chart.
plot(slowMA): This plots the slow moving average as a red line on the price chart. These help visualize the crossover points and the trend direction on the chart.
8. Plotting Buy and Sell Signals:
plotshape(): The script uses plotshape() to add visual markers when buy or sell conditions are met:
"Long Signal": When a buy condition (longCondition) is met, a green marker is plotted below the price bar with the label "Long".
"Short Signal": When a sell condition (shortCondition) is met, a red marker is plotted above the price bar with the label "Short".
These markers help traders quickly see when buy or sell signals occurred on the chart.
In addition, triangle markers are plotted:
Green Triangle: Indicates where a buy entry occurred.
Red Triangle: Indicates where a sell entry occurred.
Summary of What the Script Does:
Inputs: The script allows the user to adjust moving average lengths, daily profit targets, stop-loss amounts, and trailing stop offsets.
Signals: It generates buy and sell signals based on the crossovers of the fast and slow moving averages.
Order Execution: It executes long positions on buy signals and short positions on sell signals.
Stop-Loss and Trailing Stop: It sets dynamic stop-losses and uses a trailing stop to protect profits.
Daily Profit Target: The strategy stops trading for the day once the net profit reaches the daily target (unless the target is disabled by setting it to 0).
Visual Markers: It plots moving averages and buy/sell signals directly on the main price chart to aid in visual analysis.
This script is designed to trade based on moving average crossovers, with robust risk management features like stop-loss and trailing stops, along with an optional daily profit target to limit daily trading activity. Let me know if you need further clarification or want to adjust any specific part of the script!
Bull Bear Power With EMA FilterDescription of Indicator:
This Pine Script indicator colors price bars based on the open price in relation to custom moving averages (EMA/SMA), Bull/Bear Power (BBPower), and an optional VWAP filter. The bar colors help identify bullish and bearish conditions with added visual cues for price positioning relative to VWAP.
Key Features:
Customizable Moving Averages (EMA/SMA):
The user can select between EMA or SMA for both short-term and long-term moving averages.
Default moving averages are set to 5 (short-term) and 9 (long-term) but can be adjusted by the user.
Bullish Condition (Blue or Purple Bars):
A bar is colored blue if the following conditions are met:
The open price is above both the short-term and long-term moving averages.
The short-term moving average (MA 1) is above the long-term moving average (MA 2).
BBPower (open price minus the 13-period EMA) is positive, indicating bullish strength.
If the VWAP filter is enabled and the price opens below VWAP, the bullish bars will turn purple.
Bearish Condition (Yellow or Orange Bars):
A bar is colored yellow if the following conditions are met:
The open price is below both the short-term and long-term moving averages.
The short-term moving average (MA 1) is below the long-term moving average (MA 2).
BBPower is negative or zero, indicating bearish market conditions.
If the VWAP filter is enabled and the price opens above VWAP, the bearish bars will turn orange.
VWAP Filter (Optional):
An optional filter allows the user to add VWAP (Volume-Weighted Average Price) to the bar coloring logic.
When the VWAP filter is enabled, it provides additional information about price positioning relative to VWAP, turning bullish bars purple and bearish bars orange depending on whether the price opens above or below VWAP.
Usage:
Bullish Trend: Look for blue or purple bars to identify potential bullish momentum.
Bearish Trend: Look for yellow or orange bars to spot bearish conditions in the market.
The indicator allows users to customize the length and type of moving averages (EMA or SMA), as well as decide whether to apply the VWAP filter.
This indicator provides traders with clear visual signals to quickly assess the strength of bullish or bearish conditions based on the price's position relative to custom moving averages, BBPower, and VWAP, helping with trend identification and potential trade setups.
Hull MA with Alerts and LabelsThis script is designed to help traders visually track market trends using various types of moving averages (MAs) and to receive alerts when certain conditions are met. Here’s a detailed breakdown of how the script works:
1. User Inputs and Customization:
MA Length: Traders can define the length of the moving average (default is 100).
Confirmation Candles: The trader can specify how many candles must confirm a trend before the script triggers a signal (default is 1).
MA Variation: The trader can choose between different moving average types: Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), or Hull Moving Average (HMA).
Source: Traders select the price source for the moving average calculation (e.g., close price).
Ribbon Transparency: Allows control over the transparency level of the ribbon plotted between the moving averages.
Bullish/Bearish Ribbon Colors: The user can choose the colors for bullish and bearish trends.
2. Moving Average Calculations:
The script provides multiple options for calculating moving averages:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
For the Hull Moving Average (HMA), it uses a specific formula that smoothens the movement and reduces lag, which is helpful for more reactive trend detection.
3. Plotting Moving Averages and Trend Ribbon:
The script calculates two key moving averages:
MHULL: The main moving average, selected based on the user’s chosen MA variation and source.
SHULL: A shifted version of the MHULL to help compare trends (shifted by 2 bars).
These two moving averages are plotted on the chart for visualization. MHULL is plotted in green (or another color if changed), while SHULL is plotted in red. A ribbon is drawn between MHULL and SHULL to indicate trends visually. The ribbon changes color depending on whether the trend is bullish (MHULL > SHULL) or bearish (MHULL < SHULL). The ribbon’s transparency can be adjusted for visual clarity.
4. Trend Detection:
Bullish Trend: The script checks if the price has closed above MHULL for the defined number of confirmation candles. If confirmed, a bullish trend is detected.
Bearish Trend: Similarly, the script checks if the price has closed below SHULL for the confirmation period, indicating a bearish trend.
The script tracks whether the market is in a bullish or bearish trend and prevents repeated signals by remembering the current trend state.
5. Alerts and Labels:
Bullish Alerts and Labels: When a confirmed bullish trend is detected (i.e., price closes above MHULL for the entire confirmation period and MHULL > SHULL), the script triggers an alert notifying the trader of the bullish condition. A "BULLISH" label is placed on the chart near the low of the candle where the trend was confirmed.
Bearish Alerts and Labels: If a confirmed bearish trend is detected (i.e., price closes below SHULL for the confirmation period and MHULL < SHULL), the script triggers an alert for the bearish condition. A "BEARISH" label is placed on the chart near the high of the candle where the trend was confirmed.
These alerts and labels help traders act quickly on trend changes and align their trading strategy with market conditions.
6. Practical Use for Traders:
For traders, this script offers:
Customizability : It allows traders to define the length and type of moving averages, choose price sources, and control how signals are confirmed.
Visual Trend Representation : The plotted MA lines and colored ribbons help traders easily see market direction.
Early Warnings : With alerts and labels, the script gives traders early signals when trends are shifting, allowing them to adjust positions accordingly.
Trend Confirmation : The script waits for a user-defined number of confirmation candles before signaling a new trend, reducing false signals.
Overall, the script helps traders automate their strategy by tracking moving averages and alerting them when key trend conditions are met.
Pink's Daily SMA Script🚗 This script provides a customizable overlay of seven simple moving averages (SMAs) on the chart. Users can control the display of each SMA by toggling them on or off. The lengths of these SMAs are adjustable, allowing for tailored analysis based on individual preferences.
📊 The script calculates daily SMA values using the request.security() function and plots them as horizontal lines on the chart. These SMAs are updated once per day, typically at the start of the pre-market session (9:00 AM in the "America/New_York" timezone). The script resets the SMA values at the start of each new day, ensuring fresh data for daily analysis.
🕒 In addition to the SMAs, the script includes an optional feature that highlights specific time ranges on the chart: from 11:00 AM to 11:05 AM and from 1:00 PM to 1:30 PM (based on the "America/New_York" timezone). Users can toggle these background highlights on or off, providing visual cues for key times during the trading day. The 11:00 AM window is highlighted in gray, while the 1:00 PM window is highlighted in blue.
🔖 The SMAs are labeled on the right side of the chart, with only one label visible at a time for each SMA. These labels display the length of the respective SMA, and their colors match the lines drawn on the chart, helping to distinguish between the different SMAs.
Special thanks to Pinks333 (www.tradingview.com)
Who provided the logic for the script and was willing to share her logic and open source the script.
Dynamic ConfluenceThe Dynamic MA Confluence Indicator is a powerful tool designed to simplify your trading experience by automatically identifying the most influential moving average (MA) lengths on your chart. Whether you're using Simple Moving Averages (SMA) or Exponential Moving Averages (EMA), this indicator helps you pinpoint the MA length that holds the greatest confluence, allowing you to make informed trading decisions with ease.
How It Works:
This indicator analyzes a wide range of moving averages, from short-term to long-term, to determine which ones are closest to each other. By setting a "Proximity Percentage," you can control how close these MAs need to be to be considered as having confluence. The indicator then calculates the average of these close MAs to establish a dynamic support or resistance level on your chart.
Why Use This Indicator?
Automatic Optimization: Unsure of which MA length to apply? The indicator automatically highlights the MA length with the most confluence, giving you a clear edge in identifying significant market levels.
Adaptability: Choose between SMA and EMA to suit your trading strategy and market conditions.
Enhanced Decision-Making: By focusing on the MA length with the greatest influence, you can better anticipate market movements and adjust your strategies accordingly.
Customizable Sensitivity: Adjust the Proximity Percentage to fine-tune the indicator's sensitivity, ensuring it aligns with your trading preferences.
Key Feature:
Current Key Confluence MA Length: Displayed in an optional table, this feature shows the MA length that currently has the most impact on the confluence level, providing you with actionable insights at a glance.
Whether you're a seasoned trader or just starting, the Dynamic MA Confluence Indicator offers a streamlined approach to understanding market dynamics, helping you trade smarter and with more confidence. This presentation text is designed to clearly communicate the purpose, functionality, and benefits of the indicator, making it easy for users to understand its value and how it can enhance their trading strategies.
The Dynamic MA Confluence Indicator is a tool designed to assist traders in analyzing market trends. It should not be considered as financial advice or a guarantee of future performance. Trading involves significant risk, and it is possible to lose more than your initial investment. Users should conduct their own research and consider their financial situation before making trading decisions. Always consult with a financial advisor if you are unsure about any trading strategies or decisions. This disclaimer is intended to remind users of the inherent risks in trading and the importance of conducting their own due diligence.
Stochastic RSI Strategy with Inverted Trend LogicOverview:
The Stochastic RSI Strategy with Inverted Trend Logic is a custom-built Pine Script indicator that leverages the Stochastic RSI and a 200-period moving average to generate precise buy and sell signals. It is specifically designed for traders looking to capture opportunities during short-term market movements while factoring in broader trend conditions.
Key Components:
Stochastic RSI:
Stochastic RSI is a momentum indicator that applies stochastic calculations to the standard Relative Strength Index (RSI), rather than price data. This makes it particularly sensitive to market momentum changes, which is essential for timing entries and exits.
K Line and D Line: The indicator calculates and smooths both the K and D lines to capture momentum shifts more accurately.
200-Period Moving Average:
The 200-period Simple Moving Average (SMA) is used as a trend filter.
If the price is above the 200-period SMA, the trend is considered bullish.
If the price is below the 200-period SMA, the trend is considered bearish.
Inverted Trading Logic:
The trading logic is inverted from traditional strategies:
Long trades are executed only when the market is in a bearish trend (price below the 200-period moving average).
Short trades are executed only when the market is in a bullish trend (price above the 200-period moving average).
This inversion allows traders to take advantage of potential trend reversals by entering positions in the opposite direction of the prevailing trend.
Trading Rules:
Long Trade Conditions (Buy Signal):
The Stochastic RSI K line must be below 5 for 4 consecutive candles (oversold condition).
The price must be below the 200-period SMA (indicating a bearish trend).
Once these conditions are met, the indicator will generate a buy signal on the close of the 4th candle.
Exit Condition: The long position is exited when the Stochastic RSI K line crosses above 50 (neutral level).
Short Trade Conditions (Sell Signal):
The Stochastic RSI K line must be above 95 for 4 consecutive candles (overbought condition).
The price must be above the 200-period SMA (indicating a bullish trend).
Once these conditions are met, the indicator will generate a sell signal on the close of the 4th candle.
Exit Condition: The short position is exited when the Stochastic RSI K line crosses below 50.
Visual Signals on the Chart:
Buy Signal:
A green triangle below the bar is displayed on the chart when a buy condition is met, indicating a potential long trade opportunity.
The text "BUY" is displayed for further clarity.
Sell Signal:
A red triangle above the bar is displayed on the chart when a sell condition is met, indicating a potential short trade opportunity.
The text "SELL" is displayed for further clarity.
How to Use the Indicator:
Attach the Indicator: Apply the indicator to your desired chart (works on any time frame, but is optimized for short- to medium-term trading).
Monitor Signals: Watch for buy and sell signals on the chart:
Buy Signal: Enter long positions when a green triangle appears below the candle.
Sell Signal: Enter short positions when a red triangle appears above the candle.
Exit Positions: Exit long positions when the Stochastic RSI crosses above the 50 level, and exit short positions when the Stochastic RSI crosses below the 50 level.
Indicator Display:
Stochastic RSI: A visual representation of the Stochastic RSI (K and D lines) is plotted below the price chart, with overbought (100), midpoint (50), and oversold (0) levels clearly marked.
200-period SMA: The 200-period moving average is plotted on the price chart, giving a clear indication of the broader trend direction (orange line).
Key Benefits:
Reversal Opportunities: This strategy allows traders to capture reversal trades by using an inverted logic where longs are taken in bearish conditions and shorts are taken in bullish conditions. This can help capitalize on potential trend exhaustion and reversals.
Clear and Simple Rules: The use of Stochastic RSI and the 200-period moving average ensures the strategy remains simple yet effective, making it easy for traders to follow.
Visual Alerts: The indicator provides clear buy and sell signals, making it easy for traders to spot trading opportunities in real-time without needing to monitor multiple conditions manually.
Limitations and Considerations:
Trend Changes: Since the strategy is designed to work during trend reversals, it might not perform as well during strong, prolonged trends where price continues moving in one direction without significant pullbacks.
Time Frame Suitability: While the indicator works on any time frame, shorter time frames may result in more frequent signals and higher trade frequency, whereas higher time frames will provide fewer but potentially stronger signals.
Conclusion:
The Stochastic RSI Strategy with Inverted Trend Logic is a powerful tool for traders looking to capture market reversals by entering trades against the prevailing trend direction based on momentum exhaustion. Its simple and clear logic, combined with easy-to-understand visual signals, makes it a versatile indicator for both novice and experienced traders.
Pseudo-Renko Stabilized (Val)█ CALCULATE PSEUDO-RENKO VALUE
Calculates and returns the Pseudo-Renko Stabilized value (or close price) based on a given input value, along with the direction of the current Renko brick. This function adapts the traditional Renko brick size dynamically based on the volatility of the input value using a combination of SMA and EMA calculations. The calculated price represents the closing price of the most recent Pseudo-Renko brick, while the direction indicates the trend ( 1 for uptrend, -1 for downtrend).
Parameters:
* `val` :
* Type: ` float `
* Description: The input value upon which the Pseudo-Renko calculations are performed. You can use any price series or custom value as input.
* `sensitivity` :
* Type: ` float `
* Default Value: ` 1.0 `
* Description: Controls the sensitivity of the brick size to the volatility of the `val`. Higher values lead to larger bricks, resulting in a smoother Renko chart. Lower values produce smaller bricks, leading to a more reactive chart.
* Possible Values: Any positive float.
* `length` :
* Type: ` int `
* Default Value: ` 7 `
* Description: The length used for calculating the EMA and SMA in the dynamic brick size calculation. It influences how quickly the brick size adapts to changing volatility of the `val`.
* Possible Values: Any positive integer.
Return Values:
* `lastRenkoClose` :
* Type: ` float `
* Description: The closing price of the last completed Pseudo-Renko brick based on the `val`.
* `renkoDirection` :
* Type: ` int `
* Description: The direction of the current Pseudo-Renko brick based on the `val`:
* ` 1 `: Uptrend
* ` -1 `: Downtrend
* ` 0 `: No change (initially, or no brick change since the previous bar)
Example Usage:
//@version=5
indicator("Pseudo-Renko Stabilized (Val)", overlay=true)
// Get user inputs
sensitivityInput = input.float(0.1, "Sensitivity",0.01,step=0.01)
lengthInput = input.int(5, "Length",2)
// Example usage with the 'close' price as the input value
= pseudo_renko(math.avg(close,open), sensitivityInput, lengthInput)
// Plot the Renko close price
plot(renkoClose, "Renko Close", renkoDirection>0?color.aqua:color.orange,2)
// You can also use other values as input, such as:
// = pseudo_renko(high, sensitivityInput, lengthInput)
// = pseudo_renko(low, sensitivityInput, lengthInput)
This example demonstrates how to use the `pseudo_renko` function within an indicator. It takes user inputs for `sensitivity` and `length`, then calculates the Pseudo-Renko values using the average of the `close` and `open` prices as the `val`. The resulting `renkoClose` price is plotted on the chart, with a color change based on the `renkoDirection`. It also illustrates how you can use other values, like `high` and `low`, as input to the function.
Note: The Pseudo-Renko algorithm is based on adapting the Renko brick size dynamically based on the input `val`. This provides more flexibility compared to the normal, but is experimental. The `sensitivity` and `length` parameters, along with the choice of the `val`, offer further customization to tune the algorithm's behavior to your preference and trading style.
Dema EFI Volume | viResearchDema EFI Volume | viResearch
Conceptual Foundation and Innovation
The "Dema EFI Volume" indicator from viResearch integrates the Double Exponential Moving Average (DEMA) with the Elder Force Index (EFI), providing a dynamic approach to analyzing both price trends and volume strength. The DEMA is applied to smooth out price fluctuations while minimizing lag, which enhances the ability to detect trend direction. The EFI, developed by Dr. Alexander Elder, measures the power behind price movements by incorporating both price change and volume. This indicator, when combined with DEMA smoothing, gives traders a more accurate understanding of whether the current price movements are supported by significant volume, helping them make more informed trading decisions. The combination of DEMA and EFI allows traders to track trend strength while assessing the market’s volume dynamics, offering a more reliable method for identifying potential trend continuations or reversals.
Technical Composition and Calculation
The "Dema EFI Volume" script consists of two key components: the Double Exponential Moving Average (DEMA) and the Elder Force Index (EFI). The DEMA is applied to the selected source price over a user-defined length, providing a smoothed representation of price movements while reducing the noise that can occur with traditional moving averages. The EFI is calculated by multiplying the change in the DEMA by the volume over a user-defined period, which indicates whether the price movement is being driven by strong or weak volume. The script monitors the EFI values and volume data to generate trend signals. If the EFI is positive and volume increases, this indicates bullish pressure, while a negative EFI with decreasing volume suggests bearish conditions. The combination of these signals helps traders determine whether a price move is backed by sufficient volume, making it easier to identify trend continuations or potential reversals.
Features and User Inputs
The "Dema EFI Volume" script offers several customizable inputs, allowing traders to adapt the indicator to their specific strategies. The DEMA Length controls the smoothing applied to the price data, while the EFI Length defines the period over which the force index is calculated. Additionally, traders can set alert conditions for when a bullish or bearish EFI signal occurs, enabling them to react quickly to changing market conditions.
Practical Applications
The "Dema EFI Volume" indicator is designed for traders who want to combine price trend analysis with volume dynamics in a single tool. This makes it particularly effective for identifying trend continuations, as rising volume alongside a positive EFI suggests that the market move is supported by strong momentum. Conversely, decreasing volume and a negative EFI may indicate a weakening trend, giving traders early warning of potential reversals. The combination of DEMA and EFI also makes this indicator valuable for detecting trend strength by measuring whether price movements are backed by strong volume, confirming trend reversals by comparing price changes with volume activity, and improving trade entries and exits by analyzing both price and volume for more robust signals.
Advantages and Strategic Value
The "Dema EFI Volume" script offers significant advantages by combining the DEMA’s smoothing power with the EFI’s volume analysis. This integration allows traders to filter out noise in price data while ensuring that trend signals are backed by meaningful volume. The result is a more reliable tool for trend-following and reversal detection, making it easier for traders to stay aligned with strong market moves while avoiding false signals caused by low-volume fluctuations. The dual focus on price and volume makes the "Dema EFI Volume" an ideal tool for traders who value a comprehensive approach to market analysis.
Alerts and Visual Cues
The script includes alert conditions that notify traders when a significant EFI signal occurs. The "EFI Volume Long" alert is triggered when the EFI is positive and volume increases, indicating a potential upward trend. The "EFI Volume Short" alert signals a possible downward trend when the EFI turns negative and volume decreases. Visual cues, such as the color and direction of the plotted EFI line, help traders quickly identify trend shifts and make timely decisions.
Summary and Usage Tips
The "Dema EFI Volume | viResearch" indicator provides traders with a powerful tool for analyzing both price trends and volume strength. By incorporating this script into your trading strategy, you can improve your ability to detect trend continuations and reversals, making more informed decisions based on a combination of price movement and volume dynamics. Whether you are focused on identifying trend strength or looking for early reversal signals, the "Dema EFI Volume" offers a reliable and customizable solution for traders of all levels.
Note: Backtests are based on past results and are not indicative of future performance.
Sinc Bollinger BandsKaiser Windowed Sinc Bollinger Bands Indicator
The Kaiser Windowed Sinc Bollinger Bands indicator combines the advanced filtering capabilities of the Kaiser Windowed Sinc Moving Average with the volatility measurement of Bollinger Bands. This indicator represents a sophisticated approach to trend identification and volatility analysis in financial markets.
Core Components
At the heart of this indicator is the Kaiser Windowed Sinc Moving Average, which utilizes the sinc function as an ideal low-pass filter, windowed by the Kaiser function. This combination allows for precise control over the frequency response of the moving average, effectively separating trend from noise in price data.
The sinc function, representing an ideal low-pass filter, provides the foundation for the moving average calculation. By using the sinc function, analysts can independently control two critical parameters: the cutoff frequency and the number of samples used. The cutoff frequency determines which price movements are considered significant (low frequency) and which are treated as noise (high frequency). The number of samples influences the filter's accuracy and steepness, allowing for a more precise approximation of the ideal low-pass filter without altering its fundamental frequency response characteristics.
The Kaiser window is applied to the sinc function to create a practical, finite-length filter while minimizing unwanted oscillations in the frequency domain. The alpha parameter of the Kaiser window allows users to fine-tune the trade-off between the main-lobe width and side-lobe levels in the frequency response.
Bollinger Bands Implementation
Building upon the Kaiser Windowed Sinc Moving Average, this indicator adds Bollinger Bands to provide a measure of price volatility. The bands are calculated by adding and subtracting a multiple of the standard deviation from the moving average.
Advanced Centered Standard Deviation Calculation
A unique feature of this indicator is its specialized standard deviation calculation for the centered mode. This method employs the Kaiser window to create a smooth deviation that serves as an highly effective envelope, even though it's always based on past data.
The centered standard deviation calculation works as follows:
It determines the effective sample size of the Kaiser window.
The window size is then adjusted to reflect the target sample size.
The source data is offset in the calculation to allow for proper centering.
This approach results in a highly accurate and smooth volatility estimation. The centered standard deviation provides a more refined and responsive measure of price volatility compared to traditional methods, particularly useful for historical analysis and backtesting.
Operational Modes
The indicator offers two operational modes:
Non-Centered (Real-time) Mode: Uses half of the windowed sinc function and a traditional standard deviation calculation. This mode is suitable for real-time analysis and current market conditions.
Centered Mode: Utilizes the full windowed sinc function and the specialized Kaiser window-based standard deviation calculation. While this mode introduces a delay, it offers the most accurate trend and volatility identification for historical analysis.
Customizable Parameters
The Kaiser Windowed Sinc Bollinger Bands indicator provides several key parameters for customization:
Cutoff: Controls the filter's cutoff frequency, determining the divide between trends and noise.
Number of Samples: Sets the number of samples used in the FIR filter calculation, affecting the filter's accuracy and computational complexity.
Alpha: Influences the shape of the Kaiser window, allowing for fine-tuning of the filter's frequency response characteristics.
Standard Deviation Length: Determines the period over which volatility is calculated.
Multiplier: Sets the number of standard deviations used for the Bollinger Bands.
Centered Alpha: Specific to the centered mode, this parameter affects the Kaiser window used in the specialized standard deviation calculation.
Visualization Features
To enhance the analytical value of the indicator, several visualization options are included:
Gradient Coloring: Offers a range of color schemes to represent trend direction and strength for the moving average line.
Glow Effect: An optional visual enhancement for improved line visibility.
Background Fill: Highlights the area between the Bollinger Bands, aiding in volatility visualization.
Applications in Technical Analysis
The Kaiser Windowed Sinc Bollinger Bands indicator is particularly useful for:
Precise trend identification with reduced noise influence
Advanced volatility analysis, especially in the centered mode
Identifying potential overbought and oversold conditions
Recognizing periods of price consolidation and potential breakouts
Compared to traditional Bollinger Bands, this indicator offers superior frequency response characteristics in its moving average and a more refined volatility measurement, especially in centered mode. These features allow for a more nuanced analysis of price trends and volatility patterns across various market conditions and timeframes.
Conclusion
The Kaiser Windowed Sinc Bollinger Bands indicator represents a significant advancement in technical analysis tools. By combining the ideal low-pass filter characteristics of the sinc function, the practical benefits of Kaiser windowing, and an innovative approach to volatility measurement, this indicator provides traders and analysts with a sophisticated instrument for examining price trends and market volatility.
Its implementation in Pine Script contributes to the TradingView community by making advanced signal processing and statistical techniques accessible for experimentation and further development in technical analysis. This indicator serves not only as a practical tool for market analysis but also as an educational resource for those interested in the intersection of signal processing, statistics, and financial markets.
Related:
Sinc MAKaiser Windowed Sinc Moving Average Indicator
The Kaiser Windowed Sinc Moving Average is an advanced technical indicator that combines the sinc function with the Kaiser window to create a highly customizable finite impulse response (FIR) filter for financial time series analysis.
Sinc Function: The Ideal Low-Pass Filter
At the core of this indicator is the sinc function, which represents the impulse response of an ideal low-pass filter. In signal processing and technical analysis, the sinc function is crucial because it allows for the creation of filters with precise frequency cutoff characteristics. When applied to financial data, this means the ability to separate long-term trends from short-term fluctuations with remarkable accuracy.
The primary advantage of using a sinc-based filter is the independent control over two critical parameters: the cutoff frequency and the number of samples used. The cutoff frequency, analogous to the "length" in traditional moving averages, determines which price movements are considered significant (low frequency) and which are treated as noise (high frequency). By adjusting the cutoff, analysts can fine-tune the filter to respond to specific market cycles or timeframes of interest.
The number of samples used in the filter doesn't affect the cutoff frequency but instead influences the filter's accuracy and steepness. Increasing the sample size results in a better approximation of the ideal low-pass filter, leading to sharper transitions between passed and attenuated frequencies. This allows for more precise trend identification and noise reduction without changing the fundamental frequency response characteristics.
Kaiser Window: Optimizing the Sinc Filter
While the sinc function provides excellent frequency domain characteristics, it has infinite length in the time domain, which is impractical for real-world applications. This is where the Kaiser window comes into play. By applying the Kaiser window to the sinc function, we create a finite-length filter that approximates the ideal response while minimizing unwanted oscillations (known as the Gibbs phenomenon) in the frequency domain.
The Kaiser window introduces an additional parameter, alpha, which controls the trade-off between the main-lobe width and side-lobe levels in the frequency response. This parameter allows users to fine-tune the filter's behavior, balancing between sharp cutoffs and minimal ripple effects.
Customizable Parameters
The Kaiser Windowed Sinc Moving Average offers several key parameters for customization:
Cutoff: Controls the filter's cutoff frequency, determining the divide between trends and noise.
Length: Sets the number of samples used in the FIR filter calculation, affecting the filter's accuracy and computational complexity.
Alpha: Influences the shape of the Kaiser window, allowing for fine-tuning of the filter's frequency response characteristics.
Centered and Non-Centered Modes
The indicator provides two operational modes:
Non-Centered (Real-time) Mode: Uses half of the windowed sinc function, suitable for real-time analysis and current market conditions.
Centered Mode: Utilizes the full windowed sinc function, resulting in a zero-phase filter. This mode introduces a delay but offers the most accurate trend identification for historical analysis.
Visualization Features
To enhance the analytical value of the indicator, several visualization options are included:
Gradient Coloring: Offers a range of color schemes to represent trend direction and strength.
Glow Effect: An optional visual enhancement for improved line visibility.
Background Fill: Highlights the area between the moving average and price, aiding in trend visualization.
Applications in Technical Analysis
The Kaiser Windowed Sinc Moving Average is particularly useful for precise trend identification, cycle analysis, and noise reduction in financial time series. Its ability to create custom low-pass filters with independent control over cutoff and filter accuracy makes it a powerful tool for analyzing various market conditions and timeframes.
Compared to traditional moving averages, this indicator offers superior frequency response characteristics and reduced lag in trend identification when properly tuned. It provides greater flexibility in filter design, allowing analysts to create moving averages tailored to specific trading strategies or market behaviors.
Conclusion
The Kaiser Windowed Sinc Moving Average represents an advanced approach to price smoothing and trend identification in technical analysis. By making the ideal low-pass filter characteristics of the sinc function practically applicable through Kaiser windowing, this indicator provides traders and analysts with a sophisticated tool for examining price trends and cycles.
Its implementation in Pine Script contributes to the TradingView community by making advanced signal processing techniques accessible for experimentation and further development in technical analysis. This indicator serves not only as a practical tool for market analysis but also as an educational resource for those interested in the intersection of signal processing and financial markets.
Related script:
Sma Standard Deviation | viResearchSma Standard Deviation | viResearch
Conceptual Foundation and Innovation
The "Sma Standard Deviation" indicator from viResearch combines the benefits of Simple Moving Average (SMA) smoothing with Standard Deviation (SD) analysis, offering traders a powerful tool for understanding price trends and volatility. The SMA provides a straightforward approach to trend detection by calculating the average price over a defined period, while the SD component adds insight into the market's volatility by measuring the variation of prices around the SMA. This combination helps traders identify whether the price is moving within a typical range or deviating significantly, which can signal potential trend shifts or periods of increased volatility. By using both SMA and SD together, this indicator enhances the trader's ability to detect not only the trend direction but also how strongly the market is deviating from that trend, offering more informed decision-making.
Technical Composition and Calculation
The "Sma Standard Deviation" script uses two key elements: the Simple Moving Average (SMA) and Standard Deviation (SD). The SMA is calculated over a user-defined length and represents the smoothed average price over this period. The script also incorporates DEMA smoothing applied to different price sources, providing further refinement to the trend analysis. The SD is calculated by measuring the deviation of the price from the SMA over a separate user-defined length, showing how volatile the price is relative to its average. The script generates upper and lower SD boundaries by adding and subtracting the SD from the SMA, creating a volatility-adjusted range for the price. This allows traders to visualize whether the price is moving within expected bounds or breaking out of its typical range. The script monitors crossovers between the DEMA, SMA, and SD boundaries, generating trend signals based on these interactions.
Features and User Inputs
The "Sma Standard Deviation" script offers several customizable inputs, allowing traders to adjust the indicator to their specific strategies. The SMA Length controls the period for which the moving average is calculated, while the SD Length defines how long the period is for measuring price deviation. Additionally, the DEMA smoothing length can be adjusted for both the trend and standard deviation calculations, giving traders control over how responsive or smooth they want the indicator to be. The script also includes alert conditions that notify traders when trend shifts occur, either to the upside or downside.
Practical Applications
The "Sma Standard Deviation" indicator is designed for traders who want to analyze both market trends and volatility in a unified tool. The combination of the SMA and SD helps traders identify potential trend reversals, as large deviations from the SMA can indicate periods of increased volatility that precede significant price moves. This makes the indicator particularly effective for identifying trend reversals, managing volatility, and improving trend-following strategies. By analyzing when the price moves outside the volatility-adjusted range defined by the SD, traders can detect early signals of potential trend reversals. The SD component helps traders understand how volatile the market is relative to its average price, allowing for more informed decisions in both trending and volatile market conditions. The dual use of DEMA and SMA smoothing allows for a clearer trend signal, helping traders stay aligned with the prevailing market direction while managing the noise caused by short-term volatility.
Advantages and Strategic Value
The "Sma Standard Deviation" script offers significant value by integrating both trend detection and volatility analysis into a single tool. The use of SMA for smoothing price trends, combined with the SD for assessing price volatility, provides a more comprehensive view of the market. This dual approach helps traders filter out false signals caused by short-term fluctuations while identifying potential trend changes driven by increased volatility. This makes the "Sma Standard Deviation" indicator ideal for traders seeking a balance between trend-following and volatility management.
Alerts and Visual Cues
The script includes alert conditions that notify traders when significant trend shifts occur based on price crossovers with the SMA and SD boundaries. The "Sma Standard Deviation Long" alert is triggered when the price crosses above the upper volatility boundary, indicating a potential upward trend. Conversely, the "Sma Standard Deviation Short" alert signals a possible downward trend when the price crosses below the lower boundary. Visual cues, such as changes in the color of the SMA line, help traders quickly identify trend shifts and act accordingly.
Summary and Usage Tips
The "Sma Standard Deviation | viResearch" indicator provides traders with a robust tool for analyzing market trends and volatility. By combining the benefits of SMA smoothing with SD analysis, this script offers a comprehensive approach to detecting trend changes and managing risk. Incorporating this indicator into your trading strategy can help improve your ability to spot trend reversals, understand market volatility, and stay aligned with the broader market direction. The "Sma Standard Deviation" is a reliable and customizable solution for traders looking to enhance their technical analysis in both trending and volatile markets.
Note: Backtests are based on past results and are not indicative of future performance.
Lsma ATR | viResearchLsma ATR | viResearch
Conceptual Foundation and Innovation
The "Lsma ATR" indicator from viResearch combines the power of the Least Squares Moving Average (LSMA) with the Average True Range (ATR) to offer traders a dynamic approach to trend analysis and volatility management. The LSMA is highly regarded for its ability to fit a linear regression line to price data, providing a smooth and precise trend line with minimal lag. When paired with the ATR, which measures market volatility, this indicator not only tracks trend direction but also adapts to changes in volatility. The integration of both elements allows traders to identify potential trend reversals and assess the strength of trends in the context of market volatility. This combination makes the "Lsma ATR" a versatile tool for following trends while managing risk, as it responds quickly to changes in price direction while accounting for shifts in market volatility.
Technical Composition and Calculation
The "Lsma ATR" script consists of two primary components: the Least Squares Moving Average (LSMA) and the Average True Range (ATR). The LSMA is calculated over a user-defined length, providing a smoothed representation of the market trend based on linear regression. The ATR, also user-defined, is used to measure market volatility by calculating the average range between high and low prices over a specified period. By adding and subtracting the ATR from the LSMA, the indicator creates upper and lower boundaries that help define the market's current volatility-adjusted range. The script monitors for price crossovers with these boundaries to generate trend signals. When the price crosses above the upper boundary, it signals a potential upward trend. Conversely, when the price crosses below the lower boundary, it signals a possible downward trend. These boundaries dynamically adjust based on volatility, providing more accurate signals as market conditions change.
Features and User Inputs
The "Lsma ATR" script offers several customizable inputs, allowing traders to fine-tune the indicator to their trading preferences. The LSMA Length controls the lookback period for the LSMA, determining how smooth or responsive the trend line is. The ATR Length defines the period used for calculating the average volatility, affecting the width of the volatility-adjusted range. Additionally, the indicator includes alert conditions that notify traders when a trend shift occurs, either to the upside or downside.
Practical Applications
The "Lsma ATR" indicator is designed for traders who want to follow market trends while accounting for changes in volatility. The LSMA provides a clear, smoothed trend line that helps identify the direction of the market, while the ATR adjusts the boundaries based on the current volatility level. This combination makes the indicator particularly effective for detecting trend reversals, as the LSMA tracks the overall trend direction and price crossovers with the ATR boundaries provide early signals of potential trend changes. It also helps manage risk by understanding market volatility, allowing traders to adjust their strategies based on the strength of price movements. The indicator improves trend-following strategies by combining LSMA’s trend detection with ATR’s volatility adjustment, offering a nuanced approach in various market conditions.
Advantages and Strategic Value
The "Lsma ATR" script offers significant value by integrating the precision of the LSMA with the adaptability of the ATR. This dual approach allows traders to reduce noise in price data while responding to changes in volatility, leading to more accurate trend signals. The volatility-adjusted boundaries provide a dynamic range that helps traders avoid false signals and stay aligned with stronger trends. This makes the "Lsma ATR" an ideal tool for traders seeking to enhance their trend-following strategies while accounting for market volatility.
Alerts and Visual Cues
The script includes alert conditions that notify traders when the price crosses the ATR boundaries, signaling a potential trend change. The "Lsma ATR Long" alert is triggered when the price crosses above the upper boundary, indicating a potential upward trend, while the "Lsma ATR Short" alert signals a possible downward trend when the price crosses below the lower boundary. Visual cues, such as changes in the color of the LSMA line and shaded areas between the ATR boundaries, help traders quickly identify these trend shifts.
Summary and Usage Tips
The "Lsma ATR | viResearch" indicator combines the smoothing benefits of the LSMA with the volatility sensitivity of the ATR, providing traders with a robust tool for trend detection and volatility management. By incorporating this script into your trading strategy, you can improve your ability to detect trend reversals, confirm trend direction, and manage risk by adjusting to market volatility. The "Lsma ATR" offers a reliable and customizable solution for traders looking to enhance their technical analysis in both trending and volatile market environments.
Note: Backtests are based on past results and are not indicative of future performance.
Rational Qaudratic Kernel Elder Force Index Introduction:
The Rational Quadratic Kernel Elder Force Index is a versatile and mathematically sophisticated technical indicator that enhances the traditional Elder Force Index (EFI) by applying a rational quadratic kernel smoothing technique. This advanced regression method is designed to provide traders with a more adaptive and accurate tool for measuring the strength behind price movements, incorporating the influence of volume. This indicator does not predict future price movements, but it offers a clearer view of market dynamics through its advanced smoothing mechanism.
Key Features:
Elder Force Index Foundation:
The core of this indicator is built on the Elder Force Index, a popular tool developed by Dr. Alexander Elder. The EFI is a momentum indicator that calculates the strength of price movements by combining both price change and volume.
Rational Quadratic Kernel Smoothing: The indicator incorporates a rational quadratic kernel for smoothing, providing traders with a more refined view of price action trends. This kernel is highly adjustable based on user inputs, allowing for flexible tuning to suit individual strategies.
Adaptive Time Frame Weighting:
Through the adjustable parameter Relative Weighting (r), traders can modify the influence of different time frames. Lower values give more weight to longer time frames, while higher values make the behavior resemble that of a Gaussian kernel.
Dynamic Visualization:
The indicator visually displays the smoothed force index as a color-coded line. It dynamically changes color based on market conditions—green when the smoothed force index is positive and red when it is negative—providing a clear and easy-to-read signal for traders.
How It Works:
The Elder Force Index is calculated by multiplying the price change between two bars with the volume of the current bar.
A rational quadratic kernel regression is applied to this raw EFI data. The smoothing process provides a more stable and reliable signal by reducing noise, particularly in volatile markets.
The user-defined parameters, such as the length of the smoothing window and the relative weighting factor, allow traders to customize the indicator to suit their specific trading style or asset class.
User Inputs:
Length:
Sets the smoothing window for the kernel regression. A longer length results in more significant smoothing.
Relative Weighting (r):
Controls the influence of different time frames in the smoothing process. A smaller value emphasizes longer-term data, while a higher value makes it behave more like a traditional Gaussian kernel.
Source:
Select the price source (default is the closing price) for the calculations.
LRS-Strategy: 200-EMA Buffer & Long/Short Signals LRS-Strategy: 200-EMA Buffer & Long/Short Signals
This indicator is designed to help traders implement the Leveraged Return Strategy (LRS) using the 200-day Exponential Moving Average (EMA) as a key trend-following signal. The indicator offers clear long and short signals by analyzing the price movements relative to the 200-day EMA, enhanced by customizable buffer zones for increased precision.
Key Features:
200-Day EMA: The main trend indicator. When the price is above the 200-day EMA, the market is considered in an uptrend, and when it is below, it indicates a downtrend.
Customizable Buffer Zones: Users can define a percentage buffer around the 200-day EMA (default is 3%). The upper and lower buffer zones help filter out noise and prevent premature signals.
Precise Long/Short Signals:
Long Signal: Triggered when the price moves from below the lower buffer zone, crosses the 200-day EMA, and then breaks above the upper buffer zone.
Short Signal: Triggered when the price moves from above the upper buffer zone, crosses the 200-day EMA, and then breaks below the lower buffer zone.
Alternating Signals: Ensures that a new signal (long or short) is only generated after the opposite signal has been triggered, preventing multiple signals of the same type without a reversal.
Clear Visual Aids: The indicator displays the 200-day EMA and buffer zones on the chart, along with buy (long) and sell (short) signals. This makes it easy to track trends and time entries/exits.
How to Use:
Long Entry: Look for the price to move below the lower buffer, cross the 200-day EMA from below, and then break out of the upper buffer to confirm a long signal.
Short Entry: Look for the price to move above the upper buffer, cross below the 200-day EMA, and then break below the lower buffer to confirm a short signal.
This indicator is perfect for traders who prefer a structured, trend-following approach, using clear rules to minimize noise and identify meaningful long or short opportunities.
