The Trap Play█ INTRODUCTION
The Trap Play Indicator is designed to identify a market liquidity pattern where the price initially makes a new high or low, luring traders into believing a strong trend is forming. However, the price quickly reverses and invalidates the breakout, trapping those traders who entered positions based on the initial move. This sudden reversal often results in a rapid exit of positions, leading to significant price movement in the opposite direction. Trap Plays can occur in various financial markets and timeframes and are characterized by their ability to catch traders off guard and create significant market volatility.
█ WHY USE THE TRAP PLAY INDICATOR?
The Trap Play indicator provides buyers with crucial information about potential market traps, enabling them to avoid false signals, optimize their entry timing, manage risk more effectively, and make more informed trading decisions.
This indicator leverages the Donchian Channel (DC) to read highs and lows, but its uniqueness lies in its ability to identify Trap Plays, which is why this indicator delivers additional value. This is something that the free, open-source Donchian Channel indicator does not offer.
The Donchian Channel is an effective tool for identifying Trap Plays and includes three lines, which are concealed within the Trap Play Indicator for a clearer visual presentation of Trap Plays. In the picture(s) below, the Donchian Channel is visible for reference.
◆ The Upper & Lower Channel Lines: These lines track the highest and lowest prices over a specified period, helping identify potential breakout levels where Trap Plays may occur.
◆ The Middle Channel Line: This line represents the average value between the upper and lower channel lines, serving as a reference for assessing the overall market trend.
◆ The default period is set to 5, but it can be customized to suit specific market conditions.
█ SCRIPT INPUT
◆ Period Input: This defines the period during which the script calculates the highest high and lowest low. By default, this period is set to 5, indicating that the DC uses the most recent 5 closed bars for its calculations.
█ SCRIPT CONDITIONS FOR BULL TRAPS
A Bull Trap is identified when the close of a bar is above the Donchian Channel's high, followed by a bar that closes below the previous bar's low. The indicator will display specific signals or markers on the chart when it detects Bull Traps. These signals are customizable and could be visual elements like arrows, lines, or highlights.
█ SCRIPT CONDITIONS FOR BEAR TRAPS
A Bear Trap is identified when the close of a bar is below the Donchian Channel's low, followed by a bar that closes above the previous bar's high. The indicator will display specific signals or markers on the chart when it detects Bear Traps. These signals are customizable and could be visual elements like arrows, lines, or highlights.
█ FEATURES
◆ Alert System: Stay informed with email notifications and TradingView alerts on your PC or smartphone whenever new Bull Traps or Bear Traps are detected.
◆ Adjustable Period Calculation: Tailor the calculation period to align with your specific trading strategy and timeframe.
█ SETTINGS
■ Period: 5
■ Bull Trap Signal Color: Red
■ Bear Trap Signal Color: Green
█ IN SUMMARY
The Trap Play Indicator is a powerful tool for identifying false breakouts and potential reversals in the market. By analyzing the Donchian Channel, this indicator helps traders spot Trap Plays, allowing them to avoid common trading pitfalls and capitalize on significant market movements. Customize the indicator settings to fit your trading style and receive real-time alerts to stay ahead of market changes. Whether you are trading stocks, forex, or cryptocurrencies, the Trap Play Indicator provides valuable insights to enhance your trading strategy. The premium nature of this indicator ensures that it remains a refined, high-quality product, providing traders with a unique edge in the market.
볼래틸리티
Volumetric Volatility Blocks [UAlgo]The Volumetric Volatility Blocks indicator is designed to identify significant volatility blocks based on price and volume data. It utilizes a combination of the Average True Range (ATR) and Simple Moving Average (SMA) to determine the volatility level and identify periods of heightened market activity. The indicator highlights these volatility blocks, providing traders with visual cues for potential trading opportunities. It differentiates between bullish and bearish volatility by analyzing price movement and volume, offering a nuanced view of market sentiment. This tool is particularly useful for traders looking to capitalize on periods of high volatility and momentum shifts.
🔶 Key Features
Volatility Measurement Length: Controls the period used to calculate the ATR.
Smooth Length of Volatility: Defines the period for the SMA used to smooth the ATR.
Multiplier of SMA: Sets the minimum threshold for the ATR to be considered a "high volatility" block.
Show Last X Volatility Blocks: Determines how many of the most recent volatility blocks are displayed on the chart.
Mitigation Method: Choose between "Close" or "Wick" price to filter volatility blocks based on price action. This helps avoid highlighting blocks broken by the chosen price level.
Volume Info: Displaying the volume associated with each block.
Up/Down Block Color: Sets the color for bullish and bearish volatility blocks.
🔶 Usage
The Volumetric Volatility Blocks indicator visually represents periods of high volatility with blocks on the chart. Green blocks indicate bullish volatility, while red blocks indicate bearish volatility.
Bullish Volatility Blocks: When the ATR surpasses the smoothed ATR multiplied by the set multiplier, and the price closes higher than it opened, a bullish block is formed. These blocks are generally used to identify potential buying opportunities as they indicate upward momentum.
Bearish Volatility Blocks: Conversely, bearish blocks form under the same conditions, but when the price closes lower than it opened. These blocks can signal potential selling opportunities as they highlight downward momentum.
Volume Information: Each block can display volume data, providing insight into the strength of the market movement. The percentage shown on the block indicates the relative volume contribution of that block, helping traders assess the significance of the volatility.
The volume percentages in the Volumetric Volatility Blocks indicator are calculated based on the total volume of the most recent volatility blocks. For each of the most recent volatility blocks, the percentage of the total volume is calculated by dividing the block's volume by the total volume:
🔶 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.
test - ClassificationTensor-Based Classification Experiment
This innovative script represents an experimental foray into classification techniques, specifically designed to analyze returns within a compact time frame. By leveraging tensor-based analytics, it generates a comprehensive table that visually illustrates the distribution of counts across both current and historical bars, providing valuable insights into market patterns.
The script's primary objective is to classify returns over a small window, using this information to inform trading decisions. The output table showcases a normal distribution of count values for each bar in the lookback period, allowing traders to gain a deeper understanding of market behavior and identify potential opportunities.
Key Features:
Experimental classification approach utilizing tensor-based analytics
Compact time frame analysis (small window)
Comprehensive table displaying return counts across current and historical bars
Normal distribution visualization for better insight into market patterns
By exploring this script, traders can gain a deeper understanding of the underlying dynamics driving market movements and develop more effective trading strategies.
Premarket Std Dev BandsOverview
The Premarket Std Dev Bands indicator is a powerful Pine Script tool designed to help traders gain deeper insights into the premarket session's price movements. This indicator calculates and displays the standard deviation bands for premarket trading, providing valuable information on price volatility and potential support and resistance levels during the premarket hours.
Key Features
Premarket Focus: Specifically designed to analyze price movements during the premarket session, offering unique insights not available with traditional indicators.
Customizable Length: Users can adjust the averaging period for calculating the standard deviation, allowing for tailored analysis based on their trading strategy.
Standard Deviation Bands: Displays both 1 and 2 standard deviation bands, helping traders identify significant price movements and potential reversal points.
Real-Time Updates: Continuously updates the premarket open and close prices, ensuring the bands are accurate and reflective of current market conditions.
How It Works
Premarket Session Identification: The script identifies when the current bar is within the premarket session.
Track Premarket Prices: It tracks the open and close prices during the premarket session.
Calculate Premarket Moves: Once the premarket session ends, it calculates the price movement and stores it in an array.
Compute Averages and Standard Deviation: The script calculates the simple moving average (SMA) and standard deviation of the premarket moves over a specified period.
Plot Standard Deviation Bands: Based on the calculated standard deviation, it plots the 1 and 2 standard deviation bands around the premarket open price.
Usage
To utilize the Premarket Std Dev Bands indicator:
Add the script to your TradingView chart.
Adjust the Length input to set the averaging period for calculating the standard deviation.
Observe the plotted standard deviation bands during the premarket session to identify potential trading opportunities.
Benefits
Enhanced Volatility Analysis: Understand price volatility during the premarket session, which can be crucial for making informed trading decisions.
Support and Resistance Levels: Use the standard deviation bands to identify key support and resistance levels, aiding in better entry and exit points.
Customizable and Flexible: Tailor the averaging period to match your trading style and strategy, making this indicator versatile for various market conditions.
ATR X-PowerATR X-Power is a simple graphical representation of Average True Range.
The ATR is calculated on a daily basis and averaged over the "Length" specified in settings (default is 14 days).
At the start of the day, the starting price is recorded and five horizontal lines are drawn which illustrate possible ranges for the day:
Starting price
Starting price + ATR (+100%)
Starting price - ATR (-100%)
Starting price + ATR/2 (+50%)
Starting price - ATR/2 (-50%)
The final two lines are drawn using the ATR half values in such a way that a X is formed. The X represents possible motion of the price back to starting price (also known as reversion to mean). The two lines are drawn as follows:
Beginning at (Starting Price + ATR/2) and ending at (Starting Price - ATR/2)
Beginning at (Starting Price - ATR/2) and ending at (Starting Price + ATR/2)
Use cases:
ATR presents us with the average amount of price fluctuation we can expect to see in a single day on a specific instrument
If price is near the extremes (+/-100% ATR) for the day, then probability of it moving outside that range is low, which increases odds of a reversal
Bugs?
Kindly report any issues you run into and I'll try to fix them promptly.
Thank you!
ADR (Log Scale) with MTF LabelsHere's a detailed presentation of the Average Daily Range (ADR) indicator, with a focus on its advantages compared to the classic ADR, its unique features, utility, and interpretation:
Advantages Compared to Classic ADR
1. Logarithmic Scale: Unlike the classic ADR, which uses a linear scale, this version uses a logarithmic scale for calculations. This approach provides a more accurate representation of relative price movements, especially for assets with large price ranges.
2. Multi-Timeframe Analysis: This enhanced ADR indicator allows traders to view daily, weekly, and monthly ADRs simultaneously. This multi-timeframe capability helps traders understand volatility trends over different periods, offering a more comprehensive market analysis.
3. Optional Smoothing: The inclusion of an optional smoothing feature (using Exponential Moving Average, EMA) helps reduce noise in the data. This makes the indicator more reliable by filtering out short-term fluctuations and highlighting the underlying volatility trend.
4. Information Display Labels: The indicator includes labels that display precise ADR values for each timeframe directly on the chart. This feature provides immediate, clear insights without requiring additional calculations or references.
Utility of the Indicator
1. Volatility Analysis: The ADR indicator is essential for assessing market volatility. By showing the average daily price range, it helps traders gauge how much an asset typically moves within a day, week, or month.
2. Risk Management: ADR levels can be used to set stop-loss points, improving risk management strategies. Knowing the average range helps traders avoid setting stops too close to the current price, which might otherwise be triggered by normal market fluctuations.
3. Setting Realistic Targets: By understanding the average daily range, traders can set more realistic profit targets. This helps in avoiding over-ambitious goals that are unlikely to be reached within the typical market movement.
4. Identifying Entry and Exit Points: The ADR can signal potential entry and exit points. For example, if the price approaches the upper or lower ADR boundary, it might indicate an overbought or oversold condition, respectively.
Interpretation and Examples
1. Increasing Volatility: If the ADR is increasing, it indicates rising market volatility. Traders might adjust their strategies accordingly, such as widening their stop-losses to accommodate larger price swings.
2. Range Breakout: If the price significantly exceeds the daily ADR, it may signal a strong trend or exceptional market movement. Traders can use this information to stay in the trade longer or to anticipate a potential reversal.
3. Mean Reversion: Prices often revert to the ADR mean. A trader might consider mean reversion trades when the price approaches the extremes of the ADR range, expecting it to move back towards the average.
4. Multi-Timeframe Comparison: If the daily ADR is higher than the weekly ADR, it may indicate unusually high short-term volatility. This can be a signal for traders to be cautious or to capitalize on the increased movement.
While the ADR indicator provides valuable insights into market volatility and can significantly enhance trading strategies, it is essential to remember that no indicator is foolproof. Market conditions can change rapidly, and past performance is not always indicative of future results. Traders should use the ADR indicator in conjunction with other tools and follow sound risk management practices to protect their capital.
Relative Measured Volatility [Seven Campbell]Relative Measured Volatility
Overview:
This indicator measures the current daily volatility of an asset and compares it to the average volatility observed over the past 15 days. It provides a dynamic gauge of how much the market’s volatility is deviating from its recent historical norms.
Key Features:
Dynamic Comparison: The indicator calculates the standard deviation of daily price changes over a user-defined period (default is 14 days) and compares it to a smoothed average of this volatility over the last 15 days. This creates a "moving measuring stick" to highlight periods of unusually high or low volatility.
Customizable Settings:
Lookback Period: Set to 15 days by default, this period defines the historical window used to calculate the average volatility.
Volatility Length: Adjustable length (default is 14) for the standard deviation calculation, allowing you to fine-tune the sensitivity of the volatility measurement.
Smoothing Length: Set to 50 by default, this parameter smooths the volatility data to highlight longer-term trends.
How It Works:
Volatility Calculation: The indicator computes the daily returns using the logarithmic change in closing prices. It then calculates the standard deviation of these returns over the specified volatility length.
Smoothing: The standard deviation values are smoothed using a simple moving average over the smoothing length, providing a clearer view of trends.
Relative Measurement: The current daily volatility is divided by the smoothed volatility, giving a relative value. A value above 1 indicates higher volatility than the average over the past 15 days, while a value below 1 suggests lower volatility.
Visual Representation:
Line Plot: The relative volatility is plotted as a line, allowing you to quickly see changes in volatility relative to the historical average.
Reference Line: A horizontal line at 1 is included for easy reference. Values above this line indicate periods of higher-than-average volatility, and values below suggest lower-than-average volatility.
Use Cases:
Market Sentiment Analysis: Identify periods of high or low volatility to gauge market sentiment.
Trade Timing: Use the indicator to decide on entry and exit points, especially in volatile or calm market conditions.
Risk Management: Monitor volatility to adjust position sizes and stop-loss levels dynamically.
Example Usage:
When the line rises above 1, it signals increasing volatility, which may be a good time to take profit or adjust your stop-loss orders.
When the line drops below 1, it indicates lower volatility, potentially highlighting a stable market period.
Multi-Regression StrategyIntroducing the "Multi-Regression Strategy" (MRS) , an advanced technical analysis tool designed to provide flexible and robust market analysis across various financial instruments.
This strategy offers users the ability to select from multiple regression techniques and risk management measures, allowing for customized analysis tailored to specific market conditions and trading styles.
Core Components:
Regression Techniques:
Users can choose one of three regression methods:
1 - Linear Regression: Provides a straightforward trend line, suitable for steady markets.
2 - Ridge Regression: Offers a more stable trend estimation in volatile markets by introducing a regularization parameter (lambda).
3 - LOESS (Locally Estimated Scatterplot Smoothing): Adapts to non-linear trends, useful for complex market behaviors.
Each regression method calculates a trend line that serves as the basis for trading decisions.
Risk Management Measures:
The strategy includes nine different volatility and trend strength measures. Users select one to define the trading bands:
1 - ATR (Average True Range)
2 - Standard Deviation
3 - Bollinger Bands Width
4 - Keltner Channel Width
5 - Chaikin Volatility
6 - Historical Volatility
7 - Ulcer Index
8 - ATRP (ATR Percentage)
9 - KAMA Efficiency Ratio
The chosen measure determines the width of the bands around the regression line, adapting to market volatility.
How It Works:
Regression Calculation:
The selected regression method (Linear, Ridge, or LOESS) calculates the main trend line.
For Ridge Regression, users can adjust the lambda parameter for regularization.
LOESS allows customization of the point span, adaptiveness, and exponent for local weighting.
Risk Band Calculation:
The chosen risk measure is calculated and normalized.
A user-defined risk multiplier is applied to adjust the sensitivity.
Upper and lower bounds are created around the regression line based on this risk measure.
Trading Signals:
Long entries are triggered when the price crosses above the regression line.
Short entries occur when the price crosses below the regression line.
Optional stop-loss and take-profit mechanisms use the calculated risk bands.
Customization and Flexibility:
Users can switch between regression methods to adapt to different market trends (linear, regularized, or non-linear).
The choice of risk measure allows adaptation to various market volatility conditions.
Adjustable parameters (e.g., regression length, risk multiplier) enable fine-tuning of the strategy.
Unique Aspects:
Comprehensive Regression Options:
Unlike many indicators that rely on a single regression method, MRS offers three distinct techniques, each suitable for different market conditions.
Diverse Risk Measures: The strategy incorporates a wide range of volatility and trend strength measures, going beyond traditional indicators to provide a more nuanced view of market dynamics.
Unified Framework:
By combining advanced regression techniques with various risk measures, MRS offers a cohesive approach to trend identification and risk management.
Adaptability:
The strategy can be easily adjusted to suit different trading styles, timeframes, and market conditions through its various input options.
How to Use:
Select a regression method based on your analysis of the current market trend (linear, need for regularization, or non-linear).
Choose a risk measure that aligns with your trading style and the market's current volatility characteristics.
Adjust the length parameter to match your preferred timeframe for analysis.
Fine-tune the risk multiplier to set the desired sensitivity of the trading bands.
Optionally enable stop-loss and take-profit mechanisms using the calculated risk bands.
Monitor the regression line for potential trend changes and the risk bands for entry/exit signals.
By offering this level of customization within a unified framework, the Multi-Regression Strategy provides traders with a powerful tool for market analysis and trading decision support. It combines the robustness of regression analysis with the adaptability of various risk measures, allowing for a more comprehensive and flexible approach to technical trading.
[SGM Geometric Brownian Motion]Description:
This indicator uses Geometric Brownian Motion (GBM) simulations to predict possible price trajectories of a financial asset. It helps traders visualize potential price movements, assess risks, and make informed decisions.
Geometric Brownian Motion:
Geometric Brownian Motion is an extension of standard Brownian motion (or Wiener process) used to model the random behavior of particles in physics. In finance, this concept is used to model the evolution of asset prices over time in a continuous manner. The basic idea is that the price of an asset does not only change randomly but also exponentially depending on certain parameters.
Basic formula
The formula for the evolution of the price of an asset S(t) under MBG is given by the following stochastic differential equation:
𝑑𝑆(𝑡) = 𝜇𝑆(𝑡)𝑑𝑡 + 𝜎𝑆(𝑡)𝑑𝑊(𝑡)
where:
S(t) is the price of the asset at time
μ is the expected growth rate (or drift).
σ is the volatility of the price of the asset.
dW(t) represents the noise term, i.e. the standard Brownian motion.
Explanations of the terms
Expected growth rate (μ):
This is the expected average return on the asset. If you think your asset will grow by 5% per year,
μ will be 0.05.
Volatility (σ):
It is a measure of the uncertainty or risk associated with the asset. If the asset price varies a lot, σ will be high.
Noise term (dW(t)):
It represents the randomness of the price change, modeled by a Wiener process.
Features:
Customizable number of simulations: Choose the number of price trajectories to simulate to get a better estimate of future movements.
Adjustable simulation length: Set the duration of the simulations in number of periods to adapt the indicator to your trading horizons.
Trajectory display: Visualize the simulated price trajectories directly on the chart to better understand possible future scenarios.
Dispersion calculations: Display the distribution of simulated final prices to assess dispersion and potential variations.
Sharpe ratio distribution: Analyze the risk-adjusted performance of simulations using the Sharpe ratio distribution.
Risk Statistics: Get key risk metrics like maximum drawdown, average return, and Value at Risk (VaR) at different confidence levels.
User Inputs:
Number of Simulations: 200 by default.
Simulation Length: 10 periods by default.
Brownian Motion Transparency: Adjust the transparency of simulated lines for better visualization.
Brownian Motion Display: Enable or disable the display of simulated paths.
Brownian Dispersion Display: Display the distribution of simulated final prices.
Sharpe Dispersion Display: Display the distribution of Sharpe ratios.
Customizable Colors: Choose colors for lines and tables.
Usage:
Configure Settings: Adjust the number of simulations, simulation length, and display preferences to suit your needs.
Analyze Simulated Paths: Simulated path lines appear on the chart, representing possible price developments.
Review Dispersion Charts: Review the charts to understand the distribution of final prices and Sharpe ratios, as well as key risk statistics. This indicator is ideal for traders looking to anticipate future price movements and assess the associated risks. With its detailed simulations and dispersion analyses, it provides valuable insight into the financial markets.
zavaUnni-bitcoin signals(1day)
📌 This strategy predicts price movements based on trading volume and enters positions accordingly. It calculates the expected price increase based on bullish volume and the expected price decrease based on bearish volume to determine the direction of the position.
Top predicted price based on declining bullish volume: top_ifpricebull
Bottom predicted price based on declining bearish volume: top_ifpricebear
Top predicted price based on increasing bullish volume: bot_ifpricebull
Bottom predicted price based on increasing bearish volume: bot_ifpricebear
Using these four values, the strategy calculates the final maxprice and minprice based on volume. If the price settles above the max value, it indicates an upward trend; if it settles below the min value, it indicates a downward trend.
📌 The indicator does not solely rely on the maxprice and minprice conditions. It incorporates complex and sophisticated analysis by considering average volume and candle size.
During a decline, if the average volume and spread of bullish candles exceed those of bearish candles and the price settles above the max value, a long position is entered.
During a rise, if the average volume and spread of bearish candles exceed those of bullish candles and the price settles below the min value, a short position is entered.
Even if the above conditions are met, if the buying pressure significantly outweighs the selling pressure, the position will be closed, but a reverse position will not be entered.
Reviewing historical data shows that while there are instances where the position switches from long to short immediately, there are also cases where the position is closed and re-entered after a few candles.
📌 Trading volume is one of the most traditional yet essential indicators, accurately reflecting price direction. This strategy, which simultaneously predicts fundamental trading volume and price changes, consistently achieves a profit factor above 3.
Characteristics and Historical Data of the Strategy
🔴 Short position entry: April 11, 2022
🟢 Long position entry after closing short: January 11, 2023
⚫ Short position holding period: 270 days
🟢 Long position entry: October 9, 2020
🔵 Long position exit: November 30, 2019
⚫ Long position holding period: 52 days
🟢 Long position entry: November 30, 2019
🔵 Long position exit: February 22, 2021
⚫ Long position holding period: 84 days
Settings Explanation
🛠️ In the input, you can choose between spot and futures. Buy and sell signals are generated in spot trading, while long and short signals are generated in futures trading.
🌈 You can configure the screen view.
Fibonacci Trend
Falling Fibonacci levels from the top: 382 and 618 levels (Red lines)
Rising Fibonacci levels from the bottom: 382 and 618 levels (Green lines)
When the price stays within the 382 and 618 levels of the falling Fibonacci, the background turns red; when it stays within the 382 and 618 levels of the rising Fibonacci, the background turns green.
Real-time Volume Strength of Bullish and Bearish Candles
Red arrow: Appears when the strength of bearish candles increases
Green arrow: Appears when the strength of bullish candles increases
Cumulative Volume of Bullish and Bearish Candles during the Trend
Cumulative data of falling bullish and bearish candles from the top
Cumulative data of rising bullish and bearish candles from the bottom
Profit Table
Provides annual and monthly profit tables.
Setting Options
You can change the options in the attributes to test different configurations.
📌 Trading Data
Although Binance data starts from 2017, limiting the number of trades to 60 as of July 2024, this does not undermine the validity of the strategy. Binance provides reliable volume data, which is crucial for evaluating the strategy's performance. In contrast, exchanges like Bitstamp may have longer trading histories but insufficient volume to properly assess the strategy's actual performance. A volume-based strategy cannot be reliably tested on an exchange with low trading volume. Therefore, despite the limited number of trades on Binance, its reliable volume data justifies its use for this strategy.
► Backtesting Details:
Timeframe: 1D / Bitcoin / TetherUS
Initial Balance: $50,000 (Enter the initial capital you will invest)
Order Size: 10% (Enter the percentage of your account balance you will trade)
Commission: 0.04% (Enter the trading commission)
Slippage: 10 ticks (Enter the slippage you want to test)
When using the strategy:
📢 Timeframe: While the strategy performs well on timeframes lower than daily, it is particularly profitable on the daily timeframe.
📢 Exchange: It is recommended to use Binance due to its reliable volume data.
📢 This strategy is suitable for traders who have the patience to hold positions for extended periods, as it calculates the size of bullish and bearish candles carefully and does not change positions easily.
📢 Spot trading is recommended over futures, and if using futures, leverage should be limited to a maximum of 2x.
Daily Liquidity Peaks and Troughs [ST]Daily Liquidity Peaks and Troughs
Description in English:
This indicator identifies peaks and troughs of highest liquidity on a daily timeframe by analyzing volume data. It helps traders visualize key points of high buying or selling pressure, which could indicate potential reversal or continuation areas.
Detailed Explanation:
Configuration:
Lookback Length: This input defines the period over which the highest high and lowest low are calculated. The default value is 14. This means the script will look at the past 14 bars to determine if the current high or low is a pivot point.
Volume Threshold Multiplier: This input defines the multiplier for the average volume. For example, a multiplier of 1.5 means the volume needs to be 1.5 times the average volume to be considered a significant peak or trough.
Peak Color: This input sets the color for liquidity peaks. The default color is red.
Trough Color: This input sets the color for liquidity troughs. The default color is green.
Volume Calculation:
Average Volume: The script calculates the simple moving average (SMA) of the volume over the lookback period. This helps to identify periods of significantly higher volume.
Volume Threshold: The threshold is determined by multiplying the average volume by the volume threshold multiplier. Only volumes exceeding this threshold are considered significant.
Identifying Peaks and Troughs:
Liquidity Peak: A peak is identified when the current high is the highest high over the lookback period and the current volume exceeds the volume threshold. This indicates a potential area of strong selling pressure.
Liquidity Trough: A trough is identified when the current low is the lowest low over the lookback period and the current volume exceeds the volume threshold. This indicates a potential area of strong buying pressure.
These peaks and troughs are marked on the chart with labels and shapes for easy visualization.
Plotting Peaks and Troughs:
Labels: The script uses labels to mark peaks and troughs on the chart. Peaks are marked with a red label and troughs with a green label.
Shapes: The script plots triangles above peaks and below troughs to highlight these areas visually.
Indicator Benefits:
Liquidity Identification: Helps traders identify key areas of high liquidity, indicating strong buying or selling pressure.
Visual Cues: Provides clear visual signals for potential reversal or continuation points, aiding in making informed trading decisions.
Customizable Parameters: Allows traders to adjust the lookback length and volume threshold to suit different trading strategies and market conditions.
Justification of Component Combination:
Peaks and Troughs Identification: Combining pivot points with volume analysis provides a robust method to identify significant liquidity areas. This helps in detecting potential market reversals or continuations.
Volume Analysis: Utilizing average volume and volume threshold ensures that only significant volume spikes are considered, enhancing the accuracy of identified peaks and troughs.
How Components Work Together:
The script first calculates the average volume over the specified lookback period.
It then checks each bar to see if it qualifies as a liquidity peak or trough based on the highest high, lowest low, and volume threshold.
When a peak or trough is identified, it is marked on the chart with a label and a shape, providing clear visual cues for traders.
Título: Picos e Fundos de Liquidez Diários
Descrição em Português:
Este indicador identifica picos e fundos de maior liquidez no gráfico diário, analisando os dados de volume. Ele ajuda os traders a visualizar pontos-chave de alta pressão de compra ou venda, o que pode indicar áreas potenciais de reversão ou continuação.
Explicação Detalhada:
Configuração:
Comprimento de Retrocesso: Este input define o período sobre o qual a máxima e mínima são calculadas. O valor padrão é 14. Isso significa que o script analisará os últimos 14 candles para determinar se a máxima ou mínima atual é um ponto de pivô.
Multiplicador de Limite de Volume: Este input define o multiplicador para o volume médio. Por exemplo, um multiplicador de 1.5 significa que o volume precisa ser 1.5 vezes o volume médio para ser considerado um pico ou fundo significativo.
Cor do Pico: Este input define a cor para os picos de liquidez. A cor padrão é vermelha.
Cor do Fundo: Este input define a cor para os fundos de liquidez. A cor padrão é verde.
Cálculo do Volume:
Volume Médio: O script calcula a média móvel simples (SMA) do volume ao longo do período de retrocesso. Isso ajuda a identificar períodos de volume significativamente mais alto.
Limite de Volume: O limite é determinado multiplicando o volume médio pelo multiplicador de limite de volume. Apenas volumes que excedem esse limite são considerados significativos.
Identificação de Picos e Fundos:
Pico de Liquidez: Um pico é identificado quando a máxima atual é a máxima mais alta no período de retrocesso e o volume atual excede o limite de volume. Isso indica uma potencial área de forte pressão de venda.
Fundo de Liquidez: Um fundo é identificado quando a mínima atual é a mínima mais baixa no período de retrocesso e o volume atual excede o limite de volume. Isso indica uma potencial área de forte pressão de compra.
Esses picos e fundos são marcados no gráfico com etiquetas e formas para fácil visualização.
Plotagem de Picos e Fundos:
Etiquetas: O script usa etiquetas para marcar picos e fundos no gráfico. Os picos são marcados com uma etiqueta vermelha e os fundos com uma etiqueta verde.
Formas: O script plota triângulos acima dos picos e abaixo dos fundos para destacar essas áreas visualmente.
Benefícios do Indicador:
Identificação de Liquidez: Ajuda os traders a identificar áreas-chave de alta liquidez, indicando forte pressão de compra ou venda.
Cues Visuais: Fornece sinais visuais claros para pontos potenciais de reversão ou continuação, auxiliando na tomada de decisões informadas.
Parâmetros Personalizáveis: Permite que os traders ajustem o comprimento de retrocesso e o limite de volume para se adequar a diferentes estratégias de negociação e condições de mercado.
Justificação da Combinação de Componentes:
Identificação de Picos e Fundos: A combinação de pontos de pivô com análise de volume fornece um método robusto para identificar áreas significativas de liquidez. Isso ajuda na detecção de potenciais reversões ou continuações de mercado.
Análise de Volume: Utilizar o volume médio e o limite de volume garante que apenas picos de volume significativos sejam considerados, aumentando a precisão dos picos e fundos identificados.
Como os Componentes Funcionam Juntos:
O script primeiro calcula o volume médio ao longo do período especificado de retrocesso.
Em seguida, verifica cada barra para ver se ela se qualifica como um pico ou fundo de liquidez com base
Chieu - Bollinger Bands SMA 50 StrategyOverview
The Custom Bollinger Bands Indicator is a versatile tool designed to help traders identify potential market reversals and optimize their trading strategies. This indicator combines Bollinger Bands with an ATR-based stop-loss mechanism, configurable take-profit levels, and dynamic position sizing to manage risk effectively. By highlighting key market conditions and providing clear visual cues, it enables traders to make informed decisions and execute trades with precision.
Key Features
Bollinger Bands Calculation:
The indicator calculates Bollinger Bands based on a configurable Simple Moving Average (SMA) length.
Standard deviation multiplier is adjustable, allowing traders to fine-tune the width of the bands.
Candlestick Highlighting:
Candles that touch the upper or lower Bollinger Bands are highlighted, indicating potential overbought or oversold conditions.
Reversal candles are identified and highlighted based on specific criteria:
The candle must touch the Bollinger Bands for two consecutive periods.
The reversal candle must have a body at least twice the size of the previous candle's body.
The reversal candle must close in the opposite direction to the previous candle (e.g., a bullish candle following a bearish one).
Stop-Loss and Take-Profit Levels:
Stop-loss levels are calculated using the ATR (Average True Range) indicator, ensuring they are dynamically adjusted based on market volatility.
Two configurable take-profit levels (1R and 2R) are plotted based on the initial risk (distance between entry and stop-loss).
Take-profit and stop-loss lines are visually represented on the chart for easy reference.
Position Sizing and Risk Management:
The indicator includes configurable inputs for account balance, leverage, and risk percentage.
It calculates the nominal value (position size without leverage) and cost value (position size with leverage) based on the specified risk parameters.
Combined labels display SL, TP, nominal value, and cost value, replacing the default "Reversal" text for clear, concise information.
Customization Options:
Users can configure the length of the take-profit lines.
The option to toggle the highlighting of candles touching the Bollinger Bands on or off, while always highlighting the identified reversal candles.
How to Use
Configuration:
Set the desired SMA length and Bollinger Bands multiplier in the input settings.
Configure the ATR length for accurate stop-loss calculations.
Adjust the risk-reward ratio and take-profit line length according to your trading strategy.
Specify your account balance, leverage, and risk percentage for precise position sizing.
Chart Analysis:
Monitor the chart for candles touching the upper or lower Bollinger Bands. These highlights indicate potential overbought or oversold conditions.
Look for highlighted reversal candles, which meet the specified criteria and suggest a potential market reversal.
Use the plotted stop-loss and take-profit lines to manage your trades effectively. The combined labels provide all necessary information (SL, TP, nominal value, and cost value) for quick decision-making.
Execution and Risk Management:
Enter trades based on the reversal candle signals.
Set your stop-loss at the indicated level using the ATR calculation.
Take partial profits at the first take-profit level (1R) and adjust your stop-loss to the entry point to secure the remaining position.
Exit the trade entirely at the second take-profit level (2R) or if the price returns to the adjusted stop-loss level.
Consolidation Range Detector [Pt]█ Author's Note:
After extensively reviewing the existing consolidation detection tools in the TradingView library, I found that none fully met my expectations. Some tools were overly sensitive, producing too many invalid ranges, while others lacked the necessary sensitivity. Consequently, I decided to develop my own tool. I hope that you, fellow traders, find it valuable and enjoy using it.
█ Description:
The Consolidation Range Detector is a sophisticated TradingView tool designed to identify and visualize periods of price consolidation on any financial chart. This indicator employs advanced algorithms to detect ranges where price movements are confined, helping traders spot potential breakout zones and make informed trading decisions.
█ Key Features:
► Customizable Detection Sensitivity: Adjust the sensitivity of the detection algorithm to suit your trading strategy, ensuring a precise fit within the consolidation range.
► Dynamic Coloring: Choose between random or fixed colors for the consolidation ranges, with options to match different background color schemes (Dark, Light, Neutral).
► Visual Clarity: Highlight detected consolidation ranges directly on the chart with customizable color schemes to enhance visibility and provide clear visual cues.
► ATR-Based Validation: Ensures detected consolidation ranges are significant and reliable by using the Average True Range (ATR) for validation.
█ User-Defined Inputs:
► Minimum Detection Bars: Set the minimum number of bars required to detect a consolidation range.
► Max Range Multiplier: Define the maximum range for detection as a multiple of the ATR.
► Detection Sensitivity: Adjust the sensitivity of the detection algorithm. Higher values mean a tighter fit within the consolidation range.
► Color Options: Choose the color for the consolidation range boxes and decide whether to use random colors.
► Color Scheme (Background): Select a color scheme for the chart background (Dark, Light, Neutral).
█ How It Works:
► Range Detection: The indicator scans the chart for potential consolidation ranges based on user-defined parameters. It calculates the average price and ATR to determine the significance of the range.
► Validation: Each detected range is validated based on criteria such as ATR threshold, range validity, average price comparison, and the number of touches at the range boundaries.
► Visualization: Validated ranges are highlighted on the chart with colored boxes, providing a clear visual cue of potential consolidation zones.
█ Usage Examples:
► Example 1:
The image below showcases the Consolidation Range Detector in action on a chart of S&P 500 E-mini Futures. The indicator highlights several consolidation ranges with different colors, demonstrating its ability to adapt to varying market conditions and visually emphasize key areas of price consolidation. The annotations for breakouts and price reactions are manually marked to illustrate the practical application of the tool in identifying potential trading opportunities based on these key areas.
█ Practical Applications:
► Identify Breakout Zones: Use the detected consolidation ranges to identify potential breakout zones, helping to anticipate significant price movements.
► Identify Key Price Levels: The tool helps in pinpointing key price levels where there is a high probability of significant price reactions, providing crucial insights for trading strategies.
► Enhance Technical Analysis: Integrate the Consolidation Range Detector into your existing technical analysis toolkit to improve the accuracy of your trading decisions.
█ Conclusion:
The Consolidation Range Detector is a powerful tool for traders looking to identify periods of price consolidation and potential breakout zones. With its customizable settings and advanced detection algorithms, it provides a reliable and visual method to enhance your trading strategy. Whether you're a beginner or an experienced trader, this indicator can add significant value to your technical analysis.
█ Cautionary Note:
While the Consolidation Range Detector is a powerful tool, it's important to combine it with other indicators and analysis methods for comprehensive trading decisions. Always consider market context and external factors when interpreting detected consolidation ranges.
Rolling Price Activity Heatmap [AlgoAlpha]📈 Rolling Price Activity Heatmap 🔥
Enhance your trading experience with the Rolling Price Activity Heatmap , designed by AlgoAlpha to provide a dynamic view of price activity over a rolling lookback period. This indicator overlays a heatmap on your chart, highlighting areas of significant price activity, allowing traders to spot key price levels at a glance.
🌟 Key Features
📊 Rolling Heatmap: Visualize historical price activity intensity over a user-defined lookback period.
🔄 Customizable Lookback: Adjust the heatmap lookback period to suit your trading style.
🌫️ Transparency Filter: Fine-tune the heatmap’s transparency to filter out less significant areas.
🎨 Color Customization: Choose colors for up, down, and highlight areas to fit your chart’s theme.
🔄 Inverse Heatmap Option: Flip the heatmap to highlight less active areas if needed.
🛠 Add the Indicator: Add the Indicator to favorites. Customize settings like lookback period, transparency filter, and colors to fit your trading style.
📊 Market Analysis: Watch for areas of high price activity indicated by the heatmap to identify potential support and resistance levels.
🔧 How it Works
This script calculates the highest and lowest prices within a specified lookback period and divides the price range into 15 segments. It counts the number of candles that fall within each segment to determine areas of high and low price activity. The script then plots the heatmap on the chart, using varying levels of transparency to indicate the strength of price activity in each segment, providing a clear visual representation of where significant trading occurs.
Stay ahead of the market with this powerful visualization tool and make informed trading decisions! 📈💼
Harmonic Trading Tachometer [Pinescriptlabs]Key Features:
Visual Tachometer:
Represents market harmony through a speedometer on the chart.
The tachometer displays a range of harmony from "Highly Bearish" to "Highly Bullish."
Harmony Calculation:
Harmony Score: Based on ATR (Average True Range) range calculations for short, medium, and long periods. The harmony score is a weighted combination of these scores.
Interpretation: Harmony is translated into an interpretive category that can be "Highly Bearish," "Bearish," "Neutral," "Bullish," or "Highly Bullish."
Price Projection:
Estimates future price movement considering the current trend and the weight of each trend period (short, medium, and long).
Harmonic Change Detection:
Identifies significant changes in market harmony and adjusts sensitivity with predefined thresholds.
Confirmation and Divergence Signals:
Detects bullish or bearish confirmation signals as well as divergences, based on market harmony and price projection.
Additional Visualization:
Includes an optional market pentagram chart to visualize harmony on a broader scale.
Provides detailed information in a table about harmony, price projection, and harmonic changes.
How the Script Works:
Initial Calculations:
Ranges and Scores: Calculates ATR ranges for different periods (short, medium, and long). Then, evaluates the harmony score using the given formula.
Harmony: Obtained through the weighted combination of short, medium, and long-term scores.
Price Projection:
The projection is adjusted based on the difference between the current closing price and the exponential moving averages (EMAs) for different periods, weighted by the defined factors.
How to Use :
Tachometer Interpretation:
Observe the needle's position on the tachometer to assess the current market harmony.
Use the colors and labels to quickly interpret the market's state.
Projection and Changes:
Use the price projection to identify potential support or resistance levels.
Monitor harmonic changes and their strengths to adjust your trading strategies.
Confirmations and Divergences:
Pay attention to confirmation and divergence signals to decide on potential entries or exits.
Customization:
Adjust the indicator parameters, such as base length, harmony factor, change detection period, and trend weights, to fit your trading style and timeframe.
Español:
**Tacómetro Visual:
- Representa la armonía del mercado mediante un velocímetro en el gráfico.
- El tacómetro muestra un rango de armonía desde "Altamente Bajista" hasta "Altamente Alcista."
Cálculo de Armonía:
- Puntuación de Armonía:** Basada en los cálculos del rango ATR (Average True Range) para períodos cortos, medios y largos. La puntuación de armonía es una combinación ponderada de estas puntuaciones.
- Interpretación: La armonía se traduce en una categoría interpretativa que puede ser "Altamente Bajista," "Bajista," "Neutral," "Alcista," o "Altamente Alcista."
**Proyección de Precios:
- Estima el movimiento futuro de los precios considerando la tendencia actual y el peso de cada período de tendencia (corto, medio y largo).
**Detección de Cambios Armonicos:
- Identifica cambios significativos en la armonía del mercado y ajusta la sensibilidad con umbrales predefinidos.
**Señales de Confirmación y Divergencia:
- Detecta señales de confirmación alcista o bajista, así como divergencias, basadas en la armonía del mercado y la proyección de precios.
**Visualización Adicional:**
- Incluye un gráfico opcional de un pentagrama de mercado para visualizar la armonía en una escala más amplia.
- Proporciona información detallada en una tabla sobre la armonía, la proyección de precios y los cambios armónicos.
**Cómo Funciona el Script:**
Cálculos Iniciales:
- **Rangos y Puntuaciones:** Calcula los rangos del ATR para diferentes períodos (corto, medio y largo). Luego, evalúa la puntuación de armonía utilizando la fórmula dada.
- **Armonía:** Se obtiene a través de la combinación ponderada de las puntuaciones de corto, medio y largo plazo.
**Proyección de Precios:**
- La proyección se ajusta según la diferencia entre el precio de cierre actual y las medias móviles exponenciales (EMA) para diferentes períodos, ponderadas por los factores definidos.
**Cómo Usar:**
**Interpretación del Tacómetro:**
- Observa la posición de la aguja en el tacómetro para evaluar la armonía actual del mercado.
- Usa los colores y las etiquetas para interpretar rápidamente el estado del mercado.
**Proyección y Cambios:**
- Usa la proyección de precios para identificar posibles niveles de soporte o resistencia.
- Monitorea los cambios armónicos y sus fortalezas para ajustar tus estrategias de trading.
**Confirmaciones y Divergencias:**
- Presta atención a las señales de confirmación y divergencia para decidir posibles entradas o salidas.
**Personalización:**
- Ajusta los parámetros del indicador, como la longitud base, el factor de armonía, el período de detección de cambios y los pesos de tendencia, para adaptarlo a tu estilo de trading y marco de tiempo.
Volume Based Volatility Trail [UAlgo]"Volume Based Volatility Trail ", is designed to identify potential trading opportunities based on volatility and volume analysis. It calculates the Average True Range (ATR) to gauge market volatility and uses a volume-based multiplier to dynamically adjust a trailing stop level. The indicator also incorporates volume analysis to identify high volume periods that might signal potential breakouts.
🔶 Key Features
Volume-Based Volatility Trail: The indicator calculates a trailing stop level based on the ATR, which is then adjusted based on volume. Higher volume periods can lead to a wider trailing stop to account for increased volatility.
Price Source: Users can select the price source (e.g., close, open) for volume calculations.
Customizable Inputs: Users can adjust various parameters like the ATR period, multiplier, smoothing period, volume SMA period, ATR adjustment factor, and colors for buy/sell signals and the trailing stop area.
Buy/Sell Alerts: The indicator generates alerts for potential buy and sell opportunities based on the trailing stop crossing the price.
🔶 Usage
Look for buy signals (▲ marker) when the price crosses above the trailing stop level, potentially indicating a bullish trend.
Conversely, sell signals (▼ marker) appear when the price falls below the trailing stop, suggesting a bearish trend.
The shaded area around the trailing stop represents a buffer zone that might offer some protection against price fluctuations, but it can also indicate areas of potential pullbacks. During volatile periods or after strong price movements, the price might retrace back towards the trailing stop before continuing its trend. This shaded area can help visualize these potential retracement zones.
High volume periods (highlighted by the indicator) can be used in conjunction with other technical analysis to confirm potential breakouts. Analyze these high volume periods alongside price action and other indicators to assess the strength of the breakout and the likelihood of the price continuing its upward move.
🔶 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.
CoT Trend Change MomentumI discovered that whenever there's huge change in long IO or short IO there will be a momentum shift. So, I created this indicator to spot massive explosive volume changes for commercials and non commercials activity. Using standard deviation 2 and -2 as extreme point. Whatever crossing above standard deviation 2 indicating positions are added regardless whether it is long or shorts, whatever crossing below standard deviation -2 means positions are closed.
This is how I use this indicator:
1) In this example , i use only the commercials long and shorts. Whenever the longs exceed stdeviation +2, means that long volume flow in massively, for me this can be indicating potential to the upside. Whenever longs fall below stdeviation-2, for me this can be indicating that commercials are either taking profits for the short positions or accumulating for another bull price.
2) For shorts same logic applied here, when it exceeds stdeviation +2, mean commercials shorts position increase massively, when it exceeds stdeviation-2, means that commercials closed their short positions.
For this script, I use 13 weeks period as lookback, u guys may directly modify the period in the script to set the period that u want.
I've added for non-commercials as well, to ease people who emphasizes on non-commercials positioning analysis process.
I'm still trying to incorporate this with Open Interest Analysis. Hopefully u guys find this indicator useful. Feel free to modify it, to understand it more, my suggestions are u compare date by date the positions, to see the extreme points. The indicator only works in weekly chart, it is non repainted only in weekly chart, meaning that the indicator shows the histogram just as the week open.
Alpha-Sutte Multi-Price Indicator [CHE] Overview
The AlphaSutte MultiPrice Indicator is a powerful tool for forecasting market movements and generating trading signals. At its core is the AlphaSutte Model, which stands out for its innovative approach to predicting future price movements.
Inspired by the () on TradingView, this indicator enhances the original concept by integrating it with the T3 smoothing technique to improve trend identification and signal reliability.
The AlphaSutte Model
The AlphaSutte Model is a mathematical method for forecasting prices based on the analysis of historical price data. It is applied to various price components such as High, Low, Open, and Close. The model predicts future values using differences and weighted averages of previous periods. Here are the key steps and components of the AlphaSutte Model:
1. Data Extraction:
The model extracts historical values at specified intervals. For example, it uses the values from the last four periods for calculations.
2. Difference Calculations:
Differences between successive historical values are calculated:
Delta_x: Difference between the first and fourth values.
Delta_y: Difference between the second and first values.
Delta_z: Difference between the third and second values.
3. Weighted Average Calculation:
These differences are then integrated into a weighted average to forecast the future value:
The weighted average combines the historical values and their differences to calculate the forecasted value, referred to as a_t.
4. Application to Price Components:
The AlphaSutte Model can be applied to various price components:
High: Forecasting the future high price.
Low: Forecasting the future low price.
Open: Forecasting the future opening price.
Close: Forecasting the future closing price.
5. Averaging AlphaSutte Values:
If multiple price components are used for calculation, an average of the AlphaSutte values is computed. This average serves as the basis for generating trading signals.
Trading Signals and Directional Change
The AlphaSutte Model is used to generate long and short trading signals. These signals are confirmed by the directional change of the T3 Indicator to enhance reliability:
Long Signals:
A long signal is generated when the average value of the AlphaSutte Model is positive, and the T3 indicator previously showed a downtrend.
These signals are displayed with green labels and lines on the chart.
Short Signals:
A short signal is generated when the average value of the AlphaSutte Model is negative, and the T3 indicator previously showed an uptrend.
These signals are displayed with red labels and lines on the chart.
StepbyStep Explanation of the Script
The AlphaSutte MultiPrice Indicator script in TradingView is designed to provide comprehensive market trend analysis and trading signal generation. Here is a stepbystep explanation of how the script operates:
1. Input Parameters:
The script begins by defining several input parameters for the T3 indicator and AlphaSutte Model, including:
`t3Length`: The length of the T3 moving average.
`t3VolumeFactor`: The volume factor used in T3 smoothing.
Boolean inputs to determine which price components (High, Low, Open, Close) should use the AlphaSutte Model.
`numLastLabels`: The number of last labels to display for recent signals.
2. T3 Smoothing Function:
The `t3Smoothing` function calculates the T3 smoothed value for the specified source price using a series of exponential moving averages (EMAs):
It calculates six sequential EMAs of the source price.
It then combines these EMAs using specific coefficients to obtain the T3 value.
3. AlphaSutte Calculation Function:
The `get_alpha_sutte` function forecasts future values based on historical price data:
It extracts historical price values at specific intervals.
It calculates the differences (deltas) between these values.
It computes a weighted average of these deltas to obtain the AlphaSutte value.
4. Calculating AlphaSutte Components:
The script calculates the AlphaSutte values for the selected price components (High, Low, Open, Close) based on user input.
It then averages these values if multiple components are selected.
5. Generating Long and Short Conditions:
The script defines conditions for generating long and short signals based on the AlphaSutte average:
`long_condition`: True if the AlphaSutte average is positive.
`short_condition`: True if the AlphaSutte average is negative.
6. Tracking T3 Trend Direction:
The script updates state variables to track whether the T3 line is in an uptrend or downtrend:
`t3_uptrend`: True if the T3 value is higher than the previous T3 value.
`t3_downtrend`: True if the T3 value is lower than the previous T3 value.
7. Generating and Managing Labels and Lines:
The script generates labels and lines on the chart to visualize long and short signals:
For long signals, green labels and lines are created when the long condition is met, and the T3 was previously in a downtrend.
For short signals, red labels and lines are created when the short condition is met, and the T3 was previously in an uptrend.
Old labels and lines are deleted to keep the chart clean and relevant.
8. Updating Lines to Current Candle:
The script dynamically updates the end points of the lines to the current candle to reflect the latest market data.
9. Highlighting Movements:
The script optionally highlights the T3 line based on its direction to visually emphasize the trend:
Green for an uptrend and red for a downtrend.
10. Plotting the T3 Line:
Finally, the T3 line is plotted on the chart with the specified color and line width to provide a clear visualization of the trend.
Conclusion
The primary focus of the AlphaSutte MultiPrice Indicator is on the forecasting capabilities of the AlphaSutte Model. This model's forecasts are the most critical part of the indicator, providing the essential signals for potential market movements. The T3 indicator serves as a confirmation tool, validating these forecasts by indicating the direction of the trend. This combination enhances the reliability of the trading signals, making the AlphaSutte MultiPrice Indicator a valuable asset for traders looking to make informed decisions based on robust market analysis.
Best regards Chervolino
Buffett Valuation Indicator [TradeDots]The Buffett Valuation Indicator (also known as the Buffett Index or Buffett Ratio) measures the ratio of the total United States stock market to GDP.
This indicator helps determine whether the valuation changes in US stocks are justified by the GDP level.
For example, the ratio is calculated based on the standard deviations from the historical trend line. If the value exceeds +2 standard deviations, it suggests that the stock market is overvalued relative to GDP, and vice versa.
This "Buffett Valuation Indicator" is an enhanced version of the original indicator. It applies a Bollinger Band over the Valuation/GDP ratio to identify overvaluation and undervaluation across different timeframes, making it efficient for use in smaller timeframes, e.g. daily or even hourly intervals.
HOW DOES IT WORK
The Buffett Valuation Indicator measures the ratio between US stock valuation and US GDP, evaluating whether stock valuations are overvalued or undervalued in GDP terms.
In this version, the total valuation of the US stock market is represented by considering the top 10 market capitalization stocks.
Users can customize this list to include other stocks for a more balanced valuation ratio. Alternatively, users may use S&P 500 ETFs, such as SPY or VOO, as inputs.
The ratio is plotted as a line chart in a separate panel below the main chart. A Bollinger Band with a default 100-period and multiples of 1 and 2 is used to identify overvaluation and undervaluation.
For instance, if the ratio line moves above the +2 standard deviation line, it indicates that stocks are overvalued, signaling a potential selling opportunity.
APPLICATION
When the indicator is applied to a chart, we observe the ratio line's movements relative to the standard deviation lines. The further the line deviates from the standard deviation lines, the more extreme the overvaluation or undervaluation.
We look for buying opportunities when the Buffett Index moves below the first and second standard deviation lines and sell opportunities when it moves above these lines. This indicator is used as a microeconomic confirmation tool, in combination with other indicators, to achieve higher win-rate setups.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
No Lag SupertrendNo Lag Supertrend indicator improves upon the original supertrend by incorporating calculation methods that enhance responsiveness and accuracy. Traditional supertrend indicators often suffer from lag, which can delay signals and affect trading decisions. No Lag Supertrend addresses this issue through the use of KAMA (Kaufman’s Adaptive Moving Average) and Hull ATR (Average True Range) calculations.
Goals of No Lag Supertrend:
- Lag reduction: one of the main issues with traditional supertrend indicators is their lag, which can result in delayed entry and exit signals. By integrating KAMA and Hull ATR, the no lag supertrend minimizes this delay, providing more timely signals.
- Market Noise Filtering: The combined use of KAMA and Hull ATR effectively filters out market noise, ensuring that signals are based on significant price movements rather than minor fluctuations.
- Consistency Across Different Market Conditions: The adaptive nature of KAMA and the smooth responsiveness of Hull ATR ensure that the No Lag Supertrend performs consistently across various market conditions, from trending to volatile markets.
Credits: This code is based on the TradingView supertrend but improved the ATR calculations.
Custom ATR Trailing StopThis Script creates a custom ATR (Average True Range) trailing stop. It allows traders to set up automated stop-loss levels based on the ATR, which adjusts dynamically to market volatility. The script is designed to support both long and short trades, offering flexibility and precision in trade management.
When loading the indicator to your chart, simply click to set the trade begining time, confirm various settings and you are set.
Check tooltips for more details in the input settigns menu.
User Inputs
Trade Setup: Allows users to set the trade direction (Long or Short), the signal source for entries, and the specific bar time for the trade setup.
ATR Settings: Configurable ATR lookback period, ATR smoothing period, initial ATR multiplier for setting the stop-loss, breakeven ATR multiplier, and a manual breakeven level.
ATR Calculations
Computes the ATR and its moving average.
Determines initial and breakeven stop levels based on the ATR.
Signal Validation
Validates long or short trade signals based on the specified bar time and trade direction.
Triggers alerts when a valid trade signal is detected.
Trailing Stop Logic
For long trades, adjusts the stop-loss level dynamically based on the ATR.
For short trades, performs similar adjustments in the opposite direction.
Updates the trailing stop level to ensure it follows the price, moving closer as the price moves favorably.
Resets the trade state when the stop-loss is hit, triggering an alert.
Plotting
Plots the trailing stop levels on the chart.
Uses green for stop levels indicating profit and red for stop levels indicating a loss.
T3 [RATE OF CHANGE] by SKiNNiEHDeveloped by Tim Tillson, the Tilson Moving Average (T3) is a trend indicator with the advantage of having less lag than other ones. That is, a faster moving average. The T3 moving average is an "indicator of an indicator" as it includes several EMAs of another EMA. Unlike other moving averages, the t3 adds the so-called volume factor, a value between 0 and 1.
The T3 RATE OF CHANGE by SKiNNiEH is a unique indicator that integrates the T3 moving average with a normalized Rate of Change (RoC) calculation. Unlike traditional T3 moving averages, this indicator provides additional smoothing modes (SINGLE, DOUBLE & TRIPLE) for the T3, whilst enhancing visual feedback of the plotted line by generating a dynamic line thickness, a dynamic line color & brightness and trade entry bars, offering traders a more dynamic view of market conditions without going "overboard" with settings.
How It Works
Visualization
The T3 line varies in thickness and color based on the RoC values, giving traders visual cues about market strength and direction.
Thicker and brighter lines indicate stronger trends, while thinner and duller lines suggest weaker trends.
Rate of Change Filte r
This filter refines trend detection by using the line thickness measurement.
Adjustable from 0 (disabled) to 4, where higher settings only consider stronger trends for signals.
The T3 line turns gray when the filter is triggered or when the RoC is extremely low, signaling a weak or neutral market.
T3 Calculation (mode)
SINGLE
The T3 calculation is applied once to the closing price.
This mode has the least smoothing effect and the least lag. It reacts more quickly to price changes but is less smooth.
DOUBLE
The T3 calculation is applied twice sequentially.
The first T3 calculation smooths the closing price.
The second T3 calculation smooths the result of the first T3 calculation.
This mode provides more smoothing and introduces more lag compared to SINGLE mode. It is smoother but reacts slower to price changes.
TRIPLE
The T3 calculation is applied three times sequentially.
The first T3 calculation smooths the closing price.
The second T3 calculation smooths the result of the first T3 calculation.
The third T3 calculation smooths the result of the second T3 calculation.
This mode provides the most smoothing and introduces the most lag by reacting the slowest to price changes.
Rate of Change (RoC) Calculation
The script calculates the Rate of Change (RoC) for the T3 values based on the selected mode (SINGLE, DOUBLE, TRIPLE). The RoC measures the percentage change between the most recent value and a value in the past. The measurement is then normalized in three different ranges.
Normalization 5: Determines T3 line thickness on a scale from 0 - 5
Normalization 10: Determines T3 color brightness on a scale from 0 - 10
Normalization 100: Determines Rate of Change percentage
Rate of Change Filter
The script uses the RoC filter to refine the trend detection logic. By using the line thickness measurement, a filter can be enabled by setting this input on 1 - 4. As an example, setting this to 4 means that only a line thickness of 5 would be considered for a trade signal. Setting this to 0 disables the filter. The T3 line will turn gray when the filter is triggered, the T3 line can also turn gray without the filter, when the Rate of Change is extremely low.
Trade Signals
A trade signal is printed as a vertical green or red bar when the following conditions are met:
Long:
Closing price is above the T3 line
Rate of Change percentage is above 0
Previous trade signal was a short signal **
Rate of Change is not filtered
Short:
Closing price is below the T3 line
Rate of Change percentage is below 0
Previous trade signal was a long signal **
Rate of Change is not filtered
** Or this is the very first recorded trade signal
It should be noted that the trade signals in this script are trade entry signals, not trade exit signals. Use at your own risk.
Instructions for Use
Setting Up the Indicator
Apply the indicator to your trading chart.
Choose the desired T3 mode (SINGLE, DOUBLE, TRIPLE) based on your need for smoothing and lag.
Set the desired length (lookback period).
Set the desired factor between 0 and 1 (increments of 0.1)
Choose an overall line thickness and brightness that suits your screen and taste preferences.
Apply the Rate of Change filter. Setting this to 0 will disable the filter
Tip: use the trade entry vertical bars as a visual calibration tool the adjust mode, length, factor and filter.
Interpreting Visual Cues
Observe the T3 line's thickness: thicker lines indicate stronger trends, while thinner lines suggest weaker trends.
Observe the T3 line's color and color brightness: green indicates a more bullish trend, while red indicates a more bearish trend. A brighter color suggest a stronger trend. A gray color means the RoC is very low / neutral, or the RoC filter is active.
Observe the T3 line's location relative to price: below price indicates a more bullish trend, above price indicates a more bearish trend. The T3 line distance from price can also be an indication of trend strength.
Observe vertical bars: a vertical bar is printed green when long conditions are met, a vertical bar is printed red when short conditions are met. See the rules that explain the trigger for this bar above.
Alerts
Go to the settings tab, set the condition to T3.RoC.S + LONG or SHORT.
Enter an alert name and message.
Configure your notification preferences in the notifications tab and create the alert
Notifications-tab: Choose your notification preferences
Create the alert.
Fractalyst Moving Average [Adaptive] | FractalystWhat's the indicator purpose and functionality?
Moving averages are widely used technical indicators in trading.
Typically, they provide reliable entry signals in trending markets but can falter during consolidation periods.
Now, imagine a moving average that adjusts to market conditions.
The Fractalyst Moving Average does just that by adapting to the market's noise level, which is the erratic price movement within trends or consolidation phases.
This indicator incorporates market structure into moving averages to more effectively identify potential market trends.
By dynamically calculating moving averages based on external swing highs and lows, it offers robust trend identification and adapts to different market conditions, giving traders valuable insights into current market condition.
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How does FRMA react in a trending and consolidating market?
When the market trends, the FRMA adjusts quickly to price movements, closely tracking the trend and positioning itself close to prices. This responsiveness allows it to provide timely signals and effectively capture trends.
However, in consolidating markets where there is little net change in price over time, the FRMA reacts slowly. As consolidation prolongs, the FRMA may even cease to move significantly, appearing non-reactive. This characteristic helps minimize false signals and unnecessary trades during periods of market indecision.
Notice how the FRMA tracks prices closely when the market is trending. When the market begins to consolidate, however, the FRMA becomes relatively unresponsive and stays horizontal.
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What are the underlying calculations behind FRMA?
Identifying Swing Highs and Lows: FRMA begins by identifying the most recent external swing highs and lows, which are key pivot points in the market's price structure.
Defining Market Structure: It calculates the distance between these external swing levels. When price remains confined between these levels, indicating a horizontal market, it signifies minor intermediate ranges or a lack of clear trend direction.
Adapting to Breaks of Structure: When a new break of structure occurs—such as a significant price movement above a previous swing high or below a swing low—the FRMA updates dynamically.
It adjusts its values to reflect the midpoint (50%) of the distance between the external swing highs and lows.
This adjustment helps the FRMA react promptly to changes in different market environments.
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How to use the FRMA in trading?
In a trend-following context, the FRMA provides clear signals for trading:
Buying Signal: Look to buy when the FRMA is rising. This indicates that the market is in an uptrend, with prices consistently moving higher. Buying at these points aligns with the trend momentum and increases the likelihood of capturing profitable movements.
Selling Signal: Consider selling when the FRMA is falling. A declining FRMA suggests that the market is in a downtrend, where prices are consistently decreasing. Selling during these periods helps capitalize on downward movements and potential profit-taking opportunities.
Avoiding Trades: Avoid trading when the FRMA appears horizontal and the market is consolidating. This indicates a lack of clear trend direction or significant price movement, which can lead to choppy price action and increased risk of false signals. Waiting for the FRMA to resume a clear trend direction can help avoid unnecessary losses in consolidating markets.
Note: These rules are just examples and may generate numerous false signals. Even when the FRMA is less responsive, it can exhibit frequent changes in direction.
Traders should apply additional filters or confirmatory indicators to refine their trading decisions and mitigate the impact of false signals.
Depending on whether they're employing mean-reversion or trend-following trading styles, traders need to adjust other market filters accordingly.
It's crucial to conduct thorough backtesting using various market conditions and filters to validate and optimize their trading strategies effectively.
This process helps traders identify the settings that best align with their trading goals and market conditions.
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What makes this moving average unique compared to others?
Yes, it's another moving average, but the Fractalyst Adaptive Moving Average stands out for a compelling reason.
Its calculation is more sophisticated, leveraging market structure to identify potential consolidation and trending environments, similar to conventional moving averages such as SMA and EMA.
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How does the FRMA's stack up against the other moving averages?
Since markets are always evolving, using adaptive strategy elements like the FRMA certainly makes a whole lot of sense.
However, from a practical standpoint, the only way to find out would be to exhaustively backtest the various moving averages across all markets of interest.
Establishing equivalency between the FRMA and other moving averages may be a little challenging, since the FRMA does not use a single integer value for its lookback period.
Assuming the backtests produced roughly equal results, I’d personally prefer to use the FRMA. Its adaptive qualities give me confidence that the strategy can weather changing market conditions.
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User-inputs and customizations
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Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
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