LIT - ConfirmationsOverview
The LIT - Confirmations Indicator is a dynamic checklist tool designed for traders who uses LIT Strategy (Liquidity Inducement Theory) following liquidity and smart money concepts as benefit. This tool allows users to document and track essential trading confirmations directly on their TradingView charts, offering a structured and visual approach to market analysis.
What Makes This Unique?
Unlike other open-source tools, the LIT - Confirmations Indicator introduces a fully interactive and customizable table directly on the chart. This table provides real-time feedback with clear ✅ (checked) and ❌ (unchecked) visual indicators for each confirmation. The user can position the table on the chart according to their preference, ensuring it integrates seamlessly into their trading workflow without obscuring critical chart data.
How It Works
1. Predefined Confirmations
The indicator includes a set of commonly used trading confirmations:
Identify Liquidity: Mark areas where liquidity might pool.
Inducement: Confirm the presence of inducements before market reversals.
Relevant Break of Structure (BOS): Validate critical structural changes.
Mitigation after RBoS: Check for mitigation following a BOS.
Smart Money Trap (SMT): Identify traps often utilized by smart money.
Timing: Ensure trades are entered during high-probability time windows.
Mitigation to the Leftside: Confirm whether price action aligns with prior mitigations.
Set Targets: Define and document logical take-profit or stop-loss levels.
2.Interactive Table Display
A table is dynamically created on the chart, showing all confirmations with their current state (checked or unchecked).
Users can choose the position of the table (top, middle, or bottom and left, center, or right) and customize its background color for better visibility.
3. Customization
All confirmations are toggled through the input settings, allowing traders to adapt the indicator to their unique strategies.
The display can be easily adjusted to match the trader’s preferences without cluttering the chart.
How to Use
1. Add the indicator to your chart.
2. Open the settings panel to activate the relevant confirmations for your analysis.
3. Use the Display Settings section to adjust the table's position and background color.
4. View the table on your chart to track selected confirmations in real-time.
Who Is This For?
This indicator is ideal for traders who:
Use Liquidity Inducent Theory strategy in their analysis.
Prefer a structured and systematic trading approach.
Need an on-chart tool to document confirmations without relying on external notes or tools.
Why Closed Source?
The logic behind the interactive table and confirmation system is specifically tailored to LIT practitioners and is not publicly available in existing open-source scripts. The closed-source nature of this script protects its unique implementation, ensuring the integrity and exclusivity of the tool.
Disclaimer
This indicator does not provide trading signals or strategies. It is a tool to document user-defined confirmations and should be used in conjunction with a thorough understanding of market behavior and risk management practices.
사이클
Logarithmic Regression AlternativeLogarithmic regression is typically used to model situations where growth or decay accelerates rapidly at first and then slows over time. Bitcoin is a good example.
𝑦 = 𝑎 + 𝑏 * ln(𝑥)
With this logarithmic regression (log reg) formula 𝑦 (price) is calculated with constants 𝑎 and 𝑏, where 𝑥 is the bar_index .
Instead of using the sum of log x/y values, together with the dot product of log x/y and the sum of the square of log x-values, to calculate a and b, I wanted to see if it was possible to calculate a and b differently.
In this script, the log reg is calculated with several different assumed a & b values, after which the log reg level is compared to each Swing. The log reg, where all swings on average are closest to the level, produces the final 𝑎 & 𝑏 values used to display the levels.
🔶 USAGE
The script shows the calculated logarithmic regression value from historical swings, provided there are enough swings, the price pattern fits the log reg model, and previous swings are close to the calculated Top/Bottom levels.
When the price approaches one of the calculated Top or Bottom levels, these levels could act as potential cycle Top or Bottom.
Since the logarithmic regression depends on swing values, each new value will change the calculation. A well-fitted model could not fit anymore in the future.
Swings are based on Weekly bars. A Top Swing, for example, with Swing setting 30, is the highest value in 60 weeks. Thirty bars at the left and right of the Swing will be lower than the Top Swing. This means that a confirmation is triggered 30 weeks after the Swing. The period will be automatically multiplied by 7 on the daily chart, where 30 becomes 210 bars.
Please note that the goal of this script is not to show swings rapidly; it is meant to show the potential next cycle's Top/Bottom levels.
🔹 Multiple Levels
The script includes the option to display 3 Top/Bottom levels, which uses different values for the swing calculations.
Top: 'high', 'maximum open/close' or 'close'
Bottom: 'low', 'minimum open/close' or 'close'
These levels can be adjusted up/down with a percentage.
Lastly, an "Average" is included for each set, which will only be visible when "AVG" is enabled, together with both Top and Bottom levels.
🔹 Notes
Users have to check the validity of swings; the above example only uses 1 Top Swing for its calculations, making the Top level unreliable.
Here, 1 of the Bottom Swings is pretty far from the bottom level, changing the swing settings can give a more reliable bottom level where all swings are close to that level.
Note the display was set at "Logarithmic", it can just as well be shown as "Regular"
In the example below, the price evolution does not fit the logarithmic regression model, where growth should accelerate rapidly at first and then slows over time.
Please note that this script can only be used on a daily timeframe or higher; using it at a lower timeframe will show a warning. Also, it doesn't work with bar-replay.
🔶 DETAILS
The code gathers data from historical swings. At the last bar, all swings are calculated with different a and b values. The a and b values which results in the smallest difference between all swings and Top/Bottom levels become the final a and b values.
The ranges of a and b are between -20.000 to +20.000, which means a and b will have the values -20.000, -19.999, -19.998, -19.997, -19.996, ... -> +20.000.
As you can imagine, the number of calculations is enormous. Therefore, the calculation is split into parts, first very roughly and then very fine.
The first calculations are done between -20 and +20 (-20, -19, -18, ...), resulting in, for example, 4.
The next set of calculations is performed only around the previous result, in this case between 3 (4-1) and 5 (4+1), resulting in, for example, 3.9. The next set goes even more in detail, for example, between 3.8 (3.9-0.1) and 4.0 (3.9 + 0.1), and so on.
1) -20 -> +20 , then loop with step 1 (result (example): 4 )
2) 4 - 1 -> 4 +1 , then loop with step 0.1 (result (example): 3.9 )
3) 3.9 - 0.1 -> 3.9 +0.1 , then loop with step 0.01 (result (example): 3.93 )
4) 3.93 - 0.01 -> 3.93 +0.01, then loop with step 0.001 (result (example): 3.928)
This ensures complicated calculations with less effort.
These calculations are done at the last bar, where the levels are displayed, which means you can see different results when a new swing is found.
Also, note that this indicator has been developed for a daily (or higher) timeframe chart.
🔶 SETTINGS
Three sets
High/Low
• color setting
• Swing Length settings for 'High' & 'Low'
• % adjustment for 'High' & 'Low'
• AVG: shows average (when both 'High' and 'Low' are enabled)
Max/Min (maximum open/close, minimum open/close)
• color setting
• Swing Length settings for 'Max' & 'Min'
• % adjustment for 'Max' & 'Min'
• AVG: shows average (when both 'Max' and 'Min' are enabled)
Close H/Close L (close Top/Bottom level)
• color setting
• Swing Length settings for 'Close H' & 'Close L'
• % adjustment for 'Close H' & 'Close L'
• AVG: shows average (when both 'Close H' and 'Close L' are enabled)
Show Dashboard, including Top/Bottom levels of the desired source and calculated a and b values.
Show Swings + Dot size
Kalman Filter Oscillator v4The Kalman Filter Oscillator v4 is an advanced tool designed to help traders and investors identify trends more effectively while reducing the impact of market noise. As the latest iteration in its development, this version integrates improvements that make it more adaptive and precise, catering to the challenges of today’s financial markets.
This indicator operates on the principle of the Kalman filter, a well-regarded mathematical approach used for estimating the state of a dynamic system. By filtering out random fluctuations, it smooths price data to provide clearer insights into underlying trends. Unlike traditional methods such as moving averages, which often lag and can miss rapid shifts, the Kalman Filter Oscillator is reactive in real time, making it particularly suited for dynamic markets.
Version v4 builds on earlier versions by offering a refined combination of short-term and long-term trend analysis. Through adjustable parameters, traders can balance sensitivity to immediate price changes with a broader perspective of the market direction. Additionally, the oscillator incorporates a unique feature that tracks a price’s position relative to its recent highs and lows, which enhances its ability to pinpoint potential turning points or key market conditions.
The indicator’s value lies in its adaptability and practicality. Traders can use it to confirm trends, identify overbought or oversold conditions, or smooth out erratic price movements, reducing the likelihood of false signals. By presenting information in a clear and actionable format, it allows users to make better-informed decisions with greater confidence.
As of late 2024, the Kalman Filter Oscillator v4 represents a sophisticated yet user-friendly advancement in trend analysis. While not a one-size-fits-all solution, it serves as a valuable component in a trader’s toolkit, complementing other strategies and enhancing overall market understanding.
Master Litecoin Market Cap Network Value ModelMaster Litecoin Market Cap Network Value Model
This indicator visualizes Litecoin's network fundamentals compared to Bitcoin, developed by @masterbtcltc. By analyzing various on-chain metrics and market data, this script helps users evaluate Litecoin’s intrinsic value relative to Bitcoin.
Key Features:
Network Metrics:
NewAddressValueModel: Tracks the ratio of new addresses in Litecoin compared to Bitcoin.
TotalAddressValueModel: Compares total addresses across the two networks.
Transaction & Volume Metrics:
TXValueModel: Compares transaction activity.
VolumeValueModel and VolumeUSDValueModel: Analyzes transaction volumes in native units and USD.
Usage & Adoption:
ActiveValueModel: Tracks the ratio of active addresses between Litecoin and Bitcoin.
RetailValueModel: Measures retail adoption strength in the Litecoin network.
Blockchain & Holder Data:
BlockValueModel: Compares block sizes.
NonZeroModel: Evaluates addresses with non-zero balances.
HodlerModel: Compares long-term holders between Litecoin and Bitcoin.
Averaged Insights:
AverageValueModel: Aggregates all metrics for a complete view of network valuation.
Visual Design:
Blue Themed Metrics: Network value models are displayed in a uniform blue color with a line thickness of 4 and 25% transparency for clarity.
Distinct Price Plot: Litecoin’s price is plotted in yellow, with a thin line (width 2) and no transparency, keeping it visually separate.
Use Cases:
Ideal for traders, investors, and enthusiasts aiming to:
Identify Litecoin’s market trends.
Detect periods of undervaluation or overvaluation.
Gain deeper insights into Litecoin’s network fundamentals.
Important Instruction: To ensure accurate results, plot this indicator on VANTAGE:LTCUSD * GLASSNODE:LTC_SUPPLY. This ensures alignment with the data sources and guarantees the script performs as intended.
Feel free to explore, use, and share this open-source script to better understand Litecoin’s value potential!
Monest Value Indicator (MVI)
Description
The Monest Value Indicator (MVI) is a modern oscillator designed to address common issues in traditional oscillators like RSI or MACD. Unlike classical oscillators, the MVI dynamically adjusts to relative price movements and market volatility, providing a transparent and reliable valuation for short-term trading decisions.
This indicator normalizes price data around a consensus line and accounts for market volatility using the Average True Range (ATR). It highlights overbought and oversold conditions, offering a unique perspective for traders.
Key Features
Dynamic Overbought/Oversold Levels : Highlights significant price extremes for better entry and exit signals. Volatility Normalization : Adapts to market conditions, ensuring consistent readings across various assets. Consensus-Based Valuation : Uses a moving average of the midrange price for baseline calculations. No Lag or Stickiness : Reacts promptly to price movements without getting stuck in extreme zones.
How It Works
Consensus Line :
Calculated as a 5-day moving average of the midrange:
Consensus = SMA((High + Low) / 2, 5) .
Offset OHLC Data :
All prices are adjusted relative to the consensus line:
Offset Price = Price - Consensus .
Volatility Normalization :
Adjusted prices are normalized using a 5-day ATR divided by 5:
Normalized Price = Offset Price / (ATR / 5) .
MVI Calculation :
The normalized closing price is plotted as the MVI.
Overbought/Oversold Levels :
Default levels are set at +8 (overbought) and -8 (oversold).
How to Use
Identifying Overbought/Oversold Conditions :
When the MVI crosses above +8 , the asset is overbought, signaling a potential reversal or pullback.
When the MVI drops below -8 , the asset is oversold, indicating a potential bounce or upward move.
Trend Confirmation :
Use the MVI to confirm trends by observing sustained movements above or below zero.
Combine with other trend indicators (e.g., Moving Averages) for robust analysis.
Alerts :
Set alerts for when the MVI crosses overbought or oversold levels to stay informed about potential trading opportunities.
Inputs
ATR Length : Default is 5. Adjust to modify the sensitivity of volatility normalization. Consensus Length : Default is 5. Change to tweak the baseline calculation.
Example
Overbought Signal : MVI exceeds +8 , indicating the asset may reverse from an overvalued position. Oversold Signal : MVI drops below -8 , suggesting the asset may recover from an undervalued state. Flat Market : MVI hovers near zero, indicating price consolidation.
Session Highs and Lows IndicatorThis indicator marks the high and low levels for key trading sessions, allowing traders to identify significant price zones across different markets. The default session times are defined in UTC and will automatically adjust to your local timezone:
- **London Session (07:00-09:00 UTC)**: Tracks intraday liquidity zones for potential highs/lows.
- **New York Session (12:00-14:00 UTC)**: Highlights volatility during market overlaps with Europe.
- **Asia Session (23:00-01:00 UTC)**: Confirms trend continuation and retracement opportunities.
- **New York Close Session (19:00-21:00 UTC)**: Focuses on reversals and breakout tests during global transitions.
The script dynamically updates session highs and lows with clear labels and dashed horizontal lines for better visualization. **Time ranges can be adjusted to suit your trading preferences.** This makes the indicator flexible and effective for liquidity hunting, trend trading, and breakout strategies.
Gold Friday Anomaly StrategyThis script implements the " Gold Friday Anomaly Strategy ," a well-known historical trading strategy that leverages the gold market's behavior from Thursday evening to Friday close. It is a backtesting-focused strategy designed to assess the historical performance of this pattern. Traders use this anomaly as it captures a recurring market tendency observed over the years.
What It Does:
Entry Condition: The strategy enters a long position at the beginning of the Friday trading session (Thursday evening close) within the defined backtesting period.
Exit Condition: Friday evening close.
Backtesting Controls: Allows users to set custom backtesting periods to evaluate strategy performance over specific date ranges.
Key Features:
Custom Backtest Periods: Easily configurable inputs to set the start and end date of the backtesting range.
Fixed Slippage and Commission Settings: Ensures realistic simulation of trading conditions.
Process Orders on Close: Backtesting is optimized by processing orders at the bar's close.
Important Notes:
Backtesting Only: This script is intended purely for backtesting purposes. Past performance is not indicative of future results.
Live Trading Recommendations: For live trading, it is highly recommended to use limit orders instead of market orders, especially during evening sessions, as market order slippage can be significant.
Default Settings:
Entry size: 10% of equity per trade.
Slippage: 1 tick.
Commission: 0.05% per trade.
Cabal Dev IndicatorThis is a TradingView Pine Script (version 6) that creates a technical analysis indicator called the "Cabal Dev Indicator." Here's what it does:
1. Core Functionality:
- It calculates a modified version of the Stochastic Momentum Index (SMI), which is a momentum indicator that shows where the current close is relative to the high/low range over a period
- The indicator combines elements of stochastic oscillator calculations with exponential moving averages (EMA)
2. Key Components:
- Uses configurable input parameters for:
- Percent K Length (default 15)
- Percent D Length (default 3)
- EMA Signal Length (default 15)
- Smoothing Period (default 5)
- Overbought level (default 40)
- Oversold level (default -40)
3. Calculation Method:
- Calculates the highest high and lowest low over the specified period
- Finds the difference between current close and the midpoint of the high-low range
- Applies EMA smoothing to both the range and relative differences
- Generates an SMI value and further smooths it using a simple moving average (SMA)
- Creates an EMA signal line based on the smoothed SMI
4. Visual Output:
- Plots the smoothed SMI line in green
- Plots an EMA signal line in red
- Shows overbought and oversold levels as gray horizontal lines
- Fills the areas above the overbought level with light red
- Fills the areas below the oversold level with light green
This indicator appears designed to help traders identify potential overbought and oversold conditions in the market, as well as momentum shifts, which could be used for trading decisions.
Would you like me to explain any specific part of the indicator in more detail?
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.
[w3ss1] TimewindowsYou can use this if you want some subtle indication of a specific timewindow on the chart.
You can use it to see the macrowindows, or set the time of a session or any timewindow you want.
You can choose the color and plot it on the bottom or the top of the chart.
[w3ss1] Colored candlesA simple script that colors the candles in a color of choise on specific times of choice.
You can use it if you want to color like Asia session, or if you want to focus on specific times of day.
This keeps the chart clean, it just colors the candles in the choosen timings.
Kalman Trend Strength Index (K-TSI)The Kalman Trend Strength Index (K-TSI) is an innovative technical indicator that combines the Kalman filter with correlation analysis to measure trend strength in financial markets. This sophisticated tool aims to provide traders with a more refined method for trend analysis and market dynamics interpretation.
The use of the Kalman filter is a key feature of the K-TSI. This advanced algorithm is renowned for its ability to extract meaningful signals from noisy data. In financial markets, this translates to smoothing out price action while maintaining responsiveness to genuine market movements. By applying the Kalman filter to price data before performing correlation analysis, the K-TSI potentially offers more stable and reliable trend signals.
The synergy between the Kalman-filtered price data and correlation analysis creates an oscillator that attempts to capture market dynamics more effectively. The correlation component contributes by measuring the strength and consistency of price movements relative to time, while the Kalman filter adds robustness by reducing the impact of market noise. Basing these calculations on Kalman-filtered data may help reduce false signals and provide a clearer picture of underlying market trends.
A notable aspect of the K-TSI is its normalization process. This approach adjusts the indicator's values to a standardized range (-1 to 1), allowing for consistent interpretation across different market conditions and timeframes. This flexibility, combined with the noise-reduction properties of the Kalman filter, positions the K-TSI as a potentially useful tool for various market environments.
In practice, traders might find that the K-TSI offers several potential benefits:
Smoother trend identification, which could aid in detecting the start and end of trends more accurately.
Possibly reduced false signals, particularly in choppy or volatile markets.
Potential for improved trend strength assessment, which might lead to more confident trading decisions.
Consistent performance across different timeframes, due to the adaptive nature of the Kalman filter and the normalization process.
The K-TSI's visual representation as a color-coded histogram further enhances its utility. The changing colors and intensities provide an intuitive way to gauge both the direction and strength of trends, making it easier for traders to quickly assess market conditions.
While the K-TSI builds upon existing concepts in technical analysis, its integration of the Kalman filter with correlation analysis offers traders an interesting tool for market analysis. It represents an attempt to address common challenges in technical analysis, such as noise reduction and trend strength quantification.
As with any technical indicator, the K-TSI should be used as part of a broader trading strategy rather than in isolation. Its effectiveness will depend on how well it aligns with a trader's individual approach and market conditions. For traders looking to explore a more refined trend strength oscillator, the Kalman Trend Strength Index could be a worthwhile addition to their analytical toolkit.
Precision Swing Point V2.0 - [Gozlan]"Precision Swing Point V2.0," is well-structured and aims to highlight specific conditions in the chart while factoring in time zones and user configurations. Here's a quick breakdown and a couple of improvements or fixes to consider:
Key Features:
Multi-Symbol Analysis:
Incorporates three symbols (Symbol 1, Symbol 2, and Symbol 3) and compares their open/close values to derive candle states (green/red).
Highlighting Conditions:
Green: When Symbol 2 is red and Symbol 1 is green.
Red: When Symbol 2 is green and Symbol 1 is red.
Blue: When Symbol 3 is green and Symbol 1 is red.
Custom Time Highlights:
Allows users to specify times for highlighting specific bars.
Timezone Flexibility:
Time calculations adjust based on user-defined UTC offsets.
Edwin K Stochastic Candle ColorsThe Stochastic Candle Colors indicator highlights price action using candle colors based on signals from the stochastic oscillator. Here's how to use it:
1. Indicator Purpose
This indicator overlays on your price chart and changes candle colors based on stochastic oscillator signals:
Green candles: Indicate a bullish signal when the %K line crosses above the %D line in an oversold area (below 20).
Red candles: Indicate a bearish signal when the %K line crosses below the %D line in an overbought area (above 80).
2. How to Use the Inputs
K (periodK): The lookback period for calculating the %K line of the stochastic oscillator. A smaller value makes the indicator more sensitive to price changes.
D (periodD): The period for smoothing the %K line to get the %D line. A larger value creates smoother signals but may result in delays.
Smooth (smoothK): The additional smoothing applied to the %K line before calculating the %D line. This helps reduce noise.
3. How to Interpret the Candle Colors
Green Candle:
Occurs when the %K line crosses above the %D line in the oversold zone (below 20).
Signals a potential bullish reversal.
Red Candle:
Occurs when the %K line crosses below the %D line in the overbought zone (above 80).
Signals a potential bearish reversal.
No Color:
No crossover occurs, or the crossover doesn't happen in overbought/oversold zones.
4. Application in Trading
Entry Points:
Buy when you see a green candle and confirm with other indicators or chart patterns.
Sell when you see a red candle and confirm with additional signals.
Trend Context:
Combine this indicator with trend-following tools like moving averages or support/resistance levels to improve accuracy.
Stop Loss/Take Profit:
Use nearby swing highs/lows for stop-loss placement.
Set profit targets based on risk-reward ratios or key levels.
5. Customization
Adjust the input parameters (K, D, and Smooth) to align the indicator's sensitivity with your trading style:
Short-term traders might prefer lower values for quicker signals.
Long-term traders might opt for higher values for smoother, more reliable signals.
6. Limitations
Signals in isolation might not be reliable. Always use this indicator in conjunction with other tools.
Avoid using during low volatility or sideways markets as stochastic oscillators can produce false signals.
Wick Length Display + Alert conditionsDescription of the Wick Length Display (Advanced) script
Originality and purpose of the script
The Wick Length Display (Advanced) script is an innovative tool for traders who want to gain detailed insights into the length of candle wicks. It stands out for its versatility and user-friendly customization options. It combines precise technical calculations with visual representation to provide important information about market movements and dynamics right on the chart.
Functionality
The script calculates and displays the length of the upper and lower wicks of each candle on the chart. It also provides additional visual cues such as:
• “Bull pressure”: When green candles do not have upper wicks, this indicates strong buying pressure.
• “Bear pressure”: When red candles do not have lower wicks, this indicates strong selling pressure.
• Threshold conditions: Only displays wicks that exceed a certain threshold (optional).
• Display in pips: Allows you to display wick lengths in pips, which is useful for forex traders.
How it works
The script analyzes each candle using the following calculations:
1. Wick length calculation:
◦ Upper wick length = High - (top of the body)
◦ Lower wick length = (bottom of the body) - Low
2. Display conditions:
◦ It distinguishes between bullish and bearish candles.
◦ It checks if the calculated wicks exceed the defined thresholds before displaying them.
3. Dynamic labels:
◦ Labels are placed above or below the respective candles.
◦ Size, color and type of labels are fully customizable.
4. Limitation of labels:
◦ To ensure clarity, a maximum number of labels is defined.
Usage
1. Customization:
◦ Open the script in the Pine Script Editor in TradingView.
◦ Use the input options to customize parameters such as color selection, label size, thresholds and other details according to your requirements.
2. Enable thresholds:
◦ Enable thresholds to show labels only for relevant wicks (default is 6).
◦ Define the minimum wick lengths for bullish (green) and bearish (red) candles.
3. Show in pips:
◦ Enable the “Show wick length in pips” option to show the results in pips (especially suitable for Forex).
4. Edit pressure labels:
◦ Turn the “Bull Pressure” and “Bear Pressure” features on or off depending on your analysis settings.
Concepts behind the calculations
• Technical market analysis: Wick lengths can indicate buying or selling pressure and provide important information on market psychology.
• Thresholds and filtering: The script uses thresholds to avoid visual overload and highlight only essential data.
• Label display: Dynamic labels improve chart readability and give the user instant feedback on market developments.
Usage
This script is great for:
• Intraday trading: Analyzing short-term movements using wick lengths.
• Forex trading: Tracking market momentum using the pip indicator.
• Swing trading: Identifying buying or selling pressure in key markets.
• Visual support: Ideal for traders who prefer a graphical display.
Description of the Wick Length Display (Advanced) script
Originality and purpose of the script
The Wick Length Display (Advanced) script is an innovative tool for traders who want to gain detailed insights into the length of candle wicks. It stands out for its versatility and user-friendly customization options. It combines precise technical calculations with visual representation to provide important information about market movements and dynamics right on the chart.
Functionality
The script calculates and displays the length of the upper and lower wicks of each candle on the chart. It also provides additional visual cues such as:
• “Bull pressure”: When green candles do not have upper wicks, this indicates strong buying pressure.
• “Bear pressure”: When red candles do not have lower wicks, this indicates strong selling pressure.
• Threshold conditions: Only displays wicks that exceed a certain threshold (optional).
• Display in pips: Allows you to display wick lengths in pips, which is useful for forex traders.
How it works
The script analyzes each candle using the following calculations:
1. Wick length calculation:
◦ Upper wick length = High - (top of the body)
◦ Lower wick length = (bottom of the body) - Low
2. Display conditions:
◦ It distinguishes between bullish and bearish candles.
◦ It checks if the calculated wicks exceed the defined thresholds before displaying them.
3. Dynamic labels:
◦ Labels are placed above or below the respective candles.
◦ Size, color and type of labels are fully customizable.
4. Limitation of labels
Alert conditions:
Alerts are triggered when the wick length of a bullish or bearish candle exceeds the defined thresholds.
Alert function:
alert() is used to issue messages with a frequency of once per candle when the conditions are met.
How to set up alerts
Save the script and add it to your chart.
Open the alert settings in TradingView.
Select the script's custom message as a trigger.
Adjust the frequency and notification type (popup, email, etc.).
Now you have a powerful tool with visual analysis and alert function!
New Bar AlertThis is probably the simplest indicator on Tradingview, it generates an alert on every new bar.
Useful for strategies where you only need chart attention at the new bar, see if you have a setup.
Helps not having to stare at the charts, the alert will tell you when it's time to take a look.
Works on all timeframes but in order to keep your sanity, best used on higher timeframes, 5mins and up.
Risk Indicator# Risk Indicator
A dynamic risk analysis tool that helps traders identify optimal entry and exit points using a normalized risk scale from 0 to 1. The indicator combines price action, moving averages, and logarithmic scaling to provide clear visual signals for different risk zones.
### Key Features
• Displays risk levels on a scale of 0-1 with intuitive color gradients (blue → cyan → green → yellow → orange → red)
• Shows predicted price levels for different risk values
• Divides the chart into 5 DCA (Dollar Cost Average) zones
• Includes customizable alerts for rapid risk changes and zone transitions
• Automatically adjusts to market conditions using dynamic ATH/ATL calculations
### Customizable Parameters
• SMA Period: Adjust the smoothing period for the baseline moving average
• Power Factor: Fine-tune the sensitivity of risk calculations
• Initial ATL Value: Set the starting point for ATL calculations
• Label Offset: Adjust the position of price level labels
• Visual Options: Toggle price levels and zone labels
• Alert Settings: Customize alert thresholds and enable/disable notifications
### Risk Zones Explained
The indicator divides the chart into five distinct zones:
- 0.0-0.2: DCA 5x (Deep Blue) - Strongest buy zone
- 0.2-0.4: DCA 4x (Cyan) - Strong buy zone
- 0.4-0.6: DCA 3x (Green) - Neutral zone
- 0.6-0.8: DCA 2x (Yellow/Orange) - Take profit zone
- 0.8-1.0: DCA 1x (Red) - Strong take profit / potential sell zone
### Alerts
Built-in alerts for:
• Rapid increases in risk level
• Rapid decreases in risk level
• Entry into buy zones
• Entry into sell zones
### How to Use
1. Add the indicator to your chart
2. Adjust the SMA period and power factor to match your trading timeframe
3. Monitor the risk level and corresponding price predictions
4. Use the DCA zones to guide your position sizing
5. Set up alerts for your preferred risk thresholds
### Tips
- Lower risk values (blue/cyan) suggest potentially good entry points
- Higher risk values (orange/red) suggest taking profits or reducing position size
- Use in conjunction with other technical analysis tools for best results
- Adjust the power factor to fine-tune sensitivity to price movements
### Notes
- Past performance is not indicative of future results
- This indicator is meant to be used as part of a complete trading strategy
- Always manage your risk and position size according to your trading plan
Version 1.0
Detrended Price Oscillator [NexusSignals]Detrended Price Oscillator (DPO) is a detrended price oscillator, used in technical analysis, strips out price trends in an effort to estimate the length of price cycles from peak to peak or trough to trough.
DPO is not a momentum indicator, instead highlights peaks and troughs in price, which are used to estimate buy and sell points in line with the historical cycle. (cf. to investopedia)
DPO indicator made by NexusSignals components :
a filled area that allow users to see easy the trend of an asset;
a sma moving average on chart (default length is 20)
a 20 sma on oscillator, both ma's are color coded to show uptrend / downtrend
a donchian channel applied to the dpo to show breakouts, breakdowns and resistances/support, reversals
few alerts for price crossing above ma, cross above the 0 dpo line, and for cross above and below the donchian channels top and bottom
How you can use DPO indicator ?
The detrended price oscillator (DPO) can be used for measuring the distance between peaks and troughs in the indicator that may help traders to make future decisions as they can locate the most recent trough and determine when the next one may occur in the meassured distance on oscillator between peaks and troughs.
You can use the indicator to find the potential price reversals, for example when the price of an asset is in a bearish trend and the dpo is bouncing from the donchian channel bottom, that may be a potential swing low for that asset, same thing in a bullish trend when the dpo rejecting at top of donchian channel may be a trend reversal, a pullback or swing high.
When DPO is above the 0 trend is in an uptrend and when dpo is below the zero the asset is possible to move into a downtrend.
Also crosses of DPO above and below the DPO moving average may signalising a trend change.
Asset MaxGain MinLoss Tracker [CHE]Asset MaxGain MinLoss Tracker – Your Tool to Discover the Best Trading Opportunities
Introduction
Hello dear traders,
Today, I'd like to introduce you to a fantastic tool: the Asset MaxGain MinLoss Tracker . This indicator is designed to help you identify the best trading opportunities in the market by analyzing the maximum gain and adjusted maximum loss potentials of various assets.
Why Use This Indicator?
1. Time-Saving Analysis
Instead of spending hours sifting through different charts, this indicator provides you with key metrics for up to 10 assets at a glance.
2. Compare Multiple Assets Simultaneously
Monitor and compare multiple assets to discover which ones offer the highest profit potential and the lowest risk of loss.
3. Customizable Settings
Adjust the observation period and select the assets you want to analyze according to your trading strategy.
4. Clear Visual Representation
Data is presented in an easy-to-read table directly on your chart, highlighting assets with the highest maximum gain and the lowest adjusted maximum loss.
How to Use It in Everyday Trading
Step 1: Setting Up the Indicator
Select Your Assets: Choose up to 10 assets you wish to track. These can be cryptocurrencies, stocks, forex pairs, etc.
Configure the Trading Period Length: Set the number of bars (candles) over which you want to calculate the maximum gain and adjusted maximum loss. This allows you to tailor the analysis to your preferred time frame, whether it's short-term trading or long-term investing.
Step 2: Interpreting the Results
Maximum Gain (%): This value shows the potential upside of each asset over the selected period. A higher percentage indicates a greater potential for profit if the asset's price moves upward.
Adjusted Maximum Loss (%): This figure represents the potential downside risk, adjusted to give a more accurate reflection of loss potential. A lower percentage means less risk of significant loss.
Category Highlighting: Assets are categorized based on their performance:
High Gain & Low Loss: Assets that have both the highest max gain and the lowest adjusted max loss.
High Gain: Assets with the highest max gain.
Low Loss: Assets with the lowest adjusted max loss.
Step 3: Making Trading Decisions
Identify Opportunities: Focus on assets categorized as High Gain & Low Loss for the most favorable risk-to-reward scenarios.
Risk Management: Use the adjusted maximum loss to assess and mitigate potential risks associated with each asset.
Portfolio Diversification: Allocate your investments across assets with varying levels of gain and loss potentials to diversify your portfolio effectively.
Practical Example
Imagine you're monitoring the following assets:
Asset 1: BTCUSD
Asset 2: ETHUSD
Asset 3: ADAUSD
Asset 4: XRPUSD
After applying the indicator:
BTCUSD shows a high maximum gain but also a high adjusted maximum loss.
ETHUSD has both a high maximum gain and a low adjusted maximum loss, categorizing it as High Gain & Low Loss.
ADAUSD indicates a low maximum gain but the lowest adjusted maximum loss.
XRPUSD reflects moderate values in both categories.
Decision Making:
Primary Focus: ETHUSD may be your top choice due to its high reward and lower risk.
Risk-Averse Option: ADAUSD could be considered if you prioritize minimizing losses.
Balanced Approach: Diversify by investing in both ETHUSD and ADAUSD.
Understanding the Core Functionality
While you don't need to delve deep into the code to use the indicator effectively, understanding its core function can enhance your confidence in the tool.
The Main Function: Calculating Max Gain and Adjusted Max Loss
The heart of the indicator is a function that calculates two critical metrics for each asset:
Maximum Gain (sym_MaxGain):
Purpose: Measures the highest potential profit over the selected period.
How It Works: It finds the lowest price (sym_minlow) within the period and calculates the percentage increase to the current high price. This shows how much you could have gained if you bought at the lowest point.
Adjusted Maximum Loss (sym_AdjustedMaxLoss):
Purpose: Provides an adjusted measure of the potential loss, giving a more realistic risk assessment.
How It Works: It identifies the highest price (sym_maxhigh) within the period and calculates the percentage decrease to the current low price. This value is adjusted to account for the diminishing impact as losses approach 100%.
Simplified Explanation of the Function
Data Retrieval: For each asset (sym), the function retrieves the high and low prices over the specified timeframe.
Calculations:
Find Highest and Lowest Prices: Determines sym_maxhigh and sym_minlow within the tracking period.
Compute Max Gain: Calculates the potential gain from sym_minlow to the current high.
Compute Max Loss: Calculates the potential loss from sym_maxhigh to the current low.
Adjust Max Loss: Adjusts the max loss calculation to prevent distortion as losses near 100%.
Output: Returns both sym_MaxGain and sym_AdjustedMaxLoss for further analysis.
Benefits of Understanding the Function
Transparency: Knowing how these values are calculated can increase your trust in the indicator's outputs.
Customization: If you're familiar with coding, you might tailor the function to suit specific trading strategies.
Enhanced Analysis: Understanding the underlying calculations allows you to interpret the results more effectively, aiding in better decision-making.
Conclusion
The Asset MaxGain MinLoss Tracker is a powerful tool that can significantly enhance your trading efficiency and effectiveness by:
Providing Quick Insights: Save time by getting immediate access to essential performance metrics of multiple assets.
Assisting in Risk Management: Use the adjusted maximum loss to understand and mitigate potential risks.
Supporting Strategic Decisions: Identify assets with the best risk-to-reward ratios to optimize your trading strategy.
Take advantage of this indicator to elevate your trading game and make more informed decisions with confidence.
Thank you for your time, and happy trading!
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 "Max Gain" indicator. A special thanks to Skipper86 for his relentless effort, creativity, and contributions to the TradingView community, which served as a foundation for this work.
Risk-Reward Labels Minimal with OffsetIndicator Explanation
The indicator “Risk-Reward Labels Minimal with Offset” is designed to assist traders in managing risk and potential rewards. It displays the Stop-Loss (SL) and Take-Profit (TP) levels for both long and short positions based on identified support and resistance levels.
Key Features:
1. Risk-Reward Ratio: Traders can adjust the risk-reward ratio to define the relationship between potential losses and potential gains (e.g., 1:1 or 1:2).
2. Risk Distance: The distance (in pips) is set to determine where to place the SL and TP levels.
3. Labels with Offset: SL and TP labels can be shifted by an offset (bars), allowing for better visualization.
4. Support and Resistance Levels: The indicator dynamically calculates support and resistance. When a support or resistance level is broken, the corresponding labels are deleted.
5. Display in Range Markets: If the market is ranging or lacks a clear trend, both long and short labels are displayed. This allows traders to identify potential entry opportunities in both directions, even when the market is not clearly trending.
6. Deletion Logic: If the price falls below support or rises above resistance, the relevant SL and TP labels are removed. However, in a Range situation, the possibility of seeing both long and short labels remains, increasing flexibility and helping to avoid false signals.
Prometheus Markov ChainThe Prometheus Markov Chain Indicator is a custom-built tool designed to predict potential future price movements using a Markov Chain approach. A Markov Chain is a statistical model that assumes the probability of moving to a future state depends solely on the current state. In this indicator, states represent price movement classifications—bullish, bearish, or neutral—and are determined based on historical price changes (percentage returns). The indicator builds a transition matrix to calculate probabilities of transitioning from one state to another, enabling traders to identify patterns and forecast likely price actions.
Core Functionality and Transition Matrix
The transition matrix is the backbone of the Markov Chain. It captures the frequency of transitions between states in the historical price data and normalizes these counts into probabilities. For example, if the price was in a bearish state and transitioned to a bullish state 3 out of 10 times, the probability of transitioning from bearish to bullish would be 0.3. The matrix is created dynamically using the stateFunc function to classify states, which can use either dynamic thresholds (highest and lowest returns over a lookback period) or a user-defined percent return threshold. Below is the snippet that updates the transition matrix:
transitionMatrix = matrix.new(dimension, dimension, 0.0)
for i = 0 to array.size(vec) - 2
fromState = array.get(vec, i)
toState = array.get(vec, i + 1)
transitionMatrix.set(fromState, toState, transitionMatrix.get(fromState, toState) + 1)
for i = 0 to dimension - 1
rowSum = 0.0
for j = 0 to dimension - 1
rowSum += transitionMatrix.get(i, j)
for j = 0 to dimension - 1
prob = transitionMatrix.get(i, j) / rowSum
transitionMatrix.set(i, j, prob)
This snippet iterates through historical price movements, counts state transitions, and then normalizes each row of the matrix so that the sum of probabilities for all possible transitions from a given state equals 1.
How the Indicator Predicts Future States
After constructing the transition matrix, the indicator calculates the current state of the price based on the latest percentage return and then uses the matrix to compute probabilities for transitioning to other states. The state with the highest probability is predicted as the next state, which is displayed on the chart using color-coded labels: green for bullish and red for bearish. The following snippet demonstrates how the current state and predictions are calculated:
current_chng = (close - close ) / close
var int current_state = na
if not use_custom_thresh
highest_chng = ta.highest(current_chng, int(size) * 2)
lowest_chng = ta.lowest(current_chng, int(size) * 2)
current_state := stateFunc(current_chng, highest_chng, lowest_chng)
else
current_state := stateFunc(current_chng, custom_thresh)
predicted_probs = array.new(dimension, 0.0)
for j = 0 to dimension - 1
array.set(predicted_probs, j, transitionMatrix.get(current_state, j))
The indicator evaluates which state has the highest transition probability (highest_prob) and places corresponding labels on the chart. For example, if the next state is predicted to be bullish, a green "Bullish" label is placed below the current bar. This predictive functionality helps traders anticipate potential reversals or continuations in price trends based on historical behavior patterns.
Usage:
Here we see the indicator at work on $PLTR. The states predicted are bullish then bearish. In this example we then see price move in a way that verifies those predictions.
On this 4 Hour NASDAQ:AMZN chart we see predictions play out in a short trade style. States quickly move from one to another but not without giving traders a way to take advantage.
This is the perspective we aim to provide. We encourage traders to not follow indicators blindly. No indicator is 100% accurate. This one can give you a different perspective market state. We encourage any comments about desired updates or criticism!
Weekly Stacked Daily Changes [LuxAlgo]The Weekly Stacked Daily Changes tool allows traders to compare daily net price changes for each day of the week, stacked by week. It provides a very convenient way to compare daily and weekly volatility at the same time.
🔶 USAGE
The tool requires no configuration and works perfectly out of the box, displaying the net price change for each day of the week as stacked boxes of the appropriate size.
Traders can adjust the width of the columns and the spacing between days and weeks, options to change the color and disable the months and new month lines are also available.
🔹 Bottom Stack Bias
This feature allows traders to compare weekly volatility in two different ways.
With this feature disabled, all weeks use zero as the bottom of the stack, so traders can see at a glance weeks with more volatility and weeks with less volatility.
Enabling this feature will cause the tool to display the stacks with the weekly net price change as the bottom, so if a stack starts below the zero line it means that week has a negative net return, and if it starts above the zero line it means that week has a positive net return.
🔶 SETTINGS
Width: Select the fixed width for each column.
Offset: Choose the fixed width between each column.
Spacing: Select the distance between each day within each column.
🔹 Style
Bottom Stack Bias: Use weekly net price change as the bottom of the stack.
Bullish Change: Color for days with positive net price change
Bearish Change: Color for days with negative net price change
Show Months: Under each week stack, display the month
Show Months Delimiter: Display a line indicating the start of a new month
Price Action Dynamics Oscillator (PADO)1 minute ago
Price Action Dynamics Oscillator (PADO)
Indicator Overview and Technical Deep Dive
Concept and Philosophy
The Price Action Dynamics Oscillator (PADO) is a sophisticated technical analysis tool designed to provide multi-dimensional insights into market behavior by decomposing price action into manipulation and distribution metrics. The indicator goes beyond traditional momentum or trend indicators by introducing a nuanced approach to understanding market microstructure.
Key Architectural Components
1. Timeframe and Depth Selection
Pivot Depth Options:
Short Term (Length: 12 periods)
Intermediate Term (Length: 20 periods)
Long Term (Length: 100 periods)
This flexible configuration allows traders to adapt the indicator's sensitivity to different market conditions and trading styles.
2. Core Calculation Methodology
Manipulation Metrics
Calculates manipulation differently for green (bullish) and red (bearish) candles
Normalized against Average True Range (ATR) for consistent comparison across different volatility environments
Green Candle Manipulation: (Open - Low) / ATR
Red Candle Manipulation: (High - Open) / ATR
Distribution Metrics
Measures the directional strength and potential momentum shift
Green Candle Distribution: (Close - Open)
Red Candle Distribution: (Open - Close)
3. Normalization and Smoothing
Uses Simple Moving Average (SMA) for smoothing
Dynamic length calculation based on price range distance
Ensures minimum SMA length of 2 to prevent calculation errors
Unique Features
Visualization Toggles
Traders can selectively display:
Manipulation data
Distribution data
Long-term reference lines
Valuation metrics
Strategy signals
Valuation Comparative Analysis
Compares current manipulation and distribution metrics to 1000-bar long-term averages
Color-coded visualization for quick interpretation
Blue: Manipulation above average
Purple: Manipulation below average
Orange: Distribution above average
Yellow: Distribution below average
Strategy Deployment
Generates a composite strategy signal by comparing manipulation and distribution valuations
Uses Exponential Moving Average (EMA) for smoother signal generation
Incorporates volatility bands for context-aware signal interpretation
Quadrant Analysis
Classifies market state into four quadrants based on manipulation and distribution valuations:
Q1: Low Manipulation, High Distribution
Q2: High Manipulation, High Distribution
Q3: Low Manipulation, Low Distribution
Q4: High Manipulation, Low Distribution
Each quadrant is color-coded to provide visual market state representation.
Warning Signals
Manipulation Warning: When strategy crosses below low volatility band
Distribution Warning: When strategy crosses above high volatility band
Visual Indicators
Bar coloration based on strategy momentum
Multiple color states representing different market dynamics
Recommended Use Cases
Intraday and swing trading
Multi-timeframe market analysis
Volatility and momentum assessment
Trend reversal and continuation identification
Potential Limitations
Complexity might require significant trader education
Performance can vary across different market conditions
Requires careful parameter optimization
Recommended Settings
Best used on liquid markets with clear price action
Ideal for:
Forex
Futures
Large-cap stocks
Cryptocurrency pairs
Customization and Optimization
Traders should:
Backtest across multiple assets
Adjust timeframe settings
Calibrate visualization toggles
Use in conjunction with other technical indicators
Licensing
Mozilla Public License 2.0
Open-source and modification-friendly
Conclusion
The PADO represents an advanced approach to market analysis, blending traditional technical analysis with innovative metrics for deeper market understanding.
PADO Quadrant Color Analysis: Deep Dive
Quadrant Color Scheme Breakdown
Quadrant 1: Lime Green Background (RGB: 0, 255, 21, 90)
Condition: val_manip < 1 AND val_distr > 1
Market Interpretation:
Low Manipulation Pressure
High Distribution Activity
Potential Scenario:
Smart money might be gradually distributing positions
Trading Implications:
Caution for current trend followers
Potential preparation for trend change
Increased probability of consolidation or reversal
Quadrant 2: Bright Blue Background (RGB: 0, 191, 255, 90)
Condition: val_manip > 1 AND val_distr > 1
Market Interpretation:
High Manipulation Pressure
High Distribution Activity
Potential Scenario:
Strong institutional involvement
Potential market transition phase
Significant volume and momentum
Trading Implications:
High volatility expected
Increased market uncertainty
Potential for sharp price movements
Requires careful risk management
Quadrant 3: Light Gray Background (RGB: 252, 252, 252, 90)
Condition: val_manip < 1 AND val_distr < 1
Market Interpretation:
Low Manipulation Pressure
Low Distribution Activity
Potential Scenario:
Market consolidation
Reduced institutional activity
Potential low-volatility period
Trading Implications:
Range-bound market
Reduced trading opportunities
Potential setup for future breakout
Ideal for mean reversion strategies
Quadrant 4: Light Yellow Background (Hex: #f6ff0019)
Condition: val_manip > 1 AND val_distr < 1
Market Interpretation:
High Manipulation Pressure
Low Distribution Activity
Potential Scenario:
Accumulation of positions
Trading Implications:
Increased probability of directional move soon
Color Psychology and Technical Significance
Color Selection Rationale
Lime Green (Q1): Represents potential growth and transition
Bright Blue (Q2): Signifies high energy and institutional activity
Light Gray (Q3): Indicates neutrality and consolidation
Transparent Green (Q4): Suggests emerging trend potential
Advanced Interpretation Guidelines
Color Transition Analysis
Observe how the quadrant colors change
Rapid color shifts might indicate:
Market regime changes
Shifts in institutional sentiment
Potential trend acceleration or reversal
Technical Implementation Notes
Calculation Snippet
pinescriptCopyq1 = (val_manip < 1) and (val_distr > 1)
q2 = (val_manip > 1) and (val_distr > 1)
q3 = (val_manip < 1) and (val_distr < 1)
q4 = (val_manip > 1) and (val_distr < 1)
bgcolor(q1 ? color.rgb(0, 255, 21, 90):
q2 ? color.rgb(0, 191, 255, 90):
q3 ? color.rgb(252, 252, 252, 90):
q4 ? #f6ff0019:na)
Alpha Channel (Transparency)
90 and 0x19 values ensure background color doesn't overwhelm chart
Allows underlying price action to remain visible
Subtle visual cue without significant chart obstruction
Practical Trading Recommendations
Never Trade Solely on Quadrant Colors
Use as a complementary analysis tool
Combine with other technical and fundamental indicators
Timeframe Considerations
Validate quadrant signals across multiple timeframes
Longer timeframes provide more reliable signals
Risk Management
Set appropriate stop-loss levels
Use position sizing strategies
Be prepared for false signals
Recommended Workflow
Identify current quadrant
Assess overall market context
Confirm with other indicators
Execute with proper risk management
