ADM Indicator [CHE] Comprehensive Description of the Three Market Phases for TradingView
Introduction
Financial markets often exhibit patterns that reflect the collective behavior of participants. Recognizing these patterns can provide traders with valuable insights into potential future price movements. The ADM Indicator is designed to help traders identify and capitalize on these patterns by detecting three primary market phases:
1. Accumulation Phase
2. Manipulation Phase
3. Distribution Phase
This indicator places labels on the chart to signify these phases, aiding traders in making informed decisions. Below is an in-depth explanation of each phase, including how the ADM Indicator detects them.
1. Accumulation Phase
Definition
The Accumulation Phase is a period where informed investors or institutions discreetly purchase assets before a potential price increase. During this phase, the price typically moves within a confined range between established highs and lows.
Characteristics
- Price Range Bound: The asset's price stays within the previous high and low after a timeframe change.
- Low Volatility: Minimal price movement indicates a balance between buyers and sellers.
- Steady Volume: Trading volume may remain relatively constant or show slight increases.
- Market Sentiment: General market interest is low, as the accumulation is not yet apparent to the broader market.
Detection with ADM Indicator
- Criteria: An accumulation is detected when the price remains within the previous high and low after a timeframe change.
- Indicator Action: At the end of the period, if accumulation has occurred, the indicator places a label "Accumulation" on the chart.
- Visual Cues: A yellow semi-transparent background highlights the accumulation phase, enhancing visual recognition.
Implications for Traders
- Entry Opportunity: Consider preparing for potential long positions before a possible upward move.
- Risk Management: Use tight stop-loss orders below the support level due to the defined trading range.
2. Manipulation Phase
Definition
The Manipulation Phase, also known as the Shakeout Phase, occurs when dominant market players intentionally move the price to trigger stop-loss orders and create panic among less-informed traders. This action generates liquidity and better entry prices for large positions.
Characteristics
- False Breakouts: The price moves above the previous high or below the previous low but quickly reverses.
- Increased Volatility: Sharp price movements occur without fundamental reasons.
- Stop-Loss Hunting: The price targets common stop-loss areas, triggering them before reversing.
- Emotional Trading: Retail traders may react impulsively, leading to poor trading decisions.
Detection with ADM Indicator
- Manipulation Up:
- Criteria: Detected when the price rises above the previous high and then falls back below it.
- Indicator Action: Places a label "Manipulation Up" on the chart at the point of detection.
- Manipulation Down:
- Criteria: Detected when the price falls below the previous low and then rises back above it.
- Indicator Action: Places a label "Manipulation Down" on the chart at the point of detection.
- Visual Cues:
- Manipulation Up: Blue background highlights the phase.
- Manipulation Down: Orange background highlights the phase.
Implications for Traders
- Caution Advised: Be wary of false signals and avoid overreacting to sudden price changes.
- Preparation for Next Phase: Use this phase to anticipate potential distribution and adjust strategies accordingly.
3. Distribution Phase
Definition
The Distribution Phase occurs when the institutions or informed investors who accumulated positions start selling to the general market at higher prices. This phase often follows a Manipulation Phase and may signal an impending trend reversal.
Characteristics
- Price Reversal: The price moves in the opposite direction of the prior manipulation.
- High Trading Volume: Increased selling activity as large players offload positions.
- Trend Weakening: The previous trend loses momentum, indicating a potential shift.
- Market Sentiment Shift: Optimism fades, and uncertainty or pessimism may emerge.
Detection with ADM Indicator
- Distribution Up:
- Criteria: Detected after a verified Manipulation Up when the price subsequently falls below the previous low.
- Indicator Action: Places a label "Distribution Up" on the chart.
- Distribution Down:
- Criteria: Detected after a verified Manipulation Down when the price subsequently rises above the previous high.
- Indicator Action: Places a label "Distribution Down" on the chart.
- Visual Cues:
- Distribution Up: Purple background highlights the phase.
- Distribution Down: Maroon background highlights the phase.
Implications for Traders
- Exit Signals: Consider closing long positions if in a Distribution Up phase.
- Short Selling Opportunities: Potential to enter short positions anticipating a downtrend.
Using the ADM Indicator on TradingView
Indicator Overview
The ADM Indicator automates the detection of Accumulation, Manipulation, and Distribution phases by analyzing price movements relative to previous highs and lows on a selected timeframe. It provides visual cues and labels on the chart, helping traders quickly identify the current market phase.
Features
- Multi-Timeframe Analysis: Choose from auto, multiplier, or manual timeframe settings.
- Visual Labels: Clear labeling of market phases directly on the chart.
- Background Highlighting: Distinct background colors for each phase.
- Customizable Settings: Adjust colors, styles, and display options.
- Period Separators: Optional separators delineate different timeframes.
Interpreting the Indicator
1. Accumulation Phase
- Detection: Price stays within the previous high and low after a timeframe change.
- Label: "Accumulation" placed at the period's end if detected.
- Background: Yellow semi-transparent color.
- Action: Prepare for potential long positions.
2. Manipulation Phase
- Detection:
- Manipulation Up: Price rises above previous high and then falls back below.
- Manipulation Down: Price falls below previous low and then rises back above.
- Labels: "Manipulation Up" or "Manipulation Down" placed at detection.
- Background:
- Manipulation Up: Blue color.
- Manipulation Down: Orange color.
- Action: Exercise caution; avoid impulsive trades.
3. Distribution Phase
- Detection:
- Distribution Up: After a Manipulation Up, price falls below previous low.
- Distribution Down: After a Manipulation Down, price rises above previous high.
- Labels: "Distribution Up" or "Distribution Down" placed at detection.
- Background:
- Distribution Up: Purple color.
- Distribution Down: Maroon color.
- Action: Consider exiting positions or entering counter-trend trades.
Configuring the Indicator
- Timeframe Type: Select Auto, Multiplier, or Manual for analysis timeframe.
- Multiplier: Set a custom multiplier when using "Multiplier" type.
- Manual Resolution: Define a specific timeframe with "Manual" option.
- Separator Settings: Customize period separators for visual clarity.
- Label Display Options: Choose to display all labels or only the most recent.
- Visualization Settings: Adjust colors and styles for personal preference.
Practical Tips
- Combine with Other Analysis Tools: Use alongside volume indicators, trend lines, or other technical tools.
- Backtesting: Review historical data to understand how the indicator signals would have impacted past trades.
- Stay Informed: Keep abreast of market news that might affect price movements beyond technical analysis.
- Risk Management: Always employ stop-loss orders and position sizing strategies.
Conclusion
The ADM Indicator is a valuable tool for traders seeking to understand and leverage market phases. By detecting Accumulation, Manipulation, and Distribution phases through specific price action criteria, it provides actionable insights into market dynamics.
Understanding the precise conditions under which each phase is detected empowers traders to make more informed decisions. Whether preparing for potential breakouts during accumulation, exercising caution during manipulation, or adjusting positions during distribution, the ADM Indicator aids in navigating the complexities of the financial markets.
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
This indicator is inspired by the Super 6x Indicators: RSI, MACD, Stochastic, Loxxer, CCI, and Velocity . A special thanks to Loxx for their relentless effort, creativity, and contributions to the TradingView community, which served as a foundation for this work.
Best regards Chervolino
Overview of the Timeframe Levels in the `autotimeframe()` Function
The `autotimeframe()` function automatically adjusts the higher timeframe based on the current chart timeframe. Here are the specific timeframe levels used in the function:
- Current Timeframe ≤ 1 Minute
→ Higher Timeframe: 240 Minutes (4 Hours)
- Current Timeframe ≤ 5 Minutes
→ Higher Timeframe: 1 Day
- Current Timeframe ≤ 1 Hour
→ Higher Timeframe: 3 Days
- Current Timeframe ≤ 4 Hours
→ Higher Timeframe: 7 Days
- Current Timeframe ≤ 12 Hours
→ Higher Timeframe: 1 Month
- Current Timeframe ≤ 1 Day
→ Higher Timeframe: 3 Months
- Current Timeframe ≤ 7 Days
→ Higher Timeframe: 6 Months
- For All Higher Timeframes (over 7 Days)
→ Higher Timeframe: 12 Months
Summary:
The function assigns a corresponding higher timeframe based on the current timeframe to optimize the analysis:
- 1 Minute or Less → 4 Hours
- Up to 5 Minutes → 1 Day
- Up to 1 Hour → 3 Days
- Up to 4 Hours → 7 Days
- Up to 12 Hours → 1 Month
- Up to 1 Day → 3 Months
- Up to 7 Days → 6 Months
- Over 7 Days → 12 Months
This automated adjustment ensures that the indicator works effectively across different chart timeframes without requiring manual changes.
Cerca negli script per "liquidity"
Trading Sessions with Highs and LowsTrading Sessions with Highs and Lows is designed to visually highlight specific trading sessions on the chart, providing traders with key insights into market behavior during these time periods. Here’s a detailed explanation of how the indicator works:
Key Features
1. Session Boxes:
• The indicator plots colored boxes on the chart to represent the price range of defined trading sessions.
• Each box spans the session’s start and end times and encapsulates the high and low prices during that period.
• Two trading sessions are defined by default:
• USA Trading Session: 9:30 AM - 4:00 PM (New York Time).
• UK Trading Session: 8:00 AM - 4:30 PM (London Time).
2. Session Labels:
• The name of the session (e.g., “USA” or “UK”) is displayed above the session box for clear identification.
3. High and Low Markers:
• Markers are added to the chart at the session’s high and low points:
• High Marker: A green label indicating the session high.
• Low Marker: A red label indicating the session low.
4. Dynamic Reset:
• After the session ends, the session high and low values are reset to na to prepare for the next trading day.
5. Customizable Background Colors:
• Each session’s box has a distinct, semi-transparent background color for better visual separation.
How It Works
1. Core Functionality:
• A function, plot_box, takes the session name, start time, end time, and background color as input.
• It calculates whether the current time is within the session.
• During the session:
• It tracks the session’s highest and lowest prices.
• It identifies the bars where the high and low occurred.
• At the session’s end:
• It plots a box on the chart covering the session’s time and price range.
• Labels are created for the session name and its high/low points.
2. Session Timing:
• Timestamps for the USA and UK trading sessions are calculated using the timestamp function with respective time zones.
3. Visual Elements:
• The box.new function draws the session boxes on the chart.
• The label.new function creates session name and high/low labels.
Usage
• Overlay Mode: The indicator is applied directly on the price chart (overlay=true), making it easy to visualize session-specific price behavior.
• Trading Strategy:
• Identify session-specific support and resistance levels.
• Observe price action trends during key trading periods.
• Align trading decisions with session dynamics.
Customization
While the indicator is preset for the USA and UK trading sessions, it can be easily modified:
1. Add/Remove Sessions: Define additional sessions by providing their start and end times.
2. Change Colors: Update the background_color in the plot_box calls to use different colors for sessions.
3. Adjust Time Zones: Replace the current time zones with others relevant to your trading style.
Visualization Example
• USA Session:
• Time: 9:30 AM - 4:00 PM (New York Time).
• Box Color: Semi-transparent orange.
• UK Session:
• Time: 8:00 AM - 4:30 PM (London Time).
• Box Color: Semi-transparent green.
Why Use This Indicator?
1. Market Awareness: Easily spot price behavior during high-liquidity trading periods.
2. Trend Analysis: Analyze how sessions overlap or affect each other.
3. Session Boundaries: Use session high/low levels as dynamic support and resistance zones.
This indicator is an essential tool for intraday and swing traders who want to align their strategies with key market timings.
Crypto Arbitrage Scanner [CryptoSea]Crypto Arbitrage Scanner
The Crypto Arbitrage Scanner is an advanced tool designed to help traders identify arbitrage opportunities across multiple cryptocurrency exchanges. With the ability to compare prices, volumes, and differences in price, this indicator is a must-have for any trader seeking to exploit cross-exchange inefficiencies in real time.
Key Features
Multi-Exchange Price and Volume Comparison: Tracks data from multiple major cryptocurrency exchanges, including BINANCE, COINBASE, KUCOIN, and others, allowing traders to easily compare prices and volume across platforms.
Customizable Difference Metrics: Allows users to toggle between displaying price differences in percentages or absolute dollar values, depending on the preferred metric for arbitrage analysis.
Sorting and Filtering Options: Includes user-defined sorting options to order the data by Price, Volume, or Difference, helping to prioritize potential arbitrage opportunities based on the trader's chosen criteria.
Difference and Volume Thresholds: Users can specify the minimum volume and price difference thresholds, ensuring that only significant arbitrage opportunities are highlighted.
Real-Time Alerts: Built-in alert conditions notify users when arbitrage opportunities exceed their defined price difference thresholds, helping traders respond instantly to market movements.
The Crypto Arb Scanner displays a table of prices, volumes, and price differences across selected exchanges. Each exchange is listed along with the current close price, volume, and the difference in price compared to the average price across all exchanges. Highlighting is used to indicate significant differences that may present arbitrage opportunities.
In the example below, we can see a highlighted opportunity in green showing that the price is below the user inputed thresold.
How it Works
Data Collection: Gathers real-time volume and price data from various exchanges using a streamlined process, allowing for a detailed comparison.
Average Price Calculation: Computes the average price across all valid exchanges to identify where price discrepancies occur, providing a clear picture of arbitrage potential.
Sorting Mechanism: Utilizes custom sorting based on user preferences, making it easy to quickly analyze and identify key opportunities.
Dynamic Highlighting and Alerts: Price differences that exceed user-defined thresholds are highlighted, and alerts can be triggered for these arbitrage opportunities, allowing for a timely response.
Application
Arbitrage Trading: The Crypto Arb Scanner is ideal for traders looking to exploit price differences across exchanges, enabling efficient arbitrage opportunities.
Market Efficiency Analysis: Offers insights into the consistency of prices across exchanges, which can help gauge the efficiency and liquidity of the markets being traded.
Customizable Alerts: Set alerts based on price differences or volume, allowing traders to stay informed about changes without constantly monitoring the markets.
The Crypto Arbitrage Scanner is a powerful addition to any trader's toolkit, offering comprehensive features to detect arbitrage opportunities with confidence. With real-time monitoring, customizable metrics, and a user-friendly interface, this tool allows traders to make informed decisions and capitalize on inefficiencies across exchanges.
Trend Speed Analyzer (Zeiierman)█ Overview
The Trend Speed Analyzer by Zeiierman is designed to measure the strength and speed of market trends, providing traders with actionable insights into momentum dynamics. By combining a dynamic moving average with wave and speed analysis, it visually highlights shifts in trend direction, market strength, and potential reversals. This tool is ideal for identifying breakout opportunities, gauging trend consistency, and understanding the dominance of bullish or bearish forces over various timeframes.
█ How It Works
The indicator employs a Dynamic Moving Average (DMA) enhanced with an Accelerator Factor, allowing it to adapt dynamically to market conditions. The DMA is responsive to price changes, making it suitable for both long-term trends and short-term momentum analysis.
Key components include:
Trend Speed Analysis: Measures the speed of market movements, highlighting momentum shifts with visual cues.
Wave Analysis: Tracks bullish and bearish wave sizes to determine market strength and bias.
Normalized Speed Values: Ensures consistency across different market conditions by adjusting for volatility.
⚪ Average Wave and Max Wave
These metrics analyze the size of bullish and bearish waves over a specified Lookback Period:
Average Wave: This represents the mean size of bullish and bearish movements, helping traders gauge overall market strength.
Max Wave: Highlights the largest movements within the period, identifying peak momentum during trend surges.
⚪ Current Wave Ratio
This feature compares the current wave's size against historical data:
Average Wave Ratio: Indicates if the current momentum exceeds historical averages. A value above 1 suggests the trend is gaining strength.
Max Wave Ratio: Shows whether the current wave surpasses previous peak movements, signaling potential breakouts or trend accelerations.
⚪ Dominance
Dominance metrics reveal whether bulls or bears have controlled the market during the Lookback Period:
Average Dominance: Compares the net difference between average bullish and bearish wave sizes.
Max Dominance: Highlights which side had the stronger individual waves, indicating key power shifts in market dynamics.
Positive values suggest bullish dominance, while negative values point to bearish control. This helps traders confirm trend direction or anticipate reversals.
█ How to Use
Identify Trends: Leverage the color-coded candlesticks and dynamic trend line to assess the overall market direction with clarity.
Monitor Momentum: Use the Trend Speed histogram to track changes in momentum, identifying periods of acceleration or deceleration.
Analyze Waves: Compare the sizes of bullish and bearish waves to identify the prevailing market bias and detect potential shifts in sentiment. Additionally, fluctuations in Current Wave ratio values should be monitored as early indicators of possible trend reversals.
Evaluate Dominance: Utilize dominance metrics to confirm the strength and direction of the current trend.
█ Settings
Maximum Length: Sets the smoothing of the trend line.
Accelerator Multiplier: Adjusts sensitivity to price changes.
Lookback Period: Defines the range for wave calculations.
Enable Table: Displays statistical metrics for in-depth analysis.
Enable Candles: Activates color-coded candlesticks.
Collection Period: Normalizes trend speed values for better accuracy.
Start Date: Limits calculations to a specific timeframe.
Timer Option: Choose between using all available data or starting from a custom date.
-----------------
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!
Max Pain StrategyThe Max Pain Strategy uses a combination of volume and price movement thresholds to identify potential "pain zones" in the market. A "pain zone" is considered when the volume exceeds a certain multiple of its average over a defined lookback period, and the price movement exceeds a predefined percentage relative to the price at the beginning of the lookback period.
Here’s how the strategy functions step-by-step:
Inputs:
length: Defines the lookback period used to calculate the moving average of volume and the price change over that period.
volMultiplier: Sets a threshold multiplier for the volume; if the volume exceeds the average volume multiplied by this factor, it triggers the condition for a potential "pain zone."
priceMultiplier: Sets a threshold for the minimum percentage price change that is required for a "pain zone" condition.
Calculations:
averageVolume: The simple moving average (SMA) of volume over the specified lookback period.
priceChange: The absolute difference in price between the current bar's close and the close from the lookback period (length).
Pain Zone Condition:
The condition for entering a position is triggered if both the volume is higher than the average volume by the volMultiplier and the price change exceeds the price at the length-period ago by the priceMultiplier. This is an indication of significant market activity that could result in a price move.
Position Entry:
A long position is entered when the "pain zone" condition is met.
Exit Strategy:
The position is closed after the specified holdPeriods, which defines how many periods the position will be held after being entered.
Visualization:
A small triangle is plotted on the chart where the "pain zone" condition is met.
The background color changes to a semi-transparent red when the "pain zone" is active.
Scientific Explanation of the Components
Volume Analysis and Price Movement: These are two critical factors in trading strategies. Volume often serves as an indicator of market strength (or weakness), and price movement is a direct reflection of market sentiment. Higher volume with significant price movement may suggest that the market is entering a phase of increased volatility or trend formation, which the strategy aims to exploit.
Volume analysis: The study of volume as an indicator of market participation, with increased volume often signaling stronger trends (Murphy, J. J., Technical Analysis of the Financial Markets).
Price movement thresholds: A large price change over a short period may be interpreted as a breakout or a potential reversal point, aligning with volatility and liquidity analysis (Schwager, J. D., Market Wizards).
Repainting Check: This strategy does not involve any repainting because it is based on current and past data, and there is no reference to future values in the decision-making process. However, any strategy that uses lagging indicators or conditions based on historical bars, like close , is inherently a lagging strategy and might not predict real-time price action accurately until after the fact.
Risk Management: The position hold duration is predefined, which adds an element of time-based risk control. This duration ensures that the strategy does not hold a position indefinitely, which could expose it to unnecessary risk.
Potential Issues and Considerations
Repainting:
The strategy does not utilize future data or conditions that depend on future bars, so it does not inherently suffer from repainting issues.
However, since the strategy relies on volume and price change over a set lookback period, the decision to enter or exit a trade is only made after the data for the current bar is complete, meaning the trade decisions are somewhat delayed, which could be seen as a lagging feature rather than a repainting one.
Lagging Nature:
As with many technical analysis-based strategies, this one is based on past data (moving averages, price changes), meaning it reacts to market movements after they have already occurred, rather than predicting future price actions.
Overfitting Risk:
With parameters like the lookback period and multipliers being user-adjustable, there is a risk of overfitting to historical data. Adjusting parameters too much based on past performance can lead to poor out-of-sample results (Gauthier, P., Practical Quantitative Finance).
Conclusion
The Max Pain Strategy is a simple approach to identifying potential market entries based on volume spikes and significant price changes. It avoids repainting by relying solely on historical and current bar data, but it is inherently a lagging strategy that reacts to price and volume patterns after they have occurred. Therefore, the strategy can be effective in trending markets but may struggle in highly volatile, sideways markets.
XAMD/AMDX ICT 01 [TradingFinder] SMC Quarterly Theory Cycles🔵 Introduction
The XAMD/AMDX strategy, combined with the Quarterly Theory, forms the foundation of a powerful market structure analysis. This indicator builds upon the principles of the Power of 3 strategy introduced by ICT, enhancing its application by incorporating an additional phase.
By extending the logic of Power of 3, the XAMD/AMDX tool provides a more detailed and comprehensive view of daily market behavior, offering traders greater precision in identifying key movements and opportunities
This approach divides the trading day into four distinct phases : Accumulation (19:00 - 01:00 EST), Manipulation (01:00 - 07:00 EST), Distribution (07:00 - 13:00 EST), and Continuation or Reversal (13:00 - 19:00 EST), collectively known as AMDX.
Each phase reflects a specific market behavior, providing a structured lens to interpret price action. Building on the fractal nature of time in financial markets, the Quarterly Theory introduces the Four Quarters Method, where a currency pair’s price range is divided into quarters.
These divisions, known as quarter points, highlight critical levels for analyzing and predicting market dynamics. Together, these principles allow traders to align their strategies with institutional trading patterns, offering deeper insights into market trends
🔵 How to Use
The AMDX framework provides a structured approach to understanding market behavior throughout the trading day. Each phase has its own characteristics and trading opportunities, allowing traders to align their strategies effectively. To get the most out of this tool, understanding the dynamics of each phase is essential.
🟣 Accumulation
During the Accumulation phase (19:00 - 01:00 EST), the market is typically quiet, with price movements confined to a narrow range. This phase is where institutional players accumulate their positions, setting the stage for future price movements.
Traders should use this time to study price patterns and prepare for the next phases. It’s a great opportunity to mark key support and resistance zones and set alerts for potential breakouts, as the low volatility makes immediate trading less attractive.
🟣 Manipulation
The Manipulation phase (01:00 - 07:00 EST) is often marked by sharp and deceptive price movements. Institutions create false breakouts to trigger stop-losses and trap retail traders into the wrong direction. Traders should remain cautious during this phase, focusing on identifying the areas of liquidity where these traps occur.
Watching for price reversals after these false moves can provide excellent entry opportunities, but patience and confirmation are crucial to avoid getting caught in the manipulation.
🟣 Distribution
The Distribution phase (07:00 - 13:00 EST) is where the day’s dominant trend typically emerges. Institutions execute large trades, resulting in significant price movements. This phase is ideal for trading with the trend, as the market provides clearer directional signals.
Traders should focus on identifying breakouts or strong momentum in the direction of the trend established during this period. This phase is also where traders can capitalize on setups identified earlier, aligning their entries with the market’s broader sentiment.
🟣 Continuation or Reversal
Finally, the Continuation or Reversal phase (13:00 - 19:00 EST) offers a critical juncture to assess the market’s direction. This phase can either reinforce the established trend or signal a reversal as institutions adjust their positions.
Traders should observe price behavior closely during this time, looking for patterns that confirm whether the trend is likely to continue or reverse. This phase is particularly useful for adjusting open positions or initiating new trades based on emerging signals.
🔵 Settings
Show or Hide Phases.
Adjust the session times for each phase :
Accumulation: 19:00-01:00 EST
Manipulation: 01:00-07:00 EST
Distribution: 07:00-13:00 EST
Continuation or Reversal: 13:00-19:00 EST
Modify Visualization : Customize how the indicator looks by changing settings like colors and transparency.
🔵 Conclusion
AMDX provides traders with a practical method to analyze daily market behavior by dividing the trading day into four key phases: Accumulation, Manipulation, Distribution, and Continuation or Reversal. Each phase highlights specific market dynamics, offering insights into how institutional activity shapes price movements.
From the quiet buildup in the Accumulation phase to the decisive trends of the Distribution phase, and the critical transitions in Continuation or Reversal, this approach equips traders with the tools to anticipate movements and make informed decisions.
By recognizing the significance of each phase, traders can avoid common traps during Manipulation, capitalize on clear trends during Distribution, and adapt to changes in the final phase of the day.
The structured visualization of market phases simplifies decision-making for traders of all levels. By incorporating these principles into your trading strategy, you can enhance your ability to align with market trends, optimize entry and exit points, and achieve more consistent results in your trading journey.
Global Index Spread RSI StrategyThis strategy leverages the relative strength index (RSI) to monitor the price spread between a global benchmark index (such as AMEX) and the currently opened asset in the chart window. By calculating the spread between these two, the strategy uses RSI to identify oversold and overbought conditions to trigger buy and sell signals.
Key Components:
Global Benchmark Index: The strategy compares the current asset with a predefined global index (e.g., AMEX) to measure relative performance. The choice of a global benchmark allows the trader to analyze the current asset's movement in the context of broader market trends.
Spread Calculation:
The spread is calculated as the percentage difference between the current asset's closing price and the global benchmark index's closing price:
Spread=Current Asset Close−Global Index CloseGlobal Index Close×100
Spread=Global Index CloseCurrent Asset Close−Global Index Close×100
This metric provides a measure of how the current asset is performing relative to the global index. A positive spread indicates the asset is outperforming the benchmark, while a negative spread signals underperformance.
RSI of the Spread: The RSI is then calculated on the spread values. The RSI is a momentum oscillator that ranges from 0 to 100 and is commonly used to identify overbought or oversold conditions in asset prices. An RSI below 30 is considered oversold, indicating a potential buying opportunity, while an RSI above 70 is overbought, suggesting that the asset may be due for a pullback.
Strategy Logic:
Entry Condition: The strategy enters a long position when the RSI of the spread falls below the oversold threshold (default 30). This suggests that the asset may have been oversold relative to the global benchmark and might be due for a reversal.
Exit Condition: The strategy exits the long position when the RSI of the spread rises above the overbought threshold (default 70), indicating that the asset may have become overbought and a price correction is likely.
Visual Reference:
The RSI of the spread is plotted on the chart for visual reference, making it easier for traders to monitor the relative strength of the asset in relation to the global benchmark.
Overbought and oversold levels are also drawn as horizontal reference lines (70 and 30), along with a neutral level at 50 to show market equilibrium.
Theoretical Basis:
The strategy is built on the mean reversion principle, which suggests that asset prices tend to revert to a long-term average over time. When prices move too far from this mean—either being overbought or oversold—they are likely to correct back toward equilibrium. By using RSI to identify these extremes, the strategy aims to profit from price reversals.
Mean Reversion: According to financial theory, asset prices oscillate around a long-term average, and any extreme deviation (overbought or oversold conditions) presents opportunities for price corrections (Poterba & Summers, 1988).
Momentum Indicators (RSI): The RSI is widely used in technical analysis to measure the momentum of an asset. Its application to the spread between the asset and a global benchmark allows for a more nuanced view of relative performance and potential turning points in the asset's price trajectory.
Practical Application:
This strategy works best in markets where relative strength is a key factor in decision-making, such as in equity indices, commodities, or forex markets. By assessing the performance of the asset relative to a global benchmark and utilizing RSI to identify extremes in price movements, the strategy helps traders to make more informed decisions based on potential mean reversion points.
While the "Global Index Spread RSI Strategy" offers a method for identifying potential price reversals based on relative strength and oversold/overbought conditions, it is important to recognize that no strategy is foolproof. The strategy assumes that the historical relationship between the asset and the global benchmark will hold in the future, but financial markets are subject to a wide array of unpredictable factors that can lead to sudden changes in price behavior.
Risk of False Signals:
The strategy relies heavily on the RSI to trigger buy and sell signals. However, like any momentum-based indicator, RSI can generate false signals, particularly in highly volatile or trending markets. In such conditions, the strategy may enter positions too early or exit too late, leading to potential losses.
Market Context:
The strategy may not account for macroeconomic events, news, or other market forces that could cause sudden shifts in asset prices. External factors, such as geopolitical developments, monetary policy changes, or financial crises, can cause a divergence between the asset and the global benchmark, leading to incorrect conclusions from the strategy.
Overfitting Risk:
As with any strategy that uses historical data to make decisions, there is a risk of overfitting the model to past performance. This could result in a strategy that works well on historical data but performs poorly in live trading conditions due to changes in market dynamics.
Execution Risks:
The strategy does not account for slippage, transaction costs, or liquidity issues, which can impact the execution of trades in real-market conditions. In fast-moving markets, prices may move significantly between order placement and execution, leading to worse-than-expected entry or exit prices.
No Guarantee of Profit:
Past performance is not necessarily indicative of future results. The strategy should be used with caution, and risk management techniques (such as stop losses and position sizing) should always be implemented to protect against significant losses.
Traders should thoroughly test and adapt the strategy in a simulated environment before applying it to live trades, and consider seeking professional advice to ensure that their trading activities align with their risk tolerance and financial goals.
References:
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
SessionsOverview of the "Sessions" Indicator
The "Sessions" indicator is a powerful tool designed for traders who want to visualize and analyze the market activity during different global trading sessions directly on their charts. This indicator highlights the London, New York, Tokyo, and Sydney sessions with distinct background colors, making it easy to see when each market is open.
Key Features
Session Visualization: The indicator provides clear visual cues for the active trading sessions, allowing traders to quickly identify periods of high market activity.
Customizable Timeframes: Users can set their preferred resolution for viewing session data, making it adaptable to any trading strategy.
Automatic Session Detection: The indicator automatically detects the start and end of each session based on specified times, updating in real-time as the market progresses.
Practical Applications
Trend Identification: By observing how prices move during specific sessions, traders can identify trends and make informed predictions about future price movements.
Volatility Analysis: Different sessions often exhibit varying levels of volatility. This indicator helps traders anticipate potential price spikes or lulls during these times.
Strategy Optimization: Traders can optimize their strategies by focusing on sessions that align with their trading style, whether it's the high volatility of the London session or the quieter Sydney session.
Market Overlap: The indicator makes it easy to see when sessions overlap, which is typically when the market experiences increased liquidity and volatility.
Conclusion
The "Sessions" indicator is an essential tool for traders looking to enhance their market analysis by visualizing global trading sessions. Whether you're a day trader seeking to capitalize on volatile market conditions or a swing trader looking for optimal entry and exit points, this indicator provides valuable insights into market dynamics.
M2 Suite [KFB Quant]M2 Suite
The M2 Suite is a specialized technical indicator designed to analyze global M2 money supply data from major economies (US, EU, China, and Japan). It aggregates this macroeconomic data and transforms it into actionable insights for crypto trading, assisting with trend-following strategies on a 1D timeframe. By leveraging M2 money supply changes as an economic signal, the M2 Suite highlights potential long and short opportunities based on market liquidity trends.
Functionality:
The M2 Suite aggregates global M2 money supply data, normalizing it to USD for comparability. It calculates percentage changes over multiple timeframes (30–360 days) and averages these changes to score the strength and direction of the M2 trend. With customizable smoothing options, users can tailor the indicator to suit their trading style.
Signal Modes:
Users can choose from three signal modes for maximum flexibility:
Standard – Displays raw trend signals without smoothing.
Smoothed – Applies user-selected smoothing (EMA, SMA, or WMA) for cleaner signals.
Combined – Provides both standard and smoothed signals for a complete picture.
Indicator Features:
Thresholds: Define long and short entry points using customizable score and percentage change thresholds.
Signal Smoothing: Adjust signal clarity with selectable smoothing methods and lengths.
Visual Enhancements: Features gradient-colored signal lines, dynamic background shading, and labeled signal markers for enhanced chart readability.
Limitations:
The M2 Suite is intended for crypto markets and performs best on the 1D timeframe due to the daily data it requests. It should be used as part of a broader trading strategy, as it reflects historical macroeconomic trends and doesn’t predict future movements. Additionally, past results do not guarantee future performance.
Disclaimer: This tool is provided for informational and educational purposes only and should not be considered as financial advice. Always conduct your own research and consult with a licensed financial advisor before making any investment decisions.
Adaptive Kalman Trend Filter (Zeiierman)█ Overview
The Adaptive Kalman Trend Filter indicator is an advanced trend-following tool designed to help traders accurately identify market trends. Utilizing the Kalman Filter—a statistical algorithm rooted in control theory and signal processing—this indicator adapts to changing market conditions, smoothing price data to filter out noise. By focusing on state vector-based calculations, it dynamically adjusts trend and range measurements, making it an excellent tool for both trend-following and range-based trading strategies. The indicator's adaptive nature is enhanced by options for volatility adjustment and three unique Kalman filter models, each tailored for different market conditions.
█ How It Works
The Kalman Filter works by maintaining a model of the market state through matrices that represent state variables, error covariances, and measurement uncertainties. Here’s how each component plays a role in calculating the indicator’s trend:
⚪ State Vector (X): The state vector is a two-dimensional array where each element represents a market property. The first element is an estimate of the true price, while the second element represents the rate of change or trend in that price. This vector is updated iteratively with each new price, maintaining an ongoing estimate of both price and trend direction.
⚪ Covariance Matrix (P): The covariance matrix represents the uncertainty in the state vector’s estimates. It continuously adapts to changing conditions, representing how much error we expect in our trend and price estimates. Lower covariance values suggest higher confidence in the estimates, while higher values indicate less certainty, often due to market volatility.
⚪ Process Noise (Q): The process noise matrix (Q) is used to account for uncertainties in price movements that aren’t explained by historical trends. By allowing some degree of randomness, it enables the Kalman Filter to remain responsive to new data without overreacting to minor fluctuations. This noise is particularly useful in smoothing out price movements in highly volatile markets.
⚪ Measurement Noise (R): Measurement noise is an external input representing the reliability of each new price observation. In this indicator, it is represented by the setting Measurement Noise and determines how much weight is given to each new price point. Higher measurement noise makes the indicator less reactive to recent prices, smoothing the trend further.
⚪ Update Equations:
Prediction: The state vector and covariance matrix are first projected forward using a state transition matrix (F), which includes market estimates based on past data. This gives a “predicted” state before the next actual price is known.
Kalman Gain Calculation: The Kalman gain is calculated by comparing the predicted state with the actual price, balancing between the covariance matrix and measurement noise. This gain determines how much of the observed price should influence the state vector.
Correction: The observed price is then compared to the predicted price, and the state vector is updated using this Kalman gain. The updated covariance matrix reflects any adjustment in uncertainty based on the latest data.
█ Three Kalman Filter Models
Standard Model: Assumes that market fluctuations follow a linear progression without external adjustments. It is best suited for stable markets.
Volume Adjusted Model: Adjusts the filter sensitivity based on trading volume. High-volume periods result in stronger trends, making this model suitable for volume-driven assets.
Parkinson Adjusted Model: Uses the Parkinson estimator, accounting for volatility through high-low price ranges, making it effective in markets with high intraday fluctuations.
These models enable traders to choose a filter that aligns with current market conditions, enhancing trend accuracy and responsiveness.
█ Trend Strength
The Trend Strength provides a visual representation of the current trend's strength as a percentage based on oscillator calculations from the Kalman filter. This table divides trend strength into color-coded segments, helping traders quickly assess whether the market is strongly trending or nearing a reversal point. A high trend strength percentage indicates a robust trend, while a low percentage suggests weakening momentum or consolidation.
█ Trend Range
The Trend Range section evaluates the market's directional movement over a specified lookback period, highlighting areas where price oscillations indicate a trend. This calculation assesses how prices vary within the range, offering an indication of trend stability or the likelihood of reversals. By adjusting the trend range setting, traders can fine-tune the indicator’s sensitivity to longer or shorter trends.
█ Sigma Bands
The Sigma Bands in the indicator are based on statistical standard deviations (sigma levels), which act as dynamic support and resistance zones. These bands are calculated using the Kalman Filter's trend estimates and adjusted for volatility (if enabled). The bands expand and contract according to market volatility, providing a unique visualization of price boundaries. In high-volatility periods, the bands widen, offering better protection against false breakouts. During low volatility, the bands narrow, closely tracking price movements. Traders can use these sigma bands to spot potential entry and exit points, aiming for reversion trades or trend continuation setups.
Trend Based
Volatility Based
█ How to Use
Trend Following:
When the Kalman Filter is green, it signals a bullish trend, and when it’s red, it indicates a bearish trend. The Sigma Cloud provides additional insights into trend strength. In a strong bullish trend, the cloud remains below the Kalman Filter line, while in a strong bearish trend, the cloud stays above it. Expansion and contraction of the Sigma Cloud indicate market momentum changes. Rapid expansion suggests an impulsive move, which could either signal the continuation of the trend or be an early sign of a possible trend reversal.
Mean Reversion: Watch for prices touching the upper or lower sigma bands, which often act as dynamic support and resistance.
Volatility Breakouts: Enable volatility-adjusted sigma bands. During high volatility, watch for price movements that extend beyond the bands as potential breakout signals.
Trend Continuation: When the Kalman Filter line aligns with a high trend strength, it signals a continuation in that direction.
█ Settings
Measurement Noise: Adjusts how sensitive the indicator is to price changes. Higher values smooth out fluctuations but delay reaction, while lower values increase sensitivity to short-term changes.
Kalman Filter Model: Choose between the standard, volume-adjusted, and Parkinson-adjusted models based on market conditions.
Band Sigma: Sets the standard deviation used for calculating the sigma bands, directly affecting the width of the dynamic support and resistance.
Volatility Adjusted Bands: Enables bands to dynamically adapt to volatility, increasing their effectiveness in fluctuating markets.
Trend Strength: Defines the lookback period for trend strength calculation. Shorter periods result in more responsive trend strength readings, while longer periods smooth out the calculation.
Trend Range: Specifies the lookback period for the trend range, affecting the assessment of trend stability over time.
-----------------
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!
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.
-----------------
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!
Volumetric Rejection Blocks [UAlgo]The Volumetric Rejection Blocks is designed to help traders identify and visualize key price levels where volumetric rejections occur, which may indicate a shift in market sentiment. These rejections can signal potential trend reversals or areas where price action is likely to face support or resistance. By drawing rejection blocks based on volumetric strength, the indicator allows users to observe where significant buying or selling pressure has been exerted, which can be used as a reference point for future price action.
Also indicator dynamically calculates swing highs and lows, analyzes bullish and bearish strengths based on volume-weighted price movements, and displays rejection blocks on the chart. Each rejection block represents an area where the price attempted to move beyond a certain level but faced rejection, either on a close or wick basis. This can be particularly useful for traders who rely on market structure and order flow to make informed decisions about entering or exiting trades.
🔶 Key Features
Swing Length Customization: Allows users to define the swing length, helping tailor the sensitivity of the swing high and low detection to the specific market conditions.
Rejection Block Visualization: Displays up to the last 10 rejection blocks based on user settings, clearly marking areas of significant bullish or bearish rejections.
Volumetric Strength Analysis: The indicator calculates bullish and bearish strength for each rejection block, based on volume-weighted price movements over the last few bars, giving insight into the intensity of the rejection.
Violation Check Type: Offers two options for violation detection—"Close" and "Wick". This allows traders to specify whether a price level is considered broken only if it closes beyond the level or if any wick breaches it.
Bullish and Bearish Block Coloring: Rejection blocks are colored to represent bullish (green) and bearish (red) rejection areas. The color transparency can be adjusted for clear visibility overlaid on the price chart.
Market Structure Labels: Labels and lines marking "Market Structure Shift" (MSS) and "Break of Structure" (BOS) are displayed, giving traders context about significant market structure changes.
🔶 Interpreting the Indicator
Rejection Blocks: These colored blocks on the chart indicate areas where the price faced significant buying or selling pressure. A green block suggests a bullish rejection (support zone), where buyers absorbed the sell-off, potentially pushing the price upward. Conversely, a red block indicates a bearish rejection (resistance zone), where sellers overpowered buyers, potentially driving the price lower.
Strength Analysis: The width of the green and red sections within a rejection block represents the relative bullish and bearish strengths. A wider green section indicates stronger bullish support, while a wider red section suggests more robust bearish resistance. This helps traders gauge the likelihood of price holding or breaching these levels.
Market Structure Shift (MSS) and Break of Structure (BOS): The indicator automatically detects and labels significant changes in market structure. An "MSS" label indicates the first break, suggesting a potential shift in trend direction. A "BOS" label indicates a subsequent confirmation in trend direction, allowing traders to recognize potential trend continuations.
Violation Check: Traders can choose how to interpret breaks of these rejection blocks. Using the "Close" option provides a more conservative approach, requiring a close beyond the level for confirmation. The "Wick" option is more aggressive, treating any wick beyond the level as a break.
🔶 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.
Globex time (New York Time)This indicator is designed to highlight and analyze price movements within the Globex session. Primarily geared toward the Globex Trap trading strategy, this tool visually identifies the session's high and low prices, allowing traders to better assess price action during extended hours. Here’s a comprehensive breakdown of its features and functionality:
Purpose
The "Globex Time (New York Time)" indicator tracks price levels during the Globex trading session, providing a clear view of overnight market activity. This session, typically running from 6 p.m. ET (18:00) until the following morning at 8:30 a.m. ET, is a critical period where significant market positioning can occur before the regular session opens. In the Globex Trap strategy, the session high and low are essential levels, as price movements around these areas often indicate potential support, resistance, or reversal zones, which traders use to set up entries or exits when the regular trading session begins.
Key Features
Customizable Session Start and End Times
The indicator allows users to specify the exact start and end times of the Globex session in New York time. The default settings are:
Start: 6 p.m. ET (18:00)
End: 8:30 a.m. ET
These settings can be adjusted to align with specific market hours or personal preferences.
Session High and Low Identification
Throughout the defined session, the indicator dynamically calculates and tracks:
Session High: The highest price reached within the session.
Session Low: The lowest price reached within the session.
These levels are essential for the Globex Trap strategy, as price action around them can indicate likely breakout or reversal points when regular trading resumes.
Vertical Lines for Session Start and End
The indicator draws vertical lines at both the session start and end times:
Session Start Line: A solid line marking the exact beginning of the Globex session.
Session End Line: A similar vertical line marking the session’s conclusion.
Both lines are customizable in terms of color and thickness, making it easy to distinguish the session boundaries visually on the chart.
Horizontal Lines for Session High and Low
At the end of the session, the indicator plots horizontal lines representing the Globex session's high and low levels. Users can customize these lines:
Color: Define specific colors for the session high (default: red) and session low (default: green) to easily differentiate them.
Line Style: Options to set the line style (solid, dashed, or dotted) provide flexibility for visual preferences and chart organization.
Automatic Reset for Daily Tracking
To adapt to the next trading day, the indicator resets the session high and low data once the current session ends. This reset prepares it to start tracking new levels at the beginning of the next session without manual intervention.
Practical Application in the Globex Trap Strategy
In the Globex Trap strategy, traders are primarily interested in price behavior around the high and low levels established during the overnight session. Common applications of this indicator for this strategy include:
Breakout Trades: Watching for price to break above the Globex high or below the Globex low, indicating potential momentum in the breakout direction.
Reversal Trades: Monitoring for failed breakouts or traps where price tests and rejects the Globex high or low, suggesting a reversal as liquidity is trapped in these zones.
Support and Resistance Zones: Using the session high and low as key support and resistance levels during the regular trading session, with potential entry or exit points when price approaches these areas.
Additional Configuration Options
Vertical Line Color and Width: Define the color and thickness of the vertical session start and end lines to match your chart’s theme.
Upper and Lower Line Colors and Styles: Customize the appearance of the session high and low horizontal lines by setting color and line style (solid, dashed, or dotted), making it easy to distinguish these critical levels from other chart markings.
Summary
This indicator is a valuable tool for traders implementing the Globex Trap strategy. It visually segments the Globex session and marks essential price levels, helping traders analyze market behavior overnight. Through its customizable options and clear visual representation, it simplifies tracking overnight price activity and identifying strategic levels for potential trade setups during the regular session.
Implied Fair Value Gap (IFVG) ICT [TradingFinder] Hidden FVG OTE🔵 Introduction
The Implied Fair Value Gap (IFVG) is distinctive due to its unique three-candlestick formation, which differentiates it from conventional Fair Value Gaps.
Implied fair value represents an estimated worth of an asset—often a business or its goodwill—based on the price likely to be received in a structured transaction between market participants at a specific point in time.
In the ever-evolving world of technical analysis, pinpointing price reversal points and market anomalies can significantly enhance trading strategies and decision-making for traders and investors. Among the advanced concepts gaining traction in this field is the Implied Fair Value Gap (IFVG), introduced by the renowned analyst Inner Circle Trader (ICT).
This tool has proven to be an effective method for identifying hidden supply and demand zones in financial markets, offering a unique edge to traders looking for high-probability setups.
Unlike traditional gaps that are visible on price charts, IFVG is a hidden gap that doesn’t appear explicitly on the chart and thus requires specialized technical analysis tools for accurate identification.
This hidden gap can signal potential price reversals and offers traders insight into high-liquidity areas where price is likely to react. This article will guide you through using the ICT Implied Fair Value Gap Indicator effectively, covering its settings, usage strategies, and key features to help you make informed decisions in the market.
🟣 Bullish Implied FVG
🟣 Bearish Implied FVG
🔵 How to Use
The IFVG indicator is designed to assist traders in recognizing hidden support and resistance zones by identifying Bullish and Bearish IFVG patterns. With this tool, traders can make better-informed decisions about suitable entry and exit points for their trades based on these patterns.
🟣 Bullish Implied Fair Value Gap
This pattern occurs in an uptrend when a large bullish candlestick forms, with the wicks of the previous and following candles overlapping the body of the central candlestick.
This overlap creates a demand zone or a hidden support level, which can act as an ideal entry point for buy trades. Often, when the price returns to this area, it is likely to resume its upward trend, presenting a profitable buying opportunity.
🟣 Bearish Implied Fair Value Gap
This pattern is similar but forms in downtrends. Here, a large bearish candlestick appears on the chart, with the wicks of adjacent candles overlapping its body. This overlap defines a supply zone or a hidden resistance level and serves as a signal for potential sell trades.
When the price returns to this zone, it often continues its downward trend, providing an optimal point for entering sell trades.
The IFVG indicator also includes various filters that traders can use to refine their analysis based on market conditions. These filters, including Very Aggressive, Aggressive, Defensive, and Very Defensive, allow users to customize the IFVG zones' width, offering flexibility according to the trader’s risk tolerance and trading style.
🟣 Example Trading Scenarios
Suppose you’re in a strong uptrend and the IFVG indicator identifies a Bullish IFVG zone. In this scenario, you could consider entering a buy trade when the price retraces to this zone, expecting the uptrend to resume. Conversely, in a downtrend, a Bearish IFVG zone can signal a favorable entry point for short trades when the price revisits this area.
🔵 Settings
Implied Block Validity Period: This parameter specifies the validity period of each identified block, taking into account the number of bars that have passed since its formation. Proper adjustment of this period helps traders focus only on relevant zones, increasing the accuracy of the analysis.
Mitigation Level OB : This option defines the mitigation level for supply and demand blocks (Order Blocks), with settings including Proximal, 50% OB, and Distal.
Depending on the selected level, the indicator will focus on closer, mid-range, or farther points for block identification, allowing traders to adjust for the level of precision required.
Implied Filter : Activating this filter allows traders to apply conditions based on the width of the IFVG zones. With options like Very Aggressive and Very Defensive, traders can control the width of IFVG zones to suit their risk management strategy—whether they prefer high-risk setups or low-risk setups.
Display and Color Settings : This section enables users to customize the appearance of the IFVG zones on their charts. Traders can set different colors for Bullish and Bearish zones, allowing for easier distinction and improved visualization.
Alert Settings : One of the standout features of the IFVG indicator is the alert system. By setting up alerts, users can be notified whenever the price approaches a demand or supply zone.
Alerts can be customized to trigger Once Per Bar (one alert per bar) or Per Bar Close (alert at the close of each bar), ensuring that traders stay updated on critical price movements without needing to monitor the chart continuously.
🔵 Conclusion
The ICT Implied Fair Value Gap (IFVG) indicator is a powerful and sophisticated tool in technical analysis, allowing professional traders to identify hidden supply and demand zones and use them as entry and exit points for buy and sell trades.
This indicator’s automatic detection of IFVG zones helps traders uncover hidden trading opportunities that can enhance their analysis.
While the IFVG indicator offers numerous advantages, it is important to use it in conjunction with other technical analysis tools and sound risk management practices.
IFVG alone does not guarantee profitability in trading; it works best when combined with other indicators such as volume analysis and trend-following indicators for a comprehensive trading strategy.
Dynamic Market Correlation Analyzer (DMCA) v1.0Description
The Dynamic Market Correlation Analyzer (DMCA) is an advanced TradingView indicator designed to provide real-time correlation analysis between multiple assets. It offers a comprehensive view of market relationships through correlation coefficients, technical indicators, and visual representations.
Key Features
- Multi-asset correlation tracking (up to 5 symbols)
- Dynamic correlation strength categorization
- Integrated technical indicators (RSI, MACD, DX)
- Customizable visualization options
- Real-time price change monitoring
- Flexible timeframe selection
## Use Cases
1. **Portfolio Diversification**
- Identify highly correlated assets to avoid concentration risk
- Find negatively correlated assets for hedging strategies
- Monitor correlation changes during market events
2. Pairs Trading
- Detect correlation breakdowns for potential trading opportunities
- Track correlation strength for pair selection
- Monitor technical indicators for trade timing
3. Risk Management
- Assess portfolio correlation risk in real-time
- Monitor correlation shifts during market stress
- Identify potential portfolio vulnerabilities
4. **Market Analysis**
- Study sector relationships and rotations
- Analyze cross-asset correlations (e.g., stocks vs. commodities)
- Track market regime changes through correlation patterns
Components
Input Parameters
- **Timeframe**: Custom timeframe selection for analysis
- **Length**: Correlation calculation period (default: 20)
- **Source**: Price data source selection
- **Symbol Selection**: Up to 5 customizable symbols
- **Display Options**: Table position, text color, and size settings
Technical Indicators
1. **Correlation Coefficient**
- Range: -1 to +1
- Strength categories: Strong/Moderate/Weak (Positive/Negative)
2. **RSI (Relative Strength Index)**
- 14-period default setting
- Momentum comparison across assets
3. **MACD (Moving Average Convergence Divergence)**
- Standard settings (12, 26, 9)
- Trend direction indicator
4. **DX (Directional Index)**
- Trend strength measurement
- Based on DMI calculations
Visual Components
1. **Correlation Table**
- Symbol identifiers
- Correlation coefficients
- Correlation strength descriptions
- Price change percentages
- Technical indicator values
2. **Correlation Plot**
- Real-time correlation visualization
- Multiple correlation lines
- Reference levels at -1, 0, and +1
- Color-coded for easy identification
Installation and Setup
1. Load the indicator on TradingView
2. Configure desired symbols (up to 5)
3. Adjust timeframe and calculation length
4. Customize display settings
5. Enable/disable desired components (table, plot, RSI)
Best Practices
1. **Symbol Selection**
- Choose related but distinct assets
- Include a mix of asset classes
- Consider market cap and liquidity
2. **Timeframe Selection**
- Match timeframe to trading strategy
- Consider longer timeframes for strategic analysis
- Use shorter timeframes for tactical decisions
3. **Interpretation**
- Monitor correlation changes over time
- Consider multiple timeframes
- Combine with other technical analysis tools
- Account for market conditions and volatility
Performance Notes
- Calculations update in real-time
- Resource usage scales with number of active symbols
- Historical data availability may affect initial calculations
Version History
- v1.0: Initial release with core functionality
- Multi-symbol correlation analysis
- Technical indicator integration
- Customizable display options
Future Enhancements (Planned)
- Additional technical indicators
- Advanced correlation algorithms
- Enhanced visualization options
- Custom alert conditions
- Statistical significance testing
Austin's Apex AcceleratorIndicator Name: Austin’s Apex Accelerator
Overview
The Austin’s Apex Accelerator is a highly aggressive trading indicator designed specifically for high-frequency Forex trading. It combines several technical analysis tools to identify rapid entry and exit points, making it well-suited for intraday or even lower timeframe trades. The indicator leverages a combination of exponential moving averages (EMAs), Bollinger Bands, volume filters, and volatility-adjusted ranges to detect breakout opportunities and manage risk with precision.
Core Components
Fast and Slow EMAs: The two EMAs act as trend and momentum indicators. When the shorter EMA crosses the longer EMA, it signals a change in momentum. The crossover of these EMAs often indicates a potential entry point, especially when combined with volume and volatility filters.
ATR-Based Range Filter: Using the Average True Range (ATR) for dynamic range calculation, the indicator adapts to market volatility. Higher ATR values widen the range, helping the indicator adjust for volatile conditions.
Volume Filter: A volume condition ensures that buy and sell signals only trigger when there’s significant market interest, reducing the likelihood of false signals in low-liquidity environments.
Bollinger Bands: The Bollinger Bands provide additional context for potential overbought or oversold conditions, highlighting opportunities for price reversals or trend continuations.
Key Features
Aggressive Buy and Sell Signals:
Buy Signal: A buy signal is generated when the fast EMA crosses above the slow EMA, confirming bullish momentum, and the volume condition is met. If the price is also near the lower Bollinger Band, it adds further confirmation of an oversold condition.
Sell Signal: A sell signal is generated when the fast EMA crosses below the slow EMA, confirming bearish momentum, with sufficient trading volume. If the price is near the upper Bollinger Band, it signals a potential overbought condition, which supports the sell signal.
Dynamic Range with ATR:
The indicator uses a volatility-based range, derived from the ATR, to adjust the signal sensitivity based on recent price fluctuations. This dynamic range ensures that signals are responsive in both high and low volatility conditions.
The range’s upper and lower bands act as thresholds, with trades often occurring when the price breaches these levels, signaling momentum shifts or trend reversals.
Trend Background Color:
A green background highlights bullish trends when the fast EMA is above the slow EMA.
A red background signifies bearish trends when the fast EMA is below the slow EMA, providing a visual indication of the overall market trend direction.
Trend Line:
The indicator plots a dynamic trend line that changes color based on the price's relationship to the EMAs, helping traders quickly assess the current trend’s strength and direction.
Alerts:
The indicator includes configurable alerts for buy and sell signals, allowing traders to be notified of entry opportunities without needing to monitor the chart continuously.
How to Use Austin’s Apex Accelerator
Identify Entry Points:
Buy Entry: When the fast EMA crosses above the slow EMA, a buy signal is triggered. Confirm this signal by checking if the price is near or below the lower Bollinger Band (indicating an oversold condition) and if trading volume meets the set threshold.
Sell Entry: When the fast EMA crosses below the slow EMA, a sell signal is triggered. Confirm the signal by ensuring the price is near or above the upper Bollinger Band (suggesting an overbought condition) and that volume is sufficient.
Exit Strategy:
Take Profit: The take profit level is calculated as 1.5 times the ATR from the entry point. This ensures that each trade aims to achieve a positive risk/reward ratio.
Stop Loss: The stop loss is set at 1 ATR from the entry, providing a tight risk control mechanism that limits potential losses on each trade.
Trend Identification and Background Colors:
Use the background colors to assess the trend direction. A green background indicates a bullish trend, while a red background suggests a bearish trend. These colors can help you filter signals that go against the trend, increasing the chances of a successful trade.
Volume Confirmation:
This indicator has an inbuilt volume filter to prevent trading in low-volume conditions. Look for signals only when volume exceeds the average volume threshold, which is set by the multiplier. This helps avoid trading during quieter times when false signals are more likely.
Alerts:
Set up alerts for buy and sell signals to be notified in real-time whenever a new trading opportunity arises, so you can act on high-quality signals promptly.
Practical Tips for Using Austin’s Apex Accelerator
Timeframe: Best suited for short timeframes such as 5-minute or 15-minute charts for high-frequency trading.
EMD Oscillator (Zeiierman)█ Overview
The Empirical Mode Decomposition (EMD) Oscillator is an advanced indicator designed to analyze market trends and cycles with high precision. It breaks down complex price data into simpler parts called Intrinsic Mode Functions (IMFs), allowing traders to see underlying patterns and trends that aren’t visible with traditional indicators. The result is a dynamic oscillator that provides insights into overbought and oversold conditions, as well as trend direction and strength. This indicator is suitable for all types of traders, from beginners to advanced, looking to gain deeper insights into market behavior.
█ How It Works
The core of this indicator is the Empirical Mode Decomposition (EMD) process, a method typically used in signal processing and advanced scientific fields. It works by breaking down price data into various “layers,” each representing different frequencies in the market’s movement. Imagine peeling layers off an onion: each layer (or IMF) reveals a different aspect of the price action.
⚪ Data Decomposition (Sifting): The indicator “sifts” through historical price data to detect natural oscillations within it. Each oscillation (or IMF) highlights a unique rhythm in price behavior, from rapid fluctuations to broader, slower trends.
⚪ Adaptive Signal Reconstruction: The EMD Oscillator allows traders to select specific IMFs for a custom signal reconstruction. This reconstructed signal provides a composite view of market behavior, showing both short-term cycles and long-term trends based on which IMFs are included.
⚪ Normalization: To make the oscillator easy to interpret, the reconstructed signal is scaled between -1 and 1. This normalization lets traders quickly spot overbought and oversold conditions, as well as trend direction, without worrying about the raw magnitude of price changes.
The indicator adapts to changing market conditions, making it effective for identifying real-time market cycles and potential turning points.
█ Key Calculations: The Math Behind the EMD Oscillator
The EMD Oscillator’s advanced nature lies in its high-level mathematical operations:
⚪ Intrinsic Mode Functions (IMFs)
IMFs are extracted from the data and act as the building blocks of this indicator. Each IMF is a unique oscillation within the price data, similar to how a band might be divided into treble, mid, and bass frequencies. In the EMD Oscillator:
Higher-Frequency IMFs: Represent short-term market “noise” and quick fluctuations.
Lower-Frequency IMFs: Capture broader market trends, showing more stable and long-term patterns.
⚪ Sifting Process: The Heart of EMD
The sifting process isolates each IMF by repeatedly separating and refining the data. Think of this as filtering water through finer and finer mesh sieves until only the clearest parts remain. Mathematically, it involves:
Extrema Detection: Finding all peaks and troughs (local maxima and minima) in the data.
Envelope Calculation: Smoothing these peaks and troughs into upper and lower envelopes using cubic spline interpolation (a method for creating smooth curves between data points).
Mean Removal: Calculating the average between these envelopes and subtracting it from the data to isolate one IMF. This process repeats until the IMF criteria are met, resulting in a clean oscillation without trend influences.
⚪ Spline Interpolation
The cubic spline interpolation is an advanced mathematical technique that allows smooth curves between points, which is essential for creating the upper and lower envelopes around each IMF. This interpolation solves a tridiagonal matrix (a specialized mathematical problem) to ensure that the envelopes align smoothly with the data’s natural oscillations.
To give a relatable example: imagine drawing a smooth line that passes through each peak and trough of a mountain range on a map. Spline interpolation ensures that line is as smooth and close to reality as possible. Achieving this in Pine Script is technically demanding and demonstrates a high level of mathematical coding.
⚪ Amplitude Normalization
To make the oscillator more readable, the final signal is scaled by its maximum amplitude. This amplitude normalization brings the oscillator into a range of -1 to 1, creating consistent signals regardless of price level or volatility.
█ Comparison with Other Signal Processing Methods
Unlike standard technical indicators that often rely on fixed parameters or pre-defined mathematical functions, the EMD adapts to the data itself, capturing natural cycles and irregularities in real-time. For example, if the market becomes more volatile, EMD adjusts automatically to reflect this without requiring parameter changes from the trader. In this way, it behaves more like a “smart” indicator, intuitively adapting to the market, unlike most traditional methods. EMD’s adaptive approach is akin to AI’s ability to learn from data, making it both resilient and robust in non-linear markets. This makes it a great alternative to methods that struggle in volatile environments, such as fixed-parameter oscillators or moving averages.
█ How to Use
Identify Market Cycles and Trends: Use the EMD Oscillator to spot market cycles that represent phases of buying or selling pressure. The smoothed version of the oscillator can help highlight broader trends, while the main oscillator reveals immediate cycles.
Spot Overbought and Oversold Levels: When the oscillator approaches +1 or -1, it may indicate that the market is overbought or oversold, signaling potential entry or exit points.
Confirm Divergences: If the price movement diverges from the oscillator's direction, it may indicate a potential reversal. For example, if prices make higher highs while the oscillator makes lower highs, it could be a sign of weakening trend strength.
█ Settings
Window Length (N): Defines the number of historical bars used for EMD analysis. A larger window captures more data but may slow down performance.
Number of IMFs (M): Sets how many IMFs to extract. Higher values allow for a more detailed decomposition, isolating smaller cycles within the data.
Amplitude Window (L): Controls the length of the window used for amplitude calculation, affecting the smoothness of the normalized oscillator.
Extraction Range (IMF Start and End): Allows you to select which IMFs to include in the reconstructed signal. Starting with lower IMFs captures faster cycles, while ending with higher IMFs includes slower, trend-based components.
Sifting Stopping Criterion (S-number): Sets how precisely each IMF should be refined. Higher values yield more accurate IMFs but take longer to compute.
Max Sifting Iterations (num_siftings): Limits the number of sifting iterations for each IMF extraction, balancing between performance and accuracy.
Source: The price data used for the analysis, such as close or open prices. This determines which price movements are decomposed by the indicator.
-----------------
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!
India market cap and smart dataThis indicator displays important financial and technical data, such as Market Cap, P/E Ratio, ADR %, etc.
It is specially designed for swing traders.
Key Features and Highlights
- Market Cap Alert: If the Market Cap of a stock is below 1000 crore , it is displayed in red to indicate a potential liquidity issue.
- P/E Ratio for Loss-Making Companies : For companies with net losses, the P/E ratio is shown as 0 and displayed in red , alerting you to the unprofitable status of the company.
- ADR Alert: When the ADR is below 4% , it is highlighted in red . Swing traders typically look for stocks with high ADR.
- 52-Week High Proximity: If a stock is more than 20% below its 52-week high , this data is shown in red .
- 52-Week Low Performance: If a stock is up by more than 70% from its 52-week low , the data is displayed in green , indicating strong performance.
Additional Features
- Toggle data points on or off as desired.
- Supports both dark and light modes.
- Position the table wherever preferred on the chart.
- Customize the ADR % calculation based on the desired number of days (default is 20 days).
Note: The calculation for the percentage away from the 52-week high is based on the closing price of the 52-week high candle, not the high price.
Swing Breakout Sequence [LuxAlgo]The Swing Breakout Sequence tool enables traders to identify a directional price action scalping sequence comprising two unsuccessful breakouts in the same direction, with the expectation of a third.
🔶 USAGE
This sequence looks for pressure on one side of a swing zone.
The market tried to break out of the zone twice but failed. This led to a pullback into the zone after each attempt. Once a reversal inside the zone is identified, the sequence is complete. It is expected that the market will move from the final reversal within the zone to the final breakout attempt outside the zone.
The sequence of price action is as follows:
Point 1: Breakout attempt out of the swing zone
Point 2: Pullback into the zone
Point 3: Breakout attempt out of Point 1
Point 4: Pullback into the zone, tapping into Point 2 liquidity
Point 5: Reversal structure with Point 4 in the form of a double top or double bottom
This sequence assumes traders will be caught off-guard when they try to capitalize on the initial breakout at Point 1, which is likely to result in a loss. If the breakout at Point 3 fails, all traders will be caught out and switch positions.
If there is enough pressure in the swing zone to cause a reversal at Point 5, the trapped traders could be the start of the next breakout attempt.
🔹 Sequence Detection
Traders can define sequence behavior and adjust detection with three parameters from the Settings panel.
Disabling Points 4 and 5 will detect the most uncompleted sequences.
🔹 Showing/Hiding Elements
Traders can change the look of sequences by showing or hiding their parts using the Style settings.
🔶 SETTINGS
Swing Length: Number of candles to confirm a swing high or swing low. A higher number detects larger swings.
Internal Length: Number of candles to confirm a internal high or internal low. A lower number detects smaller swings. It must be the same size or smaller than the swing length.
🔹 Detection
Point 4 Beyond Point 2: It only detects sequences where Point 4 is beyond Point 2.
Show Point 5: Enable/disable Point 5 detection.
Require Equal H/L at Point 5: Enable/Disable double top/bottom detection at Point 5 within a given threshold. A bigger value detects more sequences.
🔹 Style
Show Sequence Path: Enable/disable a line between sequence points.
Show Boxes: Enable/disable colored boxes for each sequence.
Show Lines: Enable/disable horizontal lines from each point of the sequence.
Default Color: Define the color or enable/disable auto color.
Custom Candlestick Pattern IndicatorCustom Candlestick Pattern Indicator - Buy Signal Based on Green Candles Breaking Previous Lows
Overview:
This custom candlestick pattern indicator is designed to highlight potential buy opportunities based on a simple yet powerful candlestick pattern. The indicator identifies green candles that break below the low of the previous candle. This combination may signal a potential market reversal or a bullish continuation after a pullback, depending on the market context. Traders can use this indicator to detect areas where prices may be bouncing from recent lows, indicating a potential buying opportunity.
Pattern Explanation:
The strategy underlying this indicator is a two-part condition that must be met before a buy signal is generated:
Green Candle: A green candle forms when the closing price of the current candle is higher than its opening price. This visually represents bullish momentum as buyers have taken control, closing the price higher than where it opened.
Breaking the Previous Low: The low of the current candle must be lower than the low of the previous candle. This suggests that, despite initial bearish pressure during the candle formation (which drove the price below the previous candle's low), buyers stepped in to push the price higher by the candle’s close. This pattern can signify a potential reversal or bullish continuation, as it demonstrates that buyers are overcoming initial selling pressure.
When the Pattern Occurs:
This pattern is particularly interesting to traders who look for potential reversal signals after a brief decline in price.
It may also work well in markets where pullbacks are common, as this pattern could mark the end of a retracement and the resumption of the bullish trend.
How the Indicator Works:
Green Candle: The indicator first identifies a green candle, where the close of the candle is greater than its open (close > open). This signals that the current period closed higher than it opened, which is generally a bullish sign.
Breaking Previous Low: The indicator checks if the current candle's low is below the low of the previous candle (low < low ). If this condition is met, it means the price dropped below the previous candle's low but was still able to close higher (green candle), signaling a potential reversal or buying opportunity.
Buy Signal: If both conditions are true (green candle + breaking previous low), the indicator plots a buy signal below the candle in the form of an upward-facing triangle labeled "Buy" in green. This serves as a visual cue for traders to consider entering a buy position.
Optional Previous Low Plot: For added reference, the indicator plots the previous candle's low as a red step-line on the chart. This helps traders visualize when the price has dipped below the prior candle's low, making it easier to spot instances where the pattern is forming.
How to Use:
This indicator can be used across multiple timeframes, whether you’re trading short-term intraday patterns or longer-term swing trades.
It works well in markets that experience pullbacks or minor retracements, as the pattern it identifies suggests a rejection of lower prices followed by a push higher.
Traders can combine this indicator with other technical analysis tools (such as moving averages, support/resistance levels, or momentum oscillators) to strengthen the buy signals and add more context to the trading decision.
Example Scenarios:
Reversal Signal: Suppose a market has been in a minor downtrend, and suddenly a green candle forms after a low that breaks the previous day’s low. This indicator would generate a buy signal, suggesting the downtrend may be losing strength and that buyers are taking control. This could be an early indication of a reversal.
Bullish Continuation After Pullback: Imagine a market in a steady uptrend experiences a temporary pullback. The price breaks the previous candle’s low, but the current candle closes higher (green candle). This buy signal could indicate that the pullback is over, and the uptrend is likely to continue.
Advantages:
Simplicity: This indicator relies on basic price action (green candles and lows) without requiring complicated indicators or oscillators, making it easy to understand and use.
Visual Alerts: The plotted buy signals and previous lows provide a clear, visual representation on the chart, simplifying decision-making for traders.
Versatility: It can be applied across different timeframes and asset classes (stocks, forex, crypto, etc.), making it a versatile tool for all kinds of traders.
Limitations:
As with any single indicator or pattern, this should not be used in isolation. It is important to incorporate broader market context, support/resistance levels, and other forms of analysis to avoid false signals.
The pattern tends to be more effective when there’s sufficient market liquidity and may perform better in trending or volatile markets compared to sideways or flat markets.
SMT Divergences [OutOfOptions]Smart Money Technique (SMT) Divergence is designed to identify discrepancies between correlated assets within the same timeframe. It occurs when two related assets exhibit opposing signals, such as one forming a higher low while the other forms a lower low. This technique is particularly useful for anticipating market shifts or reversals before they become evident through other Premium Discount (PD) Arrays.
This indicator works by identifying the highs and lows that have formed for an asset on the current chart and the correlated symbol defined in the settings. Once a pivot on either asset is formed, it checks if the pivot has taken liquidity as identified by the previous pivot in the same direction (i.e., a new high taking out a previous high). If this is the case and the corresponding asset has not taken a similar pivot, the condition is determined to be a potential valid divergence. The indicator will then filter out SMTs formed by adjacent candles, requiring at least one candle difference between the candles forming the SMT.
If the “Candle Direction Validation” setting is enabled, the indicator will further check both assets to ensure that for bullish SMTs, the last high on both assets was formed by down candle, and for bearish SMTs, the low was formed by an up candle. This check can often eliminate low-probability SMTs that are frequently broken.
The referenced chart shows divergence between Nasdaq (NQ) and S&P 500 (ES) futures, which are normally closely correlated assets that move in the same direction. The lines shown represent bullish and bearish divergences between the two when they are formed. As you can see from the chart, SMT Divergences may not always indicate a reversal, or a reversal might be just a short-term retrace. Therefore, SMT Divergences should not be used independently. However, in conjunction with other PD arrays, they can provide strong confirmation of a change in market direction.
Configurability:
Pivot strength - Indicates how many bars to the left/right of a high for pivot to be considered, recommended to keep at 1 for maximum detection speed
Candle Direction Validation - Additional SMT validation to filter out weak/low-probability SMTs be examining candle direction
Line Styling for Bullish/Bearish SMTs - Ability to customize line style, color & width for bullish/bearish SMTs
Label Control - Whether or not to show SMT label and if shown what font size & color should be used
What makes this indicator different:
Unlike other SMT indicators, this indicators has additional built-in controls to remove low-probability SMTs
Advanced Economic Indicator by USCG_VetAdvanced Economic Indicator by USCG_Vet
tldr:
This comprehensive TradingView indicator combines multiple economic and financial metrics into a single, customizable composite index. By integrating key indicators such as the yield spread, commodity ratios, stock indices, and the Federal Reserve's QE/QT activities, it provides a holistic view of the economic landscape. Users can adjust the components and their weights to tailor the indicator to their analysis, aiding in forecasting economic conditions and market trends.
Detailed Description
Overview
The Advanced Economic Indicator is designed to provide traders and investors with a powerful tool to assess the overall economic environment. By aggregating a diverse set of economic indicators and financial market data into a single composite index, it helps identify potential turning points in the economy and financial markets.
Key Features:
Comprehensive Coverage: Includes 14 critical economic and financial indicators.
Customizable Components: Users can select which indicators to include.
Adjustable Weights: Assign weights to each component based on perceived significance.
Visual Signals: Clear plotting with threshold lines and background highlights.
Alerts: Set up alerts for when the composite index crosses user-defined thresholds.
Included Indicators
Yield Spread (10-Year Treasury Yield minus 3-Month Treasury Yield)
Copper/Gold Ratio
High Yield Spread (HYG/IEF Ratio)
Stock Market Performance (S&P 500 Index - SPX)
Bitcoin Performance (BLX)
Crude Oil Prices (CL1!)
Volatility Index (VIX)
U.S. Dollar Index (DXY)
Inflation Expectations (TIP ETF)
Consumer Confidence (XLY ETF)
Housing Market Index (XHB)
Manufacturing PMI (XLI ETF)
Unemployment Rate (Inverse SPY as Proxy)
Federal Reserve QE/QT Activities (Fed Balance Sheet - WALCL)
How to Use the Indicator
Configuring the Indicator:
Open Settings: Click on the gear icon (⚙️) next to the indicator's name.
Inputs Tab: You'll find a list of all components with checkboxes and weight inputs.
Including/Excluding Components
Checkboxes: Check or uncheck the box next to each component to include or exclude it from the composite index.
Default State: By default, all components are included.
Adjusting Component Weights:
Weight Inputs: Next to each component's checkbox is a weight input field.
Default Weights: Pre-assigned based on economic significance but fully adjustable.
Custom Weights: Enter your desired weight for each component to reflect your analysis.
Threshold Settings:
Bearish Threshold: Default is -1.0. Adjust to set the level below which the indicator signals potential economic downturns.
Bullish Threshold: Default is 1.0. Adjust to set the level above which the indicator signals potential economic upswings.
Setting the Timeframe:
Weekly Timeframe Recommended: Due to the inclusion of the Fed's balance sheet data (updated weekly), it's best to use this indicator on a weekly chart.
Changing Timeframe: Select 1W (weekly) from the timeframe options at the top of the chart.
Interpreting the Indicator:
Composite Index Line
Plot: The blue line represents the composite economic indicator.
Movement: Observe how the line moves relative to the threshold lines.
Threshold Lines
Zero Line (Gray Dotted): Indicates the neutral point.
Bearish Threshold (Red Dashed): Crossing below suggests potential economic weakness.
Bullish Threshold (Green Dashed): Crossing above suggests potential economic strength.
Background Highlights
Red Background: When the composite index is below the bearish threshold.
Green Background: When the composite index is above the bullish threshold.
No Color: When the composite index is between the thresholds.
Understanding the Components
1. Yield Spread
Description: The difference between the 10-year and 3-month U.S. Treasury yields.
Economic Significance: An inverted yield curve (negative spread) has historically preceded recessions.
2. Copper/Gold Ratio
Description: The price ratio of copper to gold.
Economic Significance: Copper is tied to industrial demand; gold is a safe-haven asset. The ratio indicates risk sentiment.
3. High Yield Spread (HYG/IEF Ratio)
Description: Ratio of high-yield corporate bonds (HYG) to intermediate-term Treasury bonds (IEF).
Economic Significance: Reflects investor appetite for risk; widening spreads can signal credit stress.
4. Stock Market Performance (SPX)
Description: S&P 500 Index levels.
Economic Significance: Broad measure of U.S. equity market performance.
5. Bitcoin Performance (BLX)
Description: Bitcoin Liquid Index price.
Economic Significance: Represents risk appetite in speculative assets.
6. Crude Oil Prices (CL1!)
Description: Front-month crude oil futures price.
Economic Significance: Influences inflation and consumer spending.
7. Volatility Index (VIX)
Description: Market's expectation of volatility (fear gauge).
Economic Significance: High VIX indicates market uncertainty; inverted in the indicator to align directionally.
8. U.S. Dollar Index (DXY)
Description: Value of the U.S. dollar relative to a basket of foreign currencies.
Economic Significance: Affects international trade and commodity prices; inverted in the indicator.
9. Inflation Expectations (TIP ETF)
Description: iShares TIPS Bond ETF prices.
Economic Significance: Reflects market expectations of inflation.
10. Consumer Confidence (XLY ETF)
Description: Consumer Discretionary Select Sector SPDR Fund prices.
Economic Significance: Proxy for consumer confidence and spending.
11. Housing Market Index (XHB)
Description: SPDR S&P Homebuilders ETF prices.
Economic Significance: Indicator of the housing market's health.
12. Manufacturing PMI (XLI ETF)
Description: Industrial Select Sector SPDR Fund prices.
Economic Significance: Proxy for manufacturing activity.
13. Unemployment Rate (Inverse SPY as Proxy)
Description: Inverse of the SPY ETF price.
Economic Significance: Represents unemployment trends; higher inverse SPY suggests higher unemployment.
14. Federal Reserve QE/QT Activities (Fed Balance Sheet - WALCL)
Description: Total assets held by the Federal Reserve.
Economic Significance: Indicates liquidity injections (QE) or withdrawals (QT); impacts interest rates and asset prices.
Customization and Advanced Usage
Adjusting Weights:
Purpose: Emphasize components you believe are more predictive or relevant.
Method: Increase or decrease the weight value next to each component.
Example: If you think the yield spread is particularly important, you might assign it a higher weight.
Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Trading and investing involve risks, including possible loss of principal. Always conduct your own analysis and consult with a professional financial advisor before making investment decisions.
Candle Range Theory | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Candle Range Theory Indicator! This powerful tool offers a strategy built around the Candle Range Theory, which analyzes market movements through the relative size and structure of price candles. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new Candle Range Theory Indicator :
Implementation of the Candle Range Theory
FVG & Order Block Entry Methods
2 Different TP / SL Methods
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The Candle Range Theory (CRT) indicator operates by identifying significant price movements through the relative size and structure of candlesticks. A key part of the strategy is determining large candles based on their range compared to the Average True Range (ATR) in a higher timeframe. Once identified, a breakout of either the high wick or the low wick of the large candle is required. This breakout is considered a liquidity grab. After that, the indicator waits for confirmation through Fair Value Gaps (FVGs) or Order Blocks (OBs). The confirmation structure must be the opposite direction of the breakout, for example if the high wick is broken, a bearish FVG is required for the short entry. After a confirmation signal is received, the indicator will trigger entry points based on your chosen entry method (FVG or OB), and exit points will be calculated using either a dynamic ATR-based TP/SL method or fixed percentages. Alerts for Buy, Sell, Take-Proft, and Stop-Loss are available.
🚩 UNIQUENESS
This indicator stands out because it combines two highly effective entry methods: Fair Value Gaps (FVGs) and Order Blocks (OBs). You can choose between these strategies depending on market conditions. Additionally, the dynamic TP/SL system uses the ticker's volatility to automatically calculate stop-loss and take-profit targets. The backtesting dashboard provides metrics about the performance of the indicator. You can use it to tune the settings for best use in the current tiker. The Candle Range Theory approach offers more flexibility compared to traditional indicators, allowing for better customization and control based on your risk tolerance.
⚙️ SETTINGS
1. General Configuration
Higher Timeframe: Customize the higher timeframe for analysis. Recommended combinations include M15 -> H4, H4 -> Daily, Daily -> Weekly, and Weekly -> Monthly.
HTF Candle Size: Define the size of the higher timeframe candles as Big, Normal, or Small to filter valid setups based on their range relative to ATR.
Entry Mode: Choose between FVGs and Order Blocks for your entry triggers.
Require Retracement: Enable this option if you want a retracement to the FVG or OB for entry confirmation.
Show HTF Candle Lines: Toggle to display the higher timeframe candle lines for better visual clarity.
2. Fair Value Gaps
FVG Sensitivity: You may select between Low, Normal, High or Extreme FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivities resulting in spotting bigger FVGs, and higher sensitivities resulting in spotting all sizes of FVGs.
3. Order Blocks
Swing Length: Swing length is used when finding order block formations. Smaller values will result in finding smaller order blocks.
4. TP / SL
TP / SL Method:
a) Dynamic: The TP / SL zones will be auto-determined by the algorithm based on the Average True Range (ATR) of the current ticker.
b) Fixed : You can adjust the exact TP / SL ratios from the settings below.
Dynamic Risk: The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
