Normalized Volume Rate of ChangeThis indicator is designed to help traders gauge changes in volume dynamics and identify potential shifts in buying or selling pressure. By normalizing the volume rate of change and comparing it to moving averages of itself, it offers valuable insights into market trends and can assist in making informed trading decisions.
Calculation:
The indicator calculates the Volume Rate of Change (VROC) by measuring the percentage change in volume over a specified length. This calculation provides a relative measure of how quickly the volume is increasing or decreasing. It then normalizes the VROC to a range of -1 to +1 by scaling it based on the highest and lowest values observed within the specified length. This normalization allows for easy comparison of the current VROC value with historical levels, enabling traders to assess the intensity of volume fluctuations.
Interpretation:
The main plot of the indicator displays the normalized VROC values as columns. The color of each column provides valuable information about the relationship between the VROC and the moving averages. Lime-colored columns indicate that the VROC is above both moving averages, suggesting increased buying pressure and potential bullish sentiment. Conversely, fuchsia-colored columns indicate that the VROC is below both moving averages, suggesting increased selling pressure and potential bearish sentiment. Yellow-colored columns indicate that the VROC is between the two moving averages, reflecting a period of consolidation or indecision in the market.
To further enhance interpretation, the indicator includes two moving averages. The Aqua line represents the faster moving average (MA1), and the Orange line represents the slower moving average (MA2). These moving averages provide additional context by smoothing out the VROC values and highlighting the overall trend. Traders can observe the interaction between the moving averages and the VROC to identify potential crossovers and assess the strength of trend reversals or continuations.
Colors:
-- Lime : The lime color is used to represent high volume rate of change above both moving averages. This color indicates a potentially bullish market sentiment, suggesting that buyers are dominant.
-- Fuchsia : The fuchsia color is used to represent low volume rate of change below both moving averages. This color indicates a potentially bearish market sentiment, suggesting that sellers are dominant.
-- Yellow : The yellow color is used to represent the volume rate of change between the two moving averages. This color reflects a transitional phase where neither buyers nor sellers have a clear advantage, signaling a period of consolidation or indecision in the market.
To provide additional visual cues for potential trade signals, the indicator includes lime-colored arrows below the price chart when there is a crossover upwards (MA1 crossing above MA2). This lime arrow indicates a potential bullish signal, suggesting a favorable time to consider long positions. Similarly, fuchsia-colored arrows are displayed above the price chart when there is a crossover downwards (MA1 crossing below MA2), signaling a potential bearish signal and suggesting a favorable time to consider short positions.
Applications:
This indicator offers various applications in trading strategies, including:
-- Trend Identification : By observing the relationship between the normalized VROC and the moving averages, traders can identify potential shifts in market trends. Lime-colored columns above both moving averages indicate a strong bullish trend, suggesting an opportunity to capitalize on upward price movements. Conversely, fuchsia-colored columns below both moving averages indicate a strong bearish trend, suggesting an opportunity to profit from downward price movements. Yellow-colored columns between the moving averages indicate a period of consolidation or uncertainty, signaling a potential trend reversal or continuation.
-- Confirmation of Price Moves : The indicator's ability to reflect volume dynamics in relation to the moving averages can help traders validate price moves. When significant price movements are accompanied by lime-colored columns (indicating high volume rate of change above both moving averages), it adds confirmation to the bullish sentiment. Similarly, fuchsia-colored columns accompanying downward price movements validate the bearish sentiment. This confirmation can enhance traders' confidence in the reliability of price moves.
-- Trade Timing : The indicator's moving average crossovers and the presence of arrows provide timing signals for trade entries and exits. Lime arrows appearing below the price chart signal potential long entry opportunities, indicating a bullish market sentiment. Conversely, fuchsia arrows appearing above the price chart suggest potential short entry opportunities, indicating a bearish market sentiment. These signals can be used in conjunction with other technical analysis tools to improve trade timing and increase the probability of successful trades.
Parameter Adjustments:
Traders can adjust the length of the VROC and the moving averages according to their trading preferences and timeframes. Longer VROC lengths provide a broader view of volume dynamics over an extended period, making it suitable for assessing long-term trends. Shorter VROC lengths offer a more sensitive measure of recent volume changes, making it suitable for shorter-term analysis. Similarly, adjusting the lengths of the moving averages can help adapt the indicator to different market conditions and trading styles.
Limitations:
While the indicator provides valuable insights, it has some limitations that traders should be aware of:
-- False Signals : Like any technical indicator, false signals can occur. During periods of low liquidity or in choppy markets, the indicator may generate misleading signals. It is essential to consider other indicators, price action, and fundamental analysis to confirm the signals before taking any trading actions.
-- Lagging Nature : Moving averages inherently lag behind the price action and volume changes. As a result, there may be a delay in the generation of signals and capturing trend reversals. Traders should exercise patience and avoid solely relying on this indicator for immediate trade decisions. Combining it with other indicators and tools can provide a more comprehensive picture of market conditions.
In conclusion, this indicator offers valuable insights into volume dynamics and trend analysis. By comparing the normalized VROC with moving averages, traders can identify shifts in buying or selling pressure, validate price moves, and improve trade timing. However, it is important to consider its limitations and use it in conjunction with other technical analysis tools to form a well-rounded trading strategy. Additionally, thorough testing, experimentation, and customization of the indicator's parameters are recommended to align it with individual trading preferences and market conditions.
Search in scripts for "Volume"
Volume SpikesShows volume spikes over a certain threshold, using a symbol's volume moving average as the baseline. Offers a few different filters regarding candle shapes and types, in an attempt to catch quick moves on extremely low timeframes (sub-1m).
Ultimately I would like to integrate this logic into an indicator that contains automated stop raid/inducement detection.
Volume CompressorTurns volume into a more informative representation, ready to be further analyzed
...
Rationale
Volume
Back in the "before the quant" days I was a big fan of market & volume profile. Thing is J. Steidlmayer had lotta different ideas & works aside of profiling, it's just most of them ain't got to mainstream, one of them was "Hot / Cold volume" (yes, you can't really google it). From my interpretation, the idea was that in a given asset there is a usual constant volume that stays there no matter what, and if it ever changes it changes very slow and gradually; and there's another kind of, so to say, 'active' volume that actually influences price dynamics and very volatile by its nature. So I've met concept lately, and decided to quantify & model it one day when I'll have an idea how. That day was yesterday.
Compression
When we do music we always use different kinds of filters (low-pass, high pass, etc) for equalization and filtering itself. That stuff we use in finance as well. What we also always use in music are compressors, there dynamic processors that automatically adjust volume so it will be more consistent. Almost all the cool music you hear is compressed (both individual instruments (especially vocals) and the whole track afterwards), otherwise stuff will be too quite and too weak to flex on it, and also DJing it would be a nightmare. I am a big adept of loudness war. So I was like, how can I use compression in finance, when ima get an idea? That day was yesterday as well.
Volume structure
Being inspired by Steidlmayer's idea, I decided to distinguish volume this way:
1) Passive / static volume. The ~ volume that's always there no matter what (hedges, arbitrages, spread legs, portfolio parts etc etc), doesn't affect things;
2) Active / dynamic volume. The volume that flows from one asset to another, really matters and affects things;
3) Excess volume. The last portion of number 2 volume, that doesn't represent any powerful value to affect things.
Now it's clear that we can get rid of number 1 and number 3, the components that don't really matter, and concentrate on number 2 in order to improve information gain, both for ourselves and for the models we feed this data. How?
Model
I don't wanna explain it all in statistical / DSP way for once.
First of all, I think the population of volumes is log-normally distributed, so let's take logs of volumes, now we have a ~ normally distributed data. We take linearly weighted mean, add and subtract linearly weighted standard deviation from it, these would be our thresholds, the borders between different kinds of volumes explained before.
The upper threshold is for downward compression, that will not let volume pass it higher.
The lower threshold is for upward compression, all the volumes lower than this threshold will be brought up to the threshold's level.
Then we apply multipliers to the thresholds in order to adjust em and find the sweet spots. We do it the same way as in sound engineering when we don't aim for overcompression, we adjust the thresholds until they start to touch the signal and all good.
Afterwards, we delete all the number 1 and number 3 volume, leaving us exclusively with the clear main component, ready to be processed further.
We return the volumes to dem real scale.
About the parameters, based on testing I don't recommend changing the thresholds from dem default values, first of all they make sense statistically and second they work as intended.
Window length can and should be adjusted, find your own way, or leave the default value. ML (moving location) length is up to you as well.
So yeah, you can see now we can smooth the data and make it visually appealing not only by applying a smooth filter over it.
All good TV?
Relative Volume (rVol), Better Volume, Average Volume ComparisonThis is the best version of relative volume you can find a claim which is based on the logical soundness of its calculation.
I have amalgamated various volume analysis into one synergistic script. I wasn't going to opensource it. But, as one of the lucky few winners of TradingClue 2. I felt obligated to give something back to the community.
Relative volume traditionally compares current volume to prior bar volume or SMA of volume. This has drawbacks. The question of relative volume is "Volume relative to what?" In the traditional scripts you'll find it displays current volume relative to the last number of bars. But, is that the best way to compare volume. On a daily chart, possibly. On a daily chart this can work because your units of time are uniform. Each day represents a full cycle of volume. However, on an intraday chart? Not so much.
Example: If you have a lookback of 9 on an hourly chart in a 24 hour market, you are then comparing the average volume from Midnight - 9 AM to the 9 AM volume. What do you think you'll find? Well at 9:30 when NY exchanges open the volume should be consistently and predictably higher. But though rVol is high relative to the lookback period, its actually just average or maybe even below average compared to prior NY session opens. But prior NY session opens are not included in the lookback and thus ignored.
This problem is the most visibly noticed when looking at the volume on a CME futures chart or some equivalent. In a 24 hour market, such as crypto, there are website's like skew can show you the volume disparity from time of day. This led me to believe that the traditional rVol calculation was insufficient. A better way to calculate it would be to compare the 9:30 am 30m bar today to the last week's worth of 9:30 am 30m bars. Then I could know whether today's volume at 9:30 am today is high or low based on prior 9:30 am bars. This seems to be a superior method on an intraday basis and is clearly superior in markets with irregular volume
This led me to other problems, such as markets that are open for less than 24 hours and holiday hours on traditional market exchanges. How can I know that the script is accurately looking at the correct prior relevant bars. I've created and/or adapted solutions to all those problems and these calculations and code snippets thus have value that extend beyond this rVol script for other pinecoders.
The Script
This rVol script looks back at the bars of the same time period on the viewing timeframe. So, as we said, the last 9:30 bars. Averages those, then divides the: . The result is a percentage expressed as x.xxx. Thus 1.0 mean current volume is equal to average volume. Below 1.0 is below the average and above 1.0 is above the average.
This information can be viewed on its own. But there are more levels of analysis added to it.
Above the bars are signals that correlate to the "Better Volume Indicator" developed by, I believe, the folks at emini-watch and originally adapted to pinescript by LazyBear. The interpretation of these symbols are in a table on the right of the indicator.
The volume bars can also be colored. The color is defined by the relationship between the average of the rVol outputs and the current volume. The "Average rVol" so to speak. The color coding is also defined by a legend in the table on the right.
These can be researched by you to determine how to best interpret these signals. I originally got these ideas and solid details on how to use the analysis from a fellow out there, PlanTheTrade.
I hope you find some value in the code and in the information that the indicator presents. And I'd like to thank the TradingView team for producing the most innovative and user friendly charting package on the market.
(p.s. Better Volume is provides better information with a longer lookback value than the default imo)
Credit for certain code sections and ideas is due to:
LazyBear - Better Volume
Grimmolf (From GitHub) - Logic for Loop rVol
R4Rocket - The idea for my rVol 1 calculation
And I can't find the guy who had the idea for the multiples of volume to the average. Tag him if you know him
Final Note: I'd like to leave a couple of clues of my own for fellow seekers of trading infamy.
Indicators: indicators are like anemometers (The things that measure windspeed). People talk bad about them all the time because they're "lagging." Well, you can't tell what the windspeed is unless the wind is blowing. anemometers are lagging indicators of wind. But forecasters still rely on them. You would use an indicator, which I would define as a instrument of measure, to tell you the windspeed of the markets. Conversely, when people talk positively about indicators they say "This one is great and this one is terrible." This is like a farmer saying "Shovels are great, but rakes are horrible." There are certain tools that have certain functions and every good tool has a purpose for a specific job. So the next time someone shares their opinion with you about indicators. Just smile and nod, realizing one day they'll learn... hopefully before they go broke.
How to forecast: Prediction is accomplished by analyzing the behavior of instruments of measure to aggregate data (using your anemometer). The data is then assembled into a predictive model based on the measurements observed (a trading system). That predictive model is tested against reality for it's veracity (backtesting). If the model is predictive, you can optimize your decision making by creating parameter sets around the prediction that are synergistic with the implications of the prediction (risk, stop loss, target, scaling, pyramiding etc).
<3
Welkin Advanced Volume Overlay (for VSA)This is a PineScript translation of Welkin's Advanced Volume Indicator Overlay, originally written for ThinkOrSwim. This tool is designed to facilitate Volume Spread Analysis (VSA) by highlighting areas of above average volume alongside price movement.
This indicator does two things:
1. Plots lines that extend from candles of above average, high, and very high volume.
2. Colors in candles with colors indicating volume levels (when "Paint Candles With Volume Colors" is enabled).
Blue lines mark candles with Average volume, based on a 20 SMA.
Orange lines mark 2-sigma (2 times standard deviations higher) volume.
Magenta lines mark 3-sigma (3 times standard deviations higher) volume.
When enabled, gray colored candles indicate below average volume.
Yellow candles indicate volume that is relatively higher than the previous candle, default is 1.25x.
Crypto Multi Exchange Volume (CMEV)Crypto Multi Exchange Volume (CMEV) aggregates and plots trading volumes for supported cryptoasset pairs over multiple different cryptoasset exchanges. For developers looking for more information and for those who want to compile their own version of CMEV, please check out my GitHub (jakobpredin/crypto-multi-exchange-volume).
Configuration
CMEV comes with two configurable settings - whether base volume or quote volume is plotted and the length of the volume's EMA. By default, the base volume is used for plotting and the length of the EMA is set to 12 periods.
Use cases
The indicator was primarily developed in order to be able to chart using the trading pair with the longest available trading history. Due to the fast-changing preferences of where cryptoassets are traded, volumes tend to be very inconsistent and can give a distorted picture of a pairs history. For illustration, check out the SC-BTC pair from Poloniex using their native volume and compare it to the CMEV volume.
The other use case is to be able to spot divergences in volume. A great example here is bitcoin's 2019 rally where volumes from derivatives exchanges are at all time highs but volumes from retail/spot exchanges are not.
Supported exchanges
CMEV currently supports asset pairs from the following exchanges:
Binance
Bitfinex
Bitstamp
Bittrex
Coinbase
Gemini
Kraken
Poloniex
Limitations
Because of the fact that CMEV is pulling data from from multiple different exchanges and is computationally intensive it can take a couple of seconds to load while charting certain cryptoasset pairs.
Additionally, due to Tradingview's various limitations only a certain number of pairs can be supported at a time. By default, only pairs with a BTC or USD quote are supported and many non-unique pairs with consistently low trading volumes have been removed. For a full explanation, please refer to the docs in my GitHub (jakobpredin/crypto-multi-exchange-volume).
Future of the project
I plan on supporting pairs from more exchanges in the future as I see fit and as they become available for charting on Tradingview. Further, I may develop a strategy script using CMEV as its core indicator.
I welcome everybody from the community to help me extend the functionality of CMEV in order to make investing in cryptoassets more transparent for everybody.
Net Volume (BV-SV) Per Bar / Rolling Toggle (V6) - TP## Net Volume (BV-SV) – Per Bar / Rolling Toggle
This indicator estimates whether a bar (candle) had **more buying pressure or selling pressure**, using only the candle’s **high, low, and close** plus the bar’s **volume**.
It plots:
* **Per-bar Net Volume** (raw, bar-by-bar pressure)
* **Rolling Net Volume** (pressure summed over your chosen lookback, e.g., 20 bars)
* Or **Both**, depending on your Plot Mode.
A **zero line** is included as the “balance point”:
* Above zero = net buying pressure
* Below zero = net selling pressure
---
## How the calculation works (simple explanation)
TradingView does not provide true “buy volume vs sell volume” from the tape for stocks, so this script uses a common estimate:
* If the candle **closes near the high**, it assumes more of the day’s volume was “buying pressure.”
* If the candle **closes near the low**, it assumes more was “selling pressure.”
* If the candle **closes near the middle**, it assumes buying and selling were more balanced.
### Estimated volumes
* **BV (Buy Volume estimate)** = portion of volume attributed to buyers
* **SV (Sell Volume estimate)** = portion of volume attributed to sellers
### Net Volume
* **Net Volume = BV − SV**
* Positive = net buying pressure
* Negative = net selling pressure
### Rolling Net (optional)
Rolling Net simply **adds up Net Volume** over the last *N* bars (lookback):
* Helps you see the *bigger picture* and reduce noise.
---
## How to use it (practical)
### 1) Per-bar Net (most “raw” view)
Use this when you want to see **immediate pressure** each bar.
* **Green / positive** bars/line = buyers controlled that bar
* **Red / negative** bars/line = sellers controlled that bar
* Frequent flips are normal in choppy markets
**Good for:**
* spotting sudden demand/supply spikes
* confirming breakout candles (net turning strongly positive)
* confirming breakdown candles (net turning strongly negative)
### 2) Rolling Net (smoother, trend/flow view)
Use this when you want to know whether the last *N* bars overall show **accumulation or distribution**.
* Staying above zero = buyers dominating over the lookback
* Staying below zero = sellers dominating over the lookback
* Crossing zero = possible shift in control (buyers↔sellers) over that window
**Good for:**
* trend confirmation
* filtering trades (avoid longs when rolling net is deeply negative, etc.)
* spotting transitions after consolidation
### 3) Both (best for confirmation)
Use Both when you want:
* the **rolling line** for overall bias
* the **per-bar line** for timing entries/exits
Example logic:
* Rolling Net above 0 + Per-bar Net flips positive → stronger long confirmation
* Rolling Net below 0 + Per-bar Net flips negative → stronger short/sell confirmation
---
## Inputs / Settings
* **Plot Mode**
* Per-bar Net: raw net volume each bar
* Rolling Net (Σ): summed net over your lookback
* Both: show both lines together
* **Rolling Lookback**
* Default 20 bars (change based on your timeframe)
* **Line Style / Color Options**
* You can color by buy/sell state or pick manual colors and line styles
* **Last-bar Callout**
* Shows the latest values (BV, SV, Net, and/or Rolling Net)
---
## Important notes (limitations)
* This is an **estimate**, not true exchange “buy volume vs sell volume.”
* It works best as a **confirmation tool** alongside price action, trend, and key levels.
* In sideways markets, zero crossings can happen often (whipsaw is normal).
Auto-Anchored Fibonacci Volume Profile [Custom Array Engine]Description:
1. The Theoretical Foundation: Structure vs. Participation In professional technical analysis, traders often struggle to reconcile two distinct datasets: Price Geometry (where price should go) and Market Participation (where money actually went).
Why Fibonacci? (The Structure) Fibonacci Retracements map the mathematical structure of a trend. They identify psychological and algorithmic "interest zones" (0.382, 0.5, 0.618) where a correction is statistically likely to terminate. However, Fibonacci levels are theoretical—they are "lines in the sand" that do not guarantee liquidity or reaction.
Why Volume Profile? (The Verification) Volume Profile maps the historical exchange of shares at specific price levels. It reveals "fair value" (High Volume Nodes) and "market imbalance" (Low Volume Nodes). It is the only tool that verifies if a specific price level was actually accepted by institutional participants.
2. Underlying Calculations (The Custom Engine) This script operates on a custom-built calculation engine that bypasses standard built-in functions entirely. It uses Pine Script Arrays to build a Volume Profile from scratch. Here is the breakdown of the proprietary code logic:
A. The "Smart-Fill" Distribution Algorithm (Solves Gapping)
The Problem: Standard volume scripts often assign a candle's entire volume to a single price row. In volatile markets or steep trends, this creates visual "gaps" or a "barcode" effect because price moved too fast to register on every row.
My Solution: I wrote a custom loop that calculates the vertical overlap of every candle against the profile grid.
The Math: Volume Per Bin = Total Candle Volume / Bins Touched.
The Result: If a single volatile candle spans 10 price rows (bins), the script mathematically divides that volume and distributes it equally into all 10 array indices. This generates a solid, continuous distribution curve that accurately reflects price action through the entire candle range, not just the close.
B. Dynamic Arrays & Split-Volume Logic The script initializes two separate floating-point arrays (buyVolArray and sellVolArray) sized to the user's resolution (up to 300 rows). It iterates through the specific time-window of the swing:
If Close >= Open, the calculated volume slice is injected into the Buy Array.
If Close < Open, it is injected into the Sell Array.
These arrays are then visually stacked to render the dual-color profile, allowing traders to see the "Delta" (Buyer vs. Seller aggression) at key structural levels.
C. Custom Garbage Collection (Performance) To enable the "Auto-Anchoring" feature without causing chart lag or visual artifacts ("ghosting"), the script includes a Garbage Collection System. Before drawing a new profile, the script iterates through a tracking array of all existing objects (box.delete, line.delete) and clears them from memory. This ensures the indicator remains lightweight and responsive even when dragging chart margins or switching timeframes.
3. The Synthesis: Why Combine Them? The core philosophy of this script is Confluence . A Fibonacci level without volume is merely a suggestion; a Fibonacci level backed by volume is a defensive wall. By algorithmically anchoring a Volume Profile to the exact coordinates of a Fibonacci swing, this tool allows traders to instantly answer critical questions:
"Is the Golden Pocket (0.618) supported by a High Volume Node (HVN), or is it a Low Volume Node (LVN) that price might slice through?"
"Is the Shallow Retracement (0.382) holding because of structural support, or just a lack of selling pressure?"
4. How to Read the Indicator
The Geometry: The script automatically detects the trend and draws standard Fib levels (0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0).
The Confluence Check: Look for the Point of Control (Red Line). If this High Volume Node aligns with a key Fib level (e.g., the 0.618), the probability of a reversal increases significantly.
The Imbalance Check: Look for "Valleys" in the profile (Low Volume Nodes). These gaps often act as "slippage zones" where price travels quickly between structural levels.
Buy/Sell Splits: The dual-color bars (Teal/Red) reveal the composition of the volume. A 0.618 level held up by dominant Buy Volume is a stronger bullish signal than one with mixed volume.
5. Settings & Customization
Lookback Length: Sensitivity of the swing detection (Default: 200 bars).
Resolution: Granularity of the profile rows (Default: 100). Higher values provide smoother definition.
Width (%): Responsive sizing that scales the profile relative to the trend's duration.
Extend Lines: Option to project structural levels infinitely to the right.
Disclaimer This script is an analytical tool for visualizing historical market data. It does not provide trade signals or financial advice.
POC Volume Bar (Highest Volume in Range)What the highlighted POC bar means
🔶 1. Institutional interest
A POC often identifies where big money stepped in.
🔶 2. Support or resistance pivot
Large volume often signals:
• A reversal
• A breakout
• Or the beginning of a trend
🔶 3. Liquidity magnet
Price tends to revisit high-volume bars.
They act like magnets.
🔶 4. Trend confirmation or exhaustion
High volume on:
• Green candle → bullish participation
• Red candle → distribution / aggressive selling
Moving Average Volume (20, 50)Shows two moving averages of volume, the 20 and 50 periods.
white bars in the background show volume, look for breaks of the target lines to confirm a breakout with volume
green shaded regions show how much higher the current volume is compared to historical volume
the greener the shade, the higher the multiple is (cap is 10x higher)
indicator is to be used with other breakout identifiers, or to help confirm the strength of a move out of an SAR level.
Volumetric Expansion/Contraction### Indicator Title: Volumetric Expansion/Contraction
### Summary
The Volumetric Expansion/Contraction (PCC) indicator is a comprehensive momentum oscillator designed to identify high-conviction price moves. Unlike traditional oscillators that only look at price, the PCC integrates four critical dimensions of market activity: **Price Change**, **Relative Volume (RVOL)**, **Cumulative Volume Delta (CVD)**, and **Average True Range (ATR)**.
Its primary purpose is to help traders distinguish between meaningful, volume-backed market expansions and noisy, unsustainable price action. It gives more weight to moves that occur in a controlled, low-volatility environment, highlighting potential starts of new trends or significant shifts in market sentiment.
### Key Concepts & Purpose
The indicator's unique formula synthesizes the following concepts:
1. **Price Change:** Measures the magnitude and direction of the primary move.
2. **Relative Volume (RVOL):** Confirms that the move is backed by significant volume compared to its recent average, indicating institutional participation.
3. **Cumulative Volume Delta (CVD):** Measures the underlying buying and selling pressure, confirming that the price move is aligned with the net flow of market orders.
4. **Inverse Volatility (ATR):** This is the indicator's unique twist. It normalizes the signal by the inverse of the Average True Range. This means the indicator's value is **amplified** when volatility (ATR) is low (signifying a controlled, confident expansion) and **dampened** when volatility is high (filtering out chaotic, less predictable moves).
The goal is to provide a single, easy-to-read oscillator that signals when price, volume, and order flow are all in alignment, especially during a breakout from a period of contraction.
### Features
* **Main Oscillator Line:** A single line plotted in a separate pane that represents the calculated strength of the volumetric expansion or contraction.
* **Zero Line:** A dotted reference line to easily distinguish between bullish (above zero) and bearish (below zero) regimes.
* **Visual Threshold Zones:** The background automatically changes color to highlight periods of significant strength:
* **Bright Green:** Indicates a "Strong Up Move" when the oscillator crosses above the user-defined upper threshold.
* **Bright Fuchsia:** Indicates a "Strong Down Move" when the oscillator crosses below the user-defined lower threshold.
### Configurable Settings & Filters
The indicator is fully customizable to allow for extensive testing and adaptation to different assets and timeframes.
#### Main Calculation Inputs
* **Price Change Lookback:** Sets the period for calculating the primary price change.
* **CVD Normalization Length:** The lookback period for normalizing the Cumulative Volume Delta.
* **RVOL Avg Volume Length:** The lookback for the simple moving average of volume, used to calculate RVOL.
* **RVOL Normalization Length:** The lookback period for normalizing the RVOL score.
* **ATR Length & Normalization Length:** Sets the periods for calculating the ATR and its longer-term average for normalization.
#### Weights
* Fine-tune the impact of each core component on the final calculation, allowing you to emphasize what matters most to your strategy (e.g., give more weight to CVD or RVOL).
#### External Market Filter (Powerful Feature)
* **Enable SPY/QQQ Filter for Up Moves?:** A checkbox to activate a powerful regime filter.
* **Symbol:** A dropdown to choose whether to filter signals based on the trend of **SPY** or **QQQ**.
* **SMA Period:** Sets the lookback period for the Simple Moving Average (default is 50).
* **How it works:** When enabled, this filter will **only allow "Strong Up Move" signals to appear if the chosen symbol (SPY or QQQ) is currently trading above its specified SMA**. This is an excellent tool for aligning your signals with the broader market trend and avoiding bullish entries in a bearish market.
#### Visuals
* **Upper/Lower Threshold:** Allows you to define what level the oscillator must cross to trigger the colored background zones, letting you customize the indicator's sensitivity.
***
**Disclaimer:** This tool is designed for market analysis and confluence. It is not a standalone trading system. Always use this indicator in conjunction with your own trading strategy, risk management, and other forms of analysis.
Aggressive Volume 📊 Indicator: Aggressive Volume – Simulated Buy/Sell Pressure
Aggressive Volume estimates delta volume using candle data to simulate the market’s internal buy/sell pressure. It helps visualize how aggressive buyers or sellers are moving the price without needing full order flow access.
⚙️ How It Works:
Calculates simulated delta volume based on candle direction and volume.
Bullish candles (close > open) suggest dominance by buyers.
Bearish candles (close < open) suggest dominance by sellers.
Delta is the difference between simulated buying and selling pressure.
🔍 Key Features:
Visual bars showing aggressive buyer vs seller dominance
Helps spot trend strength, momentum bursts, and potential reversals
Simple, effective, and compatible with any timeframe
Lightweight and ideal for scalping, day trading, and swing trading
💡 How to Use:
Look for strong positive delta during bullish trends for confirmation.
Watch for delta weakening or divergence as potential reversal signals.
Combine with trend indicators or price action for enhanced accuracy.
📊 Indicador: Volume Agressivo – Pressão de Compra/Venda Simulada
Volume Agressivo estima o delta de volume utilizando dados dos candles para simular a pressão interna de compra/venda do mercado. Ele ajuda a visualizar como os compradores ou vendedores agressivos estão movendo o preço, sem precisar de acesso completo ao fluxo de ordens.
⚙️ Como Funciona:
Calcula o delta de volume simulado com base na direção do candle e no volume.
Candles de alta (fechamento > abertura) indicam predominância de compradores.
Candles de baixa (fechamento < abertura) indicam predominância de vendedores.
O delta é a diferença entre a pressão de compra e venda simulada.
🔍 Principais Funcionalidades:
Barras visuais mostrando a dominância de compradores vs vendedores agressivos
Ajuda a identificar a força da tendência, explosões de momentum e possíveis reversões
Simples, eficaz e compatível com qualquer período de tempo
Leve e ideal para scalping, day trading e swing trading
💡 Como Usar:
Procure por delta positivo forte durante tendências de alta para confirmação.
Observe o delta enfraquecendo ou divergências como sinais de possível reversão.
Combine com indicadores de tendência ou price action para maior precisão.
Volume Order Blocks [BigBeluga]Volume Order Blocks is a powerful indicator that identifies significant order blocks based on price structure, helping traders spot key supply and demand zones. The tool leverages EMA crossovers to determine the formation of bullish and bearish order blocks while visualizing their associated volume and relative strength.
🔵 Key Features:
Order Block Detection via EMA Crossovers:
Plots bullish order blocks at recent lows when the short EMA crosses above the long EMA.
Plots bearish order blocks at recent highs when the short EMA crosses below the long EMA.
Uses customizable sensitivity through the “Sensitivity Detection” setting to fine-tune block formation.
Volume Collection and Visualization:
Calculates the total volume between the EMA crossover bar and the corresponding high (bearish OB) or low (bullish OB).
Displays the absolute volume amount next to each order block for clear volume insights.
Percentage Volume Distribution:
Shows the percentage distribution of volume among bullish or bearish order blocks.
100% represents the cumulative volume of all OBs in the same category (bullish or bearish).
Order Block Removal Conditions:
Bullish order blocks are removed when the price closes below the bottom of the block.
Bearish order blocks are removed when the price closes above the top of the block.
Helps maintain chart clarity by only displaying relevant and active levels.
Midline Feature:
Dashed midline inside each order block indicates the midpoint between the upper and lower boundaries.
Traders can toggle the midline on or off through the settings.
Shadow Trend:
Shadow Trend dynamically visualizes trend strength and direction by adapting its color intensity based on price movement.
🔵 Usage:
Supply & Demand Zones: Use bullish and bearish order blocks to identify key market reversal or continuation points.
Volume Strength Analysis: Compare volume percentages to gauge which order blocks hold stronger market significance.
Breakout Confirmation: Monitor block removal conditions for potential breakout signals beyond support or resistance zones.
Trend Reversals: Combine EMA crossovers with order block formation for early trend reversal detection.
Risk Management: Use OB boundaries as potential stop-loss or entry points.
Volume Order Blocks is an essential tool for traders seeking to incorporate volume-based supply and demand analysis into their trading strategy. By combining price action, volume data, and EMA crossovers, it offers a comprehensive view of market structure and potential turning points.
VSA Volume + Fibonacci (Volunacci)Overview
This indicator combines Volume Spread Analysis (VSA) with Fibonacci levels to identify key price zones based on volume behavior. It helps traders determine potential support and resistance levels influenced by volume strength.
How It Works
Volume Calculation
The indicator calculates volume levels based on the selected timeframe.
It identifies high volume spikes and low volume dips, which are critical for detecting supply and demand shifts.
It uses a simple moving average (SMA) of volume to smooth fluctuations.
Fibonacci Levels Integration
When a high-volume event is detected, the indicator records the highest high and lowest low of that candle.
It then plots Fibonacci retracement and extension levels to highlight potential price reaction zones.
Negative Fibonacci levels are included to identify possible deep retracements.
Visual Features
The indicator adapts to both light and dark themes for better visibility.
Fibonacci lines are color-coded based on key retracement and extension levels.
A table displaying key Fibonacci levels and their corresponding prices is provided for quick reference.
Why Is This Indicator Useful?
It helps traders spot accumulation and distribution phases by analyzing volume at key price points.
The combination of VSA and Fibonacci allows traders to confirm trend strength and identify potential reversal points.
Works well for trend-following strategies, scalping, and breakout trading.
How to Use This Indicator?
Use it to confirm breakouts or reversals at Fibonacci levels when volume supports the move.
Watch for high-volume spikes near key Fibonacci zones—these can signal strong trend continuation or reversal.
Use the displayed Fibonacci table to quickly assess price reaction levels.
Credits
This script was inspired by the Hidden Gap’s VSA Volume indicator by HPotter and has been enhanced by integrating Fibonacci-based analysis.
Volume-Adjusted Bollinger BandsThe Volume-Adjusted Bollinger Bands (VABB) indicator is an advanced technical analysis tool that enhances the traditional Bollinger Bands by incorporating volume data. This integration allows the bands to dynamically adjust based on market volume, providing a more nuanced view of price movements and volatility. The key qualities of the VABB indicator include:
1. Dynamic Adjustment with Volume: Traditional Bollinger Bands are based solely on price data and standard deviations. The VABB indicator adjusts the width of the bands based on the volume ratio, making them more responsive to changes in market activity. This means that during periods of high volume, the bands will expand, and during periods of low volume, they will contract. This adjustment helps to reinforce the significance of price movements relative to the central line (VWMA).
2. Volume-Weighted Moving Average (VWMA): Instead of using a simple moving average (SMA) as the central line, the VABB uses the VWMA, which weights prices by volume. This provides a more accurate representation of the average price level, considering the trading volume.
3. Enhanced Signal Reliability: By incorporating volume, the VABB can filter out false signals that might occur in low-volume conditions. This makes the indicator particularly useful for identifying significant price movements that are supported by strong trading activity.
How to Use and Interpret the VABB Indicator
To use the VABB indicator, you need to set it up on your trading platform with the following parameters:
1. BB Length: The number of periods for calculating the Bollinger Bands (default is 20).
2. BB Multiplier: The multiplier for the standard deviation to set the width of the Bollinger Bands (default is 2.0).
3. Volume MA Length: The number of periods for calculating the moving average of the volume (default is 14).
Volume Ratio Smoothing Length: The number of periods for smoothing the volume ratio (default is 5).
Interpretation
1.Trend Identification: The VWMA serves as the central line. When the price is above the VWMA, it indicates an uptrend, and when it is below, it indicates a downtrend. The direction of the VWMA itself can also signal the trend's strength.
2. Volatility and Volume Analysis: The width of the VABB bands reflects both volatility and volume. Wider bands indicate high volatility and/or high volume, suggesting significant price movements. Narrower bands indicate low volatility and/or low volume, suggesting consolidation.
3. Trading Signals:
Breakouts: A price move outside the adjusted upper or lower bands can signal a potential breakout. High volume during such moves reinforces the breakout's validity.
Reversals: When the price touches or crosses the adjusted upper band, it may indicate overbought conditions, while touching or crossing the adjusted lower band may indicate oversold conditions. These conditions can signal potential reversals, especially if confirmed by other indicators or volume patterns.
Volume Confirmation: The volume ratio component helps confirm the strength of price movements. For instance, a breakout accompanied by a high volume ratio is more likely to be sustained than one with a low volume ratio.
Practical Example
Bullish Scenario: If the price crosses above the adjusted upper band with a high volume ratio, it suggests a strong bullish breakout. Traders might consider entering a long position, setting a stop-loss just below the VWMA or the lower band.
Bearish Scenario: Conversely, if the price crosses below the adjusted lower band with a high volume ratio, it suggests a strong bearish breakout. Traders might consider entering a short position, setting a stop-loss just above the VWMA or the upper band.
Conclusion
The Volume-Adjusted Bollinger Bands (VABB) indicator is a powerful tool that enhances traditional Bollinger Bands by incorporating volume data. This dynamic adjustment helps traders better understand market conditions and make more informed trading decisions. By using the VABB indicator, traders can identify significant price movements supported by volume, improving the reliability of their trading signals.
The Volume-Adjusted Bollinger Bands (VABB) indicator is provided for educational and informational purposes only. It is not financial advice and should not be construed as a recommendation to buy, sell, or hold any financial instrument. Trading involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results.
Volume-Enhanced Momentum Moving Average (VEMMA)Volume-Enhanced Momentum Moving Average (VEMMA)
Overview:
The Volume-Enhanced Momentum Moving Average (VEMMA) helps you spot market trends by combining momentum and volume as a moving average. This unique moving average adjusts itself based on the strength and activity of the market, giving you a clearer picture of what’s happening.
How It Works:
1. Key Settings (all of these are adjustable in the settings panel of the indicator):
◦ Base Length: Looks back over the last 50 days by default.
◦ Momentum Length: Uses the past 14 days to measure market strength.
◦ Volume Length: Uses the past 30 days to average trading volume.
◦ High/Low Thresholds: Considers RSI values above 70 as high momentum and below 30 as low momentum.
2. Momentum and Volume:
◦ Momentum: Calculated using the Relative Strength Index (RSI) to see if the market is gaining or losing strength.
◦ Volume: Average trading volume is calculated over the last 30 days to gauge trading activity.
3. VEMMA Calculation:
◦ For each of the past 50 days:
▪ Check Momentum: If RSI > 70, it’s high momentum; if RSI < 30, it’s low.
▪ Weight by Volume: High momentum days with high volume get more weight; low momentum days get less.
▪ Combine: Multiply the closing price by this weight and sum it up.
◦ Average: Divide the total by 50 to get the VEMMA value.
4. Visuals:
◦ Lines: Two lines, VEMMA1 (blue) and VEMMA2 (orange), show the adjusted moving averages.
◦ Colours: Background colors help you quickly spot high (green) and low (red) momentum periods.
How to Use:
• Spot Trends: Rising VEMMA lines suggest an uptrend; falling lines suggest a downtrend.
• Confirm Signals: When both VEMMA1 and VEMMA2 move together, it indicates a strong trend.
• Identify Reversals: Watch for background color changes from green to red or vice versa to catch potential trend reversals.
If the market has been strong and active, the VEMMA line will rise more sharply. If the market is weak and quiet, the line will be smoother.
Benefits:
• Integrated View: Combines market strength and trading activity for a fuller picture.
• Responsive: Adapts to significant market changes, highlighting key movements.
• Easy to Read: Clear visuals with color-coded backgrounds make interpretation simple.
Remember, just like any other indicator, this is not supposed to be used alone. Use it as part of your greater trading strategy. I do however believe it works exceptionally well for finding longer term trends early. The default VEMMA settings work very well as replacement for the EMA 200. Try it and see how it goes. Play around with the settings. Feedback appreciated.
Volume Flow Oscillator (VFO)I created the Volume Flow Oscillator (VFO) to explore the intricate interplay between volume and price movements over a specific lookback period. This tool contrasts volumes that move in sync with the price against those that move in opposition, signaling potential overbought or oversold territories. To determine the direction, I compare the current price to its value four periods back, shedding light on underlying bullish or bearish momentum. The VFO enriches my analysis and decision-making by offering a detailed perspective on how volume trends correlate with price changes. Its color-coded visuals are crucial for highlighting optimal trading points based on volume dynamics.
Volume Speed [By MUQWISHI]▋ INTRODUCTION :
The “Volume Dynamic Scale Bar” is a method for determining the dominance of volume flow over a selected length and timeframe, indicating whether buyers or sellers are in control. In addition, it detects the average speed of volume flow over a specified period. This indicator is almost equivalent to Time & Sales (Tape) .
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▋ OVERVIEW:
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▋ ELEMENTS
(1) Volume Dynamic Scale Bar. As we observe, it has similar total up and down volume values to what we're seeing in the table. Note they have similar default inputs.
(2) A notice of a significant volume came.
(3) It estimates the speed of the average volume flow. In the tooltip, it shows the maximum and minimum recorded speeds along with the time since the chart was updated.
(4) Info of entered length and the selected timeframe.
(5) The widget will flash gradually for 3 seconds when there’s a significant volume occurred based on the selected timeframe.
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▋ INDICATOR SETTINGS:
(1) Timezone.
(2) Widget location and size on chart.
(3) Up & Down volume colors.
(4) Option to enable a visual flash when a single volume is more than {X value} of Average. For instance, 2 → means double the average volume.
(5) Fetch data from the selected lower timeframe.
(6) Number of bars at chosen timeframe.
(7) Volume OR Price Volume.
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▋ COMMENT:
The Volume Dynamic Scale Bar should not be taken as a major concept to build a trading decision.
Please let me know if you have any questions.
Thank you.
Relative Volume Intensity Control Chart***NOTE THE VOLUME OSCILATOR PROVIDED AT THE BOTTOM IS FOR COMPARSION AND IS NOT PART OF THE INDICATOR****
This indicator provides a comprehensive and a nuanced representation of volume relative to historical volume. The indicator aims to provide insights into the relative intensity of trading volume compared to historical data. It calculates two types of relative volume intensity: mean volume intensity and point volume intensity. The final indicator, "Relative_volume_intensity," is a combination of these two.
1. Point Volume Intensity:
Calculate the ratio of the current volume to the corresponding SMA from the previous period for each of the periods.
Normalize each ratio by dividing it by the corresponding normalized SMA.
Assign weights to each normalized ratio and calculate the point volume intensity.
Point volume intensity calculates the intensity of the current trading volume at a specific point in time relative to its historical moving average. It assesses how much the current volume deviates from the previous historical average for different lookback periods(current volume/ average volume of previous n days). The calculation involves dividing the current volume by the corresponding previous historical moving average and normalizing the result. The purpose of point volume intensity is to capture the immediate impact of the current volume on the overall intensity, providing a more dynamic and responsive measure.
2. Mean Volume Intensity:
Calculate the simple moving averages (SMA) of the volume for different periods (5, 8, 13, 21, 34, 55, 89, 144).
Normalize each SMA by dividing it by the SMA with the longest lookback (144).
Assign weights to each normalized SMA and calculate the mean volume intensity.
Mean volume intensity, on the other hand, takes a broader approach by looking at the mean (average) of various historical moving averages of volume. Instead of focusing on the current volume alone, it considers the historical average intensity over multiple periods. The purpose of mean volume intensity is to provide a smoother and more stable representation of the overall historical volume intensity. It helps filter out short-term fluctuations and provides a more comprehensive view of how the current volume compares to historical norms.
Purpose of Both:
Both point volume intensity and mean volume intensity contribute to the calculation of the final indicator, "Relative_volume_intensity." The idea is to combine these two perspectives to create a more comprehensive measure of relative volume intensity. By assigning equal weights to both components and taking a balanced approach, the indicator aims to capture both short-term spikes in volume and trends in volume intensity over a relatively extended periods.
In calculation of both point volume intensity and mean volume intensity, shorter-term moving averages (e.g., 5, 8) have higher weights, suggesting a greater emphasis on recent volume behavior.
Visualization:
The script then calculates the mean and standard deviation of the relative volume intensity over a specified lookback length.
Plot lines for the centerline (mean), upper and lower 3 standard deviations, upper and lower 2 standard deviations, and upper and lower 1 standard deviation.
Plot the relative volume intensity as a step line with diamond markers.
It is displayed like a control chart where we can see how the relative intensity is behaving when compared to longer historical lookback period.
Filtered Volume Profile [ChartPrime]The "Filtered Volume Profile" is a powerful tool that offers insights into market activity. It's a technical analysis tool used to understand the behavior of financial markets. It uses a fixed range volume profile to provide a histogram representing how much volume occurred at distinct price levels.
Profile in action with various significant levels displayed
How to Use
The script is designed to analyze cumulative trading volumes in different price bins over a certain period, also known as `'lookback'`. This lookback period can be defined by the user and it represents the number of bars to look back for calculating levels of support and resistance.
The `'Smoothing'` input determines the degree to which the output is smoothed. Higher values lead to smoother results but may impede the responsiveness of the indicator to rapid changes in volatility.
The `'Peak Sensitivity'` input is used to adjust the sensitivity of the script's peak detection algorithm. Setting this to a lower value makes the algorithm more sensitive to local changes in trading volume and may result in "noisier" outputs.
The `'Peak Threshold'` input specifies the number of bins that the peak detection mechanism should account for. Larger numbers imply that more volume bins are taken into account, and the resultant peaks are based on wider intervals.
The `'Mean Score Length'` input is used for scaling the mean score range. This is particularly important in defining the length of lookback bars that will be used to calculate the average close price.
Sinc Filter
The application of the sinc-filter to the Filtered Volume Profile reduces the risk of viewing artefacts that may misrepresent the underlying market behavior. Sinc filtering is a high-quality and sharp filter that doesn't manifest any ringing effects, making it an optimal choice for such volume profiling.
Histogram
On the histogram, the volume profile is colored based on the balance of bullish to bearish volume. If a particular bar is more intense in color, it represents a larger than usual volume during a single price bar. This is a clear signal of a strong buying or selling pressure at a particular price level.
Threshold for Peaks
The `peak_thresh` input determines the number of bins the algorithm takes in account for the peak detection feature. The 'peak' represents the level where a significant amount of volume trading has occurred, and usually is of interest as an indicative of support or resistance level.
By increasing the `peak_thresh`, you're raising the bar for what the algorithm perceives as a peak. This could result in fewer, but more significant peaks being identified.
History of Volume Profiles and Evolution into Sinc Filtering
Volume profiling has a rich history in market analysis, dating back to the 1950s when Richard D. Wyckoff, a legendary trader, introduced the concept of volume studies. He understood the critical significance of volume and its relationship with market price movement. The core of Wyckoff's technical analysis suite was the relationship between prices and volume, often termed as "Effort vs Results".
Moving forward, in the early 1800s, the esteemed mathematician J. R. Carson made key improvements to the sinc function, which formed the basis for sinc filtering application in time series data. Following these contributions, trading studies continued to create and integrate more advanced statistical measures into market analysis.
This culminated in the 1980s with J. Peter Steidlmayer’s introduction of Market Profile. He suggested that markets were a function of continuous two-way auction processes thus introducing the concept of viewing markets in price/time continuum and price distribution forms. Steidlmayer's Market Profile was the first wide-scale operation of organized volume and price data.
However, despite the introduction of such features, challenges in the analysis persisted, especially due to noise that could misinform trading decisions. This gap has given rise to the need for smoothing functions to help eliminate the noise and better interpret the data. Among such techniques, the sinc filter has become widely recognized within the trading community.
The sinc filter, because of its properties of constructing a smooth passing through all data points precisely and its ability to eliminate high-frequency noise, has been considered a natural transition in the evolution of volume profile strategies. The superior ability of the sinc filter to reduce noise and shield against over-fitting makes it an ideal choice for smoothing purposes in trading scripts, particularly where volume profiling forms the crux of the market analysis strategy, such as in Filtered Volume Profile.
Moving ahead, the use of volume-based studies seems likely to remain a core part of technical analysis. As long as markets operate based on supply and demand principles, understanding volume will remain key to discerning the intent behind price movements. And with the incorporation of advanced methods like sinc filtering, the accuracy and insight provided by these methodologies will only improve.
Mean Score
The mean score in the Filtered Volume Profile script plays an important role in probabilistic inferences regarding future price direction. This score essentially characterizes the statistical likelihood of price trends based on historical data.
The mean score is calculated over a configurable `'Mean Score Length'`. This variable sets the window or the timeframe for calculation of the mean score of the closing prices.
Statistically, this score takes advantage of the concept of z-scores and probabilities associated with the t-distribution (a type of probability distribution that is symmetric and bell-shaped, just like the standard normal distribution, but has heavier tails).
The z-score represents how many standard deviations an element is from the mean. In this case, the "element" is the price level (Point of Control).
The mean score section of the script calculates standard errors for the root mean squared error (RMSE) and addresses the uncertainty in the prediction of the future value of a random variable.
The RMSE of a model prediction concerning observed values is used to measure the differences between values predicted by a model and the values observed.
The lower the RMSE, the better the model is able to predict. A zero RMSE means a perfect fit to the data. In essence, it's a measure of how concentrated the data is around the line of best fit.
Through the mean score, the script effectively predicts the likelihood of the future close price being above or below our identified price level.
Summary
Filtered Volume Profile is a comprehensive trading view indicator which utilizes volume profiling, peak detection, mean score computations, and sinc-filter smoothing, altogether providing the finer details of market behavior.
It offers a customizable look back period, smoothing options, and peak sensitivity setting along with a uniquely set peak threshold. The application of the Sinc Filter ensures a high level of accuracy and noise reduction in volume profiling, making this script a reliable tool for gaining market insights.
Furthermore, the use of mean score calculations provides probabilistic insights into price movements, thus providing traders with a statistically sound foundation for their trading decisions. As trading markets advance, the use of such methodologies plays a pivotal role in formulating effective trading strategies and the Filtered Volume Profile is a successful embodiment of such advancements in the field of market analysis.
Volume-Blended Candlesticks [QuantVue]Introducing the Volume-Blended Candlestick Indicator, a powerful tool that seamlessly integrates volume information with candlesticks, providing you with a comprehensive view of market dynamics in a single glance.
The Volume-Blended Candlestick Indicator employs a unique approach of projecting volume totals by calculating the total volume traded per second and comparing it to the time left in the session as well as the historical average length selected by the user.
The indicator then dynamically adjusts the opacity of the candlestick colors based on the intensity of the projected volume. As volume intensifies, the candlestick colors become more pronounced, while low volume will cause colors to fade allowing you to visually perceive the level of buying or selling.
One of the standout features of the Volume-Blended Candlestick Indicator is its ability to identify pocket pivots. A pocket pivot is an up day with volume greater than any of the down days volume in the past 10 days. By highlighting these pocket pivots on your chart, the indicator helps you identify potential stealth accumulation.
In addition to blending volume with candlesticks and spotting pocket pivots, this versatile indicator provides you with an insightful table displaying key volume metrics. The table includes the average volume, average dollar volume, and the up-down volume ratio, allowing you to get a clear picture of buying and selling pressure.
Settings Include:
🔹Sensitivty Level: Normal, More, Less
🔹Volume MA Length
🔹Toggle Color based on previous close
🔹Show or hide volume info
🔹Chose candlestick colors
🔹Show or hide pocket pivots
🔹Show or hide volume info table
Don't hesitate to reach out with any questions or concerns.
We hope you enjoy!
Cheers.
OSPL Volume [Community Edition]NSE:BANKNIFTY1!
This indicator is based on the concepts popularized by @OptionsScalper123 "Siva" of OiPulse. His ideology Is that large moves come after high volume candles. For Nifty, high volume is considered to be a candle above 125k volume and for BankNifty it’s 50k.
This indicator allows you to cut the noise and focus only on the high volume candle. It shows high volume candle in a brighter shade and lower volume candles in a less visible shade.
You can set the minimum volume threshold limit for Nifty and BankNifty. The indicator smartly recognizes which index you are using it in and uses the respective threshold volume limit.
All colors are customizable.
Thanks for Siva for all the ideas and wonderful products he has given to the community
Thanks to all the wonderful Pinescipters for developing awesome indicators and keeping the source open.
The source code of this indicator is just a few lines. Hope you can use it in your projects and learn something from this just how I learned from other scripts.
Any changes or updates needed in this indicator, please suggest. I was thinking some kind of alerts can be added when volume crosses the threshold. Let me know.
Boost/like this indicator and comment if you find this useful. Cheers and happy trading!!!
Up/Down Volume + DeltaThis simple script is a modification of Tradingview's Up/Down Volume. In this case the delta between the buys and sells is plotted in columns style above the regular up/down volume columns. This gives a better visual of the dominant volume and is useful to spot divergences in tops and bottoms.
The indicators uses data from lower timeframe volumes. By default the lowest timeframe it will use is 1m, but for those that have a premium account you can try using a custom LTF set to seconds when scalping on the 1m chart.
Enjoy :)
