Liquidation Volume (Zeiierman)█ Overview
The Liquidation Volume (Zeiierman) indicator highlights real-time long and short liquidations across all timeframes on TradingView. The indicator assists traders in identifying potential liquidation points in the market based on volume and price movements. Liquidation, in this context, refers to the forced closure of a trader's position due to insufficient margin in their account to support open positions, often occurring during significant price movements.
█ How It Works
The indicator operates primarily through the computation of a MomentumAdjustedPrice function, which is applied to volume-weighted prices (open, high, low, close) adjusted for volatility.
█ How to Use
Identifying Support and Resistance Levels: Liquidation data can provide valuable insights into key market levels where significant trading activities occur. These levels often act as support or resistance in the price chart. Support levels are typically where an asset's price finds a floor, as buying interest is significant enough to outweigh selling pressure. Conversely, resistance levels are where an asset's price may find a ceiling, with selling interest outweighing buying pressure. By analyzing liquidation data, traders can identify these critical points.
Start of a New Trend:
The initiation of a new trend can often be identified by a significant shift in liquidation volumes near breakout levels.
Trend Continuations:
Trend continuations are periods where the current trend is sustained and further confirmed by liquidation patterns. For example, in an uptrend, continuous short liquidations might occur, suggesting that the trend is strong and likely to persist as bearish traders keep getting squeezed out. In a downtrend, continuous long liquidations can serve as confirmation that the trend is still in place. Recognizing these patterns in liquidation data can help traders to stay aligned with the prevailing trend and avoid premature exits or entries against the trend.
Trend Reversals: Patterns in liquidations can be crucial in signaling potential trend reversals. A sudden and significant change in liquidation volumes—like a spike in long liquidations during a downtrend or short liquidations during an uptrend—can indicate that the current trend is losing steam and a reversal may be imminent. This information can be particularly useful for traders looking to anticipate market turns and adjust their strategies accordingly.
Spot Potential Liquidation Points: By observing the liquidation candles and their colors, traders can identify where large liquidations are likely occurring, signaling potential market turning points.
Understand Market Sentiment: Changes in liquidation volumes can provide insights into bullish or bearish sentiment, helping traders gauge the market mood. By observing liquidation patterns and clusters, traders can get insights into prevailing market sentiments and emerging trends.
█ Settings
Liquidation Source: Allows selection between 'Price' and 'Volume' for liquidation analysis.
Volume Period: Determines the period over which volume is averaged.
Volatility Period: Sets the length for calculating standard deviation, influencing the volatility measure.
Candle Display Toggle: Enables or disables the display of liquidation candles on the chart.
Threshold: Sets the level at which liquidation bars are triggered.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Volumen
Price Volume Harmony Indicator [Nasan]The indicator "Price Volume Harmony Indicator " (abbreviated as PVHI) combines relative volume intensity (RVI) and relative price change (PC) to identify potential synergy or divergence between price and volume movements. Let's break down the key components and discuss how to interpret the output:
Relative Volume Intensity (RVI):
It calculates the mean volume intensity using simple moving averages (SMA) of different periods (5, 8, 13, and 144).
It then computes point volume intensity based on the current volume compared to the previous bar's volume.
The final RVI is a combination of mean and point volume intensities.
Relative Price Change (PC):
It calculates the median absolute deviation (MAD) and the price change relative to MAD for three different lengths (5, 8, and 13).
The average relative PC is a weighted combination of the three PC values.
Normalization:
RVI and PC are normalized using Z-scores (standard scores) to bring them to the same scale. This enables easier comparison.
Histogram Plotting:
The RVI and PC are plotted as histograms below the main price chart. Green color bars represent RVI, and blue color bars indicate PC. The RVI bars are light green when the RVI values are decreasing compared to previous bar. Similarly, when PC bars are light blue it indicates that the PC values are decreasing compared to previous bars.
There is a zero line +/- 0.5 SD lines movements above and below the SD lines are practically
significant.
Interpretation :
(1) Strong Bullish Movement :
This is when both the green bars (RVI) and blue bars (PC) increases and are on the same side above zero .
(2) Strong Bearish Movement :
This is when the green bars (RVI) increases and blue bars (PC) decreases. The green bars above zero but blue bars below zero.
(3) Weak Bullish Movement :
This is when the green bars (RVI) decreases and are below zero but the blue bars (PC) increases and are above zero .
(2) Weak Bearish Movement :
This is when both the green bars (RVI) and blue bars (PC) decreases. The green bars and blue bars are below zero.
This output is slightly hard to read but with practice can be read easily.
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.
ka66: Normalised/Relative VolumeThis is an idea taken from a John Bollinger (of Bollinger Bands fame) talk. Instead of showing volume with a moving average overlay, we show volume relative to its moving average:
avgVolume = sma(volume, 10) // several configurable MAs allowed
relativeVolume = volume / avgVolume
Now if we get a value of 1, that means the current volume is the same as its historical average. Under 0, less than average, and above zero, greater than its average.
If we get a value like 2, then current volume is twice its average. I hope the implication of this being displayed visually is becoming clearer.
We plot this relative volume as columns.
We then plot horizontal levels, like 1, 2, 3 to see the magnitude of the current volume relative to its average.
Consecutive rising or falling relative volume is shown in the same colour.
I am still exploring volume as trading data point, but we see some ideas from this visual representation:
How do volume patterns change across timeframes? Do we get better signals or higher or lower time frames (e.g. big relative volume spikes)
Can consecutive rises or falls indicate a big potential move, even though price is just fluctuating.
What about a switch from rise to fall.
If we get pinbars/spikes with a big relative volume spike, can we then infer more clearly whether buyers or sellers are in control.
Temporary imbalances 2.0 This indicator attempts to calculate potential points of imbalance and equilibrium based on VWAPs and modified moving averages. The idea is to determine if there has been a change in volume and perform the calculation from that point It uses the standard deviation to determine the significant imbalance threshold. Candles with bullish imbalances are highlighted in green, while candles with bearish imbalances are highlighted in red.
"It also features a set of VWAPs and modified moving averages that you can enable or disable."
When you activate the 'Show Anchor VWAP' option, it will add five modified VWAPs.
Practical Significance:
The Anchored VWAP is a volume-weighted average price that serves as a dynamic reference to assess the average price during specific moments of market imbalance.
During a bullish imbalance, the anchor_vwap reflects the VWAP at that moment, emphasizing price behavior during that specific period.
Similarly, in a bearish imbalance, the anchor_vwap provides the associated VWAP for that condition, highlighting price movements during the imbalance phase.
How to Use:
The anchor_vwap can be employed to contextualize the volume-weighted average price during critical moments associated with significant changes in market imbalance.
By analyzing price behavior during and after periods of imbalance, the Anchored VWAP can help better understand market dynamics and identify potential areas of support or resistance.
Show VWAP Percent Imbalance"
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The "showDeltaVWAP" is a toggleable setting that you can turn on or off. When activated, it displays special lines on the chart. Let's understand what these lines represent:
Delta Anchor VWAP:
A green line (Delta Anchor VWAP) represents a measure of market volume imbalance.
Delta2 Anchor VWAP:
A red line (Delta2 Anchor VWAP) shows another perspective of volume imbalance.
VWAP Delta Volume:
A light blue line (VWAP Delta Volume) displays a volume-weighted average of price.
VWAP Delta Volume2:
An orange line (VWAP Delta Volume2) shows another view of the volume-weighted average of price.
Delta3 Anchor VWAP:
A light blue line (Delta3 Anchor VWAP) represents a combination of the previous measures.
Delta4 Anchor VWAP:
A purple line (Delta4 Anchor VWAP) is another combination, providing an overall view.
These lines are based on different conditions and calculations related to trading volume. When you activate "showDeltaVWAP," these lines appear on the chart, aiding in better understanding market behavior.
"Show Faster Volatility" is an option that you can enable or disable. When activated (set to true), it displays special lines on the chart called "Faster Volatility VWAP," "Faster Volatility VWAP2," and "Faster Volatility VWAP3." Let's understand what these lines represent:
Faster Volatility VWAP:
A purple line (Faster Volatility VWAP) is a Volume Weighted Average Price (VWAP) that is calculated more quickly based on short-term price reversal patterns.
Faster Volatility VWAP2:
A light gray line (Faster Volatility VWAP2) is another Volume Weighted Average Price (VWAP) that is calculated even more quickly based on even shorter-term price reversal patterns.
Faster Volatility VWAP3:
A purple line (Faster Volatility VWAP3) is another Volume Weighted Average Price (VWAP) calculated rapidly based on even shorter-term price reversal patterns.
These lines are designed to indicate moments of possible exhaustion of volatility in the market, suggesting that there may be a subsequent increase in volatility. When you activate "Show Faster Volatility," these lines are displayed on the chart.
"Show Average VWAPs Imbalance" displays weighted averages of different Volume Weighted Average Prices (VWAPs) in relation to specific market conditions. Here's an explanation of each component:
Standard VWAP:
The blue line represents the standard VWAP, a volume-weighted average of asset prices over a specific period.
VWAP with Added Imbalance (avg_vwap2):
The pink line is a weighted average that adds an imbalance value to the standard VWAP. This component highlights periods of market imbalance.
VWAP with Balance (avg_vwap3):
The lilac line is a weighted average that adds balance based on the imbalance between uptrend and downtrend, reflecting changes in volume. This provides insights into supply and demand dynamics.
Overall Average of VWAPs (avg_vwaptl):
The violet line is a weighted average that incorporates both standard and adjusted VWAPs, offering an overview of market behavior under different considered conditions.
Visual Customization (Show Average VWAPs Imbalance):
Users have the option to show or hide these average lines on the chart, allowing for a clear visualization of market trends.
"Show Min Variation VWAP" is associated with the calculation and display of a smoothed version of the Volume Weighted Average Price (VWAP), taking into account the minimum price variation over a specific period.
"How Imbalance Anchor VWAP Calculated as the smoothed relationship between liquidity difference and maximum VWAP equilibrium" is associated with the calculation and display of a smoothed version of the Imbalance Anchor VWAP. Here is a detailed explanation:
Calculations and Smoothing:
The variable "smoothed_difference" represents the exponential moving average (EMA) of the difference between two variables related to liquidity.
"smoothed_difference2" is the division of "smoothed_difference" by the maximum variation of the VWAP Equilibrium.
"smoothed_difference3" involves additional manipulation of "smoothed_difference" and "vwap_delta3."
"smoothed_difference4" incorporates the previous results, adjusted by the value of the VWAP.
Visual Customization:
The user has the option to enable or disable the display on the chart.
The line is colored in a shade of green.
It provides a smoothed representation of the Imbalance Anchor VWAP.
The line is colored in a shade of blue, and the calculation involves the summation of moving averages (20, 50, 200). Afterward, there is division by 3. Additionally, there is the summation of moving averages (766, 866, 966), divided by 3. The final step is to add these results together and divide by 2. media name is Imbalance Value2
Show VWAP Equilibrium (Max Variation) Calculated as the difference between two VWAPs derived from the highest and lowest price changes
Show Equilibrium VWAP Calculated as the sum of VWAP and (sma200 - sma20)
calculate the difference between the media of 200 to 20
Show Equilibrium VWAP Calculated as the sum of VWAP and (766+866+966)/3 - (sma200 - sma20)
Show Equilibrium VWAP Standard Deviation Calculated as the Exponential Moving Average (EMA) of the Standard Deviation of SMA (sma200 + sma20 + sma8)/3
Show Equilibrium VWAP Delta Calculated as the ratio of the smoothed VWAP Delta Result componentes
Show Standard Deviation Equilibrium VWAP Delta: Calculated as the Standard Deviation between the Average of VWAP Delta Result Components and Their Smoothed Versions
This average attempts to calculate the equilibrium."
vwap_equilibrium:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price (hl2) multiplied by volume, focusing on periods of volume equilibrium.
Calculation: Utilizes the simple moving average weighted (sma) of the product of the volume-weighted average price and volume only when there is no volume imbalance.
Interpretation: This indicator provides a view of the volume-weighted price trend during moments when the market is in equilibrium, meaning there is no noticeable imbalance in volume conditions. The calculation of VWAP is adjusted to reflect market characteristics during periods of stability.
vwap_percent_condition:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The objective of these two VWAPs is to calculate possible equilibrium points between buyers and sellers.
The indicator works for all timeframes This indicator can be adjusted according to the preferences and characteristics of the specific asset or market. It provides clear visual information and can be used as a complementary tool for technical analysis in trading strategies.
Interesting
Interesting
lookback period 7 , 12, 20,70,200, 500,766,866,966
imbalance threshold 2.4, 3.3 ,4.2
The objective of this indicator is to identify and highlight various points of imbalance and equilibrium.
Performante's Average Bitcoin Volume IndicatorThe volume of all major exchanges, including:
Bitfinex, Coinbase, Bitstamp, Bitmex, Kraken, Binance, Bithumb, Flyer, and OkEx
Volume Outlier Signal Detector (Based on IQR)This indicator can detect outliers in trading volume using the 1.5 IQR rule or the outlier formula.
The outlier formula designates outliers based on upper and lower boundaries. Any value that is 1.5 times the Interquartile Range (IQR) greater than the third quartile is designated as an outlier.
The indicator computes the Q3 (75th percentile) and Q1 (25th percentile) of a given volume dataset. The IQR is then calculated by subtracting the Q1 volume from the Q3 volume.
To identify volume outliers, the indicator uses the formula:
Q3 Volume + IQR Multiplier(1.5) * IQR
If the trading volume surpasses the volume outlier, the indicator will display either a green or red column.
A green column indicates that the current bar volume is higher than the volume outlier, and simultaneously, the current bar close is higher than the previous bar's close. Vice versa for the red column.
Moving averages are an optional parameter that can be added to filter out instances where the indicator shows a green or red column. If this option is enabled, the indicator will not display a green column if the price is not above the moving average, and vice versa for red columns.
Several settings can be customized to personalize this indicator, such as setting the moving average filter to higher timeframes. The MA type can also be switched, and IQR settings can be adjusted to fit different markets.
This indicator only works with TradingView charts with volume data.
***Disclaimer:
Before using this indicator for actual trading, make sure to conduct a back test to ensure the strategy is not a losing one in the long run. Apply proper risk management techniques, such as position sizing and using stop loss.
Fourier Smoothed Volume Zone Oscillator (FSVZO) [AlgoAlpha]Description
The Fourier Smoothed Volume Zone Oscillator (FSVZO) is an implementation of the Discrete Fourier Transform in a Volume Zone Oscillator. Its purpose is to smooth price data and reduce noise to provide a more clear and accurate indication of price movement. This indicator also includes additional EMA smoothing to accurately depict reversals.
Discrete Fourier Transform
The Discrete Fourier Transform (DFT) is a mathematical algorithm used to convert discrete time-domain data into its frequency-domain representation. By decomposing a signal into its constituent frequencies, it reveals the amplitude and phase information associated with each frequency component.
Volume Zone Oscillator
The Volume Zone Oscillator is an indicator that combines volume and price data to provide insights into market trends and momentum. It calculates the difference between the volume traded above and below a specified price level and represents it as a line plot on the chart. The Volume Zone Oscillator helps traders identify periods of high buying or selling pressure and can be used to confirm trends, spot divergences, and generate trading signals. By analyzing the relationship between volume and price, traders can gain a deeper understanding of market dynamics and make more informed trading decisions.
Features
This indicator incorporates Ehler's Universal Oscillator concept and presents a histogram to provide valuable insights into the market's noise levels. Ehler's Universal Oscillator represents the statistical model that characterizes random and unpredictable market behavior. By utilizing this concept, the histogram enhances traders' ability to identify periods of increased or decreased volatility in the market.
How to use it?
Green dots and lines represent bullish price movement, while red dots and lines indicate bearish price movement. These signals gain additional strength when considering our oversold and overbought zones. Traders and investors can leverage these signals to initiate long positions when green signals coincide with oversold conditions, and vice versa. By combining these signals in synergy with Ehler's Universal Oscillator, a more precise representation of market trends can be achieved. To optimize its effectiveness, it is advisable to integrate this indicator with complementary technical analysis tools and incorporate it into a comprehensive trading strategy. Traders are encouraged to explore diverse settings and timeframes to align the indicator with their individual trading preferences and adapt it to prevailing market conditions.
Utility
By combining the FSVZO indicator with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions. It empowers traders and investors to evaluate the intensity of buying or selling pressure, detect potential trend reversals or continuations, and ultimately make more informed trading decisions. This information can serve as confirmation or validation for other technical indicators, enabling traders to identify potential market turning points and enhance their comprehension of market dynamics.
The indicator offers several valuable applications, including the detection of divergence patterns between volume and price, identification of accumulation or distribution phases, and assessment of overall market trend strength. It accommodates various trading styles, such as swing trading, trend following, or mean reversion strategies. By leveraging these capabilities, traders can expand their toolkit and make more informed trading decisions.
Originality
The originality of the script lies in the combination of the Fourier analysis, white noise calculations, and the Volume Zone Oscillator. It provides a unique perspective on market dynamics and can be used to identify potential trading opportunities based on overbought and oversold conditions as well as trend reversals. Special thanks to @QuantiLuxe for their assistance in the development of this indicator
Total number strength by ticker volumeThis is about stocks, which I always analyze.
Figure this out by looking at what the code calls ta.secutity.
This indicator plots the highest value of the ratio of total volume to individual volume for the stock you are analyzing, and the histogram tumbles to red when the stock changes in that value. The changed value is plotted as a label above that histogram. By using this indicator, you can determine which is currently the focus of attention, and if there are outliers, you will know by the histogram's detachment.
The parameters are explained below, but Timefream is the market value to be determined
setvalue sets the item to be judged, and lenght sets the time period to be judged. setvalue is the parameter that determines the timeframe for the judgment. vol is the volume, VP is the total purchase price, VPMA is its average, VPMAD is the detachment from its average, MA is the average of the vol, MAD is the detachment from its average, LRC is the average of the vol, and LRC is the average of the vol. value of linear regression, and also
The calculation of detachment is not negative because it comes out as a square, but it is not a problem because it is calculated as a percentage.
There is a *problem, and if the timefreame to be displayed is not calculated below the value of timefreame, an error will occur. We are currently searching for a solution to this problem. If you know the solution, I would appreciate it if you could let me know in the chat.
MADALGO's Fear and Greed OscillatorThe Fear and Greed Oscillator is a dynamic tool designed to gauge market sentiment by analyzing various components such as volatility, momentum, and volume. This indicator synthesizes multiple metrics to provide a singular view of market emotion, oscillating between fear and greed.
🔷 Calculation -
The oscillator integrates the following components, each normalized and weighted to contribute equally:
ATR (Average True Range): Represents market volatility.
MACD (Moving Average Convergence Divergence): Captures market momentum.
RSI (Relative Strength Index): Provides insights into overbought or oversold conditions.
Volume: Reflects market participation levels.
Each component is first normalized to ensure a balanced impact and then averaged to create the final oscillator value.
🔷 Color Coding -
The oscillator's plot changes color based on its value, representing market sentiment:
Green: Indicates a leaning towards greed.
Red: Suggests a leaning towards fear.
The intensity of the color represents the strength of the sentiment.
🔷 Usage -
This indicator is valuable for traders looking to understand market sentiment. It works best when combined with other forms of analysis, such as fundamental or other technical indicators, to form a comprehensive trading strategy.
🔷 Signal Lines -
Two horizontal lines represent extreme conditions:
A line for Extreme Fear.
Another for Extreme Greed.
These lines help identify when the market sentiment is at potentially unsustainable levels.
🔷 Customization -
The Fear and Greed Oscillator is designed with flexibility in mind, allowing users to adjust several parameters to match their specific analysis requirements. Understanding and utilizing these customization options can significantly enhance the indicator's relevance and effectiveness in various market conditions.
1. Length Parameters:
ATR and RSI Length: This input determines the period over which the Average True Range (ATR) and the Relative Strength Index (RSI) are calculated. Adjusting this length can affect the sensitivity of the oscillator to recent market movements. A shorter length makes the oscillator more responsive to recent changes, while a longer length smoothens it, reducing sensitivity to short-term fluctuations.
MACD Parameters: These include the Fast Length, Slow Length, and Signal Smoothing. By adjusting these, users can control how the Moving Average Convergence Divergence (MACD) component reacts to price movements. This customization is crucial for aligning the oscillator with different trading strategies, whether short-term or long-term focused.
Volume Length: This parameter sets the period for the moving average and standard deviation calculations of the volume component. Altering this length allows the oscillator to either emphasize recent volume changes or consider a broader historical context.
2. Weight Adjustments:
Component Weights: Each component (ATR, MACD, RSI, Volume) has an associated weight factor. These weights determine the relative influence of each component on the final oscillator value. Users can increase the weight of a component to give it more influence or decrease it to lessen its impact. This feature is particularly beneficial for traders who have a preference or insight into which market aspects are more indicative of fear or greed at given times.
Balancing the Components: The key to effective customization lies in balancing these weights to reflect the user's market perspective and trading style. For instance, a trader focusing on volatility might increase the weight of the ATR, while one interested in momentum might prioritize the MACD and RSI weights.
3. Color and Signal Line Customization:
Color Intensity: The intensity of the color gradient of the oscillator line can be a visual aid in quickly identifying market sentiment. Users can experiment with the colorValue calculation within the script to adjust how rapidly the color changes with the oscillator values
Extreme Levels: The extreme fear and greed levels, represented by horizontal lines, are customizable. Users can set these levels based on historical data analysis or personal risk tolerance. These lines act as alerts for potentially overextended market conditions.
🔷 Limitations -
As with any technical tool, the Fear and Greed Oscillator should not be used in isolation. It does not predict market direction but rather gauges the prevailing market emotion. Its effectiveness may vary across different markets and timeframes.
🔷 Conclusion -
The Fear and Greed Oscillator offers a unique perspective on market sentiment, encapsulating various aspects of market behavior into a single indicator. It serves as a versatile tool for traders aiming to understand the emotional undercurrents of the market.
🔷 Risk Disclaimer -
Financial trading involves significant risk. The value of investments can fluctuate, and past performance is not indicative of future results. This indicator is for informational purposes and should not be construed as financial advice. Always consider your personal circumstances and seek independent advice before making financial decisions.
Logarithmic CVD [IkkeOmar]The LCVD is another Mean-Reversion Indicator. it doesn't detect trends and does not give a signal per se. However the logarithmic transformation is made to visualize the direction of the trend for the volume. This allows you to see if money is flowing in or out of an asset.
What it does is tell you if we have a flashcrash based on the difference in volume.
Think of this indicator like a form of a volatility index.
Smoothing input:
The only input is an input for the smoothing length of the logDelta.
Volume Calculation:
// @IkkeOmar
//@version=5
indicator('Logarithmic CVD', shorttitle='CVD', overlay=false)
smooth = input.int(defval = 25, title = "Smoothing Distance")
// Calculate buying and selling volume
askVolume = volume * (close > open ? 1 : 0) // Assuming higher close than open indicates buying
bidVolume = volume * (close < open ? 1 : 0) // Assuming lower close than open indicates selling
// Delta is the difference between buying and selling volume
delta = askVolume - bidVolume
// Apply logarithmic transformation to delta
// Adding a check to ensure delta is not zero as log(0) is undefined
logDelta = delta > 0 ? math.log(math.abs(delta)) * math.sign(delta) : - math.log(math.abs(delta)) * math.sign(delta)
// use the the ta lib for calculating the sma of the logDelta
smoothLogDelta = ta.sma(logDelta, smooth)
// Create candlestick plot
plot(logDelta, color= color.green, title='Logarithmic CVD')
plot(smoothLogDelta, color= color.rgb(145, 37, 1), title='Smooth CVD')
These lines calculate the buying and selling volumes. askVolume is calculated as the total volume when the closing price is higher than the opening price, assuming this indicates buying pressure. bidVolume is calculated as the total volume when the closing price is lower than the opening price, assuming selling pressure.
The Delta is simply the difference between buying and selling volumes.
Logarithmic Transformation:
logDelta = delta > 0 ? math.log(math.abs(delta)) * math.sign(delta) : - math.log(math.abs(delta)) * math.sign(delta)
Applies a logarithmic transformation to delta. The math.log function is used to calculate the natural logarithm of the absolute value of delta. The sign of delta is preserved to differentiate between positive and negative values. This transformation helps in scaling the delta values, especially useful when dealing with large numbers.
This script essentially provides a visual representation of the buying and selling pressures in a market, transformed logarithmically for better scaling and smoothed for trend analysis.
Hope it makes sense!
Stay safe everyone!
Don't hesitate to ask any questions if you have any!
Tick Volume Direction IndicatorTick Volume Direction Indicator
This indicator captures:
• tick volume
• tick direction
The settings are as follows:
• volume or base currency value selection.
• label distance (away from the low of the candle).
• Tick volume - on/off switch for tick volume.
• label size.
• Up tick move color.
• tick move absorbed - when the tick doesn't change position.
• Down tick move.
On the first initial load, it will have the existing volume data as "?" as tradingview doesn't have a history of each tick.
Be aware, any settings change you make will refresh the tick data from start.
This indicator is one of the best real-time ways of seeing buying and selling pressure.
HTF Volume by Prosum SolutionsOverview of Features
This indicator was inspired by the work of "LonesomeTheBlue" in the script called "Volume Multi Time Frame" . This script will provide a highly customizable interface to specify the higher timeframe period for the volume with the ability to link to the "HTF Candles by Prosum Solutions" indicator using the "HTF Setting Code" data point, as well as adjusting various styling options for the volume bar color fill and border.
Usage Information
The indicator can be applied to any chart at any time frame. When the "Chart" option is chosen for the "Timeframe" field, the indicator will attempt to find a higher timeframe resolution to ensure the volume bars are drawn. The indicator will simply accumulate the volume value for each candlestick bar and reset when the new high timeframe period has started. The color of the volume bars are relative to the higher timeframe setting so that you can visually interpret when the volume in a rising or falling state relative to the higher timeframe price action.
If you choose to add the "HTF Candles by Prosum Solutions" indicator, you can link this indicator to it by choosing the "HTF Candles" option for the "Timeframe Source" field and then choosing the "HTF Setting Code" option for the "HTF Candles" field. At this point, whenever you adjust the high timeframe setting in the "HTF Candles by Prosum Solutions" indicator, this indicator will automatically adjust the timeframe to match it, thereby reducing the steps you need to take to keep the two indicators in sync.
Enjoy! 👍
AlgoDude_Volume1. Timeframe Selection (selectedTimeframe):
Allows the user to choose the timeframe for the volume data analysis.
Options range from 1 minute to 1 month, including 1, 3, 5, 15, 30, 45 minutes, 1, 2, 3, 4 hours, and daily, weekly, monthly.
2.Moving Average Length (maLength):
Users can specify the length of the moving average applied to the inverse volume.
The range for this input is from 1 to 200 periods, with a default value of 14.
These inputs provide flexibility in analyzing volume data over various timeframes and smoothing the inverse volume data with a moving average of chosen length.
Relative Volume Candles [QuantVue]In the words of Dan Zanger, "Trying to trade without using volume is like trying to drive a few hundred miles without putting gas in your tank. Trying to trade without chart patterns is like leaving without having an idea how to get there!"
Volume tends to show up at the beginning and the end of trends. As a general rule, when a stock goes up on low volume, it's seen as negative because it means buyers aren't committed. When a stock goes down on low volume, it means that not many people are trying to sell it, which is positive.
The Relative Volume Candles indicator is based on the Zanger Volume Ratio and designed to help identify key volume patterns effortlessly, with color coded candles and wicks.
The indicator is designed to be used on charts less than 1 Day and calculates the average volume for the user selected lookback period at the given time of day. From there a ratio of the current volume vs the average volume is used to determine the candle’s colors.
The candles wicks are color coded based on whether or not the volume ratio is rising or falling.
So when is it most important to have volume? When prices break out of a consolidation pattern like a bull flag or cup and handle pattern, volume plays a role. When a stock moves out of a range, volume shows how committed buyers are to that move.
Note in order to see this indicator you will need to change the visual order. This is done by selecting the the 3 dots next to the indicator name, scrolling down to visual order and selecting bring to front.
Indicator Features
🔹Selectable candle colors
🔹Selectable ratio levels
🔹Custom lookback period***
***TradingView has a maximum 5,000 bar lookback for most plans. If you are on a lower time frame chart and you select a lookback period larger than 5,000 bars the indicator will not show and you will need to select a shorter lookback period or move to a higher time frame chart.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
Time & Sales (Tape) [By MUQWISHI]▋ INTRODUCTION :
The “Time and Sales” (Tape) indicator generates trade data, including time, direction, price, and volume for each executed trade on an exchange. This information is typically delivered in real-time on a tick-by-tick basis or lower timeframe, providing insights into the traded size for a specific security.
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▋ OVERVIEW:
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▋ Volume Dynamic Scale Bar:
It's a way for determining dominance on the time and sales table, depending on the selected length (number of rows), indicating whether buyers or sellers are in control in selected length.
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▋ INDICATOR SETTINGS:
#Section One: Table Settings
#Section Two: Technical Settings
(1) Implement By: Retrieve data by
(1A) Lower Timeframe: Fetch data from the selected lower timeframe.
(1B) Live Tick: Fetch data in real-time on a tick-by-tick basis, capturing data as soon as it's observed by the system.
(2) Length (Number of Rows): User able to select number of rows.
(3) Size Type: Volume OR Price Volume.
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▋ COMMENT:
The values in a table should not be taken as a major concept to build a trading decision.
Please let me know if you have any questions.
Thank you.
Kashif_MFI+RSI+BBMerging Money Flow Index (MFI), Relative Strength Index (RSI), and Bollinger Bands in TradingView can offer traders a comprehensive view of market conditions, providing insights into potential price reversals, overbought or oversold conditions, and potential trend changes. Here are some benefits of combining these indicators:
Confirmation of Overbought and Oversold Conditions:
MFI and RSI are both oscillators that measure overbought and oversold conditions. When MFI and RSI readings are high (above their respective overbought levels), and the price is near or above the upper Bollinger Band, it may suggest that the asset is overextended and a reversal could be imminent. Conversely, when MFI and RSI readings are low (below their respective oversold levels) and the price is near or below the lower Bollinger Band, it may indicate potential buying opportunities.
Divergence Analysis:
Traders often look for divergences between price action and MFI/RSI. If the price is making new highs, but MFI/RSI is not confirming these highs (bearish divergence), it could signal weakening momentum and a possible reversal. Combining this analysis with Bollinger Bands can add another layer of confirmation, especially if the price is touching or exceeding the upper Bollinger Band during this divergence.
Volatility Confirmation:
Bollinger Bands provide a measure of volatility by expanding and contracting based on price volatility. If the bands are widening, it indicates increased volatility. Combining this information with MFI and RSI readings can help traders assess the strength of a trend. For example, during a strong uptrend, if MFI and RSI are high and Bollinger Bands are expanding, it may suggest a sustained bullish trend.
Identifying Trend Reversals:
The combination of MFI, RSI, and Bollinger Bands can be useful in identifying potential trend reversals. For instance, if MFI and RSI are in overbought conditions and the price is significantly above the upper Bollinger Band, it may signal that the trend is reaching an extreme and could reverse. Conversely, if MFI and RSI are in oversold conditions and the price is near or below the lower Bollinger Band, it may suggest that selling pressure is exhausted, and a reversal might be in play.
Comprehensive Market Assessment:
By merging these indicators, traders get a more comprehensive view of market conditions. They can assess both momentum (MFI and RSI) and volatility (Bollinger Bands) simultaneously, helping them make more informed trading decisions.
It's important to note that no single indicator or combination of indicators guarantees accurate predictions in trading. Traders should use these tools as part of a broader analysis and consider other factors such as fundamental analysis, market trends, and risk management.
VWAP Oscillator (Normalised)Thanks:
Thanks to upslidedown for his VWAP Oscillator that served as the inspiration for this normalised version.
Core Aspects:
The script calculates the VWAP by considering both volume and price data, offering a comprehensive view of market activity.
Uses an adaptive normalization function to balance the data, ensuring that the VWAP reflects current market conditions accurately.
The oscillator includes customizable settings such as VWAP source, lookback period, and buffer percentage.
Provides a clear visual representation of market trends.
Usage Summary:
Detect divergences between price and oscillator for potential trend reversals.
Assess market momentum with oscillator’s position relative to the zero line.
Identify overbought and oversold conditions to anticipate market corrections.
Use volume-confirmed signals for enhanced reliability in trend strength assessments.
SaAy New Volume ComputationOverview of the Indicator
The "SaAy New Volume Computation" is a trading tool designed to give traders a clear understanding of market volume movements. It overlays on the main trading chart, providing insights into buying and selling pressures.
Key Features of the Indicator
Up and Down Volume Analysis
Buying Pressure (Up Volume) : This metric totals the trading volume on days when the market closes higher than it opens, indicating a bullish or positive market sentiment.
Selling Pressure (Down Volume) : Conversely, this measures the trading volume on days when the market closes lower than it opens, reflecting a bearish or negative sentiment.
Comparative Volume Analysis
Average Volume Comparison : The indicator also compares recent trading volume with the average volume over a set period. This comparison helps identify whether the current trading volume is unusually high or low compared to normal conditions.
Practical Use for Traders
Market Sentiment Understanding : By analyzing the up and down volumes, traders can get a sense of whether the market is dominated by buyers (bulls) or sellers (bears).
Volume Trend Identification: Comparing current trading volumes with the average volume can help traders spot trends or significant changes in market activity. For example, a higher than average volume on a day with rising prices might suggest strong buying interest and a possible continuation of the upward trend.
Conclusion
Overall, the "SaAy New Volume Computation" indicator is a valuable tool for traders. It simplifies the complex task of volume analysis, providing easy-to-understand metrics that indicate market trends and trader sentiment. This can help traders make more informed decisions and better understand the dynamics of the markets they are trading in.
Re-Anchoring VWAP TripleThe Triple Re-Anchoring VWAP (Volume Weighted Average Price) indicator is a tool designed for traders seeking a deeper understanding of market trends and key price levels. This indicator dynamically recalibrates VWAP calculations based on significant market pivot points, offering a unique perspective on potential support and resistance levels.
Key Features:
Dynamic Re-anchoring at All-Time Highs (ATH) : The first layer of this indicator continuously tracks the all-time high and recalibrates the VWAP from each new ATH. This VWAP line, typically acting as a dynamic resistance level, offers insights into the overbought conditions and potential reversal zones.
Adaptive Re-anchoring to Post-ATH Lows : The second component of the indicator shifts focus to the market's reaction post-ATH. It identifies the lowest low following an ATH and re-anchors the VWAP calculation from this point. This VWAP line often serves as a dynamic support level, highlighting key areas where the market finds value after a significant high.
Re-anchoring to Highs After Post-ATH Lows : The third element of this tool takes adaptation one step further by tracking the highest high achieved after the lowest low post-ATH. This VWAP line can act as either support or resistance, providing a nuanced view of the market's valuation in the recovery phase or during consolidation after a significant low.
Applications:
Trend Confirmation and Reversal Signals : By comparing the price action relative to the dynamically anchored VWAP lines, traders can gauge the strength of the trend and anticipate potential reversals.
Entry and Exit Points : By highlighting significant support and resistance areas, it assists in determining optimal entry and exit points, particularly in swing trading and mean reversion strategies.
Enhanced Market Insight : The dynamic nature of the indicator, with its shifting anchor points, offers a refined understanding of market sentiment and valuation changes over time.
Why Triple Re-Anchoring VWAP?
Traditional VWAP tools offer a linear view, often missing out on the intricacies of market fluctuations. The Triple Re-Anchoring VWAP addresses this by providing a multi-faceted view of the market, adapting not just to daily price changes but pivoting around significant market events. Whether you're a day trader, swing trader, or long-term investor, this indicator adds depth to your market analysis, enabling more informed trading decisions.
Examples:
OneThingToRuleThemAll [v1.4]This script was created because I wanted to be able to display a contextual chart of commonly used indicators for scalping and swing traders, with the ability to control the visual representation on the charts as their cross-overs, cross-unders, or changes of state happen in real time. Additionally, I wanted the ability to control how or when they are displayed. While looking through other community projects, I found they lacked the ability to full customize the output controls and values used for these indicators.
The script leverages standard RSI/MACD/VWAP/MVWAP/EMA calculations to help a trader visually make more informed decisions on entering or exiting a trade, depending on their understanding on what the indicators represent. Paired with a table directly on the chart, it allows a trader to quickly reference values to make more informed decisions without having to look away from the price action or look through multiple indicator outputs.
The main functionality of the indicator is controlled within the settings directly on the chart. There a user can enable the visual representations, or disable, and configure how they are displayed on the charts by altering their values or style types.
Users have the ability to enable/disable visual representations of:
The indicator chart
RSI Cross-over and RSI Reversals
MACD Uptrends and Downtrends
VWAP Cross-overs and Cross-unders
VWAP Line
MVWAP Cross-overs and Cross-unders
MVWAP Line
EMA Cross-overs and Cross-unders
EMA Line
Some traders like to use these visual indications as thresholds to enter or exit trades. Its best to find out which ones work the best with the security you are trying to trade. Personally, I use the table as a reference in conjunction with the RSI chart indicators to help me decide a logical trailing stop if I am scalping. Some users might like the track EMA200 crossovers, and have visual representations on the chart for when that happens. However, users may use the other indicators in other methods, and this script provides the ability to be able to configure those both visually and by value.
The pine script code is open source and itself is fairly straightforward, it is mostly written to provide the ultimate level of control the the user of the various indicators. Please reach out to me directly if you would like a further understanding of the code and an explanation on anything that may be unclear.
Enjoy :)
-dead1.
MTF External Range Liquidity - SMC IndicatorsThe Multi-Timeframe External Range Liquidity highlights possible “Key Liquidity Zones” above and below Short-Term highs and lows. Allowing for the filtering out of shorter-term swings and easily identifying levels for possible “liquidity runs” or “stop runs”.
Purged Liquidity
This shows areas where the price has already reached above previous key highs or below previous key lows. Recognizing “Purged Liquidity” areas is useful for historical analysis and understanding prior liquidity-driven movements.
Open Liquidity
These mark possible or potential Open Liquidity Zones where the price might reach above or below short-term key highs and lows.
Multi-Timeframe Analysis
The Multi Timeframe Feature allows traders to have all “key Liquidity Levels” from higher and lower timeframes relative to the current timeframe. (Weekly and down to the 1-Minute Chart) while trading in real-time allowing the trader to keep the higher time frame “levels” in mind when trading on lower time frames.
1W BSL & 1W SSL indicate levels of transposed from the Weekly timeframe to the Daily timeframe or lower.
1D BSL & 1D SSL indicate levels of transposed from the Daily timeframe to the 4H timeframe or lower.
4H BSL & 4H SSL indicate levels of transposed from the 4H timeframe to the 1H timeframe or lower.
1H BSL & 1H SSL indicate levels of transposed from the 1H timeframe to the 15M timeframe or lower.
15M BSL & 15M SSL indicate levels of transposed from the 15M timeframe to the 5M timeframe or lower.
5M BSL & 5M SSL indicate levels of transposed from the 5M timeframe to the timeframes lower than 5M.
How This Can Help with Analysis
Timing Entries
This tool can be used to look for possible entry levels by looking at where the last run on liquidity (Purged Liquidity) above a previous key high or low was. The trader would use this indicator by waiting until the liquidity is purged before looking for a possible trade setup.
This helps in waiting for entries and may avoid or reduce the number of entries where the trade would get stopped due to an early entry.
Setting Possible Targets
This indicator can be used to look for higher time frame “Open Liquidity” key levels above short-term highs or below short-term lows as potential targets.
Other Key Features
Alerts on selected time frame “key levels”
Choose to show and hide levels on any timeframe.
Choose the number of the Purged and Open Liquidity desired to show on the chart.
Highlights the Daily, Weekly, and Monthly Highs and Lows.
Liquidity composition / quantifytools- Overview
Liquidity composition divides each candle into sections that are used to display transaction activity at price. In simple terms, an X-ray through candle is formed, revealing the orderflow that built the candle in greater detail. Liquidity composition consists of two main components, lots and columns. Lots and columns can be used to visualize user specified volume types, currently supporting net volume and volume delta. Lots and columns can be used to visualize same or different volume types, allowing a combination of volume footprint, volume delta footprint and volume profile in one single view. Liquidity composition principally works on any chart, whether that is equities, currencies, cryptocurrencies or commodities, even charts with no volume data (in which case volatility is used to approximate transaction activity). The script also works on any timeframe, from minute charts to monthly charts. Orderflow can be observed in real-time as it develops and none of the indications are repainted.
Example: Displaying same volume types on lots and columns
Example: Displaying different volume types on lots and columns
Liquidity composition supports user specified derivative data, such as point of control(s) and net activity coloring. Derivative data can be calculated based on either net volume or volume delta, resulting in different highlights.
With net volume, volume delta and derivative data in one view, key orderflow events such as delta imbalances, high volume nodes, low volume nodes and point of controls can be used to quickly identify accumulation/distribution, imbalances, unfinished/finished auctions and trapped traders.
Accessing script 🔑
See "Author's instructions" section, found at bottom of the script page.
Key takeaways
- Liquidity composition breaks down transaction activity at price, measured in net volume or volume delta
- Developing activity can be observed real-time, none of the indications are repainted
- Transaction activity is calculated using volumes accrued in lower timeframe price movements
- Lots and columns can be used to display same or different volume types (e.g. volume delta lots and net volume columns) in single view
- Users can specify derivative data such as volume delta POCs, net volume POC and net activity coloring
- For practical guide with practical examples, see last section
Disclaimer
Orderflow data is estimated using lower timeframe price movement. While accurate and useful, it's important to note the calculations are estimations and are not based on orderbook data. Estimates are calculated by allotting volume developing on lower timeframe chart to its respective section based on closing price. Volume delta (difference between buyers/sellers) is calculated by subtracting down move volumes (sell volume) from up move volumes (buy volume). Accuracy of the orderflow estimations largely depends on quality of lower timeframe chart used for calculations, which is why this tool cannot be expected to work accurately on illiquid charts with broken data.
Liquidity composition does not provide a standalone trading strategy or financial advice. It also does not substitute knowing how to trade. Example charts and ideas shown for use cases are textbook examples under ideal conditions, not guaranteed to repeat as they are presented. Liquidity composition should be viewed as one tool providing one kind of evidence, to be used in conjunction with other means of analysis.
- Example charts
Chart #1: BTCUSDT
Chart #2: EURUSD
Chart #3: ES futures
- Calculations
By default, size of sections and lower timeframe accuracy are automatically determined for all charts and timeframes. Number of lower timeframe price moves used for calculating orderflow is kept at fixed value, by default set to 350. Accuracy value dictates how many lower timeframe candles are included in the calculation of volume at price. At 350, the script will always use 350 lower timeframe price movements in calculations (when possible). When calculated dynamic timeframe is less than 1 minute, the script switches to available seconds based timeframes. Minimum dynamic timeframe can be capped to 1 minute (as seconds based timeframes are not available for all plans) or dynamic timeframe can be overridden using an user specified timeframe.
Example: Calculating dynamic lower timeframe
Main chart: 4H / 240 minutes
Accuracy value: 100
Formula: 240 minutes / 100 = 2.4 minutes
Timeframe used for calculations = 2 minutes
Section size is automatically determined based on typical historical candle range, the bigger it is, the bigger the section size as well. Like dynamic timeframe, automatic section size can be manually overridden by user specified size expressed in ticks (minimum price unit). Users can also adjust sensitivity of automatic sizing by setting it higher (smaller sections, more detail and more noise) or lower (less sections, less detail and less noise). Section size and dynamic timeframe can be monitored via metric table.
Volume at price is calculated by allotting volume associated with a lower timeframe price movement to its respective section based on closing price (volume is stored to the section that covers closing price). When used on a chart with no volume data, volatility is used instead to determine likely magnitude of participation. Volume delta (difference between buyers/sellers) is calculated by subtracting down move volumes (sell volume) from up move volumes (buy volume). Volumes accrued in sections are monitored over a longer period of time to determine a "normal" amount of activity, which is then used to normalize accrued volumes by benchmarking them against historical values.
Volume values displayed on the left side represent how close or far volume traded at given section is to an extreme, represented by value of 10 . The more value exceeds 10, the more extreme transaction activity is historically. The lesser the value, the less extreme (and therefore more typical) transaction activity is. Users can adjust sensitivity of volume extreme threshold, either by increasing it (more transaction activity is needed to constitute an extreme) or decreasing it (less transaction activity is needed to constitute an extreme).
Example: Interpreting volume scale
0 = Very little to no transaction activity compared to historical values
5 = Transaction activity equal to average historical values
10 = Transaction activity equal to an extreme in historical values
10+ = The more transaction activity exceeds value of 10, the more extreme it is historically
Accuracy of orderflow data largely depends on quality of lower timeframe data used in calculations. Sometimes quality of underlying lower timeframe data is insufficient due to suboptimal accuracy or broken lower timeframe data, usually caused by illiquid charts with gaps and inconsistent values. Therefore, one should always ensure the usage of most liquid chart available with no gaps in lower timeframe data. To combat poor orderflow data, a simple data quality check is conducted by calculating percentage of sections with volume data out of all available sections. Idea behind the test is to capture instances where unusual amount of sections are completely empty, most likely due to data gaps in LTF chart. E.g. 90% of sections hold some volume data, 10% are completely empty = 90% data quality score.
Data quality score should be viewed as a metric alerting when detail of underlying data is insufficient to consider accurate. When data quality score is slightly below threshold, lower timeframe chart used for calculations is likely fine, but accuracy value is too low. In this case, one should increase accuracy value or manually override used timeframe with a smaller one. When data quality score is well below threshold, lower timeframe chart used for calculations is likely broken and cannot be fixed. In this case, one should look for alternative charts with more reliable data (e.g. ES1! -> SPY, BITSTAMP:BTCUSD -> BINANCE:BTCUSDT).
Example : When insufficient data quality scores can/cannot be fixed
- Derivative data
Point of control
Point of control, referring to point in price where transaction activity is highest, can be calculated based on the volume type of lots or columns (based on net volume or volume delta). Depending on the calculation basis, displayed point of controls will vary. POC calculated based on net volume is no different from traditional POC, it is simply the section with highest amount of transaction activity, marked with an X. When calculating POC based on volume delta, the script will highlight two point of controls, named leading and losing point of control . Leading POC refers to lot with highest amount of volume delta, marked with an X. If leading POC was net buy volume, losing POC is marked on section with highest net sell volume, marked with S respectfully. Same logic applies in vice versa, if leading POC is net sell volume, losing POC is marked on highest buy volume section, using the letter B.
Net activity
Similarly to point of control calculation, net activity can be calculated based on either volume types, lots or columns. When calculating net activity based on net volume, candles will be colorized according to magnitude of total volume traded. When calculating net activity based on volume delta, candles will be colorized according to side with most volume traded (buyers or sellers). Net activity color can be applied on borders or body of a candle.
- Visuals
Lots, columns, candles and POCs can be colorized using a fixed color or a volume based dynamic color, with separate color options for buy side volume, sell side volume and net volume.
Metric table can be offsetted horizontally or vertically from any four corners of the chart, allowing space for tables from other scripts.
Table sizes, label sizes and offsets for visuals are fully customizable using settings menu.
- Practical guide
OHLC data (candles) is a simple condensed visualization of an auction market process. Candles show where price was in the beginning of an auction period (timeframe), the highest/lowest point and where price was at the end of an auction. The core utility of Liquidity composition is being able to view the same auction market process in much greater detail, revealing likely intention, effort and magnitude driving the process. All basic orderflow concepts, such as ones presented by auction market theory can be applied to Liquidity composition as well.
The most obvious and easy to spot use case for orderflow tools is identifying trapped traders/absorption, seen in high transaction activity at the very highs/lows of a candle or even better, at wicks. High participation at wicks can be used to identify forced orders absorbed into limit orders, idea behind being that when high transaction activity is placed at a wick, price went one direction with a lot of participation (high effort) and came right back up (low impact) within the same time period.
Absorption can show itself in many ways:
- Extreme buy volume sections at wick highs or buy side POC at wick highs
- Multiple, clustered high buy volume sections (but not extreme) at wick highs
- Positive net volume delta into a reversal down
- Extreme sell volume sections at wick lows or sell side POC at wick lows
- Multiple, clustered high sell volume sections (but not extreme) at wick lows
- Negative net volume delta into a reversal up
- Extreme net volume sections at or net volume POC at wick highs/lows
- Extreme net volume into a reversal up/down
For accurate analysis, orderflow based events should be viewed in the context of price action. To identify absorption, it's best to look for opportunities where an opposing trend is clearly in place, e.g. absorption into highs on an uptrend, absorption into lows on a downtrend. When price is ranging without a clear trend or there's no opposing trend, extreme activity at an extreme end of a candle might be aggressive participants attempting to initiate a new trend, rather than getting absorbed in the same sense. With enough effort put into pushing price to the opposite direction at overextended price, a shift in trend direction might be near.
Price action based levels are a great way to get context around orderflow events. Simple range highs/lows as a single data point serve as a high probability regimes for reversals, making them a great point of confluence for identifying trapped traders.
Low to zero volume sections can be used to identify points in price with little to no trading, leaving a volume null/void behind. Typically sections like these represent gaps on a lower timeframe chart, which can be used as reference levels for targets and support/resistance.
Net volume can be used for same purposes as above, but for determining general intention of market participants it's a much more suitable tool than volume delta. According to auction market theory, low/no participation is considered to reject prices and high participation is considered to accept prices. With this concept in mind, unfinished auctions occur when participation is high at highs or high at lows, idea behind being that participants are showing willingness and interest to trade at higher or lower prices. Auction is considered finished when the opposite is true, i.e. when participants are not showing willingness to trade at higher/lower prices. In general, direction of unfinished auctions can be expected to continue shortly and direction of unfinished auctions can be expected to hold.
While shape of volume delta and net volume are usually similar, they're not the same thing and do not represent the same event under the hood. Volume delta at 0 does not necessarily mean participation is 0, but can also mean high participation with equal amount of buying and selling. With this distinction in mind, using volume delta and net volume in tandem has the benefit of being able to identify points in price with a lot of up and down price movement packed into a small area, i.e. consolidation. Points in price where price hangs around for an extended period of time can be used to identify levels of interest for re-tests and breakout opportunities.
