Market Push Meter - CoffeeStyleMarket Push Meter - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the Market Push Meter indicator, a sophisticated volume analysis tool developed by CoffeeKiller with the help and assistance of FindBetterTrades that measures and visualizes the ongoing battle between buyers and sellers through volume pressure analysis.
🔔 **Warning: This Is Not a Standard Volume Indicator** 🔔 This indicator analyzes volume pressure in a unique way, combining directional volume with price action to identify market imbalances between buyers and sellers. All credit for the core logic for this indicator goes to FindBetterTrades and his/hers Volume Pressure Histogram (Normalized) (this is my adaptation and style added to that core logic, thus the CoffeeStyle name was added).
Core Concept: Volume Pressure Analysis
The foundation of this indicator lies in measuring the imbalance between buying and selling volume, providing insights into which market participants are exerting more pressure on price movements.
Volume Pressure Columns: Buying vs Selling Force
- Positive Green Columns: Net buying pressure
- Negative Red Columns: Net selling pressure
- Color intensity varies based on pressure strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during buying phases
- Low Marker Line (Cyan): Tracks the lowest point reached during selling phases
- Creates visual boundaries showing pressure extremes
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important pressure peaks
- Helps identify potential reversal points and pressure exhaustion
Reference Lines:
- Overbought Level: Threshold for extreme selling pressure
- Oversold Level: Threshold for extreme buying pressure
- Used to identify potential reversal zones
Core Components
1. Volume Pressure Calculation
- Separation of up-volume and down-volume
- Calculation of net volume pressure
- Smoothing for consistent visualization
- Normalization against total volume for percentage scaling
2. Boundary Tracking System
- Automatic detection of highest values in buying phases
- Automatic detection of lowest values in selling phases
- Step-line visualization of boundaries
- Color-coded for easy identification
3. Peak Detection System
- Identification of local maxima and minima
- Background highlighting of significant peaks
- Triangle markers for peak visualization
- Zero-line cross detection for trend changes
4. Threshold Settings
- Extreme threshold multiplier for identifying significant pressure
- Overbought/oversold levels for potential reversals
- Dynamic color coding based on pressure intensity
- Alert conditions for key pressure levels
Main Features
Volume Analysis Settings
- Customizable volume MA length
- Signal smoothing for clearer readings
- Optional log scale for handling wide range variations
- Adjustable threshold multiplier for sensitivity
Visual Elements
- Color-coded columns showing pressure direction and strength
- Dynamic marker lines for pressure boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
- Overbought/oversold reference lines
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for pressure strength
- Peak formation for potential reversals
- Color changes for pressure direction and intensity
- Alert conditions for extreme pressure levels
Customization Options
- Volume analysis parameters
- Marker line visibility and colors
- Peak marker display options
- Log scale toggle for handling various markets
- Overbought/oversold threshold adjustments
Trading Applications
1. Trend Identification
- Volume pressure crossing above zero: buying pressure emerging
- Volume pressure crossing below zero: selling pressure emerging
- Column color: indicates pressure direction
- Column height: indicates pressure strength
- Signal line: confirms overall trend direction
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Volume pressure approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing pressure
- Readings beyond overbought/oversold levels: potential reversal zones
3. Pressure Analysis
- Breaking above previous high boundary: accelerating buying pressure
- Breaking below previous low boundary: accelerating selling pressure
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Extreme readings: potential climactic buying/selling
4. Market Structure Assessment
- Consecutive higher peaks: strengthening buying structure
- Consecutive lower troughs: strengthening selling structure
- Peak comparisons: relative strength of pressure phases
- Boundary line steps: market structure levels
Optimization Guide
1. Volume Analysis Settings
- Volume MA Length: Default 25 provides balanced signals
- Lower values (10-15): More responsive, potentially noisier
- Higher values (30-50): Smoother, fewer false signals
- Signal Smoothing Length: Default 8 provides good balance
- Lower values: More responsive to pressure changes
- Higher values: Smoother trend identification
2. Threshold Settings
- Extreme Threshold Multiplier: Default 20.0
- Lower values: More signals, potentially more noise
- Higher values: Fewer signals, but more significant
- Overbought/Oversold Levels: Defaults at 20/-20
- Adjust based on instrument volatility
- Wider settings for more volatile instruments
3. Visual Customization
- Marker Line Colors: Adjust for visibility on your chart
- Peak Marker Color: Default yellow provides good contrast
- Enable/disable background highlights based on preference
- Consider log scale for instruments with wide volume ranges
4. Alert Settings
- Configure alerts for high buying pressure
- Configure alerts for high selling pressure
- Set additional alerts for zero-line crosses
- Consider timeframe when setting alert sensitivity
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm pressure changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong pressure
- Use with price action for entry/exit precision
- Consider extreme threshold crossings as significant signals
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Multiple timeframes: confirm signals across time horizons
- Match to your trading style and holding period
3. Market Context
- Strong buying phase: positive columns breaking above marker line
- Strong selling phase: negative columns breaking below marker line
- Columns approaching zero: potential pressure shift
- Columns beyond overbought/oversold: extreme conditions, potential reversal
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with price action oscillators for divergence detection
- Combine with traditional volume indicators for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when volume pressure breaks above previous high marker line
- Enter short when volume pressure breaks below previous low marker line
- Use zero-line as initial stop-loss reference
- Take profits at formation of opposing peaks
2. Peak Trading Strategy
- Identify significant peaks with triangular markers
- Look for consecutive lower peaks in buying phases for shorting opportunities
- Look for consecutive higher troughs in selling phases for buying opportunities
- Use zero-line crosses as confirmation
3. Extreme Reading Strategy
- Look for volume pressure beyond overbought/oversold levels
- Watch for color changes and peak formations
- Enter counter-trend positions after confirmed peaks
- Use tight stops due to extreme market conditions
4. Volume Color Strategy
- Enter long when columns turn bright green (increasing buying pressure)
- Enter short when columns turn bright red (increasing selling pressure)
- Exit when color intensity fades (decreasing pressure)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Volume pressure crosses above zero line
- Green columns grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant buying pressure peaks
Bearish Market Scenario
- Volume pressure crosses below zero line
- Red columns grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant selling pressure troughs
Consolidation Scenario
- Volume pressure oscillates around zero line
- Column colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Pressure values remain small
Understanding Market Dynamics Through Market Push Meter
At its core, this indicator provides a unique lens to visualize market pressure through volume analysis:
1. Volume Imbalance: By separating and comparing buying volume (up candles) from selling volume (down candles), the indicator provides insights into which side is exerting more pressure in the market.
2. Normalized Pressure: The indicator normalizes volume pressure as a percentage of total volume, making it more comparable across different market conditions and instruments.
3. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of pressure in both directions, helping to identify when markets are making new pressure extremes.
4. Exhaustion Signals: The peak detection system highlights moments where pressure has reached a local maximum or minimum, often precursors to reversals or consolidations.
Remember:
- Combine signals from volume pressure, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences and market
- Consider overall market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
DISCLAIMER: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
In den Scripts nach "Buy sell" suchen
Holding Volume StrengthHolding Volume Strength Indicator
1. Overview :
The Holding Volume Strength indicator is designed to measure the buying and selling volume based on price action (bullish vs. bearish candles) over a user-defined lookback period. This indicator helps traders gauge the strength of market participants' involvement (buyers vs. sellers) during a specific time frame.
2. Key Inputs :
- Lookback Period : The period over which you want to calculate the Buy and Sell volumes. For example, a lookback of 5 will calculate the volume for the current candle and the previous candle , while a lookback of 10 will consider the current candle and the 9 preceding candles.
- Text Color : This allows customization of the label's text color for better visibility and style.
3. Volume Calculation :
- Buy Volume : If the close price of a candle is greater than its open price (bullish candle), the body size (difference between open and close) is multiplied by the volume for that candle to calculate the buy volume. This represents the market's buying strength.
- Sell Volume : If the close price of a candle is less than its open price (bearish candle), the body size is multiplied by the volume for that candle to calculate the sell volume. This represents the market's selling strength.
4. Volume Display :
The Buy and Sell Volumes are displayed in a readable format, such as:
- Buy Volume: "1.5M" (1.5 million)
- Sell Volume: "500K" (500 thousand)
These values can help identify whether buying or selling is more dominant over a specified period.
5. Label Display :
The calculated Buy and Sell volumes are shown as labels on the main price chart (overlay). These labels dynamically update with each new candle and show the values for the current candle and the previous `n` candles (based on the lookback period).
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How This Indicator Helps in Making Buy/Sell Decisions :
1. Volume Analysis :
- High Buy Volume : A significant amount of buying volume can indicate strong market interest in the asset, suggesting potential upward momentum. If the market is in a bullish trend (e.g., after a series of green candles), and you see increasing buy volume, this might indicate that buyers are in control , making it a potential signal to buy .
- High Sell Volume : On the other hand, a significant amount of selling volume, particularly after a series of bullish candles, can signal that sellers are taking control of the market, which could indicate bearish pressure . If you observe increasing sell volume, it might be a potential signal to sell or to short the asset.
2. Volume Confirmation :
- Volume is often used to confirm price movements . For example, if the price breaks above a resistance level with strong buy volume , it suggests that the breakout is likely genuine and not a false move. Similarly, if the price drops below a support level with strong sell volume , it could signal that the breakout is real and the downtrend is continuing.
3. Divergence Analysis :
- Volume divergence occurs when price makes a new high or low but volume doesn't confirm it. For instance:
- If price makes a new high but the buy volume does not increase (or even decreases), it could signal a weak trend or potential reversal.
- Similarly, if price makes a new low but sell volume is weak, it might suggest the downtrend is losing steam and could reverse.
4. Buy/Sell Signal Strategy :
- Buy Signal : A potential buy signal might occur when you see a bullish candle with increased buy volume (especially if the buy volume is higher than the sell volume) during an uptrend or near a support level.
- Sell Signal : A potential sell signal might occur when you see a bearish candle with increased sell volume (especially if the sell volume is higher than the buy volume) during a downtrend or near a resistance level.
You could also combine this with other technical indicators (like Moving Averages, RSI, etc.) to form a more robust trading strategy.
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Example of How It Works in Practice :
- Scenario 1 (Bullish) :
- You're trading a stock or cryptocurrency, and you have the Holding Volume Strength indicator plotted.
- Over the past 10 candles, you notice a bullish trend where the price is rising.
- On the current candle, you see a strong buy volume value, indicating that buyers are in control .
- Given that the buy volume is higher than the sell volume , this might reinforce the bullish trend , and you could consider buying or entering a long position .
- Scenario 2 (Bearish) :
- You're analyzing the same asset, but this time, the price is in a downtrend .
- You notice that a recent bearish candle has a strong sell volume , suggesting sellers are dominating .
- If this sell volume is higher than the buy volume, it could indicate that the downtrend is likely to continue , and you might consider selling or entering a short position .
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Why Volume Matters :
- Volume precedes price : Volume is often considered a leading indicator, as changes in volume can signal future price movements . For example, a sudden increase in buy volume often precedes upward price movement, while a sudden increase in sell volume often precedes downward price movement.
- Volume confirms trends : Volume helps confirm trends. A price move accompanied by high volume is typically more reliable , while a price move with low volume might be a false signal or less likely to sustain itself.
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Conclusion :
The Holding Volume Strength indicator helps traders understand the market sentiment (buyers vs. sellers) by showing the cumulative buying and selling volume over a specified period. By examining the buy and sell volumes, traders can make more informed decisions about when to buy, sell, or hold based on market strength.
This volume analysis is essential because it allows traders to understand how strong the price movement is and whether it is likely to continue or reverse. By incorporating volume analysis with other indicators or chart patterns, traders can improve the accuracy of their trading signals and reduce risk.
Injected Volume Footprint (IVF)Reading volume footprints to interpret buying and selling pressure involves examining the intensity and timing of buy/sell activity within each candle. Although this IVF indicator does not directly show the sequence of buying and selling events within a single candle (as a true footprint chart would), here’s how you can interpret the volume data presented by IVF to get insights on market pressure:
Step 1: Identifying Strong Pressure
Check Color Intensity:
Darker shades represent higher intensity for both buy and sell volumes.
Look for dark green shades for strong buying pressure and dark red or orange shades for strong selling pressure. This helps you quickly spot candles with a high level of activity on one or both sides.
Check Volume Stacking:
Since buy volumes are above the zero line and sell volumes are below, large differences between the two suggest dominance by one side.
If buy volume is significantly higher (e.g., tall green bar with a small red/yellow bar underneath), buying pressure is dominant. Conversely, if sell volume is larger (tall red/yellow bar with a small green bar above), selling pressure dominates.
Step 2: Interpreting Both Buy and Sell Activity
Simultaneous Pressure:
If you see strong green (buy) and red/yellow (sell) volumes within the same candle, it indicates that there was active trading on both sides during that period.
This scenario might suggest a battle between buyers and sellers—often seen near critical support or resistance levels where both sides are actively defending their positions.
Balance vs. Imbalance:
Balanced Pressure: When buy and sell volumes are similar in size, it indicates a period of indecision or a potential consolidation. This usually happens when neither buyers nor sellers have a clear upper hand.
Imbalanced Pressure: If one side has a much larger volume than the other, it shows a clear dominance. For instance, if green buy volume dominates, it means buyers were willing to absorb sell orders aggressively, suggesting a possible uptrend.
Step 3: Estimating Sequence (Hypothetical)
Although IVF doesn’t provide a direct sequence, you can make educated guesses based on context:
Price Action Context:
If the candle opens and initially moves down but then closes higher (bullish candle), it might indicate that selling pressure came first and buying pressure followed, pushing the price up.
Conversely, if the candle opens and moves up first but closes lower (bearish candle), buying might have started first but was overtaken by selling pressure.
Volume Reaction to Price Levels:
At support levels, if you see strong buy volumes with some sell volumes, it might mean initial selling pressure was absorbed by buyers defending the level.
At resistance levels, if sell volume increases with some buy activity, it may indicate initial buying was met by aggressive selling, potentially reversing the price.
Trend Context:
In an uptrend, strong sell volume within an otherwise bullish candle may indicate profit-taking or the start of a pullback, as sellers try to cap further gains.
In a downtrend, strong buy volume in a bearish candle may indicate potential accumulation or buyers attempting to slow the decline, signaling a possible reversal if the trend weakens.
Conclusion
The IVF indicator doesn’t provide the exact sequence of events within each candle like true footprint data would, but by analyzing the intensity, balance, and context within the price action, you can get a reasonable sense of which side was more aggressive and how both buying and selling pressures interacted.
ICT Judas Swing | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Judas Swing Indicator! This indicator is built around the ICT's "Judas Swing" strategy. The strategy looks for a liquidity grab around NY 9:30 session and a Fair Value Gap for entry confirmation. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Judas Swing :
Implementation of ICT's Judas Swing Strategy
2 Different TP / SL Methods
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The strategy begins by identifying the New York session from 9:30 to 9:45 and marking recent liquidity zones. These liquidity zones are determined by locating high and low pivot points: buyside liquidity zones are identified using high pivots that haven't been invalidated, while sellside liquidity zones are found using low pivots. A break of either buyside or sellside liquidity must occur during the 9:30-9:45 session, which is interpreted as a liquidity grab by smart money. The strategy assumes that after this liquidity grab, the price will reverse and move in the opposite direction. For entry confirmation, a fair value gap (FVG) in the opposite direction of the liquidity grab is required. A buyside liquidity grab calls for a bearish FVG, while a sellside grab requires a bullish FVG. Based on the type of FVG—bullish for buys and bearish for sells—the indicator will then generate a Buy or Sell signal.
After the Buy or Sell signal, the indicator immediately draws the take-profit (TP) and stop-loss (SL) targets. The indicator has three different TP & SL modes, explained in the "Settings" section of this write-up.
You can set up alerts for entry and TP & SL signals, and also check the current performance of the indicator and adjust the settings accordingly to the current ticker using the backtesting dashboard.
🚩 UNIQUENESS
This indicator is an all-in-one suit for the ICT's Judas Swing concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. Different and customizable algorithm modes will help the trader fine-tune the indicator for the asset they are currently trading. Three different TP / SL modes are available to suit your needs. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️ SETTINGS
1. General Configuration
Swing Length -> The swing length for pivot detection. Higher settings will result in
FVG Detection Sensitivity -> You may select between Low, Normal, High or Extreme FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
2. TP / SL
TP / SL Method ->
a) Dynamic: The TP / SL zones will be auto-determined by the algorithm based on the Average True Range (ATR) of the current ticker.
b) Fixed : You can adjust the exact TP / SL ratios from the settings below.
Dynamic Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
[FXAN] 75 Cygni Algorithm (Day Trading)⚜️ FXAN CYGNI INDICATORS ORIGINALITY
Originality comes from proprietary formula we use to measure the relationship between Volume and Price Volatility in relation to overall current market positioning in developing Volume Profile and multiple custom period Volume Profiles. We combine that with our own approach to measure price velocity in correlation to average daily/weekly/monthly ranges of the given market.
The relationship between current volume and price volatility gives us information about how much the volume that is currently coming into the market affects the price movement (volatility) and which side is more dominant/involved in the market (Buyers/Sellers). We call this the " Volume Impact " factor.
This information is then compared in relation to overall current market positioning in developing Volume Profile and Multiple custom period Volume Profiles. We have created a rating system based on current price positioning in relation to the Volume Profile. Volume profile consists of different volume nodes, high volume nodes where we consider market interest to be high (a lot of transactions - High Volume) and low volume nodes where we consider market interest to be low (not a lot of transactions - Low Volume). We call this the current " Market Interest " factor.
We combine this information with our own approach to measure price velocity in correlation to the higher-timeframe price ranges. Calculation is done by measuring current ranges of market movement in correlation to average daily/weekly/monthly ranges. We call this " Price Velocity " factor.
This approach was applied to develop key components of our Tradingview Indicators, we've simplified some of the calculations and made them easy to use by programming them to display buying/selling volume pressure with colors.
In addition to our own proprietary formulas and criterias to measure volume impact on price, we've also used an array of indicators that measure the percentage change in volume over custom specified periods of time, including custom period ranged Volume Profile, Developing VA, Accumulation/Distribution (A/D Line), Volume Rate of Change (VROC), Volume Price Trend (VPT) - all of them with of course fine-tuned settings to fit the purpose in the overall calculation.
Reasons for multiple indicator use:
Custom period ranged Volume Profiles: To determine current interest of market participants. Used for " Market Interest "
Developing VA: To determine current fair price of the market (value area). Used for " Market Interest ".
Accumulation/Distribution (A/D Line): Helping to gauge the strength of buying and selling pressure. Used for " Volume Impact "
Volume Rate of Change (VROC): To give us information about percentage change in volume. Used for " Volume Impact "
Volume Price Trend (VPT): To help identify potential trends. Used for " Volume Impact ".
Average True Range (ATR): Used for measuring volatility. Used for " Volume Impact " and " Price Velocity" .
Average Daily Range (ADR): Used for measuring average market price movement. Used for " Price Velocity ".
How it all works together:
"Volume Impact" factor tells us the influence of incoming market volume on price movement. This information alongside the overall market positioning information derived from "Market Interest" factor combined with information about speed and direction relative to higher-timeframe price ranges frin "Price Velocity.
This is the basis of our proprietary developed Volume Dynamics analysis approach
"Volume Impact" x "Market Interest" x "Price Velocity"
Combining this factors together gives a good overall understanding of which side is currently more involved in the market to gauge the direction ("Volume Impact"), where the market is currently positioned to gauge the context ("Market Interest") and what the current market's momentum to improve the timing of our trades ("Price Velocity"). This increases our probabilities for successful trades, executed with good timing.
To simplify - our indicators will always analyze the volume behind every price movement and rate those movements based on the relationship between movement distance and volume behind it through an array of criterias and rate them.
Colors displayed by the indicators will be a result of that, suggesting which side of the market (Buyers or sellers) is currently more involved in the market, aiming to increase the probabilities for profitable trades. With the help of our indicators you have deep volume analysis behind price movements done without looking at anything else then indicator components.
🔷 OVERVIEW
Cygni 75 Algorithm is a TradingView indicator crafted to refine your market analysis and assist in identifying potential entry and exit points by analyzing the underlying volume behind market movements. It helps you determine the overall daily context of the market and its conditions/trends by offering a suite of features tailored to provide insights to traders across various market conditions.
🔷 KEY FEATURES
▊ Candle Coloring
▊ Deviation Bands
▊ Momentum Bar | on the bottom of the chart
▊ Area of Interest (AOI) | Yellow rectangle
🔷 HOW DOES IT WORK?
□ Candles will color in reference to the dominance of buyers or sellers based on underlying volume calculated by a proprietary formula. The green color indicates that buyers are in control, and the red color indicates the selling volume is dominating the market. To simplify, green means there's more buying - red means there's more selling.
□ Deviation bands are used to determine potential trade entries and exits, derived by average price weighted by volume.
□ Momentum Bar shows market momentum by analyzing the differences between multiple moving averages. Green is bullish; red is bearish. The colors will lighten up when momentum is strong, and once the market slows down, they will get darker.
□ Area of Interest (AOI) is used for contextual reference, derived from the previous day's market movements. They remain static throughout the current day.
🔷 HOW TO USE IT?
□ In general, we look for areas where all components are in sync. This are valid trading signals (refer to the usage example below).
□ Candle Colors: Looking for longs when the candles are green, and looking for shorts when the colors are red
□ Deviation Bands: Once we enter the trade, we can place the SL and TP levels at the closest bands.
□ Momentum Bar: Helps with the timing of the entry, looking to enter on light Green/Red colors. Longs when green and shorts when red.
□ Area Of Interest: Generally, we're expecting rotational conditions inside the area and breakouts above/below once the market price gets outside of it. Longs above the area and shorts below the area for breakouts.
🔷 COMBINING THE COMPONENTS
Each component of the indicator serves it's own purpose and analyzes the market from it's own perspective and with its own custom settings and formulas (one looks at trading direction from the perspective of the overall trend and the other looks at price volatility to measure momentum - different perspectives). The calculation of the individual component is done independently from other components. Once all of them align we're able to execute trades with edge as it signals that different aspects of volume and price analysis line up for the trading opportinity.
- Candle Colors are used for determining trading direction
- Deviation bands are used for determining TP/SL levels
- Momentum bar is used to for better timing of your entries/exits.
- AOI is used to help you determine potential market conditions
It's important to combine the components to increase the probability of success - here's how you should look for a trade:
1. Determine the direction you want to trade in with the help of Candle Colors
2. Assess the current market price in reference to AOI - look for longs if the price is above the AOI, shorts if the price is below AOI, and rotations if it's inside the AOI.
3. Wait for the right momentum to develop to improve the timing of the entry by using Momentum Bar.
4. Place TP/SL levels with the help of Deviation bands based on your risk appetite.
A valid example of the trade would be:
- Green Candle Colors (indicating longs)
- Market price is currently above the AOI or breaking the edge of AOI in the upside movement (indicating longs)
- Momentum Bar is Green (indicating long momentum)
- Placing SL to the closest Deviation Band below the price and TP to the closest Deviation Band above the price.
📊 USAGE EXAMPLES
Buyside/Sellside Liquidity [Real-Time] (Expo)█ Overview
Buyside/Sellside Liquidity (Expo) is an indicator that identifies buy-side and sell-side liquidity in real time. Buy-side liquidity represents a level on the chart where short sellers will have their stops positioned. Sell-side liquidity represents a level on the chart where long-buyers will place their stops. These levels are found in areas where traders are "proven wrong" and, therefore, want to get out of their trades. Smart money will accumulate or distribute positions near these levels where many stops are placed and absorb all provided liquidity.
█ What is Buy-side and Sell-side liquidity?
Liquidity is the ability of a market to absorb large orders without significantly affecting the asset's price. Buy-side liquidity refers to the ability of buyers to buy large amounts of contracts without significantly affecting the price. Sell-side liquidity refers to the ability of sellers to sell large amounts of contracts without significantly affecting the price. This type of liquidity is important for large institutional investors, such as hedge funds and investment banks, who need to buy/sell large amounts of contracts without significantly affecting the price.
█ How to use
The price will always seek liquidity to either reverse or continue in the current move.
Reversals
Reversals are common around these levels since many traders are forced to close their positions, pushing the price in the other direction. Look for price actions that confirm a reversal around those levels.
Continuations
Liquidity is also a must for a trend to continue. If the price pushes through the liquidity levels and the current order flow structure is intact, traders should look for a continuation setup.
Inducement
Inducement is the act where smart money manipulates the price to access liquidity. Buy-side and Sell-side liquidity levels can be used to identify potential areas of inducement.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Accumulated Net ValueThe Concept:
Accumulated Net Value (ANV) is an indicator that gauges buying/selling strength by looking at whether the closing price is closer to the high or the low. It’s like a tug of war - if buyers are more dominant, then the closing price should be closer to the high; and if sellers are more dominant, then the closing price should be closer to the low.
Additional adjustments are implemented to address price gaps. The indicator first compares the high and low of the current bar with the previous bar, and then use the higher high/lower low among the current and previous bars to calculate the distance from the closing price.
Price is only part of the equation. We know that volume is also an important factor when considering the strength of buyers and sellers. The ANV indicator takes volume into account by multiplying volume with the difference between the closing price and the high or low (depending on which one is more dominant). This generates the ANV for one bar, where such one-bar ANV will have a positive value during buyer-dominant conditions, and a negative value during seller-dominant conditions.
Since ANV for only one bar can be quite choppy, this indicator further adds the ANV of N bars together to get the final ANV signal, and then applies a simple moving average (SMA) to it.
The Variables:
This indicator has two inputs: (1) N bars of Accumulation, and (2) SMA Length.
N bars of Accumulation determines how many bars of ANV values are added together. SMA Length determines the length of SMA applied to the final ANV.
For daily charts, I use “5” or “10” for N bars of accumulation and “20” for SMA length.
For weekly charts, I use “4” for N bars of accumulation and “10” for SMA length.
The user will have to do some testing to see which numbers suit their needs. Smaller values are more sensitive and move faster, but show more choppiness and false signals. Larger values tend to be more reliable, but are slow to react to price movements.
The Signals:
Trading signals can be generated by comparing the ANV with either the SMA or the zero line:
- ANV above SMA: bullish;
- ANV below SMA: bearish;
- ANV above zero: bullish;
- ANV below zero: bearish.
Given that SMA signals are generally triggered earlier than the zero line signals, aggressive traders can trade based on the SMA line, while more conservative traders can trade based on the zero line (i.e., waiting for ANV to turn positive or negative).
Whale Trading SystemThis script is an advanced version of the distributional blocks script.
In distributional buys and sells:
I used a high - low cloud filter, which makes it more prudent to sell the next sell higher for sells and to buy the next purchase lower for buys.
I also used the Stochastic Money Flow Index function because it also uses volume to separate regions.
The long period is 52 weeks, which is equal to one year,
The short period is one-fourth of its value, which is equal to a financial quarter.
Then the values calculated with these periods are calculated by stochastic - rsi logic within the function, giving us two averages and separating the regions according to crossovers and crossunders .
In buys and sales, the higher your next distributional position size makes your profit more .
In the old system, there was a confusion as it was not divided into zones.
Because we divide into zones here, zone changes are the last stop to free up existing positions, and you must reopen each time you change zones.
And I changed standard distribution days, depending on the price change and the histogram, as StochMFI also took into account the volume.
In this way, there is sustainability.
I am also sharing my educational idea that explains the logic of this system in more detail :
Now that we have been divided into regions, a maximum of 10 pieces will suffice us.
And the regional shifts will allow us to sell and buy all of our position size, and now we will feel much more comfortable.
The most timeframe I find most accurate are the weekly bars.
Even in the example, we see how we have benefited from the sharp drop in bitcoin, while the price is falling, and we have lowered the average with higher-weight purchases than the previous one.
In both buys and sales here, both the histogram intensities and the average of the purchases you have reduced with the transactions, or the earnings you have increased with the sales, guide you.
In areas with high volatility ,if we adjust our positions properly, even if we follow the changes in the region, we will get rid of those situations with few wounds and we will surely catch the trend!
NOTE : Crossover/crossunder and distributional buy/sell alerts added.
Best regards , Noldo.
Power Trader Study The Power Trader is an indicator based around the Balance of Power Oscillator. Balance of Power is a price-based measurement that evaluates and compares the strength of buyers and sellers by assessing their respective abilities to push prices to extreme points(both extreme highs and extreme lows).
BoP values fluctuate between a maximum value of 100 and a minimum value of -100. When the BoP value is greater than 0, it indicates that buying pressure is greater than selling pressure. Conversely, negative BoP readings mean that selling pressure is greater than buying pressure.
The exponential moving average of Balance of Power values is displayed as a gray line on the chart. The upper red line represents the upper bound at which a security is considered overbought. The lower green line represents the threshold where we start to consider a security to be in an oversold state.
When the gray BoP EMA line crosses below the lower green line, it changes color to green then changes back to gray once it crosses back above that lower threshold. Similarly, the line turns red when it crosses above the upper red line.
When the EMA line is between the upper and lower bounds, it signifies that there is no significant difference between the power of buyers versus the power of sellers. The top red area indicates that the amount of buying pressure is relatively high. The lower green area means that selling pressure is abnormally high.
When the BoP line falls between the red and green areas, do not take action. When the BoP line turns green and is inside the green area, enter a long position. When the BoP line rises above the red line and into the upper red area, exit the long position.
Entry signals are displayed as vertical green lines that extend the length of the chart. Exit signals are represented by the same lines, except in red.
Users can decide the order of signals in the input option menu through the ‘allow repeat signals’ parameter. If this is set to false, the study will generate signals in the logical chronologic order of . If it is set to true, then signals will be generated as they come, regardless of whether the last signal was its inverse. This means that it could generate sequences like this for example .
Additionally, the stop and limit can also be set in the input menu through the ‘stop’ and ‘limit’ options. This input option accepts parameters of type float (ie: numbers that contain decimals).
The 'Upper Bound for BoP Values' and 'Lower Bound for BoP Values' input options gives traders the option to adjust the upper and lower thresholds for buy and sell signals. It is important to note that setting the upper bound higher or the lower bound lower will result in less frequent signals (and vice versa).
When it is time to enter a long position, an alert with the following message is sent “Power Trader - High Sell Pressure, Enter Long”.
When it is time to exit a long position, an alert with the following message is sent “Power Trader - High Buy Pressure, Exit Long”.
The Power Trader, along with all of our other invite-only scripts, can be found on our website:
profitprogrammers.com
Adaptive Volume Delta Map---
📊 Adaptive Volume Delta Map (AVDM)
What is Adaptive Volume Delta Map (AVDM)?
The Adaptive Volume Delta Map (AVDM) is a smart, multi-timeframe indicator that visualizes buy and sell volume imbalances directly on the chart.
It adapts automatically to the best available data resolution (tick, second, minute, or daily), allowing traders to analyze market activity with micro-level precision .
In addition to calculating volume delta (the difference between buying and selling pressure), AVDM can display a Volume Distribution Map — a per-price-level visualization showing how volume is split between buyers and sellers.
Key Features
✅ Adaptive Resolution Selection — Automatically chooses the highest possible data granularity — from tick to daily timeframe.
✅ Volume Delta Visualization — Displays delta candles reflecting the dominance of buyers (green), sellers (red), and delta (orange).
✅ Per-Level Volume Map (optional) — Shows detailed buy/sell volume distribution per price level, grouped by `Ticks Per Row`.
✅ Bid/Ask Classification — When enabled, AVDM uses bid/ask logic to classify trade direction with greater accuracy.
✅ Smart Auto-Disable Protection — Automatically disables volume map if too many price levels (>50) are detected — preventing performance degradation.
Inputs Overview
Use Seconds Resolution — Enables use of second-level data (if your TradingView subscription allows it).
Use Tick Resolution — Enables tick-based analysis for the most detailed view. If available, enable both tick and seconds resolution.
Use Bid/Ask Calculated — Uses bid/ask midpoint logic to classify trades.
Show Volume Distribution — Toggles per-price-level buy/sell volume visualization.
Ticks Per Row — Controls how many ticks are grouped per volume level. Reduce this value for finer detail, or increase it to reduce visual load.
Calculated Bars — Sets how many historical bars the indicator should process. Higher value increases accuracy but may impact performance.
How to Use
1. Add the indicator to your chart.
2. Ensure that your symbol provides volume data (and preferably tick or second-level data).
3. The indicator will automatically select the optimal timeframe for detailed calculation.
4. If your TradingView subscription allows second-level data , enable “Use Seconds Resolution.”
5. If your subscription allows tick-level data , enable both “Use Tick Resolution” and “Use Seconds Resolution.”
6. Adjust the “Calculated Bars” input to set how many historical bars the indicator should process.
7. Observe the Volume Delta Candles :
* Green = Buy pressure dominates
* Red = Sell pressure dominates
8. To see buy/sell clustering by price, enable “Show Volume Distribution.”
9. If the indicator disables the map and shows:
" Volume Distribution disabled: Too many price levels detected (>50). Try decreasing 'Ticks Per Row' or using a lower chart resolution. If you don’t care about the map, just turn off 'Show Volume Distribution'. "
— follow the instructions to reduce chart load.
Notes
* Automatically adapts to your chart’s resolution and data availability.
* If your symbol doesn’t provide volume data, a runtime warning will appear.
* Works best on futures , FX , and crypto instruments with high-frequency volume streams.
Why Traders Love It
AVDM combines adaptive resolution , volume delta analysis , and visual distribution mapping into one clean, efficient tool.
Perfect for traders studying:
* Market microstructure
* Aggressive vs. passive participation
* Volume absorption
* Order flow imbalance zones
* Delta-based divergence signals
Technical Highlights
* Built with Pine Script v6
* Adaptive resolution logic (`security_lower_tf`)
* Smart memory-safe map rendering
* Dynamic bid/ask classification
* Automatic overload protection
---
悟隐高阶战法//@version=5
indicator("悟隐高阶战法", shorttitle='HT', overlay=true, max_labels_count=500, max_bars_back=5000)
// 输入参数
count_bull = input.int(3, title='非连续阳线数量', group='设置')
count_bear = input.int(3, title='非连续阴线数量', group='设置')
show_points = input.bool(true, title='显示高低点')
show_lines = input.bool(true,title = '显示线条')
max_points = input.int(200, title='最大点数')
line_color = input.color(color.purple, "连线颜色")
line_width = input.int(2, "线宽", minval=1, maxval=4)
h_color=input.color(color.red,title = 'H点颜色')
h_trs=input.float(80,title = 'h点透明度')
l_color=input.color(color.green,title = 'L点颜色')
l_trs=input.float(80,title = 'L点透明度')
// 警报设置
enable_alerts = input.bool(true, title='启用警报', group='警报设置')
show_signals = input.bool(true, title='显示BUY/SELL标记', group='信号显示设置')
signal_size = input.string('normal', title='信号标记大小', options= , group='信号显示设置')
signal_distance = input.float(0.1, title='信号标记距K线距离(%)', minval=0.05, maxval=0.5, group='信号显示设置')
// 各信号显示开关
show_signal_yyx = input.bool(true, title='显示看跌【阴阳阴】', group='信号开关')
show_signal_ayy = input.bool(true, title='显示看涨【阳阴阳】', group='信号开关')
show_signal_bull_1v2 = input.bool(true, title='显示看涨【一大于二】', group='信号开关')
show_signal_bear_1v2 = input.bool(true, title='显示看跌【一大于二】', group='信号开关')
show_signal_bear_2v2 = input.bool(true, title='显示看跌【二大于二】', group='信号开关')
show_signal_bull_2v2 = input.bool(true, title='显示看涨【二大于二】', group='信号开关')
show_signal_bull_engulf = input.bool(true, title='显示看涨吞没【吞没随阴线】', group='信号开关')
show_signal_bear_engulf = input.bool(true, title='显示看跌【吞没随阳线】', group='信号开关')
// 子条件显示开关
show_signal_bear_2v2_c1 = input.bool(true, title='看跌【二大于二】-条件1', group='子条件开关')
show_signal_bear_2v2_c2 = input.bool(true, title='看跌【二大于二】-条件2', group='子条件开关')
show_signal_bull_2v2_c1 = input.bool(true, title='看涨【二大于二】-条件1', group='子条件开关')
show_signal_bull_2v2_c2 = input.bool(true, title='看涨【二大于二】-条件2', group='子条件开关')
// ------------------ 自定义数据类型 ------------------
type RecordPrice
int bar_index
float open_price
float high_price
float low_price
float close_price
type Extremum
chart.point pt
string kind // "high" 或 "low"
type ABCPoints
float price_a
int index_a
float price_b
int index_b
float price_c
int index_c
string trend_type // "bull" 或 "bear"
bool broken // 是否被突破
// ------------------ 数组初始化 ------------------
var bullRecords = array.new()
var bearRecords = array.new()
var allPoints = array.new() // 存储所有高低点
var label pointLabels = array.new() // 存储绘制的标签，方便清理
var abcBullPoints = ABCPoints.new() // 存储牛市ABC点
var abcBearPoints = ABCPoints.new() // 存储熊市ABC点
// 存储黄线和标签的引用
var line yellowLines = array.new()
var label yellowLabels = array.new()
// 存储绿线和标签的引用
var line greenLines = array.new()
var label greenLabels = array.new()
// 突破状态变量
var bool cBroken = false
var int breakBarIndex = na
var bool fBroken = false
var int breakBarIndexBear = na
// 信号检测变量
var string currentSignal = ""
var string alertMessage = ""
var bool buySignal = false
var bool sellSignal = false
// ------------------ 状态变量 ------------------
var string lastPosition = "none"
var float lastHigh = na
var int lastHighBarIndex = na
var float lastLow = na
var int lastLowBarIndex = na
var float currentHigh = 0.0
var float currentLow = 0.0
var int currentHighBar = 0
var int currentLowBar = 0
// 使用Map存储每根K线是否创新高/新低
var map newHighMap = map.new()
var map newLowMap = map.new()
// 初始化
if barstate.isfirst
currentHigh := high
currentLow := low
currentHighBar := bar_index
currentLowBar := bar_index
// 更新区间高低并标记
bool isNewHigh = false
bool isNewLow = false
if high > currentHigh
currentHigh := high
currentHighBar := bar_index
isNewHigh := true
if low < currentLow
currentLow := low
currentLowBar := bar_index
isNewLow := true
// 存储当前K线的标记
map.put(newHighMap, bar_index, isNewHigh)
map.put(newLowMap, bar_index, isNewLow)
// ------------------ 方法 ------------------
method putRecord(array arr, int bar_idx, float open_pr, float high_pr, float low_pr, float close_pr) =>
newRecord = RecordPrice.new()
newRecord.bar_index := bar_idx
newRecord.open_price := open_pr
newRecord.high_price := high_pr
newRecord.low_price := low_pr
newRecord.close_price := close_pr
array.push(arr, newRecord)
method getRecord(array arr, int index) =>
if array.size(arr) > index and index >= 0
array.get(arr, index)
else
na
method removeRecord(array arr, int index) =>
if array.size(arr) > index and index >= 0
array.remove(arr, index)
method getLastRecord(array arr) =>
int size = array.size(arr)
if size > 0
array.get(arr, size - 1)
else
na
method isIncreasingLastN(array arr, int N) =>
if array.size(arr) < N
false
else
inc = true
for i = array.size(arr) - N to array.size(arr) - 2
prev = arr.getRecord(i)
curr = arr.getRecord(i + 1)
if curr.high_price <= prev.high_price
inc := false
break
inc
method isDecreasingLastN(array arr, int N) =>
if array.size(arr) < N
false
else
dec = true
for i = array.size(arr) - N to array.size(arr) - 2
prev = arr.getRecord(i)
curr = arr.getRecord(i + 1)
if curr.low_price >= prev.low_price
dec := false
break
dec
// 删除所有黄线和标签的方法
deleteYellowLinesAndLabels() =>
// 删除黄线
if array.size(yellowLines) > 0
for i = 0 to array.size(yellowLines) - 1
line l = array.get(yellowLines, i)
if not na(l)
line.delete(l)
array.clear(yellowLines)
// 删除标签
if array.size(yellowLabels) > 0
for i = 0 to array.size(yellowLabels) - 1
label lab = array.get(yellowLabels, i)
if not na(lab)
label.delete(lab)
array.clear(yellowLabels)
// 删除所有绿线和标签的方法
deleteGreenLinesAndLabels() =>
// 删除绿线
if array.size(greenLines) > 0
for i = 0 to array.size(greenLines) - 1
line l = array.get(greenLines, i)
if not na(l)
line.delete(l)
array.clear(greenLines)
// 删除标签
if array.size(greenLabels) > 0
for i = 0 to array.size(greenLabels) - 1
label lab = array.get(greenLabels, i)
if not na(lab)
label.delete(lab)
array.clear(greenLabels)
// 辅助函数：判断K线类型
isBullish(int offset = 0) =>
close > open
isBearish(int offset = 0) =>
close < open
// 辅助函数：获取当前趋势
getCurrentTrend() =>
if lastPosition == "low"
"uptrend" // 上涨趋势
else if lastPosition == "high"
"downtrend" // 下跌趋势
else
"none"
// 辅助函数：检查指定偏移的K线是否创过新高
wasNewHigh(int offset) =>
int targetBarIndex = bar_index - offset
bool result = false
if map.contains(newHighMap, targetBarIndex)
result := map.get(newHighMap, targetBarIndex)
result
// 辅助函数：检查指定偏移的K线是否创过新低
wasNewLow(int offset) =>
int targetBarIndex = bar_index - offset
bool result = false
if map.contains(newLowMap, targetBarIndex)
result := map.get(newLowMap, targetBarIndex)
result
// 辅助函数：检查过去N根K线中是否有创新高
hasNewHigh(int lookback = 3) =>
bool newHigh = false
for i = 0 to lookback - 1
if wasNewHigh(i)
newHigh := true
break
newHigh
// 辅助函数：检查过去N根K线中是否有创新低
hasNewLow(int lookback = 3) =>
bool newLow = false
for i = 0 to lookback - 1
if wasNewLow(i)
newLow := true
break
newLow
// 辅助函数：在过去5根K线中检查阴阳阴组合且有新高（相对于趋势起点）
checkBearishYYXPattern() =>
bool hasPattern = false
bool hasHighInRange = false
// 检查过去5根K线中是否有创新高
for i = 0 to 4
if wasNewHigh(i)
hasHighInRange := true
break
if hasHighInRange
// 检查过去3根K线的阴阳阴组合
if isBearish(0) and isBullish(1) and isBearish(2)
hasPattern := true
hasPattern
// 辅助函数：在过去5根K线中检查阳阴阳组合且有新低（相对于趋势起点）
checkBullishAYYPattern() =>
bool hasPattern = false
bool hasLowInRange = false
// 检查过去5根K线中是否有创新低
for i = 0 to 4
if wasNewLow(i)
hasLowInRange := true
break
if hasLowInRange
// 检查过去3根K线的阳阴阳组合
if isBullish(0) and isBearish(1) and isBullish(2)
hasPattern := true
hasPattern
// 辅助函数：检查是否是看涨吞没形态
isBullishEngulf(int offset = 0) =>
// 当前K线是阳线
isBullish(offset) and
// 吞没前一根K线
high > high and low < low and
// 确保只吞没前一根，不吞没前二根
not (high > high and low < low )
// 辅助函数：检查是否是看跌吞没形态
isBearishEngulf(int offset = 0) =>
// 当前K线是阴线
isBearish(offset) and
// 吞没前一根K线
high > high and low < low and
// 确保只吞没前一根，不吞没前二根
not (high > high and low < low )
// ------------------ 阳线/阴线处理 ------------------
if close > open
bullRecords.putRecord(bar_index, open, high, low, close)
if array.size(bullRecords) > count_bull
bullRecords.removeRecord(0)
if close < open
bearRecords.putRecord(bar_index, open, high, low, close)
if array.size(bearRecords) > count_bear
bearRecords.removeRecord(0)
// 做一个统计 ,记录当时的高价
var int count_long=na
var int count_short=na
var float high_price=na
var float low_price=na
// ------------------ 寻找低点 ------------------
if array.size(bullRecords) >= count_bull and bullRecords.isIncreasingLastN(count_bull) and close > open
if (lastPosition == "none" or lastPosition == "high") and low!=currentLow and bullRecords.first().bar_index >= currentLowBar
lastPosition := "low"
lastLow := currentLow
lastLowBarIndex := currentLowBar
if array.size(allPoints) >= max_points
array.shift(allPoints)
array.push(allPoints, Extremum.new(chart.point.from_index(lastLowBarIndex, lastLow), "low"))
currentHigh := high
currentHighBar := bar_index
count_long:=0
high_price:=high
// ------------------ 寻找高点 ------------------
if array.size(bearRecords) >= count_bear and bearRecords.isDecreasingLastN(count_bear) and close < open
if (lastPosition == "none" or lastPosition == "low") and high!=currentHigh and bearRecords.first().bar_index >= currentHighBar
lastPosition := "high"
lastHigh := currentHigh
lastHighBarIndex := currentHighBar
if array.size(allPoints) >= max_points
array.shift(allPoints)
array.push(allPoints, Extremum.new(chart.point.from_index(lastHighBarIndex, lastHigh), "high"))
currentLow := low
currentLowBar := bar_index
count_short:=0
low_price:=low
// ------------------ 绘制 ------------------
if barstate.islast and array.size(allPoints) > 1
// 删除旧的标签
for l in pointLabels
label.delete(l)
array.clear(pointLabels)
// 历史折线
if array.size(allPoints) > 2 and show_lines
tmpPts = array.new()
for i = 0 to array.size(allPoints)-2
ex = array.get(allPoints, i)
array.push(tmpPts, ex.pt)
polyline.new(tmpPts, xloc=xloc.bar_index, line_color=line_color, line_width=line_width)
// 最后一段线
if array.size(allPoints) >= 2 and show_lines
ex1 = array.get(allPoints, array.size(allPoints)-2)
ex2 = array.get(allPoints, array.size(allPoints)-1)
line.new(x1=ex1.pt.index, y1=ex1.pt.price, x2=ex2.pt.index, y2=ex2.pt.price,
xloc=xloc.bar_index, color=line_color, width=line_width)
// 高低点标签
if show_points
for i = 0 to array.size(allPoints)-1
ex = array.get(allPoints, i)
label lbl = na
if ex.kind == "low"
lbl := label.new(ex.pt.index, ex.pt.price, text=str.tostring(ex.pt.price),
style=label.style_label_up, color=color.new(color.green,80), textcolor=color.white)
else
lbl := label.new(ex.pt.index, ex.pt.price, text=str.tostring(ex.pt.price),
style=label.style_label_down, color=color.new(color.red,80), textcolor=color.white)
array.push(pointLabels,lbl)
// ------------------ 虚线预测段 ------------------
var line lastDashedLine = na
var label lastDashedLabel = na
if barstate.islast and array.size(allPoints) > 0
lastEx = array.get(allPoints, array.size(allPoints)-1)
if lastEx.kind == "low" and show_lines
if not na(lastDashedLine)
line.delete(lastDashedLine)
lastDashedLine := line.new(lastEx.pt.index, lastEx.pt.price, currentHighBar, currentHigh,
xloc=xloc.bar_index, color=line_color, width=line_width, style=line.style_dashed)
if show_points
if not na(lastDashedLabel)
label.delete(lastDashedLabel)
lastDashedLabel := label.new(lastEx.pt.index, lastEx.pt.price, text='H',
style=label.style_label_down, color=color.new(h_color,h_trs), textcolor=color.white)
if lastEx.kind == "high" and show_lines
if not na(lastDashedLine)
line.delete(lastDashedLine)
lastDashedLine := line.new(lastEx.pt.index, lastEx.pt.price, currentLowBar, currentLow,
xloc=xloc.bar_index, color=line_color, width=line_width, style=line.style_dashed)
if show_points
if not na(lastDashedLabel)
label.delete(lastDashedLabel)
lastDashedLabel := label.new(currentLowBar, currentLow, text='L',
style=label.style_label_up, color=color.new(l_color,l_trs), textcolor=color.white)
// ------------------ 信号检测逻辑 ------------------
// 重置信号
buySignal := false
sellSignal := false
currentSignal := ""
alertMessage := ""
if enable_alerts and bar_index >= 2
// 获取当前趋势
trend = getCurrentTrend()
// 信号1：看跌【阴阳阴】- 上涨趋势中，过去5根K线中有新高且出现阴线-阳线-阴线组合
if show_signal_yyx and trend == "uptrend" and checkBearishYYXPattern()
sellSignal := true
currentSignal := "SELL"
alertMessage := "看跌【阴阳阴】"
// 信号2：看涨【阳阴阳】- 下跌趋势中，过去5根K线中有新低且出现阳线-阴线-阳线组合
if show_signal_ayy and trend == "downtrend" and checkBullishAYYPattern()
buySignal := true
currentSignal := "BUY"
alertMessage := "看涨【阳阴阳】"
// 信号3：看涨【一大于二】- 下跌趋势中创新低，出现阳线，左边2根K至少有一根阴线
if show_signal_bull_1v2 and trend == "downtrend" and isBullish(0) and (isBearish(1) or isBearish(2)) and hasNewLow(3)
// 条件1：阳线实体最高价(收盘价)大于左边2根K实体最高价且实体最低价(开盘价)小于左边2根K实体最低价
condition1 = close > math.max(close , open ) and close > math.max(close , open ) and
open < math.min(close , open ) and open < math.min(close , open )
// 条件2：阳线最高价分别大于左边2根K最高价且最低价分别小于左边2根K最低价
condition2 = high > high and high > high and low < low and low < low
if condition1 or condition2
buySignal := true
currentSignal := "BUY"
alertMessage := "看涨【一大于二】"
// 信号4：看跌【一大于二】- 上涨趋势中，出现阴线，左边2根K至少有一根阳线
if show_signal_bear_1v2 and trend == "uptrend" and isBearish(0) and (isBullish(1) or isBullish(2)) and hasNewHigh(3)
// 条件1：阴线实体最高价(开盘价)大于左边2根K实体最高价且实体最低价(收盘价)小于左边2根K实体最低价
condition1 = open > math.max(close , open ) and open > math.max(close , open ) and
close < math.min(close , open ) and close < math.min(close , open )
// 条件2：阴线最高价分别大于左边2根K最高价且最低价分别小于左边2根K最低价
condition2 = high > high and high > high and low < low and low < low
if condition1 or condition2
sellSignal := true
currentSignal := "SELL"
alertMessage := "看跌【一大于二】"
// 信号5：看跌【二大于二】- 上涨趋势中
if show_signal_bear_2v2 and trend == "uptrend" and bar_index >= 3
// 条件1：连续2根阴线收盘价低于左边2根K线，且4根K线前3根必须有一根创新高（相对于趋势起点）
condition1 = show_signal_bear_2v2_c1 and isBearish(0) and isBearish(1) and
close < close and close < close and close < close and close < close and
(wasNewHigh(1) or wasNewHigh(2) or wasNewHigh(3))
// 条件2：连续2根阳线后再连续2根阴线，2根阴线最低价低于前面2根阳线最低价，最高价大于前面2根阳线最高价，中间2根K必须有一根创新高（相对于趋势起点）
condition2 = show_signal_bear_2v2_c2 and isBearish(0) and isBearish(1) and isBullish(2) and isBullish(3) and
math.min(low, low ) < math.min(low , low ) and
math.max(high, high ) > math.max(high , high ) and
(wasNewHigh(1) or wasNewHigh(2))
if condition1 or condition2
sellSignal := true
currentSignal := "SELL"
alertMessage := "看跌【二大于二】" + (condition1 ? "-条件1" : "") + (condition2 ? "-条件2" : "")
// 信号6：看涨【二大于二】- 下跌趋势中
if show_signal_bull_2v2 and trend == "downtrend" and bar_index >= 3
// 条件1：连续2根阳线收盘价高于左边2根K线，且4根K线前3根必须有一根创新低（相对于趋势起点）
condition1 = show_signal_bull_2v2_c1 and isBullish(0) and isBullish(1) and
close > close and close > close and close > close and close > close and
(wasNewLow(1) or wasNewLow(2) or wasNewLow(3))
// 条件2：连续2根阴线后再连续2根阳线，2根阳线最低价低于前面2根阴线最低价，最高价大于前面2根阴线最高价，中间2根K必须有一根创新低（相对于趋势起点）
condition2 = show_signal_bull_2v2_c2 and isBullish(0) and isBullish(1) and isBearish(2) and isBearish(3) and
math.min(low, low ) < math.min(low , low ) and
math.max(high, high ) > math.max(high , high ) and
(wasNewLow(1) or wasNewLow(2))
if condition1 or condition2
buySignal := true
currentSignal := "BUY"
alertMessage := "看涨【二大于二】" + (condition1 ? "-条件1" : "") + (condition2 ? "-条件2" : "")
// 信号7：看跌【吞没随阴线】- 上涨趋势中阳线吞没前一根K线，阳线后出现阴线，且有一根K创新高
if show_signal_bull_engulf and trend == "uptrend" and bar_index >= 2 and
isBullishEngulf(1) and isBearish(0) and hasNewHigh(3)
sellSignal := true
currentSignal := "SELL"
alertMessage := "看跌【吞没随阴线】"
// 信号8：看涨【吞没随阳线】- 下跌趋势中阴线吞没前一根K线，阴线后出现阳线，且有一根K创新低
if show_signal_bear_engulf and trend == "downtrend" and bar_index >= 2 and
isBearishEngulf(1) and isBullish(0) and hasNewLow(3)
buySignal := true
currentSignal := "BUY"
alertMessage := "看涨【吞没随阳线】"
// ------------------ BUY/SELL标记显示 ------------------
if show_signals
// 根据signal_size设置标记大小
labelSize = switch signal_size
"tiny" => size.tiny
"small" => size.small
"normal" => size.normal
"large" => size.large
"huge" => size.huge
=> size.normal
// 显示BUY信号
if buySignal
label.new(bar_index, low - (high - low) * signal_distance, text="BUY",
style=label.style_label_up, color=color.new(color.green, 0),
textcolor=color.white, size=labelSize, tooltip=alertMessage)
// 显示SELL信号
if sellSignal
label.new(bar_index, high + (high - low) * signal_distance, text="SELL",
style=label.style_label_down, color=color.new(color.red, 0),
textcolor=color.white, size=labelSize, tooltip=alertMessage)
// ------------------ TradingView警报条件 ------------------
// 检查是否有启用的买入/卖出信号（包括子条件）
enabledBuySignals = show_signal_ayy or
(show_signal_bull_1v2 ) or
(show_signal_bull_2v2 and (show_signal_bull_2v2_c1 or show_signal_bull_2v2_c2)) or
show_signal_bear_engulf
enabledSellSignals = show_signal_yyx or
(show_signal_bear_1v2) or
(show_signal_bear_2v2 and (show_signal_bear_2v2_c1 or show_signal_bear_2v2_c2)) or
show_signal_bull_engulf
// 买入信号警报
alertcondition(enable_alerts and enabledBuySignals and buySignal, title="买入信号", message="{{alertMessage}}")
// 卖出信号警报
alertcondition(enable_alerts and enabledSellSignals and sellSignal, title="卖出信号", message="{{alertMessage}}")
// 所有信号的通用警报
alertcondition(enable_alerts and (enabledBuySignals and buySignal or enabledSellSignals and sellSignal), title="所有交易信号",
message="信号类型: {{currentSignal}}, 详情: {{alertMessage}}")
// 具体的信号类型警报
alertcondition(enable_alerts and show_signal_ayy and buySignal and str.contains(alertMessage, "阳阴阳"), title="看涨【阳阴阳】", message="看涨【阳阴阳】")
alertcondition(enable_alerts and show_signal_yyx and sellSignal and str.contains(alertMessage, "阴阳阴"), title="看跌【阴阳阴】", message="看跌【阴阳阴】")
alertcondition(enable_alerts and show_signal_bull_1v2 and buySignal and str.contains(alertMessage, "一大于二"), title="看涨【一大于二】", message="看涨【一大于二】")
alertcondition(enable_alerts and show_signal_bear_1v2 and sellSignal and str.contains(alertMessage, "一大于二"), title="看跌【一大于二】", message="看跌【一大于二】")
alertcondition(enable_alerts and show_signal_bull_2v2 and buySignal and str.contains(alertMessage, "二大于二"), title="看涨【二大于二】", message="看涨【二大于二】")
alertcondition(enable_alerts and show_signal_bear_2v2 and sellSignal and str.contains(alertMessage, "二大于二"), title="看跌【二大于二】", message="看跌【二大于二】")
alertcondition(enable_alerts and show_signal_bull_engulf and sellSignal and str.contains(alertMessage, "吞没随阴线"), title="看涨吞没【吞没随阴线】", message="看涨吞没【吞没随阴线】")
alertcondition(enable_alerts and show_signal_bear_engulf and buySignal and str.contains(alertMessage, "吞没随阳线"), title="看跌【吞没随阳线】", message="看跌【吞没随阳线】")
RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
________________________________________
What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
________________________________________
Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
________________________________________
Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
________________________________________
TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
________________________________________
Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
________________________________________
Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
________________________________________
Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
MRL Slim — SuperBuy/Sell + Bands (v6.4)MRL — Mean Reversion Bands + Super Buy/Sell (RSI-10)
What it does
This overlay plots a mean-reversion line (linear regression of price) with k·σ bands and adds clean RSI-10 signals on the chart.
Signals (tags on price):
SB = Super Buy: fires when RSI(10) (on close) crosses down through your oversold threshold (default 29).
– Capped to 2 touches per cycle; the cycle resets when RSI crosses above 50 (configurable).
SS = Super Sell (71): fires when RSI(10) crosses up through your overbought threshold (default 71).
SS80 = Super Sell (Hard):
– Fires on cross above 80, and (optionally) again while RSI ≥ 80 using a cooldown to prevent spam.
– Per-cycle cap = 2 by default; you can let hard sells bypass the cap.
Bands & Source
Bands are built around a linreg mean of your chosen Source (default hlc3).
Toggle Log Space to make bands act percent-like on long histories/trending assets.
Filters (optional)
Price ≥ Upper Band required for sells.
Mean slope down required for sells.
(Disable if you want every RSI event, even in strong trends.)
Debug (optional)
Turn on Debug to see raw RSI crosses/touches and why a signal was blocked (e.g., cap, band, slope, cooldown).
Separate toggle to show/hide CAP dots.
Tips
For fast charts or very strong momentum, consider loosening the sell filters or shortening the HARD cooldown.
If your panel RSI shows signals you don’t see on price: ensure you’re comparing RSI(10, close) on the same timeframe.
Disclaimer
For research/education only. Not financial advice; always manage risk.
Volume Footprint Anomaly Scanner [PhenLabs]📊 PhenLabs - Volume Footprint Anomaly Scanner (VFAS)
Version: PineScript™ v6
📌 Description
The PhenLabs Volume Footprint Anomaly Scanner (VFAS) is an advanced Pine Script indicator designed to detect and highlight significant imbalances in buying and selling pressure within individual price bars. By analyzing a calculated "Delta" – the net difference between estimated buy and sell volume – and employing statistical Z-score analysis, VFAS pinpoints moments when buying or selling activity becomes unusually dominant. This script was created not in hopes of creating a "Buy and Sell" indicator but rather providing the user with a more in-depth insight into the intrabar volume delta and how it can fluctuate in unusual ways, leading to anomalies that can be capitalized on.
This indicator helps traders identify high-conviction points where strong market participants are active, signaling potential shifts in momentum or continuation of a trend. It aims to provide a clearer understanding of underlying market dynamics, allowing for more informed decision-making in various trading strategies, from identifying entry points to confirming trend strength.
🚀 Points of Innovation
● Z-Score for Delta Analysis : Utilizes statistical Z-scores to objectively identify statistically significant anomalies in buying/selling pressure, moving beyond simple, arbitrary thresholds.
● Dynamic Confidence Scoring : Assigns a multi-star confidence rating (1-4 stars) to each signal, factoring in high volume, trend alignment, and specific confirmation criteria, providing a nuanced view of signal strength.
● Integrated Trend Filtering : Offers an optional Exponential Moving Average (EMA)-based trend filter to ensure signals align with the broader market direction, reducing false positives in ranging markets.
● Strict Confirmation Logic : Implements specific confirmation criteria for higher-confidence signals, including price action and a time-based gap from previous signals, enhancing reliability.
● Intuitive Info Dashboard : Provides a real-time summary of market trend and the latest signal's direction and confidence directly on the chart, streamlining information access.
🔧 Core Components
● Core Delta Engine : Estimates the net buying/selling pressure (bar Delta) by analyzing price movement within each bar relative to volume. It also calculates average volume to identify bars with unusually high activity.
● Anomaly Detection (Z-Score) : Computes the Z-score for the current bar's Delta, indicating how many standard deviations it is from its recent average. This statistical measure is central to identifying significant anomalies.
● Trend Filter : Utilizes a dual Exponential Moving Average (EMA) cross-over system to define the prevailing market trend (uptrend, downtrend, or range), providing contextual awareness.
● Signal Processing & Confidence Algorithm : Evaluates anomaly conditions against trend filters and confirmation rules, then calculates a dynamic confidence score to produce actionable, contextualized signal information.
🔥 Key Features
● Advanced Delta Anomaly Detection : Pinpoints bars with exceptionally high buying or selling pressure, indicating potential institutional activity or strong market conviction.
● Multi-Factor Confidence Scoring : Each signal comes with a 1-4 star rating, clearly communicating its reliability based on high volume, trend alignment, and specific confirmation criteria.
● Optional Trend Alignment : Users can choose to filter signals, so only those aligned with the prevailing EMA-defined trend are displayed, enhancing signal quality.
● Interactive Signal Labels : Displays compact labels on the chart at anomaly points, offering detailed tooltips upon hover, including signal type, direction, confidence, and contextual information.
● Customizable Bar Colors : Visually highlights bars with Delta anomalies, providing an immediate visual cue for strong buying or selling activity.
● Real-time Info Dashboard : A clean, customizable dashboard shows the current market trend and details of the latest detected signal, keeping key information accessible at a glance.
● Configurable Alerts : Set up alerts for bullish or bearish Delta anomalies to receive real-time notifications when significant market pressure shifts occur.
🎨 Visualization
Signal Labels :
* Placed at the top/bottom of anomaly bars, showing a "📈" (bullish) or "📉" (bearish) icon.
* Tooltip: Hovering over a label reveals detailed information: Signal Type (e.g., "Delta Anomaly"), Direction, Confidence (e.g., "★★★☆"), and a descriptive explanation of the anomaly.
* Interpretation: Clearly marks actionable signals and provides deep insights without cluttering the chart, enabling quick assessment of signal strength and context.
● Info Dashboard :
* Located at the top-right of the chart, providing a clean summary.
* Displays: "PhenLabs - VFAS" header, "Market Trend" (Uptrend/Downtrend/Range with color-coded status), and "Direction | Conf." (showing the last signal's direction and star confidence).
* Optional "💡 Hover over signals for details" reminder.
* Interpretation: A concise, real-time summary of the market's pulse and the most recent high-conviction event, helping traders stay informed at a glance.
📖 Usage Guidelines
Setting Categories
⚙️ Core Delta & Volume Engine
● Minimum Volume Lookback (Bars)
○ Default: 9
○ Range: Integer (e.g., 5-50)
○ Description: Defines the number of preceding bars used to calculate the average volume and delta. Bars with volume below this average won't be considered for high-volume signals. A shorter lookback is more reactive to recent changes, while a longer one provides a smoother average.
📈 Anomaly Detection Settings
Delta Z-Score Anomaly Threshold
○ Default: 2.5
○ Range: Float (e.g., 1.0-5.0+)
○ Description: The number of standard deviations from the mean that a bar's delta must exceed to be considered a significant anomaly. A higher threshold means fewer, but potentially stronger, signals. A lower threshold will generate more signals, which might include less significant events. Experiment to find the optimal balance for your trading style.
🔬 Context Filters
Enable Trend Filter
○ Default: False
○ Range: Boolean (True/False)
○ Description: When enabled, signals will only be generated if they align with the current market trend as determined by the EMAs (e.g., only bullish signals in an uptrend, bearish in a downtrend). This helps to filter out counter-trend noise.
● Trend EMA Fast
○ Default: 50
○ Range: Integer (e.g., 10-100)
○ Description: The period for the faster Exponential Moving Average used in the trend filter. In combination with the slow EMA, it defines the trend direction.
● Trend EMA Slow
○ Default: 200
○ Range: Integer (e.g., 100-400)
○ Description: The period for the slower Exponential Moving Average used in the trend filter. The relationship between the fast and slow EMA determines if the market is in an uptrend (fast > slow) or downtrend (fast < slow).
🎨 Visual & UI Settings
● Show Info Dashboard
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles the visibility of the dashboard on the chart, which provides a summary of market trend and the last detected signal.
● Show Dashboard Tooltip
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles a reminder message in the dashboard to hover over signal labels for more detailed information.
● Show Delta Anomaly Bar Colors
○ Default: True
○ Range: Boolean (True/False)
○ Description: Enables or disables the coloring of bars based on their delta direction and whether they represent a significant anomaly.
● Show Signal Labels
○ Default: True
○ Range: Boolean (True/False)
○ Description: Controls the visibility of the “📈” or “📉” labels that appear on the chart when a delta anomaly signal is generated.
🔔 Alert Settings
Alert on Delta Anomaly
○ Default: True
○ Range: Boolean (True/False)
○ Description: When enabled, this setting allows you to set up alerts in TradingView that will trigger whenever a new bullish or bearish delta anomaly is detected.
✅ Best Use Cases
Early Trend Reversal / Continuation Detection: Identify strong surges of buying/selling pressure at key support/resistance levels that could indicate a reversal or the continuation of a strong move.
● Confirmation of Breakouts: Use high-confidence delta anomalies to confirm the validity of price breakouts, indicating strong conviction behind the move.
● Entry and Exit Points: Pinpoint precise entry opportunities when anomalies align with your trading strategy, or identify potential exhaustion signals for exiting trades.
● Scalping and Day Trading: The indicator’s sensitivity to intraday buying/selling imbalances makes it highly effective for short-term trading strategies.
● Market Sentiment Analysis: Gain a real-time understanding of underlying market sentiment by observing the prevalence and strength of bullish vs. bearish anomalies.
⚠️ Limitations
Estimated Delta: The script uses a simplified method to estimate delta based on bar close relative to its range, not actual order book or footprint data. While effective, it’s an approximation.
● Sensitivity to Z-Score Threshold: The effectiveness heavily relies on the `Delta Z-Score Anomaly Threshold`. Too low, and you’ll get many false positives; too high, and you might miss valid signals.
● Confirmation Criteria: The 4-star confidence level’s “confirmation” relies on specific subsequent bar conditions and previous confirmed signals, which might be too strict or specific for all contexts.
● Requires Context: While powerful, VFAS is best used in conjunction with other technical analysis tools and price action to form a comprehensive trading strategy. It is not a standalone “buy/sell” signal.
💡 What Makes This Unique
Statistical Rigor: The application of Z-score analysis to bar delta provides an objective, statistically-driven way to identify true anomalies, moving beyond arbitrary thresholds.
● Multi-Factor Confidence Scoring: The unique 1-4 star confidence system integrates multiple market dynamics (volume, trend alignment, specific follow-through) into a single, easy-to-interpret rating.
● User-Friendly Design: From the intuitive dashboard to the detailed signal tooltips, the indicator prioritizes clear and accessible information for traders of all experience levels.
🔬 How It Works
1. Bar Delta Calculation:
● The script first estimates the “buy volume” and “sell volume” for each bar. This is done by assuming that volume proportional to the distance from the low to the close represents buying, and volume proportional to the distance from the high to the close represents selling.
● How this contributes: This provides a proxy for the net buying or selling pressure (delta) within that specific price bar, even without access to actual footprint data.
2. Volume & Delta Z-Score Analysis:
● The average volume over a user-defined lookback period is calculated. Bars with volume less than twice this average are generally considered of lower interest.
● The Z-score for the calculated bar delta is computed. The Z-score measures how many standard deviations the current bar’s delta is from its average delta over the `Minimum Volume Lookback` period.
● How this contributes: A high positive Z-score indicates a bullish delta anomaly (significantly more buying than usual), while a high negative Z-score indicates a bearish delta anomaly (significantly more selling than usual). This identifies statistically unusual levels of pressure.
3. Trend Filtering (Optional):
● Two Exponential Moving Averages (Fast and Slow EMA) are used to determine the prevailing market trend. An uptrend is identified when the Fast EMA is above the Slow EMA, and a downtrend when the Fast EMA is below the Slow EMA.
● How this contributes: If enabled, the indicator will only display bullish delta anomalies during an uptrend and bearish delta anomalies during a downtrend, helping to confirm signals within the broader market context and avoid counter-trend signals.
4. Signal Generation & Confidence Scoring:
● When a delta Z-score exceeds the user-defined anomaly threshold, a signal is generated.
● This signal is then passed through a multi-factor confidence algorithm (`f_calculateConfidence`). It awards stars based on: high volume presence, alignment with the overall trend (if enabled), and a fourth star for very strong Z-scores (above 3.0) combined with specific follow-through candle patterns after a cooling-off period from a previous confirmed signal.
● How this contributes: Provides a qualitative rating (1-4 stars) for each anomaly, allowing traders to quickly assess the potential significance and reliability of the signal.
💡 Note:
The PhenLabs Volume Footprint Anomaly Scanner is a powerful analytical tool, but it’s crucial to understand that no indicator guarantees profit. Always backtest and forward-test the indicator settings on your chosen assets and timeframes. Consider integrating VFAS with your existing trading strategy, using its signals as confirmation for entries, exits, or trend bias. The Z-score threshold is highly customizable; lower values will yield more signals (including potential noise), while higher values will provide fewer but potentially higher-conviction signals. Adjust this parameter based on market volatility and your risk tolerance. Remember to combine statistical insights from VFAS with price action, support/resistance levels, and your overall market outlook for optimal results.
LiquidEdge Original1️⃣ Why Most Traders Miss Key Market Turning Points
Most traders (you) struggle to identify true market pivots THE REAL TOP and BOTTOMS where reversals begin.
❌ You enter too early or too late because price alone doesn’t give enough confirmation
❌ You follow price blindly, unaware of the volume pressure building underneath
❌ You get caught in sideways markets, not realizing they’re often accumulation or distribution zones
❌ You can’t tell if momentum is building or fading, which leads to low confidence and inconsistent results
👉 LiquidEdge helps solve this by tracking volume momentum through a modified MFI slope and scoring system. It highlights potential pivots with real context, so you can see where smart money might be entering or exiting before price makes it obvious.
2️⃣ What LiquidEdge Actually Does and How
LiquidEdge helps solve common trading problems by adding structure and clarity to volume analysis.
✅ It builds on the classic Money Flow Index (MFI), but instead of just showing overbought/oversold levels, it calculates the slope of MFI to track real-time changes in volume momentum
✅ Each setup is scored based on a combination of factors: divergence strength, trend alignment using EMA, and whether the signal occurs inside a liquidity zone
✅ Hidden accumulation or distribution is revealed when volume pressure increases or fades while price remains flat or moves slightly, a sign of smart money positioning
✅ Divergences are only flagged when they occur near pivot zones and align with overall trend conditions, helping reduce false signals
✅ Potential pivots are identified when multiple factors overlap such as a liquidity zone breach, volume slope shift, and valid divergence which often signals entry or exit points for institutional players
👉 The result is a structured interpretation of price and volume flow, helping traders read momentum shifts and potential reversals more clearly in both trending and ranging markets.
3️⃣ What Makes LiquidEdge Different
LiquidEdge is built on top of the classic Money Flow Index (MFI), but adds structure that transforms it from a basic momentum tool into a decision-support system.
Instead of simply showing highs and lows, it scores each potential setup based on:
✅ The steepness and direction of the MFI slope (used to measure volume pressure)
✅ Whether the setup aligns with the broader trend using an EMA filter (default: 200 EMA)
✅ Whether the signal appears inside predefined liquidity zones (MFI above 80 or below 20)
👉 This scoring system reduces noise and helps you focus only on high-probability setups.
👉 It also checks volume pressure across multiple timeframes using MFI slope on 5M, 15M, 1H, 4H, and Daily charts. This reveals whether short-term moves are backed by longer-term volume momentum.
Color changes in the line and histogram are not decorative they reflect real shifts in volume pressure. Every visual cue is linked to live market logic.
What Makes It Stand Out
👉 Setup Scoring That Makes Sense
Each setup is scored by combining:
Signal strength (MFI slope intensity and stability)
Trend direction (via customizable EMA)
Liquidity zone relevance (MFI range filtering)
This structured scoring means you spend less time second-guessing and more time reading clean signals.
👉 Flow That Follows Real Momentum
The slope of the MFI tracks whether volume pressure is rising or falling:
🟢 Green = increasing inflow (buying pressure)
🔴 Red = increasing outflow (selling pressure)
👉 Multi-Timeframe Volume Context
LiquidEdge calculates flow direction independently on each major timeframe. You’ll know if short-term setups are confirmed by higher timeframe volume or going against it.
👉 Smart Divergence Filtering
Unlike simple divergence tools that compare price highs/lows directly, LiquidEdge filters divergences based on:
Local pivot zones (defined by lookback periods)
Trend confirmation (to eliminate countertrend noise)
4️⃣ How LiquidEdge Works (Under the Hood)
LiquidEdge tracks directional momentum using the slope of the Money Flow Index (MFI) giving you a real-time read on buying and selling pressure.
When the slope rises, it means buyers are stepping in and volume is supporting the move.
When it falls, sellers are taking control and volume outflow is increasing.
This slope acts like a pressure gauge for the market, helping you spot when a trend has strength or when it's starting to fade.
💡 Quick Comparison
RSI = momentum from price
MFI = momentum from price + volume
LiquidEdge takes it one step further by calculating the rate of change (slope) in MFI. That’s where the pressure signal comes from not just value, but directional flow.
Core Calculations (Simplified)
Typical Price = (High + Low + Close) ÷ 3
Raw Money Flow = Typical Price × Volume
MFI = 100 −
MFI ranges from 0 to 100.
High = strong buying volume
Low = growing selling pressure
LiquidEdge then calculates the slope of this MFI over time to track volume momentum dynamically.
Divergence Engine
LiquidEdge detects divergence by comparing price pivots with the direction of MFI slope.
❌ If price makes a higher high but MFI slope turns down, it’s a bearish divergence
✅ If price makes a lower low but MFI slope rises, it’s a bullish divergence
Divergences are only confirmed when they occur:
Near local pivot zones (defined by configurable lookback windows)
And, optionally, in alignment with the broader trend using an EMA filter
This filtering helps reduce false positives and keeps you focused on clean setups.
Structured Confidence Scoring
Each signal is visually scored based on:
➡️ Whether a valid divergence is detected
➡️ Whether the signal occurs inside a liquidity zone (MFI > 80 or < 20)
➡️ Whether the setup aligns with the overall trend direction (EMA filter)
More confluence = higher confidence
The scoring system helps prioritize setups that meet multiple criteria, not just one.
Liquidity Zones
Above 80: Signals possible buying exhaustion 👉 risk of reversal
Below 20: Indicates potential selling exhaustion 👉 watch for a bounce
Zones are shaded directly on the chart to highlight pressure extremes in real time.
Price + Volume Fusion
LiquidEdge blends price action with volume pressure using MFI slope and histogram behavior. It doesn’t just show you where price is moving. it shows whether the move is backed by real volume.
This lets you see:
Whether volume is confirming or fading behind a move
If a reversal is building even before price confirms it
Visual Feedback That Speaks Clearly
🟢 Green slope = increasing buying pressure
🔴 Red slope = increasing selling pressure
5️⃣ When Price Is Flat but LiquidEdge Moves: Volume Tells the Truth
One of the most useful things LiquidEdge can do is reveal pressure shifts when price looks neutral.
If price is moving sideways but the MFI slope or histogram rises, it may suggest that buying pressure is quietly increasing possibly pointing to early accumulation.
If price stays flat while the volume slope or histogram drops, this could indicate distribution, where sellers are exiting without moving the market noticeably.
These changes don’t guarantee a breakout or breakdown, but they often precede key moves especially when combined with other confluences like trend alignment or liquidity zones.
👉 LiquidEdge helps spot these setups by measuring volume momentum shifts beneath price action.
It doesn’t predict the future, but it gives you additional context to evaluate what may be developing before it’s visible on price alone.
6️⃣ Multi-Timeframe Flow Table
LiquidEdge includes a real-time table that tracks volume pressure across multiple timeframes including 5-minute, 15-minute, 1-hour, 4-hour, and daily charts.
Each row reflects the direction of the MFI slope on that timeframe, indicating whether volume pressure is increasing (inflow) or decreasing (outflow).
🟢 A rising slope suggests that buying momentum is building
🔴 A falling slope suggests selling pressure may be increasing
👉 This lets traders quickly assess whether short-term setups are aligned with higher timeframe volume trends a useful layer of confirmation for both intraday and swing strategies.
Rather than flipping between charts, the table gives you a snapshot of flow strength across the board, helping you stay focused on opportunities that align with broader market pressure.
7️⃣ Timeframes & Assets
Where LiquidEdge Works Best:
✅ Crypto: Supports major coins and high-volume altcoins (BTC, ETH, Top 100)
✅ Stocks: Effective on large-cap and mid-cap equities with consistent volume
✅ Futures: Tested on instruments like NQ, MNQ, ES, and MES
✅ Any liquid market where volume data is reliable and stable
For best results, use LiquidEdge on assets with consistent trading volume. It’s not recommended for ultra-low volume crypto pairs or micro-cap stocks, where irregular volume can distort signals.
Recommended Timeframes:
👉 Intraday trading: Works well on 3-minute, 5-minute, 15-minute, and 1-hour charts
👉 Swing trading: Performs reliably on 4-hour, daily, and weekly charts
👉 Ultra short-term (1-minute or less): Not recommended due to high noise and low reliability
LiquidEdge adapts to various trading styles from scalping short-term momentum shifts to analyzing broader volume trends across swing and positional setups. The key is choosing assets and timeframes with reliable volume flow for the tool to work effectively.
8️⃣ Common Mistakes to Avoid When Using LiquidEdge
❌ Using It in Isolation
LiquidEdge offers valuable context, but it’s not designed to function as a standalone trading system. Always combine it with key tools such as trendlines, support/resistance zones, chart structure, or fundamental data. The more supporting evidence you have, the stronger your analysis becomes.
❌ Relying on a Single Indicator
No indicator, including LiquidEdge, can account for every market condition. It’s important to use it alongside other forms of confirmation to avoid making decisions based on limited data.
❌ Misinterpreting Divergences as Reversals
A divergence between price and volume pressure doesn't always signal the end of a trend. If the broader direction remains strong (based on EMAs or higher timeframe volume flow), a divergence could reflect temporary consolidation rather than reversal.
❌ Ignoring Trend Alignment and Confidence Scoring
LiquidEdge includes confidence scoring to help validate signals. Disregarding this structure can lead to reacting to weak or out-of-context divergences, especially in choppy or low-volume environments.
❌ Using It on Second-Based or Tick Charts
Very low timeframes introduce too much noise, which can distort volume slope and divergence signals. For intraday analysis, start with 3-minute charts or higher. For swing trading, use 4H and up for clearer, more reliable structure.
9️⃣ LiquidEdge Settings Overview
A quick breakdown of what you can customize in the indicator and how each option affects what you see:
➡️ LiquidEdge Length
Controls how sensitive the indicator is to changes in volume pressure (via MFI slope).
Shorter values = faster response, more frequent signals
Longer values = smoother output, less noise
👉 Default: 14
➡️ EMA Trend Filter
Determines overall trend direction based on EMA slope. Used to filter out signals that go against the broader move.
Helps reduce countertrend entries
Adjustable to suit your strategy
👉 Recommended: 200 EMA
➡️ Pivot Lookback (Left & Right)
Defines how many bars the system looks back and forward to identify swing highs/lows for divergence detection.
Narrow: more responsive but can be noisy
Wide: slower but more stable pivot zones
👉 Default: 5 left / 5 right
➡️ Histogram Toggle
Enables a visual histogram showing how volume pressure deviates from its recent average.
Useful for spotting shifts in flow intensity
👉 Optional for added visual detail
➡️ Liquidity Zones
Highlights potential exhaustion zones based on MFI value:
Above 80 = potential distribution (buying pressure peaking)
Below 20 = possible accumulation (selling pressure fading)
👉 Zones are fully customizable (color, opacity, background)
➡️ Custom Threshold Zones
Set your own upper/lower boundaries for liquidity extremes helpful when adapting to different markets or asset classes.
👉 Especially useful outside of crypto/forex
➡️ Show LiquidEdge Line
Toggle the main MFI slope line. When turned off, liquidity zones and levels also disappear.
👉 Use if you prefer to focus only on histogram/divergences
➡️ Style Settings
Customize line colors, histogram appearance, and background shading
👉 Helps tailor visuals to your chart layout
➡️ Simplified Mode
Removes all colors and replaces visuals with a clean, grayscale output.
👉 Ideal for minimalist or distraction-free charting
➡️ Signal Score Label
Displays the confidence score of the current setup, based on:
Divergence presence
Liquidity zone positioning
Trend alignment (EMA)
👉 Tooltip explains how the score is calculated
➡️ Divergence Labels
Shows “Bullish” or “Bearish” labels at divergence points.
Optional Filters based on trend if EMA filter is active
➡️ Multi-Timeframe Flow Table
Shows directional flow (based on MFI slope) across: 5M, 15M, 1H, 4H, 1D
Color-coded (faded green/red) for clarity
👉 Table position is customizable on your chart
➡️ Alerts
Get notified when any of these conditions are met:
✅ Bullish or bearish divergence detected
✅ Price enters high/low liquidity zones
✅ Signal score reaches a defined value
➡️ Visibility Settings
Control which timeframes display the LiquidEdge indicator
👉 Best used on 3-minute and above
⚠️ Not recommended on ultra-low or second-based charts due to noise
🔟 Q&A – What Traders Usually Ask
➡️ Can this help reduce bad trades?
To a degree, yes. LiquidEdge is built to highlight areas where price may react, based on volume pressure, liquidity zones, and divergence patterns. It can offer clarity in sideways or messy markets, helping traders avoid impulsive or poorly timed entries.
That said, it’s not predictive or guaranteed. It works best when used with broader context including structure, support/resistance, trend, and volume-based confluence.
👉 Reminder: LiquidEdge is not a signal tool. It’s a decision-support framework designed to help you assess potential shifts, not replace judgment or trading rules.
➡️ Is this just another flashy signal tool?
No. LiquidEdge doesn’t give buy/sell alerts. Instead, it visualizes volume shifts using MFI slope, divergence filtering, and trend-based scoring. It’s built to help you understand why price action may be changing not just react to a one-dimensional signal.
You’re seeing how volume pressure evolves across timeframes, which gives added context to what’s unfolding in the market.
➡️ How do I know this isn’t just another overhyped tool?
LiquidEdge is based on real trading logic: volume pressure (via MFI slope), price behavior, and divergence within trend and liquidity zones. It was developed and tested by traders, not packaged by marketers.
No performance is guaranteed. It’s designed to support your decisions not promise results.
➡️ Will this work with my trading style?
If you trade any market with volume crypto, stocks, or futures LiquidEdge can add value.
✔️ Scalpers: Best from 3-minute and up
✔️ Swing traders: Works well on 4H, Daily, Weekly
✔️ Investors: Weekly charts show pressure buildup over time
⚠️ Avoid ultra-low timeframes (under 1M) or illiquid markets, as noise and irregular data can reduce reliability.
➡️ Can I trust the signals?
These are not buy/sell signals. LiquidEdge offers confidence-weighted insights based on:
✔️ Valid divergence
✔️ Zone positioning (above 80 / below 20)
✔️ Optional trend alignment (via EMA)
Each setup is scored visually to reflect how much confluence exists. You can combine that information with structure, price action, or your existing tools to evaluate opportunities.
👉 Think of LiquidEdge as a decision filter not a trigger.
It’s meant to slow down impulsive trades and help you make more context-aware decisions.
1️⃣1️⃣ Limitations – Know When It’s Less Effective
LiquidEdge performs best in stable, high-volume markets where volume data is consistent and structure is visible.
It’s not recommended for:
❌ Low-volume tokens
❌ Micro-cap or penny stocks
❌ Newly listed assets with limited trading history
These types of markets often show inconsistent or erratic volume behavior, making it difficult for LiquidEdge to accurately assess pressure or identify reliable divergences.
⚠️ During major news events or sudden volatility spikes, volume and price behavior can become disconnected or extreme. This may distort MFI slope calculations and reduce the accuracy of divergence or confidence scoring.
LiquidEdge is built to read structured volume flow. When market conditions become highly erratic or unpredictable, it's best to:
Wait for structure to return
Use it alongside other filters for additional confirmation
This isn't a flaw it's simply the nature of tools that rely on consistency in price and volume data.
1️⃣2️⃣ Real Chart Examples – See It in Action
Now that you’ve seen how LiquidEdge works, here are real-world chart examples from various asset classes
including:
✅ Crypto
✅ Stocks
✅ Futures
✅ Commodities
These examples demonstrate how LiquidEdge behaves under different conditions, and how both the line (MFI slope) and histogram (volume deviation) can be used to interpret market flow.
In each walkthrough, you’ll see:
How the histogram can highlight potential momentum shifts
When the slope line provides stronger directional clarity
Examples of possible hidden accumulation or distribution (before price responds)
What to watch out for such as weak volume, false divergences, or conflicting flow signals
👉 These are real examples based on live market data not theoretical setups. They’re meant to help you recognize how LiquidEdge reacts across multiple styles and timeframes.
Let’s walk through each one and break down the logic step by step, so you can understand how to evaluate setups using structure, volume behavior, and context-driven confluence.
Example: Microsoft (MSFT) – Possible Hidden Accumulation
In this setup, price was moving lower within a short-term downtrend. However, LiquidEdge began showing signs of increasing inflow pressure a common characteristic of accumulation, where volume rises even as price declines.
This divergence suggested that buying interest may have been increasing behind the scenes, despite weak price action on the surface.
Step-by-step breakdown:
👉 Trend context – Price was clearly trending down at the time
👉 Volume divergence – Price made lower lows, but LiquidEdge slope was rising = possible bullish divergence
👉 Accumulation clue – The rising slope, despite falling price, pointed to volume inflow often seen during quiet accumulation
👉 Histogram support – Volume pressure (via the histogram) also increased, confirming the flow shift
👉 Anticipating reaction – When liquidity pressure rises ahead of price, it can signal potential reversal interest
In this case, price later moved sharply higher. While not guaranteed, setups like this illustrate how divergence + volume flow may help highlight early accumulation zones before price confirms the shift.
Same Setup – Focusing on the Histogram Alone
Here, we’re revisiting the Microsoft setup but this time focusing only on the histogram, without the MFI slope line.
Even without the directional slope, the histogram showed rising volume pressure while price continued to drift lower. This visual pattern may indicate that buying interest was quietly increasing, despite weak price movement.
This is where the histogram adds value: it helps visualize the intensity of volume flow over time. When volume pressure builds during a flat or declining price phase, it can be consistent with accumulation where larger participants begin positioning before the market responds.
This example highlights how the histogram alone can provide early insight into underlying volume dynamics even before price shifts noticeably.
Filtering with EMA and why It Matters
Here, we revisit the Microsoft example this time applying the 200 EMA filter, which helps define the broader trend.
Once enabled, LiquidEdge automatically removed any bullish or bearish divergence signals that were against the prevailing trend. This helped reduce noise and focus only on setups aligned with market structure.
✅ The EMA acts as a contextual filter.
For example, if a bullish divergence occurs during a confirmed downtrend, LiquidEdge suppresses that signal helping you avoid setups that may carry more risk.
This filtering mechanism is especially useful in fast or choppy markets, where not all divergences are meaningful.
Want More Flexibility? Adjust the Filter
If you're a more aggressive trader or prefer shorter-term signals, you can reduce the EMA length (e.g., to 150, 50, or even 25). This increases the number of setups shown but also raises the importance of additional context and confirmation.
⚠️ Keep in mind:
❌ More signals doesn’t always mean better outcomes
✅ Focused, context-aware signals tend to be more consistent with broader market pressure
If you’re using this in combination with strategies like options trading, this filter can help refine your entry zones especially when paired with other structure or volatility tools.
Distribution Example and Bitcoin Setup Before a Major Drop
In this example, Bitcoin was trading in a relatively tight range while price continued to push upward. However, LiquidEdge began to show signs of volume outflow, which can suggest potential distribution.
Here’s what was observed:
🔴 Price was moving up inside a horizontal range
🔴 LiquidEdge’s slope indicated declining volume pressure
🔴 Several bearish divergence signals appeared during this consolidation phase
🔴 The histogram also showed weakening flow, even before price broke down
These overlapping signals pointed to a possible distribution phase, where buying momentum was fading despite price still holding up.
🧭 Signs to Watch for in Potential Distribution:
1️⃣ Price holding flat or rising slightly within a tight range
2️⃣ Volume pressure (line or histogram) sloping downward
3️⃣ Repeated bearish divergences forming at the highs
4️⃣ Lack of follow-through on bullish setups signaling hesitation in demand
While LiquidEdge can’t predict market outcomes, this scenario demonstrates how a combination of divergence, outflow, and failure to break out may serve as early warnings that momentum is shifting beneath the surface.
Failed Auction Example – Volume Shift Before a Breakdown
In this example, price attempted to break out above a recent high, creating the appearance of a bullish continuation. However, LiquidEdge began to signal volume outflow, despite the upward price move a potential sign of a failed auction.
Here’s what was observed:
👉 Price made a new high, appearing to break resistance
👉 LiquidEdge slope and histogram both showed declining liquidity
👉 The indicator formed lower lows, even as price pushed higher
👉 This divergence suggested that volume wasn’t supporting the breakout
Shortly after, price reversed and returned back inside the range which is a common characteristic of failed auction behavior.
🧭 Spotting a Potential Failed Auction with LiquidEdge:
1️⃣ Price breaks above a recent high
2️⃣ Volume flow (line + histogram) shows outflow, not inflow
3️⃣ Indicator forms lower lows while price makes higher highs (bearish divergence)
4️⃣ Market reverts back into the previous range without follow-through
While no tool can predict outcomes, this setup demonstrated how volume pressure and divergence can help identify moments where a breakout may lack real support offering context before price action confirms the shift.
Reading the Histogram - Spotting Pressure Fades
In this example, price was still rising but the LiquidEdge histogram showed falling volume pressure. This type of divergence between price and volume can serve as a potential early signal that momentum may be fading.
🔻 Histogram levels declined while price continued higher
🔻 This suggested that buying pressure was weakening, even though price hadn’t turned
🔻 Volume flow behavior didn’t support the continuation possibly indicating buyer exhaustion
Just before the peak, the histogram nearly reached its lower threshold, despite price still being near its highs.
💡 How to Read It:
When volume pressure (shown by the histogram) starts to fade while price is still rising, it can indicate that momentum is weakening. This may precede a pullback or reversal particularly if other factors like divergence or zone exhaustion are also present.
Conversely, rising histogram values during a price drop may suggest potential accumulation.
👉 Use the histogram as a volume intensity gauge, not a signal on its own especially when evaluating whether a move is supported by actual flow, or just price momentum.
The Table – Fast, Visual Multi-Timeframe Flow Insight
The multi-timeframe flow table in LiquidEdge provides a consolidated view of volume momentum across several key timeframes so you don’t need to switch between charts to compare flow strength.
👉 Instead of flipping from 5-minute to 15M, 1H, 4H, and Daily, the table displays flow direction on all of them at a glance.
Example layout:
🔼 Daily: Up
🔽 1H: Down
🔼 15M: Up
🔽 5M: Down
This setup gives you a quick read on whether volume momentum is aligned across multiple timeframes or diverging which can help frame your trade approach.
🧠 Why It’s Useful:
✅ Supports timeframe alignment
If higher timeframes show strong inflow while lower ones are mixed, you may interpret it as a swing-based opportunity. If short timeframes show pressure but higher frames are flat, it might suggest short-term setups with caution.
✅ Improves context awareness
Instead of interpreting a move in isolation, the table helps you assess whether short-term signals are part of a broader shift or going against higher timeframe flow.
💡 Pro Tip: Use the table as a starting point in your analysis. It’s a simple but effective snapshot of current liquidity pressure across the board helping you plan trades with broader context, rather than reacting chart-by-chart.
🔚 Final Thoughts
If you're focused on trading with better clarity and structure, LiquidEdge is designed to help you interpret what’s happening beneath the surface not just follow price movement.
While many tools highlight price alone, LiquidEdge combines volume pressure, divergence filtering, and trend-based context to help identify potential areas of accumulation, distribution, or momentum shifts even before they become obvious on a chart.
👉 This isn’t just another signal tool. It’s a framework to support smarter decision-making:
✔️ One that helps you filter out noise
✔️ One that scores setups using multiple layers of confirmation
✔️ One that brings volume context into every trade idea
Whether you're scalping on a 5-minute chart or managing a longer-term swing trade, LiquidEdge is built to help you stay aligned with volume-driven behavior not just react to price alone.
If you've struggled with late entries, unreliable setups, or second-guessing trades, this tool was designed to bring more structure to your process. It won’t remove all uncertainty but it can help you stay more selective, confident, and intentional.
✅ Trade with clarity
✅ Stay process-driven
✅ Focus on structure, not noise
LiquidEdge is not meant to replace your strategy. It’s here to enhance it.
In this chart, the 200 EMA filter was applied. As a result, only signals that aligned with the dominant trend direction were displayed helping to reduce distractions and focus on setups with stronger context.
💡 Using a higher EMA setting like 200 can reduce the number of signals shown, but may help you focus on higher-conviction opportunities.
That said, every trader is different:
Longer EMAs = fewer signals, but more trend-filtered setups
Shorter EMAs = more signals, faster entries but with potentially more noise
👉 Adjust the filter based on your trading style. Use a 200 EMA for swing trading, or reduce it to 50, 25, or even 5 if you're trading more aggressively or intraday.
LiquidEdge adapts to you not the other way around.
🔁 Adjusting EMA for Your Trading Style
Personal Tip: When trading more aggressively, I often use a 5 EMA filter especially when combining histogram strength with other tools. This increases signal responsiveness and may help highlight short-term flow shifts more quickly.
Below are visual examples that show how different EMA lengths impact the behavior of LiquidEdge:
50 EMA ON
25 EMA ON
5 EMA ON
Lower EMA Example – Gold with the 5 EMA
In this example, the 5 EMA filter was applied to Gold. As expected, more signals were plotted compared to higher EMA settings. The tool became more responsive to rapid shifts in volume momentum, making it more suitable for fast-paced trading environments.
This setting can help traders who prefer early entries but it also introduces more sensitivity, so context and additional confirmation become even more important.
Each setting affects signal frequency and filtering:
Higher EMA → fewer signals, more trend-confirmed setups
Lower EMA → more signals, quicker responses, but with more potential for noise
Choose what fits your approach:
Long-term swing → Stick with 200 EMA
Intraday or scalping → Consider shorter EMAs (50, 25, or 5)
💡 Reminder: EMA filtering is fully adjustable. LiquidEdge doesn’t lock you into one trading style it’s meant to adapt to your process, whether you’re swing trading or scalping short-term moves.
But There’s a Catch…
Using a lower EMA setting (like 5) opens up faster, more frequent signals but it also increases the need for precision and stronger trade management.
❗ More signals = More responsiveness
❗ Faster setups mean quicker decisions
❗ Risk control becomes even more important
💡 Lower Timeframes = More Detail, Less Margin for Error
A short EMA (like 5) can help you:
✅ Identify early momentum shifts
✅ Respond before traditional trend-followers
✅ Highlight short-term divergence and volume changes
But it also comes with tradeoffs:
❌ Greater signal noise
❌ Higher potential for misreads or fakeouts
❌ Requires clear structure and disciplined entries
🚩 Watch Out for Liquidity Grabs
In lower timeframes, a common trap is the liquidity grab where price pushes beyond recent highs or lows, triggers stops, then quickly reverses.
📌 These moves can look like breakouts, but often reverse quickly possibly reflecting institutional order placement or low-liquidity manipulation.
🧭 How to Approach It Smartly
✅ Use structure: Mark support and resistance to frame moves
✅ Confirm volume behavior: Is histogram strength rising or fading?
✅ Avoid chasing: Look for confluence, not just a single signal
✅ Be intentional with stops: Place them with structure in mind to avoid being swept out
NASDAQ Futures Example – Low Timeframe Setups with LiquidEdge
In this example, we look at how LiquidEdge was used to identify both short and long setups on the NASDAQ Futures (NQ) particularly on a low timeframe (5M), where quick decision-making and volume precision matter most.
⚠️ A Note on Futures and Volume
When trading futures, especially on intraday charts, it’s important to separate overnight volume from regular session activity.
🕒 Overnight Volume ≠ Real Volume Context
Overnight price action is informative, but the volume data itself may not reflect true market participation. In LiquidEdge, histogram and pressure calculations emphasize regular session flow helping avoid skewed signals that could come from low-volume overnight moves.
Using the Histogram to Spot Potential Shifts
One of the key cues I use is color transition in the histogram:
🔴 A flip from strong green to red can signal fading buying pressure, sometimes marking the beginning of a potential short setup.
🟢 A shift from red to green may indicate that buyers are returning, suggesting possible accumulation.
These shifts serve as early visual cues of changing pressure especially when confirmed by other tools or context.
🔁 Adding Context with the Line + Structure
After spotting a histogram shift, I look at:
1️⃣ Slope Line – Is it confirming the same directional pressure?
2️⃣ Support/Resistance – Are we near a meaningful zone?
3️⃣ Additional Tools – This includes trendlines, VWAP, EMAs, and overall price structure.
On lower timeframes like 5M, these pieces become even more important. LiquidEdge gives directional insight, but your full setup provides confirmation and execution logic.
⚠️ Disclaimer
LiquidEdge is not a signal tool. It’s a visual representation of market pressure and flow designed to help you make more informed trading and investing decisions. It shows you what’s happening beneath the price action but you are still responsible for your decisions.
Always combine LiquidEdge with your own strategy, research, and supporting tools. That includes trend analysis, support/resistance levels, chart patterns, and fundamentals (like P/E ratios, price-to-sales, debt ratios, etc.).
This tool should never be used alone or treated as financial advice.
Some content may include AI-powered enhancements for clarity or formatting.
Always do your own research. For personal financial guidance, speak with a licensed financial advisor.
Polarity-VoVix Fusion Index (PVFI) Polarity-VoVix Fusion Index (PVFI) - Order Flow and Volatility Regime Detector
The PVFI is a next-generation indicator that fuses the Order Flow Polarity Index (OFPI) with a proprietary VoVix Volume Delta (VVD) engine. This tool is designed for traders who want to see not just how much volume is trading, but who is in control and how volatility is shifting beneath the surface.
What Makes PVFI Standout from the rest?
- Dual Engine: PVFI combines two advanced signals:
* OFPI: Measures real-time buy/sell pressure using candle body position and volume, then smooths it with a T3 moving average for clarity and responsiveness.
* VVD: Captures the "volatility of volume delta" - a normalized, memory-boosted measure of aggressive buying/selling, with a custom non-linear clamp for organic, non-pegged signals.
- Visual Clarity: Neon-glow OFPI line and shadowed, color-gradient VVD area make regime shifts and momentum instantly visible.
- Adaptive Dashboard: Toggle between a full-featured dashboard (desktop) and a compact info line (mobile) for seamless use on any device.
- Universal: Works on any asset - crypto, stocks, futures, forex - and any timeframe.
- No Chart Clutter: Clean, modern visuals and toggles for a pro look.
Inputs:
OFPI Lookback Length (ofpi_len): Sets the window for order flow pressure calculation. Shorter = more sensitive, longer = smoother. For scalping, try 5-10. For swing trading, 15-30. Crypto often benefits from shorter windows due to volatility.
OFPI T3 Smoothing Length (t3_len): Controls the smoothness of the OFPI line. Lower = more responsive, higher = smoother. Use 3-7 for fast markets, 8-15 for slow or higher timeframes.
OFPI T3 Volume Factor (t3_vf): Adjusts the T3’s sensitivity. Higher = more responsive, lower = more stable. 0.6-0.8 is typical. Raise for more “snappy” signals, lower for less noise.
VVD Delta Lookback (delta_len): Sets the window for VVD’s volume delta calculation. 10-20 for most assets. Shorter for high-volatility, longer for slow markets.
VVD Volatility Normalization Length (vol_norm_len): Normalizes VVD by recent volume. 15-30 is typical. Use higher for assets with wild volume swings.
VVD Momentum Memory (momentum_mem): Adds a “memory” boost to VVD, amplifying persistent buying/selling. 2-5 is common. Lower for choppy markets, higher for trending.
Show Dashboard (showDash): Toggles the full dashboard table (best for desktop). Turn off for a minimalist or mobile setup.
Show Compact Info Line (showInfoLabel): Toggles a single-line info label (best for mobile). Turn on for mobile or minimalist setups.
How PVFI Works:
- OFPI Calculation: Splits each candle’s volume into buy/sell pressure based on where the close is within the range. Aggregates over your chosen lookback, then smooths with a T3 moving average for a neon, lag-minimized signal.
- VVD Calculation: Measures the “aggression” of volume (body-weighted), normalizes by recent volume, and applies a memory boost for persistent trends. Uses a custom tanh clamp for a natural, non-pegged range.
- Visuals: OFPI is plotted as a neon line (with glow). VVD is a color-gradient area with a soft shadow, instantly showing regime shifts.
- Dashboard/Info Line: Desktop: Full dashboard with all key stats, color-coded and branded. Mobile: Compact info line with arrows for quick reads.
How you'll use PVFI:
- Bullish OFPI (Teal Neon, Up Arrow): Buyers are dominating. Look for breakouts, trend continuations, or confirmation with your own system.
- Bearish OFPI (Green Neon, Down Arrow): Sellers are in control. Watch for breakdowns or short setups.
- VVD Positive (Teal Area): Aggressive buying is increasing. Confirm with price action.
- VVD Negative (Purple Area): Aggressive selling is increasing. Use for risk management or short bias.
- Neutral/Flat: Market is balanced or indecisive. Consider waiting for a clear regime shift.
- Dashboard/Info Line: Use the dashboard for full context, or the info line for a quick glance on mobile.
Tips:
- For scalping, use lower lookbacks and smoothing.
- For swing trading, increase lookbacks and smoothing for stability.
- Works on all assets and timeframes - tune to your style.
Why PVFI is Unique:
- Fusion of Order Flow and Volatility: No other indicator combines body-based order flow with a volatility-of-volume delta, both visualized with modern, pro-grade graphics.
- Adaptive, Not Static: PVFI adapts to market regime, not just price movement.
- Mobile-Ready: Dashboard and info line toggles for any device.
- No Chart Clutter: Clean, color-coded, and easy to read.
For Educational Use Only
PVFI is a research and educational tool, not financial advice. Always use proper risk management and combine with your own strategy.
Trade with clarity. Trade with edge.
— Dskyz , for DAFE Trading Systems
Puts vs Longs vs Price Oscillator SwiftEdgeWhat is this Indicator?
The "Low-Latency Puts vs Longs vs Price Oscillator" is a custom technical indicator built for TradingView to help traders visualize buying and selling activity in a market without access to order book data. It displays three lines in an oscillator below the price chart:
Green Line (Longs): Represents the strength of buying activity (bullish pressure).
Red Line (Puts): Represents the strength of selling activity (bearish pressure).
Yellow Line (Price): Shows the asset’s price in a scaled format for direct comparison.
The indicator uses price movements, volume, and momentum to estimate when buyers or sellers are active, providing a quick snapshot of market dynamics. It’s optimized for fast response to price changes (low latency), making it useful for both short-term and longer-term trading strategies.
How Does it Work?
Since TradingView doesn’t provide direct access to order book data (which shows real-time buy and sell orders), this indicator approximates buying and selling pressure using commonly available data: price, volume, and a momentum measure called Rate of Change (ROC). Here’s how it combines these elements:
Price Movement: The indicator checks if the price is rising or falling compared to the previous candlestick. A rising price suggests buying (longs), while a falling price suggests selling (puts).
Volume: Volume acts as a "weight" to measure the strength of these price moves. Higher volume during a price increase boosts the green line, while higher volume during a price decrease boosts the red line. This mimics how large orders in an order book would influence the market.
Rate of Change (ROC): ROC measures how fast the price is changing over a set period (e.g., 5 candlesticks). It adds a momentum filter—strong upward momentum reinforces buying signals, while strong downward momentum reinforces selling signals.
These components are calculated for each candlestick and summed over a short lookback period (e.g., 5 candlesticks) to create the green and red lines. The yellow line is simply the asset’s closing price scaled down to fit the oscillator’s range, allowing you to compare buying/selling strength directly with price action.
Why Combine These Elements?
The combination of price, volume, and ROC is intentional and synergistic:
Price alone isn’t enough—it tells you what happened but not how strong the move was.
Volume adds context by showing the intensity behind price changes, much like how order book volume indicates real buying or selling interest.
ROC ensures the indicator captures momentum, filtering out weak or random price moves and focusing on significant trends, similar to how aggressive order execution might appear in an order book.
Together, they create a balanced picture of market activity that’s more reliable than any single factor alone. The goal is to simulate the insights you’d get from an order book—where you’d see buy/sell imbalances—using data available in TradingView.
How to Use It
Setup:
Add the indicator to your chart via TradingView’s Pine Editor by copying and pasting the script.
Adjust the inputs to suit your trading style:
Lookback Period: Number of candlesticks (default 5) to sum buying/selling activity. Shorter = more responsive; longer = smoother.
Price Scale Factor: Scales the yellow price line (default 0.001). Increase for high-priced assets (e.g., 0.01 for indices like DAX) or decrease for low-priced ones (e.g., 0.0001 for crypto).
ROC Period: Candlesticks for momentum calculation (default 5). Shorter = faster response.
ROC Weight: How much momentum affects the signal (default 0.5). Higher = stronger momentum influence.
Volume Threshold: Minimum volume multiplier (default 1.5) to boost signals during high activity.
Reading the Oscillator:
Green Line Above Yellow: Strong buying pressure—price is rising with volume and momentum support. Consider this a bullish signal.
Red Line Above Yellow: Strong selling pressure—price is falling with volume and momentum support. Consider this a bearish signal.
Green/Red Crossovers: When the green line crosses above the red, it suggests buyers are taking control. When the red crosses above the green, sellers may be dominating.
Yellow Line Context: Compare green/red lines to the yellow price line to see if buying/selling strength aligns with price trends.
Trading Examples:
Bullish Setup: Green line spikes above yellow after a price breakout with high volume (e.g., DAX opening jump). Enter a long position if confirmed by other indicators.
Bearish Setup: Red line rises above yellow during a price drop with increasing volume. Look for a short opportunity.
Reversal Warning: If the green line stays high while price (yellow) flattens or drops, it could signal overbought conditions—be cautious.
What Makes It Unique?
Unlike traditional oscillators like RSI or MACD, which focus solely on price momentum or trends, this indicator blends price, volume, and momentum into a three-line system that mimics order book dynamics. Its low-latency design (short lookback and no heavy smoothing) makes it react quickly to market shifts, ideal for volatile markets like DAX or forex. The visual separation of buying (green) and selling (red) against price (yellow) offers a clear, intuitive way to spot imbalances without needing complex data.
Tips and Customization
Volatile Markets: Use a shorter lookback (e.g., 3) and ROC period (e.g., 3) for faster signals.
Stable Markets: Increase lookback (e.g., 10) for smoother, less noisy lines.
Scaling: If the green/red lines dwarf the yellow, adjust Price Scale Factor up (e.g., 0.01) to balance them.
Experiment: Test on your asset (stocks, crypto, indices) and tweak inputs to match its behavior.
Time x Sales)Time x Sales Indicator (Enhanced Features)
This indicator displays a real-time Time and Sales (T&S) table with 10 columns: Timestamp, Price, Size (with arrows), Filled At (red for Ask, blue for Bid), Bid Size, Bid, Ask, Ask Size, Trades, and Average. It features dynamic color intensity, volume trend in the header, customizable themes (Basic, Dark Mode, Light Mode, Minimalist, Vibrant), highlighting for large trades, alternating row colors, thousands separators, and adjustable price decimals for enhanced trading analysis.
How to Use the Time x Sales Indicator
View the Table: The Time and Sales table appears on your chart (default: top-right) with 10 columns, each showing specific trade data:
Timestamp: Displays the time of each trade (e.g., "HH:MM:SS MM/DD"). Use this to track when trades occur.
Price: Shows the price at which the trade executed. Compare prices to see price movement trends.
Size: Indicates the trade volume (number of contracts/shares) with an arrow (↑ for price increase, ↓ for decrease, — for no change). Higher sizes suggest stronger market activity.
Filled At: Marks if the trade was at the "Bid" (blue, buyer-initiated) or "Ask" (red, seller-initiated). This helps identify buying or selling pressure.
Bid Size: Simulated size of buy orders at the bid price. Larger numbers indicate stronger buying interest.
Bid: Simulated bid price (slightly below the current price). It represents the highest price buyers are willing to pay.
Ask: Simulated ask price (slightly above the current price). It shows the lowest price sellers are offering.
Ask Size: Simulated size of sell orders at the ask price. Larger numbers suggest more selling interest.
Trades: Counts the number of trades in the update period. A higher count indicates more frequent trading activity.
Average: Shows the average trade size in the update period. Use this to gauge typical trade volume.
Customize Settings:
Adjust table position, number of rows, and sort order (Newest First/Last) in the indicator settings.
Set price decimal places and enable/disable thousands separators.
Choose a color theme (e.g., Dark Mode) and toggle buy/sell colors or dynamic intensity.
Highlight trades by setting size or price thresholds.
Monitor Trades: Watch the table update in real-time, with volume trends in the header (↑ for increasing, ↓ for decreasing, — for stable) and color-coded Filled At (red for Ask, blue for Bid).
Adjust Responsiveness: If updates are slow, reduce the "Update Cooldown (ms)" value in the settings (e.g., to 0 or 50) for faster refreshes.
Volume Delta & Order Block Suite [QuantAlgo]Upgrade your volume analysis and order flow trading with Volume Delta & Order Block Suite by QuantAlgo, a sophisticated technical indicator that leverages advanced volume delta calculations, along with dynamic order block detection to provide deep insights into market participant behavior. By calculating the distribution of volume between buyers and sellers and tracking pivotal volume zones, the indicator helps traders understand the underlying forces driving price movements. It is particularly valuable for those looking to identify high-probability trading opportunities based on volume imbalances and key price levels where significant activity has occurred.
🟢 Technical Foundation
The Volume Delta & Order Block Suite utilizes sophisticated volume analysis techniques to estimate buying and selling pressure within each price candle. The core volume delta calculation employs a formula that estimates buy volume as: Volume × (Close - Low) ÷ (High - Low) , with sell volume calculated as the remainder of total volume. This approach assumes that when price closes near the high of a candle, most volume represents buying pressure, and when price closes near the low, most volume represents selling pressure.
For order block detection, the indicator implements a multi-step process involving volume pivot identification and price state tracking. It first detects significant volume pivot points using the ta.pivothigh function with a user-defined pivot period. It then tracks the market's order state based on whether the high exceeds the highest high or the low falls below the lowest low. When a volume pivot occurs, the indicator creates order blocks based on price levels at that pivot point. These blocks are continuously monitored for invalidation based on subsequent price action.
🟢 Key Features & Signals
1. Volume Delta Representation on Candles
The Volume Delta visualization on candles shows the buy/sell distribution directly on price bars, creating an immediate visual representation of volume pressure.
When buyers are dominant, candles are colored with the bullish theme color (default: green/teal).
Similarly, when sellers are dominant, candles are colored with the bearish theme color (default: red).
This visualization provides immediate insights into underlying volume pressure without requiring separate indicators, helping traders quickly identify which side of the market is in control.
2. Buy/Sell Pressure Information Table
The Volume Analysis Table provides a comprehensive breakdown of volume metrics across multiple timeframes, helping traders identify shifts in market behavior.
The table is organized into four timeframe columns:
Current Volume
1 Bar Before
1 Day Before
1 Week Before
For each timeframe, the table displays:
Buy volume: The estimated buying volume based on price action
Sell volume: The estimated selling volume based on price action
Total volume: The sum of buy and sell volume
Delta: The difference between buy and sell volume (positive when buyers are dominant, negative when sellers are dominant)
Additionally, the table shows both absolute values and percentage distributions, with trend indicators (Up, Down, or Neutral) at the bottom row of each timeframe column.
This multi-timeframe approach helps traders:
→ Identify volume imbalances between buyers and sellers
→ Track changes in volume delta across different periods
→ Compare current conditions with historical patterns
→ Detect potential reversals by watching for shifts in delta direction
The delta values are particularly useful as they provide a clear indication of market dominance – positive delta (Up) when buyers are dominant, and negative delta (Down) when sellers are dominant.
3. Order Blocks and Their Confluence
Order blocks represent significant price zones where volume pivots occur, potentially indicating areas of significant market participant activity.
The indicator identifies two types of order blocks:
Bullish Order Blocks (support): Highlighted with a green/teal color, these represent potential support areas where price might bounce when revisited
Bearish Order Blocks (resistance): Highlighted with a red color, these represent potential resistance areas where price might reverse when revisited
Each order block is visualized as a colored rectangle with a dashed line showing the average price within the block. The blocks are extended to the right until they are invalidated.
Order blocks can serve as key reference points for trading decisions, for example:
Support/resistance identification
Stop loss placement (beyond the opposite edge of the block)
Potential reversal zones
Target areas for profit-taking
When price approaches an order block, traders should look for confluence with the volume delta on candles and the information in the volume analysis table. Strong setups occur when all three components align – for example, when price approaches a bearish order block with increasing sell volume shown on the candles and in the volume table.
🟢 Practical Usage Tips
→ Volume Analysis and Interpretation: The indicator visualizes the buy/sell volume ratio directly on price candles using color intensity, allowing traders to immediately identify which side (buyers or sellers) is dominant. This information helps in assessing the strength behind price movements and potential continuation or reversal signals.
→ Order Block Trading Strategies: The indicator highlights significant price zones where volume pivots occur, marking these as potential support (bullish order blocks) or resistance (bearish order blocks). Traders can use these levels to identify potential reversal points, stop placement, and profit targets.
→ Multi-timeframe Volume Comparison: Through its comprehensive volume analysis table, the indicator enables traders to compare volume patterns across current, recent, daily, and weekly timeframes. This helps in identifying shifts in market behavior and confirming the strength of ongoing trends.
🟢 Pro Tips
Adjust Pivot Period based on your timeframe:
→ Lower values (3-5) for more frequent order blocks
→ Higher values (7-10) for stronger, less frequent order blocks
Fine-tune Mitigation Method based on your trading style:
→ "Wick" for more conservative invalidation
→ "Close" for more lenient order block survival
Look for confluence between components:
→ Strong volume delta in the expected direction when price touches an order block
→ Corresponding patterns in the volume analysis table
→ Overall market context aligning with the expected direction
Use for multiple trading approaches:
→ Support/resistance trading at order blocks
→ Trend confirmation with volume delta
→ Reversal detection when volume delta changes direction
→ Stop loss placement using order block boundaries
Combine with:
→ Trend analysis using trend-following indicators for trade confirmation
→ Multiple timeframe analysis for strategic context
Twiggs Money FlowTwiggs Money Flow (TMF)
This indicator is an implementation of the Twiggs Money Flow (TMF), a volume-based tool designed to measure buying and selling pressure over a specified period. TMF is an enhancement of Chaikin Money Flow (CMF), utilizing more sophisticated smoothing techniques for improved accuracy and reduced noise. This version is highly customizable and includes advanced features for both new and experienced traders.
What is Twiggs Money Flow?
Twiggs Money Flow was developed by Colin Twiggs to provide a clearer picture of market momentum and the balance between buyers and sellers. It uses a combination of price action, trading volume, and range calculations to assess whether a market is under buying or selling pressure.
Unlike traditional volume indicators, TMF incorporates Weighted Moving Averages (WMA) by default but allows for other moving average types (SMA, EMA, VWMA) for added flexibility. This makes it adaptable to various trading styles and market conditions.
Features of This Script:
Customizable Moving Average Types:
Select from SMA , EMA , WMA , or VWMA to smooth volume and price-based calculations.
Tailor the indicator to align with your trading strategy or the asset's behavior.
Optional HMA Smoothing:
Apply Hull Moving Average (HMA) smoothing for a cleaner, faster-reacting TMF line.
Perfect for traders who want to reduce lag and capture trends earlier.
Dynamic Thresholds for Signal Filtering:
Set user-defined thresholds for Long (LT) and Short (ST) signals to highlight significant momentum.
Focus on actionable trends by ignoring noise around neutral levels.
Bar Coloring for Visual Clarity:
Automatically colors your chart bars based on TMF values:
Aqua for strong bullish signals (above the long threshold).
Fuchsia for strong bearish signals (below the short threshold).
Gray for neutral or undecided market conditions.
Ensures that trend direction and strength are visually intuitive.
Configurable Lookback Period:
Adjust the sensitivity of TMF by customizing the length of the lookback period to suit different timeframes and market conditions.
How It Works:
True Range Calculation: The script determines the high, low, and close range to calculate buying and selling pressure.
Adjusted Volume: Incorporates the relationship between price and volume to gauge whether trading activity is favoring buyers or sellers.
Weighted Moving Averages (WMAs): Smooths both volume and adjusted volume values to eliminate erratic fluctuations.
TMF Line: Computes the ratio of adjusted volume to total volume, representing the net buying/selling pressure as a percentage.
HMA Option (if enabled): Smooths the TMF line further to reduce lag and enhance trend identification.
Bar Coloring Logic:
Bars are colored dynamically based on TMF values, thresholds, and smoothing preferences.
Provides an at-a-glance understanding of market conditions.
Input Parameters:
Lookback Period: Defines the number of bars used to calculate TMF (default: 21).
Use HMA Smoothing: Toggle Hull Moving Average smoothing (default: true).
HMA Smoothing Length: Length of the HMA smoothing period (default: 14).
Moving Average Type: Select SMA, EMA, WMA, or VWMA (default: WMA).
Long Threshold (LT): Threshold value above which a long signal is considered (default: 0).
Short Threshold (ST): Threshold value below which a short signal is considered (default: 0).
How to Use It:
Confirm Trends: TMF can validate trends by identifying periods of sustained buying or selling pressure.
Divergence Signals: Watch for divergences between price and TMF to anticipate potential reversals.
Filter Trades: Use the thresholds to ignore weak signals and focus on strong trends.
Combine with Other Indicators: Pair TMF with trend-following or momentum indicators (e.g., RSI, Bollinger Bands) for a comprehensive trading strategy.
Example Use Cases:
Spotting breakouts when TMF crosses above the long threshold.
Identifying sell-offs when TMF dips below the short threshold.
Avoiding sideways markets by ignoring neutral (gray) bars.
Notes:
This indicator is highly customizable, making it versatile across different assets (e.g., stocks, crypto, forex).
While the default settings are robust, tweaking the lookback period, moving average type, and thresholds is recommended for different trading instruments or strategies.
Always backtest thoroughly before applying the indicator to live trading.
This version of Twiggs Money Flow goes beyond standard implementations by offering advanced smoothing, custom thresholds, and enhanced visual feedback to give traders a competitive edge.
Add it to your charts and experience the power of volume-driven analysis!
Quantify [Entry Model] | FractalystWhat’s the indicator’s purpose and functionality?
Quantify is a machine learning entry model designed to help traders identify high-probability setups to refine their strategies.
➙ Simply pick your bias, select your entry timeframes, and let Quantify handle the rest for you.
Can the indicator be applied to any market approach/trading strategy?
Absolutely, all trading strategies share one fundamental element: Directional Bias
Once you’ve determined the market bias using your own personal approach, whether it’s through technical analysis or fundamental analysis, select the trend direction in the Quantify user inputs.
The algorithm will then adjust its calculations to provide optimal entry levels aligned with your chosen bias. This involves analyzing historical patterns to identify setups with the highest potential expected values, ensuring your setups are aligned with the selected direction.
Can the indicator be used for different timeframes or trading styles?
Yes, regardless of the timeframe you’d like to take your entries, the indicator adapts to your trading style.
Whether you’re a swing trader, scalper, or even a position trader, the algorithm dynamically evaluates market conditions across your chosen timeframe.
How can this indicator help me to refine my trading strategy?
1. Focus on Positive Expected Value
• The indicator evaluates every setup to ensure it has a positive expected value, helping you focus only on trades that statistically favor long-term profitability.
2. Adapt to Market Conditions
• By analyzing real-time market behavior and historical patterns, the algorithm adjusts its calculations to match current conditions, keeping your strategy relevant and adaptable.
3. Eliminate Emotional Bias
• With clear probabilities, expected values, and data-driven insights, the indicator removes guesswork and helps you avoid emotional decisions that can damage your edge.
4. Optimize Entry Levels
• The indicator identifies optimal entry levels based on your selected bias and timeframes, improving robustness in your trades.
5. Enhance Risk Management
• Using tools like the Kelly Criterion, the indicator suggests optimal position sizes and risk levels, ensuring that your strategy maintains consistency and discipline.
6. Avoid Overtrading
• By highlighting only high-potential setups, the indicator keeps you focused on quality over quantity, helping you refine your strategy and avoid unnecessary losses.
How can I get started to use the indicator for my entries?
1. Set Your Market Bias
• Determine whether the market trend is Bullish or Bearish using your own approach.
• Select the corresponding bias in the indicator’s user inputs to align it with your analysis.
2. Choose Your Entry Timeframes
• Specify the timeframes you want to focus on for trade entries.
• The indicator will dynamically analyze these timeframes to provide optimal setups.
3. Let the Algorithm Analyze
• Quantify evaluates historical data and real-time price action to calculate probabilities and expected values.
• It highlights setups with the highest potential based on your selected bias and timeframes.
4. Refine Your Entries
• Use the insights provided—entry levels, probabilities, and risk calculations—to align your trades with a math-driven edge.
• Avoid overtrading by focusing only on setups with positive expected value.
5. Adapt to Market Conditions
• The indicator continuously adapts to real-time market behavior, ensuring its recommendations stay relevant and precise as conditions change.
How does the indicator calculate the current range?
The indicator calculates the current range by analyzing swing points from the very first bar on your charts to the latest available bar it identifies external liquidity levels, also known as BSLQ (buy-side liquidity levels) and SSLQ (sell-side liquidity levels).
What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Pivot levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into pivot level level. Status: "■" - Inactive
2. Once pivot level is tapped into, the pivot status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
4. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
What does the multi-timeframe functionality offer?
You can incorporate up to 4 higher timeframe probabilities directly into the table.
This feature allows you to analyze the probabilities of buyside and sellside liquidity across multiple timeframes, without the need to manually switch between them.
By viewing these higher timeframe probabilities in one place, traders can spot larger market trends and refine their entries and exits with a better understanding of the overall market context.
What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and uses security function to request the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
How does the Indicator Identifies Positive Expected Values?
Quantify instantly calculates whether a trade setup has the potential to generate positive expected value (EV).
To determine a positive EV setup, the indicator uses the formula:
EV = ( P(Win) × R(Win) ) − ( P(Loss) × R(Loss))
where:
- P(Win) is the probability of a winning trade.
- R(Win) is the reward or return for a winning trade, determined by the current risk-to-reward ratio (RR).
- P(Loss) is the probability of a losing trade.
- R(Loss) is the loss incurred per losing trade, typically assumed to be -1.
By calculating these values based on historical data and the current trading setup, the indicator helps you understand whether your trade has a positive expected value.
How can I know that the setup I'm going to trade with has a positive EV?
If the indicator detects that the adjusted pivot and buy/sell side probabilities have generated positive expected value (EV) in historical data, the risk-to-reward (RR) label within the range box will be colored blue and red .
If the setup does not produce positive EV, the RR label will appear gray.
This indicates that even the risk-to-reward ratio is greater than 1:1, the setup is not likely to yield a positive EV because, according to historical data, the number of losses outweighs the number of wins relative to the RR gain per winning trade.
What is the confidence level in the indicator, and how is it determined?
The confidence level in the indicator reflects the reliability of the probabilities calculated based on historical data. It is determined by the sample size of the probabilities used in the calculations. A larger sample size generally increases the confidence level, indicating that the probabilities are more reliable and consistent with past performance.
How does the confidence level affect the risk-to-reward (RR) label?
The confidence level (★) is visually represented alongside the probability label. A higher confidence level indicates that the probabilities used to determine the RR label are based on a larger and more reliable sample size.
How can traders use the confidence level to make better trading decisions?
Traders can use the confidence level to gauge the reliability of the probabilities and expected value (EV) calculations provided by the indicator. A confidence level above 95% is considered statistically significant and indicates that the historical data supporting the probabilities is robust. This high confidence level suggests that the probabilities are reliable and that the indicator’s recommendations are more likely to be accurate.
In data science and statistics, a confidence level above 95% generally means that there is less than a 5% chance that the observed results are due to random variation. This threshold is widely accepted in research and industry as a marker of statistical significance. Studies such as those published in the Journal of Statistical Software and the American Statistical Association support this threshold, emphasizing that a confidence level above 95% provides a strong assurance of data reliability and validity.
Conversely, a confidence level below 95% indicates that the sample size may be insufficient and that the data might be less reliable. In such cases, traders should approach the indicator’s recommendations with caution and consider additional factors or further analysis before making trading decisions.
How does the sample size affect the confidence level, and how does it relate to my TradingView plan?
The sample size for calculating the confidence level is directly influenced by the amount of historical data available on your charts. A larger sample size typically leads to more reliable probabilities and higher confidence levels.
Here’s how the TradingView plans affect your data access:
Essential Plan
The Essential Plan provides basic data access with a limited amount of historical data. This can lead to smaller sample sizes and lower confidence levels, which may weaken the robustness of your probability calculations. Suitable for casual traders who do not require extensive historical analysis.
Plus Plan
The Plus Plan offers more historical data than the Essential Plan, allowing for larger sample sizes and more accurate confidence levels. This enhancement improves the reliability of indicator calculations. This plan is ideal for more active traders looking to refine their strategies with better data.
Premium Plan
The Premium Plan grants access to extensive historical data, enabling the largest sample sizes and the highest confidence levels. This plan provides the most reliable data for accurate calculations, with up to 20,000 historical bars available for analysis. It is designed for serious traders who need comprehensive data for in-depth market analysis.
PRO+ Plans
The PRO+ Plans offer the most extensive historical data, allowing for the largest sample sizes and the highest confidence levels. These plans are tailored for professional traders who require advanced features and significant historical data to support their trading strategies effectively.
For many traders, the Premium Plan offers a good balance of affordability and sufficient sample size for accurate confidence levels.
What is the HTF probability table and how does it work?
The HTF (Higher Time Frame) probability table is a feature that allows you to view buy and sellside probabilities and their status from timeframes higher than your current chart timeframe.
Here’s how it works:
Data Request: The table requests and retrieves data from user-defined higher timeframes (HTFs) that you select.
Probability Display: It displays the buy and sellside probabilities for each of these HTFs, providing insights into the likelihood of price movements based on higher timeframe data.
Detailed Tooltips: The table includes detailed tooltips for each timeframe, offering additional context and explanations to help you understand the data better.
What do the different colors in the HTF probability table indicate?
The colors in the HTF probability table provide visual cues about the expected value (EV) of trading setups based on higher timeframe probabilities:
Blue: Suggests that entering a long position from the HTF user-defined pivot point, targeting buyside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Red: Indicates that entering a short position from the HTF user-defined pivot point, targeting sellside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Gray: Shows that neither long nor short trades from the HTF user-defined pivot point are expected to generate positive EV, suggesting that trading these setups may not be favorable.
What machine learning techniques are used in Quantify?
Quantify offers two main machine learning approaches:
1. Adaptive Learning (Fixed Sample Size): The algorithm learns from the entire dataset without resampling, maintaining a stable model that adapts to the latest market conditions.
2. Bootstrap Resampling: This method creates multiple subsets of the historical data, allowing the model to train on varying sample sizes. This technique enhances the robustness of predictions by ensuring that the model is not overfitting to a single dataset.
How does machine learning affect the expected value calculations in Quantify?
Machine learning plays a key role in improving the accuracy of expected value (EV) calculations. By analyzing historical price action, liquidity hits, and market bias patterns, the model continuously adjusts its understanding of risk and reward, allowing the expected value to reflect the most likely market movements. This results in more precise EV predictions, helping traders focus on setups that maximize profitability.
What is the Kelly Criterion, and how does it work in Quantify?
The Kelly Criterion is a mathematical formula used to determine the optimal position size for each trade, maximizing long-term growth while minimizing the risk of large drawdowns. It calculates the percentage of your portfolio to risk on a trade based on the probability of winning and the expected payoff.
Quantify integrates this with user-defined inputs to dynamically calculate the most effective position size in percentage, aligning with the trader’s risk tolerance and desired exposure.
How does Quantify use the Kelly Criterion in practice?
Quantify uses the Kelly Criterion to optimize position sizing based on the following factors:
1. Confidence Level: The model assesses the confidence level in the trade setup based on historical data and sample size. A higher confidence level increases the suggested position size because the trade has a higher probability of success.
2. Max Allowed Drawdown (User-Defined): Traders can set their preferred maximum allowed drawdown, which dictates how much loss is acceptable before reducing position size or stopping trading. Quantify uses this input to ensure that risk exposure aligns with the trader’s risk tolerance.
3. Probabilities: Quantify calculates the probabilities of success for each trade setup. The higher the probability of a successful trade (based on historical price action and liquidity levels), the larger the position size suggested by the Kelly Criterion.
What is a trailing stoploss, and how does it work in Quantify?
A trailing stoploss is a dynamic risk management tool that moves with the price as the market trend continues in the trader’s favor. Unlike a fixed take profit, which stays at a set level, the trailing stoploss automatically adjusts itself as the market moves, locking in profits as the price advances.
In Quantify, the trailing stoploss is enhanced by incorporating market structure liquidity levels (explain above). This ensures that the stoploss adjusts intelligently based on key price levels, allowing the trader to stay in the trade as long as the trend remains intact, while also protecting profits if the market reverses.
Why would a trader prefer a trailing stoploss based on liquidity levels instead of a fixed take-profit level?
Traders who use trailing stoplosses based on liquidity levels prefer this method because:
1. Market-Driven Flexibility: The stoploss follows the market structure rather than being static at a pre-defined level. This means the stoploss is less likely to be hit by small market fluctuations or false reversals. The stoploss remains adaptive, moving as the market moves.
2. Riding the Trend: Traders can capture more profit during a sustained trend because the trailing stop will adjust only when the trend starts to reverse significantly, based on key liquidity levels. This allows them to hold positions longer without prematurely locking in profits.
3. Avoiding Premature Exits: Fixed stoploss levels may exit a trade too early in volatile markets, while liquidity-based trailing stoploss levels respect the natural flow of price action, preventing the trader from exiting too soon during pullbacks or minor retracements.
🎲 Becoming the House: Gaining an Edge Over the Market
In American roulette, the casino has a 5.26% edge due to the presence of the 0 and 00 pockets. On even-money bets, players face a 47.37% chance of winning, while true 50/50 odds would require a 50% chance. This edge—the gap between the payout odds and the true probabilities—ensures that, statistically, the casino will always win over time, even if individual players win occasionally.
From a Trader’s Perspective
In trading, your edge comes from identifying and executing setups with a positive expected value (EV). For example:
• If you identify a setup with a 55.48% chance of winning and a 1:1 risk-to-reward (RR) ratio, your trade has a statistical advantage over a neutral (50/50) probability.
This edge works in your favor when applied consistently across a series of trades, just as the casino’s edge ensures profitability across thousands of spins.
🎰 Applying the Concept to Trading
Like casinos leverage their mathematical edge in games of chance, you can achieve long-term success in trading by focusing on setups with positive EV and managing your trades systematically. Here’s how:
1. Probability Advantage: Prioritize trades where the probability of success (win rate) exceeds the breakeven rate for your chosen risk-to-reward ratio.
• Example: With a 1:1 RR, you need a win rate above 50% to achieve positive EV.
2. Risk-to-Reward Ratio (RR): Even with a win rate below 50%, you can gain an edge by increasing your RR (e.g., a 40% win rate with a 2:1 RR still has positive EV).
3. Consistency and Discipline: Just as casinos profit by sticking to their mathematical advantage over thousands of spins, traders must rely on their edge across many trades, avoiding emotional decisions or overleveraging.
By targeting favorable probabilities and managing trades effectively, you “become the house” in your trading. This approach allows you to leverage statistical advantages to enhance your overall performance and achieve sustainable profitability.
What Makes the Quantify Indicator Original?
1. Data-Driven Edge
Unlike traditional indicators that rely on static formulas, Quantify leverages probability-based analysis and machine learning. It calculates expected value (EV) and confidence levels to help traders identify setups with a true statistical edge.
2. Integration of Market Structure
Quantify uses market structure liquidity levels to dynamically adapt. It identifies key zones like swing highs/lows and liquidity traps, enabling users to align entries and exits with where the market is most likely to react. This bridges the gap between price action analysis and quantitative trading.
3. Sophisticated Risk Management
The Kelly Criterion implementation is unique. Quantify allows traders to input their maximum allowed drawdown, dynamically adjusting risk exposure to maintain optimal position sizing. This ensures risk is scientifically controlled while maximizing potential growth.
4. Multi-Timeframe and Liquidity-Based Trailing Stops
The indicator doesn’t just suggest fixed profit-taking levels. It offers market structure-based trailing stop-loss functionality, letting traders ride trends as long as liquidity and probabilities favor the position, which is rare in most tools.
5. Customizable Bias and Adaptive Learning
• Directional Bias: Traders can set a bullish or bearish bias, and the indicator recalculates probabilities to align with the trader’s market outlook.
• Adaptive Learning: The machine learning model adapts to changes in data (via resampling or bootstrap methods), ensuring that predictions stay relevant in evolving markets.
6. Positive EV Focus
The focus on positive EV setups differentiates it from reactive indicators. It shifts trading from chasing signals to acting on setups that statistically favor profitability, akin to how professional quant funds operate.
7. User Empowerment
Through features like customizable timeframes, real-time probability updates, and visualization tools, Quantify empowers users to make data-informed decisions.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Azlan MA Silang PLUS++Overview
Azlan MA Silang PLUS++ is an advanced moving average crossover trading indicator designed for traders who want to jump back into the market when they missed their first opportunity to take a trade. It implements a sophisticated dual moving average system with customizable settings and re-entry signals, making it suitable for both trend following and swing trading strategies.
Key Features
• Dual Moving Average System with multiple MA types (EMA, SMA, WMA, LWMA)
• Customizable price sources for each moving average
• Smart re-entry system with configurable maximum re-entries
• Visual signals with background coloring and shape markers
• Comprehensive alert system for both initial and re-entry signals
• Flexible parameter customization through input options
Input Parameters
Moving Average Configuration
• MA1 Type: Choice between SMA, EMA, WMA, LWMA (default: EMA)
• MA2 Type: Choice between SMA, EMA, WMA, LWMA (default: EMA)
• MA1 Length: Minimum value 1 (default: 8)
• MA2 Length: Minimum value 1 (default: 15)
• MA1 & MA2 Shift: Offset values for moving averages
• Price Sources: Configurable for each MA (Open, High, Low, Close, HL/2, HLC/3, HLCC/4)
Re-entry System
• Enable/Disable re-entry signals
• Maximum re-entries allowed (default: 3)
Technical Implementation
Price Source Calculation
The script implements a flexible price source system through the price_source() function:
• Supports standard OHLC values
• Includes compound calculations (HL/2, HLC/3, HLCC/4)
• Defaults to close price if invalid source specified
Moving Average Types
Implements four MA calculations:
1. SMA (Simple Moving Average)
2. EMA (Exponential Moving Average)
3. WMA (Weighted Moving Average)
4. LWMA (Linear Weighted Moving Average)
Signal Generation Logic
Initial Signals
• Buy Signal: MA1 crosses above MA2 with price above both MAs
• Sell Signal: MA1 crosses below MA2 with price below both MAs
Re-entry Signals
Re-entry system activates when:
1. Price crosses under MA1 in buy mode (or over in sell mode)
2. Price returns to cross back over MA1 (or under for sells)
3. Position relative to MA2 confirms trend direction
4. Number of re-entries hasn't exceeded maximum allowed
Visual Components
• MA1: Blue line (width: 2)
• MA2: Red line (width: 2)
• Background Colors:
o Green (60% opacity): Bullish conditions
o Red (60% opacity): Bearish conditions
• Signal Markers:
o Initial Buy/Sell: Up/Down arrows with "BUY"/"SELL" labels
o Re-entry Buy/Sell: Up/Down arrows with "RE-BUY"/"RE-SELL" labels
Alert System
Generates alerts for:
• Initial buy/sell signals
• Re-entry opportunities
• Alerts include ticker and timeframe information
• Configured for once-per-bar-close frequency
Usage Tips
1. Moving Average Selection
o Shorter periods (MA1) capture faster moves
o Longer periods (MA2) identify overall trend
o EMA responds faster to price changes than SMA
2. Re-entry System
o Best used in strong trending markets
o Limit maximum re-entries based on market volatility
o Monitor price action around MA1 for potential re-entry points
3. Risk Management
o Use additional confirmation indicators
o Set appropriate stop-loss levels
o Consider market conditions when using re-entry signals
Code Structure
The script follows a modular design with distinct sections:
1. Input parameter definitions
2. Helper functions for price and MA calculations
3. Main signal generation logic
4. Visual elements and plotting
5. Alert system implementation
This organization makes the code maintainable and easy to modify for custom needs.
MTFHTS with Moving Average Ribbon and Buy/Sell Signals 3.2Multi-Timeframe Moving Average Strategy with Buy and Sell Signals
Purpose
This strategy is designed to provide clear, data-driven buy and sell signals based on moving average crossovers across multiple timeframes. It aims to help traders identify potential trend reversals and entry/exit points using a systematic approach.
How it Works
Moving Averages Across Multiple Timeframes:
Five customizable moving averages (MA №1 to MA №5) are calculated using different lengths and types, including SMA, EMA, WMA, and VWMA, to suit various trading styles.
The MAs are plotted on different timeframes, allowing traders to visualize trend alignment and identify market momentum across short, medium, and long terms.
Signals for Buying and Selling:
Buy Signals: When the shorter-term MA (MA №1) crosses above a longer-term MA (MA №2 or MA №3), the strategy triggers a buy signal, indicating potential upward momentum.
Sell Signals: When MA №1 crosses below a longer-term MA (MA №2 or MA №3), a sell signal is triggered, suggesting potential downward movement.
Visual Aids and Alerts:
The strategy uses color fills between MAs to indicate bullish (green) or bearish (red) trends, helping traders assess market conditions at a glance.
Alerts for buy and sell signals keep traders notified in real-time, helping to avoid missed opportunities.
Important Note
This strategy is purely educational and does not constitute investment advice. It serves as a tool to help traders understand how multi-timeframe moving averages and crossovers can be used in technical analysis. As with any trading strategy, we recommend testing in a simulated environment and exercising caution.
