Dynamic Stop Loss & Take ProfitDynamic Stop Loss & Take Profit is a versatile risk management indicator that calculates dynamic stop loss and take profit levels based on the Average True Range (ATR). This indicator helps traders set adaptive exit points by using a configurable ATR multiplier and defining whether they are in a Long (Buy) or Short (Sell) trade.
How It Works
ATR Calculation – The indicator calculates the ATR value over a user-defined period (default: 14).
Stop Loss and Take Profit Multipliers – The ATR value is multiplied by a configurable factor (ranging from 1.5 to 4) to determine volatility-adjusted stop loss and take profit levels.
Trade Type Selection – The user can specify whether they are in a Long (Buy) or Short (Sell) trade.
Long (Buy) Trade:
Stop Loss = Entry Price - (ATR × Stop Loss Multiplier)
Take Profit = Entry Price + (ATR × Take Profit Multiplier)
Short (Sell) Trade:
Stop Loss = Entry Price + (ATR × Stop Loss Multiplier)
Take Profit = Entry Price - (ATR × Take Profit Multiplier)
Features
Configurable ATR length and multipliers
Supports both long and short trades
Clearly plotted Stop Loss (red) and Take Profit (green) levels on the chart
Helps traders manage risk dynamically based on market volatility
This indicator is ideal for traders looking to set adaptive stop loss and take profit levels without relying on fixed price targets.
指标和策略
On-chain Zscore | QuantumResearchQuantumResearch On-chain Zscore Indicator
The On-chain Zscore Indicator by QuantumResearch is a cutting-edge tool designed for traders and analysts who leverage on-chain metrics to assess Bitcoin’s market conditions. This indicator calculates a composite Z-score using three key on-chain metrics: NUPL (Net Unrealized Profit/Loss), SOPR (Spent Output Profit Ratio), and MVRV (Market Value to Realized Value). By normalizing these values through standard deviations, the indicator provides a dynamic, data-driven approach to identifying overbought and oversold conditions, improving market timing and decision-making.
1. Overview
This indicator integrates multiple on-chain metrics to:
Assess Market Cycles – Utilize Z-score normalization to detect potential tops and bottoms.
Smooth Volatility – Apply EMA and standard deviation filtering to refine signals.
Identify Buy & Sell Signals – Use adaptive thresholds to highlight market extremes.
Provide Visual Clarity – Color-coded bar signals and background fills for intuitive analysis.
2. How It Works
A. Z-score Calculation
What is a Z-score? – The Z-score measures how far a data point deviates from its historical mean in terms of standard deviations. This helps in identifying statistical extremes.
Zscore(source,mean,std)=>
zscore = (source-mean)/std
zscore
Standard Deviation Normalization – Each on-chain metric (NUPL, SOPR, MVRV) is individually standardized before being combined into a final score.
B. On-Chain Components
NUPL Z-score – Measures unrealized profits and losses relative to market cycles.
SOPR Z-score – Evaluates profit-taking behavior on spent outputs.
MVRV Z-score – Assesses whether Bitcoin is overvalued or undervalued based on market cap vs. realized cap.
C. Composite On-chain Score
The indicator computes an average Z-score of the three on-chain metrics to create a composite market assessment.
Adaptive thresholds (default: 0.73 for bullish signals, -0.44 for bearish signals) dynamically adjust based on market conditions.
3. Visual Representation
This indicator features color-coded elements and dynamic threshold visualization:
Bar Colors
Green Bars – Bullish conditions when Z-score exceeds the upper threshold.
Red Bars – Bearish conditions when Z-score drops below the lower threshold.
Gray Bars – Neutral market conditions.
Threshold Bands & Background Fill
Upper Band (Overbought) – Default threshold set at 0.73.
Middle Band – Neutral zone at 0.
Lower Band (Oversold) – Default threshold set at -0.44.
4. Customization & Parameters
This indicator is highly configurable, allowing traders to fine-tune settings based on their strategy:
On-Chain Z-score Settings
NUPL Z-score Length – Default: 126 periods
SOPR Z-score Length – Default: 111 periods
MVRV Z-score Length – Default: 111 periods
Signal Thresholds
Upper Threshold (Bullish Zone) – Default: 0.73
Lower Threshold (Bearish Zone) – Default: -0.44
Color & Visual Settings
Choose from eight customizable color modes to suit personal preferences.
5. Trading Applications
The On-chain Zscore Indicator is versatile and can be applied in various market scenarios:
Macro Trend Analysis – Identify long-term market tops and bottoms using normalized on-chain metrics.
Momentum Confirmation – Validate price action trends with SOPR & MVRV behavior.
Market Timing – Use deviation thresholds to enter at historically significant price zones.
Risk Management – Avoid overextended markets by watching for extreme Z-score readings.
6. Final Thoughts
The QuantumResearch On-chain Zscore Indicator provides a unique approach to market evaluation by combining three critical on-chain metrics into a single, normalized score.
By standardizing Bitcoin’s market behavior, this tool helps traders and investors make informed decisions based on historical statistical extremes.
Backtesting and validation are essential before using this indicator in live trading. While it enhances market analysis, it should be used alongside other tools and strategies.
Disclaimer: No indicator can guarantee future performance. Always use appropriate risk management and perform due diligence before trading.
Combo Gama Exposure + EMA + SMA 1.0Gamma Exposure (GEX) for the CBOE Volatility Index ( TVC:VIX ) is an estimate of how much option sellers need to hedge for every 1% change in the underlying asset's price. It's also known as Gamma Levels.
How is GEX calculated?
GEX is calculated based on a 1% move of the underlying security
It's calculated and updated throughout the day
It's based on market positioning and open interest
These regions are important because they show the regions where players can act more aggressively to defend their positions. When inserting the indicator on the chart, a popup will open requesting the GEX levels (Put wall, Vix Call Wall 0DTE, etc.)
In addition, 3 moving averages will be inserted into the chart. A 9-period exponential moving average, a 20-period arithmetic moving average, and a 200-period arithmetic moving average. These moving averages aim to indicate the possible trend of the asset, where pullbacks in these averages can signal a possible entry in favor of the trend.
NFP High/Low LevelsThis indicator plots high and low levels with horizontal lines for the last 12 NFP Days
NFP Days are input in the indicator settings
Labels are placed according to the Month and if it is a High or Low price for the NFP Day
Price tracking on each NFP day starts 30 min before market open until market close (0830-1559 EST)
NFP hours are marked at the bottom of the chart to verify the NFP session visually, adjustable in settings
Works for 1H and below timeframes and on Futures
Here is an example of the indicator on NQ1! chart
Stochastic-Dynamic Volatility Band ModelThe Stochastic-Dynamic Volatility Band Model is a quantitative trading approach that leverages statistical principles to model market volatility and generate buy and sell signals. The strategy is grounded in the concepts of volatility estimation and dynamic market regimes, where the core idea is to capture price fluctuations through stochastic models and trade around volatility bands.
Volatility Estimation and Band Construction
The volatility bands are constructed using a combination of historical price data and statistical measures, primarily the standard deviation (σ) of price returns, which quantifies the degree of variation in price movements over a specific period. This methodology is based on the classical works of Black-Scholes (1973), which laid the foundation for using volatility as a core component in financial models. Volatility is a crucial determinant of asset pricing and risk, and it plays a pivotal role in this strategy's design.
Entry and Exit Conditions
The entry conditions are based on the price’s relationship with the volatility bands. A long entry is triggered when the price crosses above the lower volatility band, indicating that the market may have been oversold or is experiencing a reversal to the upside. Conversely, a short entry is triggered when the price crosses below the upper volatility band, suggesting overbought conditions or a potential market downturn.
These entry signals are consistent with the mean reversion theory, which asserts that asset prices tend to revert to their long-term average after deviating from it. According to Poterba and Summers (1988), mean reversion occurs due to overreaction to news or temporary disturbances, leading to price corrections.
The exit condition is based on the number of bars that have elapsed since the entry signal. Specifically, positions are closed after a predefined number of bars, typically set to seven bars, reflecting a short-term trading horizon. This exit mechanism is in line with short-term momentum trading strategies discussed in literature, where traders capitalize on price movements within specific timeframes (Jegadeesh & Titman, 1993).
Market Adaptability
One of the key features of this strategy is its dynamic nature, as it adapts to the changing volatility environment. The volatility bands automatically adjust to market conditions, expanding in periods of high volatility and contracting when volatility decreases. This dynamic adjustment helps the strategy remain robust across different market regimes, as it is capable of identifying both trend-following and mean-reverting opportunities.
This dynamic adaptability is supported by the adaptive market hypothesis (Lo, 2004), which posits that market participants evolve their strategies in response to changing market conditions, akin to the adaptive nature of biological systems.
References:
Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
Bollinger, J. (1980). Bollinger on Bollinger Bands. Wiley.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 30(5), 15-29.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Moneyball EMA-MACD indicator [VinnieTheFish]Summary of the Moneyball EMA-MACD Indicator Script
Author: VinnieTheFish
Purpose:
This indicator helps traders identify trend direction, momentum shifts, and potential trade signals based on EMA and MACD crossovers.
This Pine Script is a custom indicator that combines Exponential Moving Averages (EMAs) and MACD (Moving Average Convergence Divergence) to analyze price trends and momentum. The script uses a custom 9/50 MACD with a 16 smoothing period. The script is written in a way that you can create your own custom MACD settings and create alerts based on those parameters. The chart bars are color coded based on the relative position of the MACD and Signal line primarily for bullish long trade setups.
Bar color coding helps the trader spot potential reversals based on where the price currently resides in relation to the custom 9/50 EMA based MACD and the 16 period smoothing period for the signal line. Indicator also has custom alerts to notify the trader when a potential trade setup exists that correspond with the bar color change.
Question: So why is this called the Moneywell EMA-MACD Indicator?
Answer: In the movie Moneyball the Oakland A's broke down how to win a championship based on data. To make the playoffs you needed so many wins, then broken down by runs and then broken down to base hits. A base hit was good as a walk. With trading often times we look too often for home runs and ignore the importance of getting on base with small wins. This indicator was designed on shorter timeframes to identify those base hits, but can also be adapted to higher timeframes for swing trading.
Key Features:
User Inputs:
Configurable fast and slow lengths for MACD calculation.
Choice between SMA and EMA for oscillator and signal line smoothing.
Customizable signal smoothing length.
EMA Calculation:
Computes 3 EMA, 9 EMA, 20 EMA, and 50 EMA to track short-term and long-term trends.
MACD Calculation:
Computes MACD using either SMA or EMA based on user selection.
Generates the MACD signal line for comparison.
Crossover Conditions:
Detects MACD and Signal line crossovers above and below the zero line.
Identifies price momentum shifts.
Bar Coloring Logic:
Green: MACD is above 0 and above the signal line.
White: MACD is below the signal line.
Orange: MACD is below 0 but above the signal line.
Fuchsia: Bullish EMA 3/9 cross but price is still below the 20/50 EMA.
Alerts for Key Trading Signals:
MACD crossing above/below the zero line.
Signal line crossing above/below the zero line.
MACD reaching new highs/lows.
Alerts for colored bar conditions.
dmarcLevelParserLibrary "dmarcLevelParser"
Provides a parsing library that indicator authors can use in order to parse dmarcLevels.
parseLevels(s)
Parses the string content and returns the `dmarcLevels` found within.
Parameters:
s (string) : The string to parse.
Returns: The parsed dmarc levels.
zoneRange
Fields:
high (series float)
low (series float)
wtdLevels
Fields:
lvnLines (array)
lvnZones (array)
supplyLines (array)
supplyZones (array)
vses (array)
vahs (array)
vals (array)
pocs (array)
miscZones (array)
miscLines (array)
fbos (array)
fbds (array)
majorLevels (array)
mansupLines (array)
mansupmajLines (array)
mansupZones (array)
mansupmajZones (array)
manresLines (array)
manresmajLines (array)
manresZones (array)
manresmajZones (array)
Candlestick Color Change AlertIt is an alert for change of candlestick color.
Identifies Candle Type
A candle is bullish if the closing price is higher than the opening price.
A candle is bearish if the closing price is lower than the opening price.
Detects a Color Change
The script checks if the current candle is bullish while the previous candle was bearish, or vice versa.
If a change is detected, an alert is triggered.
Triggers an Alert
Users receive an alert notification whenever a candlestick color change occurs.
Alerts can be set for popup, email, mobile push, or webhook notifications.
Visual Highlighting (Optional)
The script can also apply a background color (blue) on the chart to visually mark color changes.
Daily Open @Alpha PipsOverview
The Daily Open @Alpha Pips indicator displays the daily opening price as a reference line on the chart. This level is widely used by traders to gauge market sentiment, potential support/resistance zones, and price reactions throughout the trading session.
How It Works
The line color is red with a 30% transparency level, ensuring visibility without overwhelming the chart.
The line width is set to 2 for clear visualization.
Use Cases
Identify potential intraday support/resistance at the daily open.
Observe price reactions around the daily open level to refine entries and exits.
Use in conjunction with price action, order flow, or smart money concepts for enhanced decision-making.
Additional Information
Works on any timeframe but is best suited for intraday trading strategies.
The script is fully transparent, ensuring traders can easily understand its function.
It does not repaint, providing reliable and stable levels throughout the session.
Advanced Supertrend Enhanced ADXEnhanced Supertrend ADX Indicator - Technical Documentation
Overview
The Enhanced Supertrend ADX indicator combines ADX directional strength with Supertrend trend-following capabilities, creating a comprehensive trend detection system. It's enhanced with normalization techniques and multiple filters to provide reliable trading signals.
Key Features and Components
The indicator incorporates three main components:
Core ADX and Supertrend Fusion
Uses a shorter ADX period for increased sensitivity
Integrates Supertrend signals for trend confirmation
Applies a long-term moving average for trend context
Advanced Filtering System
Volatility filter: Identifies periods of significant market movement
Momentum filter: Confirms the strength and sustainability of trends
Lateral market detection: Identifies ranging market conditions
Data Normalization
Standardizes indicator readings across different instruments
Makes signals comparable across various market conditions
Reduces extreme values and false signals
Model Assumptions
The indicator operates under several key assumptions:
Market Behavior
Markets alternate between trending and lateral phases
Strong trends correlate with increased volatility
Price momentum confirms trend strength
Market transitions follow identifiable patterns
Signal Reliability
Low ADX values indicate lateral markets
Valid signals require both volatility and momentum confirmation
Multi-filter confirmation increases signal reliability
Price normalization enhances signal quality
Trading Applications
The indicator supports different trading approaches:
Trend Trading
Strong signals when all filters align
Clear distinction between bullish and bearish trends
Momentum confirmation for trend continuation
Range Trading
Clear identification of lateral markets
Band-based trading boundaries
Reduced false breakout signals
Transition Trading
Early identification of trend-to-range transitions
Clear signals for range-to-trend transitions
Momentum-based confirmation of breakouts
Risk Considerations
Important factors to consider:
Signal Limitations
Potential delay in fast-moving markets
False signals during extreme volatility
Time frame dependency
Best Practices
Use in conjunction with other indicators
Apply proper position sizing
Focus on liquid instruments
Consider market context
Performance Characteristics
The indicator shows optimal performance under specific conditions:
Ideal Conditions
Daily timeframe analysis
Clear trending market phases
Liquid market environments
Normal volatility conditions
Challenging Conditions
Choppy market conditions
Extremely low volatility
Highly volatile markets
Illiquid instruments
Implementation Recommendations
For optimal use, consider:
Market Selection
Best suited for major markets
Requires adequate liquidity
Works well with trending instruments
Timeframe Selection
Primary: Daily charts
Secondary: 4-hour charts
Caution on lower timeframes
Risk Management
Use appropriate position sizing
Set clear stop-loss levels
Consider market volatility
Monitor overall exposure
This indicator serves as a comprehensive tool for market analysis, combining traditional technical analysis with modern filtering techniques. Its effectiveness depends on proper implementation and understanding of market conditions.
Adaptive Supply and Demand [EdgeTerminal]Adaptive Supply and Demand is a dynamic supply and demand indicator with a few unique twists. It considers volume pressure, volatility-based adjustments and multi-time frame momentum for confidence scoring (multi-step confirmation) to generate dynamic lines that adjust based on the market and also to generate dynamic support/resistance levels for the supply and demand lines.
The dynamic support and resistance lines shown gives you a better situational awareness of the current state of the market and add more context to why the market is moving into a certain direction.
> Trading Scenarios
When the confidence score is over 80%, strong volume pressure in trend direction (up or down), volatility is low and momentum is aligned across timeframes, there is an indication of a strong upward or downward trend.
When the supply and demand line crossover, the confidence score is over 75% and the volume pressure is shifting, this can be an indicator of trend reversal. Use tight initial stops, scale into position as trend develops, monitor the volume pressure for continuation and wait for confidence confirmation.
When the confiance score is below 60%, the volume pressure is choppy, volatility is high, you want to avoid trading or reduce position size, wait for confidence improvements, use support and resistance for entries/exits and use tighter stops due to market conditions. This is an indication of a ranging market.
Another scenario is when there is a sudden volume pressure increase, and a raising confidence score, the volatility is expanding and the bar momentum is aligning the volatility direction. This can indicate a breakout scenario.
> How it Works
1. Volume Pressure Analysis
Volume Pressure Analysis is a key component that measures the true buying and selling force in the market. Here's a detailed breakdown. The idea is to standardize volume to prevent large spikes from skewing results.
The indicator employs an adaptive volume normalization technique to detect genuine buying and selling pressure.
It takes current volume and divides it by average volume.
If normVol > 1: Current volume is above average
If normVol < 1: Current volume is below average
An example if this would be If current volume is 1500 and average is 1000, normVol = 1.5 (50% above average)
Another component of the volume pressure analysis is the Price Change Calculation sub-module. The purpose of this is to measure price movement relative to recent average.
It works by subtracting the average price from the current price. If the value is positive, price is average and if negative, price is below average.
Finally, the volume pressure is calculated to combine volume and price for true pressure reading.
2. Savitzky-Golay Filtering
SG filtering implements advanced signal smoothing while preserving important trend features. It uses weighted moving average approximation, preserves higher moments of data and reduces noise while maintaining signal integrity.
This results in smoother signal lines, reduced false crossovers and better trend identification. Traditional moving averages tend to lag and smooth out important features. Additionally, simple moving averages can miss critical turning points and regular smoothing can delay signal generation.
SG filtering preserves higher moments such as peaks, valleys and trends, reduces noise while maintaining signal sharpness.
It works by creating a symmetric weighting scheme. This way center points get the highest weights while edge points get the lowest weight.
3. Parkinson's Volatility
Parkinson's Volatility is an advanced volatility measurement formula using high-low range data. It uses high-low range for volatility calculation, incorporates logarithmic returns and annualized the volatility measure.
This results in more accurate volatility measurement, better risk assessment and dynamic signal sensitivity.
4. Multi-timeframe Momentum
This combines signals from each module for each timeframe to calculate momentum across three timeframes. It also applies weighted importance to each timeframe and generates a composite momentum signal.
This results in a more comprehensive trend analysis, reduced timeframe bias and better trend confirmation.
> Indicator Settings
Short-term Period:
Lower values makes it more sensitive, meaning it will generate more signals. Higher values makes it less sensitive, resulting in fewer signals. We recommend a 5 to 15 range for day trading, and 10 to 20 for swing trading
Medium-term Period:
Lower values result in faster trend confirmation and higher values show slower and more reliable confirmation. We recommend a range of 15-25 for day trading and 20-30 for swing trading.
Long-term Period:
Lower values makes it more responsive to trend changes and higher values are better for major trend identification. We recommend a range of 40-60 for day trading and 50-100 for swing trading.
Volume Analysis Window:
Lower values result in more sensitivity to volume changes and higher values result in smoother volume analysis. The optimal range is 15-25 for most trading styles.
Confidence Threshold:
Lower values generate more signals but quality decreases. Higher values generate fewer signals but accuracy increases.The optimal range is 0.65-0.8 for most trading conditions.
Multi-Asset Ratio (20 vs 5) - LuchapThis indicator calculates and displays the ratio between the sum of the prices of several base assets and the sum of the prices of several quote assets. You can select up to 20 base assets and 5 quote assets, and enable or disable each asset individually to refine your analysis. This ratio allows you to quickly evaluate the relative performance of different groups of assets.
SL Hunting Detector📌 Step 1: Identify Liquidity Zones
The script plots high-liquidity zones (red) and low-liquidity zones (green).
These are areas where big players target stop-losses before reversing the price.
Example:
If price is near a red liquidity zone, expect a potential stop-loss hunt & reversal downward.
If price is near a green liquidity zone, expect a potential stop-loss hunt & reversal upward.
📌 Step 2: Watch for Stop-Loss Hunts (Fakeouts)
The indicator marks stop-loss hunts with red (bearish) or green (bullish) arrows.
When do stop-loss hunts occur?
✅ A long wick below support (with high volume) = Stop hunt before reversal upward.
✅ A long wick above resistance (with high volume) = Stop hunt before reversal downward.
Confirmation:
Volume must spike (volume > 1.5x the average volume).
ATR-based wicks must be longer than usual (showing a stop-hunt trap).
📌 Step 3: Enter a Trade After a Stop-Hunt
🔹 Bullish Trade (Buying a Dip)
If a green arrow appears (stop-hunt below support):
✅ Enter a long (buy) trade at or just above the wick’s recovery level.
✅ Stop-loss: Below the wick’s low (avoid getting hunted again).
✅ Take-profit: Next resistance level or mid-range of the liquidity zone.
🔹 Bearish Trade (Shorting a Fakeout)
If a red arrow appears (stop-hunt above resistance):
✅ Enter a short (sell) trade at or just below the wick’s rejection level.
✅ Stop-loss: Above the wick’s high (avoid getting stopped out).
✅ Take-profit: Next support level or mid-range of the liquidity zone.
📌 Step 4: Set Alerts & Automate
✅ The indicator triggers alerts when a stop-hunt is detected.
✅ You can set TradingView to notify you instantly when:
A bullish stop-hunt occurs → Look for long entry.
A bearish stop-hunt occurs → Look for short entry.
📌 Example Trade Setup
Example (BTC Long Trade on Stop-Hunt)
BTC is near $40,000 support (green liquidity zone).
A long wick drops to $39,800 with a green arrow (bullish stop-hunt signal).
Volume spikes, and price recovers quickly back above $40,000.
Trade entry: Buy at $40,050.
Stop-loss: Below wick ($39,700).
Take-profit: $41,500 (next resistance).
Result: BTC pumps, stop-loss remains safe, and trade profits.
🔥 Final Tips
Always wait for confirmation (don’t enter blindly on signals).
Use higher timeframes (15m, 1H, 4H) for better accuracy.
Combine with Order Flow tools (like Bookmap) to see real liquidity zones.
🚀 Now try it on TradingView! Let me know if you need adjustments. 📈🔥
Reversal Probability Zone & Levels [LuxAlgo]The Reversal Probability Zone & Levels tool allows traders to identify a zone starting from the last detected reversal to highlight the probability of where the next reversal would be from a price and time perspective.
Price and time levels within the zone are displayed for up to 4 percentiles defined by the user.
🔶 USAGE
By default, the tool displays a zone with the 25th, 50th, 75th and 90th percentiles on both the price and time axis, indicating where, when and how many of the past reversals have occurred.
Traders can select the length for swing detection and the maximum number of reversals for probability calculations. The tool considers both bullish and bearish reversals separately, which means that if the last reversal was a swing high, the zone would show the probabilities for the last defined Maximum reversals
The Maximum reversals value has a direct impact on the probabilities, the more data traders use the more significant the result, probabilities over 10 occurrences are far weak compared to probabilities over 1000 occurrences.
🔹 Percentiles
Traders can fine-tune the percentile parameters in the settings panel.
A given percentile means that the number of occurrences in the data set is less than or equal to the percentile.
In English, this means
Percentile 20th: 20% of the occurrences are less than or equal to this value, so 80% of the occurrences are greater than this value.
Percentile 50th: 50% of the occurrences are below and 50% are above this value.
Percentile 80th: 80% of occurrences are lower than or equal to this value, so 20% of occurrences are greater than this value.
🔹 Normalize data
The Normalize Data feature allows traders to make an apples to apples comparison when we have a lot of historical data on high timeframe charts, using returns between swings instead of raw price.
🔹 Display Style
By default, the tool has the No overlapping feature enabled to display a clean chart, traders can turn it off, but this can fill the chart with too much information and barely see the price.
Traders can enable/disable settings to show only the last zone and the swing markers on the chart.
🔶 SETTINGS
Swing Length: The maximum length in bars used to identify a swing
Maximum Reversals: Maximum number of reversals included in calculations
Normalize Data: Use returns between swings instead of raw price
Percentiles: Enable/disable each of the four percentiles and select the percentile number, line style, colors, and size
🔹 Style
No Overlapping Zones: Enable or disable the No overlap between zones feature
Show Only Last Zone: Enable/disable display of last zone only
Show Marks: Enable/disable reversal markers
SNR Quarter Pointsfor btmm swingers
this is qp /quater point find in trading view
Here's a description for your TradingView Pine Script indicator:
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**Support & Resistance (SNR) Lines Indicator**
This TradingView indicator automatically draws Support and Resistance (SNR) lines on the chart at every 250-pip level, starting from 0.0000. The indicator aims to help traders identify key price levels where the market is likely to experience reversal or consolidation. By plotting lines at regular intervals, the script provides a clear visual representation of potential support and resistance zones, aiding traders in making more informed trading decisions. The levels are dynamically adjusted based on market price movement, ensuring they stay relevant for active trading.
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Let me know if you’d like to tweak it further!
Global Liquidity IndexThis custom indicator provides a composite measure of global liquidity by combining key central bank balance sheet data with additional liquidity proxies. The script aggregates asset data from major economies—including the United States, Japan, China, and the Eurozone—converting non-USD values into U.S. dollars using real-time exchange rates. It then subtracts selected liability measures (such as reverse repurchase agreements and other adjustments) to approximate net central bank liquidity.
Key features include:
• Multi-Regional Coverage:
Incorporates data from the U.S. Federal Reserve, Bank of Japan, Chinese central bank proxies, and the European Central Bank, allowing you to gauge liquidity across major global markets.
• Dynamic Currency Conversion:
Uses live exchange rates (JPY/USD, CNY/USD, EUR/USD) to ensure that all regional figures are consistently expressed in U.S. dollars.
• Customizable Weighting:
Assign adjustable weights to each region’s data, so you can reflect economic size or your own view of their relative importance.
• Additional Liquidity Proxies:
Optionally integrates measures for global money supply and global credit/repo activity (or other proxies of your choice) with user-defined scaling factors.
• User-Friendly Configuration:
All key parameters—including weights and scaling factors—are available as inputs, making the indicator flexible and easy to tailor to your analysis needs.
This indicator is designed for traders and analysts seeking a broad view of global monetary conditions. Whether you’re tracking shifts in central bank policies or assessing global market liquidity, the Global Liquidity Index provides an insightful, customizable tool to help you visualize and interpret liquidity trends over time.
Pure Price Action Breakout with 1:5 RR
Description of the Price Action Trading Script (Pine Script v6)
Overview
This script is a pure price action-based breakout strategy designed for TradingView. It identifies key breakout levels and executes long and short trades based on market structure. The strategy ensures a minimum risk-to-reward ratio (RR) of 1:5, aiming for high profitability with well-defined stop-loss and take-profit levels.
How the Script Works
1️⃣ Breakout Identification
The script uses a lookback period to find the highest high and lowest low over the last n bars.
A bullish breakout occurs when the price closes above the previous highest high.
A bearish breakout happens when the price closes below the previous lowest low.
2️⃣ Entry & Exit Strategy
Long Entry: If a bullish breakout is detected, the script enters a long position.
Short Entry: If a bearish breakout is detected, the script enters a short position.
The stop-loss is placed at the recent swing low (for long trades) or recent swing high (for short trades).
The target price is calculated based on a risk-to-reward ratio of 1:5, ensuring profitable trades.
3️⃣ Risk Management
The stop-loss prevents excessive losses by exiting trades when the market moves unfavorably.
The strategy ensures that each trade has a reward potential at least 5 times the risk.
Positions are executed based on price action only, without indicators like moving averages or RSI.
4️⃣ Visual Representation
The script plots breakout levels to help traders visualize potential trade setups.
Entry points, stop-loss, and take-profit levels are labeled on the chart for easy tracking.
Key Features & Benefits
✔ Pure Price Action – No lagging indicators, only real-time price movements.
✔ High Risk-to-Reward Ratio (1:5) – Ensures high-profit potential trades.
✔ Real-time Entry & Exit Signals – Provides accurate trade setups.
✔ Dynamic Stop-loss Calculation – Adjusts based on recent market structure.
✔ Customizable Parameters – Lookback periods and risk ratios can be modified.
Emotion Line with Volume Confirmation by langshenHow to Use It?
Add the Indicator:
Copy the code into TradingView's Pine Script editor.
Save and add the indicator to your chart.
Understand the Lines:
Emotion Line (Green): Represents the current market sentiment.
MA Emotion Line (Red): A smoothed version of the Emotion Line.
Horizontal Lines:
20% (Gray): Indicates potential positive sentiment (Attention Zone).
40% (Orange): Suggests strong market sentiment (Entry Zone).
80% (Red): Signals overly optimistic sentiment (Reduce Position Zone).
Interpret the Signals:
When the Emotion Line crosses above 20%, it may indicate a positive shift in sentiment.
When the Emotion Line crosses above 40%, it suggests a strong market sentiment, which could be a potential entry point.
When the Emotion Line crosses above 80%, it may indicate an overbought market, signaling a potential reduction in positions.
When the Emotion Line crosses below the MA Emotion Line, it may indicate a weakening sentiment, signaling an exit.
Customize the Inputs:
N Period: Adjust the period for calculating the Emotion Line (default is 7).
MA Period: Adjust the period for the moving average of the Emotion Line (default is 6).
Logic Explanation
Ray Calculation:
The Ray is a smoothed price value calculated as the simple moving average (SMA) of (2 * close + high + low) / 4.
Close Line (CL):
The CL is derived from the Ray and represents the core price trend.
Directional Change (DlR1):
Measures the absolute difference between the current CL and its value two bars ago (CL ).
Volume in Range (VlR1):
Sums the absolute differences between the current CL and its previous value (CL ) over a specified period.
Efficiency Ratio (ER1):
Calculates the ratio of directional change (DlR1) to volume in range (VlR1), representing the efficiency of price movement.
Cumulative Strength (CS1):
Simplified as the efficiency ratio (ER1).
Cumulative Quotient (CQ1):
Squares the cumulative strength (CS1) to amplify its effect.
Adjusted Moving Average (AMA5):
A dynamic moving average that adjusts based on the CQ1 value, simulating a responsive trend line.
Cost (7-day SMA of AMA5):
The 7-period SMA of the AMA5.
Composite Line (CLX):
The average of AMA5 and Cost.
Emotion Line:
Calculated as the percentage of days where the CLX is higher than its previous value over the last N periods.
MA Emotion Line:
The moving average of the Emotion Line, smoothing out its fluctuations.
Key Features
Trend Identification: Helps identify shifts in market sentiment.
Customizable Periods: Adjust N and M to fit your trading style.
Visual Cues: Horizontal lines provide clear levels for attention, entry, and reduce position signals.
Best Practices
Use this indicator in conjunction with other tools (e.g., RSI, MACD) for confirmation.
Adjust the N and M periods based on your trading timeframe (e.g., shorter periods for scalping, longer periods for swing trading).
Combine the indicator with volume analysis to confirm signals.
This indicator is designed to be simple yet powerful, providing clear insights into market sentiment while adhering to TradingView's coding standards.
Blackflag FTS (1H Trailing) + MSB-OB FibThis indicator combines a 1-hour trailing stop system with multi-timeframe Fibonacci retracement levels and ZigZag structure detection to assist traders in identifying trend direction and potential reversal zones.
Features:
✅ 1-Hour Trailing Stop: Uses an ATR-based trailing stop mechanism to track trend direction and dynamic support/resistance.
✅ Multi-Timeframe Approach: The trailing stop is calculated on the 1-hour timeframe, while the ZigZag and Fibonacci retracement levels are based on the 15-minute chart.
✅ ZigZag Structure Detection: Helps filter market swings and trend reversals dynamically.
✅ Fibonacci Levels (0.5 & 0.786): Key retracement levels to watch for price reactions.
✅ Alerts for Key Levels: Get notified when the price crosses important levels (1H trailing stop, Fib 0.5, Fib 0.786).
How It Works:
The trailing stop adapts dynamically based on ATR values and determines trend direction.
ZigZag detection filters out minor price movements to highlight major swing points.
Fibonacci levels are calculated based on ZigZag swings, helping traders spot potential reversal zones.
This tool is useful for trend-following traders, breakout traders, and Fibonacci-based strategies.
Let me know if you'd like any modifications! 🚀
Opening Range, Initial Balance, Opening Price, Pre-market Levels### Description of the Indicator: **Opening Range, Initial Balance, Opening Price, Pre-market Levels**
This custom TradingView indicator provides a comprehensive view of key price levels for intraday trading, specifically designed to track important levels from the Opening Range (OR), Initial Balance (IB), Opening Price (OP), and Pre-market session (PM). These levels are essential for traders to gauge potential market movements and identify critical areas of support and resistance.
#### **Features:**
1. **Opening Range (OR):**
- This is the high and low of the first 30 minutes of the regular market session (09:30 - 10:00 EST).
- The OR high and low act as significant levels that may influence price movement for the rest of the day.
- The mid-level of the Opening Range (OR Mid) is also plotted to give a more detailed view of potential price action.
2. **Initial Balance (IB):**
- The Initial Balance is the range created during the first hour of market activity (09:30 - 10:30 EST).
- This range often sets the tone for the market's direction. The IB high and low, along with the IB midline, are plotted for quick reference.
3. **Opening Price (OP):**
- The opening price of the market is marked as a circle and labeled "OP."
- This level provides context for market sentiment when compared to the high and low levels.
4. **Pre-market Levels (PM):**
- The pre-market session (04:00 - 09:30 EST) has its own important levels that are calculated for the high, low, and mid range (PM High, PM Low, and PM Mid).
- These levels are plotted and are useful for traders to understand where the market stood before the regular session opened.
#### **Customization Options:**
- **Exchange Timezone:** You can choose whether to display the times in the exchange's local timezone or in your own preferred timezone.
- **Mid Levels Display:** You can toggle whether the mid levels for each range (OR, IB, PM) should be shown on the chart.
- **Level Color Change:** The colors of the plotted levels (high, low, mid) change based on whether the price is above or below the respective level, making it easy to visualize potential support and resistance.
- **Label Positions:** The position of the labels (OR, IB, OP, PM) on the chart can be customized to avoid overlap with other data points.
#### **Key Use Cases:**
- **Intraday Trend Analysis:** Use the OR and IB to identify key levels for the day, providing insights into the possible trend or range for the day.
- **Pre-market Insights:** The PM levels are crucial for understanding where the market stood during the pre-market hours and can be used as reference points during the regular session.
- **Potential Support and Resistance:** The high and low levels of the OR, IB, and PM sessions can act as potential support or resistance, which are useful for setting stop-loss and take-profit levels.
#### **How to Use:**
- Pay attention to the levels provided for OR, IB, and PM as potential entry and exit points.
- Watch for breakouts or reversals around these levels, especially when combined with other technical indicators or price action patterns.
- The mid levels offer an additional reference to assess price direction or identify possible areas of consolidation.
This indicator is perfect for day traders who rely on key intraday levels and pre-market activity to make informed trading decisions. It helps to streamline the process of identifying potential breakouts, reversals, and ranges in the market.
Momentum Edge Strategy - 1D BTC OptimizedMomentum Edge Strategy - 1D BTC Optimized
Description
The Momentum Edge Strategy - 1D BTC Optimized is a trend-following and momentum-based trading strategy specifically designed and optimized for Bitcoin (BTC) on the Daily (1D) timeframe. This strategy leverages a confluence of proven technical indicators, including the Ichimoku Cloud, MACD Histogram, and Bollinger Band Width, to identify high-probability trading opportunities in trending markets.
By incorporating multi-timeframe analysis (Weekly trend confirmation) and adaptive risk management using ATR-based stop-loss levels, this strategy ensures robust performance with minimal drawdowns. It is ideal for swing traders looking to capture significant price movements while maintaining strong capital preservation.
Key Features
Trend Detection with Ichimoku Cloud:
Determines whether the market is trending bullish or bearish by analyzing price action relative to the Ichimoku Cloud.
Momentum Confirmation with MACD Histogram:
Confirms trade entries by analyzing bullish or bearish momentum using the MACD histogram.
Volatility Filtering with Bollinger Band Width:
Ensures trades are only executed in sufficiently volatile markets, reducing false signals in low-volatility conditions.
Multi-Timeframe Trend Confirmation:
Aligns entries on the Daily (1D) chart with the broader Weekly (1W) trend for enhanced signal reliability.
Dynamic Risk Management:
Uses ATR-based stop-loss levels that adapt to market volatility, ensuring tight risk control while allowing trades to breathe.
Strong Backtesting Results:
Optimized for Bitcoin on the Daily timeframe, achieving:
Net Profit: +10.80%.
Profit Factor: 2.593.
Percent Profitable: 50.70%.
Max Drawdown: -1.47%.
How It Works
Long Entry Conditions:
Price is above the Ichimoku Cloud.
MACD histogram is greater than -0.05.
Weekly trend confirmation (price above 50-period SMA on Weekly chart).
Bollinger Band Width exceeds the threshold (> 0.02).
Short Entry Conditions:
Price is below the Ichimoku Cloud.
MACD histogram is less than 0.
Weekly trend confirmation indicates bearish conditions (price below 50-period SMA on Weekly chart).
Bollinger Band Width exceeds the threshold (> 0.02).
Stop-Loss Logic:
Stop-loss levels are dynamically adjusted based on ATR and Bollinger Band Width:
In low-volatility conditions, stop-loss is set at recent highs/lows.
In high-volatility conditions, stop-loss is set using ATR multipliers.
Recommended Timeframe and Asset
Optimized for Bitcoin (BTC) on the Daily (1D) timeframe.
While designed for BTC, it may also perform well on other cryptocurrencies with similar trend-driven characteristics after proper backtesting and optimization.
Disclaimers
Not Financial Advice:
This script is provided for educational purposes only and should not be considered financial or investment advice. Always consult a qualified financial advisor before making trading decisions.
Use at Your Own Risk:
Trading involves significant risk, including the potential loss of all invested capital. Past performance is not indicative of future results.
Backtesting Limitations:
Backtesting results are based on historical data and do not account for slippage, spreads, or execution delays in live trading environments.
Timeframe-Specific Optimization:
This strategy has been specifically optimized for Bitcoin on the Daily timeframe. Performance may vary significantly on other assets or timeframes.
User Responsibility:
Users are encouraged to backtest and optimize this strategy for their specific use case before deploying it in live trading.
Users can adjust key parameters such as:
1. ATR Length (`atrLength`) and Multiplier (`atrMultiplier`) to fine-tune risk management.
2. Bollinger Band Width Threshold (`bbWidthThreshold`) to adapt volatility filtering to different assets or market conditions.
Final Thoughts
The Momentum Edge Strategy - 1D BTC Optimized has demonstrated elite-level performance metrics during backtesting on Bitcoin on the 1D timeframe. But backtesting doesn't tell the future, so study how it works, use at your own risk and enjoyment, and let me know any recommendations.
Refined Ichimoku with MACD and RSI Strategy - HTF OptimizedIndicator Summary: Refined Ichimoku with MACD and RSI Strategy
Philosophy and Approach
The "Refined Ichimoku with MACD and RSI Strategy" is designed as a hybrid trend-following and range-bound trading strategy. It leverages the Ichimoku Cloud for market regime detection, MACD for momentum confirmation, RSI for overbought/oversold conditions, and ATR for dynamic stop-loss placement. The strategy seeks to capture trends in trending markets while also identifying reversal opportunities in range-bound conditions.
Core Philosophy:
Use the Ichimoku Cloud as the foundation for detecting trending vs. range-bound markets.
Combine multiple indicators (MACD, RSI, Stochastic RSI) to improve signal quality and reduce false entries.
Implement robust risk management using ATR-based stop-loss levels.
Approach:
Trending Markets: Enter long trades when price is above the Ichimoku Cloud with bullish momentum (e.g., RSI > 55, MACD histogram > 0). Enter short trades when price is below the cloud with bearish momentum.
Range-Bound Markets: Enter mean-reversion trades at overbought/oversold levels (e.g., RSI < 30 or > 70, Stochastic RSI extremes).
Strengths
Robust Market Regime Detection:
The Ichimoku Cloud effectively distinguishes between trending and range-bound markets, allowing the strategy to adapt dynamically.
Confluence of Indicators:
The use of MACD, RSI, and Stochastic RSI ensures that trades are only taken when multiple conditions align, reducing false signals.
Dynamic Risk Management:
ATR-based stop-loss levels adapt to market volatility, minimizing drawdowns while allowing trades to breathe.
Visualization:
Highlights trending markets (green background) and range-bound markets (red background) for easy interpretation.
Plots the Ichimoku Cloud for visual confirmation of market structure.
Performance on Higher Timeframes:
Backtesting results show strong performance on daily (D1) charts, with a profit factor of 2.159 and a net profit of +10.71% over the testing period.
Weaknesses
Low Percent Profitable:
Across all timeframes, the percent profitable is below 40%, indicating that many trades are unprofitable.
This suggests that the entry/exit logic may need further refinement.
Overtrading on Lower Timeframes:
On H4 charts, the strategy executed 430 trades with a profit factor of only 1.219, indicating overtrading and reduced efficiency.
Missed Opportunities in Range-Bound Markets:
While designed to trade reversals in range-bound conditions, the strategy's filters may be too restrictive, leading to missed opportunities.
Complexity:
The combination of multiple indicators (Ichimoku Cloud, MACD, RSI, Stochastic RSI) increases complexity, which may make it harder for users to understand or optimize.
Recommended Timeframes
Daily (D1):
Best performance observed during backtesting.
Strong profit factor (2.159) and manageable drawdowns (-2.10%) make it ideal for swing traders looking to capture long-term trends.
4-Hour (H4):
Marginal profitability observed during backtesting (profit factor of 1.219).
Suitable for traders willing to refine filters to reduce overtrading and improve signal quality.
Avoid Lower Timeframes (e.g., M15):
High noise levels lead to frequent false signals and poor profitability.
Performance Metrics from Backtesting (BTCUSDT)
Timeframe Net Profit Profit Factor Total Trades Percent Profitable Max Drawdown
Daily (D1) +10.71% 2.159 58 37.93% 2.10%
4-Hour (H4) +6.16% 1.219 430 32.56% 2.47%
Final Thoughts
The "Refined Ichimoku with MACD and RSI Strategy" is a versatile tool for traders who prefer higher timeframes like D1 or H4 charts. While it excels in capturing long-term trends with robust risk management, it struggles with low percent profitable rates and overtrading on lower timeframes. By focusing on simplicity and refining entry/exit logic, this strategy has the potential to deliver consistent results for swing traders seeking a balance between trend-following and mean-reversion approaches. By making the code open, it is hoped that experts might be able to adjust the variables within the script to their liking while still benefiting from the overall approach and philosophy of the strategy.
Regarding the three Strategy Indicator Settings:
1. Conversion Line Length (Default: 9)
What It Does:
The Conversion Line (Tenkan-sen) is a short-term moving average that represents the midpoint of the highest high and lowest low over the specified period (default: 9).
It acts as a fast-moving signal line, similar to a short-term moving average.
Recommendations:
Default Setting (9): Works well for most timeframes, especially higher timeframes like Daily (D1) or Weekly, as it captures short-term momentum effectively.
Shorter Timeframes (M15, H1): Consider reducing this value to 6 or 7 to make the Conversion Line more responsive to rapid price changes.
Higher Timeframes (D1, Weekly): Stick with the default value of 9 to avoid excessive noise.
When to Adjust:
Decrease if you want faster signals for scalping or intraday trading.
Increase slightly (e.g., to 10 or 12) if you want smoother signals for swing trading.
2. Base Line Length (Default: 26)
What It Does:
The Base Line (Kijun-sen) is a medium-term moving average that represents the midpoint of the highest high and lowest low over the specified period (default: 26).
It serves as a key support/resistance level and a trend confirmation signal when crossed by the Conversion Line.
Recommendations:
Default Setting (26): Standard for most markets and timeframes. It balances responsiveness with stability.
Shorter Timeframes: Reduce to 20–22 for faster signals in volatile markets.
Higher Timeframes: Stick with the default value of 26 or increase slightly to 30 for smoother trend confirmation.
When to Adjust:
Decrease for quicker trend signals in fast-moving markets.
Increase for long-term trading strategies where you want stronger support/resistance levels.
3. Lagging Span Length (Default: 52)
What It Does:
The Lagging Span (Chikou Span) plots the current closing price shifted backward by the specified number of periods (default: 52).
It helps confirm trends by comparing current price action to past price levels.
Recommendations:
Default Setting (52): Works well across most timeframes, as it aligns with traditional Ichimoku settings designed for long-term trends.
Shorter Timeframes: Reduce slightly to around 40–45 if you want quicker trend confirmations in intraday trading.
Higher Timeframes: Keep at the default value of 52, as it provides reliable confirmation of long-term trends.
When to Adjust:
Decrease for faster confirmation in high-volatility environments.
Increase only if you are focusing on very long-term trends, such as on Monthly charts.
General Disclaimer
Not Financial Advice:
This script is provided for educational and informational purposes only. It should not be considered financial or investment advice. Always consult with a qualified financial advisor before making trading decisions.
Use at Your Own Risk:
Trading involves significant risk, and past performance is not indicative of future results. Users are solely responsible for any losses incurred while using this strategy.
No Guarantee of Profitability:
While this strategy has been backtested on historical data, there is no guarantee that it will perform similarly in live market conditions due to differences in market behavior, slippage, and latency.
Technical Disclaimer
Indicator Limitations:
This strategy relies on technical indicators such as the Ichimoku Cloud, MACD, RSI, and ATR. These indicators are lagging or reactive by nature and may not accurately predict future price movements.
Timeframe-Specific Performance:
This strategy has shown better performance on higher timeframes (e.g., Daily). It may not perform well on lower timeframes (e.g., M15) due to increased market noise.
Customization Required:
The default settings (e.g., Conversion Line Length = 9, Base Line Length = 26, Lagging Span Length = 52) are optimized for general use but may require adjustment based on the user's trading style, asset class, or timeframe.
Market Risks Disclaimer
Market Conditions Matter:
The effectiveness of this strategy depends heavily on market conditions. It performs best in trending markets and may struggle in highly volatile or range-bound environments without adjustments.
Slippage and Execution Risks:
Backtesting results do not account for slippage, spreads, or order execution delays that occur in live trading environments.
No Adaptation to News Events:
This strategy does not incorporate fundamental analysis or news events that can significantly impact price movements.
User Responsibility Disclaimer
Backtesting and Optimization:
Users are encouraged to backtest and optimize the strategy on their chosen assets and timeframes before deploying it in live trading.
Monitor Regularly:
This strategy is not a "set-and-forget" tool. Users should monitor trades regularly and adjust settings as needed to adapt to changing market conditions.
Risk Management Required:
Proper risk management practices (e.g., position sizing, stop-loss placement) are crucial when using this strategy to minimize potential losses.
Money Flow Index MTF + Alerts with Candle Opacity & LabelsHow to Use the Money Flow Index MTF + Alerts with Candle Opacity & Labels Indicator
Overview:
This indicator is designed to help you gauge the buying and selling pressure in a market by using the Money Flow Index (MFI). Unlike many momentum oscillators, the MFI incorporates both price and volume, providing a unique perspective on market activity. It is particularly useful when you want to visually assess potential overbought or oversold conditions.
Indicator Components:
Money Flow Index (MFI) Calculation:
The indicator computes the MFI using a user-defined look-back period (default is 14 bars). The MFI is scaled between 0 and 100, where values above 80 typically indicate overbought conditions and values below 20 suggest oversold conditions.
Multi-Timeframe (MTF) Capability:
You can choose to calculate the MFI using either the current chart’s timeframe or a custom timeframe (for example, a 4-hour chart). This flexibility allows you to compare longer-term money flow trends against your primary trading timeframe.
Candle Opacity Based on MFI:
The opacity of the candles on your chart is dynamically adjusted based on the current MFI reading. When the MFI is high (near 100), candles become more opaque; when the MFI is low (near 0), candles appear more transparent. This visual cue can help you quickly spot changes in market momentum.
Visual Labels for Overbought/Oversold Conditions:
When the MFI crosses into the overbought territory, a red label reading “Overbought” is displayed above the high of the bar. Similarly, when it crosses into the oversold territory, a green label reading “Oversold” is placed below the low of the bar. These labels provide an immediate visual alert to potential reversal points or areas of caution.
Alert Conditions:
The script also includes alert conditions for both overbought and oversold signals. You can set up TradingView alerts so that you are notified in real time when the indicator detects these conditions.
Theory Behind the Money Flow Index (MFI):
The Money Flow Index is a momentum oscillator that uses both price and volume to signal the strength behind price moves.
Overbought Conditions: When the MFI is above 80, it suggests that buying pressure is very strong and the asset might be due for a pullback or consolidation.
Oversold Conditions: Conversely, when the MFI falls below 20, selling pressure is high and the asset might be oversold, potentially priming it for a bounce.
Keep in mind that in strong trending markets, overbought or oversold readings can persist for extended periods, so the MFI should be used in conjunction with other technical analysis tools.
Position Management Guidance:
While the indicator is useful for spotting potential overbought and oversold conditions, it is not designed to serve as an automatic signal to completely close a position. Instead, you might consider using it as a guide for pyramiding—gradually adding to your position over several days rather than exiting all at once. This approach allows you to better manage risk by:
Scaling In or Out Gradually: Instead of making one large position change, you can add or reduce your position in increments as market conditions evolve.
Diversifying Risk: Pyramiding helps you avoid the pitfalls of trying to time the market perfectly on a single trade exit or entry.
How to Get Started:
Apply the Indicator:
Add the indicator to your TradingView chart. Adjust the input settings (length, oversold/overbought levels, and resolution) as needed for your trading style and the market you’re analyzing.
Watch the Candles:
Observe the dynamic opacity of your candles. A sudden change in opacity can be a sign that the underlying money flow is shifting.
Monitor the Labels:
Pay attention to the “Overbought” or “Oversold” labels that appear. Use these cues in combination with your broader analysis to decide if it might be a good time to add to or gradually exit your position.
Set Up Alerts:
Configure TradingView alerts based on the indicator’s alert conditions so that you are notified when the MFI reaches extreme levels.
Use as Part of a Broader Strategy:
Remember, no single indicator should dictate your entire trading decision. Combine MFI signals with other technical analysis, risk management rules, and market insights to guide your trades.
