Arbitrage Detector [LuxAlgo]The Arbitrage Detector unveils hidden spreads in the crypto and forex markets. It compares the same asset on the main crypto exchanges and forex brokers and displays both prices and volumes on a dashboard, as well as the maximum spread detected on a histogram divided by four user-selected percentiles. This allows traders to detect unusual, high, typical, or low spreads.
This highly customizable tool features automatic source selection (crypto or forex) based on the asset in the chart, as well as current and historical spread detection. It also features a dashboard with sortable columns and a historical histogram with percentiles and different smoothing options.
🔶 USAGE
Arbitrage is the practice of taking advantage of price differences for the same asset across different markets. Arbitrage traders look for these discrepancies to profit from buying where it’s cheaper and selling where it’s more expensive to capture the spread.
For begginers this tool is an easy way to understand how prices can vary between markets, helping you avoid trading at a disadvantage.
For advanced traders it is a fast tool to spot arbitrage opportunities or inefficiencies that can be exploited for profit.
Arbitrage opportunities are often short‑lived, but they can be highly profitable. By showing you where spreads exist, this tool helps traders:
Understand market inefficiencies
Avoid trading at unfavorable prices
Identify potential profit opportunities across exchanges
As we can see in the image, the tool consists of two main graphics: a dashboard on the main chart and a histogram in the pane below.
Both are useful for understanding the behavior of the same asset on different crypto exchanges or forex brokers.
The tool's main goal is to detect and categorize spread activity across the major crypto and forex sources. The comparison uses data from up to 19 crypto exchanges and 13 forex brokers.
🔹 Forex or Crypto
The tool selects the appropriate sources (crypto exchanges or forex brokers) based on the asset in the chart. Traders can choose which one to use.
The image shows the prices and volumes for Bitcoin and the euro across the main sources, sorted by descending average price over the last 20 days.
🔹 Dashboard
The dashboard displays a list of all sources with four main columns: last price, average price, volume, and total volume.
All four columns can be sorted in ascending or descending order, or left unsorted. A background gradient color is displayed for the sorted column.
Price and volume delta information between the chart asset and each exchange can be enabled or disabled from the settings panel.
🔹 Histogram
The histogram is excellent for visualizing historical values and comparing them with the asset price.
In this case, we have the Euro/U.S. Dollar daily chart. As we can see, the unusual spread activity detected since 2016, with values at or above 98%, is usually a good indication of increased trader activity, which may result in a key price area where the market could turn around.
By default, the histogram has the gradient and smoothing auto features enabled.
The differences are visible in the chart above. On top is an adaptive moving average with higher values for unusual activity. At the bottom is an exponential moving average with a length of 9.
The differences between the gradient and solid colors are evident. In the first case, the colors are in sync with the data values, becoming more yellow with higher values and more green with lower values. In the second case, the colors are solid and only distinguish data above or below the defined percentiles.
🔶 SETTINGS
Sources: Choose between crypto exchanges, forex brokers, or automatic selection based on the asset in the chart.
Average Length: Select the length for the price and volume averages.
🔹 Percentiles
Percentile Length: Select the length for the percentile calculation, or enable the use of the full dataset. Enabling this option may result in runtime errors due to exceeding the allotted resources.
Unusual % >: Select the unusual percentile.
High % >: Select the high percentile.
Typical % >: Select the typical percentile.
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Sorting: Select the sorting column and direction.
Position: Select the dashboard location.
Size: Select the dashboard size.
Price Delta: Show the price difference between each exchange and the asset on the chart.
Volume Delta: Show the volume difference between each exchange and the asset on the chart.
🔹 Style
Unusual: Enable the plot of the unusual percentile and select its color.
High: Enable the plot of the high percentile and select its color.
Typical: Enable the plot of the typical percentile and select its color.
Low: Select the color for the low percentile.
Percentiles Auto Color: Enable auto color for all plotted percentiles.
Histogram Gradient: Enable the gradient color for the histogram.
Histogram Smoothing: Select the length of the EMA smoothing for the histogram or enable the Auto feature. The Auto feature uses an adaptive moving average with the data percent rank as the efficiency ratio.
Kripto
Multi-Factor Long Bias ToolThis indicator is designed to help identify higher‑probability long opportunities by combining trend, momentum, and participation into a single visual tool. It runs best on a 1‑hour chart and highlights periods when several bullish conditions align.
What the tool does
Measures short‑term trend and momentum with a fast MACD, looking for instances where MACD is above its signal line, above zero, and showing positive histogram.
Uses RSI as an oscillator filter, favoring conditions that are neither oversold nor overbought, but in a healthy momentum zone.
Confirms participation with a daily volume check, requiring current daily volume to be at or above a configurable multiple of its 20‑day average.
Optionally incorporates short‑interest (via a manual input) so you can require a minimum short percentage when seeking squeeze‑style long setups.
How signals are shown
When MACD, RSI, volume, and optional short‑interest all agree, the chart background turns softly green to show a “long bias” environment.
A triangle‑up marker (“LONG”) appears below price when the long bias is active and the “Focus on Longs Only” option is enabled.
A separate panel can display MACD, its signal line, histogram, and RSI together, with a toggle to show or hide this pane to keep charts clean.
Intended use
Helps discretionary traders quickly see when multiple conditions favor looking for long entries, rather than acting on a single indicator in isolation.
Works as a bias and timing aid; actual entries and exits are meant to be refined with your own levels, risk management, and higher‑timeframe context.
Parameters for MACD, RSI, volume threshold, and short‑interest are fully adjustable so the tool can be tuned to different markets, timeframes, and styles.
As always, none of this is investment or financial advice. Please do your own due diligence and research.
RunRox - Pairs Screener📊 Pairs Screener is part of our premium suite for pair trading.
This indicator is designed to scan and rank the most profitable and optimal pairs for the Pairs Strategy. The screener can backtest multiple metrics on deep historical data and display results for many pairs against one base asset at the same time.
This allows you to quickly detect market inefficiencies and select the most promising pairs for live trading.
HOW DOES THIS STRATEGY WORK⁉️
The core idea of the strategy is described in detail in our main indicator Pairs Strategy from the same product line.
There you can find a full explanation of the concept, the math behind pair trading, and the internal logic of the engine.
The Pairs Screener is built on top of the same core technology as the main indicator and uses the same internal logic and calculations.
It is designed as a key companion tool to the main strategy: it helps you find tradeable pairs, evaluate current deviations, sort and filter lists of candidates, and much more. All of these features will be described in this post.
✅ KEY FEATURES
More than 400+ assets available for scanning
Forex assets
Crypto assets
Lower Timeframe Backtester Strategy support
Invert signals mode
Hedge Coefficient (position size balancing between both legs)
6 hedge modes
Stop Loss support
Take Profit support
Whitelist with your own custom asset list
Blacklist to exclude unwanted assets
Custom filters
12 tracking metrics for pair evaluation
Customizable alerts
And many other tools for fine-tuning your search
The screener runs backtests simultaneously across a large number of assets and calculates metrics automatically.
This helps you very quickly find pairs with strong structural relationships or current inefficiencies that can be used as the basis for your pair trading strategies.
⚙️ MAIN SETTINGS
The first section controls the core parameters of the screener: Score, correlation, asset groups for scanning, and other base settings. All major crypto and forex symbols are embedded directly into the screener.
Since there are more than 400 assets, it is technically impossible to analyze everything at once, so we grouped them into batches of 40 assets per group.
The workflow is simple:
Open the chart of the asset you want to use as the base ticker.
In the screener settings choose the market (Crypto or Forex).
Select a Group (for example, Group 1) and the indicator will scan all assets inside that group against your base ticker.
Then you switch to Group 2, Group 3, etc., and repeat the scan.
Embedded universe:
400+ assets total
350+ Crypto – split into 10 groups
70+ Forex – split into 3 groups
Below is a description of each setting.
🔸 Exclude Dates
Allows you to specify a period that should be excluded from analysis.
Useful for removing abnormal spikes, news events, or any non-typical segments that distort the statistics for your pairs.
🔸 Market
Defines which universe will be used to build pairs with the current main asset:
Crypto – 350+ crypto symbols
Forex – 70+ FX symbols
Whitelist – your own custom list of assets
🔸 Group
Selects the asset group to scan.
As mentioned above, assets are split into groups of about 40 instruments:
350+ Crypto → 10 groups
70+ Forex → 3 groups
The screener will calculate all metrics only for the group you select.
🔸 Lower Timeframe
This option enables deep history analysis.
Each TradingView plan has a limit on the number of visible bars (for example, 5,000 bars on the basic plan). In standard mode you would only get statistics for the last 5,000 bars of your current timeframe.
If you want a deeper backtest on a lower timeframe, you can do the following:
Suppose your target timeframe for analysis is 5 minutes.
Switch your chart to a 30-minute timeframe.
Enable Lower Timeframe in the indicator.
Select 5 minutes as the lower timeframe inside the screener.
In this mode the screener can reconstruct and analyze up to 99,000 bars of data for your assets. This allows you to evaluate pairs on a much deeper history and see whether the results are stable over a larger sample.
🔸 Method
Here you choose the deviation model:
preferred Z-Score or S-Score for your analysis,
plus you can enable Invert to search for negatively correlated pairs and calculate their profit correctly.
🔸 Period
This is the lookback period for Z/S Score.
It defines how many bars are used to calculate the deviation metric for each pair.
🔸 Correlation Period
This is the number of bars used to calculate correlation between the base asset and each candidate in the group.
The resulting correlation value is also displayed in the results table.
🔀 HEDGE COEFFICIENT
The next block of settings is related to the hedge coefficient.
This defines how much margin is allocated to each leg of the pair.
The classic approach in pair trading is to split the position equally between both assets.
For example, if you allocate 100 USD to a trade , the standard model would open 50 USD long on one asset and 50 USD short on the other.
This works well for pairs with similar volatility , such as BTCUSDT / ETHUSDT
However, if you use a pair like BTCUSDT / DOGEUSDT , the volatility of these assets is very different.
They can still be correlated, but their amplitude is not the same. While Bitcoin might move 2% , Dogecoin can move 10% over the same period.
Because of that, for pairs with strongly different volatility, we can use a hedge coefficient and, for example, enter with 30 USD on one leg and 70 USD on the other, taking the volatility difference into account.
This is the main idea behind the Hedge Coefficient section and its primary use.
The indicator includes 6 methods of calculating the coefficient:
Cumulative RMA
Beta OLS
Beta TLS
Beta EMA
RMA Range
RMA Delta
Each method uses a different formula to compute the hedge coefficient and to size the position based on different metrics of the assets.
We leave it to the trader to decide which algorithm works best for their specific pair and style.
Below are the settings inside this section:
🔹 Method
When Auto Hedge is enabled, you can select which method to use from the list above.
The chosen method will automatically calculate the hedge coefficient between the two legs.
🔹 Hedge Coefficient
This is the manual hedge ratio per trade when Auto Hedge is disabled.
By default it is set to 1, which means the position is opened 50/50 between the two assets.
🔹 Min Allowed Hedge Coef.
This is the minimum allowed hedge coefficient.
By default it is 0.2, which means the model will not go below a 20% / 80% split between the legs.
🔹 MA Length
For methods that use moving averages (for example Beta EMA), this parameter sets the period used to calculate the hedge coefficient.
💰 STRATEGY SETTINGS
This section defines the base backtesting settings for all assets in the screener.
Here you configure entries, exits, Stop Loss, and other parameters used to find the most optimal pairs for your strategy. 🔸 Commission %
In this field you set your broker’s fee percentage per trade.
The indicator automatically calculates the correct commission for each leg of every trade. You only need to input the real commission rate that your broker charges for volume. No additional manual calculations are required.
🔸 Qty $
The margin amount used for backtesting across all assets in the screener.
This margin is split between both legs of the pair either equally or according to the selected hedge coefficient.
🔸 Entry
The Z/S Score deviation level at which the backtest opens a trade for each pair.
🔸 Exit
The Z/S Score level at which the backtest closes trades for the tested assets.
🔸 Stop Loss
PnL threshold at which a trade is force-closed during the historical test.
🔸 Cooldown
Number of bars the strategy will wait after a Stop Loss before opening the next trade.
This block gives you flexible control over how your strategy is tested on 400+ assets, helping you standardize the rules and compare pairs under the exact same conditions.
🗒️ WHITELIST
In this section you can define your own custom list of assets for monitoring and backtesting.
This is useful if you want to work with symbols that are not included in the built-in lists, such as exotic crypto from smaller exchanges, specific stocks, or any custom universe 🔹 Exchange Prefix
Enter the exchange prefix used for your tickers.
Example: BINANCE, OANDA, etc.
🔹 Ticker Postfix
Enable this option if the tickers require a postfix.
Example 1: .P for Binance Futures perpetual contracts.
Example 2: USDT if you only provide the base asset in the ticker list.
🔹 Ticker List
Enter a comma-separated list of tickers to analyze.
Example 1: BTCUSDT, ETHUSDT, BNBUSDT (when the exchange prefix is set).
Example 2: BTC, ETH, BNB (when using postfix USDT).
Example 3: BINANCE:BTCUSDT.P, OANDA:EURUSD (when different exchanges are used and the prefix option is disabled).
This gives you full flexibility to build a screener universe that matches exactly the assets you trade.
⛔ BLACKLIST
In this section you can enable a blacklist of unwanted assets that should be skipped during analysis. Enter a comma-separated list of tickers to exclude from the screener:
Example 1: BTCUSDT, ETHUSDT
Example 2: BTC, ETH (all tickers that contain these symbols will be excluded)
This helps you quickly remove illiquid, noisy, or unwanted instruments from the results without changing your main groups or whitelist.
📈 DASHBOARD
This section controls the results dashboard: table position, style, and sorting logic.
Here is what you can configure:
Result Table – position of the results table on the chart.
Background / Text – colors and opacity for the table background and text.
Table Size – overall size of the results table (from 0 to 30).
Show Results – how many rows (pairs) to display in the table.
Sort by (stat) – which metric to use for sorting the results.
Available options: Profit Factor, Profit, Winrate, Correlation, Score.
This lets you quickly focus on the most interesting pairs according to the exact metric that matters most for your strategy.
📎 FILTER SETTINGS
This section lets you filter the results table by metric values.
For example, you can show only pairs with a minimum correlation of 0.8 to focus on more stable relationships. 🔸 Min Correlation
Minimum allowed correlation between the two assets over the selected lookback period.
🔸 Min Score
Minimum absolute Score (Z-Score or S-Score) required to include a pair in the results.
For example, 2.0 means only pairs with Score >= 2.0 or <= -2.0 will be displayed.
🔸 Min Winrate
Minimum win rate percentage for a pair to be included in the table.
🔸 Min Profit Factor
Minimum profit factor required for a pair to stay in the results. These filters help you quickly narrow the list down to pairs that meet your quality criteria and match your risk profile.
📌 COLUMN SELECTION
This section lets you fully customize which metrics are displayed in the results table.
You can enable or hide any column to focus only on the data you need to identify the best pairs for trading. The screener allows you to show up to 12 metrics at the same time, which gives a detailed view of pair quality. Available columns:
🔹 Exchange Prefix
Show the exchange prefix in the ticker.
🔹 Correlation
Correlation between the two assets’ prices over the lookback period.
🔹 Score
Current Score value (Z-Score or S-Score).
On lower timeframe research, Score is not displayed.
🔹 Spread
Shows spread as % change since entry.
Positive value = profit on the main position.
🔹 Unrealized PnL
Shows unrealized PnL as a $ value based on current prices.
🔹 Profit
Total profit from all trades: Gross Profit − Gross Loss.
🔹 Winrate
Percentage of profitable trades out of all executed trades.
🔹 Profit Factor
Gross Profit / Gross Loss.
🔹 Trades
Total number of trades.
🔹 Max Drawdown
Maximum observed loss from peak to trough before a new peak is made.
🔹 Max Loss
Largest loss recorded on a single trade.
🔹 Long/Short Profit
Separate profit/loss for long trades and short trades.
🔹 Avg. Trade Time
Average duration of trades.
All these metrics are designed to help you quickly identify the strongest pairs for your strategy.
You can change colors, opacity, and hide any columns that are not relevant to your workflow.
🔔 ALERT
The alert system in this screener works in a specific way.
Alerts are tied directly to the filters you set in the Filter Settings section:
Minimum Correlation
Minimum Score
Minimum Winrate
Minimum Profit Factor
You can configure alerts to trigger when a new pair appears that matches all your filter conditions. 💡 Example
You set:
Minimum Score = 3
Then you create an alert based on the screener.
When any pair reaches a Score greater than +3 or less than −3, you will receive a notification.
This is how alerts work in this screener.
The idea is to deliver the most relevant information about the current market situation without forcing you to watch the screener all the time.
Supported placeholders for alert messages: {{ticker_1}} – main ticker (the one on the chart).
{{ticker_2}} – the paired ticker listed in the table.
{{corr}} – correlation value.
{{score}} – Score value (Z-Score or S-Score).
{{time}} – bar open time (UTC).
{{timenow}} – alert trigger time (UTC). You can use these placeholders to build alert text or JSON payloads in any format required by your tools.
The screener is designed to significantly enhance your pair trading workflow: it helps you quickly identify working pairs and current market inefficiencies, and with the alert system you can react to opportunities without constantly sitting in front of the screen.
Always remember that past performance does not guarantee future results.
Use the screener data within a risk-controlled trading system and adjust position sizing according to your own risk management rules.
RunRox - Pairs Strategy🧬 Pairs Strategy is a new indicator by RunRox included in our premium subscription.
It is a specialized tool for trading pairs, built around working with two correlated instruments at the same time.
The indicator is designed specifically for pair trading logic: it helps track the relationship between two assets, identify statistical deviations, and generate signals for opening and managing long/short combinations on both legs of the pair.
Below in this description I will go through the core functions of the indicator and the main concepts behind the strategy so you can clearly understand how to apply it in your trading.
📌 CONCEPT
The core idea of pair trading is to find and trade correlated instruments that usually move in a similar way.
When these two assets temporarily diverge from each other, a trading opportunity appears.
In such moments, the relatively overvalued asset is sold (short leg), and the relatively undervalued asset is bought (long leg).
When the spread between them narrows and both instruments revert back toward their typical relationship (mean), the position is closed and the trader captures the profit from this convergence.
In practice, one leg of the pair can end up in a loss while the other generates a larger profit.
Due to the difference in performance between the two assets, the combined result of the pair trade can still be positive.
✅ KEY FEATURES:
2 deviation types (Z-Score and S-Score)
Invert signals mode
Hedge Coefficient (position size balancing between both legs)
6 hedge modes
Entries based on Score or RSI
Extra entries based on Score or Spread
Stop Loss
Take Profit
RSI Filter
RSI Pivot Mode
Built-in Backtester Strategy
Lower Timeframe Backtester Strategy
Live trade panel for current position
Equity curve chart
21 performance metrics in the backtester
2 alert types
*And many more fine-tuning options for pair trading
🔗 SCORE
Score is the core deviation metric between the two assets in the pair.
For example, if you are trading ETHUSDT/BTCUSDT, the indicator analyzes the relationship ETH/BTC, and when one leg temporarily diverges from the other, this difference is reflected in the Score value.
In other words, Score shows how much the current spread between the two instruments deviates from its typical state and is used as the main signal source for pair entries and exits.
In the screenshot above you can see how Score looks in our indicator.
Depending on how large the difference is between the two assets, the Score value can move in a range from −N to +N
When Score is in the −N zone, this is a 🟢 long zone for the first asset and a short zone for the second.
Using the ETH/BTC example: when Score is deeply negative, you open a long on ETH and a short on BTC at the same time, then close both legs when Score returns back to the 0 zone (balance between the two assets).
When Score is in the +N zone, this is a 🔴 short zone for the first asset and a long zone for the second.
In the same ETH/BTC example: when Score is strongly positive, you short ETH and long BTC, and again close both positions when Score comes back to the neutral 0 zone.
☯️ Z/S SCORE
Inside the indicator we added two different formulas for calculating the spread between the two legs of the pair: Z-Score and S-Score.
These approaches measure deviation in different ways and can produce slightly different signals depending on the chosen pair and its behavior.
This allows you to switch between Z-Score and S-Score and choose the method that gives more stable and cleaner signals for your specific instruments.
As you can see in the screenshot above, we used the same pair but applied different Score types to measure the spread and deviation from the norm.
🟣 Z-Score – generated 9 entry signals .
It reacts to price fluctuations more smoothly and usually stays within a range of approximately −8 to +8 .
🟠 S-Score – generated 5 entry signals .
It reacts to price changes more aggressively and produces wider deviations, often reaching −15 to +15 .
This gives traders the choice between a more sensitive but smoother model (Z-Score) and a more selective, stronger-deviation model (S-Score)
⁉️ HOW DOES THE STRATEGY WORK
Here is a basic example of how you can trade this pair trading strategy using our indicator and its signals.
In the classic approach the trade consists of one initial entry and several scale-ins (averaging) if the spread continues to move against the position.
The first entry is opened when Score reaches a standard deviation of −2 or +2.
If price does not revert to the mean and moves further against the position so that Score expands to −3 or +3, the strategy performs the first scale-in.
If Score extends to −4 or +4, a second scale-in is added.
If the spread grows even more and Score reaches −5 or +5, a third scale-in is executed.
In our indicator the number of averaging steps can be up to 4 scale-ins .
After that the position waits until Score returns back to the 0 level , where the whole pair position is closed.
This is the standard model of classical pair trading.
However there are many variations:
using Stop Loss and Take Profit,
exiting earlier or later than the 0 zone,
scaling in not by Score but by Spread, since Score is not linear while Spread is linear,
entering when RSI on both tickers shows opposite extremes, for example RSI 20 on one asset and RSI 80 on the other, and so on.
The number of possible trading styles for this strategy is very large.
We designed the indicator to cover as many of these variations as possible and added flexible tools so you can build your own pair trading logic on top of it.
Below is an example of a classic pair trade with two entries: one main entry and one extra entry (scale-in) .
The pair SUIUSDT / PENGUUSDT shows a high correlation, and on one of the trades the sequence looked like this:
A −2 Score deviation occurred into the long zone and triggered the Main Entry .
🔹 Main Entry
Long SUIUSDT – Margin: 5,000 USD, Entry price: 1.5708
Short PENGUUSDT – Margin: 5,000 USD, Entry price: 0.011793
Price then moved further against the position, Score went deeper into deviation, and the strategy added one extra entry.
🔸 Extra Entry
Long SUIUSDT – Margin: 5,000 USD, Entry price: 1.5938
Short PENGUUSDT – Margin: 5,000 USD, Entry price: 0.012173
The trade was closed when Score reverted back toward the 0 zone (mean reversion of the spread):
❎ Exit
SUIUSDT P&L: −403.34 USD, Exit price: 1.5184
PENGUUSDT P&L: +743.73 USD, Exit price: 0.011089
✅ Total P&L: +340.39 USD
With a total margin of 10,000 USD used per side (20,000 USD combined), this trade yielded around +1.7% on the deployed margin.
On different assets the size and speed of the spread movement will vary, but the principle remains the same.
This is just one example to illustrate how the strategy works in practice using simplified theoretical balances.
⚙️ MAIN SETTINGS
After explaining how the strategy works, we can move to the indicator settings and their logic.
The first block is Main Settings, which controls how the pair is built, how the spread is calculated, and how the backtest is performed.
The core idea of the indicator is to backtest historical data, generate entry signals, show open-position parameters, and provide all necessary metrics for both discretionary and algorithmic trading.
This is a complete framework for analyzing a pair of assets and building a trading system around them. Below I will go through the main parameters one by one.
🔹 Exclude Dates
Allows you to exclude abnormal periods in the pair’s history to remove outlier trades from the backtest.
This is useful when the market experienced extreme news events, listing spikes, or other non-typical situations that distort statistics.
🔹 Pair
Here you select the second asset for your pair.
For example, if your main chart is BTCUSDT, in this field you choose a correlated asset such as ETHUSDT, and the working pair becomes BTCUSDT / ETHUSDT.
The indicator then calculates spread, Score, and all related metrics based on this asset combination.
🔹 Lower Timeframe
This is a special mode for backtesting on a lower timeframe while using a higher timeframe chart to extend the history limit.
For example, if your TradingView plan provides only 5,000 bars of history on the current timeframe, you can switch your chart to a higher timeframe and select a lower timeframe in this setting.
The indicator will then reconstruct the pair logic using up to 99,000 bars of lower timeframe data for backtesting.
This allows you to test the pair on a much longer historical period and find more stable combinations of assets.
🔹 Method
Here you choose which deviation model you want to use: Z-Score or S-Score.
Both methods calculate spread deviation but use different formulas, which can give different signal behavior depending on the pair.
Examples of these two methods are shown earlier in this description.
🔹 Period
This parameter defines how many bars are used to calculate the average deviation for the pair.
If you set Period = 300, the indicator looks back 300 bars and calculates the typical spread deviation over that window.
For example, if the average deviation over 300 bars is around 1%, then a move to 2% or more will push Z/S Score closer to its boundary levels, since such a deviation is considered abnormal for that lookback period.
A larger Period means that only bigger deviations will be treated as anomalies.
A smaller Period makes the model more sensitive and treats smaller deviations as anomalies.
This allows you to tune how aggressive or conservative your pair trading signals should be.
🔹 Invert
This setting is used for negatively correlated pairs.
Some instruments have a positive correlation in the range from +0.8 to +1.0 (strong positive correlation), while others show a negative correlation from −0.8 to −1.0, meaning they usually move in opposite directions.
A classic example is the pair EURUSD and DXY.
As shown in the screenshot above, these instruments often have strong negative correlation due to macro factors and typically move in opposite directions: when EURUSD is rising, DXY is falling, and vice versa.
Such pairs can also be traded with our indicator.
To do this, we use the Invert option, which effectively flips one of the assets (as shown in the screenshot below). After inversion, both instruments are brought to a “same-direction” behavior from the model’s point of view.
From there, you trade the pair in the same way as a positively correlated one:
you open both legs in the same direction (both long or both short) depending on the spread and Score, and then wait for the spread between the inverted pair to converge back toward its mean.
🔀 HEDGE COEFFICIENT
The next block of settings is related to the hedge coefficient.
This defines how much margin is allocated to each leg of the pair.
The classic approach in pair trading is to split the position equally between both assets.
For example, if you allocate 100 USD to a trade , the standard model would open 50 USD long on one asset and 50 USD short on the other.
This works well for pairs with similar volatility , such as BTCUSDT / ETHUSDT
However, if you use a pair like BTCUSDT / DOGEUSDT , the volatility of these assets is very different.
They can still be correlated, but their amplitude is not the same. While Bitcoin might move 2% , Dogecoin can move 10% over the same period.
Because of that, for pairs with strongly different volatility, we can use a hedge coefficient and, for example, enter with 30 USD on one leg and 70 USD on the other, taking the volatility difference into account.
This is the main idea behind the Hedge Coefficient section and its primary use.
The indicator includes 6 methods of calculating the coefficient:
Cumulative RMA
Beta OLS
Beta TLS
Beta EMA
RMA Range
RMA Delta
Each method uses a different formula to compute the hedge coefficient and to size the position based on different metrics of the assets.
We leave it to the trader to decide which algorithm works best for their specific pair and style.
Below are the settings inside this section:
🔹 Method
When Auto Hedge is enabled, you can select which method to use from the list above.
The chosen method will automatically calculate the hedge coefficient between the two legs.
🔹 Hedge Coefficient
This is the manual hedge ratio per trade when Auto Hedge is disabled.
By default it is set to 1, which means the position is opened 50/50 between the two assets.
🔹 Min Allowed Hedge Coef.
This is the minimum allowed hedge coefficient.
By default it is 0.2, which means the model will not go below a 20% / 80% split between the legs.
🔹 MA Length
For methods that use moving averages (for example Beta EMA), this parameter sets the period used to calculate the hedge coefficient.
🛠️ STRATEGY SETTINGS
The next important block is Strategy Settings .
Here you define the core parameters used for backtesting: trading commission, position size, entry / exit logic, Stop Loss, Take Profit, and other rules that describe how you want the strategy to operate.
Below are all parameters with a detailed explanation.
🔸 Commission %
In this field you set your broker’s fee percentage per trade .
The indicator automatically calculates the correct commission for each leg of every trade. You only need to input the real commission rate that your broker charges for volume. No additional manual calculations are required.
🔸 Main Entry Mode
There are two options for the main entry:
Score - This is the primary entry method based on Z/S Score.
When Score reaches the deviation level defined in the settings below, the strategy opens the first position.
For example, if you set “Entry at 2 deviations”, the trade will be opened when Score hits ±2.
RSI Only - Alternative entry method based on RSI divergence between the two assets.
The exact RSI levels are defined in the RSI settings section below.
For example, if you set the entry threshold at 30, then when one asset has RSI below 30 and the second one has RSI above 70, the first entry will be triggered.
🔸 Extra Entries Mode
This defines how scale-ins (averaging) are executed. There are two modes:
Score - Works the same way as the main entry, but for additional entries.
For example, the main entry can be at 2 deviations, the first scale-in at 3, the second at 4, etc.
Spread - This mode uses the Spread (difference between the two assets) starting from the main entry moment.
As the spread continues to widen, the strategy can add extra entries based on spread growth rather than Score.
Since Score is a non-linear metric and Spread is linear, in some configurations averaging by Spread can produce better results than averaging by Score. This is pair- and strategy-dependent. 🔸 Entry parameters
Deviation / Spread threshold
Entry size
Main Entry – first field (deviation / spread), second field (position size)
Entry 2 – first field (deviation / spread), second field (position size)
Entry 3 – first field (deviation / spread), second field (position size)
Entry 4 – first field (deviation / spread), second field (position size)
This allows you to define up to four scaling steps with different triggers and different sizing.
🔸 Exit Level
This parameter defines at what Score level you want to exit the trade.
By default it is 0, which means the backtester closes the position when Score returns to the neutral (0) zone.
You can also use positive or negative values. Example:
Assume your main entry is configured at a 3 deviation.
You can exit at the 0 level, or you can set Exit Level = 2.
If your initial entry was at −3, the position will be closed when Score reaches +2.
If your initial entry was at +3, the position will be closed when Score reaches −2.
This approach can increase the profit per trade due to a larger captured spread, but it may also increase the holding time of the position.
🔸 Stop Loss
Here you define the maximum loss per trade in PnL units.
If a trade reaches the negative PnL value specified in this field and the Stop Loss option is enabled, the indicator will close the trade at a loss.
The Cooldown parameter sets a pause after a losing trade:
the strategy will wait a specified number of bars before opening the next trade.
🔸 Take Profit
Works similar to Stop Loss but for profit targets.
You set the desired PnL value you want to reach.
The trade will be closed when either the Take Profit target is hit or when Score reaches the exit level defined in the settings, whichever occurs first (depending on your configuration).
🔸 Show Qty in currency
When enabled, trade size is displayed in currency (USD) instead of token quantity.
This is useful for quickly understanding position size in monetary terms.
You will see this in the Current Trade panel, which is described later.
🔸 Size Rounding
Controls how many decimal places are used when rounding position size (from 0 to 10 digits after the decimal).
This is also used for the Current Trade panel so you can adjust how detailed or compact the size display should be.
📊 RSI FILTERS
This section is used for additional trade filtering.
RSI can be used in two ways:
as a primary entry signal,
or as an extra filter for entries based on Z/S Score.
If in the Strategy Settings the Main Entry Mode is set to RSI, then RSI becomes the main trigger for opening a position.
In this case a trade is opened when the RSI of the two assets reaches opposite zones.
Example:
If the threshold is set to 30, then:
when one asset has RSI below 30, and
the second asset has RSI above 70 (100 − 30),
the strategy opens the first entry.
All extra entries after that will be executed either by Spread or by Z/S Score, depending on your Extra Entries Mode.
Below are the parameters in this block:
RSI Length – standard RSI period setting.
RSI Pivot Mode – when enabled, RSI is used as an additional filter together with Z/S Score. The indicator looks for a reversal pattern on RSI (pivot behavior). If RSI forms a reversal structure, the trade is allowed to open. If not, the signal is skipped until a proper RSI pivot is formed.
Entry RSI Filter – here you define the RSI thresholds used for RSI-based entries. These are the same boundary levels described in the example above.
Overall, this section helps filter out lower-quality trades using additional RSI conditions or lets you build RSI-only entry logic based on extreme levels.
🎨 MAIN CHART STYLING
This section controls the visual appearance of trades on the main chart.
You can customize how the second asset line is drawn, as well as the icons for entries, scale-ins, and exits, including their size and style.
▫️ Price Line
This is the line that shows the price of the second asset and the relative difference between the two instruments.
You can adjust the line thickness and color to make it more readable on your chart.
▫️ Adjust Price Line by Hedge Coefficient
When this option is enabled, the second asset’s line is normalized by the hedge coefficient.
If you turn it off, the hedge coefficient will not be applied to the second asset’s line, and it will be displayed in raw form.
▫️ Entry Label
Here you can customize how the entry markers look:
choose the color, icon style, and size of the label that marks each trade entry and scale-in on the chart.
▫️ Exit Label
Similarly, you can define the color, icon style, and size of the label used for exits.
This helps visually separate entries and exits and makes it easier to read the trade history directly from the chart.
🎯 INDICATOR PANEL
This section controls the settings of the indicator panel, which works like an oscillator and allows you to visualize multiple metrics in one place.
You can flexibly enable, style, and scale each parameter.
🔹 Score
Displays the main deviation metric between the two assets.
You can customize the color and line thickness of the Score plot.
🔹 Spread
Shows the spread between the two assets.
It starts calculating from the moment the trade is opened.
You can adjust its color and thickness for better visibility.
🔹 Total Profit
Displays the cumulative profit for this pair and strategy as a line that grows (or falls) over time.
Color, opacity, and line thickness can be customized.
🔹 Unrealized PNL
Once a trade is opened, this line shows the current PnL of the active position.
It also lets you see historical drawdowns on the pair.
Color and thickness can be adjusted.
🔹 Released PNL
Shows the realized PnL of each closed trade as bars.
Useful for quickly evaluating the result of every individual trade in the backtest.
🔹 Correlation
Plots the correlation coefficient between the two assets as a graph, so you can visually track how stable or unstable the relationship between them is over time.
🔹 Hedge Coefficient
Shows the hedge coefficient as a line, which helps understand how the model is rebalancing exposure between the two legs depending on their behavior.
For each metric there is also a 📎 Stretch option.
Stretch allows you to compress or expand the scale of a specific line to visually align metrics with different ranges on the same panel and make the chart easier to read.
📈 PROFIT CHART
Since TradingView does not natively support proper backtesting for pair trading, this indicator includes its own profit curve for the pair.
You can visually see how the strategy performed over historical data: whether there were deep drawdowns, abnormal profit spikes, or stable equity growth over time. This makes it much easier to evaluate the quality of the pair and the strategy on history.
In the settings of this section you can flexibly customize how the profit chart is displayed:
labels, position of the panel, padding, and other visual details.
Everything depends on your personal preferences, so we give full control over styling:
you can adjust the look of the profit chart to match your layout or completely hide it from the chart if you do not need it.
📌 CURRENT TRADE
This section controls the current trade table.
When there is an active trade on the chart, the panel displays all key information for the open position:
direction for each ticker (long or short),
required position size for each leg,
entry price for both assets,
and real-time PnL for each leg separately,
so you always have a clear view of the current situation.
The main thing you can do with this table is customize its appearance:
you can change the size, position on the chart, background and text colors, as well as separate coloring for positive / negative PnL and different colors for long and short positions.
📅 BACKTEST RESULTS
The next key block is Backtest Results.
This results table with detailed metrics gives you an extended view of how the pair and strategy perform: win rate, profit factor, long/short breakdown, and more than 20 additional stats that help you evaluate the potential of your setup.
⚠️ First of all, it is important to note ⚠️
past performance does not guarantee future results.
Every trader must keep this in mind and factor these risks into their strategy.
The table shows metrics in three cuts:
All Entries
Main Entries
Extra Entries (scale-ins)
Core metrics:
Profit – total profit for each entry type.
Winrate – win rate for this pair.
Profit Factor – ratio of gross profit to gross loss for the strategy.
Trades – number of trades in the backtest.
Wins – number of winning trades.
Losses – number of losing trades.
Long Profit – profit generated by long positions.
Short Profit – profit generated by short positions.
Longs – total number of long trades.
Shorts – total number of short trades.
Avg. Time – average time spent in a trade.
Additional metrics for a deeper evaluation of the pair:
Correlation – current correlation between the two assets in the pair.
Bars Processed – number of bars used in the analysis.
Max Drawdown – maximum historical drawdown of the strategy.
Biggest Loss – the largest single losing trade in the backtest.
Recommended Hedge – recommended hedge coefficient based on historical behavior.
Max Spread – maximum positive spread observed in history.
Min Spread – maximum negative spread observed in history.
Avg. Max Spread – average of positive extreme spread values (above 0).
Avg. Min Spread – average of negative extreme spread values (below 0).
Avg Positive Spread – average positive spread across all trades (only values above 0).
Avg Negative Spread – average negative spread across all trades (only values below 0).
Current Spread – current spread between the assets when a trade is open.
These metrics together allow you to quickly assess how stable the pair is, how the risk/return profile looks, and whether the strategy parameters are suitable for live trading. You can fully customize this results table to fit your workflow:
hide metrics you don’t need, change colors, opacity, and other visual styles, and reorder the focus of the stats according to your trading style.
This way the backtest block can show only the metrics that matter to you most and remain clean and readable during analysis.
📣 ALERTS
The next section is dedicated to alerts.
Here you can configure all signals you need, both for manual trading and for full automation of this pair trading strategy. This block is designed to cover most practical use cases. The indicator supports two alert modes:
Single Alert – one universal custom alert for all events.
Two Alerts – separate alerts for each ticker so you can receive different messages per asset.
Available alert events:
Main Entry – when the main entry is triggered.
Entry 2 – when the first scale-in is executed.
Entry 3 – when the second scale-in is executed.
Entry 4 – when the third scale-in is executed.
Exit Alert – when the position is closed.
StopLoss Alert – when Stop Loss is hit.
TakeProfit Alert – when Take Profit is hit.
All alerts are fully customizable and support a set of placeholders for building structured messages or JSON payloads.
🔹1 Alert Type
List of supported placeholders: {{event}} – trigger name ('Entry 1', 'Exit').
{{dir_1}} – 'Long' or 'Short' for the main ticker.
{{dir_2}} – 'Long' or 'Short' for the other ticker.
{{action_1}} – 'Buy', 'Sell' or 'Close' for the main ticker.
{{action_2}} – 'Buy', 'Sell' or 'Close' for the other ticker.
{{price_1}} – price for the main ticker.
{{price_2}} – price for the other ticker.
{{qty_1}} – order size for the main ticker.
{{qty_2}} – order size for the other ticker.
{{ticker_1}} – main ticker (e.g. 'BTCUSD').
{{ticker_2}} – other ticker (e.g. 'ETHUSD').
{{time}} – candle open time in UTC.
{{timenow}} – signal time in UTC.
🔹2 Alert Type
List of supported placeholders: {{event}} – trigger name ('Entry 1', 'Exit', 'SL', 'TP').
{{action}} – 'Buy', 'Sell' or 'Close'.
{{price}} – order price.
{{qty}} – order size.
{{ticker}} – ticker (e.g. 'BTCUSD').
{{time}} – candle open time in UTC.
{{timenow}} – signal time in UTC. You can use these placeholders to build any JSON structure or custom alert text required by your trading bot, exchange API, or automation service.
In this post I’ve explained how the indicator works, the core concept behind this pair trading strategy, and shown practical examples of trades together with a detailed breakdown of each unique feature inside the tool.
We have invested a lot of work into building this indicator and we truly hope it will help you trade pair strategies more efficiently and more profitably by giving you structured, strategy-specific information that is difficult to obtain in any other way.
⚠️ Please also remember that past performance does not guarantee future results.
Always evaluate the risks, the robustness of your setup, and your own risk tolerance before entering any position, and make independent, well-considered decisions when using this or any other strategy.
RS High Beta Exposure | QuantLapseRS High Beta Exposure | QuantLapse
Conceptual Foundation and Innovation
The RS High Beta Exposure indicator from QuantLapse is a comprehensive multi-asset allocation and momentum-ranking system that integrates beta and trend analysis, pairwise relative strength comparison, and volatility-adjusted filtering.
Its objective is to identify dominant crypto assets while dynamically reallocating High Beta exposure based on a calculated relative strength. The objective is to integrate trend analysis along with volatility filtering to these pairs to determine its relative strength.
At its core, RS High Beta Exposure indicator measures the systematic (β) performance of each asset relative to other assets provided combining these measures with inter-asset ratio trends to determine which assets exhibit superior strength and momentum relative to the other assets.
This integration of relative strength comparison, and trend and filtering analysis represents a quantitative evolution of traditional relative strength analysis, designed for adaptive asset rotation across major cryptocurrencies.
Technical Composition and Calculation
The indicator is structured around three major analytical layers:
1. Beta and Alpha Analysis
-Each asset’s return is decomposed into systematic components relative to the other assets by using a trend based, volatility filtering model.
-Assets with the highest point on a relative strength basis above the median are considered outperformers and eligible for allocation.
2. Pairwise Ratio Momentum
-Every asset is compared against all others through a ratio-trend, where momentum based trend scores quantify the directional momentum between each pair.
-In addition, we filter any false signals with volatility adjusted trends in which ensure high quality signals.
3. High Confidence Ranking
-Using the Pairwise Momentum signals, the RS High Beta Exposure scores them. If the asset comparison is given a signal, the RS High Beta Exposure scores points for each asset.
-If the total points of an asset is 5, its given the rank the dominant asset and is most likely to outperform.
By combining these layers, RS High Beta Exposure determines not only which assets is the strongest but also which assets to be invested.
User Inputs and Feature Adaptability
The indicator includes set of customizable parameters to support portfolio and risk management preferences:
Start Date Filter – Defines the beginning of live strategy evaluation.
Display Options – Able to change the location of the RS Table, Background and equity color.
Asset Selection – Modify or replace up to six crypto assets in the ranking matrix
asset1 = input.symbol("CRYPTO:XRPUSD", title ="Asset 1")
asset2 = input.symbol("CRYPTO:BNBUSD", title ="Asset 2")
asset3 = input.symbol("CRYPTO:ADAUSD", title ="Asset 3")
asset4 = input.symbol("CRYPTO:DOGEUSD", title ="Asset 4")
asset5 = input.symbol("CRYPTO:XLMUSD", title ="Asset 5")
asset6 = input.symbol("CRYPTO:LINKUSD", title ="Asset 6")
Each module operates cohesively to maintain analytical transparency while allowing user-level control over system sensitivity and behavior.
Real World, Practical Applications
The RS High Beta Exposure indicator is designed for systematic traders and quantitative portfolio managers who seek a disciplined framework for dynamic crypto asset rotation.
Key applications include:
High-Beta Asset Identification: Systematically identify crypto assets exhibiting relative dominance and stronger momentum characteristics versus peers within the comparison set.
Rule-Based Portfolio Rotation: Reallocate exposure toward leading assets using objective pairwise signals, reducing emotional decision-making and FOMO-driven trades.
Trend-Aligned Risk Participation: Employ the pairwise relative strength model to maintain exposure only during favorable momentum conditions, helping avoid prolonged participation in weak or deteriorating trends.
By combining relative strength comparisons with trend-aware filtering, this framework bridges quantitative finance and market regime analysis, providing a structured, data-driven approach to crypto asset allocation.
Advantages and Strategic Value
RS High Beta Exposure goes beyond conventional relative strength tools by integrating multi-asset comparison, ratio-based dominance scoring, and volatility-aware regime filtering into a single coherent framework.
By employing a three-layer confluence model — combining trend integrity, relative performance attribution, and volatility-state confirmation — the system improves the reliability of rotation and trend-following decisions.
The model is particularly valuable for traders seeking to:
Mitigate drawdowns while participating in higher-beta assets through regime-aware exposure control.
Identify persistent outperformers early in emerging market trends.
Maintain capital exposure only when statistical and momentum conditions signal elevated confidence.
The inclusion of visual allocation tables and a dynamic alert system makes RS High Beta Exposure both transparent and actionable, supporting discretionary analysis as well as systematic or automated trading workflows.
Alerts and Visualization
The script delivers clear, intuitive visual cues and alert-based feedback to support real-time decision-making:
Color-coded background states visually indicate the current allocation regime.
Allocation labels and summary tables display the dominant asset and its relative strength in real time.
An integrated alert system automatically notifies users whenever allocation states change (e.g., “100% XRP” or “100% CASH”).
Together, these visualization and alert features make RS High Beta Exposure both analytically rigorous and easy to interpret, even in fast-moving live market conditions.
Summary and Usage Tips
RS High Beta Exposure is an advanced interpretation of relative strength analysis, blending pairwise momentum comparisons, multi-asset dominance scoring, and adaptive volatility filters into a disciplined framework for crypto asset rotation.
By combining cross-asset selection with systematic allocation logic, the indicator helps traders determine when to be exposed, which asset demonstrates leadership, and when to step aside during unfavorable conditions. The model is best applied on the 1D timeframe, where its structure is optimized for identifying sustained leadership rather than short-term price noise. For broader context and confirmation, it can be used alongside other QuantLapse systematic models at the portfolio level.
Note: Past performance does not guarantee future results. This indicator is intended for research and educational use within TradingView.
Vega Convexity Regime Filter [Institutional Lite]STOP TRADING THE NOISE.
90% of retail trading losses occur during "Chop"—sideways markets where standard trend-following bots bleed capital through slippage and fees. Institutional desks know that the secret to high returns isn't just winning trades; it's knowing when to sit in cash.
The Vega V6 Regime Filter is the "Gatekeeper" layer of our proprietary Hierarchical Machine Learning engine (developed by a 25-year TradFi Risk Quant). It calculates a composite volatility score to answer one simple question: Is this asset tradeable right now?
THE VISUAL LOGIC
This indicator visually filters market conditions into two distinct Regimes based on our institutional backtests:
🌫️ GREY BARS (Noise / Chop)
The State: Volatility is compressing. The trend is undefined or weak.
The Trap: This is where MACD/RSI give false signals.
Institutional Action: Sit in Cash. Preserve Capital. Wait.
🟢 🔴 COLORED BARS (Impulse)
The State: Volatility is expanding. Momentum is statistically significant.
The Opportunity: A "Fat-Tail" move is likely beginning.
Institutional Action: Deploy Risk. Look for entries.
HOW IT WORKS (The Math)
Unlike simple moving average crossovers, the Vega Gatekeeper analyzes 4 distinct market dimensions simultaneously to generate a Tradeability Score (0-10) :
Trend Strength (ADX): Is there a vector?
Momentum (RSI/MACD): Is the move accelerating?
Volatility (Bollinger Bands): Is the range expanding?
Volume Flow: Is there institutional participation?
The Rule: If the composite score is < 4 , the market is Noise. The bars turn Grey. You do nothing.
BEST PRACTICES
For Swing Trading (Daily): Use Medium sensitivity. Only look for entries when the background turns Green/Red.
For Day Trading (4H/1H): Use Low sensitivity (more conservative). Use the Grey zones to tighten stops or exit positions.
THE PHILOSOPHY: "CASH IS A POSITION"
Most traders feel the need to be in a trade 24/7. The Vega V6 Engine (the system this tool is based on) achieved a +3,849% backtested return (18 months) largely by sitting in cash during chop. This tool visualizes that discipline.
🔒 WANT THE DIRECTIONAL SIGNALS?
This Lite version provides the Regime (When to trade).
To get the specific Entry Signals , Intraday Stop-Losses , and Probability Matrix (Stage 2 of our model), you need the Vega V6 Convexity Engine .
The Pro Version includes:
🚀 Specific Direction: Classification of "Explosion," "Rally," or "Crash."
🛡️ Dynamic Risk: Plots the exact Stop Loss levels used in our institutional backtests.
🌊 Macro Data: Integration of M2 Liquidity flow alerts.
👉 ACCESS INSTRUCTIONS:
Links to the Pro System , our Live Dashboard , and the 18-Month Performance Audit can be found in the Author Profile below or in the script settings.
Disclaimer: This tool is for educational purposes only. Past performance is not indicative of future results. Trading cryptocurrencies involves significant risk.
NEURAL FLOW | The AI-Powered Regime Classifier [by @Ash_TheTrade📉 Stop Trading Blindly. Filter the Noise with AI.
Why do your favorite strategies work perfectly one week and bleed your account the next?
The answer is simple: Context.
A Moving Average crossover works in a trend but gets slaughtered in chop. RSI works in a range but fails in a strong breakout. Most indicators are "dumb"—they apply the same math regardless of the market's current reality.
I created Neural Flow to fix this.
Developed by @Ash_TheTrader, this isn't just another buy/sell arrow indicator. It is a sophisticated market Regime Classifier built on concepts derived from machine learning (Lorentzian Distance algorithms).
It doesn't just tell you where price is; it tells you what the market is doing.
🧠 The Concept: How It Works
The core idea behind this script is simple yet powerful: Don't trade unless the environment is right.
The Neural Flow algorithm acts like a veteran trader watching over your shoulder. It analyzes multiple "neurons" (data points representing momentum, volatility, and cyclicality) and compares the current price action to historical data.
By identifying what "state" the market is currently in, it paints your chart in real-time, acting as the ultimate filter for any strategy you use.
👁️ The 4 Market Regimes
The indicator instantly classifies the market into one of four distinct states, visualizing them with a full-chart background glow and candle painting:
1. 🐂 Bull Trend (Neon Green)
The market has clear upward momentum, healthy RSI, and strong trend orientation.
Action: Look for Long entries. Buy dips.
2. 🐻 Bear Trend (Neon Red)
The market has clear downward momentum and weak underlying metrics.
Action: Look for Short entries. Sell rallies.
3. 🚫 CHOP (Grey/Monochrome)
This is the most important feature. The AI has detected low volatility squeeze conditions or directionless ADX. This is where 80% of traders lose money due to fake-outs and whipsaws.
Action: DO NOT TRADE. Sit on your hands and preserve capital.
4. ⚡ Breakout Detected (Gold/Yellow)
The algorithm has detected a sudden, violent expansion in volatility (Bollinger Width explosion) following a period of chop. The direction is not yet confirmed, but a big move is imminent.
Action: Get ready. Watch for a transition into a Bull or Bear regime.
💻 The Glassmorphism Dashboard & AI Confidence
In the corner of your chart, you will find a futuristic, transparent "Glass UI" dashboard designed by @Ash_TheTrader.
It provides instant situational awareness without cluttering your view.
The AI Confidence Score:
This is your conviction meter. It calculates how aligned the various "neurons" of the algorithm are (ranging from 0% to 100%).
A Bull Trend with 40% Confidence might be weak and prone to reversal.
A Bull Trend with 85%+ Confidence indicates strong confluence across multiple data points.
Pro Tip from @Ash_TheTrader: Only take trades when the AI Confidence is above 75%.
🚀 How to Use This in Your Trading
This tool is designed to be versatile.
As a Strategy Filter (Recommended): Use your existing favorite strategy (e.g., MACD, SMC, Price Action). Before taking a trade, glance at the Neural Flow background.
Your strategy says Buy, but the background is Grey (Chop)? Skip the trade.
Your strategy says Sell, and the background is Red (Bear)? Take the trade with confidence.
As a Standalone System: Wait for the market to transition out of "Grey Chop" into a "Green Bull" or "Red Bear" regime. Confirm that the "AI Confidence" on the dashboard is high (>70%), and enter in the direction of the new trend.
⚙️ Settings & Customization
While the default settings are tuned for most markets, @Ash_TheTrader believes in flexibility:
Training Window: Adjust the sensitivity of the regime detection.
Visuals: Customize all colors to match your chart aesthetic.
Glass Dashboard: Move it, resize it, or turn it off completely.
Baseline EMA: Toggle the 50-period baseline reference line on or off to keep your charts ultra-clean.
A Note from the Author:
"Trading isn't about catching every move; it's about catching the right moves and staying safe during the noise. I built this tool to help me instantly recognize when to step on the gas and when to hit the brakes. I hope it brings clarity to your charts."
— @Ash_TheTrader
Disclaimer: This tool is for informational purposes only and does not constitute financial advice. Always manage your risk.
Price Action Visualizer (EMA/SMA Color Bars)This custom Pine Script indicator, "EMA(21) vs SMA(30) Color Bars," provides a unique and immediate visual representation of market bias by dynamically painting the candlesticks based on their position relative to two critical moving averages.
💡 What It Does:
The indicator calculates and plots the 21-period Exponential Moving Average (EMA) and the 30-period Simple Moving Average (SMA). It then analyzes the closing price of each candle and colors the entire candlestick (body and border) according to pre-defined trend conditions.
This visualization allows traders to identify strong trend environments versus periods of consolidation or indecision at a glance, removing the need to constantly check the price relationship manually.
🎨 Color Conditions and Meaning:
The indicator uses three distinct color states to signal the market's current momentum:
Color,Condition,Market Interpretation
🟢 GREEN,Closing Price is ABOVE both the 21 EMA AND the 30 SMA.,Strong Bullish Trend: Suggests high momentum and confirmation of an uptrend. Ideal for long bias.
🔴 RED,Closing Price is BELOW both the 21 EMA AND the 30 SMA.,Strong Bearish Trend: Suggests high downward pressure and confirmation of a downtrend. Ideal for short bias.
⚫ GRAY,"Closing Price is in any other state (e.g., between the two MAs, or under one and over the other).","Neutral / Consolidation: Indicates uncertainty, low momentum, or potential trend exhaustion/reversal. Caution is advised."
🔧 Customization Options:The indicator is fully customizable, allowing users to fine-tune the periods to match their preferred trading style (e.g., scalping, swing trading).Dĺžka EMA (Length EMA): Allows you to change the period for the Exponential Moving Average (default is 21).Dĺžka SMA (Length SMA): Allows you to change the period for the Simple Moving Average (default is 30).
VCAI Stochastic RSI+VCAI Stoch RSI+ is a cleaned-up Stochastic RSI built with V-Core colours for faster, clearer momentum reads and more reliable OB/OS signals.
What it shows:
Purple %K line → bearish momentum strengthening
Yellow %D line → bullish momentum building and smoothing
Soft purple/yellow background bands → OB/OS exhaustion zones, not just raw 80/20 triggers
Midline at 50 → balance point where momentum shifts between bull- and bear-side control
Optional HTF mode → run Stoch RSI from any timeframe while viewing it on your current chart
How to read it:
Both lines rising out of OS → early bullish shift; pullbacks that hold direction favour continuation
Both lines falling from OB → early bearish shift; bounces into the purple OB zone can become fade setups
Lines stacked and moving together → strong, cleaner momentum
Lines crossing repeatedly → low-conviction, choppy conditions
OB/OS shading highlights exhaustion so you focus on moves with context, not every 80/20 tick
Why it’s different:
Classic Stoch RSI is hyper-sensitive and mostly noise.
VCAI Stoch RSI+ applies V-Core’s colour-driven regime logic, controlled OB/OS shading, and optional HTF smoothing so you see momentum structure instead of clutter — making it easier to judge when momentum is genuinely shifting and when it’s just another wiggle.
VCAI RSI Divergence +VCAI RSI Divergence+ is an RSI that shows trend, momentum, and divergence using V-CoresAI colour logic instead of a single white line.
What it shows:
Yellow RSI line → bullish momentum (RSI above its MA; buy-side pressure in control)
Purple RSI line → bearish momentum (RSI below its MA; sell-side pressure in control)
Thin blue line → fast RSI moving average that drives the colour flips
Dashed 70/30 lines → classic OB/OS zones
Background bands → soft purple in OB, soft yellow in OS to mark exhaustion areas
How to read it:
Yellow & rising → momentum shifting bullish; pullbacks into yellow OS band can be accumulation zones
Purple & falling → momentum shifting bearish; pushes into purple OB band can be distribution/sell zones
Hard colour flips (yellow ↔ purple) mark trend regime changes, not minor RSI noise
Divergence mode (on/off)
The divergence engine scans RSI and price pivot structure:
Bullish divergence (yellow) → price lower low + RSI higher low
Bearish divergence (purple) → price higher high + RSI lower high
Lines and tags appear only where a meaningful disagreement between price and RSI exists, giving early context for potential reversals or fade setups.
Together, the momentum colours + optional divergence mapping give a far clearer market read than a standard RSI, with zero clutter and no guesswork.
Structure Break ModelMAIN FEATURES
Supported Assets & Timeframe
This indicator is specifically designed and calibrated for 30 USDT trading pairs on the H4 timeframe, all of which have been actively traded for over 1,000 days, including:
BTCUSDT, ETHUSDT, XRPUSDT, BNBUSDT, SOLUSDT, TRXUSDT, DOGEUSDT, ADAUSDT, XLMUSDT, BCHUSDT,
ZECUSDT, LINKUSDT, HBARUSDT, UNIUSDT, LTCUSDT, AVAXUSDT, SHIBUSDT, DOTUSDT, AAVEUSDT, NEARUSDT,
ETCUSDT, ICPUSDT, FILUSDT, APTUSDT, ENSUSDT, ATOMUSDT, VETUSDT, QNTUSDT, CRVUSDT, INJUSDT
Using the script on other pairs or timeframes will trigger an automatic warning to prevent incorrect usage.
1. Structural Weakening Model (Core Logic)
At the heart of the system lies the Structural Weakening Model (SWM) — a multi-layered market-structure engine that identifies momentum exhaustion and confirms genuine reversals using pivot-based swing architecture.
Pivot Structure Mapping
The indicator continuously analyzes Pivot Highs and Pivot Lows (length = 5) to establish clean, stable swing structure.
Weakening Pattern Detection
The model evaluates directional fatigue by detecting pivot sequences:
2–6 Higher Lows → Weakening buyers → Potential SELL setup
2–6 Lower Highs → Weakening sellers → Potential BUY setup
This mechanism identifies “compression zones” where market pressure fades before a structural shift.
Breakout Confirmation Layer
A signal is only triggered when price breaks the final structural anchor of the pivot chain.
This ensures:
Optional Trend Filter (MA Alignment)
Users may select EMA, SMA, WMA, HMA and more.
Price above MA → BUY-only mode
Price below MA → SELL-only mode
This keeps signals aligned with broader market flow.
Visual Example – SELL Signal (TP Hit)
2. Signal Conditions (How the System Works)
SELL Setups
Triggered when:
Price forms 2–6 higher lows, signaling weakening buyers
Price breaks below the structural pivot anchor
(Optional) Price is below the MA filter
BUY Setups
Triggered when:
Price forms 2–6 lower highs, signaling weakening sellers
Price breaks above the structural pivot anchor
(Optional) Price is above the MA filter
Visual Example – SELL Signal (SL Hit)
3. Automatic Capital Management
The script integrates full risk-management utilities:
Starting capital (default 10,000 USDT)
Risk % per trade
Leverage (x10 → x100)
Automatic position sizing
Margin requirements
Real-time TP/SL calculations
This turns the indicator into not just a signal tool, but a complete trading assistant.
4. Flexible Stop-Loss System
Users may choose:
Swing-based SL (nearest structural pivot)
Fixed SL %
Custom TP based on R:R (1:1.5 → 1:5)
Default R:R = 1:2
SL/TP levels update instantly whenever settings change.
Input Settings Menu
5. Visual Interface
The chart displays:
Entry, TP, SL (extended 20 candles)
BUY/SELL labels
Real-time TP/SL hit status
Full info panel:
Latest signal
Entry price
TP/SL
Leverage
Risk %
Required margin
Win/loss & R statistics
Days on chart: The total number of trading days calculated from your chart’s visible data
All signals follow the exact same logic in historical and real-time charts.
Zero repainting.
6. Internal Backtest Engine (Not Official TradingView Backtesting)
The script includes an internal backtest calculator that evaluates:
SL methods
TP R:R settings
Signal quality
Aggregate R performance
⚠ This is an internal calculation tool, not the official TradingView Strategy Tester.
Its purpose is to help users understand how different settings behave when applied to past data.
7. 1-Day Free Trial
Users may message the author on TradingView to request:
1-day trial access
Ability to test signals in real-time
Compare different SL/RR settings
Verify that the indicator does not repaint
Inspect how the engine behaves on the supported 30-coin dataset
This allows users to evaluate the tool transparently before subscribing.
8. Market Coverage & Deep Backtest Basis This indicator is calibrated on the 30 largest USDT pairs, providing a deep historical dataset with stable liquidity and clearer structural swings. The long backtest range and high signal density help reduce noise and ensure more consistent behavior across different market conditions.
⚠ Disclaimer
This indicator is a quantitative analysis tool created for educational purposes only.
All “optimal settings” are derived from historical market behavior and do not guarantee future performance.
Market conditions change, and every trader must apply independent risk management.
Trading involves risk.
Use responsibly.
Open Interest Z-Score [BackQuant]Open Interest Z-Score
A standardized pressure gauge for futures positioning that turns multi venue open interest into a Z score, so you can see how extreme current positioning is relative to its own history and where leverage is stretched, decompressing, or quietly re loading.
What this is
This indicator builds a single synthetic open interest series by aggregating futures OI across major derivatives venues, then standardises that aggregated OI into a rolling Z score. Instead of looking at raw OI or a simple change, you get a normalized signal that says "how many standard deviations away from normal is positioning right now", with optional smoothing, reference bands, and divergence detection against price.
You can render the Z score in several plotting modes:
Line for a clean, classic oscillator.
Colored line that encodes both sign and momentum of OI Z.
Oscillator histogram that makes impulses and compressions obvious.
The script also includes:
Aggregated open interest across Binance, Bybit, OKX, Bitget, Kraken, HTX, and Deribit, using multiple contract suffixes where applicable.
Choice of OI units, either coin based or converted to USD notional.
Standard deviation reference lines and adaptive extreme bands.
A flexible smoothing layer with multiple moving average types.
Automatic detection of regular and hidden divergences between price and OI Z.
Alerts for zero line and ±2 sigma crosses.
Aggregated open interest source
At the core is the same multi venue OI aggregation engine as in the OI RSI tool, adapted from NoveltyTrade's work and extended for this use case. The indicator:
Anchors on the current chart symbol and its base currency.
Loops over a set of exchanges, gated by user toggles:
Binance.
Bybit.
OKX.
Bitget.
Kraken.
HTX.
Deribit.
For each exchange, loops over several contract suffixes such as USDT.P, USD.P, USDC.P, USD.PM to cover the common perp and margin styles.
Requests OI candles for each exchange plus suffix pair into a small custom OI type that carries open, high, low and close of open interest.
Converts each OI stream into a common unit via the sw method:
In COIN mode, OI is normalized relative to the coin.
In USD mode, OI is scaled by price to approximate notional.
Exchange specific scaling factors are applied where needed to match contract multipliers.
Accumulates all valid OI candles into a single combined OI "candle" by summing open, high, low and close across venues.
The result is oiClose , a synthetic close for aggregated OI that represents cross venue positioning. If there is no valid OI data for the symbol after this process, the script throws a clear runtime error so you know the market is unsupported rather than quietly plotting nonsense.
How the Z score is computed
Once the aggregated OI close is available, the indicator computes a rolling Z score over a configurable lookback:
Define subject as the aggregated OI close.
Compute a rolling mean of this subject with EMA over Z Score Lookback Period .
Compute a rolling standard deviation over the same length.
Subtract the mean from the current OI and divide by the standard deviation.
This gives a raw Z score:
oi_z_raw = (subject − mean) ÷ stdDev .
Instead of plotting this raw value directly, the script passes it through a smoothing layer:
You pick a Smoothing Type and Smoothing Period .
Choices include SMA, HMA, EMA, WMA, DEMA, RMA, linear regression, ALMA, TEMA, and T3.
The helper ma function applies the chosen smoother to the raw Z score.
The result is oi_z , a smoothed Z score of aggregated open interest. A separate EMA with EMA Period is then applied on oi_z to create a signal line ma that can be used for crossovers and trend reads.
Plotting modes
The Plotting Type input controls how this Z score is rendered:
1) Line
In line mode:
The smoothed OI Z score is plotted as a single line using Base Line Color .
The EMA overlay is optionally plotted if Show EMA is enabled.
This is the cleanest view when you want to treat OI Z like a standard oscillator, watching for zero line crosses, swings, and divergences.
2) Colored Line
Colored line mode adds conditional color logic to the Z score:
If the Z score is above zero and rising, it is bright green, representing positive and strengthening positioning pressure.
If the Z score is above zero and falling, it shifts to a cooler cyan, representing positive but weakening pressure.
If the Z score is below zero and falling, it is bright red, representing negative and strengthening pressure (growing net de risking or shorting).
If the Z score is below zero and rising, it is dark red, representing negative but recovering pressure.
This mapping makes it easy to see not only whether OI is above or below its historical mean, but also whether that deviation is intensifying or fading.
3) Oscillator
Oscillator mode turns the Z score into a histogram:
The smoothed Z score is plotted as vertical columns around zero.
Column colors use the same conditional palette as colored line mode, based on sign and change direction.
The histogram base is zero, so bars extend up into positive Z and down into negative Z.
Oscillator mode is useful when you care about impulses in positioning, for example sharp jumps into positive Z that coincide with fast builds in leverage, or deep spikes into negative Z that show aggressive flushes.
4) None
If you only want reference lines, extreme bands, divergences, or alerts without the base oscillator, you can set plotting to None and keep the rest of the tooling active.
The EMA overlay respects plotting mode and only appears when a visible Z score line or histogram is present.
Reference lines and standard deviation levels
The Select Reference Lines input offers two styles:
Standard Deviation Levels
Plots small markers at zero.
Draws thin horizontal lines at +1, +2, −1 and −2 Z.
Acts like a classic Z score ladder, zero as mean, ±1 as normal band, ±2 as outer band.
This mode is ideal if you want a textbook statistical framing, using ±1 and ±2 sigma as standard levels for "normal" versus "extended" positioning.
Extreme Bands
Extreme bands build on the same ±1 and ±2 lines, then add:
Upper outer band between +3 and +4 Z.
Lower outer band between −3 and −4 Z.
Dynamic fill colors inside these bands:
If the Z score is positive, the upper band fill turns red with an alpha that scales with the magnitude of |Z|, capped at a chosen max strength. Stronger deviations towards +4 produce more opaque red fills.
If the Z score is negative, the lower band fill turns green with the same adaptive alpha logic, highlighting deep negative deviations.
Opposite side bands remain a faint neutral white when not in use, so they still provide structural context without shouting.
This creates a visual "danger zone" for position crowding. When the Z score enters these outer bands, open interest is many standard deviations away from its mean and you are dealing with rare but highly loaded positioning states.
Z score as a positioning pressure gauge
Because this is a Z score of aggregated open interest, it measures how unusual current positioning is relative to its own recent history, not just whether OI is rising or falling:
Z near zero means total OI is roughly in line with normal conditions for your lookback window.
Positive Z means OI is above its recent mean. The further above zero, the more "crowded" or extended positioning is.
Negative Z means OI is below its recent mean. Deep negatives often mark post flush environments where leverage has been cleared and the market is under positioned.
The smoothing options help control how much noise you want in the signal:
Short Z score lookback and short smoothing will react quickly, suited for short term traders watching intraday positioning shocks.
Longer Z score lookback with smoother MA types (EMA, RMA, T3) give a slower, more structural view of where the crowd sits over days to weeks.
Divergences between price and OI Z
The indicator includes automatic divergence detection on the Z score versus price, using pivot highs and lows:
You configure Pivot Lookback Left and Pivot Lookback Right to control swing sensitivity.
Pivots are detected on the OI Z series.
For each eligible pivot, the script compares OI Z and price at the last two pivots.
It looks for four patterns:
Regular Bullish – price makes a lower low, OI Z makes a higher low. This can indicate selling exhaustion in positioning even as price washes out. These are marked with a line and a label "ℝ" below the oscillator, in the bullish color.
Hidden Bullish – price makes a higher low, OI Z makes a lower low. This suggests continuation potential where price holds up while positioning resets. Marked with "ℍ" in the bullish color.
Regular Bearish – price makes a higher high, OI Z makes a lower high. This is a classic warning sign of trend exhaustion, where price pushes higher while OI Z fails to confirm. Marked with "ℝ" in the bearish color.
Hidden Bearish – price makes a lower high, OI Z makes a higher high. This is often seen in pullbacks within downtrends, where price retraces but positioning stretches again in the direction of the prevailing move. Marked with "ℍ" in the bearish color.
Each divergence type can be toggled globally via Show Detected Divergences . Internally, the script restricts how far back it will connect pivots, so you do not get stray signals linking very old structures to current bars.
Trading applications
Crowding and squeeze risk
Z scores are a natural way to talk about crowding:
High positive Z in aggregated OI means the market is running high leverage compared to its own norm. If price is also extended, the risk of a squeeze or sharp unwind rises.
Deep negative Z means leverage has been cleaned out. While it can be painful to sit through, this environment often sets up cleaner new trends, since there is less one sided positioning to unwind.
The extreme bands at ±3 to ±4 highlight the rare states where crowding is most intense. You can treat these events as regime markers rather than day to day noise.
Trend confirmation and fade selection
Combine Z score with price and trend:
Bull trends with positive and rising Z are supported by fresh leverage, usually more persistent.
Bull trends with flat or falling Z while price keeps grinding up can be more fragile. Divergences and extreme bands can help identify which edges you do not want to fade and which you might.
In downtrends, deep negative Z that stays pinned can mean persistent de risking. Once the Z score starts to mean revert back toward zero, it can mark the early stages of stabilization.
Event and liquidation context
Around major events, you often see:
Rapid spikes in Z as traders rush to position.
Reversal and overshoot as liquidations and forced de risking clear the book.
A move from positive extremes through zero into negative extremes as the market transitions from crowded to under exposed.
The Z score makes that path obvious, especially in oscillator mode, where you see a block of high positive bars before the crash, then a slab of deep negative bars after the flush.
Settings overview
Z Score group
Plotting Type – None, Line, Colored Line, Oscillator.
Z Score Lookback Period – window used for mean and standard deviation on aggregated OI.
Smoothing Type – SMA, HMA, EMA, WMA, DEMA, RMA, linear regression, ALMA, TEMA or T3.
Smoothing Period – length for the selected moving average on the raw Z score.
Moving Average group
Show EMA – toggle EMA overlay on Z score.
EMA Period – EMA length for the signal line.
EMA Color – color of the EMA line.
Thresholds and Reference Lines group
Select Reference Lines – None, Standard Deviation Levels, Extreme Bands.
Standard deviation lines at 0, ±1, ±2 appear in both modes.
Extreme bands add filled zones at ±3 to ±4 with adaptive opacity tied to |Z|.
Extra Plotting and UI
Base Line Color – default color for the simple line mode.
Line Width – thickness of the oscillator line.
Positive Color – positive or bullish condition color.
Negative Color – negative or bearish condition color.
Divergences group
Show Detected Divergences – master toggle for divergence plotting.
Pivot Lookback Left and Pivot Lookback Right – how many bars left and right to define a pivot, controlling divergence sensitivity.
Open Interest Source group
OI Units – COIN or USD.
Exchange toggles for Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Internally, all enabled exchanges and contract suffixes are aggregated into one synthetic OI series.
Alerts included
The indicator defines alert conditions for several key events:
OI Z Score Positive – Z crosses above zero, aggregated OI moves from below mean to above mean.
OI Z Score Negative – Z crosses below zero, aggregated OI moves from above mean to below mean.
OI Z Score Enters +2σ – Z enters the +2 band and above, marking extended positive positioning.
OI Z Score Enters −2σ – Z enters the −2 band and below, marking extended negative positioning.
Tie these into your strategy to be notified when leverage moves from normal to extended states.
Notes
This indicator does not rely on price based oscillators. It is a statistical lens on cross venue open interest, which makes it a complementary tool rather than a replacement for your existing price or volume signals. Use it to:
Quantify how unusual current futures positioning is compared to recent history.
Identify crowded leverage phases that can fuel squeezes.
Spot structural divergences between price and positioning.
Frame risk and opportunity around events and regime shifts.
It is not a complete trading system. Combine it with your own entries, exits and risk rules to get the most out of what the Z score is telling you about positioning pressure under the hood of the market.
VCAI Volume LiteVCAI Volume Lite is a clean, modern take on volume analysis designed for traders who want a clearer read on participation without loading multiple indicators.
This Lite edition focuses on the essentials:
real activity vs dead sessions
expansion vs contraction
momentum shifts around breakouts and pullbacks
No hype, no filters, no hidden logic — just a straightforward volume tool rebuilt with the VCAI visual framework.
Use it to quickly spot:
stronger moves backed by genuine participation
weak pushes running on low volume
areas where momentum may stall or accelerate
Part of the VCAI Lite Series.
DeM Trend Bias Strength with Alerts (RB Trading)This tool is built to help users understand trend direction, exhaustion, and momentum shifts on the daily timeframe. It highlights when a market is transitioning from weakness to strength or strength to weakness by displaying color-coded bias bars. The script does not forecast future outcomes and should be used as an analytical aid.
Intended Usage
• Timeframe: Daily
• Instruments: Works on most FX pairs and liquid markets
• Style: Trend and bias evaluation
• Purpose: Identify early signs of momentum recovery within ongoing trends
How It Works
Bias Rotation Engine
The script measures directional pressure and smooths it into a bar display that changes color as conditions shift.
• Green bars show rising strength conditions
• Red bars show declining strength conditions
• Transitional periods often appear near market turning points and consolidation zones
This helps users visually separate healthy directional trends from weakening phases.
Trend Alignment Filter
The bars are designed to be interpreted alongside moving averages or broader trend tools. When the bars turn higher while price respects an upward structure, it often supports continuation themes. When the bars weaken during downward phases, it highlights potential areas where the trend retains control.
Identifying Exhaustion and Recovery
Repeated cycles in the bar display can highlight areas where:
• Downside pressure is fading before an upswing
• Upside pressure is fading before a pullback
• Consolidation is forming before a breakout
These transitions tend to align with moments shown in the image where the arrows mark bias shifts occurring before price acceleration.
How to Use It
• Wait for a clear color rotation before making any decisions
• Confirm with the daily trend and price structure
• Avoid using the tool by itself for entries
• Combine with support and resistance, moving averages, and candle structure
• Not intended for scalping or intraday signals
Why Daily Chart Works Best
The daily timeframe smooths out noise and gives the strength bars enough data to reveal genuine trend transitions. Higher timeframes also reduce false rotations that are common in lower timeframes.
Notes
The script does not predict or guarantee price movement. It processes historical inputs to help the user understand directional conditions. Each trader should apply their own risk plan and confirm levels before acting on any idea.
Green to Red Money RailsWhat this indicator does
Green to Red Money Rails (G2R Rails) is a price-action tool that draws dynamic “rails” from recent swing lows and highs. It tracks how support and resistance are shifting so you can see where trend pressure is building or weakening.
Core logic (high level)
Detects pivot lows and stores the last three (L1, L2, L3).
Builds green support “fans”: inner dotted rails L1→L2 and L2→L3, plus a main solid base rail L1→L3.
Detects pivot highs and, when the last high is lower than the previous one, draws a red resistance rail from H2→H3.
Optional labels mark the most recent swing low (“L”) and swing high (“H”).
How to use it
Use the green rails as dynamic support zones for trend-following, pullback entries, or stop placement.
Use the red rail as a visual ceiling in downtrends: breaks above it can signal the end of a sell-off; rejections at it confirm sellers still in control.
Works best on liquid markets and swing-trading timeframes (for example, 1h–1D). Always combine with your own risk management and higher-timeframe context.
This script does not auto-generate signals or manage risk for you; it is a visual framework for reading structure and building your own trading plans.
AI Chakra for Global Markets by Pooja🌐 AI Chakra for Global Markets by Pooja
⚡ Advanced Multi-Signal Trading Framework for Forex & Crypto
AI Chakra is a complete institutional-grade market analysis system, combining
Trend + Structure + Momentum + Volatility + Breakouts + Multi-TF Context + Smart Levels
into a single clean and powerful charting tool.
Designed especially for Forex and Crypto, where speed, precision and clarity matter most.
✨ Key Features
1️⃣ 🎯 Smart Auto Buy/Sell Signal System
Signals appear only when multiple conditions align:
✔️ Buy Sell Signals include:
🟢 Supertrend in bullish zone
💪 RSI momentum in upper strength zone
🔄 CHoCH or BOS supporting upward shift
🚀 Breakout above key levels (Prev-Day High)
⚙️ Optional filters: ADX-Volatility + RSI-MA Protection
✔️ Sell Signals include:
🔴 Supertrend bearish
📉 RSI in weakness zone
🔄 CHoCH/BOS supporting downward structure
🕳️ Breakout below previous-day low
⚙️ Optional filters for momentum validation
📌 Signals are printed as clean labels — visually distinct and easy to interpret.
2️⃣ 🧠 Smart Money Concepts (SMC Suite)
Built-in structural analysis for professional traders:
🔶 CHoCH (Change of Character)
🔷 BOS (Break of Structure)
Every CHoCH/BOS is plotted with:
Horizontal structural level
Precision labels
ATR-adjusted spacing to avoid overlap
Perfect for identifying:
✔️ Trend reversals
✔️ Continuation breaks
✔️ Manipulation zones
✔️ Smart entry areas
3️⃣ 📊 Multi-Timeframe Trend Dashboard (Top-Down View)
A clean institutional-level dashboard across:
1m ▸ 5m ▸ 15m ▸ 30m ▸ 1H ▸ 4H ▸ 1D ▸ 1W ▸ 1M
Each timeframe evaluates:
EMA alignment
VWAP alignment
Supertrend direction
Shows 🔵 Bullish, 🔴 Bearish, ⚪ Neutral
in a visually intuitive format.
4️⃣ 📐 Auto Trendline System + Breakout Detection (Optional Module)
When enabled:
Detects swing highs/lows automatically
Draws dynamic support/resistance trendlines
Uses ATR / Stdev / Linear Regression slopes
Extends lines into future
Marks Breakout events with labels
Ideal for:
✔️ Crypto volatility
✔️ Forex swings
✔️ Breakout traders
✔️ Channel/wedge detection
5️⃣ 🏛️ Institutional Levels – Traditional Pivot Points
Includes complete dynamic Support/Resistance map:
Daily / Weekly / Monthly
Quarterly / Yearly
Multi-Year levels
Adjustable:
Line width
Line color
Price labels (Left/Right)
Works perfectly for:
XAUUSD
GBPJPY
EURUSD
BTCUSDT
NAS100
US30
📌 6. Volatility & Momentum Safety Filters (Optional)
ADX Filter
Allows signals only when volatility/trend strength is acceptable
Avoids signals in low-volatility sideways markets
RSI-MA Filter
Detects fake breakouts
Evaluates RSI displacement & momentum slope
Keeps only reliable directional conditions
These filters help refine signals for Forex (high-flow sessions) and Crypto (high-volatility assets).
📌 7. Previous-Day High/Low Break Detection
A pure price-action breakout feature tuned for global markets:
Detects clean breaks of yesterday’s high (bullish strength)
Detects breaks of yesterday’s low (bearish weakness)
Auto-avoids duplicate prints
Works extremely well in:
XAUUSD
GBPJPY
BTCUSDT
ETHUSDT
Indices like NAS100 or US30
6️⃣ 📡 JSON-Ready Alerts (Webhook Compatible)
Send signals directly to:
Telegram bots
Discord servers
Custom trading bots
Automation platforms
Every Buy/Sell alert includes JSON payload support.
🌍 Optimized for Global Markets
Forex
EURUSD • GBPJPY • XAUUSD • USDJPY • GBPUSD • AUDUSD
Majors, minors, exotics supported.
Crypto
BTC • ETH • SOL • BNB • XRP • Futures & Spot.
Timeframes Supported
Scalping: 1m–15m
Intraday: 30m–4H
Swing: 1D–1W–1M
⚠️ Policy-Safe Disclaimer
This script is a technical analysis tool, not financial advice.
It does not guarantee profits or automate trading decisions.
Always verify signals with your own strategy and risk management.
🌟 Final Summary
AI Chakra unifies:
📈 Trend
🧠 Structure
🎯 Signals
💹 Momentum
🔥 Breakouts
🏛️ Institutional Levels
🧩 Multi-TF Logic
🔐 ACCESS
This version is an Invite-Only Script.
Access is granted manually.
🛡 Support
This is an invite-only indicator.
Approved users may contact the author via the “Author’s Instructions” section on TradingView for help or usage guidance.
CDVI – First Crypto Dominance Volatility Index by Armi GoldmanThe Crypto Dominance Volatility Index (CDVI) is the first volatility-based indicator designed specifically to analyze the stability and instability of dominance flows in the crypto market.
Instead of measuring price volatility, CDVI focuses on the volatility of market dominance itself — a structural driver behind capital rotation cycles such as Bitcoin Season, Altseason, accumulation zones, and macro cycle transitions.
CDVI transforms dominance changes into a clear volatility index that highlights compression, expansion, and regime shifts.
How it works
CDVI calculates the absolute or percentage-based realized volatility of your chosen dominance benchmark (BTC.D, TOTAL.D, or any dominance index available on TradingView).
The indicator then:
1. Smooths the volatility curve using adjustable parameters
2. Builds a long-term mean to identify regime structure
3. Computes percentile zones over a rolling lookback window
4. Highlights high-risk and low-risk dominance conditions using color-coded backgrounds
This creates a clean, noise-reduced volatility representation of the dominance market.
Why it looks like this
The CDVI curve is intentionally smooth and cyclical because dominance volatility behaves differently from price volatility:
• Dominance tends to trend slowly, then spike violently during rotation phases
• Periods of prolonged compression often occur before large macro moves
• Volatility bursts cluster during transitions (e.g. BTC → Alts, cycle tops, market-wide repricing)
The percentile zones (90% / 10%) give structural thresholds for extreme conditions.
Background color reveals when dominance volatility enters these extremes, creating visually clear “regime blocks.”
How to interpret CDVI
High CDVI (above the 90th percentile):
• Dominance instability
• Capital rotation phases are active
• Market is repricing sector allocations
• Often appears near Altseason tops or bottoms
• Signals caution for trend traders and opportunity for rotation traders
Low CDVI (below the 10th percentile):
• Compression and calm dominance
• Accumulation and structural balance
• Often precedes major expansions in Bitcoin or Alt markets
• Useful for anticipating cycle transitions before they break out
Long-term mean:
• Helps identify when the market is in a high-vol or low-vol regime
• Crossings around the mean often coincide with early cycle shifts
How to use CDVI in practice
1. Cycle Timing
Use CDVI to detect when the market moves from calm → expansion or expansion → exhaustion.
Low CDVI usually precedes major moves. High CDVI often marks transition turbulence.
2. BTC vs Altcoins Rotation
Combine CDVI with BTC.D / TOTAL2 / TOTAL3 to detect rotation windows.
High CDVI = dominance is unstable → rotations happen.
Low CDVI = dominance is stable → trending environment.
3. Risk Management
High CDVI suggests elevated structural risk (dominance shifting).
Low CDVI supports directional conviction.
4. Confluence with Price
When both price volatility and dominance volatility expand together → macro transition.
When price is volatile but CDVI is flat → noise, not structural change.
Who this indicator is for
• Cycle analysts
• Macro crypto traders
• BTC vs Alts rotation traders
• Portfolio allocators
• Long-term investors looking at structural market phases
CDVI is designed as a clean, structural tool for understanding volatility not of price — but of market power distribution.
Dumb Money Flow - Retail Panic & FOMO# Dumb Money Flow (DMF) - Retail Panic & FOMO
## 🌊 Overview
**Dumb Money Flow (DMF)** is a powerful **contrarian indicator** designed to track the emotional state of the retail "herd." It identifies moments of extreme **Panic** (irrational selling) and **FOMO** (irrational buying) by analyzing on-chain data, volume anomalies, and price velocity.
In crypto markets, retail traders often buy the top (FOMO) and sell the bottom (Panic). This indicator helps you do the opposite: **Buy when the herd is fearful, and Sell when the herd is greedy.**
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## 🧠 How It Works
The indicator combines multiple data points into a single **Sentiment Index** (0-100), normalized over a 90-day period to ensure it always uses the full range of the chart.
### 1. Panic Index (Bearish Sentiment)
Tracks signs of capitulation and fear. High values contribute to the **Panic Zone**.
* **Exchange Inflows:** Spikes in funds moving to exchanges (preparing to sell).
* **Volume Spikes:** High volume during price drops (panic selling).
* **Price Crash (ROC):** Rapid, emotional price drops over 3 days.
* **Volatility (ATR):** High market nervousness and instability.
### 2. FOMO Index (Bullish Sentiment)
Tracks signs of euphoria and greed. High values contribute to the **FOMO Zone**.
* **Exchange Outflows:** Funds moving to cold storage (HODLing/Greed).
* **Profitable Addresses:** When >90% of holders are in profit, tops often form.
* **Parabolic Rise:** Rapid, unsustainable price increases.
---
## 🎨 Visual Guide
The indicator uses a distinct color scheme to highlight extremes:
* **🟢 Dark Green Zone (> 80): Extreme FOMO**
* **Meaning:** The crowd is euphoric. Risk of a correction is high.
* **Action:** Consider taking profits or looking for short entries.
* **🔴 Dark Burgundy Zone (< 20): Extreme Panic**
* **Meaning:** The crowd is capitulating. Prices may be oversold.
* **Action:** Look for buying opportunities (catching the knife with confirmation).
* **🔵 Light Blue Line:**
* The smoothed moving average of the sentiment, helpful for seeing the trend direction.
---
## 🛠️ How to Use (Trading Strategies)
### 1. Contrarian Reversals (The Primary Strategy)
* **Buy Signal:** Wait for the line to drop deep into the **Burgundy Panic Zone (< 20)** and then start curling up. This indicates that the worst of the selling pressure is over.
* **Sell Signal:** Wait for the line to spike into the **Green FOMO Zone (> 80)** and then start curling down. This suggests buying exhaustion.
### 2. Divergences
* **Bullish Divergence:** Price makes a **Lower Low**, but the DMF Indicator makes a **Higher Low** (less panic on the second drop). This is a strong reversal signal.
* **Bearish Divergence:** Price makes a **Higher High**, but the DMF Indicator makes a **Lower High** (less FOMO/buying power on the second peak).
### 3. Trend Confirmation (Midline Cross)
* **Crossing 50 Up:** Sentiment is shifting from Fear to Greed (Bullish).
* **Crossing 50 Down:** Sentiment is shifting from Greed to Fear (Bearish).
---
## ⚙️ Settings
* **Data Source:** Defaults to `INTOTHEBLOCK` for on-chain data.
* **Crypto Asset:** Auto-detects BTC/ETH, but can be forced.
* **Normalization Period:** Default 90 days. Determines the "window" for defining what is considered "Extreme" relative to recent history.
* **Weights:** You can customize how much each factor (Volume, Inflows, Price) contributes to the index.
---
**Disclaimer:** This indicator is for educational purposes only. "Dumb Money" analysis is a probability tool, not a crystal ball. Always manage your risk.
**Indicator by:** @iCD_creator
**Version:** 1.0
**Pine Script™ Version:** 6
---
## Updates & Support
For questions, suggestions, or bug reports, please comment below or message the author.
**Like this indicator? Leave a 👍 and share your feedback!**
Alos Volume Profile Candles (SVP)ALOS Volume Profile Candles (SVP)
Summary
IMPORTANT: This indicator is designed to be used only with TradingView's 'Session Volume Profile' chart type. It will not work correctly with standard candle charts.
This indicator powerfully visualizes intra-session price action by dividing a single session profile into a specific number of equal-sized synthetic candles.
Instead of viewing a session as one single block, you can now break it down into parts (like quarters or thirds) to see how price behaved during each segment of the profile.
Key Features
Custom Session Slicing: Set "Candles per session" to 4 to see the session in quarters, 6 to see it in sixths, or any number you choose.
Full Session Control: Works perfectly with any custom session time, including complex overnight sessions (like '1800-1700' for CME crypto futures)
Accurate OHLC Calculation: Each synthetic candle correctly calculates and displays its own Open, High, Low, and Close for its specific time slice.
Clean Charting: Use the "Keep last sessions" input to control how many old sessions are drawn, preventing chart clutter and keeping your analysis focused on recent price action.
How to Use
On your TradingView chart, change the chart type to "Session Volume Profile".
Add the "ALOS Volume Profile Candles (SVP)" indicator to your chart.
Set your desired Session time in the indicator settings (or keep the default).
Choose the number of Candles per session you want to divide it into.
Adjust Keep last sessions to control how much history is displayed.
This tool is ideal for traders who want to analyze price behavior during the opening, middle, and closing parts of a session, or for breaking down long 24-hour crypto sessions into more manageable chunks.
Smart Money Flow - Exchange & TVL Composite# Smart Money Flow - Exchange & TVL Composite Indicator
## Overview
The **Smart Money Flow (SMF)** indicator combines two powerful on-chain metrics - **Exchange Flows** and **Total Value Locked (TVL)** - to create a composite index that tracks institutional and "smart money" movement in the cryptocurrency market. This indicator helps traders identify accumulation and distribution phases by analyzing where capital is flowing.
## What It Does
This indicator normalizes and combines:
- **Exchange Net Flow** (from IntoTheBlock): Tracks Bitcoin/Ethereum movement to and from exchanges
- **Total Value Locked** (from DefiLlama): Measures capital locked in DeFi protocols
The composite index is displayed on a 0-100 scale with clear zones for overbought/oversold conditions.
## Core Concept
### Exchange Flows
- **Negative Flow (Outflows)** = Bullish Signal
- Coins moving OFF exchanges → Long-term holding/accumulation
- Indicates reduced selling pressure
- **Positive Flow (Inflows)** = Bearish Signal
- Coins moving TO exchanges → Preparation for selling
- Indicates potential distribution phase
### Total Value Locked (TVL)
- **Rising TVL** = Bullish Signal
- Capital flowing into DeFi protocols
- Increased ecosystem confidence
- **Falling TVL** = Bearish Signal
- Capital exiting DeFi protocols
- Decreased ecosystem confidence
### Combined Signals
**🟢 Strong Bullish (70-100):**
- Exchange outflows + Rising TVL
- Smart money accumulating and deploying capital
**🔴 Strong Bearish (0-30):**
- Exchange inflows + Falling TVL
- Smart money preparing to sell and exiting positions
**⚪ Neutral (40-60):**
- Mixed or balanced flows
## Key Features
### ✅ Auto-Detection
- Automatically detects chart symbol (BTC/ETH)
- Uses appropriate exchange flow data for each asset
### ✅ Weighted Composite
- Customizable weights for Exchange Flow and TVL components
- Default: 50/50 balance
### ✅ Normalized Scale
- 0-100 index scale
- Configurable lookback period for normalization (default: 90 days)
### ✅ Signal Zones
- **Overbought**: 70+ (Strong bullish pressure)
- **Oversold**: 30- (Strong bearish pressure)
- **Extreme**: 85+ / 15- (Very strong signals)
### ✅ Clean Interface
- Minimal visual clutter by default
- Only main index line and MA visible
- Optional elements can be enabled:
- Background color zones
- Divergence signals
- Trend change markers
- Info table with detailed metrics
### ✅ Divergence Detection
- Identifies when price diverges from smart money flows
- Potential reversal warning signals
### ✅ Alerts
- Extreme overbought/oversold conditions
- Trend changes (crossing 50 line)
- Bullish/bearish divergences
## How to Use
### 1. Trend Confirmation
- Index above 50 = Bullish trend
- Index below 50 = Bearish trend
- Use with price action for confirmation
### 2. Reversal Signals
- **Extreme readings** (>85 or <15) suggest potential reversal
- Look for divergences between price and indicator
### 3. Accumulation/Distribution
- **70+**: Accumulation phase - smart money buying/holding
- **30-**: Distribution phase - smart money selling
### 4. DeFi Health
- Monitor TVL component for DeFi ecosystem strength
- Combine with exchange flows for complete picture
## Settings
### Data Sources
- **Exchange Flow**: IntoTheBlock real-time data
- **TVL**: DefiLlama aggregated DeFi TVL
- **Manual Mode**: For testing or custom data
### Indicator Settings
- **Smoothing Period (MA)**: Default 14 periods
- **Normalization Lookback**: Default 90 days
- **Exchange Flow Weight**: Adjustable 0-100%
- **Overbought/Oversold Levels**: Customizable thresholds
### Visual Options
- Show/Hide Moving Average
- Show/Hide Zone Lines
- Show/Hide Background Colors
- Show/Hide Divergence Signals
- Show/Hide Trend Markers
- Show/Hide Info Table
## Data Requirements
⚠️ **Important Notes:**
- Uses **daily data** from IntoTheBlock and DefiLlama
- Works on any chart timeframe (data updates daily)
- Auto-switches between BTC and ETH based on chart
- All other crypto charts default to BTC exchange flow data
## Best Practices
1. **Use on Daily+ Timeframes**
- On-chain data is daily, most effective on D/W/M charts
2. **Combine with Price Action**
- Use as confirmation, not standalone signals
3. **Watch for Divergences**
- Price making new highs while indicator falling = warning
4. **Monitor Extreme Zones**
- Sustained readings >85 or <15 indicate strong conviction
5. **Context Matters**
- Consider broader market conditions and fundamentals
## Calculation
1. **Exchange Net Flow** = Inflows - Outflows (inverted for index)
2. **TVL Rate of Change** = % change over smoothing period
3. **Normalize** both metrics to 0-100 scale
4. **Composite Index** = (ExchangeFlow × Weight) + (TVL × Weight)
5. **Smooth** with moving average
## Disclaimer
This indicator uses on-chain data for analysis. While valuable, it should not be used as the sole basis for trading decisions. Always combine with other technical analysis tools, fundamental analysis, and proper risk management.
On-chain data reflects blockchain activity but may lag price action. Use this indicator as part of a comprehensive trading strategy.
---
## Credits
**Data Sources:**
- IntoTheBlock: Exchange flow metrics
- DefiLlama: Total Value Locked data
**Indicator by:** @iCD_creator
**Version:** 1.0
**Pine Script™ Version:** 6
---
## Updates & Support
For questions, suggestions, or bug reports, please comment below or message the author.
**Like this indicator? Leave a 👍 and share your feedback!**
OTT Volatility [RunRox]📊 OTT Volatility is an indicator developed by the RunRox team to pinpoint the most optimal time to trade across different markets.
OTT stands for Optimal Trade Time Volatility and is designed primarily for markets without a fixed trading session, such as cryptocurrencies that trade 24/7. At the same time, it works equally well on any other market.
🔶 The concept is straightforward. The indicator takes a specified number of historical periods (Samples) and statistically evaluates which hours of the day or which days show the highest volatility for the selected asset.
As a result, it highlights time windows with elevated volatility where traders can focus on searching for trade setups and building positions.
🔶 As the core volatility metric, the indicator uses ATR (Average True Range) to measure intraday volatility. Then it calculates the average ATR value over the last N Samples, creating a statistically stable estimate of typical volatility for the selected asset.
🔶 Statistically, during these highlighted periods the market shows higher-than-average volatility.
This means that in these time windows price is more likely to be subject to stronger moves and potential manipulation, making them attractive for active trade execution and position management.
⚠️ However, historical behavior does not guarantee future results.
These periods should be treated only as zones where volatility has a higher probability of being above normal, not as a promise of movement.
As shown in the screenshot above, the indicator also projects potential future volatility based on historical data. This helps you better plan your trading hours and align your activity with periods where volatility is statistically expected to be higher or lower.
🔶 Current Volatility – as shown in the screenshot above, you can also monitor the real-time volatility of the market without any statistical averaging.
On top of that, you can overlay the current volatility on top of the statistical volatility levels, which makes it easy to see whether the market is now trading in a high- or low-volatility regime relative to its usual behavior.
4 display modes – you can choose any visualization style that fits your trading workflow:
Absolute – displays the raw volatility values.
Relative – shows volatility relative to its typical levels.
Average Centered – centers volatility around its average value.
Trim Low Value – filters out low-volatility noise and highlights only more significant moves.
This indicator helps you define the most effective trading hours on any market by relying on historical volatility statistics.
Use it to quickly see when your market tends to be more active and to structure your trading sessions around those periods.
✅ We hope this tool becomes a useful part of your trading toolkit and helps you improve the quality of your decisions and timing.
BTC Future CME Cross-Market DetectorProject Spec: BTC CME Cross-Market Detector
1. Project Overview
Indicator Name
CME Cross-Market Detector
Objective
To identify high-probability trade setups by detecting and confirming "smart money" activity across two distinct market venues simultaneously: a primary crypto exchange (e.g., Bybit, Binance) and the institutional CME futures market.
Core Philosophy
Price movements are often preceded by the positioning of large, institutional players ("smart money"). While their activity can be seen on any single exchange, the signal becomes exceptionally reliable when the same footprint appears at the same time in both the broader crypto derivatives market and the highly regulated institutional futures market. This dual-market confirmation acts as a powerful noise filter, isolating signals that have a higher probability of follow-through.
2. Key Concepts & Signal Logic
The indicator's entire foundation rests on confirming that specific conditions are met on two datasets at the same time: (1) The user's current chart (e.g., BYBIT:BTCUSDT) and (2) The CME Bitcoin Futures chart (CME:BTC1!).
Smart Volume Analysis
To gauge buying vs. selling pressure, the total volume of a single candle is algorithmically split. This is not a perfect science but an effective estimation based on the candle's structure.
Buying Pressure is considered proportional to the distance the price closed from the low. Buying Pressure ≈ Total Volume × ((Close - Low) / (High - Low))
Selling Pressure is considered proportional to the distance the price closed from the high. Selling Pressure ≈ Total Volume × ((High - Close) / (High - Low))
Signal Trigger Conditions
For a potential signal to be identified on each market independently, two conditions must be met:
Volume Spike: The volume of the current candle must be significantly higher than the recent average volume (e.g., >150% of the 20-period moving average). This shows a sudden, high level of interest.
Pressure Imbalance: The estimated buying pressure must overwhelm the selling pressure by a certain factor (e.g., 3x), or vice versa for a sell signal. This indicates a clear directional intent.
The Final Confirmed Signal
A signal is only considered valid and plotted on the chart when the Signal Trigger Conditions (both Volume Spike and Pressure Imbalance) are met on both the primary chart and the CME chart on the very same candle.
3. Signal Strength Calculation
The percentage shown on the chart is a Signal Strength Score (0-100%), which rates the quality and conviction of the confirmed signal.
The score is calculated as follows:
Base Score Calculation (0-100 points): A base score is calculated for each market (primary and CME) by combining two factors:
Volume Component (0-50 pts): Measures the intensity of the volume spike. A 300% volume spike will score higher than a 150% spike.
Imbalance Component (0-50 pts): Measures the intensity of the buy/sell pressure ratio. A 5x imbalance will score higher than a 3x imbalance.
Advanced Modifiers (Bonus Points): The base score is then enhanced with bonus points for favorable conditions:
Trend Alignment (+10 pts): A buy signal that occurs during a clear uptrend receives extra points.
Candle Structure (+10 pts): A buy signal on a candle with a long lower wick (indicating rejection of lower prices) receives extra points.
Final Averaged Score: The final percentage you see is the average of the two individual strength scores calculated for the primary exchange and the CME market.
4. Visualization
Energy Waves: Signals are displayed as circles. Green for Buy Signals (below the candle) and Red for Sell Signals (above the candle).
Dynamic Sizing: The size of the circle directly reflects the Signal Strength Score, categorized into four distinct levels (e.g., 10%+, 40%+, 60%+, and 80%+) for at-a-glance interpretation.
Percentage Labels: Each signal is plotted with its precise, final strength score for clear analysis.
5. Summary: Steps to Replicate the Logic
To recreate this indicator, follow these high-level steps for each candle on the chart:
Gather Data: Fetch the Open, High, Low, Close, and Volume data for the primary chart asset AND for the corresponding CME Bitcoin Futures symbol (CME:BTC1!).
Calculate Buy/Sell Pressure: For both datasets, use the "Smart Volume Analysis" formula to estimate the buying and selling pressure for the current candle.
Check for Volume Spikes: For both datasets, calculate a simple moving average of the volume. Check if the current candle's volume exceeds this average by a set threshold (e.g., 150%).
Check for Pressure Imbalance: For both datasets, check if the buying pressure is greater than the selling pressure by a set multiplier (e.g., 3.0), or vice versa.
Confirm the Signal: A final signal is only valid if the conditions from both Step 3 and Step 4 are true for both datasets on the same candle.
Calculate Strength: If a signal is confirmed, compute a strength score (0-100) for each dataset based on the intensity of the volume spike and pressure imbalance. Add bonus points for confluence factors like trend alignment.
Finalize and Plot: Average the two strength scores from each market. Plot a colored, sized circle on the chart that visually represents this final averaged score, and display the score as a text label.
Last but not least, the idea of the indicator is inspired by 52SIGNAL
Scaling_mastery:Free TrendlinesScaling_mastery Trendlines is a clean, trading-ready smart trendline tool built for the Scaling_mastery community.
It automatically finds swing highs/lows and draws dynamic trendlines or channels that stay locked to price, on any symbol and any timeframe.
🔧 Modes
Trendline type
Wicks – classic trendlines anchored on candle wicks (high/low).
Bodies – trendlines anchored on candle bodies (open/close), great for closing structure.
Channel – 3-line channel:
outer lines form a band around price
middle line runs through the centre of the channel
thickness is adjustable (Small / Medium / Large).
Trend strength
Controls how strong the pivots must be to form a line.
Weak → more lines, reacts faster.
Medium → balanced, good for most pairs.
Strong → only the cleanest swings, higher-probability trendlines.
🎨 Visual controls
Max support / resistance lines – cap how many lines are kept on chart.
Show broken lines – hide broken trendlines or keep them for structure history.
Extend lines – None / Right / Both.
Support / Resistance colors – separate colors for active vs broken.
Channel thickness – Small / Medium / Large (0.5% / 1% / 2% of price).
Channel outer lines – color for channel edges.
Channel middle line – color + style (dotted / dashed / solid).
Broken lines are automatically faded + dotted, so you can instantly see what’s still respected and what’s already been taken out.
🧠 How to use
Add the indicator to any chart.
Start with:
Trendline type: Wicks
Trend strength: Strong
Max lines: 1–2 for both support & resistance
Once you like the behavior, experiment with:
Switching between Wicks / Bodies / Channel
Adjusting Channel thickness and Trend strength
Use the lines as a visual confluence tool with your own strategy:
HTF trend direction
LTF entries / retests
Liquidity grabs around broken lines
This script doesn’t generate entries or risk management – it’s designed to give you clean, reliable structure so you can execute your own edge.
⚠️ Disclaimer
This tool is for educational and visual purposes only and is not financial advice.
Always do your own research and manage risk.
