Volume Based Price Prediction [EdgeTerminal]This indicator combines price action, volume analysis, and trend prediction to forecast potential future price movements. The indicator creates a dynamic prediction zone with confidence bands, helping you visualize possible price trajectories based on current market conditions.
Key Features
Dynamic price prediction based on volume-weighted trend analysis
Confidence bands showing potential price ranges
Volume-based candle coloring for enhanced market insight
VWAP and Moving Average overlay
Customizable prediction parameters
Real-time updates with each new bar
Technical Components:
Volume-Price Correlation: The indicator analyzes the relationship between price movements and volume, Identifies stronger trends through volume confirmation and uses Volume-Weighted Average Price (VWAP) for price equilibrium
Trend Strength Analysis: Calculates trend direction using exponential moving averages, weights trend strength by relative volume and incorporates momentum for improved accuracy
Prediction Algorithm: combines current price, trend, and volume metrics, projects future price levels using weighted factors and generates confidence bands based on price volatility
Customizable Parameters:
Moving Average Length: Controls the smoothing period for calculations
Volume Weight Factor: Adjusts how much volume influences predictions
Prediction Periods: Number of bars to project into the future
Confidence Band Width: Controls the width of prediction bands
How to use it:
Look for strong volume confirmation with green candles, watch for prediction line slope changes, use confidence bands to gauge potential volatility and compare predictions with key support/resistance levels
Some useful tips:
Start with default settings and adjust gradually
Use wider confidence bands in volatile markets
Consider prediction lines as zones rather than exact levels
Best applications of this indicator:
Trend continuation probability assessment
Potential reversal point identification
Risk management through confidence bands
Volume-based trend confirmation
Komut dosyalarını "volume" için ara
Volume StatsDescription:
Volume Stats displays volume data and statistics for every day of the year, and is designed to work on "1D" timeframe. The data is displayed in a table with columns being months of the year, and rows being days of each month. By default, latest data is displayed, but you have an option to switch to data of the previous year as well.
The statistics displayed for each day is:
- volume
- % of total yearly volume
- % of total monthly volume
The statistics displayed for each column (month) is:
- monthly volume
- % of total yearly volume
- sentiment (was there more bullish or bearish volume?)
- min volume (on which day of the month was the min volume)
- max volume (on which day of the month was the max volume)
The cells change their colors depending on whether the volume is bullish or bearish, and what % of total volume the current cell has (either yearly or monthly). The header cells also change their color (based either on sentiment or what % of yearly volume the current month has).
This is the first (and free) version of the indicator, and I'm planning to create a "PRO" version of this indicator in future.
Parameters:
- Timezone
- Cell data -> which data to display in the cells (no data, volume or percentage)
- Highlight min and max volume -> if checked, cells with min and max volume (either monthly or yearly) will be highlighted with a dot or letter (depending on the "Cell data" input)
- Cell stats mode -> which data to use for color and % calculation (All data = yearly, Column = monthly)
- Display data from previous year -> if checked, the data from previous year will be used
- Header color is calculated from -> either sentiment or % of the yearly volume
- Reverse theme -> the table colors are automatically changed based on the "Dark mode" of Tradingview, this checkbox reverses the logic (so that darker colors will be used when "Dark mode" is off, and lighter colors when it's on)
- Hide logo -> hides the cat logo (PLEASE DO NOT HIDE THE CAT)
Conclusion:
Let me know what you think of the indicator. As I said, I'm planning to make a PRO version with more features, for which I already have some ideas, but if you have any suggestions, please let me know.
Volume-Supported Linear Regression Trend TableThe "Volume-Supported Linear Regression Trend Table" (VSLRT Table) script helps traders identify buy and sell opportunities by analyzing price trends and volume dynamics across multiple timeframes. It uses linear regression to calculate the trend direction and volume strength, visually representing this data with color-coded signals on the chart and in a table. Green signals indicate buying opportunities, while red signals suggest selling, with volume acting as confirmation of trend strength. Traders can use these signals for both short and long positions, with additional risk management and multi-timeframe validation to enhance the strategy.
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To use the "Volume-Supported Linear Regression Trend Table" (VSLRT Table) script in a trading strategy, you would incorporate it into your decision-making process to identify potential buy and sell opportunities based on the trend and volume dynamics. Here’s how you could apply it for trading:
1. Understanding the Key Elements:
Trend Direction (Slope of Price): The script uses linear regression to assess the trend direction of the price. If the price slope is positive, the asset is likely in an uptrend; if it's negative, the asset is in a downtrend.
Volume-Backed Signals: The buy or sell signal is not only based on the price trend but also on volume. Volume is crucial in validating the strength of a trend; large volume often indicates strong interest in a direction.
2. Interpreting the Table and Signals:
The table displayed at the bottom-right of your TradingView chart gives you a clear overview of the trends across different timeframes:
Trend Colors:
Green hues (e.g., ccol11, ccol12, etc.): Indicate a buying trend supported by volume.
Red hues (e.g., ccol21, ccol22, etc.): Indicate a selling trend supported by volume.
Gray: Indicates weak or unclear trends where no decisive direction is present.
Buy/Sell Signals:
The script plots triangles on the chart:
Upward triangle below the bar signals a potential buy.
Downward triangle above the bar signals a potential sell.
3. Building a Trading Strategy:
Here’s how you can incorporate the script’s information into a trading strategy:
Buy Signal (Long Entry):
Look for green triangles (indicating a buy signal) below a bar.
Confirm that the trend color in the table for the relevant timeframe is green, which shows that the buy signal is supported by strong volume.
Ensure that the price is in an uptrend (positive slope) and that volume is increasing on upward moves, as this indicates buying interest.
Execute a long position when these conditions align.
Sell Signal (Short Entry):
Look for red triangles (indicating a sell signal) above a bar.
Confirm that the trend color in the table for the relevant timeframe is red, which shows that the sell signal is supported by strong volume.
Ensure that the price is in a downtrend (negative slope) and that volume is increasing on downward moves, indicating selling pressure.
Execute a short position when these conditions align.
Exiting the Trade:
Exit a long position when a sell signal (red triangle) appears, or when the trend color in the table shifts to red.
Exit a short position when a buy signal (green triangle) appears, or when the trend color in the table shifts to green.
4. Multi-Timeframe Confirmation:
The script provides trends across multiple timeframes (tf1, tf2, tf3), which can help in validating your trade:
Short-Term Trading: Use shorter timeframes (e.g., 3, 5 minutes) for intraday trades. If both short and medium timeframes align in trend direction (e.g., both showing green), it strengthens the signal.
Longer-Term Trading: If you are trading on a higher timeframe (e.g., daily or weekly), confirm that the lower timeframes align with your intended trade direction.
5. Adding Risk Management:
Stop-Loss: Place stop-losses below recent lows (for long trades) or above recent highs (for short trades) to minimize risk.
Take Profit: Consider taking profit at key support/resistance levels or based on a fixed risk-to-reward ratio (e.g., 2:1).
Example Strategy Flow:
For Long (Buy) Trade:
Signal: A green triangle appears below a candle (Buy signal).
Trend Confirmation: Check that the color in the table for your selected timeframe is green, confirming the trend is supported by volume.
Execute Long: Enter a long trade if the price is trending upward (positive price slope).
Exit Long: Exit when a red triangle appears above a candle (Sell signal) or if the trend color shifts to red in the table.
For Short (Sell) Trade:
Signal: A red triangle appears above a candle (Sell signal).
Trend Confirmation: Check that the color in the table for your selected timeframe is red, confirming the trend is supported by volume.
Execute Short: Enter a short trade if the price is trending downward (negative price slope).
Exit Short: Exit when a green triangle appears below a candle (Buy signal) or if the trend color shifts to green in the table.
6. Fine-Tuning:
Backtesting: Before trading live, use TradingView’s backtesting features to test the strategy on historical data and optimize the settings (e.g., length of linear regression, timeframe).
Combine with Other Indicators: Use this strategy alongside other technical indicators (e.g., RSI, MACD) for better confirmation.
In summary, the script helps identify trends with volume support, giving more confidence in buy/sell decisions. Combining these signals with risk management and multi-timeframe analysis can create a solid trading strategy.
Volume-Trend Sentiment (VTS) [AlgoAlpha]Introducing the Volume-Trend Sentiment by AlgoAlpha, a unique tool designed for traders who seek a deeper understanding of market sentiment through volume analysis. This innovative indicator offers a comprehensive view of market dynamics, blending volume trends with price action to provide an insightful perspective on market sentiment. 🚀📊
Key Features:
1. 🌟 Dual Trend Analysis: This indicator combines the concepts of price movement and volume, offering a multi-dimensional view of market sentiment. By analyzing the relationship between the closing and opening prices relative to volume, it provides a nuanced understanding of market dynamics.
2. 🎨 Customizable Settings: Flexibility is at the core of this indicator. Users can adjust various parameters such as the length of the volume trend, standard deviation, and SMA length, ensuring a tailored experience to match individual trading strategies.
3. 🌈 Visual Appeal: With options to display noise, the main plot, and background colors, the indicator is not only informative but also visually engaging. Users can choose their preferred colors for up and down movements, making the analysis more intuitive.
4. ⚠️ Alerts for Key Movements: Stay ahead of market changes with built-in alert conditions. These alerts notify traders when the Volume-Trend Sentiment crosses above or below the midline, signaling potential shifts in market momentum.
How It Works:
The core of the indicator is the calculation of the Volume-Trend Sentiment (VTS). It is computed by subtracting a double-smoothed Exponential Moving Average (EMA) of the price-volume ratio from a single EMA of the same ratio. This method highlights the trend in volume relative to price changes.
volumeTrend = ta.ema((close - open) / volume, volumeTrendLength) - ta.ema(ta.ema((close - open) / volume, volumeTrendLength), volumeTrendLength)
To manage volatility and noise in the volume trend, the indicator employs a standard deviation calculation and a Simple Moving Average (SMA). This smoothing process helps in identifying the true underlying trend by filtering out extreme fluctuations.
standardDeviation = ta.stdev(volumeTrend, standardDeviationLength) * 1
smoothedVolumeTrend = ta.sma(volumeTrend / (standardDeviation + standardDeviation), smaLength)
A unique feature is the dynamic background color, which changes based on the sentiment level. This visual cue instantly communicates the market's bullish or bearish sentiment, enhancing the decision-making process.
getColor(volumeTrendValue) =>
sentimentLevel = math.abs(volumeTrendValue * 10)
baseTransparency = 60 // Base transparency level
colorTransparency = math.max(90 - sentimentLevel * 5, baseTransparency)
volumeTrendValue > 0 ? color.new(upColor, colorTransparency) : color.new(downColor, colorTransparency)
bgcolor(showBackgroundColor ? getColor(smoothedVolumeTrend) : na)
In summary, the Volume-Trend Sentiment by AlgoAlpha is a comprehensive tool that enhances market analysis through a unique blend of volume and price trends. Whether you're a seasoned trader or just starting out, this indicator offers valuable insights into market sentiment and helps in making informed trading decisions. 📈📉🔍🌐
Split VolumeThe Split Volume indicator displays 'Upwards' and 'Downwards' volume with an additional method for distributing 'split' candle volume.
A 'split' candle is a candle whose direction is...'Split'...since the open and close are equal. (Ex. Doji)
Upwards and Downwards Volume is tracked by comparing the Open and Closes of the Lower Timeframes.
If the Close is Greater-than the Open, we track the Volume as 'Upwards' Volume.
If the Close is Less-than the Open, we track the Volume as 'Downwards' Volume.
If the Close and Open are Equal, we assume that the Volume is an even split 50/50, and track it as such.
The indicator pulls data from lower timeframes to achieve more granular Open,Close,& Volume Data
Specifically:
<5m Timeframe: 1 Second LTF
<60m Timeframe: 5 Second LTF
<1D Timeframe: 1 Minute LTF
>1D Timeframe: 60m LTF
We have also included some nice-to-have features
50% Volume Line: This line splits each columns in half, this is used as quick reference to see exactly which side the volume is on.
High Volume Candle Identification: We are detecting bars with high relative volume and coloring them on the upper chart for use as important zones.
Status Line Readouts: The Status line for this indicator is formatted for simple reading. It Reads(Left-to-Right):Total Volume, Downwards Volume, 50% Value, Upwards Volume
Strategy - Relative Volume GainersStrategy - Relative Volume Gainers
Overview:
This trading strategy, called "Relative Volume Gainers," is designed for Long Entry opportunities in the stock market. The strategy aims to identify potential trading candidates based on specific technical conditions, including volume, price movements, and indicator alignments.
Strategy Rules:
The strategy is focused solely on Long Entry positions.
The volume for the current trading day must be greater than or equal to the volume of the previous day.
The percentage change in price must be greater than or equal to 2.5%.
The Last Traded Price (LTP) must be greater than or equal to the Exponential Moving Average (EMA) 200.
The Relative Volume for the current trading day (calculated over the last 30 days) must be greater than or equal to the Simple Moving Average (SMA) of Relative Volume over the same 30 days.
The current candle on the chart should be Green or Bullish, indicating positive price movement.
The price difference between bid and ask prices should be kept to a minimum.
It's recommended to also analyze market depth for better insights.
Strategy Requirements:
Add the Exponential Moving Average (EMA) 200 to your trading chart.
This strategy can be applied on charts of any timeframe.
For intraday trading, particularly for early entry, consider using a 1-minute timeframe.
It is advisable to create a screener to identify potential trades in real-time market conditions.
Risk Warning:
Stocks that meet the strategy criteria might exhibit high volatility and a high beta, making them inherently risky to trade. Exercise caution and adhere to predetermined risk management strategies.
Determine your trading quantity based on your entry price and stop loss in order to manage risk effectively.
Quantity Calculation Formula:
Quantity calculation is crucial to manage risk and position sizing. The following formulas can be used based on your trading scenario:
Quantity with Leverage:
Quantity = (((Using Capital / 100) * Risk Percent) / (Entry Price - Stop Loss)) * Leverage
Eg: Quantity = (((10000 / 100) * 0.2) / (405.5 - 398.5)) * 5
Quantity = 14
Risk = Rs.100 (Rs.100 is 1% of Rs.10000. So the risk is 1%, means we lose only Rs.100 when the SL is hit. If SL is increased the Quantity will get reduced to maintain a fixed risk of Rs.100)
Quantity without Leverage:
Quantity = (((Using Capital / 100) * Risk Percent) / (Entry Price - Stop Loss))
Note:
Always stay informed about market conditions and be prepared for potential rapid price movements when trading stocks that meet the strategy criteria. Strictly adhere to your predefined risk management strategy to safeguard your capital.
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.
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?
Volume Breakout (ValueRay)Easy visuals on, if volume is way over average. Good for Mean Reverting. Higher Volume tends to higher breakout chances.
Please whisper me for for ideas how to make this better. Its a very simple script, but got some alpha. If you know how to improve, let me know and i will code it into.
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
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.
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.
Enhanced volumeHi all!
This indicator plots volume at the bottom of the chart and the volume Moving Average (with the choice of Simple Moving Average (SMA) (default), Exponential Moving Average (EMA) and Volume Weighted Moving Average (VWMA)) and desired length (defaults to 20). It then changes the transparency of the volume (and the bars body) based on the close and the volume. It also changes the bar transparency. All these visual changes can be configured in the "Style" tab in the indicators settings.
The opacity will be high when the close is considered to be a "Strong close (%)" and has a bigger volume than any of the red closing in the last 10 bars. This "Strong close (%)" is defaulted to 50 which means that the bar needs to close equal or higher than 50% of the bar.
You also have an option to include red bars, which are excluded by default.
This indicator can help you to spot bars with relevant volume and find reversals.
I hope this explanation makes sense, let me know otherwise. Also let me know if you have any suggestions on improvements.
Best of trading luck!
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.
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.
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 :)
[potatoshop] Volume Profile lower timeframeThis script is a volume profile that displays the volume of transactions in price blocks over a recent period of time.
For a more detailed representation, OHCLV values on the time frame lower than the time zone on the chart were called and expressed.
Low time frames are adjustable.
You can adjust the number of blocks and the most recent time period that you want to view.
Although it cannot be compared to the volume indicators provided for paid users of Trading-View, it has functioned by displaying transactions that are difficult to find on open source.
Displays the amount traded in each block and the percentage of the total over a given period.
POC represents the middle value of the block with the highest transaction volume as a line.
TPOC represents the block that stayed the longest regardless of the volume of transaction.
The reversal line appears when you determine the trading advantage of the rising and falling closing on a block basis and then have a different value from the neighboring blocks.
(I didn't mean it much, but I just put it in for fun.)
It represents the total volume of transactions traded in each block, and there are also check boxes in the settings window that represent the volume of transactions that closed higher and closed lower.
You can specify the color of each block.
The highest and lowest values for the set period and the total sum of each block are displayed at the bottom of the box.
Because it was made using a lot of arrays, the total transaction volume was marked separately to check the value.
When expressing the price block according to the trading volume percentage, it was a pity that the minimum pixel was 1 bar, so it could not be expressed delicately.
Although set to bar_time in Box properties xloc, 1 bar was actually the minimum unit of the X-axis value.
The logic used to place the transaction volume for each block is as follows.
1. Divide the difference between the high and low values of 1 LTF bar by the transaction volume .
2. Find the percentage of this LTF bar within each block.
3. Multiply the ratio by the transaction volume again.
4. Store the value in each block cell.
Below are the codes of the people I referred to this time.
1. ‘Time & volume point of control (TPOC & VPOC)’ by quantifytools
2. ‘Volume Profile ’ by LuxAlgo
3. ‘Volume Profile and Volume Indicator by DGT’ by dgtrd
The script is for informational and educational purposes only.
이 스크립트는 최근 일정 기간동안의 거래량을 가격 블록단위로 표시해 주는 볼륨 프로화일입니다.
좀 더 자세한 표현을 위해 차트상의 시간대보다 낮은 시간 프레임상의 OHCLV 값들을 호출하여 표현하였습니다.
낮은 시간 프레임은 조절 가능합니다..
보고 싶은 최근 일정 기간과 블럭 갯수를 조절할 수 있습니다.
트뷰 유료 사용자들을 위해 제공하는 지표와는 비교할 수는 없지만, 오픈 소스상에서는 찾기 힘든 거래량을 표시해 기능을 넣었습니다.
각 블럭에서 거래되었던 양 과 주어진 기간 동안의 총량 대비 퍼센트를 표시해 줍니다.
POC는 거래량이 가장 많았던 블럭의 중간값을 라인으로 표현해 줍니다.
TPOC는 거래량에 상관없이 가장 오랜 시간 머물렸던 블럭을 표현해 줍니다.
반전선은 블럭 단위로 상승 마감과 하락 마감의 거래량 우세를 결정한 뒤, 이웃 블럭들하고 다른 값을 가질 때 나타납니다.
(어떤 뜻을 갖고 만든 건 아니고 그냥 재미로 넣어 보았습니다.)
각 블럭에서 거래되었던 총거래량을 표현해 주며, 또한 설정창에서 상승 마감한 거래량과 하락 마감한 거래량을 표현하는 체크 박스가 있습니다.
각 블럭의 색깔을 지정하실 수 있습니다.
설정된 기간 동안의 최고값과 최저값, 각 블럭을 합친 총량을 박스 하단에 표시해 두었습니다.
어레이를 많이 사용하여 만들었기 때문에 값의 확인을 위해 전체 거래량을 따로 표시하였습니다.
가격 블럭을 거래량 퍼센트에 따라 표현할 때, 최소 픽셀이 1bar 이어서 섬세하게 표현 할 수 없어 안타까웠습니다.
박스 속성을 xloc.bar_time 로 설정하였지만 실제로는 1 bar가 X축 값의 최소 단위였습니다.
각 블록 별로 거래량을 배치 할 때 쓰인 로직은 다음과 같습니다.
1. 1 LTF bar의 하이 와 로우 값의 차이를 거래량으로 나누어 줍니다.
2. 각 블록 안에서 이 LTF bar가 차지 하는 비율을 구합니다.
3. 그 비율에 다시 거래량을 곱해 줍니다.
4. 그 값을 각 블록 셀에 저장해 줍니다.
밑에 제가 이번에 참고한 분들의 코드들입니다.
1. ‘Time & volume point of control (TPOC & VPOC)’ by quantifytools
2. ‘Volume Profile ’ by LuxAlgo
3. ‘Volume Profile and Volume Indicator by DGT’ by dgtrd
Volume profile zonesHi all!
This script calculates and shows the volume profile for the range of a higher timeframe candle. It then shows support or resistance (/supply or demand) zones based on the volume profiles with the most volume. The defaults are just my preferred settings so feel free to play with them! Also feel free to let me know about bugs and features. I already have a list of features to make, e.g.:
base on pivots
more info zone calculations, e.g. breaks and retests, virgin point of control etc.
add alerts
get rid of getPriceLevels()
get rid of _barVolumeProfile prefix
handle realtime
...
Best of trading luck!
