WAGMI LAB Trend Reversal Indicator HMA-Kahlman (m15)WAGMI HMA-Kahlman Trend Reversal Indicator
This indicator combines the Hull Moving Average (HMA) with the Kahlman filter to provide a dynamic trend reversal signal, perfect for volatile assets like Bitcoin. The strategy works particularly well on lower timeframes, making it ideal for intraday trading and fast-moving markets.
Key Features:
Trend Detection: It uses a blend of HMA and Kahlman filters to detect trend reversals, providing more accurate and timely signals.
Volatility Adaptability: Designed with volatile assets like Bitcoin in mind, this indicator adapts to rapid price movements, offering smoother trend detection during high volatility.
Easy Visualization: Buy (B) and Sell (S) signals are clearly marked with labels, helping traders spot trend shifts quickly and accurately.
Trendlines Module: The indicator plots trendlines based on pivot points, highlighting important support and resistance levels. This helps traders understand the market structure and identify potential breakout or breakdown zones.
Customizable: Adjust the HMA and Kahlman parameters to fit different assets or trading styles, making it flexible for various market conditions.
Usage Tips:
Best Timeframes: The indicator performs exceptionally well on lower timeframes (such as 15-minute to 1-hour charts), making it ideal for scalping and short-term trading strategies.
Ideal for Volatile Assets: This strategy is perfect for highly volatile assets like Bitcoin, but can also be applied to other cryptocurrencies and traditional markets with high price fluctuations.
Signal Confirmation: Use the trend signals (green for uptrend, red for downtrend) along with the buy/sell labels to help you confirm potential entries and exits. It's also recommended to combine the signals with other technical tools like volume analysis or RSI for enhanced confirmation.
Trendline Analysis: The plotted trendlines provide additional visual context to identify key market zones, supporting your trading decisions with a clear view of ongoing trends and possible reversal areas.
Risk Management: As with any strategy, always consider proper risk management techniques, such as stop-loss and take-profit levels, to protect against unforeseen market moves.
Cerca negli script per "trend"
Volume & Trend Confluence OscillatorVolume & Trend Confluence Oscillator (VTCO)
Overview:
The Volume & Trend Confluence Oscillator (VTCO) is a technical analysis tool designed to help traders assess market conditions by integrating volume analysis, momentum, and trend direction into a single oscillator. This indicator provides traders with additional confirmation when evaluating potential trade entries and exits.
Key Features:
Volume Analysis: Calculates a Z-score to detect unusual trading activity.
Momentum Measurement: Evaluates the rate of price change to gauge market velocity.
Trend Confirmation: Utilizes an Exponential Moving Average (EMA) to assess overall market direction.
Signal Filtering: Incorporates minimum movement thresholds and a confirmation period to reduce false signals.
Visual Enhancements: Background shading indicates trend direction, and buy/sell markers highlight key signals.
How It Works:
The VTCO applies a volume multiplier to momentum readings when volume activity significantly deviates from its historical norm. Additionally, it prioritizes momentum moves that align with the prevailing market trend. A smoothing mechanism refines the oscillator’s signal line, ensuring a more stable and actionable output. The indicator generates alerts when key conditions are met, assisting traders in identifying potential trend shifts.
Signal Generation:
Buy Signal: Triggered when the oscillator crosses above zero after an oversold condition, ideally within an uptrend.
Sell Signal: Triggered when the oscillator crosses below zero after an overbought condition, ideally within a downtrend.
Alerts: Configurable alerts notify traders when key market conditions are met.
Usage Considerations:
Works effectively across various timeframes but may provide more reliable signals on higher timeframes.
Best utilized in conjunction with additional technical indicators and risk management strategies.
No indicator guarantees future performance; proper analysis and trade management remain essential.
Disclaimer:
This indicator is provided for educational purposes only and should not be considered financial advice. Trading involves risk, and past performance is not indicative of future results. Always conduct independent analysis before making trading decisions.
Instantaneous Trendline with Cloud Instantaneous Trendline with Cloud
Introduction & History
The Instantaneous Trendline was introduced by John Ehlers, a well-known figure in the field of technical analysis, particularly for applying digital signal processing concepts to financial markets. Ehlers aimed to create an indicator that reacts to market price changes more quickly than traditional moving averages, yet remains smooth enough to avoid excessive noise. By incorporating concepts from digital filtering, he devised a formula that calculates a trendline with minimal lag—hence the term “instantaneous.”
Purpose
The primary purpose of the Instantaneous Trendline with Cloud is to provide traders and analysts with a responsive, smoothed line that closely follows market price movements. Additionally, this script enhances the visual cues by adding a cloud fill to highlight bullish and bearish zones:
Trend Identification
The ITL (Instantaneous Trendline) is plotted alongside the price. When price consistently stays above the ITL, it may signal an uptrend. Conversely, when price dips below the ITL, it can suggest a downtrend.
Signal Generation
Crossover points between the price and the ITL can serve as potential entry or exit signals. A bullish crossover (price moving above the ITL) often indicates the start of upward momentum, while a bearish crossover (price dropping below the ITL) may point to downward momentum.
Noise Reduction
By applying digital filtering concepts and smoothing through the alpha (smoothing coefficient), the ITL reduces noise while still responding relatively quickly to price changes. Traders can adjust alpha to make the trendline more reactive (higher alpha) or smoother (lower alpha).
Clarity via Cloud Fill
A color-coded cloud between the price and the ITL provides an at-a-glance view of market bias. The green cloud highlights potentially bullish phases, while the red cloud highlights potentially bearish phases.
Experiment with the alpha value (commonly between 0.2 and 0.3) to find a balance that suits your preference for responsiveness versus smoothness.
This indicator implements John Ehlers’ Instantaneous Trendline concept and plots a smoothed trendline (ITL) alongside the price. The trendline is controlled by a user-defined smoothing coefficient (alpha). A higher alpha makes the trendline respond more quickly to price changes, while a lower alpha produces a smoother line.
A color-filled cloud helps traders identify bullish and bearish conditions:
Green cloud if the price is above the ITL (bullish potential).
Red cloud if the price is below the ITL (bearish potential).
Key Benefits
Trend Visualization: Quickly see if the market is in an uptrend or downtrend based on the position of the price relative to the trendline.
Crossover Signals: Identify potential shifts in trend or momentum when the price crosses the ITL.
Customizable Sensitivity: Adjust the alpha parameter to make the ITL more or less reactive to price moves. Use this tool to better visualize short-term trend changes and potential entry/exit signals in conjunction with other technical analysis methods.
Fibonacci Trend [ChartPrime]Fibonacci Trend Indicator
This powerful indicator leverages supertrend analysis to detect market direction while overlaying dynamic Fibonacci levels to highlight potential support, resistance, and optimal trend entry zones. With its straightforward design, it is perfect for traders looking to simplify their workflow and enhance decision-making.
⯁ KEY FEATURES AND HOW TO USE
⯌ Supertrend Trend Identification :
The indicator uses a supertrend algorithm to identify market direction. It displays purple for downtrends and green for uptrends, ensuring quick and clear trend analysis.
⯌ Fibonacci Levels for Current Swings :
Automatically calculates Fibonacci retracement levels (0.236, 0.382, 0.618, 0.786) for the current swing leg.
- These levels act as key zones for potential support, resistance, and trend continuation.
- The high and low swing points are labeled with exact prices, ensuring clarity.
- If the swing range is insufficient (less than five times ATR), Fibonacci levels are not displayed, avoiding irrelevant data.
⯌ Extended Fibonacci Levels :
User-defined extensions project Fibonacci levels into the future, aiding traders in planning price targets or projecting key zones.
⯌ Optimal Trend Entry Zone :
A filled area between 0.618 and 0.786 levels visually highlights the optimal entry zone for trend continuation. This allows traders to refine their entry points during pullbacks.
⯌ Diagonal Trend Line :
A dashed diagonal line connects the swing high and low, visually confirming the range and trend strength of the current swing.
⯌ Visual Labels for Fibonacci Levels :
Each Fibonacci level is marked with a label displaying its value for quick reference.
⯁ HOW TRADERS CAN POTENTIALLY USE THIS TOOL
Fibonacci Retracements:
Use the Fibonacci retracement levels to find key support or resistance zones where the price may pull back before continuing its trend.
Example: Enter long trades when the price retraces to 0.618–0.786 levels in an uptrend.
Fibonacci Extensions:
Use Fibonacci extensions to project future price targets based on the current trend's swing leg. Levels like 127.2% and 161.8% are commonly used as profit-taking zones.
Reversal Identification:
Spot potential reversals by monitoring price reactions at key Fibonacci retracement levels (e.g., 0.236 or 0.382) or the swing high/low.
Optimal Trend Entries:
The filled zone between 0.618 and 0.786 is a statistically strong area for entering a position in the direction of the trend.
Example: Enter long positions during retracements to this range in an uptrend.
Risk Management:
Set stop-losses below key Fibonacci levels or the swing low/high, and take profits at extension levels, enhancing your trade management strategies.
⯁ CONCLUSION
The Fibonacci Trend Indicator is a straightforward yet effective tool for identifying trends and key Fibonacci levels. It simplifies analysis by integrating supertrend-based trend identification with Fibonacci retracements, extensions, and optimal entry zones. Whether you're a beginner or experienced trader, this indicator is an essential addition to your toolkit for trend trading, reversal spotting, and risk management.
[ADDYad] Google Search Trends - Bitcoin (2012 Jan - 2025 Jan)This Pine Script shows the Google Search Trends as an indicator for Bitcoin from January 2012 to January 2025, based on monthly data retrieved from Google Trends. It calculates and displays the relative search interest for Bitcoin over time, offering a historical perspective on its popularity mainly built for BITSTAMP:BTCUSD .
Important note: This is not a live indicator. It visualizes historical search trends based on Google Trends data.
Key Features:
Data Source : Google Trends (Last retrieved in January 10 2025).
Timeframe : The script is designed to be used on a monthly chart, with the data reflecting monthly search trends from January 2012 to January 2025. For other timeframes, the data is linearly interpolated to estimate the trends at finer resolutions.
Purpose : This indicator helps visualize Bitcoin's search interest over the years, offering insights into public interest and sentiment during specific periods (e.g., major price movements or news events).
Data Handling : The data is interpolated for use on non-monthly timeframes, allowing you to view search trends on any chart timeframe. This makes it versatile for use in longer-term analysis or shorter timeframes, despite the raw data being available only on a monthly basis. However, it is most relevant for Monthly, Weekly, and Daily timeframes.
How It Works:
The script calculates the number of months elapsed since January 1, 2012, and uses this to interpolate Google Trends data values for any given point in time on the chart.
The linear interpolation function adjusts the monthly data to provide an approximate trend for intermediate months.
Why It's Useful:
Track Bitcoin's historic search trends to understand how interest in Bitcoin evolved over time, potentially correlating with price movements.
Correlate search trends with price action and other market indicators to analyze the effects of public sentiment and sentiment-driven market momentum.
Final Notes:
This script is unique because it shows real-world, non-financial dataset (Google Trends) to understand price action of Bitcoin correlating with public interest. Hopefully is a valuable addition to the TradingView community.
ADDYad
Improved G-Trend DetectionIt is the Improved version of G trend channel detection.
The Umair Trend Detection Indicator is a powerful tool designed to help traders identify potential buy and sell opportunities by combining dynamic price channels with RSI-based confirmation. This indicator is suitable for all types of financial markets, including stocks, forex, and cryptocurrencies.
Key Features:
Dynamic G-Channels
Calculates upper, lower, and average price channels based on the "G-Channel" methodology.
Helps identify market extremes and potential reversal points.
RSI Confirmation
Integrates RSI (Relative Strength Index) to filter buy and sell signals.
Avoids false signals by ensuring market momentum aligns with trend direction.
Buy/Sell Signals
Generates "Buy" signals when bullish conditions align with oversold RSI levels.
Generates "Sell" signals when bearish conditions align with overbought RSI levels.
Exit Signals
Provides optional exit points for both long and short positions using a buffer for confirmation.
Visual Clarity
Displays clearly plotted channels and average lines to help visualize price trends.
Buy and sell signals are marked with arrows for easy identification on the chart.
Custom Alerts
Offers customizable alerts for buy, sell, and exit conditions, ensuring traders never miss an opportunity.
Input Parameters:
Channel Length: Controls the sensitivity of the G-Channels.
Multiplier: Adjusts the width of the channels to suit different market conditions.
RSI Settings: Customize RSI length and thresholds for overbought/oversold conditions.
Exit Signal Buffer: Adds flexibility to the exit strategy by delaying signals for confirmation.
How It Helps:
The Umair Trend Detection Indicator is perfect for traders looking for an easy-to-use trend-following system with strong confirmation. By combining dynamic channels with RSI, it provides accurate and reliable signals to enter and exit trades, minimizing risks associated with false breakouts or trend reversals.
Use Cases:
Trend Trading: Identify and follow long-term trends with confidence.
Swing Trading: Spot reversals and capitalize on medium-term price movements.
Risk Management: Use exit signals to lock in profits or limit losses effectively.
This indicator is a versatile tool for both novice and experienced traders. Fine-tune its settings to align with your trading style and improve your decision-making in any market.
Temporary Help Services Jobs - Trend Allocation StrategyThis strategy is designed to capitalize on the economic trends represented by the Temporary Help Services (TEMPHELPS) index, which is published by the Federal Reserve Economic Data (FRED). Temporary Help Services Jobs are often regarded as a leading indicator of labor market conditions, as changes in temporary employment levels frequently precede broader employment trends.
Methodology:
Data Source: The strategy uses the FRED dataset TEMPHELPS for monthly data on temporary help services.
Trend Definition:
Uptrend: When the current month's value is greater than the previous month's value.
Downtrend: When the current month's value is less than the previous month's value.
Entry Condition: A long position is opened when an uptrend is detected, provided no position is currently held.
Exit Condition: The long position is closed when a downtrend is detected.
Scientific Basis:
The TEMPHELPS index serves as a leading economic indicator, as noted in studies analyzing labor market cyclicality (e.g., Katz & Krueger, 1999). Temporary employment is often considered a proxy for broader economic conditions, particularly in predicting recessions or recoveries. Incorporating this index into trading strategies allows for aligning trades with potential macroeconomic shifts, as suggested by research on employment trends and market performance (Autor, 2001; Valetta & Bengali, 2013).
Usage:
This strategy is best suited for long-term investors or macroeconomic trend followers who wish to leverage labor market signals for equity or futures trading. It operates exclusively on end-of-month data, ensuring minimal transaction costs and noise.
Kalman Trend Strength Index (K-TSI)The Kalman Trend Strength Index (K-TSI) is an innovative technical indicator that combines the Kalman filter with correlation analysis to measure trend strength in financial markets. This sophisticated tool aims to provide traders with a more refined method for trend analysis and market dynamics interpretation.
The use of the Kalman filter is a key feature of the K-TSI. This advanced algorithm is renowned for its ability to extract meaningful signals from noisy data. In financial markets, this translates to smoothing out price action while maintaining responsiveness to genuine market movements. By applying the Kalman filter to price data before performing correlation analysis, the K-TSI potentially offers more stable and reliable trend signals.
The synergy between the Kalman-filtered price data and correlation analysis creates an oscillator that attempts to capture market dynamics more effectively. The correlation component contributes by measuring the strength and consistency of price movements relative to time, while the Kalman filter adds robustness by reducing the impact of market noise. Basing these calculations on Kalman-filtered data may help reduce false signals and provide a clearer picture of underlying market trends.
A notable aspect of the K-TSI is its normalization process. This approach adjusts the indicator's values to a standardized range (-1 to 1), allowing for consistent interpretation across different market conditions and timeframes. This flexibility, combined with the noise-reduction properties of the Kalman filter, positions the K-TSI as a potentially useful tool for various market environments.
In practice, traders might find that the K-TSI offers several potential benefits:
Smoother trend identification, which could aid in detecting the start and end of trends more accurately.
Possibly reduced false signals, particularly in choppy or volatile markets.
Potential for improved trend strength assessment, which might lead to more confident trading decisions.
Consistent performance across different timeframes, due to the adaptive nature of the Kalman filter and the normalization process.
The K-TSI's visual representation as a color-coded histogram further enhances its utility. The changing colors and intensities provide an intuitive way to gauge both the direction and strength of trends, making it easier for traders to quickly assess market conditions.
While the K-TSI builds upon existing concepts in technical analysis, its integration of the Kalman filter with correlation analysis offers traders an interesting tool for market analysis. It represents an attempt to address common challenges in technical analysis, such as noise reduction and trend strength quantification.
As with any technical indicator, the K-TSI should be used as part of a broader trading strategy rather than in isolation. Its effectiveness will depend on how well it aligns with a trader's individual approach and market conditions. For traders looking to explore a more refined trend strength oscillator, the Kalman Trend Strength Index could be a worthwhile addition to their analytical toolkit.
ADX and DI Trend meter and status table IndicatorThis ADX (Average Directional Index) and DI (Directional Indicator) indicator helps identify:
Trend Direction & Strength:
LONG: +DI above -DI with ADX > 20
SHORT: -DI above +DI with ADX > 20
RANGE: ADX < 20 indicates choppy/sideways market
Trading Signals:
Bullish: +DI crosses above -DI (green triangle)
Bearish: -DI crosses below +DI (red triangle)
ADX Strength Levels:
Strong: ADX ≥ 50
Moderate: ADX 30-49
Weak: ADX 20-29
No Trend: ADX < 20
Best Uses:
Trend confirmation before entering trades
Identifying ranging vs trending markets
Exit signal when trend weakens
Works well on multiple timeframes
Most effective in combination with other indicators
The table displays current trend direction and ADX strength in real-time
Volatility-Adjusted Trend Deviation Statistics (C-Ratios)The Pine Script logic provided generates and displays a table with key information derived from VWMA, EMA, and ATR-based "C Ratios," alongside stochastic oscillators, correlation coefficients, Z-scores, and bias indicators. Here’s an explanation of the logic and what the output in the table informs:
Key Calculations and Their Purpose
VWMA and EMA (Smoothing Lengths):
Multiple EMAs are calculated using VWMA as the source, with lengths spanning short-term (13) to long-term (233).
These EMAs provide a hierarchy of smoothed price levels to assess trends over various time horizons.
ATR-Based "C Ratios":
The C Ratios measure deviations of smoothed prices (a_1 to a_7) from the source price relative to ATR at corresponding lengths.
These values normalize deviations, giving insight into the price's relative movement strength and direction over various periods.
Stochastic Oscillator for C Ratios:
Calculates normalized stochastic values for each C Ratio to assess overbought/oversold conditions dynamically over a rolling window.
Helps identify short-term momentum trends within the broader context of C Ratios.
Displays the average stochastic value derived from all C Ratios.
Text: Shows overbought/oversold conditions (Overbought, Oversold, or ---).
Color: Green for strong upward momentum, red for downward, and white for neutral.
Weighted and Mean C Ratio:
The script computes both an arithmetic mean (c_mean) and a weighted mean (c_mean_w) for all C Ratios.
Weighted mean emphasizes short-term values using predefined weights.
Trend Bias and Reversal Detection:
The script calculates Z-scores for c_mean to identify statistically significant deviations.
It combines Z-scores and weighted C Ratio values to determine:
Bias (Bullish/Bearish based on Z-score thresholds and mean values).
Reversals (Based on relative positioning and how the weighted c_mean and un-weighted C_mean move. ).
Correlation Coefficient:
Correlation of mean C Ratios (c_mean) with bar indices over the short-term length (sl) assesses the strength and direction of trend consistency.
Table Output and Its Meaning
Stochastic Strength:
Long-term Correlation:
List of Lengths: Define the list of lengths for EMA and ATR explicitly (e.g., ).
Calculate Mean C Ratios: For each length in the list, calculate the mean C Ratio
Average these values over the entire dataset.
Store Lengths and Mean C Ratios: Maintain arrays for lengths and their corresponding mean C Ratios.
Correlation: compute the Pearson correlation between the list of lengths and the mean C Ratios.
Text: Indicates Uptrend, Downtrend, or neutral (---).
Color: Green for positive (uptrend), red for negative (downtrend), and white for neutral.
Z-Score Bias:
Assesses the statistical deviation of C Ratios from their historical mean.
Text: Bullish Bias, Bearish Bias, or --- (neutral).
Color: Green or red based on the direction and significance of the Z-score.
C-Ratio Mean:
Displays the weighted average C Ratio (c_mean_w) or a reversal condition.
Text: If no reversal is detected, shows c_mean_w; otherwise, a reversal condition (Bullish Reversal, Bearish Reversal).
Color: Indicates the strength and direction of the bias or reversal.
Practical Insights
Trend Identification: Correlation coefficients, Z-scores, and stochastic values collectively highlight whether the market is trending and the trend's direction.
Momentum and Volatility: Stochastic and ATR-normalized C Ratios provide insights into the momentum and price movement consistency across different timeframes.
Bias and Reversal Detection: The script highlights potential shifts in market sentiment or direction (bias or reversal) using statistical measures.
Customization: Users can toggle plots and analyze specific EMA lengths or focus on combined metrics like the weighted C Ratio.
Potential Upcoming Trend ToolThis Script has the specific use of identifying when and how a new trend may start to take form, rather than focusing on how a trend has already formed on a longer term basis.
This Script is useful on it's own and not in conjunction with another. It works by taking on the most recent price data rather than a long term historical string.
It differs from standard trend following indicators because it's use is far less historical, and more present. It requires less pivot points than normal to be validated as a strong trend.
It works by taking local pivot points and fractals to form its parallel basis. The Trend lines will continually move as more recent price action data appears and the the channel will get thinner, until it is clear a trend has arrived and consolidated.
The idea really is to see a constantly evolving picture of a sudden change in movement, allowing you to have an earlier eye on what is potentially to come.
The faint mid-point line gives a reasonable reading of where you would find yourself halfway within a new trend and will also move inline with the shown trendlines.
This allows you to easily track when sentiment and therefore trends are about to change. It's much more useful on lower timeframes because they will often give the first indication something is changing.
Colours are fully customisable.
TechniTrend: Volatility and MACD Trend Highlighter🟦 Overview
The "Candle Volatility with Trend Prediction" indicator is a powerful tool designed to identify market volatility based on candle movement relative to average volume while also incorporating trend predictions using the MACD. This indicator is ideal for traders who want to detect volatile market conditions and anticipate potential price movements, leveraging both price changes and volume dynamics.
It not only highlights candles with significant price movements but also integrates a trend analysis based on the MACD (Moving Average Convergence Divergence), allowing traders to gauge whether the market momentum aligns with or diverges from the detected volatility.
🟦 Key Features
🔸Volatility Detection: Identifies candles that exceed normal price fluctuations based on average volume and recent price volatility.
🔸Trend Prediction: Uses the MACD indicator to overlay trend analysis, signaling potential market direction shifts.
🔸Volume-Based Analysis: Integrates customizable moving averages (SMA, EMA, WMA, etc.) of volume, providing a clear visualization of volume trends.
🔸Alert System: Automatically notifies traders of high-volatility situations, aiding in timely decision-making.
🔸Customizability: Includes multiple settings to tailor the indicator to different market conditions and timeframes.
🟦 How It Works
The indicator operates by evaluating the price volatility in relation to average volume and identifying when a candle's volatility surpasses a threshold defined by the user. The key calculations include:
🔸Average Volume Calculation: The user selects the type of moving average (SMA, EMA, etc.) to calculate the average volume over a set period.
🔸Volatility Measurement: The indicator measures the body change (difference between open and close) and the high-low range of each candle. It then calculates recent price volatility using a standard deviation over a user-defined length.
🔸Weighted Index: A unique index is created by dividing price change by average volume and recent volatility.
🔸Highlighting Volatility: If the weighted index exceeds a customizable threshold, the candle is highlighted, indicating potential trading opportunities.
🔸Trend Analysis with MACD: The MACD line and signal line are plotted and adjusted with a user-defined multiplier to visualize trends alongside the volatility signals.
🟦 Recommended Settings
🔸Volume MA Length: A default of 14 periods for the average volume calculation is recommended. Adjust to higher periods for long-term trends and shorter periods for quick trades.
🔸Volatility Threshold Multiplier: Set at 1.2 by default to capture moderately significant movements. Increase for fewer but stronger signals or decrease for more frequent signals.
🔸MACD Settings: Default MACD parameters (12, 26, 9) are suggested. Tweak based on your trading strategy and asset volatility.
🔸MACD Multiplier: Adjust based on how the MACD should visually compare to the average volume. A multiplier of 1 works well for most cases.
🟦 How to Use
🔸Volatile Market Detection:
Look for highlighted candles that suggest a deviation from typical price behavior. These candles often signify an entry point for short-term trades.
🔸Trend Confirmation:
Use the MACD trend analysis to verify if the highlighted volatile candles align with a bullish or bearish trend.
For example, a bullish MACD crossover combined with a highlighted candle suggests a potential uptrend, while a bearish crossover with volatility signals may indicate a downtrend.
🔸Volume-Driven Strategy:
Observe how volume changes impact candle volatility. When volume rises significantly and candles are highlighted, it can suggest strong market moves influenced by big players.
🟦 Best Use Cases
🔸Trend Reversals: Detect potential trend reversals early by spotting divergences between price and MACD within volatile conditions.
🔸Breakout Strategies: Use the indicator to confirm price breakouts with significant volume changes.
🔸Scalping or Day Trading: Customize the indicator for shorter timeframes to capture rapid market movements based on volatility spikes.
🔸Swing Trading: Combine volatility and trend insights to optimize entry and exit points over longer periods.
🟦 Customization Options
🔸Volume-Based Inputs: Choose from SMA, EMA, WMA, and more to define how average volume is calculated.
🔸Threshold Adjustments: Modify the volatility threshold multiplier to increase or decrease sensitivity based on your trading style.
🔸MACD Tuning: Adjust MACD settings and the multiplier for trend visualization tailored to different asset classes and market conditions.
🟦 Indicator Alerts
🔸High Volatility Alerts: Automatically triggered when candles exceed user-defined volatility levels.
🔸Bullish/Bearish Trend Alerts: Alerts are activated when highlighted volatile candles align with bullish or bearish MACD crossovers, making it easier to spot opportunities without constantly monitoring the chart.
🟦 Examples of Use
To better understand how this indicator works, consider the following scenarios:
🔸Example 1: In a strong uptrend, observe how volume surges and volatility highlight candles right before price consolidations, indicating optimal exit points.
🔸Example 2: During a downtrend, see how the MACD aligns with volume-driven volatility, signaling potential short-selling opportunities.
Adaptive Kalman filter - Trend Strength Oscillator (Zeiierman)█ Overview
The Adaptive Kalman Filter - Trend Strength Oscillator by Zeiierman is a sophisticated trend-following indicator that uses advanced mathematical techniques, including vector and matrix operations, to decompose price movements into trend and oscillatory components. Unlike standard indicators, this model assumes that price is driven by two latent (unobservable) factors: a long-term trend and localized oscillations around that trend. Through a dynamic "predict and update" process, the Kalman Filter leverages vectors to adaptively separate these components, extracting a clearer view of market direction and strength.
█ How It Works
This indicator operates on a trend + local change Kalman Filter model. It assumes that price movements consist of two underlying components: a core trend and an oscillatory term, representing smaller price fluctuations around that trend. The Kalman Filter adaptively separates these components by observing the price series over time and performing real-time updates as new data arrives.
Predict and Update Procedure: The Kalman Filter uses an adaptive predict-update cycle to estimate both components. This cycle allows the filter to adjust dynamically as the market evolves, providing a smooth yet responsive signal. The trend component extracted from this process is plotted directly, giving a clear view of the prevailing direction. The oscillatory component indicates the tendency or strength of the trend, reflected in the green/red coloration of the oscillator line.
Trend Strength Calculation: Trend strength is calculated by comparing the current oscillatory value against a configurable number of past values.
█ Three Kalman filter Models
This indicator offers three distinct Kalman filter models, each designed to handle different market conditions:
Standard Model: This is a conventional Kalman Filter, balancing responsiveness and smoothness. It works well across general market conditions.
Volume-Adjusted Model: In this model, the filter’s measurement noise automatically adjusts based on trading volume. Higher volumes indicate more informative price movements, which the filter treats with higher confidence. Conversely, low-volume movements are treated as less informative, adding robustness during low-activity periods.
Parkinson-Adjusted Model: This model adjusts measurement noise based on price volatility. It uses the price range (high-low) to determine the filter’s sensitivity, making it ideal for handling markets with frequent gaps or spikes. The model responds with higher confidence in low-volatility periods and adapts to high-volatility scenarios by treating them with more caution.
█ How to Use
Trend Detection: The oscillator oscillates around zero, with positive values indicating a bullish trend and negative values indicating a bearish trend. The further the oscillator moves from zero, the stronger the trend. The Kalman filter trend line on the chart can be used in conjunction with the oscillator to determine the market's trend direction.
Trend Reversals: The blue areas in the oscillator suggest potential trend reversals, helping traders identify emerging market shifts. These areas can also indicate a potential pullback within the prevailing trend.
Overbought/Oversold: The thresholds, such as 70 and -70, help identify extreme conditions. When the oscillator reaches these levels, it suggests that the trend may be overextended, possibly signaling an upcoming reversal.
█ Settings
Process Noise 1: Controls the primary level of uncertainty in the Kalman filter model. Higher values make the filter more responsive to recent price changes, but may also increase susceptibility to random noise.
Process Noise 2: This secondary noise setting works with Process Noise 1 to adjust the model's adaptability. Together, these settings manage the uncertainty in the filter's internal model, allowing for finely-tuned adjustments to smoothness versus responsiveness.
Measurement Noise: Sets the uncertainty in the observed price data. Increasing this value makes the filter rely more on historical data, resulting in smoother but less reactive filtering. Lower values make the filter more responsive but potentially more prone to noise.
O sc Smoothness: Controls the level of smoothing applied to the trend strength oscillator. Higher values result in a smoother oscillator, which may cause slight delays in response. Lower values make the oscillator more reactive to trend changes, useful for capturing quick reversals or volatility within the trend.
Kalman Filter Model: Choose between Standard, Volume-Adjusted, and Parkinson-Adjusted models. Each model adapts the Kalman filter for specific conditions, whether balancing general market data, adjusting based on volume, or refining based on volatility.
Trend Lookback: Defines how far back to look when calculating the trend strength, which impacts the indicator's sensitivity to changes in trend strength. Shorter values make the oscillator more reactive to recent trends, while longer values provide a smoother reading.
Strength Smoothness: Adjusts the level of smoothing applied to the trend strength oscillator. Higher values create a more gradual response, while lower values make the oscillator more sensitive to recent changes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Probabilistic Trend Oscillator** MACD PLOTS ARE NOT PART OF THE INDICATOR IT IS FOR COMPARSION**
The "Probabilistic Trend Oscillator" is a technical indicator designed to measure trend strength and direction by analyzing price behavior relative to a moving average over both long-term and short-term periods. This indicator incorporates several innovative features, including probabilistic trend detection, enhanced strength scaling, and percentile-based thresholds for identifying potential trend reversals.
Key Components
Inputs:
The indicator allows users to customize several key parameters:
EMA Length defines the period for the Exponential Moving Average (EMA), which serves as a baseline to classify trend direction.
Long and Short Term Lengths provide customizable periods for analyzing trend strength over different timeframes.
Signal Line Length is used to smooth the trend strength data, helping users spot more reliable trend signals.
Extreme Value Lookback Length controls how far back to look when calculating percentile thresholds, which are used to identify overbought and oversold zones.
Trend Classification:
The indicator categorizes price behavior into four conditions:
Green: Price closes above the open and is also above the EMA, suggesting a strong upward trend.
Red: Price closes below the open but is above the EMA, indicating weaker upward pressure.
Green1: Price closes above the open but remains below the EMA, representing weak upward movement.
Red1: Price closes below the open and the EMA, signaling a strong downward trend.
Trend Strength Calculation:
The script calculates long-term and short-term trend values based on the frequency of these trend conditions, normalizing them to create probabilistic scores.
It then measures the difference between the short-term and long-term trend values, creating a metric that reflects the intensity of the current trend. This comparison provides insight into whether the trend is strengthening or weakening.
Enhanced Trend Strength:
To emphasize significant movements, the trend strength metric is scaled by the average absolute price change (distance between close and open prices). This creates an "enhanced trend strength" value that highlights periods with high momentum.
Users can toggle between two variations of trend strength:
Absolute Trend Strength is a straightforward measure of the trend's force.
Relative Trend Strength accounts for deviations between short term and long term values, focusing on how current price action differs from a long term behavior.
Percentile-Based Thresholds:
The indicator calculates percentile thresholds over the specified lookback period to mark extreme values:
The 97th and 3rd percentiles act as overbought and oversold zones, respectively, indicating potential reversal points.
Intermediate levels (75th and 25th percentiles) are added to give additional context for overbought or oversold conditions, creating a probabilistic range.
Visualization:
The selected trend strength value (either absolute or relative) is plotted in orange.
Overbought (green) and oversold (red) percentiles are marked with dashed lines and filled in blue, highlighting potential reversal zones.
The signal line—a smoothed EMA of the trend strength—is plotted in white, helping users to confirm trend changes.
A gray horizontal line at zero acts as a baseline, further clarifying the strength of upward vs. downward trends.
Summary
This indicator provides a flexible, probabilistic approach to trend detection, allowing users to monitor trend strength with customizable thresholds and lookback periods. By combining percentile-based thresholds with enhanced trend strength scaling, it offers insights into market reversals and momentum shifts, making it a valuable tool for both trend-following and counter-trend trading strategies.
Enhanced Buy/Sell Pressure, Volume, and Trend Bar analysisEnhanced Buy/Sell Pressure, Volume, and Trend Bar Analysis Indicator
Overview
This indicator is designed to help traders identify buy and sell pressure, volume changes, and overall trend direction in the market. It combines multiple concepts like price action, volume, and trend analysis, candlestick anaysis to provide a comprehensive view of market dynamics. The visual elements are intuitive, making it suitable for traders at different levels. This indicator works together with Enhanced Pressure MTF Screener which is a screener based of this indicator to make it easier to see Bullish/Bearish pressures and trend across multiple timeframes.
Image below: is the Enhanced Buy/Sell Pressure, Volume, and Trend Bar Analysis with the Enhanced Pressure MTF Screener indicator both active together.
Key Features
1.Buy/Sell Pressure Identification
Buy Pressure: Calculated based on price movement where the close price is higher than the opening price.
Sell Pressure: Calculated when the closing price is equal to or lower than the opening price.These pressures help you understand whether buyers or sellers are more dominant for each bar.
2.Volume Analysis
Normalized Volume: Volume data is normalized, making it easier to compare volume levels over different periods.
Volume Histogram: The volume is also presented as a histogram for easy visualization, showing whether the current volume is higher or lower compared to the average.
3.Simplified Coloring Option
You can choose to simplify the coloring of bars to reflect the dominant pressure: green for bullish pressure and red for bearish pressure. This makes it visually easier to identify who is in control. When simplified coloring is disabled, the bars' colors will represent the combined effect of buy and sell pressure.
4.Heikin-Ashi Candles for Pressure Calculation
The indicator includes an option to use Heikin-Ashi candles instead of traditional candles to calculate buy and sell pressure. Heikin-Ashi candles are known for smoothing out price action and providing a clearer trend representation.
5.Trend Background Coloring
This feature uses exponential moving averages (EMAs) to determine the trend:
Short-Term EMA vs. Long-Term EMA: When the short-term EMA is above the long-term EMA, the trend is considered bullish, and vice versa.
The background color changes based on the identified trend: green for an uptrend and red for a downtrend. This feature helps visualize the overall market direction at a glance.
6.Signals for Key Price Actions
The indicator plots various symbols to signal important price movements:
Bullish Close (▲): Indicates a strong upward movement where the close price crosses above the open.
Bearish Close (▼): Indicates a downward movement where the close price falls below the open.
Higher High (•): Highlights new highs compared to previous bars, useful for confirming an uptrend.
Lower Low (•): Highlights lower lows compared to previous bars, which can indicate a downtrend or bearish pressure.
Calculations Explained
1.Buy and Sell Pressure Calculation
The buy pressure is determined by the price range (high - low) if the closing price is above the opening price, indicating an increase in value.
The sell pressure is similarly calculated when the closing price is equal to or below the opening price.
The indicator uses the Average True Range (ATR) for normalization. Normalizing helps you compare pressure across different periods, regardless of market volatility.
2.Volume Normalization
Volume Normalization: To make volume comparable across different periods, the indicator normalizes it using the Simple Moving Average (SMA) of volume over a user-defined length.
Volume Histogram: The histogram provides a clear representation of volume changes compared to the average, making it easier to spot unusual activity that may indicate market shifts.
3.Combined Pressure Calculation
The indicator calculates a combined pressure value by subtracting sell pressure from buy pressure.
When combined pressure is positive, buying is dominant, and when negative, selling is dominant. This helps in visually understanding the ongoing momentum.
4.Trend Calculation
The indicator uses two EMAs to determine the trend:
Short-Term EMA (default 14-period) to capture recent price movements.
Long-Term EMA (default 50-period) to provide a broader trend perspective.
By comparing these EMAs on a higher timeframe, the indicator can identify whether the trend is up or down, making it easier for traders to align their trades with the larger market movement.
Inputs and Customization
The indicator provides several options for customization, allowing you to adjust it to your preferences:
SMA Length: Determines the lookback period for moving averages and volume normalization. A longer length provides more smoothing, whereas a shorter length makes the indicator more responsive.
Buy/Sell/Volume Colors: Customize the colors used to represent buying, selling, and volume to suit your preferences.
Heikin Ashi Option: Toggle between using Heikin Ashi or traditional OHLC (Open-High-Low-Close) candles for pressure calculations.
Trend Timeframe and EMA Periods: You can choose different timeframes and EMA periods for trend analysis to suit your trading strategy.
How to Use This Indicator
Identifying Market Momentum: Use the buy/sell pressure columns to see which side (buyers or sellers) is in control. Positive pressure combined with green color indicates strong buying, while red indicates selling.
Volume Confirmation: Check the volume area plot and histogram. High volume coupled with strong pressure is a sign of conviction, meaning the current move has backing from market participants.
Trend Identification: The trend background color helps identify the overall trend direction. Trade in the direction of the trend (e.g., take long positions during a green background).
Signal Indicators: The plotted symbols like "Bullish Close" and "Bearish Close" provide visual signals of key price actions, useful for timing entry or exit points.
Practical use Example
Scenario: The market is consolidating, and you see alternating green and red bars.
Action: Wait for a consistent sequence of green bars (buy pressure) along with a green background (uptrend) to consider going long, although you can go long without having a green background, the background adds confirmation layer.
Scenario: The market has several bearish closes (red ▼ symbols) accompanied by increasing volume.
Action: This could indicate strong selling pressure. If the background also turns red, it might be a good time to exit long positions or consider shorting.
Higher timeframe pressure and volume: Another way to use the indicator is to check buy/sell volume and pressure of the higher timeframe say weekly or daily or any timeframe you consider higher, once you’ve identified or feel confident in which direction the bar is going along with the full picture of trend, you can go to the lower timeframe and wait for it to sync with the higher timeframe to consider a long or a short. It is also easier to see when markets sync up by also applying the Enhanced Pressure MTF Screener which works in companion to this indicator.
Visual Cues and Interpretation
Combined Pressure Plot: The green and red column plot at the bottom of the chart represents the dominance between buying and selling. Tall green bars signify strong buying, while tall red bars indicate selling dominance.
Trend Background: Helps visualize the overall direction without manually drawing trend lines. When the background turns green, it generally indicates that the shorter-term moving average has crossed above the longer-term average—a sign of a bullish trend.
To Summarize shortly
The Enhanced Buy/Sell Pressure, Volume, and Trend Bar Analysis Indicator is an advanced but simple tool designed to help traders visually understand market dynamics. It combines different aspects of market analysis of candle pressure from buyers and sellers, volume confirmation, and trend identification into a single view, which can assist both new and experienced traders in making informed trading decisions.
This indicator:
Saves time by simplifying market analysis.
Provides clear visual cues for buy/sell pressure, volume, and trend.
Offers customizable settings to suit individual trading styles.
Always, I am happy to share my creations with you all for free. If you guys have cool ideas you would like to share, or suggestions for improvements the comment is below and I hope this overview gave an idea of how to use the indicator :D
Arshtiq - Multi-Timeframe Trend StrategyMulti-Timeframe Setup:
The script uses two distinct timeframes: a higher (daily) timeframe for identifying the trend and a lower (hourly) timeframe for making trades. This combination allows the script to follow the larger trend while timing entries and exits with more precision on a shorter timeframe.
Moving Averages Calculation:
higher_ma: The 20-period Simple Moving Average (SMA) calculated based on the daily timeframe. This average gives a sense of the larger trend direction.
lower_ma: The 20-period SMA calculated on the hourly (current) timeframe, providing a dynamic level for detecting entry and exit points within the broader trend.
Trend Identification:
Bullish Trend: The script determines that a bullish trend is present if the current price is above the daily moving average (higher_ma).
Bearish Trend: Similarly, a bearish trend is identified when the current price is below this daily moving average.
Trade Signals:
Buy Signal: A buy signal is generated when the price on the hourly chart crosses above the hourly 20-period MA, but only if the higher (daily) timeframe trend is bullish. This ensures that buy trades align with the larger upward trend.
Sell Signal: A sell signal is generated when the price on the hourly chart crosses below the hourly 20-period MA, but only if the daily trend is bearish. This ensures that sell trades are consistent with the broader downtrend.
Plotting and Visual Cues:
Higher Timeframe MA: The daily 20-period moving average is plotted in red to help visualize the long-term trend.
Buy and Sell Signals: Buy signals appear as green labels below the price bars with the text "BUY," while sell signals appear as red labels above the bars with the text "SELL."
Background Coloring: The background changes color based on the identified trend for easier trend recognition:
Green (with transparency) when the daily trend is bullish.
Red (with transparency) when the daily trend is bearish.
RBF Kijun Trend System [InvestorUnknown]The RBF Kijun Trend System utilizes advanced mathematical techniques, including the Radial Basis Function (RBF) kernel and Kijun-Sen calculations, to provide traders with a smoother trend-following experience and reduce the impact of noise in price data. This indicator also incorporates ATR to dynamically adjust smoothing and further minimize false signals.
Radial Basis Function (RBF) Kernel Smoothing
The RBF kernel is a mathematical method used to smooth the price series. By calculating weights based on the distance between data points, the RBF kernel ensures smoother transitions and a more refined representation of the price trend.
The RBF Kernel Weighted Moving Average is computed using the formula:
f_rbf_kernel(x, xi, sigma) =>
math.exp(-(math.pow(x - xi, 2)) / (2 * math.pow(sigma, 2)))
The smoothed price is then calculated as a weighted sum of past prices, using the RBF kernel weights:
f_rbf_weighted_average(src, kernel_len, sigma) =>
float total_weight = 0.0
float weighted_sum = 0.0
// Compute weights and sum for the weighted average
for i = 0 to kernel_len - 1
weight = f_rbf_kernel(kernel_len - 1, i, sigma)
total_weight := total_weight + weight
weighted_sum := weighted_sum + (src * weight)
// Check to avoid division by zero
total_weight != 0 ? weighted_sum / total_weight : na
Kijun-Sen Calculation
The Kijun-Sen, a component of Ichimoku analysis, is used here to further establish trends. The Kijun-Sen is computed as the average of the highest high and the lowest low over a specified period (default: 14 periods).
This Kijun-Sen calculation is based on the RBF-smoothed price to ensure smoother and more accurate trend detection.
f_kijun_sen(len, source) =>
math.avg(ta.lowest(source, len), ta.highest(source, len))
ATR-Adjusted RBF and Kijun-Sen
To mitigate false signals caused by price volatility, the indicator features ATR-adjusted versions of both the RBF smoothed price and Kijun-Sen.
The ATR multiplier is used to create upper and lower bounds around these lines, providing dynamic thresholds that account for market volatility.
Neutral State and Trend Continuation
This indicator can interpret a neutral state, where the signal is neither bullish nor bearish. By default, the indicator is set to interpret a neutral state as a continuation of the previous trend, though this can be adjusted to treat it as a truly neutral state.
Users can configure this setting using the signal_str input:
simple string signal_str = input.string("Continuation of Previous Trend", "Treat 0 State As", options = , group = G1)
Visual difference between "Neutral" (Bottom) and "Continuation of Previous Trend" (Top). Click on the picture to see it in full size.
Customizable Inputs and Settings:
Source Selection: Choose the input source for calculations (open, high, low, close, etc.).
Kernel Length and Sigma: Adjust the RBF kernel parameters to change the smoothing effect.
Kijun Length: Customize the lookback period for Kijun-Sen.
ATR Length and Multiplier: Modify these settings to adapt to market volatility.
Backtesting and Performance Metrics
The indicator includes a Backtest Mode, allowing users to evaluate the performance of the strategy using historical data. In Backtest Mode, a performance metrics table is generated, comparing the strategy's results to a simple buy-and-hold approach. Key metrics include mean returns, standard deviation, Sharpe ratio, and more.
Equity Calculation: The indicator calculates equity performance based on signals, comparing it against the buy-and-hold strategy.
Performance Metrics Table: Detailed performance analysis, including probabilities of positive, neutral, and negative returns.
Alerts
To keep traders informed, the indicator supports alerts for significant trend shifts:
// - - - - - ALERTS - - - - - //{
alert_source = sig
bool long_alert = ta.crossover (intrabar ? alert_source : alert_source , 0)
bool short_alert = ta.crossunder(intrabar ? alert_source : alert_source , 0)
alertcondition(long_alert, "LONG (RBF Kijun Trend System)", "RBF Kijun Trend System flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (RBF Kijun Trend System)", "RBF Kijun Trend System flipped ⬇Short⬇")
//}
Important Notes
Calibration Needed: The default settings provided are not optimized and are intended for demonstration purposes only. Traders should adjust parameters to fit their trading style and market conditions.
Neutral State Interpretation: Users should carefully choose whether to treat the neutral state as a continuation or a separate signal.
Backtest Results: Historical performance is not indicative of future results. Market conditions change, and past trends may not recur.
Mean Trend OscillatorMean Trend Oscillator
The Mean Trend Oscillator offers an original approach to trend analysis by integrating multiple technical indicators, using statistic to get a probable signal, and dynamically adapting to market volatility.
This tool aggregates signals from four popular indicators—Relative Strength Index (RSI), Simple Moving Average (SMA), Exponential Moving Average (EMA), and Relative Moving Average (RMA)—and adjusts thresholds using the Average True Range (ATR). By using this, we can use Statistics to aggregate or take the average of each indicators signal. Mathematically, Taking an average of these indicators gives us a better probability on entering a trending state.
By consolidating these distinct perspectives, the Mean Trend Oscillator provides a comprehensive view of market direction, helping traders make informed decisions based on a broad, data-driven trend assessment. Traders can use this indicator to enter long spot or leveraged positions. The Mean Trend Oscillator is intended to be use in long term trending markets. Scalping MUST NOT be used with this indicator. (This indicator will give false signals when the Timeframe is too low. The best intended use for high-quality signals are longer timeframes).
The current price of a beginning trend series may tell us something about the next move. Thus, the Mean Trend Oscillator allows us to spot a high probability trending market and potentially exploit this information enter long or shorts strategy. (again, this indicator will give false signals when the Timeframe is too low. The best intended use for high-quality signals are longer timeframes).
Concept and Calculation and Inputs
The Mean Trend Oscillator calculates a “net trend” score as follows:
RSI evaluates market momentum, identifying overbought and oversold conditions, essential for confirming trend direction.
SMA, EMA, and RMA introduce varied smoothing methods to capture short- to medium-term trends, balancing quick price changes with smoothed averages.
ATR-Enhanced Thresholds: ATR is used as a dynamic multiplier, adjusting each indicator’s thresholds to current volatility levels, which helps reduce noise in low-volatility conditions and emphasizes significant signals when volatility spikes.
Length could be used to adjust how quickly each indicator can more or how slower each indicator can be.
Time Coherency for Inputs: Each indicator must be calculated where each signal is relatively around the same area.
For example:
Simply:
SMA, RMA, EMA, and RSI enters long around each intended trend period. Doesn't have to be perfect, but the indicators all enter long around there.
Each indicator contributes a score (+1 for bullish and -1 for bearish), and these scores are averaged to generate the final trend score:
A positive score, shown as a green line, suggests bullish conditions.
A negative score, indicated by a red line, signifies bearish conditions.
Thus, giving us a signal to long or short.
How to Use the Mean Trend Oscillator
This indicator’s output is straightforward and can fit into various trading strategies:
Bullish Signal: A green line shows that the trend is bullish, based on a positive average score across the indicators, signaling a consideration of longing an asset.
Bearish Signal: A red line indicates bearish conditions, with an overall negative trend score, signaling a consideration to shorting an asset.
By aggregating these indicators, the Mean Trend Oscillator helps traders identify strong trends while filtering out minor fluctuations, making it a versatile tool for both short- and long-term analysis. This multi-layered, adaptive approach to trend detection sets it apart from traditional single-indicator trend tools.
Z-Score Weighted Trend System I [InvestorUnknown]The Z-Score Weighted Trend System I is an advanced and experimental trading indicator designed to utilize a combination of slow and fast indicators for a comprehensive analysis of market trends. The system is designed to identify stable trends using slower indicators while capturing rapid market shifts through dynamically weighted fast indicators. The core of this indicator is the dynamic weighting mechanism that utilizes the Z-score of price , allowing the system to respond effectively to significant market movements.
Dynamic Z-Score-Based Weighting System
The Z-Score Weighted Trend System I utilizes the Z-score of price to assign weights dynamically to fast indicators. This mechanism is designed to capture rapid market shifts at potential turning points, providing timely entry and exit signals.
Traders can choose from two primary weighting mechanisms:
Threshold-Based Weighting: The fast indicators are given weight only when the absolute Z-score exceeds a user-defined threshold. Below this threshold, fast indicators have no impact on the final signal.
Continuous Weighting: By setting the threshold to zero, fast indicators always contribute to the final signal, regardless of Z-score levels. However, this increases the likelihood of false signals during ranging or low-volatility markets
// Calculate weight for Fast Indicators based on Z-Score (Slow Indicator weight is kept to 1 for simplicity)
f_zscore_weights(series float z, simple float weight_thre) =>
float fast_weight = na
float slow_weight = na
if weight_thre > 0
if math.abs(z) <= weight_thre
fast_weight := 0
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
Choice of Z-Score Normalization
Traders have the flexibility to select different Z-score processing methods to better suit their trading preferences:
Raw Z-Score or Moving Average: Traders can opt for either the raw Z-score or a moving average of the Z-score to smooth out fluctuations.
Normalized Z-Score (ranging from -1 to 1) or Z-Score Percentile: The normalized Z-score is simply the raw Z-score divided by 3, while the Z-score percentile utilizes a normal distribution for transformation.
f_zscore_perc(series float zscore_src, simple int zscore_len, simple string zscore_a, simple string zscore_b, simple string ma_type, simple int ma_len) =>
z = (zscore_src - ta.sma(zscore_src, zscore_len)) / ta.stdev(zscore_src, zscore_len)
zscore = switch zscore_a
"Z-Score" => z
"Z-Score MA" => ma_type == "EMA" ? (ta.ema(z, ma_len)) : (ta.sma(z, ma_len))
output = switch zscore_b
"Normalized Z-Score" => (zscore / 3) > 1 ? 1 : (zscore / 3) < -1 ? -1 : (zscore / 3)
"Z-Score Percentile" => (f_percentileFromZScore(zscore) - 0.5) * 2
output
Slow and Fast Indicators
The indicator uses a combination of slow and fast indicators:
Slow Indicators (constant weight) for stable trend identification: DMI (Directional Movement Index), CCI (Commodity Channel Index), Aroon
Fast Indicators (dynamic weight) to identify rapid trend shifts: ZLEMA (Zero-Lag Exponential Moving Average), IIRF (Infinite Impulse Response Filter)
Each indicator is calculated using for-loop methods to provide a smoothed and averaged view of price data over varying lengths, ensuring stability for slow indicators and responsiveness for fast indicators.
Signal Calculation
The final trading signal is determined by a weighted combination of both slow and fast indicators. The slow indicators provide a stable view of the trend, while the fast indicators offer agile responses to rapid market movements. The signal calculation takes into account the dynamic weighting of fast indicators based on the Z-score:
// Calculate Signal (as weighted average)
float sig = math.round(((DMI*slow_w) + (CCI*slow_w) + (Aroon*slow_w) + (ZLEMA*fast_w) + (IIRF*fast_w)) / (3*slow_w + 2*fast_w), 2)
Backtest Mode and Performance Metrics
The indicator features a detailed backtesting mode, allowing traders to compare the effectiveness of their selected settings against a traditional Buy & Hold strategy. The backtesting provides:
Equity calculation based on signals generated by the indicator.
Performance metrics comparing Buy & Hold metrics with the system’s signals, including: Mean, positive, and negative return percentages, Standard deviations, Sharpe, Sortino, and Omega Ratios
// Calculate Performance Metrics
f_PerformanceMetrics(series float base, int Lookback, simple float startDate, bool Annualize = true) =>
// Initialize variables for positive and negative returns
pos_sum = 0.0
neg_sum = 0.0
pos_count = 0
neg_count = 0
returns_sum = 0.0
returns_squared_sum = 0.0
pos_returns_squared_sum = 0.0
neg_returns_squared_sum = 0.0
// Loop through the past 'Lookback' bars to calculate sums and counts
if (time >= startDate)
for i = 0 to Lookback - 1
r = (base - base ) / base
returns_sum += r
returns_squared_sum += r * r
if r > 0
pos_sum += r
pos_count += 1
pos_returns_squared_sum += r * r
if r < 0
neg_sum += r
neg_count += 1
neg_returns_squared_sum += r * r
float export_array = array.new_float(12)
// Calculate means
mean_all = math.round((returns_sum / Lookback), 4)
mean_pos = math.round((pos_count != 0 ? pos_sum / pos_count : na), 4)
mean_neg = math.round((neg_count != 0 ? neg_sum / neg_count : na), 4)
// Calculate standard deviations
stddev_all = math.round((math.sqrt((returns_squared_sum - (returns_sum * returns_sum) / Lookback) / Lookback)) * 100, 2)
stddev_pos = math.round((pos_count != 0 ? math.sqrt((pos_returns_squared_sum - (pos_sum * pos_sum) / pos_count) / pos_count) : na) * 100, 2)
stddev_neg = math.round((neg_count != 0 ? math.sqrt((neg_returns_squared_sum - (neg_sum * neg_sum) / neg_count) / neg_count) : na) * 100, 2)
// Calculate probabilities
prob_pos = math.round((pos_count / Lookback) * 100, 2)
prob_neg = math.round((neg_count / Lookback) * 100, 2)
prob_neu = math.round(((Lookback - pos_count - neg_count) / Lookback) * 100, 2)
// Calculate ratios
sharpe_ratio = math.round((mean_all / stddev_all * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
sortino_ratio = math.round((mean_all / stddev_neg * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
omega_ratio = math.round(pos_sum / math.abs(neg_sum), 2)
// Set values in the array
array.set(export_array, 0, mean_all), array.set(export_array, 1, mean_pos), array.set(export_array, 2, mean_neg),
array.set(export_array, 3, stddev_all), array.set(export_array, 4, stddev_pos), array.set(export_array, 5, stddev_neg),
array.set(export_array, 6, prob_pos), array.set(export_array, 7, prob_neu), array.set(export_array, 8, prob_neg),
array.set(export_array, 9, sharpe_ratio), array.set(export_array, 10, sortino_ratio), array.set(export_array, 11, omega_ratio)
// Export the array
export_array
//}
Calibration Mode
A Calibration Mode is included for traders to focus on individual indicators, helping them fine-tune their settings without the influence of other components. In Calibration Mode, the user can visualize each indicator separately, making it easier to adjust parameters.
Alerts
The indicator includes alerts for long and short signals when the indicator changes direction, allowing traders to set automated notifications for key market events.
// Alert Conditions
alertcondition(long_alert, "LONG (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬇Short⬇")
Important Note:
The default settings of this indicator are not optimized for any particular market condition. They are generic starting points for experimentation. Traders are encouraged to use the calibration tools and backtesting features to adjust the system to their specific trading needs.
The results generated from the backtest are purely historical and are not indicative of future results. Market conditions can change, and the performance of this system may differ under different circumstances. Traders and investors should exercise caution and conduct their own research before using this indicator for any trading decisions.
70% rule strength/trend/reversalThis indicator tells you which candle closed strong for the day by identifying if the price closed above 70% of the candle's total height. this can help you identify reversals/new trends/ renewed strength in the current trend.
The indicator colors such candle green and if the candle closes with increase in price by 5% or higher then marks an asterisk under the candle.
HOPE THIS HELPS
RV- Dynamic Trend AnalyzerRV Dynamic Trend Analyzer
The RV Dynamic Trend Analyzer is a powerful TradingView indicator designed to help traders identify and capitalize on trends across multiple time frames—daily, weekly, and monthly. With dynamic adjustments to key technical indicators like EMA and MACD, the tool adapts to different chart periods, ensuring more accurate signals. Whether you are swing trading or holding longer-term positions, this indicator provides reliable buy/sell signals, breakout opportunities, and customizable visual elements to enhance decision-making. Its intelligent use of EMAs and MACD values ensures high potential returns, making it suitable for traders seeking strong, data-driven strategies. Below are its core features and their respective benefits.
Supertrend Indicator:
Importance: The Supertrend is a trend-following tool that helps traders identify the market’s direction by offering clear buy and sell signals based on price movement relative to the Supertrend line.
Benefits:
Helps filter out market noise and enables traders to stay in trends longer.
The pullback detection feature enhances trade timing by identifying potential entry points during retracements.
ATH/ATL & 52-Week High/Low with Candle Coloring:
Importance: Tracking all-time highs (ATH), all-time lows (ATL), and 52-week high/low levels helps traders identify key support and resistance levels.
Benefits:
Offers insights into the strength of price movements and potential reversal zones.
Candle coloring improves visual analysis, allowing quick identification of bullish or bearish conditions at critical levels.
Multi-Time Frame Analysis
Importance: The ability to view indicators like RSI and MACD across multiple time frames provides a more in-depth and comprehensive view of market behavior, allowing traders to make informed decisions that align with both short-term and long-term trends.
Benefits:
Align Strategies Across Time frames: By using multiple time frames, traders can align their strategies with larger trends (such as weekly or daily) while executing trades on lower time frames (like 1-minute or 5-minute charts). This improves the accuracy of trade entries and exits.
Reduce False Signals: Viewing key technical indicators like RSI and MACD across different time frames reduces the likelihood of false signals by offering a broader market context, filtering out noise from smaller time frames.
Customization of Table Display: Traders can customize the position and size of a table that displays RSI and MACD values for selected time frames. This flexibility enhances visibility and ease of analysis.
Time frame-Specific Data: The code allows for displaying RSI and MACD data for up to seven different time frames, making it highly customizable for traders depending on their preferred analysis period.
Visual Clarity: The table displays key values such as RSI and MACD histogram readings in a visually clear format, with color coding to quickly indicate overbought/oversold levels or MACD crossovers.
Pivot Points:
Importance: Pivot points serve as key support and resistance levels that help predict potential price movements.
Benefits:
Assists in identifying potential reversal zones and breakout points, aiding in trade planning.
Displaying pivot points across multiple time frames enhances market insight and improves strategic planning.
Quarterly Earnings Table:
Importance: Understanding a company’s quarterly earnings releases is crucial, as these events often lead to significant price volatility. Traders can leverage this information to adjust their strategies around earnings reports and prevent unexpected losses.
Benefits:
Helps traders anticipate potential price movements due to earnings reports.
Allows traders to avoid sudden losses by being aware of important earnings announcements and adjusting positions accordingly.
Customizable Visuals for Traders:
Dark Mode: Toggle between dark and light themes based on your chart's color scheme.
Mini Mode: A condensed version that visually simplifies the data, making it quicker to interpret through color-coded traffic lights (green for positive, red for negative).
Table Size & Position: Customize the size and position of the table for better visibility on your charts.
Data Period (FQ vs FY): Easily switch between displaying quarterly or yearly data based on the selected period.
Top-Left Cell Display: Option to display Free Float or Market Cap in the top-left cell for quick reference.
Exponential Moving Averages (EMAs) with Adjustable Lengths:
Importance: EMAs are essential for identifying trends and generating reliable buy/sell signals. The indicator plots four EMAs that dynamically adjust based on the selected time frame.
Benefits:
Dynamic Time frame Logic: EMA lengths and sources automatically adapt based on whether the user selects daily, weekly, or monthly time frames. This ensures the EMAs are relevant for the chosen strategy.
Multiple EMAs: By incorporating four different EMAs, users can observe both short-term and long-term trends simultaneously, improving their ability to identify key trend shifts.
Breakout Arrow Functionality:
Importance: This feature visually signals potential buy/sell opportunities based on the interaction between EMAs and MACD crossovers.
Benefits:
Crossover Signals: Arrows are plotted when EMAs and MACD cross, indicating breakout opportunities and aiding in quick trade decisions.
RSI Filter Option: Users can apply an optional RSI filter to refine buy/sell signals, reducing false signals and improving overall accuracy.
Disclaimer:
Before engaging in actual trading, we strongly recommend back testing the this indicator to ensure it fits your trading style and risk tolerance. Be sure to adjust your risk-reward ratio and set appropriate stop-loss levels to safeguard your investments. Proper risk management is key to successful trading.
Volatility Trend Bands [UAlgo]The Volatility Trend Bands is a trend-following indicator that combines the concepts of volatility and trend detection. Built using the Average True Range (ATR) to measure volatility, this indicator dynamically adjusts upper and lower bands around price movements. The bands act as dynamic support and resistance levels, making it easier to identify trend shifts and potential entry and exit points.
With the ATR multiplier, this indicator effectively captures volatility-based shifts in the market. The use of midline values allows for accurate trend detection, which is displayed through color-coded signals on the chart. Additionally, this tool provides clear buy and sell signals, accompanied by intuitive graphical markers for ease of use.
The Volatility Trend Bands is ideal for traders seeking an adaptive trend-following method that responds to changing market conditions while maintaining robust volatility control.
🔶 Key Features
Dynamic Support and Resistance: The indicator utilizes volatility to create dynamic bands. The upper band acts as resistance, and the lower band acts as support for the price. Wider bands indicate higher volatility, while narrower bands indicate lower volatility.
Customizable Inputs
You can tailor the indicator to your strategy by adjusting the:
Price Source: Select the price data (e.g., closing price) used for calculations.
ATR Length: Define the lookback period for the Average True Range (ATR) volatility measure.
ATR Multiplier: This factor controls the width of the volatility bands relative to the ATR value.
Color Options: Choose colors for the bands and signal arrows for better visualization.
Visual Signals: Arrows ("▲" for buy, "▼" for sell) appear on the chart when the trend changes, providing clear entry point indications.
Alerts: Integrated alerts for both buy and sell conditions, allowing you to receive notifications for potential trade opportunities.
🔶 Interpreting Indicator
Upper and Lower Bands: The upper and lower bands are dynamic, adjusting based on market volatility using the ATR. These bands serve as adaptive support and resistance levels. When price breaks above the upper band, it indicates a potential bullish breakout, signaling a strong uptrend. Conversely, a break below the lower band signals a bearish breakout, indicating a downtrend.
Buy/Sell Signals: The indicator provides clear buy and sell signals at breakout points. A buy signal ("▲") is generated when the price breaks above the upper band, suggesting the start of a bullish trend. A sell signal ("▼") is triggered when the price breaks below the lower band, indicating the beginning of a bearish trend. These signals help traders identify potential entry and exit points at key breakout levels.
Color-Coded Bars: The bars on the chart change color based on the trend direction. Teal bars represent bullish momentum, while purple bars signify bearish momentum. This color coding provides a quick visual cue about the market's current direction.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Hammers & star Patterns After a Trend
1. **Candlestick Patterns Detection:**
- **Hammers** and **Inverted Hammers** are specific candlestick patterns that can indicate potential reversals in the market.
- **Hammer**: A candle with a small body and a long lower wick, showing a possible reversal after a downtrend.
- **Inverted Hammer**: A candle with a small body and a long upper wick, indicating a possible reversal after an uptrend.
2. **Volume Consideration:**
- The script checks if these patterns occur with **high trading volume**. If the volume is significantly higher than the average volume over a certain period, the pattern is highlighted.
3. **Trend Detection:**
- The script looks for a significant trend before the pattern appears:
- **Downtrend**: A significant downward movement in price is required before a Hammer is considered.
- **Uptrend**: A significant upward movement is required before an Inverted Hammer is considered.
4. **Additional Patterns:**
- **Morning Star** and **Evening Star** patterns are also detected:
- **Morning Star**: A three-candle pattern where the first candle is a large bearish candle, followed by a small-bodied candle, and then a large bullish candle, indicating a potential reversal from downtrend to uptrend.
- **Evening Star**: The opposite pattern, signaling a potential reversal from uptrend to downtrend.
5. **Visual Indicators:**
- The script **plots arrows** and **labels** on the chart to show where these patterns occur:
- **Hammers** and **Inverted Hammers** are marked with triangle arrows.
- **Morning Stars** and **Evening Stars** are marked with labels.
In summary, this script helps traders identify key candlestick patterns that may signal potential reversals in price trends, with special emphasis on patterns that occur with high volume and after significant price movements.
