ICT Professional Accumulation DistributionICT Professional Accumulation Distribution (ICT AD) provides a x-ray view into market accumulation and distribution. You can literally see the institutions at work.
The indicator consists of two cumulative lines derived from:
Cumulative change from open to close
Cumulative change from previous close to new open
By overlaying these two cumulative lines, you can detect real meaningful divergence that is narrative based not mathematically derived. You're seeing the real works of algorithms in play working in this area.
These divergences are only useful at extremes (topping or bottoming formations), not while trending. It will probably confirm your suspicion about making a important high or low.
This works on all timeframes but is most impactful on the daily.
How to use:
Method 1:
Enable the option for "Show Open vs Close."
Calculate the shift by subtracting the "Open vs Close" line value from the ICT Accumulation/Distribution (AD) line value.
Look for divergences between the two cumulative lines.
Method 2:
Switch the chart's display mode to "Line View" (representing the Open vs Close).
look for divergences between the line chart and the ICT AD line.
Индикаторы и стратегии
Three-Bar Reversal SignalThis indicator is a simple setup of Three Bar Reversal. Logic of the code is as below.
Rules :
Long Setup
Bar 1 closes down
Low of Bar 2 is below the low of Bar 1 (and Bar 3)
Bar 3 closes above the high of both Bar 1 and Bar 2
Buy at the close of Bar 3
Short Setup
Bar 1 closes up
High of Bar 2 is above the high of Bar 1 (and Bar 3)
Bar 3 closes below the low of both Bar 1 and Bar 2
Sell at the close of Bar 3
Dynamic Range EvaluatorThe Dynamic Range Evaluator script or indicator analyzes the dynamic movement of price ranges in the market, offering several key advantages:
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1. Identifies Market Volatility
It detects when price ranges expand or contract, helping traders gauge the market's current volatility—whether it is highly volatile (wide range) or calm (narrow range).
2. Adapts Strategies Based on Market Conditions
The script allows traders to implement suitable strategies:
Use Breakout strategies when the range expands.
Use Mean Reversion strategies when the price moves within a tight range.
3. Accurate Entry and Exit Points
By identifying dynamic price zones, it helps spot potential reversals or areas near key support/resistance levels, reducing the risk of poor entry decisions in unclear market phases.
4. Versatile Across Market Phases
Whether in a bullish, bearish, or sideways market, the Dynamic Range Evaluator adjusts smoothly to shifting conditions, minimizing the need for frequent modifications.
5. Effective Across Multiple Time Frames
It works well on both lower and higher time frames. For instance:
On lower time frames, it helps identify short-term trade entries/exits.
On higher time frames, it assists with analyzing broader trends.
6. Customizable Dynamic Parameters
Traders can modify range thresholds or evaluation criteria to suit specific asset classes or currency pairs, providing flexibility and improved accuracy.
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Use Cases
Combine with ATR (Average True Range) to identify optimal average ranges.
Align Take Profit / Stop Loss levels with current market ranges.
Integrate with Breakout Strategies by monitoring for range expansion and waiting for key support/resistance breakouts.
Dynamic Score PSAR [QuantAlgo]Dynamic Score PSAR 📈🧬
The Dynamic Score PSAR by QuantAlgo introduces an innovative approach to trend detection by utilizing a dynamic trend scoring technique in combination with the Parabolic SAR. This method goes beyond traditional trend-following indicators by evaluating market momentum through a scoring system that analyzes price behavior over a customizable window. By dynamically adjusting to evolving market conditions, this indicator provides clearer, more adaptive trend signals that help traders and investors anticipate market reversals and capitalize on momentum shifts with greater precision.
💫 Conceptual Foundation and Innovation
At the core of the Dynamic Score PSAR is the dynamic trend score system, which assesses price movements by comparing normalized PSAR values across a range of historical data points. This dynamic trend scoring technique offers a unique, probabilistic approach to trend analysis by evaluating how the current market compares to past price movements. Unlike traditional PSAR indicators that rely on static parameters, this scoring mechanism allows the indicator to adjust in real time to market fluctuations, offering traders and investors a more responsive and insightful view of trends. This innovation makes the Dynamic Score PSAR particularly effective in detecting shifts in momentum and potential reversals, even in volatile or complex market environments.
✨ Technical Composition and Calculation
The Dynamic Score PSAR is composed of several advanced components designed to provide a higher probability of detecting accurate trend shifts. The key innovation lies in the dynamic trend scoring technique, which iterates over historical PSAR values and evaluates price momentum through a dynamic scoring system. By comparing the current normalized PSAR value with previous data points over a user-defined window, the system generates a score that reflects the strength and direction of the trend. This allows for a more refined and responsive detection of trends compared to static, traditional indicators.
To enhance clarity, the PSAR values are normalized against an Exponential Moving Average (EMA), providing a standardized framework for comparison. This normalization ensures that the indicator adapts dynamically to market conditions, making it more effective in volatile markets. The smoothing process reduces noise, helping traders and investors focus on significant trend signals.
Additionally, users can adjust the length of the data window and the sensitivity thresholds for detecting uptrends and downtrends, providing flexibility for different trading and investing environments.
📈 Features and Practical Applications
Customizable Window Length: Adjust the window length to control the indicator’s sensitivity to recent price movements. This provides flexibility for short-term or long-term trend analysis.
Uptrend/Downtrend Thresholds: Set customizable thresholds for identifying uptrends and downtrends. These thresholds define when trend signals are triggered, offering adaptability to different market conditions.
Bar Coloring and Gradient Visualization: Visual cues, including color-coded bars and gradient fills, make it easier to interpret market trends and identify key moments for potential trend reversals.
Momentum Confirmation: The dynamic trend scoring system evaluates price action over time, providing a probabilistic measure of market momentum to confirm the strength and direction of a trend.
⚡️ How to Use
✅ Add the Indicator: Add the Dynamic Score PSAR to your favourites, then to your chart and adjust the PSAR settings, window length, and trend thresholds to match your preferences. Customize the sensitivity to price movements by tweaking the window length and thresholds for different market conditions.
👀 Monitor Trend Shifts: Watch for trend changes as the normalized PSAR values cross key thresholds, and use the dynamic score to confirm the strength and direction of trends. Bar coloring and background fills visually highlight key moments for trend shifts, making it easier to spot reversals.
🔔 Set Alerts: Configure alerts for significant trend crossovers and reversals, ensuring you can act on market movements promptly, even when you’re not actively monitoring the charts.
🌟 Summary and Usage Tips
The Dynamic Score PSAR by QuantAlgo is a powerful tool that combines traditional trend-following techniques with the flexibility of a dynamic trend scoring system. This innovative approach provides clearer, more adaptive trend signals, reducing the risk of false entries and exits while helping traders and investors capture significant market moves. The ability to adjust the indicator’s sensitivity and thresholds makes it versatile across different trading and investing environments, whether you’re focused on short-term pivots or long-term trend reversals. To maximize its effectiveness, fine-tune the sensitivity settings based on current market conditions and use the visual cues to confirm trend shifts.
Multi-Timeframe SMA Plot**Introducing the Multi-Timeframe SMA Plot**
This script is designed to help traders easily visualize multiple Simple Moving Averages (SMAs) across different timeframes, all on a single chart. The Multi-Timeframe SMA Plot allows you to configure up to three different SMAs with customizable lengths, timeframes, colors, line styles, and line thicknesses, providing a versatile tool to analyze market trends in various granularities.
**Key Features**:
1. **Multiple SMA Timeframes**: You can plot SMAs from different timeframes like 15 minutes, 1 hour, daily, weekly, and more, enabling a comprehensive perspective of market movements.
2. **Fully Customizable**: Each SMA comes with options to adjust the length, timeframe, color, line style (solid, dashed, or dotted), and thickness, giving you control over how you visualize trend data.
3. **User-Friendly Inputs**: The script provides intuitive input fields that make it easy to adjust the settings without diving into the code, making it suitable for both beginner and advanced traders.
**How to Use**:
- Select the desired length and timeframe for each SMA (e.g., 50-period SMA on a 1-hour chart).
- Customize the line style and color to match your chart's theme or make distinctions between each SMA.
- Analyze how different SMAs align or cross over time to identify potential support, resistance, or trend changes.
The Multi-Timeframe SMA Plot is ideal for traders who rely on moving averages to gauge trend strength, direction, and potential entry or exit points. By having multiple SMAs from different timeframes on one chart, you can better understand the overall market sentiment and make more informed decisions.
Give this script a try and streamline your technical analysis with clear, customizable SMA lines!
**Code**: Check out the full script and start customizing it to fit your trading style. Your feedback is always welcome!
Altcoins vs BTC Market Cap HeatmapAltcoins vs BTC Market Cap Heatmap
"Ground control to major Tom" 🌙 👨🚀 🚀
This indicator provides a visual heatmap for tracking the relationship between the market cap of altcoins (TOTAL3) and Bitcoin (BTC). The primary goal is to identify potential market cycle tops and bottoms by analyzing how the TOTAL3 market cap (all cryptocurrencies excluding Bitcoin and Ethereum) compares to Bitcoin’s market cap.
Key Features:
• Market Cap Ratio: Plots the ratio of TOTAL3 to BTC market caps to give a clear visual representation of altcoin strength versus Bitcoin.
• Heatmap: Colors the background red when altcoins are overheating (TOTAL3 market cap equals or exceeds BTC) and blue when altcoins are cooling (TOTAL3 market cap is half or less than BTC).
• Threshold Levels: Includes horizontal lines at 1 (Overheated), 0.75 (Median), and 0.5 (Cooling) for easy reference.
• Alerts: Set alert conditions for when the ratio crosses key levels (1.0, 0.75, and 0.5), enabling timely notifications for potential market shifts.
How It Works:
• Overheated (Ratio ≥ 1): Indicates that the altcoin market cap is on par or larger than Bitcoin's, which could signal a top in the cycle.
• Cooling (Ratio < 0.5): Suggests that the altcoin market cap is half or less than Bitcoin's, potentially signaling a market bottom or cooling phase.
• Median (Ratio ≈ 0.75): A midpoint that provides insight into the market's neutral zone.
Use this tool to monitor market extremes and adjust your strategy accordingly when the altcoin market enters overheated or cooling phases.
Futures Globex Session(s)This indicator draws a box around the Globex Session for the various Futures markets. The box height defines the highs and lows of that session, and the width defines the timeframe of that session. The boxes are outlined green if price rose during that period, and red if price fell during that period. The default Globex Session is set for the Equity Index Futures and is set in the UTC-4 time zone (Eastern Time). In the settings you can adjust the session time and time zone of your Globex Session to reflect the trading times of that market. Below are the session times for various Futures markets set in time zone UTC-4.
Equity Indexes: 18:00 - 9:30
(ES, NQ, YM, RTY)
Treasuries: 18:00 - 8:20
(ZN, ZB)
Metals: 18:00 - 8:20
(GC)
Energies: 18:00 - 9:00
(CL, NG)
Agricultures: 20:00 - 9:30
(ZS, ZW)
Standard Deviation OscillatorStandard Deviation Oscillator (STDEV OSC) v1.1
Description
The Standard Deviation Oscillator transforms traditional volatility measurements into a dynamic oscillator that fluctuates between 0 and 100. This advanced technical analysis tool helps traders identify periods of extreme volatility and potential market turning points.
Features
Normalized volatility readings (0-100 scale)
Dynamic color changes based on volatility levels
Customizable overbought/oversold thresholds
Built-in alert conditions
Adaptive calculation using rolling windows
Clean, professional visualization
Indicator Parameters
Length: 20; Calculation period for standard deviation
Source: close; Price source for calculations
Overbought Level: 70; Upper threshold for high volatility
Oversold Level: 30; Lower threshold for low volatility
Visual Components
- Main Oscillator Line: Changes color based on current level
- Red: Above overbought level
- Green: Below oversold level
- Blue: Normal range
- Reference Lines:
- Overbought level (default: 70)
- Oversold level (default: 30)
- Middle line (50)
Alert Conditions
1. Volatility High Alert
- Triggers when oscillator crosses above the overbought level
- Useful for identifying potential market tops or breakout scenarios
2. Volatility Low Alert
- Triggers when oscillator crosses below the oversold level
- Helps identify potential market bottoms or consolidation periods
Risk Adjustment Tool
- Scale position sizes inversely to oscillator readings
- Reduce exposure during extremely high volatility periods
- Increase position sizes during normal volatility conditions
Best Practices
1. Timeframe Selection
- Best suited for 1H, 4H, and Daily charts
- Adjust length parameter based on timeframe
2. Confirmation
- Use in conjunction with trend indicators
- Confirm signals with price action patterns
- Consider overall market context
3. Parameter Optimization
- Backtest different length settings
- Adjust overbought/oversold levels based on asset
- Consider market conditions when setting alerts
Technical Notes
- Built in PineScript v5
- Optimized for TradingView platform
- Uses rolling window calculations for better adaptability
- Compatible with all trading instruments
- Minimal performance impact on charts
Version History
- v1.1: Added dynamic coloring, customizable levels, and alert conditions
- v1.0: Initial release with basic oscillator functionality
Disclaimer
This technical indicator is provided for educational and informational purposes only. Past performance is not indicative of future results. Always conduct thorough testing and use proper risk management techniques.
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Tags: #TechnicalAnalysis #Volatility #Trading #Oscillator #TradingView #PineScript
Wolfpack Elite - Liquidation Sniper - by 9123416916### Strategy: **Wolfpack Elite - Liquidation Sniper by Md Arif**
**Overview:**
This is a technical analysis strategy designed for trading, which combines two popular technical indicators: **Relative Strength Index (RSI)** and **Moving Averages (MA)**. It identifies potential buy (long) and sell (short) signals based on oversold and overbought conditions in the market, along with crossovers between two moving averages. The strategy also incorporates a risk management system by setting **take profit** and **stop loss** levels to protect against large losses and lock in gains.
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**Key Components:**
1. **Indicators Used:**
- **RSI (Relative Strength Index):**
- Measures the speed and change of price movements.
- Used to identify **overbought** (above 70) and **oversold** (below 30) conditions.
- **Short and Long Moving Averages:**
- The strategy uses two simple moving averages (SMA) to detect trends and potential entry points.
- Short MA (9-period) and Long MA (21-period) are used for crossovers.
2. **Entry Signals:**
- **Bullish Entry (Long Position):**
- Triggered when the RSI falls below the oversold level (30) and the **short MA** crosses above the **long MA** (bullish crossover).
- This suggests that the market might be oversold and ready to rebound.
- **Bearish Entry (Short Position):**
- Triggered when the RSI rises above the overbought level (70) and the **short MA** crosses below the **long MA** (bearish crossover).
- This suggests that the market might be overbought and due for a correction.
3. **Risk Management:**
- **Take Profit and Stop Loss:**
- The strategy calculates the take profit and stop loss levels as percentages of the entry price.
- **Take Profit:** Set at 5% above the entry price for long positions and 5% below the entry price for short positions.
- **Stop Loss:** Set at 3% below the entry price for long positions and 3% above the entry price for short positions.
4. **Position Sizing:**
- The position size is calculated as a percentage of the trader's total equity (default set to 100% of equity).
5. **Exit Conditions:**
- **For Long Positions:**
- Exit the trade if the price hits the take profit level (5% above entry) or the stop loss level (3% below entry).
- **For Short Positions:**
- Exit the trade if the price hits the take profit level (5% below entry) or the stop loss level (3% above entry).
6. **Visualization:**
- The strategy visually plots the short and long moving averages on the chart.
- It also marks **bullish crossovers** with green upward triangles and **bearish crossovers** with red downward triangles, making it easier to spot potential entry points.
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**How the Strategy Works:**
- The strategy starts by calculating the **RSI** and **moving averages**.
- It waits for specific conditions to trigger buy or sell signals. If the RSI indicates that the market is oversold and a bullish crossover occurs, it initiates a **long trade**. Similarly, if the RSI shows an overbought condition and a bearish crossover occurs, it opens a **short trade**.
- Once a trade is open, the strategy monitors the price and automatically exits the trade if the price reaches the set take profit or stop loss level.
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This strategy is designed for active traders who seek to capitalize on short-term price movements and want clear entry/exit points with built-in risk management.
Strategy: Candlestick Wick Analysis with Volume Conditions
This strategy focuses on analyzing the wicks (or shadows) of candlesticks to identify potential trading opportunities based on candlestick structure and volume. Based on these criteria, it places stop orders at the extremities of the wicks when certain conditions are met, thus increasing the chances of capturing significant price movements.
Trading Criteria
Volume Conditions:
The strategy checks if the volume of the current candle is higher than that of the previous three candles. This ensures that the observed price movement is supported by significant volume, increasing the probability that the price will continue in the same direction.
Wick Analysis:
Upper Wick:
If the upper wick of a candle represents more than 90% of its body size and is longer than the lower wick, this indicates that the price tested a resistance level before pulling back.
Order Placement: In this case, a Buy Stop order is placed at the upper extremity of the wick. This means that if the price rises back to this level, the order will be triggered, and the trader will take a buy position.
SL Management: A stop-loss is then placed below the lowest point of the same candle. This protects the trader by limiting losses if the price falls back after the order is triggered.
Lower Wick:
If the lower wick of a candle is longer than the upper wick and represents more than 90% of its body size, this indicates that the price tested a support level before rising.
Order Placement: In this case, a Sell Stop order is placed at the lower extremity of the wick. Thus, if the price drops back to this level, the order will be triggered, and the trader will take a sell position.
SL Management: A stop-loss is then placed above the highest point of the same candle. This ensures risk management by limiting losses if the price rebounds upward after the order is triggered.
Strategy Advantages
Responsiveness to Price Movements: The strategy is designed to detect significant price movements based on the market's reaction around support and resistance levels. By placing stop orders directly at the wick extremities, it allows capturing strong movements in the direction indicated by the candles.
Securing Positions: Using stop-losses positioned just above or below key levels (wicks) provides better risk management. If the market doesn't move as expected, the position is automatically closed with a limited loss.
Clear Visual Indicators: Symbols are displayed on the chart at the points where orders have been placed, making it easier to understand trading decisions. This helps to quickly identify the support or resistance levels tested by the price, as well as potential entry points.
Conclusion
The strategy is based on the idea that large wicks signal areas where buyers or sellers have tested significant price levels before temporarily retreating. By placing stop orders at the extremities of these wicks, the strategy allows capturing price movements when they confirm, while limiting risks through strategically placed stop-losses. It thus offers a balanced approach between capturing potential profit and managing risk.
This description emphasizes the idea of capturing significant market movements with stop orders while providing a clear explanation of the logic and risk management. It’s tailored for publication on TradingView and highlights the robustness of the strategy.
ORB Daily 10 min (9:30am-3pm)This script implements the Opening Range Breakout (ORB) strategy for the New York trading session, specifically from 9:30 AM to 3:00 PM (Eastern Time). It identifies the high and low of the first 10 minutes (the first two 5-minute candles) after the market opens and draws a box representing this range. The box remains on the chart throughout the day until 3:00 PM. This strategy is useful for traders looking to trade breakouts of the opening range, often indicating potential trends or reversals.
Master Bitcoin Halving Color CodingMaster Bitcoin Halving Color Coding is a customizable TradingView indicator that visualizes Bitcoin price trends relative to its halving events. It color-codes price data based on the number of days since the most recent halving:
Yellow: 0–546 days post-halving
Blue: 547–849 days
Green: 850–1179 days
White: 1180+ days
Trailing Stop Loss Smart [TradingFinder] Market Trend + CVD/EMA🔵 Introduction
Trailing Stop Loss (TSL) is one of the most powerful tools available. A Trailing Stop Loss is a modification of a typical stop order that adjusts dynamically based on market price movement. It can be set at a defined percentage or dollar amount away from the security's current market price, making it a flexible tool for locking in profits while minimizing risk. Unlike standard stop-loss orders, a Trailing Stop follows the market in the direction of the trade, protecting gains without requiring constant manual adjustments.
The Trailing Stop Loss Smart (TFlab Trailing Stop) indicator takes this concept even further by incorporating advanced metrics like Cumulative Volume Delta (CVD), volume dynamics, and Average True Range (ATR). This combination not only enhances risk management but also acts as a trend identifier, providing traders with a powerful tool to capitalize on both short-term and long-term price movements.
This indicator also supports various Order Types, allowing for flexible strategies that include a trailing stop/stop-loss combo to maximize winning trades while minimizing losses. The trailing stop limit is particularly useful for traders who want to set their stop at a precise level relative to the current market price, either by a percentage or a dollar amount. The Trailing Stop Loss Smart indicator can help ensure that traders do not exit too early during trends, while the stop-loss feature kicks in during reversals.
The advantages of using a Trailing Stop Loss are its ability to protect profits and reduce the emotional decision-making process in volatile markets. However, like all trading strategies, it has disadvantages, such as the risk of triggering too early during normal market fluctuations. By understanding how the Trailing Stop Loss Smart indicator integrates features like CVD, ATR, and volume analysis, traders can leverage its full potential while navigating these pros and cons.
With its unique ability to track market movements and trends using Cumulative Volume Delta, volume dynamics, and ATR-based trailing stops, this indicator offers a complete solution for traders looking to secure profits while minimizing downside risk. Whether you're employing a simple trailing stop or a trailing stop/stop-loss combo, this tool provides all the flexibility and precision needed to execute winning trades in various markets, including Forex, Crypto, and Stock.
🔵 How to Use
The Trailing Stop Loss Smart indicator integrates multiple advanced components to provide traders with superior risk management and trend identification.
Here’s how each part of the logic works :
🟣 Cumulative Volume Delta (CVD) Logic
The CVD tracks buying and selling pressure by calculating the difference between upward and downward price movements. When there’s more buying pressure, the CVD is positive, indicating a potential bullish trend. Conversely, more selling pressure results in a negative CVD, pointing to a bearish trend.
CVD Trend Detection : The indicator determines whether the market is in a bullish or bearish phase by comparing the CVD to its moving average. A bullish trend is confirmed when the CVD is above its moving average and the price is closing higher.
A bearish trend occurs when the CVD is below its moving average and the price is closing lower. This trend detection is critical for determining whether the trailing stop should be placed below the price (bullish) or above it (bearish).
🟣 Volume Dynamics
Volume is a key factor in identifying market strength. The Trailing Stop Loss Smart indicator pulls volume data based on the market selected (Forex, Crypto, or Stock) and adjusts the trailing stop based on whether the market is experiencing high volume or low volume.
High Volume : When the current volume exceeds the average volume, the market is in a high-volume state. During these conditions, the trailing stop is placed closer to the price, as high volume often indicates strong trends with less chance of reversals.
Low Volume : In low-volume conditions, the trailing stop gives the market more room to breathe by placing the stop further away from the price. This prevents premature stop-outs in periods of reduced market activity.
🟣 ATR-Based Trailing Stop
The Average True Range (ATR) is used to measure market volatility. The Trailing Stop Loss Smart uses the ATR to dynamically adjust the stop-loss distance.
Bullish Market : When a bullish trend is detected, the trailing stop is placed below the lowest price of the recent bars (determined by the Bar Back parameter), and adjusted by the ATR Multiplier. This allows for tighter protection during strong bullish trends.
Bearish Market : When the market is bearish, the trailing stop is placed above the highest price of recent bars, also adjusted by the ATR Multiplier. This ensures that short positions are safeguarded against sudden reversals.
🟣 Dynamic Stop-Loss Updates
The trailing stop is updated every few bars (according to the Refiner parameter), ensuring it remains relevant to the most recent price action and volume changes. This dynamic feature ensures the stop-loss adapts to both trending and volatile market conditions, without requiring manual intervention.
High Volume with Trends : In periods of high volume and a confirmed trend, the stop-loss is positioned tightly to lock in profits while minimizing the risk of reversal.
Low Volume with Trends : In low-volume conditions, the stop-loss is placed further from the price, allowing the market to move freely without triggering premature exits.
🟣 Visual Representation
The indicator visually represents the trailing stop on the chart, with green lines indicating bullish trends and red lines for bearish trends. This visual aid helps traders quickly assess the state of the market and the position of their trailing stop in real-time.
🔵 Settings
The Trailing Stop Loss Smart indicator offers several customizable settings to suit various trading strategies. Understanding these inputs is key to optimizing the tool for your specific trading style.
🟣 General Settings
Cumulative Mode : This controls how the CVD is calculated.
You can choose between :
EMA : Exponential Moving Average smoothing.
Periodic : Sums the delta over a fixed period.
CVD Period : Defines the look-back period for CVD calculation. A longer period smooths the data, making it less sensitive to short-term fluctuations.
Ultra Data : This Boolean input aggregates volume across multiple exchanges for a more comprehensive view of market activity.
Market Ultra Data : Select between Forex, Crypto, and Stock to ensure the indicator pulls accurate volume data for your market.
🟣 Logical Settings
Moving Average CVD Period : Defines the period for the moving average of the CVD. A longer period smooths the trend, reducing noise.
Moving Average Volume Period : Sets the period for the moving average used to distinguish between high and low volume conditions.
Level Finder Bar Back : Determines how many bars to look back when identifying the highest or lowest price for trailing stop placement.
Levels update per candles : Sets how often (in bars) the trailing stop should be updated to remain in sync with market movements.
ATR On : Toggles the use of ATR to adjust the trailing stop based on volatility.
ATR Multiplie r: Defines how far the stop is placed from the price based on the ATR. A larger multiplier increases the stop distance, reducing the likelihood of getting stopped out during market fluctuations.
ATR Multiplier Adjusts the distance of the trailing stop based on the ATR. A higher multiplier places the stop further from the price, providing more breathing room in volatile markets.
🔵 Conclusion
The Trailing Stop Loss Smart indicator is a comprehensive tool for traders looking to manage risk while identifying market trends. By incorporating Cumulative Volume Delta (CVD) to detect buying and selling pressure, volume dynamics to gauge market activity, and ATR to adjust for volatility, this indicator ensures that stop-loss levels are both adaptive and protective.
Whether you’re trading in Forex, Crypto, or Stock markets, the Trailing Stop Loss Smart allows you to capitalize on trends while dynamically adjusting to changing market conditions. Its ability to distinguish between high-volume and low-volume periods ensures that you’re not stopped out prematurely during periods of consolidation or market hesitation.
By providing real-time visual feedback, dynamic adjustments, and trend identification, this indicator serves as a vital tool for traders aiming to maximize profits while minimizing risk. Its versatility and adaptability make it an essential part of any trader’s toolkit, helping you stay ahead in fast-moving markets while safeguarding your positions.
Chande Momentum Oscillator StrategyThe Chande Momentum Oscillator (CMO) Trading Strategy is based on the momentum oscillator developed by Tushar Chande in 1994. The CMO measures the momentum of a security by calculating the difference between the sum of recent gains and losses over a defined period. The indicator offers a means to identify overbought and oversold conditions, making it suitable for developing mean-reversion trading strategies (Chande, 1997).
Strategy Overview:
Calculation of the Chande Momentum Oscillator (CMO):
The CMO formula considers both positive and negative price changes over a defined period (commonly set to 9 days) and computes the net momentum as a percentage.
The formula is as follows:
CMO=100×(Sum of Gains−Sum of Losses)(Sum of Gains+Sum of Losses)
CMO=100×(Sum of Gains+Sum of Losses)(Sum of Gains−Sum of Losses)
This approach distinguishes the CMO from other oscillators like the RSI by using both price gains and losses in the numerator, providing a more symmetrical measurement of momentum (Chande, 1997).
Entry Condition:
The strategy opens a long position when the CMO value falls below -50, signaling an oversold condition where the price may revert to the mean. Research in mean-reversion, such as by Poterba and Summers (1988), supports this approach, highlighting that prices often revert after sharp movements due to overreaction in the markets.
Exit Conditions:
The strategy closes the long position when:
The CMO rises above 50, indicating that the price may have become overbought and may not provide further upside potential.
Alternatively, the position is closed 5 days after the buy signal is triggered, regardless of the CMO value, to ensure a timely exit even if the momentum signal does not reach the predefined level.
This exit strategy aligns with the concept of time-based exits, reducing the risk of prolonged exposure to adverse price movements (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages the well-known phenomenon of mean-reversion in financial markets. According to research by Jegadeesh and Titman (1993), prices tend to revert to their mean over short periods following strong movements, creating opportunities for traders to profit from temporary deviations.
The CMO captures this mean-reversion behavior by monitoring extreme price conditions. When the CMO reaches oversold levels (below -50), it signals potential buying opportunities, whereas crossing overbought levels (above 50) indicates conditions for selling.
Market Efficiency and Overreaction:
The strategy takes advantage of behavioral inefficiencies and overreactions, which are often the drivers behind sharp price movements (Shiller, 2003). By identifying these extreme conditions with the CMO, the strategy aims to capitalize on the market’s tendency to correct itself when price deviations become too large.
Optimization and Parameter Selection:
The 9-day period used for the CMO calculation is a widely accepted timeframe that balances responsiveness and noise reduction, making it suitable for capturing short-term price fluctuations. Studies in technical analysis suggest that oscillators optimized over such periods are effective in detecting reversals (Murphy, 1999).
Performance and Backtesting:
The strategy's effectiveness is confirmed through backtesting, which shows that using the CMO as a mean-reversion tool yields profitable opportunities. The use of time-based exits alongside momentum-based signals enhances the reliability of the strategy by ensuring that trades are closed even when the momentum signal alone does not materialize.
Conclusion:
The Chande Momentum Oscillator Trading Strategy combines the principles of momentum measurement and mean-reversion to identify and capitalize on short-term price fluctuations. By using a widely tested oscillator like the CMO and integrating a systematic exit approach, the strategy effectively addresses both entry and exit conditions, providing a robust method for trading in diverse market environments.
References:
Chande, T. S. (1997). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. John Wiley & Sons.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Ultimate Oscillator Trading StrategyThe Ultimate Oscillator Trading Strategy implemented in Pine Script™ is based on the Ultimate Oscillator (UO), a momentum indicator developed by Larry Williams in 1976. The UO is designed to measure price momentum over multiple timeframes, providing a more comprehensive view of market conditions by considering short-term, medium-term, and long-term trends simultaneously. This strategy applies the UO as a mean-reversion tool, seeking to capitalize on temporary deviations from the mean price level in the asset’s movement (Williams, 1976).
Strategy Overview:
Calculation of the Ultimate Oscillator (UO):
The UO combines price action over three different periods (short-term, medium-term, and long-term) to generate a weighted momentum measure. The default settings used in this strategy are:
Short-term: 6 periods (adjustable between 2 and 10).
Medium-term: 14 periods (adjustable between 6 and 14).
Long-term: 20 periods (adjustable between 10 and 20).
The UO is calculated as a weighted average of buying pressure and true range across these periods. The weights are designed to give more emphasis to short-term momentum, reflecting the short-term mean-reversion behavior observed in financial markets (Murphy, 1999).
Entry Conditions:
A long position is opened when the UO value falls below 30, indicating that the asset is potentially oversold. The value of 30 is a common threshold that suggests the price may have deviated significantly from its mean and could be due for a reversal, consistent with mean-reversion theory (Jegadeesh & Titman, 1993).
Exit Conditions:
The long position is closed when the current close price exceeds the previous day’s high. This rule captures the reversal and price recovery, providing a defined point to take profits.
The use of previous highs as exit points aligns with breakout and momentum strategies, as it indicates sufficient strength for a price recovery (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages two well-established phenomena in financial markets: momentum and mean-reversion. Momentum, identified in earlier studies like those by Jegadeesh and Titman (1993), describes the tendency of assets to continue in their direction of movement over short periods. Mean-reversion, as discussed by Poterba and Summers (1988), indicates that asset prices tend to revert to their mean over time after short-term deviations. This dual approach aims to buy assets when they are temporarily oversold and capitalize on their return to the mean.
Multi-timeframe Analysis:
The UO’s incorporation of multiple timeframes (short, medium, and long) provides a holistic view of momentum, unlike single-period oscillators such as the RSI. By combining data across different timeframes, the UO offers a more robust signal and reduces the risk of false entries often associated with single-period momentum indicators (Murphy, 1999).
Trading and Market Efficiency:
Studies in behavioral finance, such as those by Shiller (2003), show that short-term inefficiencies and behavioral biases can lead to overreactions in the market, resulting in price deviations. This strategy seeks to exploit these temporary inefficiencies, using the UO as a signal to identify potential entry points when the market sentiment may have overly pushed the price away from its average.
Strategy Performance:
Backtests of this strategy show promising results, with profit factors exceeding 2.5 when the default settings are optimized. These results are consistent with other studies on short-term trading strategies that capitalize on mean-reversion patterns (Jegadeesh & Titman, 1993). The use of a dynamic, multi-period indicator like the UO enhances the strategy’s adaptability, making it effective across different market conditions and timeframes.
Conclusion:
The Ultimate Oscillator Trading Strategy effectively combines momentum and mean-reversion principles to trade on temporary market inefficiencies. By utilizing multiple periods in its calculation, the UO provides a more reliable and comprehensive measure of momentum, reducing the likelihood of false signals and increasing the profitability of trades. This aligns with modern financial research, showing that strategies based on mean-reversion and multi-timeframe analysis can be effective in capturing short-term price movements.
References:
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1976). Ultimate Oscillator. Market research and technical trading analysis.
MTF RSI+CMO PROThis RSI+CMO script combines the Relative Strength Index (RSI) and Chande Momentum Oscillator (CMO), providing a powerful tool to help traders analyze price momentum and spot potential turning points in the market. Unlike using RSI alone, the CMO (especially with a 14-period length) moves faster and accentuates price pops and dips in the histogram, making price shifts more apparent.
Indicator Features:
➡️RSI and CMO Combined: This indicator allows traders to track both RSI and CMO values simultaneously, highlighting differences in their movement. RSI and CMO values are both plotted on the histogram, while CMO values are also drawn as a line moving through the histogram, giving a visual representation of their relationship. The often faster-moving CMO accentuates short-term price movements, helping traders spot subtle shifts in momentum that the RSI might smooth out.
➡️Multi-Time Frame Table: A real-time, multi-time frame table displays RSI and CMO values across various timeframes. This gives traders an overview of momentum across different intervals, making it easier to spot trends and divergences across short and long-term time frames.
➡️Momentum Chart Label: A chart label compares the current RSI and CMO values with values from 1 and 2 bars back, providing an additional metric to gauge momentum. This feature allows traders to easily see if momentum is increasing or decreasing in real-time.
➡️RSI/CMO Bullish and Bearish Signals: Colored arrow plot shapes (above the histogram) indicate when RSI and CMO values are signaling bullish or bearish conditions. For example, green arrows appear when RSI is above 65, while purple arrows show when RSI is below 30 and CMO is below -40, indicating strong bearish momentum.
➡️Divergences in Histogram: The histogram can make it easier for traders to spot divergences between price and momentum. For instance, if the price is making new highs but the RSI or CMO is not, a bearish divergence may be forming. Similarly, bullish divergences can be spotted when prices are making lower lows while RSI or CMO is rising.
➡️Alert System: Alerts are built into the indicator and will trigger when specific conditions are met, allowing traders to stay informed of potential entry or exit points based on RSI and CMO levels without constantly monitoring the chart. These are set manually. Look for the 3 dots in the indicator name.
How Traders Can Use the Indicator:
💥Identifying Momentum Shifts: The RSI+CMO combination is ideal for spotting momentum shifts in the market. Traders can monitor the histogram and the CMO line to determine if the market is gaining or losing strength.
💥Confirming Trade Entries/Exits: Use the real-time RSI and CMO values across multiple time frames to confirm trades. For instance, if the 1-hour RSI is above 70 but the 1-minute RSI is turning down, it could indicate short-term overbought conditions, signaling a potential exit or reversal.
💥Spotting Divergences: Divergences are critical for predicting potential reversals. The histogram can be used to spot divergences when RSI and CMO values deviate from price action, offering an early signal of market exhaustion.
💥Tracking Multi-Time Frame Trends: The multi-time frame table provides insight into the market’s overall trend across several timeframes, helping traders ensure their decisions align with both short and long-term trends.
RSI vs. CMO: Why Use Both?
While both RSI and CMO measure momentum, the CMO often moves faster with a value of 14 for example, reacting to price changes more quickly. This makes it particularly effective for detecting sharp price movements, while RSI helps smooth out price action. By using both, traders get a clearer picture of the market's momentum, particularly during volatile periods.
Confluence and Price Fluidity:
One of the powerful ways to enhance the effectiveness of this indicator is by using it in conjunction with other technical analysis tools to create confluence. Confluence occurs when multiple indicators or price action signals align, providing stronger confirmation for a trade decision. For example:
🎯Support and Resistance Levels: Traders can use RSI+CMO in combination with key support and resistance zones. If the price is nearing a support level and RSI+CMO values start to signal a bullish reversal, this alignment strengthens the case for entering a long position.
🎯Moving Averages: When the RSI+CMO signals a potential trend reversal and this is confirmed by a crossover in moving averages (such as a 50-day and 200-day moving average), traders gain additional confidence in the trade direction.
🎯Momentum Indicators: Traders can also look for momentum indicators like the MACD to confirm the strength of a trend or potential reversal. For instance, if the RSI+CMO values start to decrease rapidly while both the RSI+CMO also shows overbought conditions, this could provide stronger confirmation to exit a long trade or enter a short position.
🎯Candlestick Patterns: Price fluidity can be monitored using candlestick formations. For example, a bearish engulfing pattern with decreasing RSI+CMo values offers confluence, adding confidence to the signal to close or short the trade.
By combining the MTF RSI+CMO PRO with other tools, traders ensure that they are not relying on a single indicator. This layered approach can reduce the likelihood of false signals and improve overall trading accuracy.
Abdozo - Highlight First DaysAbdozo - Highlight First Days Indicator
This Pine Script indicator helps traders easily identify key timeframes by highlighting the first trading day of the week and the first day of the month. It provides visual markers directly on your chart, helping you stay aware of potential market trends and turning points.
Features:
- Highlight First Day of the Week (Monday): Automatically marks Mondays to help you track weekly market cycles.
- Highlight First Day of the Month: Spot the start of each month with ease to analyze monthly performance and trends.
Ping Pong Bot StrategyOverview:
The Ping Pong Bot Strategy is designed for traders who focus on scalping and short-term opportunities using support and resistance levels. This strategy identifies potential buy entries when the price reaches a key support area and shows bullish momentum (a green bar). It aims to capitalize on small price movements with predefined risk management and take profit levels, making it suitable for active traders looking to maximize quick trades in trending or ranging markets.
How It Works:
Support & Resistance Calculation:
The strategy dynamically identifies support and resistance levels using the lowest and highest price points over a user-defined period. These levels help pinpoint potential price reversal areas, guiding traders on where to enter or exit trades.
Buy Entry Criteria:
A buy signal is triggered when the closing price is at or below the support level, and the bar is green (i.e., the closing price is higher than the opening price). This ensures that entries are made when prices show signs of upward momentum after hitting support.
Risk Management:
For each trade, a stop loss is calculated based on a user-defined risk percentage, helping to protect against significant drawdowns. Additionally, a take profit level is set at a ratio relative to the risk, ensuring a disciplined approach to exit points.
0.5% Take Profit Target:
The strategy also includes a 0.5% quick take profit target, indicated by an orange arrow when reached. This feature helps traders lock in small gains rapidly, making it ideal for volatile market conditions.
Customizable Inputs:
Length: Adjusts the period for calculating support and resistance levels.
Risk-Reward Ratio: Allows traders to set the desired risk-to-reward ratio for each trade.
Risk Percentage: Defines the risk tolerance for stop loss calculations.
Take Profit Target: Enables the customization of the quick take profit target.
Ideal For:
Traders who prefer an active trading style and want to leverage support and resistance levels for precise entries and exits. This strategy is particularly useful in markets that experience frequent price bounces between support and resistance, allowing traders to "ping pong" between these levels for profitable trades.
Note:
This strategy is developed mainly for the 5-minute chart and has not been tested on longer time frames. Users should perform their own testing and adjustments if using it on different time frames.
NY Open Time Indicator (London Time)The NY Open Time Indicator is designed for traders who want to mark the opening time of the New York Stock Exchange (NYSE) on their charts, specifically for assets traded during the London session. This indicator plots a vertical line at 2:30 PM London time (UTC+1), representing the moment the NYSE opens for trading.
Features:
Time Zone Adjustment: Automatically adjusts to reflect the NY opening time based on London time, accounting for daylight saving changes.
Visual Cue: The vertical line serves as a clear visual marker, helping traders identify potential market movements and volatility around the NY open.
Customizable Appearance: The color and width of the vertical line can be adjusted in the script to fit individual preferences and chart styles.
Simplicity: Easy to implement and understand, making it suitable for both novice and experienced traders.
Use Cases:
Day Trading: Use this indicator to pinpoint significant market entry and exit points around the NY open, which is often a time of increased activity and volatility.
Market Analysis: Combine this indicator with other technical analysis tools to assess potential price movements and trends as the market opens.
Installation: Add this indicator to your TradingView chart and customize it to suit your trading strategy. (Public Code)
TEMA Crosses_AIT with Manual TEMA CalculationTitle: TEMA Crosses_AIT Indicator
Description:
The TEMA Crosses_AIT Indicator is designed for traders looking to leverage the Triple Exponential Moving Average (TEMA) to identify trend reversals and momentum shifts in the market. This indicator calculates both fast and slow TEMA lines and signals potential buy or sell opportunities based on crossovers between these two lines.
Key Features:
Fast TEMA (TEMAF):
Default period: 20 (adjustable)
Represents the short-term trend and reacts quickly to price changes.
Slow TEMA (TEMAS):
Default period: 200 (adjustable)
Represents the long-term trend, smoothing out price fluctuations to give a clearer view of the overall direction.
Signal Generation:
Long Signal: A long (buy) signal is generated when the fast TEMA crosses above the slow TEMA, indicating a potential upward trend.
Short Signal: A short (sell) signal is generated when the fast TEMA crosses below the slow TEMA, indicating a potential downward trend.
Color-coded Visualization:
The fast TEMA line is displayed in green when it is above the slow TEMA (bullish signal) and in red when below (bearish signal).
The slow TEMA line is displayed in white.
A yellow triangle appears below the price bar for long entries.
A fuchsia triangle appears above the price bar for short entries.
How It Works:
The indicator calculates the Triple Exponential Moving Average (TEMA) manually using exponential moving averages (EMA). The TEMA is calculated by subtracting the second EMA from three times the first EMA, then adding the third EMA. This provides a smoother trend line that reacts more quickly than a traditional EMA, making it ideal for spotting trend changes.
Customizable Inputs:
TEMAF Period: Adjust the period of the fast TEMA to fit your trading style.
TEMAS Period: Adjust the period of the slow TEMA to match the time frame you are analyzing.
Use Cases:
Trend Reversals: The crossovers between the fast and slow TEMA provide clear signals for potential trend reversals, which can be used to enter or exit trades.
Momentum Confirmation: The color-coded TEMA lines allow traders to easily identify whether the short-term momentum is aligned with the long-term trend, helping to confirm the strength of a move.
Recommendations:
This indicator works well with other momentum-based tools like RSI or MACD for confirming signals and identifying overbought or oversold conditions. It is suitable for use across different asset classes, including stocks, cryptocurrencies, forex, and commodities.
Disclaimer:
The TEMA Crosses_AIT indicator should not be used as a standalone trading strategy. It is recommended to combine this indicator with other forms of analysis and risk management techniques. Always backtest the indicator on historical data before applying it to live trades.
Liquidity Analysis with Volume, ATR, and Chaikin Oscillator
Script Name: Liquidity Analysis with Volume, ATR, and Chaikin Oscillator
Description: This script analyzes market liquidity using three key indicators: Volume, ATR (Average True Range), and the Chaikin Oscillator. Based on the combination of these indicators, the script identifies three market conditions and visually highlights them with background colors:
High Liquidity Uptrend (Green Background):
Occurs when volume is high, ATR is above the threshold, and the Chaikin Oscillator is positive. This indicates strong liquidity with an upward trend in the market.
Alert: "High Liquidity Uptrend detected."
High Liquidity Downtrend (Red Background):
Occurs when volume is high, ATR is above the threshold, and the Chaikin Oscillator is negative. This signals strong liquidity but with a downward market trend.
Alert: "High Liquidity Downtrend detected."
Low Liquidity Stagnant Market (Yellow Background):
Occurs when volume is low, and ATR is below the threshold. This suggests a market with low liquidity and minimal price movement, indicating a range or stagnant phase.
Alert: "Low Liquidity Stagnant market detected."
Input Settings Panel:
Volume Threshold: This value sets the minimum volume required to determine high liquidity. If the volume is above this value, it is considered "high volume."
ATR Length: Defines the number of periods used to calculate ATR. The higher the value, the more smoothed the ATR calculation.
ATR Threshold: This sets the minimum ATR value required to signal a market with significant volatility. If ATR is above this value, the market is considered to have high volatility.
These settings allow you to fine-tune the script based on the characteristics of the asset being analyzed.
スクリプト名: 出来高、ATR、チャイキンオシレーターを用いた流動性分析
説明: このスクリプトは、出来高、ATR（平均真値幅）、およびチャイキンオシレーターという3つの主要な指標を用いて市場の流動性を分析します。これらの指標の組み合わせに基づいて、3つの市場状況を特定し、背景色で視覚的にハイライトします。
流動性が高い上昇相場（背景色：緑）:
出来高が高く、ATRがしきい値を超え、チャイキンオシレーターがプラスの場合に発生します。これは、強い流動性と市場の上昇トレンドを示します。
アラート: 「高流動性の上昇トレンドが検出されました。」
流動性が高い下降相場（背景色：赤）:
出来高が高く、ATRがしきい値を超え、チャイキンオシレーターがマイナスの場合に発生します。これは、強い流動性を伴う下降トレンドを示します。
アラート: 「高流動性の下降トレンドが検出されました。」
流動性が低い停滞相場（背景色：黄色）:
出来高が低く、ATRがしきい値以下の場合に発生します。これは流動性が低く、価格変動が少ない、レンジまたは停滞フェーズを示しています。
アラート: 「低流動性の停滞相場が検出されました。」
設定パネルの入力項目:
出来高のしきい値: 高流動性を判定するために必要な最小の出来高を設定します。この値を超える場合、「高出来高」と見なされます。
ATRの期間: ATRを計算する際に使用される期間数を定義します。値が大きいほど、ATRの計算が滑らかになります。
ATRのしきい値: しきい値を超えた場合に市場に大きなボラティリティがあると判断します。この値を上回るATRであれば、ボラティリティが高いと見なされます。
これらの設定により、分析対象の資産の特性に応じてスクリプトを調整できます。
NYSE UVOL RatioThis Pine Script is designed to monitor and display the ratio of advancing volume (UVOL) to declining volume (DVOL) on the NYSE in real-time on your TradingView charts. Here's a breakdown of what each part of the script does:
Indicator Declaration: The script starts by declaring an indicator called "NYSE UVOL" with the option to overlay it directly on the price chart. This allows you to see the volume ratio in context with price movements.
Volume Data Fetching:
Advancing Volume (UVOL): It retrieves the closing value of the advancing volume from the NYSE.
Declining Volume (DVOL): It fetches the closing value of the declining volume.
Ratio Calculation:
The script calculates the ratio of advancing to declining volume. To avoid division by zero, it checks if the declining volume is not zero before performing the division.
Color Coding:
The script assigns a color to the ratio value based on set thresholds:
Red for a ratio less than 1 (more declining than advancing volume).
White for ratios between 1 and 2.
Lime for ratios between 2 and 3.
Green for ratios above 3.
Display Table:
A table is created in the top-right corner of the chart to display the current ratio value.
It updates this table with the latest ratio value at each new bar, displaying the ratio with appropriate color coding for quick reference.
This script provides a visual and numerical representation of market sentiment based on volume data, aiding traders in assessing the balance between buying and selling pressure.
Quarterly Highlight ModelDiscover a new edge in your market analysis with our latest TradingView script. Designed to highlight quarterly performance, this tool not only offers insights into individual companies but also serves as a powerful lens to examine broader market trends.
Key Features:
- Quarterly Highlights: Easily identify and analyze each company's performance across four quarters, with each quarter represented by a unique color for clear visual distinction.
- Trend Analysis: Use quarterly data to spot trends and make informed decisions.
Enhance your trading strategy with deeper insights and a comprehensive view of market conditions. Check it out and let’s revolutionize the way we understand the markets!
