Put/Call RatioPut/Call Ratio Indicator
This indicator visualizes the Put/Call Ratio for various market symbols, helping traders assess market sentiment and potential reversals. It offers a dropdown menu to select from a range of Put/Call Ratios, including broad equities (CBOE), major indices (SPX, QQQ, IWM, VIX), and individual stocks (TSLA, GOOG, META, AMZN, MSFT, INTC).
The indicator plots the Put/Call Ratio with adjustable moving averages and standard deviation bands to highlight overbought or oversold conditions. A short-term moving average (default: 10 periods) is displayed with trend-based coloring, while longer-term moving averages (defaults: 30 and 200 periods) are calculated but hidden by default. Bands at 1, 1.5, and 2 standard deviations provide context for extreme readings.
Key Overbought/Oversold Signals:
Short-Term Extremes: The 10-day moving average moves beyond 1 standard deviation from the 200-day moving average, signaling potential overbought (above) or oversold (below) conditions. This will be highlighted by red or green background color.
Ratio Extremes: The Put/Call Ratio line itself crosses outside 2 standard deviations from the 200-day moving average, indicating stronger overbought or oversold zones.
Conditional coloring of the ratio line reflects its position relative to the bands, and background shading highlights when the short-term moving average crosses key levels.
Key Features:
Selectable Put/Call Ratio symbols.
Trend-colored moving averages.
Standard deviation bands for volatility analysis.
Dynamic line and background coloring for quick insights.
Usage:
Use this indicator to gauge market sentiment—high ratios may suggest bearish sentiment or oversold conditions, while low ratios may indicate bullish sentiment or overbought conditions. Combine with price action or other tools for confirmation.
"moving averages" için komut dosyalarını ara
[blackcat] L1 Small Wave Operation L1 Small Wave Operation
Overview
Are you looking to catch those elusive small waves in the market? Look no further than " L1 Small Wave Operation." This script offers a unique way to identify potential buying opportunities by analyzing price movements, volume changes, and trend directions. With customizable inputs and clear visual indicators, it’s designed to help traders spot favorable entry points with precision.
Features
Dynamic Signal Identification: Automatically detects two types of buy signals labeled "S" and "B."
Adaptable Parameters: Allows users to adjust low period, high period, EMA periods, SMA period, and various threshold values to fine-tune the strategy.
Visual Clarity: Plots K and D lines along with four distinct threshold levels for easy visualization.
Condition-Based Signals: Uses multiple conditions including volume increases, price actions, and crossover events to confirm signals.
How It Works
Calculate Percent Range: Determines where the current closing price lies within the recent low and high range.
Compute Moving Averages: Calculates Exponential Moving Average (EMA) and Simple Moving Average (SMA) of the percent range.
Define Conditions: Checks for bullish or strong bullish patterns, uptrends, and specific crossover events between K and D lines.
Generate Signals: Marks potential buying opportunities when predetermined conditions are met.
How To Use
Add this script to your TradingView chart.
Adjust the input parameters according to your preferred settings.
Monitor the plotted lines and look for "S" and "B" labels indicating buy signals.
Consider incorporating these signals into a broader trading strategy that includes risk management techniques.
What Makes It Special
Flexibility: Users can easily modify parameters to adapt the script to different markets or personal preferences.
Automation: Saves time by automatically scanning for trade setups based on predefined rules.
Comprehensive Analysis: Combines multiple factors like volume, price action, and moving averages to provide reliable signals.
Limitations
Past performance does not guarantee future results.
Market conditions can vary, affecting signal reliability.
Not suitable for very short-term trades without additional refinements.
Notes
Always perform backtesting on historical data before implementing live trades.
Understand the underlying logic of the script to avoid misinterpretation of signals.
Regularly review and adjust parameters based on changing market dynamics.
MA Rainbow-AYNETSummary of the "MA Rainbow"
The 200 MA Rainbow script creates a visually appealing representation of multiple moving averages (MAs) with varying lengths and colors to provide insights into price trends and market momentum.
Key Features:
Base Moving Average:
A starting point (ma_length, default 200) is used as the foundation for all other bands.
Rainbow Bands:
The script generates multiple moving averages (bands) with increasing lengths, spaced by a user-defined band_spacing multiplier.
The number of bands is controlled by rainbow_bands, allowing up to 7 bands.
Moving Average Types:
Users can select the MA type: Simple (SMA), Exponential (EMA), or Weighted (WMA).
Dynamic Colors:
Each band is assigned a unique color from a predefined rainbow palette, making the chart visually distinct.
Inputs for Customization:
ma_length: Adjust the base period of the moving average.
rainbow_bands: Set the number of bands to display.
band_spacing: Control the spread between bands.
How It Works:
Precomputing Bands:
Each band’s length is calculated based on the base length (ma_length) and a multiplier (band_spacing).
For example, if ma_length = 200 and band_spacing = 0.2, the lengths of the first 3 bands will be:
Band 1: 200
Band 2: 240
Band 3: 280
Global Plotting:
Each band’s moving average is precomputed using the selected type (SMA, EMA, or WMA).
Bands are plotted globally to avoid scope issues, ensuring compatibility with Pine Script rules.
Color Cycling:
Colors are assigned dynamically from a rainbow palette (red, orange, yellow, green, blue, purple, teal).
Use Case:
The 200 MA Rainbow helps traders:
Visualize market trends with multiple layers of moving averages.
Identify areas of support and resistance.
Gauge momentum through the spread and alignment of bands.
Customization:
Users can:
Change the base moving average length (ma_length).
Adjust the number of bands (rainbow_bands).
Control the spread between bands with band_spacing.
Select the moving average type (SMA, EMA, WMA).
Application:
Copy the script into the Pine Editor in TradingView.
Apply it to your chart to observe the Rainbow MA visualization.
Adjust inputs to match your trading style or strategy.
This script is a versatile tool for both beginner and advanced traders, providing a colorful way to track price trends and market conditions. 🌈
Dynamic Buy/Sell VisualizationDynamic Trend Visualization Indicator
Description:
This simple and easy to use indicator has helped me stay in trades longer.
This indicator is designed to visually represent potential buy and sell signals based on the crossover of two Simple Moving Averages (SMA). It's crafted to assist traders in identifying trend directions in a straightforward manner, making it an excellent tool for both beginners and experienced traders.
Features:
Customizable Moving Averages: Users can adjust the period length for both short-term (default: 10) and long-term (default: 50) SMAs to suit their trading strategy.
Visual Signals: Dynamic lines appear at the points of SMA crossover, with labels to indicate 'BUY' or 'SELL' opportunities.
Color and Style Customization: Customize the appearance of the buy and sell lines for better chart readability.
Alert Functionality: Alerts are set up to notify users when a crossover indicating a buy or sell condition occurs.
How It Works:
A 'BUY' signal is generated when the short-term SMA crosses above the long-term SMA, suggesting an upward trend.
A 'SELL' signal is indicated when the short-term SMA crosses below the long-term SMA, pointing to a potential downward trend.
Use Cases:
Trend Following: Ideal for markets with clear trends. For example, if trading EUR/USD on a daily chart, setting the short SMA to 10 days and the long SMA to 50 days might help in capturing longer-term trends.
Scalping: In a volatile market, setting shorter periods (e.g., 5 for short SMA and 20 for long SMA) might catch quicker trend changes, suitable for scalping.
Examples of how to use
* Short-term for Quick Trades:
SMA 5 and SMA 21:
Purpose: This combination is tailored for day traders or those looking to engage in scalping. The 5 SMA will react rapidly to price changes, providing early signals for buy or sell opportunities. The 21 SMA, being a Fibonacci number, offers a slightly longer-term view to confirm the short-term trend, helping to filter out minor fluctuations that might lead to false signals.
* Middle-term for Swing Trading:
SMA 10 and SMA 50:
Purpose: Suited for swing traders who aim to capitalize on medium-term trends. The 10 SMA picks up on immediate market movements, while the 50 SMA gives insight into the medium-term direction. This setup helps in identifying when a short-term trend aligns with a longer-term trend, providing a good balance for trades that might last several days to a couple of weeks.
* Long-term Trading:
SMA 50 and SMA 200:
Purpose: Investors focusing on long-term trends would benefit from this pair. The crossover of the 50 SMA over the 200 SMA can indicate the beginning or end of major market trends, ideal for making decisions about long-term holdings that might span months or years.
Example Strategy if not using the Buy / Sell Label Alerts:
Entry Signal: Enter a long position when the shorter SMA crosses above the longer SMA. For example:
SMA 10 crosses above SMA 50 for a medium-term bullish signal.
Exit Signal: Consider exiting or initiating a short position when:
SMA 10 crosses below SMA 50, suggesting a bearish turn in the medium-term trend.
Confirmation: Use these crossovers in conjunction with other indicators like volume or momentum indicators for better confirmation. For instance, if you're using the 5/21 combination, look for volume spikes on crossovers to confirm the move's strength.
When Not to Use:
Sideways or Range-Bound Markets: The indicator might generate many false signals in a non-trending market, leading to potential losses.
High Volatility Without Clear Trends: Rapid price movements without a consistent direction can result in misleading crossovers.
As a Standalone Tool: It should not be used in isolation. Combining with other indicators like RSI or MACD for confirmation can enhance trading decisions.
Practical Example:
Buy Signal: If you're watching Apple Inc. (AAPL) on a weekly chart, a crossover where the 10-week SMA moves above the 50-week SMA could suggest a buying opportunity, especially if confirmed by volume increase or other technical indicators.
Sell Signal: Conversely, if the 10-week SMA dips below the 50-week SMA, it might be time to consider selling, particularly if other bearish signals are present.
Conclusion:
The "Dynamic Trend Visualization" indicator provides a visual aid for trend-following strategies, offering customization and alert features to streamline the trading process. However, it's crucial to use this in conjunction with other analysis methods to mitigate the risks of false signals or market anomalies.
Legal Disclaimer:
This indicator is for educational purposes only. It does not guarantee profits or provide investment advice. Trading involves risk; please conduct thorough or consult with a financial advisor. The creator is not responsible for any losses incurred. By using this indicator, you agree to these terms.
RSI from Rolling VWAP [CHE]Introducing the RSI from Rolling VWAP Indicator
Elevate your trading strategy with the RSI from Rolling VWAP —a cutting-edge indicator designed to provide unparalleled insights and enhance your decision-making on TradingView. This advanced tool seamlessly integrates the Relative Strength Index (RSI) with a Rolling Volume-Weighted Average Price (VWAP) to deliver precise and actionable trading signals.
Why Choose RSI from Rolling VWAP ?
- Clear Trend Detection: Our enhanced algorithms ensure accurate identification of bullish and bearish trends, allowing you to capitalize on market movements with confidence.
- Customizable Time Settings: Tailor the time window in days, hours, and minutes to align perfectly with your unique trading strategy and market conditions.
- Flexible Moving Averages: Select from a variety of moving average types—including SMA, EMA, WMA, and more—to smooth the RSI, providing clearer trend analysis and reducing market noise.
- Threshold Alerts: Define upper and lower RSI thresholds to effortlessly spot overbought or oversold conditions, enabling timely and informed trading decisions.
- Visual Enhancements: Enjoy a visually intuitive interface with color-coded RSI lines, moving averages, and background fills that make interpreting market data straightforward and efficient.
- Automatic Signal Labels: Receive immediate bullish and bearish labels directly on your chart, signaling potential trading opportunities without the need for constant monitoring.
Key Features
- Inspired by Proven Tools: Building upon the robust foundation of TradingView's Rolling VWAP, our indicator offers enhanced functionality and greater precision.
- Volume-Weighted Insights: By incorporating volume into the VWAP calculation, gain a deeper understanding of price movements and market strength.
- User-Friendly Configuration: Easily adjust settings to match your trading preferences, whether you're a novice trader or an experienced professional.
- Hypothesis-Driven Analysis: Utilize hypothetical results to backtest strategies, understanding that past performance does not guarantee future outcomes.
How It Works
1. Data Integration: Utilizes the `hlc3` (average of high, low, and close) as the default data source, with customization options available to suit your trading needs.
2. Dynamic Time Window: Automatically calculates the optimal time window based on an auto timeframe or allows for fixed time periods, ensuring flexibility and adaptability.
3. Rolling VWAP Calculation: Accurately computes the Rolling VWAP by balancing price and volume over the specified time window, providing a reliable benchmark for price action.
4. RSI Analysis: Measures momentum through RSI based on Rolling VWAP changes, smoothed with your chosen moving average for enhanced trend clarity.
5. Actionable Signals: Detects and labels bullish and bearish conditions when RSI crosses predefined thresholds, offering clear indicators for potential market entries and exits.
Seamless Integration with Your TradingView Experience
Adding the RSI from Rolling VWAP to your TradingView charts is straightforward:
1. Add to Chart: Simply copy the Pine Script code into TradingView's Pine Editor and apply it to your desired chart.
2. Customize Settings: Adjust the Source Settings, Time Settings, RSI Settings, MA Settings, and Color Settings to align with your trading strategy.
3. Monitor Signals: Watch for RSI crossings above or below your set thresholds, accompanied by clear labels indicating bullish or bearish trends.
4. Optimize Your Trades: Leverage the visual and analytical strengths of the indicator to make informed buy or sell decisions, maximizing your trading potential.
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Get Started Today
Transform your trading approach with the RSI from Rolling VWAP indicator. Experience the synergy of momentum and volume-based analysis, and unlock the potential for more accurate and profitable trades.
Download now and take the first step towards a more informed and strategic trading journey!
For further inquiries or support, feel free to contact
Best regards
Chervolino
Inspired by the acclaimed Rolling VWAP by TradingView
Chandelier Exit Pro w/ExtensionsChandelier Exit Pro w/Extensions
The Chandelier Exit Pro w/Extensions indicator is designed to assist traders in managing risk and identifying trend reversals. The strategy is based on the Chandelier Exit concept, originally created by Charles Le Beau. It uses the Average True Range (ATR) to calculate dynamic stop levels that adjust based on market volatility. This script not only implements the standard Chandelier Exit, but also introduces extension levels and alerts to enhance decision-making.
Key Features:
➡️Dynamic Stop Levels: The indicator calculates stop levels for both long and short positions based on an ATR multiple. This allows traders to determine exit points by monitoring when the price crosses above or below these levels. These levels adapt in real-time based on price volatility, making them a versatile tool for trend-following strategies.
➡️Extension Levels: In addition to the primary stop levels, the script includes extension levels for more advanced stop-loss management. Traders can view active and extension levels separately, providing more flexibility in their exit strategies.
➡️Labels and Visual Cues: The indicator provides dynamic labels that automatically update and follow the plotted stop levels. Labels include the ATR multiplier value (e.g., "2.5" or "2.5ext"), clearly showing the significance of each level. When price crosses below or above a level, the corresponding label is highlighted, aiding traders in quickly identifying the most relevant stop level.
➡️Bar Confirmation and Alerts: The script includes an "await bar confirmation" option to ensure that the stop levels and alerts only trigger after the bar has closed. Alerts are customizable and will notify traders when price crosses critical levels, helping to make timely decisions without the need to constantly monitor charts.
➡️Multiple ATR Levels for Enhanced Precision: The indicator supports up to four different ATR levels, each with customizable multipliers. This allows traders to set different thresholds for exits based on varying degrees of volatility. For example, Level 1 (2.5x ATR) might represent a tighter stop, while Level 4 (10x ATR) could serve as a wider stop for long-term positions.
➡️Calc_bars_count: Improves efficiency of the indicator by reducing the on-chart calculations in to the past. This input can be found at the bottom of the INPUTS tab.
How it Helps Traders:
💥Trend Identification: By using the Chandelier Exit levels, traders can identify when the trend is likely to reverse. When the price crosses below the stop level in a long trade or above the stop level in a short trade, it signals a potential exit point.
💥Volatility-based Adjustments: Unlike static stop-loss methods, the ATR-based stop levels dynamically adjust based on the market’s volatility. This means tighter stops during low volatility periods and wider stops during high volatility periods, reducing the chance of being stopped out prematurely.
💥Risk Management: The dynamic stop levels and extension levels provide a structured way to manage risk. Traders can set tighter stops for short-term trades and wider stops for longer-term trades. The script's visual labels make it easy to track these levels in real-time.
💥Automation with Alerts: The built-in alert system ensures that traders are notified when key levels are crossed. This helps to avoid emotional decision-making and allows for better execution of trading strategies.
Confluence and Price Fluidity:
One of the powerful ways to enhance the effectiveness of the Chandelier Exit indicator is by using it in conjunction with other technical analysis tools to create confluence. Confluence occurs when multiple indicators or price action signals align, providing stronger confirmation for a trade decision. For example:
🎯Support and Resistance Levels: Traders can use the Chandelier Exit levels in combination with key support and resistance zones. If the price is nearing a support level and the Chandelier Exit signals a bullish reversal, this alignment strengthens the case for entering a long position.
🎯Moving Averages: When the Chandelier Exit signals a trend reversal and this is confirmed by a crossover in moving averages (such as a 50-day and 200-day moving average), traders gain additional confidence in the trade direction.
🎯Momentum Indicators: Traders can also look for momentum indicators like RSI or MACD to confirm the strength of a trend or potential reversal. For instance, if the Chandelier Exit triggers a short signal and the RSI also shows overbought conditions, this could provide stronger confirmation to exit a long trade or enter a short position.
🎯Candlestick Patterns: Price fluidity can be monitored using candlestick formations. For example, a bearish engulfing pattern near a Chandelier Exit resistance level offers confluence, adding confidence to the signal to close or short the trade.
By combining the Chandelier Exit with other tools, traders ensure that they are not relying on a single indicator. This layered approach can reduce the likelihood of false signals and improve overall trading accuracy.
Practical Use Case:
Imagine a trader enters a long position, and the price moves favorably. Using the Chandelier Exit, the trader sets the initial stop level at 2.5x ATR below the highest close. As the price continues to rise, the stop level follows the price, locking in profits. If the market suddenly turns, the price crossing below the stop level signals an exit, helping the trader preserve gains. With extension levels, the trader can further refine exits, adjusting based on their risk tolerance and market conditions.
Good luck and I hope that you can find a place in your tool bag to use this dynamic indicator 🙏
Market Sentiment Technicals [LuxAlgo]The Market Sentiment Technicals indicator synthesizes insights from diverse technical analysis techniques, including price action market structures, trend indicators, volatility indicators, momentum oscillators, and more.
The indicator consolidates the evaluated outputs from these techniques into a singular value and presents the combined data through an oscillator format, technical rating, and a histogram panel featuring the sentiment of each component alongside the overall sentiment.
🔶 USAGE
The Market Sentiment Technicals indicator is a tool able to swiftly and easily gauge market sentiment by consolidating the individual sentiment from multiple technical analysis techniques applied to market data into a single value, allowing users to asses if the market is uptrending, consolidating, or downtrending.
The tool includes various components and presentation formats, each described in the sub-sections below.
🔹Indicators Sentiment Panel
The indicators sentiment panel provides normalized sentiment scores for each supported indicator, along with a synthesized representation derived from the average of all individual normalized sentiments.
🔹Market Sentiment Meter
The market sentiment meter is obtained from the synthesized representation derived from the average of all individual normalized sentiments. It allows users to quickly and easily gauge the overall market sentiment.
🔹Market Sentiment Oscillator
The market sentiment oscillator provides a visual means to monitor the current and historical strength of the market. It assists in identifying the trend direction, trend momentum, and overbought and oversold conditions, aiding in the anticipation of potential trend reversals.
Divergence occurs when there is a difference between what the price action is indicating and what the market sentiment oscillator is indicating, helping traders assess changes in the price trend.
🔶 DETAILS
The indicator employs a range of technical analysis techniques to interpret market data. Each group of indicators provides valuable insights into different aspects of market behavior.
🔹Momentum Indicators
Momentum indicators assess the speed and change of price movements, often indicating whether a trend is strengthening or weakening.
Relative Strength Index (RSI): Measures the magnitude of recent price changes to evaluate overbought or oversold conditions.
Stochastic %K: Compares the closing price to the range over a specified period to identify potential reversal points.
Stochastic RSI Fast: Combines features of Stochastic oscillators and RSI to gauge both momentum and overbought/oversold levels efficiently.
Commodity Channel Index (CCI): Measures the deviation of an asset's price from its statistical average to determine trend strength and overbought and oversold conditions.
Bull Bear Power: Evaluates the strength of buying and selling pressure in the market.
🔹Trend Indicators
Trend indicators help traders identify the direction of a market trend.
Moving Averages: Provides a smoothed representation of the underlying price data, aiding in trend identification and analysis.
Bollinger Bands: Consists of a middle band (typically a simple moving average) and upper and lower bands, which represent volatility levels of the market.
Supertrend: A trailing stop able to identify the current direction of the trend.
Linear Regression: Fits a straight line to past data points to predict future price movements and identify trend direction.
🔹Market Structures
Market Structures: Analyzes the overall pattern of price movements, including Break of Structure (BOS), Market Structure Shifts (MSS), also referred to as Change of Character (CHoCH), aiding in identifying potential market turning and continuation points.
🔹The Normalization Technique
The normalization technique employed for trend indicators relies on buy-sell signals. The script tracks price movements and normalizes them based on these signals.
normalize(buy, sell, smooth)=>
var os = 0
var float max = na
var float min = na
os := buy ? 1 : sell ? -1 : os
max := os > os ? close : os < os ? max : math.max(close, max)
min := os < os ? close : os > os ? min : math.min(close, min)
ta.sma((close - min)/(max - min), smooth) * 100
In this Pine Script snippet:
The variable os tracks market sentiment, taking a value of 1 for buy signals and -1 for sell signals, indicating bullish and bearish sentiments, respectively.
max and min are used to identify extremes in sentiment and are updated based on changes in os . When market sentiment shifts from buying to selling (or vice versa), max and min adjust accordingly.
Normalization is achieved by comparing current price levels to historical extremes in sentiment. The result is smoothed by default using a 3-period simple moving average. Users have the option to customize the smoothing period via the script settings input menu.
🔶 SETTINGS
🔹Generic Settings
Timeframe: This option selects the timeframe for calculating sentiment. If a timeframe lower than the chart's is chosen, calculations will be based on the chart's timeframe.
Horizontal Offset: Determines the distance at which the visual components of the indicator will be displayed from the primary chart.
Gradient Colors: Allows customization of gradient colors.
🔹Indicators Sentiment Panel
Indicators Sentiment Panel: Toggle the visibility of the indicators sentiment panel.
Panel Height: Determines the height of the panel.
🔹Market Sentiment Meter
Market Sentiment Meter: Toggle the visibility of the market sentiment meter (technical ratings in the shape of a speedometer).
🔹Market Sentiment Oscillator
Market Sentiment Oscillator: Toggle the visibility of the market sentiment oscillator.
Show Divergence: Enables detection of divergences based on the selected option.
Oscillator Line Width: Customization option for the line width.
Oscillator Height: Determines the height of the oscillator.
🔹Settings for Individual Components
In general,
Source: Determines the data source for calculations.
Length: The period to be used in calculations.
Smoothing: Degree of smoothness of the evaluated values.
🔹Normalization Settings - Trend Indicators
Smoothing: The period used in smoothing normalized values, where normalization is applied to moving averages, Bollinger Bands, Supertrend, VWAP bands, and market structures.
🔶 LIMITATIONS
Like any technical analysis tool, the Market Sentiment Technicals indicator has limitations. It's based on historical data and patterns, which may not always accurately predict future market movements. Additionally, market sentiment can be influenced by various factors, including economic news, geopolitical events, and market psychology, which may not be fully captured by technical analysis alone.
Volatility Adjusted Weighted DEMA [BackQuant]Volatility Adjusted Weighted DEMA
The Volatility Adjusted Weighted Double Exponential Moving Average (VAWDEMA) by BackQuant is a sophisticated technical analysis tool designed for traders seeking to integrate volatility into their moving average calculations. This innovative indicator adjusts the weighting of the Double Exponential Moving Average (DEMA) according to recent volatility levels, offering a more dynamic and responsive measure of market trends.
Primarily, the single Moving average is very noisy, but can be used in the context of strategy development, where as the crossover, is best used in the context of defining a trading zone/ macro uptrend on higher timeframes.
Why Volatility Adjustment is Beneficial
Volatility is a fundamental aspect of financial markets, reflecting the intensity of price changes. A volatility adjustment in moving averages is beneficial because it allows the indicator to adapt more quickly during periods of high volatility, providing signals that are more aligned with the current market conditions. This makes the VAWDEMA a versatile tool for identifying trend strength and potential reversal points in more volatile markets.
Understanding DEMA and Its Advantages
DEMA is an indicator that aims to reduce the lag associated with traditional moving averages by applying a double smoothing process. The primary benefit of DEMA is its sensitivity and quicker response to price changes, making it an excellent tool for trend following and momentum trading. Incorporating DEMA into your analysis can help capture trends earlier than with simple moving averages.
The Power of Combining Volatility Adjustment with DEMA
By adjusting the weight of the DEMA based on volatility, the VAWDEMA becomes a powerful hybrid indicator. This combination leverages the quick responsiveness of DEMA while dynamically adjusting its sensitivity based on current market volatility. This results in a moving average that is both swift and adaptive, capable of providing more relevant signals for entering and exiting trades.
Core Logic Behind VAWDEMA
The core logic of the VAWDEMA involves calculating the DEMA for a specified period and then adjusting its weighting based on a volatility measure, such as the average true range (ATR) or standard deviation of price changes. This results in a weighted DEMA that reflects both the direction and the volatility of the market, offering insights into potential trend continuations or reversals.
Utilizing the Crossover in a Trading System
The VAWDEMA crossover occurs when two VAWDEMAs of different lengths cross, signaling potential bullish or bearish market conditions. In a trading system, a crossover can be used as a trigger for entry or exit points:
Bullish Signal: When a shorter-period VAWDEMA crosses above a longer-period VAWDEMA, it may indicate an uptrend, suggesting a potential entry point for a long position.
Bearish Signal: Conversely, when a shorter-period VAWDEMA crosses below a longer-period VAWDEMA, it might signal a downtrend, indicating a possible exit point or a short entry.
Incorporating VAWDEMA crossovers into a trading strategy can enhance decision-making by providing timely and adaptive signals that account for both trend direction and market volatility. Traders should combine these signals with other forms of analysis and risk management techniques to develop a well-rounded trading strategy.
Alert Conditions For Trading
alertcondition(vwdema>vwdema , title="VWDEMA Long", message="VWDEMA Long - {{ticker}} - {{interval}}")
alertcondition(vwdema
Trend Signals with TP & SL [UAlgo]The "Trend Signals with TP & SL " indicator is a versatile tool designed to assist traders in identifying potential trend continuation opportunities within financial markets Utilizing a combination of technical indicators and user-defined parameters, this indicator aims to provide clear and actionable signals to aid traders in making informed trading decisions.
🔶 Features:
Trend Continuation Signals : The indicator generates signals to identify potential trend continuation points based on the input parameters such as sensitivity, ATR length, and cloud moving average length.
Take-Profit and Stop-Loss Levels: It calculates and plots three levels of take-profit (1R, 2R, 3R) and stop-loss levels based on the entry price of the trade.
Short Position Example:
Long Position Example:
Visualization: The script visualizes the trend signals, entry points, take-profit levels, and stop-loss levels on the price chart, making it easier for traders to interpret the signals.
Alert System: The indicator includes an alert system that notifies the user when there is a change in trend direction or when a buy/sell signal is generated. The alerts provide essential information such as entry price, take-profit levels, and stop-loss levels.
🔶 Calculations :
Trend Calculation: Trend signals are determined based on the comparison between the current closing price and the upper and lower bounds calculated using the Average True Range (ATR) multiplied by a sensitivity factor. A trend is considered bullish if the closing price is above the upper bound and bearish if it's below the lower bound.
Entry, Stop Loss, and Take Profit Calculation: Entry points for long and short positions are identified when there's a change in trend direction.
Stop-loss levels are calculated as a percentage of the entry price, where users can define the percentage based on their risk tolerance.
Take-profit levels are calculated as multiples of the stop-loss level (1R, 2R, 3R).
Cloud Moving Averages: Simple moving averages (SMAs) are calculated for high and low prices over a specified period to create a "cloud" visualization on the chart.
MACD Clouds: Moving Average Convergence Divergence (MACD) indicator is used to determine the market's momentum and trend direction. Positive and negative clouds are plotted based on the MACD line and its signal line, indicating potential bullish or bearish trends.
Signal Generation: Buy and sell signals are generated based on specific conditions such as RSI, CMO (Chande Momentum Oscillator), and pivot points.
Signals are triggered when certain criteria are met, indicating potential opportunities for entering or exiting trades.
🔶 Disclaimer:
Use at Your Own Risk: Trading involves significant risk, and this script is provided for educational and informational purposes only. It does not guarantee profitable trades, and users should exercise caution and perform their own analysis before making trading decisions.
Parameter Sensitivity: The effectiveness of the indicator may vary depending on the chosen parameters, market conditions, and timeframe. Users are encouraged to backtest the script thoroughly and adjust the parameters according to their trading preferences.
Not Financial Advice: The information provided by this script should not be considered as financial advice. Users are solely responsible for their trading decisions and should consult with a qualified financial advisor if needed.
Backtesting and Validation: Before implementing this indicator in live trading, users are strongly encouraged to conduct rigorous backtesting and validation to assess its performance under various market conditions. Past performance is not indicative of future results, and users should carefully evaluate the effectiveness of the indicator based on their individual trading preferences and risk tolerance.
VARGAS"VARGAS" is an indicator that can be used in all timeframes on charts in the stock, crypto, and commodity markets. It allows trades to be opened according to the intersections of moving averages in different time periods.
It is an indicator using weighted moving averages. Using a weighted moving average has the following benefits for traders:
1) Precision and Smoothness: The WMA typically gives more weight to recent prices and therefore reacts faster to more recent data. This helps you catch price movements faster and recognize trend changes faster. On the other hand, the WMA is smoother than the simple moving average (SMA), which makes it less likely to generate false signals.
2) Trend Identification: The WMA is used to identify and analyze price trends. It is especially important for traders who want to track short-term movements. The WMA is used to assess the direction and strength of the trend.
3) Trading Signals: The WMA is used as part of various trading strategies. It is especially used in moving average crossover strategies. For example, a short-term WMA crossing the long-term WMA to the upside can be considered a buy signal, while a reversal can be interpreted as a sell signal.
4) Adaptability to Volatility: WMA can adapt to volatility by changing weighting factors. Investors can adopt a more flexible approach by assigning different weights based on market conditions and asset classes.
5) Data Correction: WMA can be helpful in reducing data noise. A single large price fluctuation can cause the SMA to be more affected, while the WMA reduces the impact of these fluctuations.
In our VARGAS coding, the intersection times of the 9-day and 15-day weighted moving averages allow us to decide the direction of the trend. The green and red cloud areas following the price candles make the strategy easy for the user to follow.
At the intersection between the 9-day weighted moving average and the 15-day weighted moving average, we can use buy and sell signals as follows:
If the 9-day weighted moving average crosses the 15-day weighted moving average upwards, buy,
Sell if the 9-day weighted moving average crosses the 15-day weighted moving average downwards.
Within the scope of this strategy, GOLDEN CROSS and DEATH CROSS intersections, which guide us for trend changes, are also included in the coding. Thus, it is aimed to add strength to our WMA 9 and WMA 15 intersection strategy as an idea.
VARGAS indicator gives better results for longer periods of 4 hours and above. As the time period increases, the probability of correct results will increase.
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"VARGAS" hisse senedi, kripto, ve emtia piyasalarındaki grafiklerde her türlü zaman diliminde kullanılabilen bir indikatördür. Farklı zaman periyotlarındaki hareketli ortalamaların kesişimlerine göre işlem açılmasını sağlar.
Ağırlıklı hareketli ortalamalar kullanılarak hazırlanmış bir göstergedir. Ağırlıklı hareketli ortalama kullanmanın yatırımcılara aşağıdaki gibi faydaları bulunmaktadır:
1) Duyarlılık ve Pürüzsüzlük: WMA, tipik olarak son dönem fiyatlarına daha fazla ağırlık verir ve bu nedenle daha güncel verilere daha hızlı tepki verir. Bu, fiyat hareketlerini daha hızlı yakalamanıza ve daha hızlı trend değişikliklerini tanımanıza yardımcı olur. Diğer yandan, WMA, basit hareketli ortalamaya (SMA) göre daha pürüzsüzdür, bu da yanlış sinyal üretme olasılığını azaltır.
2) Trend Belirleme: WMA, fiyat trendlerini belirlemek ve analiz etmek için kullanılır. Özellikle kısa vadeli hareketleri izlemek isteyen yatırımcılar için önemlidir. WMA, trendin yönünü ve gücünü değerlendirmek için kullanılır.
3) Ticaret Sinyalleri: WMA, çeşitli ticaret stratejilerinin bir parçası olarak kullanılır. Özellikle hareketli ortalama crossover stratejilerinde kullanılır. Örneğin, kısa vadeli WMA'nın uzun vadeli WMA'yı yukarı yönlü kesmesi bir alım sinyali olarak kabul edilebilir, tersine dönmesi ise bir satış sinyali olarak yorumlanabilir.
4) Volatiliteye Uyarlanabilirlik: WMA, ağırlıklandırma faktörlerini değiştirerek volatiliteye uyum sağlayabilir. Yatırımcılar, piyasa koşullarına ve varlık sınıflarına göre farklı ağırlıklar atayarak daha esnek bir yaklaşım benimseyebilirler.
5) Veri Düzeltme: WMA, veri gürültüsünü azaltmada yardımcı olabilir. Tek bir büyük fiyat dalgalanması, SMA'nın daha fazla etkilenmesine neden olabilirken, WMA bu dalgalanmaların etkisini azaltır.
VARGAS isimli kodlamamızda ise 9 günlük ve 15 günlük ağırlıklı hareketli ortalamaların kesişme zamanları trendin yönüne karar vermemizi sağlar. Fiyat mumlarını takip eden yeşil ve kırmızı bulut alanları stratejinin kullanıcı tarafından kolaylıkla takip edilmesini sağlamaktadır.
9 Günlük Ağırlıklı hareketli ortalama, 15 Günlük Ağırlıklı hareketli ortalama arasındaki kesişimde al ve sat sinyallerini şu şekilde kullanabiliriz:
Eğer 9 günlük ağırlıklı hareketli ortalama 15 günlük ağırlıklı hareketli ortalamayı yukarı doğru kesiyorsa al,
Eğer 9 günlük ağırlıklı hareketli ortalama, 15 günlük ağırlıklı hareketli ortalamayı aşağı doğru keserse sat.
Bu strateji kapsamında trend değişimleri için bizlere yön veren GOLDEN CROSS ve DEATH CROSS kesişimleri de kodlamanın içerisinde dahil edilmiştir. Böylelikle WMA 9 ve WMA 15 kesişim stratejimize fikir olarak güç katması hedeflenmiştir.
VARGAS indikatörü 4 saat ve üzeri daha uzun periyotlarda daha iyi sonuçlar vermektedir. Zaman periyodu büyüdükçe doğru sonuç verme olasılığı artacaktır.
Pseudo-Entropy Oscillator with Standard Deviation (modified)Intuition: The Pseudo-Entropy Oscillator with Standard Deviation (PEO_SD) was created to provide traders with a way to analyze market momentum and potential reversals. It combines the concepts of entropy, standard deviation, and moving averages to offer insights into market behavior.The oscillator's core idea is to measure the pseudo-entropy of the market using standard deviation. Pseudo-entropy refers to the degree of disorder or randomness in the price data. By calculating the standard deviation of the closing prices over a specified period, the oscillator quantifies the market's volatility.To enhance the usefulness of the pseudo-entropy measurement, the oscillator incorporates moving averages. The entropy delta is calculated by applying momentum analysis to the pseudo-entropy values. This helps identify short-term changes in the entropy, indicating shifts in market sentiment or momentum.The oscillator further smoothes the pseudo-entropy values by calculating the simple moving average (SMA) over a specified length. This helps filter out noise and provides a clearer representation of the market's overall momentum.
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The "Pseudo-Entropy Oscillator with Standard Deviation" (PEO_SD) is a custom indicator designed to help traders analyze market momentum and potential reversal points. It can be applied to various markets like stocks, commodities, forex, or cryptocurrencies. By using this indicator, you can gain insights into the market's behavior and make more informed trading decisions.
The PEO_SD indicator plots three lines on your chart: the fast pseudo-entropy line, the medium pseudo-entropy line, and the slow pseudo-entropy line. Each line represents the combined pseudo-entropy values, which are calculated using standard deviation and moving averages.
The lines are color-coded for easy identification. The fast line is represented by blue, the medium line by yellow, and the slow line by red. Additionally, three horizontal reference lines are plotted: the mid line (at 50), the lower bound (at 20), and the upper bound (at 80).
To use this indicator effectively, you can observe the interactions of the lines with the reference lines. For example, when any of the lines cross above the mid line, it might indicate a bullish signal, suggesting an upward price movement. Conversely, a crossover below the mid line could be a bearish signal, indicating a potential downward price movement. If the lines reach the upper bound, it might suggest that the market is overbought, and a reversal could be imminent. Conversely, reaching the lower bound may indicate that the market is oversold, possibly leading to a price reversal.
By applying the PEO_SD indicator and studying the lines' movements, you can gain valuable insights into market momentum, identify potential reversal points, and make more informed trading decisions.
SuperTrend with Chebyshev FilterModified Super Trend with Chebyshev Filter
The Modified Super Trend is an innovative take on the classic Super Trend indicator. This advanced version incorporates a Chebyshev filter, which significantly enhances its capabilities by reducing false signals and improving overall signal quality. In this post, we'll dive deep into the Modified Super Trend, exploring its history, the benefits of the Chebyshev filter, and how it effectively addresses the challenges associated with smoothing, delay, and noise.
History of the Super Trend
The Super Trend indicator, developed by Olivier Seban, has been a popular tool among traders since its inception. It helps traders identify market trends and potential entry and exit points. The Super Trend uses average true range (ATR) and a multiplier to create a volatility-based trailing stop, providing traders with a dynamic tool that adapts to changing market conditions. However, the original Super Trend has its limitations, such as the tendency to produce false signals during periods of low volatility or sideways trading.
The Chebyshev Filter
The Chebyshev filter is a powerful mathematical tool that makes an excellent addition to the Super Trend indicator. It effectively addresses the issues of smoothing, delay, and noise associated with traditional moving averages. Chebyshev filters are named after Pafnuty Chebyshev, a renowned Russian mathematician who made significant contributions to the field of approximation theory.
The Chebyshev filter is capable of producing smoother, more responsive moving averages without introducing additional lag. This is possible because the filter minimizes the worst-case error between the ideal and the actual frequency response. There are two types of Chebyshev filters: Type I and Type II. Type I Chebyshev filters are designed to have an equiripple response in the passband, while Type II Chebyshev filters have an equiripple response in the stopband. The Modified Super Trend allows users to choose between these two types based on their preferences.
Overcoming the Challenges
The Modified Super Trend addresses several challenges associated with the original Super Trend:
Smoothing: The Chebyshev filter produces a smoother moving average without introducing additional lag. This feature is particularly beneficial during periods of low volatility or sideways trading, as it reduces the number of false signals.
Delay: The Chebyshev filter helps minimize the delay between price action and the generated signal, allowing traders to make timely decisions based on more accurate information.
Noise Reduction: The Chebyshev filter's ability to minimize the worst-case error between the ideal and actual frequency response reduces the impact of noise on the generated signals. This feature is especially useful when using the true range as an offset for the price, as it helps generate more reliable signals within a reasonable time frame.
The Great Replacement
The Modified Super Trend with Chebyshev filter is an excellent replacement for the original Super Trend indicator. It offers significant improvements in terms of signal quality, responsiveness, and accuracy. By incorporating the Chebyshev filter, the Modified Super Trend effectively reduces the number of false signals during low volatility or sideways trading, making it a more reliable tool for identifying market trends and potential entry and exit points.
In-Depth Guide to the Modified Super Trend Settings
The Modified Super Trend with Chebyshev filter offers a wide range of settings that allow traders to fine-tune the indicator to suit their specific trading styles and objectives. In this section, we will discuss each setting in detail, explaining its purpose and how to use it effectively.
Source
The source setting determines the price data used for calculations. The default setting is hl2, which calculates the average of the high and low prices. You can choose other price data sources such as close, open, or ohlc4 (average of open, high, low, and close prices) based on your preference.
Up Color and Down Color
These settings control the color of the trend line when the market is in an uptrend (up_color) and a downtrend (down_color). You can customize these colors to your liking, making it easier to visually identify the current market trend.
Text Color
This setting controls the color of the text displayed on the chart when using labels to indicate trend changes. You can choose any color that contrasts well with your chart background for better readability.
Mean Length
The mean_length setting determines the length (number of bars) used for the Chebyshev moving average calculation. A shorter length will make the moving average more responsive to price changes, while a longer length will produce a smoother moving average. It is crucial to find the right balance between responsiveness and smoothness, as a too-short length may generate false signals, while a too-long length might produce lagging signals. The default value is 64, but you can experiment with different values to find the optimal setting for your trading strategy.
Mean Ripple
The mean_ripple setting influences the Chebyshev filter's ripple effect in the passband (Type I) or stopband (Type II). The ripple effect represents small oscillations in the frequency response, which can impact the moving average's smoothness. The default value is 0.01, but you can experiment with different values to find the best balance between smoothness and responsiveness.
Chebyshev Type: Type I or Type II
The style setting allows you to choose between Type I and Type II Chebyshev filters. Type I filters have an equiripple response in the passband, while Type II filters have an equiripple response in the stopband. Depending on your preference for smoothness and responsiveness, you can choose the type that best fits your trading style.
ATR Style
The atr_style setting determines the method used for calculating the Average True Range (ATR). By default (false), it uses the traditional high-low range. When set to true, it uses the absolute difference between the open and close prices. You can choose the method that works best for your trading strategy and the market you are trading.
ATR Length
The atr_length setting controls the length (number of bars) used for calculating the ATR. Similar to the mean_length, a shorter length will make the ATR more responsive to price changes, while a longer length will produce a smoother ATR. The default value is 64, but you can experiment with different values to find the optimal setting for your trading strategy.
ATR Ripple
The atr_ripple setting, like the mean_ripple, influences the ripple effect of the Chebyshev filter used in the ATR calculation. The default value is 0.05, but you can experiment with different values to find the best balance between smoothness and responsiveness.
Multiplier
The multiplier setting determines the factor by which the ATR is multiplied before being added
Super Trend Logic and Signal Optimization
The Modified Super Trend with Chebyshev filter is designed to minimize false signals and provide a clear indication of market trends. It does so by using a combination of moving averages, Average True Range (ATR), and a multiplier. In this section, we will discuss the Super Trend's logic, its ability to prevent false signals, and the early warning crosses added to the indicator.
Super Trend Logic
The Super Trend's logic is based on a combination of the Chebyshev moving average and ATR. The Chebyshev moving average is a smooth moving average that effectively filters out market noise, while the ATR is a measure of market volatility.
The Super Trend is calculated by adding or subtracting a multiple of the ATR from the Chebyshev moving average. The multiplier is a user-defined value that determines the distance between the trend line and the price action. A larger multiplier results in a wider channel, reducing the likelihood of false signals but potentially missing out on valid trend changes.
Preventing False Signals
The Super Trend is designed to minimize false signals by maintaining its trend direction until a significant change in the market occurs. In a downtrend, the trend line will only decrease in value, and in an uptrend, it will only increase. This helps prevent false signals caused by temporary price fluctuations or market noise.
When the price crosses the trend line, the Super Trend does not immediately change its direction. Instead, it employs a safety logic to ensure that the trend change is genuine. The safety logic checks if the new trend line (calculated using the updated moving average and ATR) is more extreme than the previous one. If it is, the trend line is updated; otherwise, the previous trend line is maintained. This mechanism further reduces the likelihood of false signals by ensuring that the trend line only changes when there is a significant shift in the market.
Early Warning Crosses
To provide traders with additional insight, the Modified Super Trend with Chebyshev filter includes early warning crosses. These crosses are plotted on the chart when the price crosses the trend line without the safety logic. Although these crosses do not necessarily indicate a trend change, they can serve as a valuable heads-up for traders to monitor the market closely and prepare for potential trend reversals.
In conclusion, the Modified Super Trend with Chebyshev filter offers a significant improvement over the original Super Trend indicator. By incorporating the Chebyshev filter, this modified version effectively addresses the challenges of smoothing, delay, and noise reduction while minimizing false signals. The wide range of customizable settings allows traders to tailor the indicator to their specific needs, while the inclusion of early warning crosses provides valuable insight into potential trend reversals.
Ultimately, the Modified Super Trend with Chebyshev filter is an excellent tool for traders looking to enhance their trend identification and decision-making abilities. With its advanced features, this indicator can help traders navigate volatile markets with confidence, making more informed decisions based on accurate, timely information.
L_Trade_BoundariesLibrary "L_Trade_Boundaries"
Trade Boundaries suggest a strength of the security with respect to previous lows. The "L" implies library, and the trade boundaries implies it could be utilized for price strengths. Though, this should not be used as a single parameter to trade wildly. This library can be imported to a custom indicator to utilized the custom functions. There are moving averages attached at the bottom right of the canvas (overlay) to benchmark the closing price with respect to Moving Averages: 20, 28, and 200 (i.e., "D" if timeframe == "D") respectively. The Volume Indicator located at the top of the canvas is a default function (function already made by the trading view) this shows the volume with respect to the selected time frame. All of the indicators tell a story with regard to the security price (in strength terms).
What is available in this Library?
Litmus Color
> This is a function will change color of two numbers, if the first number is less than the second, the color will be red; otherwise, the color will be green.
Lister
> This is simply using an array by revisiting previous lows and plotting to the current time frame (i.e., "D"). There is a custom frequency input for the function, it will go back as much as the implied/specified length. Note: I am still learning how to use array, use this function with discretion. I would also appreciate if there are suggestions commented below.
Moving Average
> This function invokes three moving average metrics: 20, 28, and 200 respectively. The values are displayed at the bottom right of the canvas.
Timeframe Highlight
> This function checks for the input timeframe (i.e., "D", "W", "M") and if the time frame happens to be the same, it will give a "true" result. This result can be utilized for highlighting the positive results on the canvas (the red lines).
litmus_color(value1, value2)
Parameters:
value1
value2
lister(length)
Parameters:
length
moving_averages()
timeframe_highlight(timeframe)
Parameters:
timeframe
[blackcat] L3 Candle Skew 3821 TraderLevel 3
Background
By modeling skew to produce long and short entry points.
Function
The concept of skew comes from physics and statistics, and is used in market technical analysis to reflect the expectation of future stock price distribution. Because the return distribution of stocks in the trend market has skew (Skew), it is reasonable to judge the trend continuity according to the historical and current skew. It is precisely because the stock price rises that there is a skew. The greater the strength of the rise, the greater the angle of inclination and the greater the skew. The degree of this upward or downward slope in the statistical distribution of stock prices is defined as skew. Through the size of skew, we can know the direction, inertia and extent of the stock's rise or fall, and find stocks with a high probability of quick profit. The technical indicator introduced today is a simplified but effective stock price skew model used to generate buying and selling points.
The principle of this technical indicator is based on the success rate test results of different moving averages corresponding to different skews as follows:
10 trading cycles profit 5% success rate (%)
5 period moving average 10 period moving average 20 period moving average 30 period moving average 60 period moving average
skew>=0 51.36 52.26 52.65 52.55 52.08
skew>=0.5 55.44 58.06 60.56 62.37 65.66
skew>=1 59.72 63.06 67.07 69.78 70.62
skew>=1.5 63.01 67.08 71.61 72.9 70.61
skew>=2 65.53 70.22 74.18 73.76 70.12
skew>=2.5 67.89 72.93 75.32 73.66 68.92
skew>=3 70.07 75.32 75.69 72.54 67.45
skew>=3.5 71.85 77.05 75.32 73.63 63.82
skew>=4 73.6 78.06 74.19 68.96 59.91
skew>=4.5 76.04 78.56 72.85 69.55 49.24
skew>=5 77.44 78.88 71.58 67.28 51.69
skew>=5.5 78.97 78.39 70.33 64.31 49.7
skew>=6 79.68 78.07 68.82 61.65 53.57
Table 1
As can be seen from the above table, with the increase of the 5-period and 10-period moving average skew values, the success rate is increasing, but after the 20- and 30-period moving average skew values increase to an upper bound, it shows a downward trend. When the skew of the 20-period and 30-period moving averages is greater than 0.5, the 10-period profit of 5% is above 60%, and when it is greater than 1.5, the success rate can reach above 70%. The larger the 5-period moving average skew, the higher the success rate, but often because the short-term skew is too large, the stock price has risen rapidly to a high level, and chasing up is risky, which is not suitable for the investment habits of most people, so prudent investors may like to do swings. Investors may wish to pay more attention to the skew of the 20-period and 30-period moving averages. Based on the above analysis, as a short-term trading enthusiast, I need to choose the 5-period and 10-period moving average skew, and consider the medium-term trend as a compromise, and I also need to consider the 20-period moving average skew. Finally, according to the principle of personal preference, I chose 3 groups of periods based on Fibonacci magic numbers: 3 periods, 8 periods, 21 periods, and skews that take into account both short-term and mid-line trends. So, I named this indicator number 3821 as a distinction.
002084 1D from TradingView
BTCUSDT 1H from TradingView
Tesla 1D from TradingView
Moving Average StackTwo groups of moving averages.
Each group can have up to 3 three different moving averages.
You can choose between SMA, EMA, WMA, VWMA, or HMA for each group.
Integrated time locked capabilities so you can have long term moving averages shown on short timeframes.
Enjoy :)
crypto futures hourly scalping with ma & rsi - ogcheckershi to all lovable traders,
hereby i want to share a combination of trade ideas for scalping
i've chosen hourly timeframe
indicators used: moving averages and rsi
moving averages:
ema 3, ema 5, ema 7
sma 3, sma 5, sma 7
daily_ema_3, daily_ema_5
daily_ema_5, daily_sma_5
rsi:
rsi 7, rsi 14, rsi 26
daily_rsi_7, daily_rsi_14, daily_rsi_26
as per the analysis over moving average behavioral patterns & rsi movements, useful points are given below which will be helpful while choosing good entry points & exit points,
strategical points for LONG:
* when ema3 crosses above sma3 - green candles start to form
* it's followed by ema5 > sma5 and ema7 > sma7
* when ema3 crosses down sma3 - it's considered as an indication of exit
* if rsi supports then can wait for ema5 crossing down sma5
* as similar, when daily_ema_3 crosses above daily_sma_3, its an higher timeframe bullish indication, so the lower timeframe entries inside this higher timeframe is a sure shot confident entry
* for LONG always take entries when rsi_14 < 30 or 25 else check rsi_7 < 25 or below
* as along the above, bullish CANDLE patterns like bullish engulfing , morning star is been used for entry at lower levels
* so here i've used OPEN as rsi_source in majority
* exit points also indicated at high_rsi and moving average crossunders or reverse crossovers
* for SHORTING, the above said ideas can be used in viceversa
* inputs in the indicator were tailored for users needs so that you will enjoy the magics of customization
if i am wrong in anyways regarding the above indicator strategy, please forgive me and help me improve in this aspect by commenting.
after few more studies and analysis and mainly QUERIES & COMMENTS, i'm planning to backtest these strategies here in tradingview.
also if these strategies are coded in python, we can link it to Binance Futures Algo or Bot Trading.
thankyou for this opportunity,
thanks to tradingview and pinecoders
thanks to Pranab (for 365MA)
thanks to Gandalf (for inspiring)
Special Thanks & Love to Chartbank for Everything
Multiple MTF Variable Moving Average by HassonyaVMA(Variable Moving Average) automatically adjusts its smoothing constant on the basis of Market Volatility.
Use VMA like other Moving Averages. This indicator lazybear's variable moving average has been upgraded and arranged in multi-time frame.
There are 5 variable moving averages whose periods can be changed.
Trend Direction Colors: GREEN COLOR = UpTrend, BLUE COLOR = Potential Congestion, RED COLOR = DownTrend.
If you want, you can use multi-time frame period breakouts
If you want, you can use moving average breakouts of different lengths in the same period.
In this way, you can use 5 moving moving averages in the same period or in different periods.
To activate, go to settings and activate the box to the left of the name. If you uncheck the box, the moving average will disappear.
Stay with the trade and investment. I wish you abundance.
Multiple EMAAn exponential moving average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average (SMA), which applies an equal weight to all observations in the period.
The EMA is a moving average that places a greater weight and significance on the most recent data points.
Like all moving averages, this technical indicator is used to produce buy and sell signals based on crossovers and divergences from the historical average.
Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
Points to remember:
Exponential moving averages are more sensitive to the recent price
EMA can signal good trades, but it can also keep you out of bad trades
EMA offers dynamic support and resistance levels, which is good for trailing Stop Loss
The EMA slope shape has hidden secrets
The rules for the EMA trading strategy can be modified to fit your own trading needs. We don’t claim this to be hard rules, but they are good on their own to make for a great trading strategy. Make sure you first test out the EMA strategy on a paper trading account before you risk any of your hard-earned money
On Balance Volume FieldsThe On Balance Volume (OBV) indicator was developed by Joseph E. Granville and published first in his book "New key to stock market profits" in 1963. It uses volume to determine momentum of an asset. The base concept of OBV is - in simple terms - you take a running total of the volume and either add or subtract the current timeframe volume if the market goes up or down. The simplest use cases only use the line build that way to confirm direction of price, but the possibilities and applications of OBV go far beyond that and are (at least to my knowledge) not found in existing indicators available on this platform.
If you are interested to get a deeper understanding of OBV, I recommend the lecture of the above mentioned book by Granville. All the features described below are taken directly from the book or are inspired by it (deviations will be marked accordingly). If you have no prior experience with OBV, I recommend to start simple and read an easy introduction (e.g. On-Balance Volume (OBV) Definition from Investopedia) and start applying the basic concepts first before heading into the more advanced analysis of OBV fields and trends.
Markets and Timeframes
As the OBV is "just" a momentum indicator, it should be applicable to any market and timeframe.
As a long term investor, my experience is limited to the longer timeframes (primarily daily), which is also how Granville applies it. But that is most likely due to the time it was developed and the lack of lower timeframe data at that point in time. I don't see why it wouldn't be applicable to any timeframe, but cannot speak from experience here so do your own research and let me know. Likewise, I invest in the crypto markets almost exclusively and hence this is where my experience with this indicator comes from.
Feature List
As a general note before starting into the description of the individual features: I use the colors and values of the default settings of the indicator to describe it. The general look and feel obviously can be customized (and I highly recommend doing so, as this is a very visual representation of volume, and it should suit your way of looking at a chart) and I also tried to make the individual features as customizable as possible.
Also, all additions to the OBV itself can be turned off so that you're left with just the OBV line (although if that's what you want, I recommend a version of the indicator with less overhead).
Fields
Fields are defined as successive UPs or DOWNs on the OBV. An UP is any OBV reading above the last high pivot and subsequently a DOWN is any reading below the last low pivot. An UP-field is the time from the first UP after a DOWN-field to the first DOWN (not including). The same goes for a DOWN field but vice versa.
The field serves the same purpose as the OBV itself. To indicate momentum direction. I haven't found much use for the fields themselves other than serving as a more smoothed view on the current momentum. The real power of the fields emerges when starting to determine larger trends of off them (as you will see soon).
Therefor the fields are displayed on the indicator as background colors (UP = green, DOWN = red), but only very faint to not distract too much from the other parts of the indicator.
Major Volume Trend
The major volume trend - from which Granville says, it's the one that tends to precede price - is determined as the succession of the highest highs and lowest lows of UP and DOWN fields. It is represented by the colors of the numbers printed on the highs and lows of the fields.
The trend to be "Rising" is defined as the highest high of an UP field being higher than the highest high of the last UP field and the lowest low of the last DOWN field being higher than the lowest low of the prior DOWN field. And vice versa for a "Falling" trend. If the trend does not have a rising or falling pattern, it is said to be "Doubtful". The colors are indicated as follows:
Rising = green
Falling = red
Doubtful = blue
ZigZag Swing count
The swing count is determined by counting the number of swings within a trend (as described above) and is represented by the numbers above the highs and lows of the fields. It determines the length and thus strength of a trend.
In general there are two ways to determine the count. The first one is by counting the swings between pivots and the second one by counting the swings between highs and lows of fields. This indicator represents the SECOND one as it represents the longer term trend (which I'm more interested in as it denotes a longer term perspective).
However, the ZigZag count has three applications on the OBV. The "simple ZigZag" is a count of three swings which mainly tells you that the shorter term momentum of the market has changed and the current trend is weakening. This doesn't mean it will reverse. A count of three downs is still healthy if it occurs on a strong uptrend (and vice versa) and it should primarily serve as a sign of caution. If the count increases beyond three, the last trend is weakening considerably, and you should probably take action.
The second count to look out for is five swings - the "compound ZigZag". If this goes hand in hand with breaking a major support/resistance on the OBV it can offer a buying/selling opportunity in the direction of the trend. Otherwise, there's a good chance that this is a reversal signal.
The third count is nine. To quote Granville directly: "there is a very strong tendency FOR MAJOR REVERSAL OF REND AFTER THE NINTH SWING" (emphasis by the author). This is something I look out for and get cautious about, although I have found signal to be weak in an overextended market. I have observed counts of 10 and even 12 which did not result in a major reversal and the market trended further after a short period of time. This is still a major sign of caution and should not be taken lightly.
Moving average
Although Granville talks only briefly about averages and the only mention of a specific one is the 10MA, I found moving averages to be a very valuable addition to my analysis of the OBV movements.
The indicator uses three Exponential Moving Averages. A long term one to determine the general direction and two short term ones to determine the momentum of the trend. Especially for the latter two, keep in mind that those are very indirect as they are indicators of an indicator anyway and I they should not necessarily be used as support or resistance (although that might sometimes be helpful). I recommend paying most attention to the longterm average as I've found it to be very accurate when determining the longterm trend of a market (even better than the same indicator on the price).
If the OBV is above the long term average, the space between OBV and average is filled green and filled red if below. The colors and defaults for the averages are:
long term, 144EMA, green
short term 1, 21EMA, blue
short term 2, 55EMA, red
Divergences
This is a very rudimentary adaption of the standard TradingView "Divergence Indicator". I find it helpful to have these on the radar, but do not actively use them (as in having a strategy based on OBV/price divergence). This is something that I would eventually pick up in a later version of the indicator if there is any demand for it, or I find the time to look into strategies based on this.
Comparison line
A small but very helpful addition to the indicator is a horizontal line that traces the current OBV value in real time, which makes it very easy to compare the current value of the OBV to historic values (which is a study I can highly recommend).
All MAs displayedThis is a collection of moving averages.
Thanks to everget and other pinecoders to pubblish their codes in tradingview.
I just collect a lot of moving averages in one script and transform them in stand alone functions, so you can copy and paste in your script the MA that best fit your needs.
Furthermore, the chart shows which moving average has more smooth and which one has less lag and so on: in this way it is easy to graphically compare moving averages.
Filter Amplitude Response Estimator - A Simple CalculationIn digital signal processing knowing how a system interact with the frequency content of an input signal is extremely important, the mathematical tool that give you this information is called "frequency response". The frequency response regroup two elements, the amplitude response, and the phase response. The amplitude response tells you how the system modify the amplitude of the frequency components in the input signal, the phase response tells you how the system modify the phase of the frequency components in the signal, each being a function of the frequency.
The today proposed tool aim to give a low resolution representation of the amplitude response of any filter.
What Is The Amplitude Response Of A Filter ?
Remember that filters allow to interact with the frequency content of a signal by amplifying, attenuating and/or removing certain frequency components in the input signal, the amplitude (also called magnitude) response of a filter let you know exactly how your filter change the amplitude of the frequency components in the input signal, another way to see the amplitude response is as a tool that tell you what is the peak amplitude of a filter using a sinusoid of a certain frequency as input signal.
For example if the amplitude response of a filter give you a value of 0.9 at frequency 0.5, it means that the filter peak amplitude using a sinusoid of frequency 0.5 is equal to 0.9.
There are several ways to calculate the frequency response of a filter, when our filter is a FIR filter (the filter impulse response is finite), the frequency response of the filter is the absolute value of the discrete Fourier transform (DFT) of the filter impulse response.
If you are curious about this process, know that the DFT of a N samples signal return N values, so if our FIR filter coefficients are composed of only 5 values we would get a frequency response of 5 values...which would not be useful, this is why we "pad" our coefficients with zeros, that is we add zeros to the start and end of our series of coefficients, this process is called "zero-padding", so if our series of coefficients is: (1,2,3,4,5), applying zero padding would give (0,0...1,2,3,4,5,...0,0) while keeping a certain symmetry. This is related to the concept of resolution, a low resolution amplitude response would be composed of a low number of values and would not be useful, this is why we use zero-padding to add more values thus increasing the resolution.
Making a Fourier transform in Pinescript is not doable, as you need the complex number i for computing a DFT, but thats not even the only problem, a DFT would not be that useful anyway (as the processes to make it useful in a trading context would be way too complex) . So how can we calculate a filter amplitude response without using a DFT ? The simple answer is by taking the peak amplitude of a filter using a sinusoid of a certain frequency as input, this is what the proposed tool do.
Using The Tool
The proposed tool give you a 50 point amplitude response from frequency 0.005 to 0.25 by default. the setting "Range Divisor" allow you to see the amplitude response by using a different range of frequency, for example if the range divisor is equal to 2 the filter amplitude response will be evaluated from frequency 0.0025 to 0.125.
In the script, filt hold the filter you want to see the frequency response, by default a simple moving average.
The position of the frequency response is defined by the "Show Amplitude Response At Bar Number" setting, if you want the frequency response to start at bar number 5000 then enter 5000, by default 10000. If you are not a premium set the number at 4000 and it should work.
amplitude response of a simple moving average of period 14, res = 2.
By default the amplitude response use an amplitude scale, a value of 1 represent an unchanged amplitude. You can use Dbfs (decibel full scale) instead by checking the "To Decibels (Full Scale)" setting.
Dbfs amplitude response, a value of 0 represent an unchanged amplitude.
Some Amplitude Responses
In order to prove the accuracy of the proposed tool we can compare the amplitude response given by the proposed tool with the mathematical function of the amplitude response of a simple moving average, that is:
abs(sin(pi*f*length)/(length*sin(pi*f)))
In cyan the amplitude response given by the proposed tool and in blue the above function. Below are the amplitude responses of some moving averages with period 14.
Amplitude response of an EMA, the EMA is a IIR filter, therefore the amplitude response can't be made by taking the DFT of the impulse response (as this ones has infinite length), however our tool can give its frequency response.
Amplitude response of the Hull MA, as you can see some frequencies are amplified, this is common with low-lag filters.
Gaussian moving average (ALMA), with offset = 0.5 and sigma = 6.
Simple moving average high-pass filter amplitude response
Center of gravity bandpass filter amplitude response
Center of gravity bandreject filter.
IMPORTANT!: The amplitude response of adaptive moving averages is not stationary and might change over time.
Conclusion
A tool giving the amplitude response of any filter has been presented, of course this method is not efficient at all and has a low resolution of 50 points (the common resolution is of 512 points) and is difficult to work with, but has the merit to work on Tradingview and can give the frequency response of IIR filters, if you really need to see the frequency response of a filter then i recommend you to use the function freqz from the scipy package.
I still hope you will enjoy using this tool to have a look at the amplitude responses of your favorite moving averages.
I'am aware of the current situation, however i'am somehow feeling left out from the pinescript community, let me know via PM if i have done something to you and i'll do my best to fix any problems i might have caused (or i might be being parano xD)
Multi Time Frame Exponential Moving AverageThis indicator allows you to reference exponential moving averages from other time frames
Same indicator for simple moving averages:
[blackcat] L3 Twin Range Filter ProOVERVIEW
The L3 Twin Range Filter Pro indicator enhances trading strategies by filtering out market noise through a sophisticated dual-range approach. Unlike previous versions, this script not only provides clear visual indications of buy/sell signals but also incorporates a dynamic trend range filter line. By averaging two smoothed exponential moving averages—one fast and one slow—the indicator generates upper and lower range boundaries that adapt to changing market conditions. Traders can easily spot buy/sell opportunities when the closing price crosses these boundaries, supported by configurable alerts for real-time notifications.
FEATURES
Dual-Range Calculation: Combines fast and slow moving averages to create adaptive range boundaries.
Customizable Parameters:
Periods: Adjustable lengths for fast (default 9 bars) and slow (default 34 bars) moving averages.
Multipliers: Coefficients to modify the distance of the trailing lines from the price.
Dynamic Trend Range Filter Line: Visually displays buy/sell signals directly on the chart.
Trailing Stop Loss Logic: Automatically follows price movements to act as a trailing stop loss indicator.
Trade Signals: Clearly indicates buy/sell points with labeled signals.
Alerts: Configurable notifications for buy/sell signals to keep traders informed.
Visual Enhancements: Colored fills and dynamic boundary lines for easy interpretation.
HOW TO USE
Add the L3 Twin Range Filter Pro indicator to your TradingView chart.
Customize the input parameters:
Price Source: Choose the desired price source (e.g., Close).
Show Trade Signals: Toggle on/off for displaying buy/sell labels.
Fast Period: Set the period for the fast moving average (default 9 bars).
Slow Period: Set the period for the slow moving average (default 34 bars).
Fast Range Multiplier: Adjust the multiplier for the fast moving average.
Slow Range Multiplier: Adjust the multiplier for the slow moving average.
Monitor the plotted trend range filter and dynamic boundaries on the chart.
Identify buy/sell signals based on the crossing of price and range boundaries.
Configure alerts for real-time notifications when signals are triggered.
TRADE LOGIC
BUY Signal: Triggered when the price is higher than or equal to the upper range level. The indicator line will trail just below the price, acting as a trailing stop loss.
SELL Signal: Triggered when the price is lower than or equal to the lower range level. The indicator line will trail just above the price, serving as a trailing stop loss.
LIMITATIONS
The performance of this indicator relies on the selected periods and multipliers.
Market volatility can impact the accuracy of the signals.
Always complement this indicator with other analytical tools for robust decision-making.
NOTES
Experiment with different parameter settings to optimize the indicator for various market conditions.
Thoroughly backtest the indicator using historical data to ensure its compatibility with your trading strategy.
THANKS
A big thank you to Colin McKee for his foundational work on the Twin Range Filter! Your contributions have paved the way for enhanced trading tools. 🙏📈🔍
