Bollinger Bands Heatmap (BBH)The Bollinger Bands Heatmap (BBH) Indicator provides a unique visualization of Bollinger Bands by displaying the full distribution of prices as a heatmap overlaying your price chart. Unlike traditional Bollinger Bands, which plot the mean and standard deviation as lines, BBH illustrates the entire statistical distribution of prices based on a normal distribution model.
This heatmap indicator offers traders a visually appealing way to understand the probabilities associated with different price levels. The lower the weight of a certain level, the more transparent it appears on the heatmap, making it easier to identify key areas of interest at a glance.
Key Features
Dynamic Heatmap: Changes in real-time as new price data comes in.
Fully Customizable: Adjust the scale, offset, alpha, and other parameters to suit your trading style.
Visually Engaging: Uses gradients of colors to distinguish between high and low probabilities.
Settings
Scale
Tooltip: Scale the size of the heatmap.
Purpose: The 'Scale' setting allows you to adjust the dimensions of each heatmap box. A higher value will result in larger boxes and a more generalized view, while a lower value will make the boxes smaller, offering a more detailed look at price distributions.
Values: You can set this from a minimum of 0.125, stepping up by increments of 0.125.
Scale ATR Length
Tooltip: The ATR used to scale the heatmap boxes.
Purpose: This setting is designed to adapt the heatmap to the instrument's volatility. It determines the length of the Average True Range (ATR) used to size the heatmap boxes.
Values: Minimum allowable value is 5. You can increase this to capture more bars in the ATR calculation for greater smoothing.
Offset
Tooltip: Offset mean by ATR.
Purpose: The 'Offset' setting allows you to shift the mean value by a specified ATR. This could be useful for strategies that aim to capitalize on extreme price movements.
Values: The value can be any floating-point number. Positive values shift the mean upward, while negative values shift it downward.
Multiplier
Tooltip: Bollinger Bands Multiplier.
Purpose: The 'Multiplier' setting determines how wide the Bollinger Bands are around the mean. A higher value will result in a wider heatmap, capturing more extreme price movements. A lower value will tighten the heatmap around the mean price.
Values: The minimum is 0, and you can increase this in steps of 0.2.
Length
Tooltip: Length of Simple Moving Average (SMA).
Purpose: This setting specifies the period for the Simple Moving Average that serves as the basis for the Bollinger Bands. A higher value will produce a smoother average, while a lower value will make it more responsive to price changes.
Values: Can be set to any integer value.
Heat Map Alpha
Tooltip: Opacity level of the heatmap.
Purpose: This controls the transparency of the heatmap. A lower value will make the heatmap more transparent, allowing you to see the price action more clearly. A higher value will make the heatmap more opaque, emphasizing the bands.
Values: Ranges from 0 (completely transparent) to 100 (completely opaque).
Color Settings
High Color & Low Color: These settings allow you to customize the gradient colors of the heatmap.
Purpose: Use contrasting colors for better visibility or colors that you prefer. The 'High Color' is used for areas with high density (high probability), while the 'Low Color' is for low-density areas (low probability).
Usage Scenarios for Settings
For Volatile Markets: Increase 'Scale ATR Length' for better smoothing and set a higher 'Multiplier' to capture wider price movements.
For Trend Following: You might want to set a larger 'Length' for the SMA and adjust 'Scale' and 'Offset' to focus on more probable price zones.
These are just recommendations; feel free to experiment with these settings to suit your specific trading requirements.
How To Interpret
The heatmap gives a visual representation of the range within which prices are likely to move. Areas with high density (brighter color) indicate a higher probability of the price being in that range, whereas areas with low density (more transparent) indicate a lower probability.
Bright Areas: Considered high-probability zones where the price is more likely to be.
Transparent Areas: Considered low-probability zones where the price is less likely to be.
Tips For Use
Trend Confirmation: Use the heatmap along with other trend indicators to confirm the strength and direction of a trend.
Volatility: Use the density and spread of the heatmap as an indication of market volatility.
Entry and Exit: High-density areas could be potential support and resistance levels, aiding in entry and exit decisions.
Caution
The Bollinger Bands Heatmap assumes a normal distribution of prices. While this is a standard assumption in statistics, it is crucial to understand that real-world price movements may not always adhere to a normal distribution.
Conclusion
The Bollinger Bands Heatmap Indicator offers traders a fresh perspective on Bollinger Bands by transforming them into a visual, real-time heatmap. With its customizable settings and visually engaging display, BBH can be a useful tool for traders looking to understand price probabilities in a dynamic way.
Feel free to explore its features and adjust the settings to suit your trading strategy. Happy trading!
Heatmap
Bollinger Bands Liquidity Cloud [ChartPrime]This indicator overlays a heatmap on the price chart, providing a detailed representation of Bollinger bands' profile. It offers insights into the price's behavior relative to these bands. There are two visualization styles to choose from: the Volume Profile and the Z-Score method.
Features
Volume Profile: This method illustrates how the price interacts with the Bollinger bands based on the traded volume.
Z-Score: In this mode, the indicator samples the real distribution of Z-Scores within a specified window and rescales this distribution to the desired sample size. It then maps the distribution as a heatmap by calculating the corresponding price for each Z-Score sample and representing its weight via color and transparency.
Parameters
Length: The period for the simple moving average that forms the base for the Bollinger bands.
Multiplier: The number of standard deviations from the moving average to plot the upper and lower Bollinger bands.
Main:
Style: Choose between "Volume" and "Z-Score" visual styles.
Sample Size: The size of the bin. Affects the granularity of the heatmap.
Window Size: The lookback window for calculating the heatmap. When set to Z-Score, a value of `0` implies using all available data. It's advisable to either use `0` or the highest practical value when using the Z-Score method.
Lookback: The amount of historical data you want the heatmap to represent on the chart.
Smoothing: Implements sinc smoothing to the distribution. It smoothens out the heatmap to provide a clearer visual representation.
Heat Map Alpha: Controls the transparency of the heatmap. A higher value makes it more opaque, while a lower value makes it more transparent.
Weight Score Overlay: A toggle that, when enabled, displays a letter score (`S`, `A`, `B`, `C`, `D`) inside the heatmap boxes, based on the weight of each data point. The scoring system categorizes each weight into one of these letters using the provided percentile ranks and the median.
Color
Color: Color for high values.
Standard Deviation Color: Color to represent the standard deviation on the Bollinger bands.
Text Color: Determines the color of the letter score inside the heatmap boxes. Adjusting this parameter ensures that the score is visible against the heatmap color.
Usage
Once this indicator is applied to your chart, the heatmap will be overlaid on the price chart, providing a visual representation of the price's behavior in relation to the Bollinger bands. The intensity of the heatmap is directly tied to the price action's intensity, defined by your chosen parameters.
When employing the Volume Profile style, a brighter and more intense area on the heatmap indicates a higher trading volume within that specific price range. On the other hand, if you opt for the Z-Score method, the intensity of the heatmap reflects the Z-Score distribution. Here, a stronger intensity is synonymous with a more frequent occurrence of a specific Z-Score.
For those seeking an added layer of granularity, there's the "Weight Score Overlay" feature. When activated, each box in your heatmap will sport a letter score, ranging from `S` to `D`. This score categorizes the weight of each data point, offering a concise breakdown:
- `S`: Data points with a weight of 1.
- `A`: Weights below 1 but greater than or equal to the 75th percentile rank.
- `B`: Weights under the 75th percentile but at or above the median.
- `C`: Weights beneath the median but surpassing the 25th percentile rank.
- `D`: All that fall below the 25th percentile rank.
This scoring feature augments the heatmap's visual data, facilitating a quicker interpretation of the weight distribution across the dataset.
Further Explanations
Volume Profile
A volume profile is a tool used by traders to visualize the amount of trading volume occurring at specific price levels. This kind of profile provides a deep insight into the market's structure and helps traders identify key areas of support and resistance, based on where the most trading activity took place. The concept behind the volume profile is that the amount of volume at each price level can indicate the potential importance of that price.
In this indicator:
- The volume profile mode creates a visual representation by sampling trading volumes across price levels.
- The representation displays the balance between bullish and bearish volumes at each level, which is further differentiated using a color gradient from `low_color` to `high_color`.
- The volume profile becomes more refined with sinc smoothing, helping to produce a smoother distribution of volumes.
Z-Score and Distribution Resampling
Z-Score, in the context of trading, represents the number of standard deviations a data point (e.g., closing price) is from the mean (average). It’s a measure of how unusual or typical a particular data point is in relation to all the data. In simpler terms, a high Z-Score indicates that the data point is far away from the mean, while a low Z-Score suggests it's close to the mean.
The unique feature of this indicator is that it samples the real distribution of z-scores within a window and then resamples this distribution to fit the desired sample size. This process is termed as "resampling in the context of distribution sampling" . Resampling provides a way to reconstruct and potentially simplify the original distribution of z-scores, making it easier for traders to interpret.
In this indicator:
- Each Z-Score corresponds to a price value on the chart.
- The resampled distribution is then used to display the heatmap, with each Z-Score related price level getting a heatmap box. The weight (or importance) of each box is represented as a combination of color and transparency.
How to Interpret the Z-Score Distribution Visualization:
When interpreting the Z-Score distribution through color and alpha in the visualization, it's vital to understand that you're seeing a representation of how unusual or typical certain data points are without directly viewing the numerical Z-Score values. Here's how you can interpret it:
Intensity of Color: This often corresponds to the distance a particular data point is from the mean.
Lighter shades (closer to `low_color`) typically indicate data points that are more extreme, suggesting overbought or oversold conditions. These could signify potential reversals or significant deviations from the norm.
Darker shades (closer to `high_color`) represent data points closer to the mean, suggesting that the price is relatively typical compared to the historical data within the given window.
Alpha (Transparency): The degree of transparency can indicate the significance or confidence of the observed deviation. More opaque boxes might suggest a stronger or more reliable deviation from the mean, implying that the observed behavior is less likely to be a random occurrence.
More transparent boxes could denote less certainty or a weaker deviation, meaning that the observed price behavior might not be as noteworthy.
- Combining Color and Alpha: By observing both the intensity of color and the level of transparency, you get a richer understanding. For example:
- A light, opaque box could suggest a strong, significant deviation from the mean, potentially signaling an overbought or oversold scenario.
- A dark, transparent box might indicate a weak, insignificant deviation, suggesting the price is behaving typically and is close to its average.
Dynamic Liquidity Map [Kioseff Trading]Hello!
Just a quick/fun project here: "Dynamic Heatmap".
This script draws a volume delta or open interest delta heatmap for the asset on your chart.
The adjective "Dynamic" is used for two reasons (:
1: Self-Adjusting Lower Timeframe Data
The script requests ~10 lower timeframe volume and open interest data sets.
When using the fixed range feature the script will, beginning at the start time, check the ~10 requested lower timeframes to see which of the lower timeframes has available data.
The script will always use the lowest timeframe available during the calculation period. As time continues, the script will continue to check if new lower timeframe data (lower than the currently used lowest timeframe) is available. This process repeats until bar time is close enough to the current time that 1-minute data can be retrieved.
The image above exemplifies the process.
Incrementally lower timeframe data will be used as it becomes available.
1: Fixed range capabilities
The script features a "fixed range" tool, where you can manually set a start time (or drag & drop a bar on the chart) to determine the interval the heatmap covers.
From the start date, the script will calculate the calculate the sub-intervals necessary to draw a rows x columns heatmap. Consequently, setting the start time further back will draw a heat map with larger rows x columns, whereas, a start time closer to the current bar time will draw a more "precise" heatmap with smaller rows x columns.
Additionally, the heatmap can be calculated using open interest data.
The image above shows the heatmap displaying open interest delta.
The image above shows alternative settings for the heatmap.
Delta values have been hidden alongside grid border colors. These settings can be replicated to achieve a more "traditional" feel for the heatmap.
Thanks for checking this out!
Options & Leveraged Shares Heatmap This is the leveraged share/option heatmap / screener.
Tradingview offers a few different tickers that have PTCR data on the daily timeframe. So I was able to pull those few tickers that display the PTCR data and format it into a heatmap.
I also had some room to add leveraged share data as well.
It is pretty self explanatory but I will go over it really briefly:
The timeframe is 1 D. This cannot be changed because this is the only timeframe available for the PTCR data.
It will pull the current day PTCR as well as the previous day PTCR and display the PTCR and change value.
The screening will be done according to the 1 day change.
You have the ability to select the option to sort by Max and Min or sort by heatmap:
Displaying max and min will show you the max positive and negative change among all the available tickers.
Max positive = bearish, as this indicates an uptick in Puts.
Max negative = bullish, as this indicates a decline in Puts.
If we flip over to the leveraged shares, it is the same:
To keep it consistent, the leveraged share ratio is displayed similar to PTCR. It is Sell to Buy ratio. The higher the ratio, the more selling and vice versa.
Thus, the same rules apply. Max positive = bearish and max negative = bullish.
If you want to display the heatmap, this is what it will look like:
The darker the blue, the higher the change in either a negative or positive direction. The same for the leveraged shares:
And that is the indicator.
Hopefully you find it helpful. I like to reference it at the end of each day to see how things are looking in terms of positioning for the following day.
Leave your comments/questions and suggestions below.
Safe trades!
Price Delta HeatmapThe Price Delta Heatmap is an indicator designed to visualize the price changes of an asset over time. It helps traders identify and analyze significant price movements and potential volatility. The indicator calculates the price delta, which is the difference between the current close price and the previous close price. It then categorizes the price deltas into different color ranges to create a heatmap-like display on the chart.
The indicator uses user-defined thresholds to determine the color ranges. These thresholds represent the minimum price change required for a specific color to be assigned. The thresholds are adjustable to accommodate different asset classes and trading strategies. Positive price deltas are associated with bullish movements, while negative price deltas represent bearish movements.
The indicator plots bars color-coded according to the price delta range it falls into. The color ranges can be customized to match personal preferences or specific trading strategies. Additionally, the indicator includes signal shapes below the bars to highlight significant positive or negative price deltas. Traders can adjust the threshold values based on their preferred sensitivity to price changes. Higher threshold values may filter out minor price movements and focus on more significant shifts, while lower threshold values will capture even minor fluctuations.
****The default settings have the thresholds set to levels of 100, 50, 20, 10, 0, -10, -20, -50, and -100. These numbers are well-suited for assets such as Ethereum or Bitcoin which are larger in price than an asset that has a price of $1.50, for example. To compensate, adjust the thresholds in the settings to reflect the price delta on the desired asset. All coloration and horizontal line plots will adjust to reflect these changes.****
Traders can interpret the Price Delta Heatmap as follows:
-- Bright green bars indicate the highest positive price deltas, suggesting strong bullish price movements.
-- Green bars represent positive price deltas above the third threshold, indicating significant bullish price changes.
-- Olive bars indicate positive price deltas above the second threshold, suggesting moderate bullish price movements.
-- Yellow bars represent positive price deltas above the lowest threshold, indicating minor bullish price changes. This color is reflected on the negative side as well. Yellow bars below zero indicate negative price deltas below the lowest threshold, suggesting minor bearish price changes.
-- White bars represent zero price deltas, indicating no significant price movement.
-- Orange bars represent negative price deltas below the second threshold, indicating moderate bearish price movements.
-- Red bars indicate negative price deltas below the third threshold, suggesting significant bearish price changes.
-- Maroon bars represent the lowest negative price deltas, indicating strong bearish price movements.
The coloration of the Price Delta line itself is determined by the line's relation to the second positive and second negative thresholds (default +/- 20) - if the line is above the second positive threshold, the line is colored lime (and is reflected in a lime arrow at the bottom of the indicator); if the line is below the second negative threshold, the line is colored fuchsia (also reflected as an arrow); if the line is between thresholds, it is colored aqua.
The Price Delta Heatmap can be used in various trading strategies and applications. Some potential use cases include:
-- Trend identification : The indicator helps traders identify periods of high volatility and potential trend reversals.
-- Volatility analysis : By observing the color changes in the heatmap, traders can gauge the volatility of an asset and adjust their risk management strategies accordingly.
-- Confirmation tool : The indicator can be used as a confirmation tool alongside other technical indicators, such as trend-following indicators or oscillators.
-- Breakout trading : Traders can look for price delta bars of a specific color range to identify potential breakout opportunities.
However, it's important to note that the Price Delta Heatmap has certain limitations. These include:
-- Lagging nature : The indicator relies on historical price data, which means it may not provide real-time insights into price movements.
-- Sensitivity to thresholds : The choice of threshold values affects the indicator's sensitivity and may vary depending on the asset being traded. It requires experimentation and adjustment to find optimal values.
-- Market conditions : The indicator's effectiveness may vary depending on market conditions, such as low liquidity or sudden news events.
Traders should consider using the Price Delta Heatmap in conjunction with other technical analysis tools and incorporate risk management strategies to enhance their trading decisions.
CANDLE STICK HEATMAPCANDLE STICK HEATMAP shows the statistics of a candle at a particular time. its very useful to find repeating pattern's at a particular time in a day.
based on the settings you can see regular repeating patterns of a day in an hourly chart. During a particular time in day there is always a down or up signal or candles.
The table boxes are candles in RED and GREEN based on open and close of the chart. The Heat map is very useful in analyzing the daily Hourly candlesticks in a week. The Time of each candlestick is plotted on the table along with default Indicators like RSI, MACD, EMA, VOLUME, ADX.
Additionally this can be used as a screener of candles on all timeframes. Analysis is easy when you want to see what happened exactly at a particular time in the previous hour, day, month etc.,
Hopefully additional updates will be introduced shortly.
Indicators:
1. MACD (close,12,26,9)
2.RSI (close,14)
3.EMA 200
3.Volume MA
Option is provided to show indicator statistics and time.
Color can be changed using settings.
Supports all Time Zones
ATR OSC and Volume Screener (ATROSCVS)In today's world of trading, having the right tools and indicators can make all the difference. With the vast number of cryptocurrencies available, I've found it challenging to keep track of the market's overall direction and make informed decisions. That's where the ATR OSC and Volume Screener comes in, a powerful Pine Script that I use to identify potential trading opportunities across multiple cryptocurrencies, all in one convenient place.
This script combines two essential components: the ATR Oscillator (ATR OSC) and a Volume Screener. It is designed to work with the TradingView platform. Let me explain how this script works and how it benefits my trading.
Firstly, the ATR Oscillator is an RSI-like oscillator that performs better under longer lookback periods. Unlike traditional RSI, the ATR OSC doesn't lose its min and max ranges with a long lookback period, as the scale remains intact. It calculates the true range by considering the high, low, open, and close prices of a financial instrument, and uses this true range instead of the standard deviation in a modified z-score calculation. This unique approach helps provide a more precise assessment of the market's volatility.
The Volume Screener, on the other hand, helps me identify unusual trading volumes across various cryptocurrencies. It employs a normalized volume calculation method, effectively filtering out outliers and highlighting potentially significant trading opportunities.
One feature I find particularly impressive about the ATR OSC and Volume Screener is its versatility and the way it displays information using color gradients. With support for over 30 different cryptocurrencies, including popular options like Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Dogecoin (DOGE), I can monitor a wide range of markets simultaneously. The color gradient on the grid is visually appealing and makes it easy to identify the strength of the indicators for each cryptocurrency, allowing me to make quick comparisons and spot potential trading opportunities.
The customizable input options allow me to fine-tune the script to suit my individual trading preferences and strategies. In summary, the ATR OSC and Volume Screener has been an invaluable tool for me as I navigate the ever-evolving world of cryptocurrencies. By combining the power of the ATR Oscillator with a robust Volume Screener, this Pine Script makes it easier than ever to identify promising trading opportunities and stay ahead of the game.
The color gradient in the ATR OSC and Volume Screener is essential for visually representing the data on the heatmap. It uses a range of colors to indicate the strength of the indicators for each cryptocurrency, making it easier to understand the market dynamics at a glance.
In the heatmap, the color gradient typically starts from a cooler color, such as blue or green, at the lower extremes (low ATR OSC values) and progresses towards warmer colors, like yellow, orange, or red, as the ATR OSC values approach the upper extremes (high ATR OSC values). This color-coding system enables me to quickly identify and interpret the data without having to examine individual numerical values.
For example, cooler colors (blue or green) might represent lower values of the ATR Oscillator, suggesting oversold conditions in the respective cryptocurrencies. On the other hand, warmer colors (yellow, orange, or red) indicate higher ATR OSC values, signaling overbought market conditions. This visual representation allows me to make rapid comparisons between different cryptocurrencies and spot potential trading opportunities more efficiently.
By utilizing the color gradient in the heatmap, the ATR OSC and Volume Screener simplifies the analysis of multiple cryptocurrencies, helping me to quickly identify market trends and make better-informed trading decisions.
I highly recommend testing the ATR OSC and Volume Screener and seeing the difference it can make in your trading decisions. Happy trading!
Net Positions (Net Longs & Net Shorts) - By LeviathanThis script is an experimental indicator that visualizes the entering and exiting of long and short positions in the market. It also includes other useful tools, such as NL/NS Profile, NL/NS Delta, NL/NS Ratio, Volume Heatmap, Divergence finder, Relative Strength Index of Net Longs and Net Shorts, EMAs and VWMAs and more.
To avoid misinterpretation, it's important to understand some basics. The “real” ratio between net long and net short positions in a given market is always 1:1. A futures contract is an agreement between two parties to buy or sell an underlying asset at an agreed-upon price. Each contract has a long side and a short side, with one party agreeing to buy (long) and the other party agreeing to sell (short) the asset at the agreed-upon price. The long position holder anticipates that the asset's price will rise, while the short position holder expects it to fall. Because every futures contract involves both a buyer and a seller, it is impossible to have more net longs than net shorts or vice versa (in terms of the net value). For every long position opened, there must be a corresponding short position taken by another market participant (and vice versa), thus maintaining the 1:1 ratio between longs and shorts. While there can be an imbalance in the number of traders/accounts holding long and short contracts, the net value of positions held on each side remains 1 to 1.
Open Interest (OI) is a metric that tracks the number of open (unsettled) contracts in a given market. For example, Open Interest of 100 BTC means that there are currently 100 BTC worth of longs and 100 BTC worth of shorts open in the market. There may be more traders on one side holding smaller positions, and fewer traders on the other side holding larger positions, but the net value of positions on one side is equal to the net value of positions on the other side → 100 BTC in longs and 100 BTC in shorts (1:1). Consider a scenario in which a trader decides to open a long position for 1 BTC at a price of HKEX:30 ,000. For this long order to be executed, a counterparty must take the opposite side of the contract by placing an order to short 1 BTC at the same price of HKEX:30 ,000. When both the long and short orders are matched and executed, the open interest increases by 1 BTC, reflecting the addition of this new contract to the market.
Changes in Open Interest essentially tell us 3 things:
- OI Increase - new positions entered the market (both longs and shorts!)
- OI Decrease - positions exited the market (both longs and shorts!)
- OI Flat - no change in open positions due to low activity or simply lots of transfers of contracts
However, different concepts can be used to analyze sentiment, aggressiveness, and activity in the market by analyzing data such as Open Interest, price, volume, etc. This indicator combines Open Interest data and price action to simplify the visualization of positions entering and exiting the market. It is based on the following concept:
Increase in Open Interest + Increase in price = Longs Opening
Decrease in Open Interest + Decrease in price = Longs Closing
Increase in Open Interest + Decrease in price = Shorts Opening
Decrease in Open Interest + Increase in price = Shorts Closing
When "Longs Opening" occurs, the OI Delta value is added to the running total of Net Longs, and when "Longs Closing" occurs, the OI Delta value is subtracted from the running total of Net Longs.
When "Shorts Opening" occurs, the OI Delta value is added to the running total of Net Shorts, and when "Shorts Closing" occurs, the OI Delta value is subtracted from the running total of Net Shorts.
To summarize:
Net Longs: Cumulative value of Longs Opening and Longs Closing (LO - LC)
Net Shorts: Cumulative value of Shorts Opening and Shorts Closing (SO - SC)
Net Delta: Net Longs - Net Shorts
Net Ratio: Net Longs / Net Shorts
This is the fundamental logic of how this script functions, but it also includes several other tools and options. Here is an overview of the settings:
Type:
- Net Positions (display values of Net Longs, Net Shorts, Net Delta, Net Ratio as described above)
- Relative Strength (display Net Longs, Net Shorts, Net Delta, Net Ratio in the form of a momentum oscillator that measures the speed and change of movements. Same logic as RSI for price)
Display as:
- Candles (display the data in the form of candlesticks)
- Lines (display the data in the form of candlesticks)
- Columns (display the data in the form of columns)
Cumulation:
- Visible Range (data is cumulated from the first visible bar on your chart)
- Full Data (data is cumulated from the beginning)
Quoted in:
- Base Currency (all data is presented in the pair’s base currency eg. BTC)
- Quote Currency (all data is presented in the pair’s quote currency eg USDT)
OI Sources
- Pick the sources from where the data is collected (if available).
Net Positions:
- NET LONGS (show/hide Net Longs plot, choose candle colors, choose line color)
- NET SHORTS (show/hide Net Shorts plot, choose candle colors, choose line color)
- NET DELTA (show/hide Net Delta plot, choose candle colors, choose line color)
- NET RATIO (show/hide Net Ratio plot, choose candle colors, choose line color)
Moving Averages:
- Type (choose between EMA and Volume Weighted Moving Average)
- NET LONGS (show/hide NL moving average plot, choose length, choose color)
- NET SHORTS (show/hide NS moving average plot, choose length, choose color)
- NET DELTA (show/hide ND moving average plot, choose length, choose color)
- NET RATIO (show/hide NR moving average plot, choose length, choose color)
Profile:
- Profile Data (choose the source data of the profile)
- Value Area % (set the percentage width of profile’s value area)
- Positions (set the position of the profile to left or right of the visible range)
- Node Size (set the relative size of nodes to make them appear smaller or larger)
- Rows (select the amount of rows displayed by the profile to control granularity)
- POC (show/hide POC- Point Of Control and select its color)
- VA (show/hide VA- Value Area and select its color)
Divergence finder
- Source (choose the source data used by the script to compare it with price pivot points)
- Maximum distance (the maximum distance between two divergent pivot points)
- Lookback Bars Left (the number of bars to the left of the current bar that the function will consider when looking for a pivot point)
- Lookback Bars Right (the number of bars to the right of the current bar that the function will consider when looking for a pivot point)
Stats:
- Show/Hide the Stats table
- Bars Back (choose the length of data analyzed for stats in number of bars)
- Position (choose the position of the Stats table)
- Select Data you want to display in the Stats table
Additional Settings:
- Volume Heatmap (show/hide volume heatmap and select its color)
- Label Offset (select how much the plot label is shifted to the right
- Position Relative Strength Length (select the length used in the calculation)
- Value Label (show/hide OI Delta values when candles are displayed)
- Plot Labels (show/hide the labels next to the plot)
- Wicks (show/hide wick when candles are displayed)
Code used for generating profiles is taken from @KioseffTrading's "Profile Any Indicator" script (used with author's permission)
Range Analysis - By LeviathanThe Interactive Range Analysis script is an essential tool for analyzing price ranges. It automatically draws important range levels, generates a Volume Profile or Open Interest profile and horizontal/vertical heatmaps, plots the anchored VWAP, draws Fibonacci levels, and much more.
How to use the indicator:
1. The script will prompt you to select the "Start Time" and "End Time" using Tradingview's interactive interface. These two points will determine the length of the range.
2. Once you have selected the range, the script will automatically anchor the range highs and lows to the highest and lowest close/wick/hlc3/ohlc4 (whichever you prefer).
3. You can then begin exploring different tools and options such as Quarters, Eighths, Fibonacci, Outer Levels, VWAP, Horizontal Volume/OI Heatmap, Vertical Volume/OI Heatmap, Fixed Range Volume Profile, Open Interest Profile, Value Area, VAH, VAL, and POC.
4. You can adjust the range by dragging the Start Time and End Time anchors or by removing/reapplying the script.
Tool overview
Range Levels
After selecting your preferred time range, the script will identify and draw a range high level and a range low level, which serve as a base for other important levels. “Half” is the level halfway between the range high and range low. “Quarters” will, as the name suggests, split the range into four equal zones (quarters) and “Eighths” will split the range into eight equal zones (eighths).
”Fibonacci” option allows you to display Fibonacci retracement levels (0.786, 0.618, 0.382, 0.236). “VWAP” will plot a Volume Weighted Average Price, anchored to the start of the range. “Direction” input lets you choose whether your range is UP or DOWN trending in order to make sure that the Fibonacci levels and labels are generated and assigned correctly. With “Outer” turned ON, the script will also generate active levels (quarters/eighths/Fibonacci) above and below the selected price range. “Extend Right” will extend all levels to the right indefinitely, while “Extend (+Bars)” lets you choose how far right the levels get extended. “Diagonal Line” is drawn from the bottom left of the range to the top right of the range or from the top left of the range to the bottom right of the range, depending on the “Direction” input.
Volume Profile / Open Interest Profile
After selecting the “Data Type”, Volume Profile or OI Profile can be generated by turning ON the “Volume/OI Profile” option.
“Resolution” input defines the amount of nodes/rows in the range that are used in profile/heatmap generation for distributing the data. While you can increase the “Resolution” to get better, more granular profiles, you should keep in mind that you might need to lower the resolution when generating profiles for larger ranges.
”Node Type” offers you two options when it comes to the representation of data: Up/Down - divides a node in two sections for up volume/OI and down volume/OI, Total - one node for total volume/OI and Delta - net difference in up volume/OI and down volume/OI.
”Profile Position” lets you choose whether the profile is positioned on the left side of the range or on the right side of the range.
“Profile Direction” determines whether the profile nodes are facing right or left.
“Profile Type” enables you to visualize the nodes in a classic way (Type 1) or in a way where down volume/negative OI are positioned on the left side of the y axis and up volume/positive OI on the right side of the y axis.
“Node Size (%)” defines how much space in the range can be taken by the profile’s nodes. Eg. 50% will allow the largest node to extend to the middle of the range (and others scaled accordingly), 100% will allow the largest node to extend the max right point of the range (and others scaled accordingly).
”Value Area (%)” defines the VA zone, which represents the area where the most volume occured (usually 70% or 68%).
”Horizontal Heatmap” will display a heatmap-like overlay, that will help you identify the price levels where most volume/open interest action occurred.
”Vertical Heatmap” will display a heatmap-like overlay, that will help you identify the points in time where most volume/open interest action occurred.
A more detailed description of this indicator is coming in the next few days.
Important:
* If volume or OI profile does not get generated, try lowering the resolution.
* Once in a while, the script will disappear from your chart. Just remove and reapply.
* Open Interest data is only avaiable on Binance Perpetual Futures pairs
To learn more, read the tooltips in the indicator’s settings and stay tuned for upcoming additions (Range Market Structure, Liquidation Levels, Range Statistics,…)
Hurst Spectral Analysis SwamiChartHaving a hard time deciding which wavelength to use for a Hurst analysis? Try a handful at once! SwamiCharts by John Ehlers offers a comprehensive way to visualize an indicator used over a range of lookback periods. The Spectral Analysis SwamiChart shows the bullish or bearish state of a spectrum of bandpasses over a user-defined range of wavelengths. The trader simply selects a bandwidth, a base wavelength, and a step/multiple to see the Spectral Analysis SwamiChart. A vertical column of green or red tends to indicate a very bullish or bearish moment in time, meaning that all bandpasses in the analyzed spectrum are in a bullish or bearish orientation simultaneously.
🏆 Shoutout to DavidF at Sigma-L for all the helpful information, conversations together, & indicator feedback.
🏅Shoutout to @HPotter for the bandpass code, and shoutout to @TerryPascoe for sharing it with me
RSI Impact Heat Map [Trendoscope]Here is a simple tool to measure and display outcome of certain RSI event over heat map.
🎲 Process
🎯Event
Event can be either Crossover or Crossunder of RSI on certain value.
🎯Measuring Impact
Impact of the event after N number of bars is measured in terms of highest and lowest displacement from the last close price. Impact can be collected as either number of times of ATR or percentage of price. Impact for each trigger is recorded separately and stored in array of custom type.
🎯Plotting Heat Map
Heat map is displayed using pine tables. Users can select heat map size - which can vary from 10 to 90. Selecting optimal size is important in order to get right interpretation of data. Having higher number of cells can give more granular data. But, chart may not fit into the window. Having lower size means, stats are combined together to get less granular data which may not give right picture of the results. Default value for size is 50 - meaning data is displayed in 51X51 cells.
Range of the heat map is adjusted automatically based on min and max value of the displacement. In order to filter out or merge extreme values, range is calculated based on certain percentile of the values. This will avoid displaying lots of empty cells which can obscure the actual impact.
🎲 Settings
Settings allow users to define their event, impact duration and reference, and few display related properties. The description of these parameters are as below:
🎲 Use Cases
In this script, we have taken RSI as an example to measure impact. But, we can do this for any event. This can be price crossing over/under upper/lower bollinger bands, moving average crossovers or even complex entry or exit conditions. Overall, we can use this to plot and evaluate our trade criteria.
🎲 Interpretation
Q1 - If more coloured dots appear on the top right corner of the table, then the event is considered to trigger high volatility and high risk environment.
Q2 - If more coloured dots appear on the top left corner, then the events are considered to trigger bearish environment.
Q3 - If more coloured dots appear on the bottom left corner of the chart, then the events are considered insignificant as they neither generate higher displacement in positive or negative side. You can further alter outlier percentage to reduce the bracket and hence have higher distribution move towards
Q4 - If more coloured dots appear on the bottom right corner, then the events are considered to trigger bullish environment.
Will also look forward to implement this as library so that any conditions or events can be plugged into it.
Price Heat MapWhat does this chart show? Take the highest high and lowest low of 200 bars. Divide that into 20 chunks. The more time the price spends in one of those 1/20th pockets, the brighter it is lit up on the chart. Number of bars back can be modified to around 500. It starts to chug beyond that. Brightness level of heat map can be adjusted. 0.5 is default. 1 = brighter, 0 = dimmer. Use on any time frame. When price moves out of a hot zone, it can move very quickly. There's no trading strategy here, just something to help you visualize recent price action. The blue band shows the price at the center of the current "hottest" band. The yellow band is the ema (exponential moving average) of the price using the "bars back" input. --enjoy!
swami_rsi
Description:
As in the practices, most traders find it hard to set the proper lookback period of the indicator to be used. SwamiCharts offers a comprehensive way to visualize the indicator used over a range of lookback periods. The SwamiCharts of Relative Strength Index (RSI), was developed by Ehlers - see Cycle Analytics for Traders, chapter 16. The indicator was computed over multiple times of the range of lookback period for the Relative Strength Index (RSI), from the deficient period to the relatively high lookback period i.e. 1 to 48, then plotted as one heatmap.
Features:
In this indicator, the improvement is to utilize the color(dot)rgb() function, which finds to giving a relatively lower time to compute, and follows the original color scheme.
The confirmation level, which assumed of 25
Blockchain Fundamentals: 200 Week MA Heatmap [CR]Blockchain Fundamentals: 200 Week MA Heatmap
This is released as a thank you to all my followers who pushed me over the 600 follower mark on twitter. Thanks to all you Kingz and Queenz out there who made it happen. <3
Indicator Overview
In each of its major market cycles, Bitcoin's price historically bottoms out around the 200 week moving average.
This indicator uses a color heatmap based on the % increases of that 200 week moving average. Depending on the rolling cumulative 4 week percent delta of the 200 week moving average, a color is assigned to the price chart. This method clearly highlights the market cycles of bitcoin and can be extremely helpful to use in your forecasts.
How It Can Be Used
The long term Bitcoin investor can monitor the monthly color changes. Historically, when we see orange and red dots assigned to the price chart, this has been a good time to sell Bitcoin as the market overheats. Periods where the price dots are purple and close to the 200 week MA have historically been good times to buy.
Bitcoin Price Prediction Using This Tool
If you are looking to predict the price of Bitcoin or forecast where it may go in the future, the 200WMA heatmap can be a useful tool as it shows on a historical basis whether the current price is overextending (red dots) and may need to cool down. It can also show when Bitcoin price may be good value on a historical basis. This can be when the dots on the chart are purple or blue.
Over more than ten years, $BTC has spent very little time below the 200 week moving average which is also worth noting when thinking about price predictions for Bitcoin or a Bitcoin price forecast.
Notes
1.) If you do not want to view the legend do the following: Indicator options > Style tab > Uncheck "Tables"
2.) I use my custom function to get around the limited historical data for bitcoin. You can check out the explanation of it here:
swami_money_flow
Description:
Chaikin Money Flow was an indicator that measuring of the volume-weighted average of accumulation and distribution over a specified period (as cited from Fidelity) developed by Marc Chaikin, aim to identify the changes in buying or selling momentum of an asset that leads to the increase or decrease of asset prices. In the original format, the cross above 0 of money flow depicts a buying pressure, while a cross under 0 means a selling pressure. In this indicator, the money flow was displayed in a swami chart, used for detecting a change not only in one specified period but instead in multiple periods at once. Sequencing from the very below, the indicator capture the shift in money flow in shorter lookback periods, going through the very above the indicator capture the change of money flow in greater lookback periods. The color is set to gradient from red as indicating the negative money flow, while green indicates a positive money flow. A smoothing function was given (from Ehlers smoothing function) to reduce noises.
Money Flow:
cmf = n-day sum of( (((close - low) - (high - close)) / (high - low)) x volume )/ n-day sum of volume
smoothed = (4*cmf + 3*cmf + 2*cmf + cmf )/10
Notes:
the Darker the color indicates the higher the value e.g. dark red means more selling pressure, and vice versa
if the color is a lineup in a one period, indicates a strong signal (both directions)
very below is for a shorter period, and increasing through to the longest (1 - 30 by default)
Other Example
normalize_heatmap
Description:
This was a simple indicator to indicate the heatmap area of an asset price, in a relative given time period. In default the lookback period was set to 50 bars, indicating the current state of the price within the previous lookback period. The color scheme was using the rainbow palette, which set blue as the cooling-off area, and red as the heating area. The indicator doesn't take into account momentum strategy and thus doesn't consider the future direction of the asset price. Note: cooling-off area, can be considered to entry or adding position as a DCA strategy.
Data Normalize:
norm = (x - min) / (max - min)
Feature:
Heatmap color condition
Weighted Moving average (Additional)
HEX Risk Metric (v0.2)This indicator plots a "risk metric" based on the % increases of the following averages:
ema21, sma50, sma100, sma200, sma300, sma600.
Depending on the rolling 7-day percentage increase of this moving average, a value is assigned to each data point, then normalized to a common range.
This set of metrics attempts to represent data similar to that of a heat map.
Users can adjust filter top, filter bottom, and toggle on/off the different metrics within the set.
HEX Risk Metric (v0.1)This indicator plots a "risk metric" based on the % increases of the following averages:
ema21, sma50, sma100, sma200, sma300, sma600.
Depending on the rolling 7-day percentage increase of this moving average, a value is assigned to each data point, then normalized to a common range.
This set of metrics attempts to represent data similar to that of a heat map.
Users can adjust filter top, filter bottom, and toggle on/off the different metrics within the set.
Morningstar Equity Style Box HeatmapStyle boxes are a classification scheme created by Morningstar. They visually provide a graphical representation of investing categories for equity investments. A style box is a valuable tool for investors to use when determining asset allocation.
There are 9 categories:
Large Value, Large Blend, Large Growth
Medium Value, Medium Blend, Medium Growth
Small Value, Small Blend, Small Growth
The strength of the 9 categories are found by using 9 Vanguard ETF's that follow the respective CRSP index of their category.
Stochastic RSI HeatmapStochastic RSI presented as a heatmap starting from the oversold (20) / overbought (80) levels respectively. The more oversold / overbought the price, the more intense the color (blue / fuchsia).
Williams Alligator Trend Filter HeatmapHello I've decided that the alligator lines can be used to find a trend. This script expands on that and checks 10 different multipliers to see trend over the long term and have 10 values. Those 10 values each give a color to one of the 10 lines in turn giving this Fire like plotting. I personaly use this to see if there is fear (red) in the markets or greed (blue), plotted 9 different crypto coins on the chart and have 4 columns in my setup to see the values on different timeframes. In the chart preview this is 1H,30M,10M,1M to see current environment. The colors use alot of data to generate especialy the bottom part, that colors based on a very long time zone.
Relative Strength Screener V2 - Top 100 volume leadersNew and improved strength heatmap for the top 100 volume leaders in the S&P. Coded in a workaround to the 40 request.security limitation that currently exists in Pine. Added the ability to input the number of columns (time frames) you wish to display.
For 3 time frame analysis, add the indicator to your chart 3 times. Change the number of columns to 3 for each of these indicators. Specify the column and time frame for each one (example, 5 minute for column 1, 1 hour for column 2 and Daily chart for column 3). It will automatically resize the columns/tables to properly display the output. This provides a sort of "Strength Heatmap" for the top 100 stocks in the S&P. To achieve this, make a copy of the indicator and substitute lines 68-105 with the following premade watchlists :
Make a copy 1 - FIrst 38 volume leaders in the S&P
s01 = input.symbol('AAPL', group = 'Symbols', inline = 's01')
s02 = input.symbol('ABBV', group = 'Symbols', inline = 's02')
s03 = input.symbol('ABT', group = 'Symbols', inline = 's03')
s04 = input.symbol('ACN', group = 'Symbols', inline = 's04')
s05 = input.symbol('AEP', group = 'Symbols', inline = 's05')
s06 = input.symbol('AIG', group = 'Symbols', inline = 's06')
s07 = input.symbol('AMAT', group = 'Symbols', inline = 's07')
s08 = input.symbol('AMD', group = 'Symbols', inline = 's08')
s09 = input.symbol('APA', group = 'Symbols', inline = 's09')
s10 = input.symbol('ATVI', group = 'Symbols', inline = 's10')
s11 = input.symbol('AXP', group = 'Symbols', inline = 's11')
s12 = input.symbol('BA', group = 'Symbols', inline = 's12')
s13 = input.symbol('BBWI', group = 'Symbols', inline = 's13')
s14 = input.symbol('BBY', group = 'Symbols', inline = 's14')
s15 = input.symbol('BK', group = 'Symbols', inline = 's15')
s16 = input.symbol('BMY', group = 'Symbols', inline = 's16')
s17 = input.symbol('BRK.B', group = 'Symbols', inline = 's17')
s18 = input.symbol('C', group = 'Symbols', inline = 's18')
s19 = input.symbol('CAT', group = 'Symbols', inline = 's19')
s20 = input.symbol('CCL', group = 'Symbols', inline = 's20')
s21 = input.symbol('CFG', group = 'Symbols', inline = 's21')
s22 = input.symbol('CL', group = 'Symbols', inline = 's22')
s23 = input.symbol('CNC', group = 'Symbols', inline = 's23')
s24 = input.symbol('COF', group = 'Symbols', inline = 's24')
s25 = input.symbol('COP', group = 'Symbols', inline = 's25')
s26 = input.symbol('COST', group = 'Symbols', inline = 's26')
s27 = input.symbol('CRM', group = 'Symbols', inline = 's27')
s28 = input.symbol('CVS', group = 'Symbols', inline = 's28')
s29 = input.symbol('CVX', group = 'Symbols', inline = 's29')
s30 = input.symbol('DAL', group = 'Symbols', inline = 's30')
s31 = input.symbol('DIS', group = 'Symbols', inline = 's31')
s32 = input.symbol('DISCA', group = 'Symbols', inline = 's32')
s33 = input.symbol('DISCK', group = 'Symbols', inline = 's33')
s34 = input.symbol('DISH', group = 'Symbols', inline = 's34')
s35 = input.symbol('DLTR', group = 'Symbols', inline = 's35')
s36 = input.symbol('DOW', group = 'Symbols', inline = 's36')
s37 = input.symbol('DVN', group = 'Symbols', inline = 's37')
s38 = input.symbol('EBAY', group = 'Symbols', inline = 's38')
Make a copy 2 - Tickers 39 to 76
s01 = input.symbol('EOG', group = 'Symbols', inline = 's01')
s02 = input.symbol('F', group = 'Symbols', inline = 's02')
s03 = input.symbol('FB', group = 'Symbols', inline = 's03')
s04 = input.symbol('FCX', group = 'Symbols', inline = 's04')
s05 = input.symbol('FIS', group = 'Symbols', inline = 's05')
s06 = input.symbol('GE', group = 'Symbols', inline = 's06')
s07 = input.symbol('GIS', group = 'Symbols', inline = 's07')
s08 = input.symbol('GM', group = 'Symbols', inline = 's08')
s09 = input.symbol('GS', group = 'Symbols', inline = 's09')
s10 = input.symbol('HD', group = 'Symbols', inline = 's10')
s11 = input.symbol('IBM', group = 'Symbols', inline = 's11')
s12 = input.symbol('INTC', group = 'Symbols', inline = 's12')
s13 = input.symbol('JNJ', group = 'Symbols', inline = 's13')
s14 = input.symbol('JPM', group = 'Symbols', inline = 's14')
s15 = input.symbol('KR', group = 'Symbols', inline = 's15')
s16 = input.symbol('LUV', group = 'Symbols', inline = 's16')
s17 = input.symbol('LVS', group = 'Symbols', inline = 's17')
s18 = input.symbol('MA', group = 'Symbols', inline = 's18')
s19 = input.symbol('MCD', group = 'Symbols', inline = 's19')
s20 = input.symbol('MCHP', group = 'Symbols', inline = 's20')
s21 = input.symbol('MDT', group = 'Symbols', inline = 's21')
s22 = input.symbol('MET', group = 'Symbols', inline = 's22')
s23 = input.symbol('MGM', group = 'Symbols', inline = 's23')
s24 = input.symbol('MOS', group = 'Symbols', inline = 's24')
s25 = input.symbol('MPC', group = 'Symbols', inline = 's25')
s26 = input.symbol('MRK', group = 'Symbols', inline = 's26')
s27 = input.symbol('MRNA', group = 'Symbols', inline = 's27')
s28 = input.symbol('MS', group = 'Symbols', inline = 's28')
s29 = input.symbol('MSFT', group = 'Symbols', inline = 's29')
s30 = input.symbol('MU', group = 'Symbols', inline = 's30')
s31 = input.symbol('NCLH', group = 'Symbols', inline = 's31')
s32 = input.symbol('NEE', group = 'Symbols', inline = 's32')
s33 = input.symbol('NEM', group = 'Symbols', inline = 's33')
s34 = input.symbol('NFLX', group = 'Symbols', inline = 's34')
s35 = input.symbol('NKE', group = 'Symbols', inline = 's35')
s36 = input.symbol('NVDA', group = 'Symbols', inline = 's36')
s37 = input.symbol('ORCL', group = 'Symbols', inline = 's37')
s38 = input.symbol('OXY', group = 'Symbols', inline = 's38')
Make a copy 3 - tickers 77 to 114
s01 = input.symbol('PENN', group = 'Symbols', inline = 's01')
s02 = input.symbol('PEP', group = 'Symbols', inline = 's02')
s03 = input.symbol('PFE', group = 'Symbols', inline = 's03')
s04 = input.symbol('PG', group = 'Symbols', inline = 's04')
s05 = input.symbol('PM', group = 'Symbols', inline = 's05')
s06 = input.symbol('PYPL', group = 'Symbols', inline = 's06')
s07 = input.symbol('QCOM', group = 'Symbols', inline = 's07')
s08 = input.symbol('RTX', group = 'Symbols', inline = 's08')
s09 = input.symbol('SBUX', group = 'Symbols', inline = 's09')
s10 = input.symbol('SCHW', group = 'Symbols', inline = 's10')
s11 = input.symbol('SLB', group = 'Symbols', inline = 's11')
s12 = input.symbol('SYF', group = 'Symbols', inline = 's12')
s13 = input.symbol('T', group = 'Symbols', inline = 's13')
s14 = input.symbol('TFC', group = 'Symbols', inline = 's14')
s15 = input.symbol('TGT', group = 'Symbols', inline = 's15')
s16 = input.symbol('TJX', group = 'Symbols', inline = 's16')
s17 = input.symbol('TMUS', group = 'Symbols', inline = 's17')
s18 = input.symbol('TSLA', group = 'Symbols', inline = 's18')
s19 = input.symbol('TWTR', group = 'Symbols', inline = 's19')
s20 = input.symbol('TXN', group = 'Symbols', inline = 's20')
s21 = input.symbol('UAL', group = 'Symbols', inline = 's21')
s22 = input.symbol('UNH', group = 'Symbols', inline = 's22')
s23 = input.symbol('V', group = 'Symbols', inline = 's23')
s24 = input.symbol('VIAC', group = 'Symbols', inline = 's24')
s25 = input.symbol('WBA', group = 'Symbols', inline = 's25')
s26 = input.symbol('WFC', group = 'Symbols', inline = 's26')
s27 = input.symbol('WMT', group = 'Symbols', inline = 's27')
s28 = input.symbol('WYNN', group = 'Symbols', inline = 's28')
s29 = input.symbol('XOM', group = 'Symbols', inline = 's29')
s30 = input.symbol('SPY', group = 'Symbols', inline = 's30')
s31 = input.symbol('SPY', group = 'Symbols', inline = 's31')
s32 = input.symbol('SPY', group = 'Symbols', inline = 's32')
s33 = input.symbol('SPY', group = 'Symbols', inline = 's33')
s34 = input.symbol('SPY', group = 'Symbols', inline = 's34')
s35 = input.symbol('SPY', group = 'Symbols', inline = 's35')
s36 = input.symbol('SPY', group = 'Symbols', inline = 's36')
s37 = input.symbol('SPY', group = 'Symbols', inline = 's37')
s38 = input.symbol('SPY', group = 'Symbols', inline = 's38')
Weekly Volume HeatmapThis tool is designed to visualize how the trading volume of each asset changes during the week.
How to use
This tool can help us better understand the market and answer many questions, such as:
◽ How to avoid getting stop hunted?
Typically, trading volume decreases at certain times of the week, which is the best time for large holders to manipulate the market. Low volume means there is less liquidity in the market. Large transactions in an illiquid market can cause large price changes.
Large holders (whales) have enough capital to push the price in the desired direction to trigger a cascade of stop-loss orders which can move the price further.
After a stop hunt, the market typically reverses, leaving stop hunted traders behind.
It is best to avoid using stop-loss orders and leveraged trading during these hours of the week.
◽ When’s the best time to make decisions
During some hours of the week the trading volume usually decreases; at these times, most traders are inactive and do not participate in transactions.
Therefore, the price changes that occur during these times lack conviction.
It is better to make decisions when there are more active traders in the market. At these periods, a relatively high trading volume is usually observed.
How it works
First, it calculates the average traded volume of each period (for example Monday 9:00 AM) from the first bar to the last bar. It then calculates the ratio of the average traded volume in each period to the average traded volume per week. Finally, the result is displayed as a percentage in each cell.
Different values are distinguished by different background colors. Light colors are used for low values and dark colors are used for high values.
Limits
It only works in the 1 hour time frame.
Samples
Stock => AAPL
Futures => ES1!
Forex => EURUSD
