ATR Stop BufferThe ATR Stop Buffer indicator calculates the Daily Average True Range (ATR) and converts it into ticks based on the symbol's minimum price movement. It then displays the full ATR, 2% of ATR, and 10% of ATR in a clean table format, rounded up for simplicity. This tool is ideal for traders who want to set volatility-based stop-loss levels or buffers for their trades.
Key Features:
- Uses a 14-period Daily ATR for robust volatility measurement.
- Converts ATR into ticks for precise application across different instruments.
- Table display with toggle option for flexibility.
- Perfect for risk management and trade planning.
How to Use:
1. Add the indicator to your chart.
2. Use the table values to adjust your stop-loss distances (e.g., 2% ATR for tight stops, 10% ATR for wider buffers).
3. Toggle the table off if you only need the values occasionally.
Note: Works best on instruments with defined tick sizes (e.g., futures, forex, stocks).
Cari dalam skrip untuk "Table"
Buy/Sell Volume ComparisonKey improvements:
Direct volume comparison: Now shows the current day's volume and previous day's volume side by side
Percentage change display: Clear percentage change with up/down arrows
Table position customization: Added a dropdown menu to select where you want the table to appear
To adjust the table position:
Click on the settings (gear icon) for the indicator after adding it to your chart
You'll see a dropdown menu labeled "Table Position"
Select from options like "Top Right", "Bottom Left", etc.
Click "OK" to apply your changes
This version also handles the case where there's no previous volume data (first bar of the chart) by checking for NA values.
Let me know if this meets your requirements, or if you'd like any other adjustments!RetryClaude does not have the ability to run the code it generates yet.Claude can make mistakes. Please double-check responses.Tip: Long chats cause you to reach your usage limits faster.
Correlation Heatmap█ OVERVIEW
This indicator creates a correlation matrix for a user-specified list of symbols based on their time-aligned weekly or monthly price returns. It calculates the Pearson correlation coefficient for each possible symbol pair, and it displays the results in a symmetric table with heatmap-colored cells. This format provides an intuitive view of the linear relationships between various symbols' price movements over a specific time range.
█ CONCEPTS
Correlation
Correlation typically refers to an observable statistical relationship between two datasets. In a financial time series context, it usually represents the extent to which sampled values from a pair of datasets, such as two series of price returns, vary jointly over time. More specifically, in this context, correlation describes the strength and direction of the relationship between the samples from both series.
If two separate time series tend to rise and fall together proportionally, they might be highly correlated. Likewise, if the series often vary in opposite directions, they might have a strong anticorrelation . If the two series do not exhibit a clear relationship, they might be uncorrelated .
Traders frequently analyze asset correlations to help optimize portfolios, assess market behaviors, identify potential risks, and support trading decisions. For instance, correlation often plays a key role in diversification . When two instruments exhibit a strong correlation in their returns, it might indicate that buying or selling both carries elevated unsystematic risk . Therefore, traders often aim to create balanced portfolios of relatively uncorrelated or anticorrelated assets to help promote investment diversity and potentially offset some of the risks.
When using correlation analysis to support investment decisions, it is crucial to understand the following caveats:
• Correlation does not imply causation . Two assets might vary jointly over an analyzed range, resulting in high correlation or anticorrelation in their returns, but that does not indicate that either instrument directly influences the other. Joint variability between assets might occur because of shared sensitivities to external factors, such as interest rates or global sentiment, or it might be entirely coincidental. In other words, correlation does not provide sufficient information to identify cause-and-effect relationships.
• Correlation does not predict the future relationship between two assets. It only reflects the estimated strength and direction of the relationship between the current analyzed samples. Financial time series are ever-changing. A strong trend between two assets can weaken or reverse in the future.
Correlation coefficient
A correlation coefficient is a numeric measure of correlation. Several coefficients exist, each quantifying different types of relationships between two datasets. The most common and widely known measure is the Pearson product-moment correlation coefficient , also known as the Pearson correlation coefficient or Pearson's r . Usually, when the term "correlation coefficient" is used without context, it refers to this correlation measure.
The Pearson correlation coefficient quantifies the strength and direction of the linear relationship between two variables. In other words, it indicates how consistently variables' values move together or in opposite directions in a proportional, linear manner. Its formula is as follows:
𝑟(𝑥, 𝑦) = cov(𝑥, 𝑦) / (𝜎𝑥 * 𝜎𝑦)
Where:
• 𝑥 is the first variable, and 𝑦 is the second variable.
• cov(𝑥, 𝑦) is the covariance between 𝑥 and 𝑦.
• 𝜎𝑥 is the standard deviation of 𝑥.
• 𝜎𝑦 is the standard deviation of 𝑦.
In essence, the correlation coefficient measures the covariance between two variables, normalized by the product of their standard deviations. The coefficient's value ranges from -1 to 1, allowing a more straightforward interpretation of the relationship between two datasets than what covariance alone provides:
• A value of 1 indicates a perfect positive correlation over the analyzed sample. As one variable's value changes, the other variable's value changes proportionally in the same direction .
• A value of -1 indicates a perfect negative correlation (anticorrelation). As one variable's value increases, the other variable's value decreases proportionally.
• A value of 0 indicates no linear relationship between the variables over the analyzed sample.
Aligning returns across instruments
In a financial time series, each data point (i.e., bar) in a sample represents information collected in periodic intervals. For instance, on a "1D" chart, bars form at specific times as successive days elapse.
However, the times of the data points for a symbol's standard dataset depend on its active sessions , and sessions vary across instrument types. For example, the daily session for NYSE stocks is 09:30 - 16:00 UTC-4/-5 on weekdays, Forex instruments have 24-hour sessions that span from 17:00 UTC-4/-5 on one weekday to 17:00 on the next, and new daily sessions for cryptocurrencies start at 00:00 UTC every day because crypto markets are consistently open.
Therefore, comparing the standard datasets for different asset types to identify correlations presents a challenge. If two symbols' datasets have bars that form at unaligned times, their correlation coefficient does not accurately describe their relationship. When calculating correlations between the returns for two assets, both datasets must maintain consistent time alignment in their values and cover identical ranges for meaningful results.
To address the issue of time alignment across instruments, this indicator requests confirmed weekly or monthly data from spread tickers constructed from the chart's ticker and another specified ticker. The datasets for spreads are derived from lower-timeframe data to ensure the values from all symbols come from aligned points in time, allowing a fair comparison between different instrument types. Additionally, each spread ticker ID includes necessary modifiers, such as extended hours and adjustments.
In this indicator, we use the following process to retrieve time-aligned returns for correlation calculations:
1. Request the current and previous prices from a spread representing the sum of the chart symbol and another symbol ( "chartSymbol + anotherSymbol" ).
2. Request the prices from another spread representing the difference between the two symbols ( "chartSymbol - anotherSymbol" ).
3. Calculate half of the difference between the values from both spreads ( 0.5 * (requestedSum - requestedDifference) ). The results represent the symbol's prices at times aligned with the sample points on the current chart.
4. Calculate the arithmetic return of the retrieved prices: (currentPrice - previousPrice) / previousPrice
5. Repeat steps 1-4 for each symbol requiring analysis.
It's crucial to note that because this process retrieves prices for a symbol at times consistent with periodic points on the current chart, the values can represent prices from before or after the closing time of the symbol's usual session.
Additionally, note that the maximum number of weeks or months in the correlation calculations depends on the chart's range and the largest time range common to all the requested symbols. To maximize the amount of data available for the calculations, we recommend setting the chart to use a daily or higher timeframe and specifying a chart symbol that covers a sufficient time range for your needs.
█ FEATURES
This indicator analyzes the correlations between several pairs of user-specified symbols to provide a structured, intuitive view of the relationships in their returns. Below are the indicator's key features:
Requesting a list of securities
The "Symbol list" text box in the indicator's "Settings/Inputs" tab accepts a comma-separated list of symbols or ticker identifiers with optional spaces (e.g., "XOM, MSFT, BITSTAMP:BTCUSD"). The indicator dynamically requests returns for each symbol in the list, then calculates the correlation between each pair of return series for its heatmap display.
Each item in the list must represent a valid symbol or ticker ID. If the list includes an invalid symbol, the script raises a runtime error.
To specify a broker/exchange for a symbol, include its name as a prefix with a colon in the "EXCHANGE:SYMBOL" format. If a symbol in the list does not specify an exchange prefix, the indicator selects the most commonly used exchange when requesting the data.
Note that the number of symbols allowed in the list depends on the user's plan. Users with non-professional plans can compare up to 20 symbols with this indicator, and users with professional plans can compare up to 32 symbols.
Timeframe and data length selection
The "Returns timeframe" input specifies whether the indicator uses weekly or monthly returns in its calculations. By default, its value is "1M", meaning the indicator analyzes monthly returns. Note that this script requires a chart timeframe lower than or equal to "1M". If the chart uses a higher timeframe, it causes a runtime error.
To customize the length of the data used in the correlation calculations, use the "Max periods" input. When enabled, the indicator limits the calculation window to the number of periods specified in the input field. Otherwise, it uses the chart's time range as the limit. The top-left corner of the table shows the number of confirmed weeks or months used in the calculations.
It's important to note that the number of confirmed periods in the correlation calculations is limited to the largest time range common to all the requested datasets, because a meaningful correlation matrix requires analyzing each symbol's returns under the same market conditions. Therefore, the correlation matrix can show different results for the same symbol pair if another listed symbol restricts the aligned data to a shorter time range.
Heatmap display
This indicator displays the correlations for each symbol pair in a heatmap-styled table representing a symmetric correlation matrix. Each row and column corresponds to a specific symbol, and the cells at their intersections correspond to symbol pairs . For example, the cell at the "AAPL" row and "MSFT" column shows the weekly or monthly correlation between those two symbols' returns. Likewise, the cell at the "MSFT" row and "AAPL" column shows the same value.
Note that the main diagonal cells in the display, where the row and column refer to the same symbol, all show a value of 1 because any series of non-na data is always perfectly correlated with itself.
The background of each correlation cell uses a gradient color based on the correlation value. By default, the gradient uses blue hues for positive correlation, orange hues for negative correlation, and white for no correlation. The intensity of each blue or orange hue corresponds to the strength of the measured correlation or anticorrelation. Users can customize the gradient's base colors using the inputs in the "Color gradient" section of the "Settings/Inputs" tab.
█ FOR Pine Script® CODERS
• This script uses the `getArrayFromString()` function from our ValueAtTime library to process the input list of symbols. The function splits the "string" value by its commas, then constructs an array of non-empty strings without leading or trailing whitespaces. Additionally, it uses the str.upper() function to convert each symbol's characters to uppercase.
• The script's `getAlignedReturns()` function requests time-aligned prices with two request.security() calls that use spread tickers based on the chart's symbol and another symbol. Then, it calculates the arithmetic return using the `changePercent()` function from the ta library. The `collectReturns()` function uses `getAlignedReturns()` within a loop and stores the data from each call within a matrix . The script calls the `arrayCorrelation()` function on pairs of rows from the returned matrix to calculate the correlation values.
• For consistency, the `getAlignedReturns()` function includes extended hours and dividend adjustment modifiers in its data requests. Additionally, it includes other settings inherited from the chart's context, such as "settlement-as-close" preferences.
• A Pine script can execute up to 40 or 64 unique `request.*()` function calls, depending on the user's plan. The maximum number of symbols this script compares is half the plan's limit, because `getAlignedReturns()` uses two request.security() calls.
• This script can use the request.security() function within a loop because all scripts in Pine v6 enable dynamic requests by default. Refer to the Dynamic requests section of the Other timeframes and data page to learn more about this feature, and see our v6 migration guide to learn what's new in Pine v6.
• The script's table uses two distinct color.from_gradient() calls in a switch structure to determine the cell colors for positive and negative correlation values. One call calculates the color for values from -1 to 0 based on the first and second input colors, and the other calculates the colors for values from 0 to 1 based on the second and third input colors.
Look first. Then leap.
Multi-Timeframe S/R & Breakout Projection1) What This Script Does
Collects S/R levels from the 15-minute and 1-hour timeframes, using each timeframe’s pivot detection.
Sorts those pivot-based levels by their distance from the current price, so you see the nearest levels first.
Draws up to a user-defined number of those levels as horizontal rays on the current chart.
Checks breakouts at the nearest S/R line (the one with the smallest distance from price):
Real Breakout: price breaks above a level and sustains above it for the specified number of bars.
False Breakout: price breaks above but quickly closes back below within the specified lookback.
On confirmation of a real or false breakout, that S/R line changes color to green if price is going higher, or red if price is going lower.
Displays a small table in the corner with:
Daily Trend: bullish or bearish, using an SMA on a 30-minute timeframe.
Sentiment: bullish or bearish, using RSI on the same 30-minute timeframe.
2) How It Works
Multi-Timeframe Pivot Detection
The script uses request.security() to fetch pivot highs/lows from two higher timeframes (15m and 60m).
It collects up to a user-specified number of these pivots (numRecent) from each TF.
Sorting & Plotting S/R Lines
Once pivot values are gathered, the script calculates their “distance” from current price.
It sorts them so that the S/R lines drawn on your chart are the nearest ones first.
Each line is drawn with a color and style you can customize:
srRayColor sets the overall color (e.g. yellow).
srRayStyleOptions can be Solid, Dashed, or Dotted.
Breakout Determination
After drawing the lines, the script looks at the nearest line and applies two specialized checks (f_isFalseBreakout & f_isRealBreakout):
A real breakout occurs if price closes above (or below) and remains on that side for breakLook bars.
A false breakout occurs if price closes above (or below) but quickly returns.
When a breakout is confirmed, that nearest line changes color to:
Green if price is ultimately going up,
Red if price is going down.
Daily Trend & Sentiment Table
A small table in the bottom-right corner shows:
Daily Trend: uses a 30-minute SMA to see if your price is above/below on that timeframe.
Sentiment: uses the RSI (also on 30m). A value over 50 suggests bullish sentiment; under 50 suggests bearish.
3) How to Use It
Timeframes & Pivots
Choose how many pivots (numRecent) from each TF to fetch (up to 10 total). A higher number means you’ll see more historical S/R lines.
Customize pivotLeft & pivotRight for how “wide” the pivot detection is.
Line Customization
In the script’s Inputs tab, you’ll find:
S/R Rays Color – sets the hue of the lines.
S/R Line Style – pick from Solid, Dashed, or Dotted.
Liquidity Lines Color – color for the smaller pivot lines from your chart timeframe’s pivot detection.
Breakout Lookback
breakLook determines how many bars must confirm or refute the breakout. Adjust it based on how conservative or aggressive you want the breakout detection.
Check the Table
In the bottom-right, watch the script’s “Daily Trend” & “Sentiment”. This can be a quick filter for trades:
“Bullish” daily trend with a bullish sentiment is often more favorable for long trades.
Conversely, “Bearish” daily trend & sentiment can confirm short ideas.
Scenarios
If you see a “Real Breakout” label near the line, the script recolors that line green or red, indicating a possible continuous move.
A “False Breakout” label suggests the price has quickly retraced.
4) Originality & Concepts
Multi-Timeframe Approach: Many S/R indicators fetch only local pivot lines; here, we explicitly gather pivot points from two separate TFs (15m & 60m) and project them onto your lower timeframe chart.
Distance-Based Sorting ensures you only see the nearest lines on the chart, preventing clutter from excessive lines.
Breakout Logic used is straightforward but effective: it checks if price truly holds beyond a level (real breakout) or fails to hold (false breakout).
Line Recoloring provides immediate visual feedback on the success or failure of the breakout.
5) Chart Usage
Plot this script on a relatively low timeframe chart (like the 1m, 5m, or 15m) to see the higher timeframe S/R lines.
Select how many S/R lines you want to show, choose the line style, set your pivot detection parameters, then watch for breakouts.
Tips:
Start with fewer lines (maxLevels=3 or 5) so the chart remains clear.
You can experiment with a small breakLook if you want more immediate breakout signals, or a higher breakLook if you need stronger confirmation.
Enjoy using the “Multi-Timeframe S/R & Breakout Projection” script! It simplifies the manual process of spotting higher timeframe pivot lines and helps you quickly assess potential breakouts or fakes on your intraday charts, all while giving you a snapshot of the higher timeframe’s trend and sentiment.
CISD with Alerts [neo|]█ OVERVIEW
CISD (or Change in State of Delivery) is an ICT concept and reversal pattern which may allow traders to identify reversals or changes in market structure early, compared to using traditional market structure. This script aims to correctly identify, and update these levels and provide alerts, so that traders can take advantage of this concept with ease.
█ CONCEPTS
Simply put, CISD may be identified when price closes above the open of the candle which started the most recent downtrend or liquidity sweep. Generally, it is most powerful when applied to key points in the market as a confirmation from where you may want price to reverse.
For example, when price is in a downtrend, we take the open of the last consecutive downwards candle and observe the CISD once price closes above it, beginning an uptrend.
Examples:
COMEX:GC1!
CME_MINI:NQ1!
█ How to use
To use the indicator, simply apply it to your chart and modify any of your desired inputs.
• Bullish CISD color allows you to change the color of +CISD levels.
• Bearish CISD color allows you to change the color of -CISD levels.
• Line width allows you to modify the width of +-CISD lines.
• Line extension bars allows you to change how far ahead CISD levels are drawn (by default it is 5).
• Keep old CISD levels will allow you to preserve all past CISD levels if you would like to observe the logic.
• Enable stat table will let you add a table on your chart which will tell you the current CISD trend, as well as your ticker and timeframe.
• Table position allows you to customize where the table will appear on your chart.
Zig Zag Trend Metrics“ Zig Zag Trend Metrics ” is a highly versatile indicator, built on the classic Zig Zag concept and thoughtfully designed for technical traders seeking a deeper, more structured view of market dynamics. This tool identifies significant swing highs and lows, classifies them, and annotates each with key metrics, offering a precise snapshot of each movement. It enhances visual analysis by drawing connecting lines that outline the flow of market structure, making trend progression and reversals instantly recognizable. Beyond visual mapping, it features a compact, real-time statistics table that calculates the average price and time deltas for both bullish and bearish swings, giving traders deep insights into trend momentum and rhythm. With extensive customization options, this indicator adapts seamlessly to vast trading styles or chart setups, empowering traders to spot patterns, evaluate trend strength, and make more confident, data-backed decisions.
❖ FEATURES
✦ Automatic Swing Detection
At its core, this indicator automatically identifies swing highs and lows based on a customizable lookback period (default: 10 bars).
✦ Labeling Swing Points
Each swing is visualized with a label that includes:
Swing Classification : “HH” (Higher High), “LH” (Lower High), “LL” (Lower Low), or “HL” (Higher Low).
Price Difference : Displayed in percentage or absolute value from the previous opposite swing.
Time Difference : The number of bars since the previous swing of the opposite type.
These labels offer traders clear, immediate insight into price movements and structural changes.
✦ Visual Lines
The indicator draws three types of lines:
Bullish Lines: Connect recent swing lows to new swing highs, indicating uptrends.
Bearish Lines: Connect recent swing highs to new swing lows, indicating downtrends.
Range Lines: Connect consecutive highs or lows to outline price channels.
Each line type can be color-coded and customized for visibility.
✦ Statistics Table
An on-screen metrics table provides a live summary of trends. Script uses Relative Averaging to smooth price and time changes. This prevents outliers from distorting the data and provides a more reliable sense of typical swing behavior.
Uptrend Metrics: Shows average price and time differences from recent bullish swings.
Downtrend Metrics: Shows the same for bearish swings.
🛠️ Customization Options
Ability to tailor the indicator to suit their strategy and aesthetic preferences:
Swing Period: Adjust sensitivity to short- or long-term swings.
Color Settings: Customize line and label colors.
Label Display: Choose between absolute or percentage price differences.
Table Settings: Modify size, location, or visibility.
This makes the indicator highly flexible and useful across various timeframes and assets.
RSI Pro+ (Bear market, financial crisis and so on EditionIn markets defined by volatility, fear, and uncertainty – the battlegrounds of bear markets and financial crises – you need tools forged in resilience. Introducing RSI Pro+, a strategy built upon a legendary indicator born in 1978, yet engineered with modern visual clarity to remain devastatingly effective even in the chaotic financial landscapes of 3078.
This isn't about complex algorithms predicting the unpredictable. It's about harnessing the raw, time-tested power of the Relative Strength Index (RSI) to identify potential exhaustion points and capitalize on oversold conditions. RSI Pro+ cuts through the noise, providing clear, actionable signals when markets might be poised for a relief bounce or reversal.
Core Technology (The 1978 Engine):
RSI Crossover Entry: The strategy initiates a LONG position when the RSI (default period 11) crosses above a user-defined low threshold (default 30). This classic technique aims to enter when selling pressure may be waning, offering potential entry points during sharp downturns or periods of consolidation after a fall.
Modern Enhancements (The 3078 Cockpit):
RSI Pro+ isn't just about the signal; it's about providing a professional-grade visual experience directly on your chart:
Entry Bar Highlight: A subtle background flash on the chart signals the exact bar where the RSI crossover condition is met, alerting you to potential entry opportunities.
Trade Bar Coloring: Once a trade is active, the price bars are subtly colored, giving you immediate visual confirmation that the strategy is live in the market.
Entry Price Line: A clear, persistent line marks your exact average entry price for the duration of the trade, serving as a crucial visual anchor.
Take Profit Line: Your calculated Take Profit target is plotted as a distinct line, keeping your objective clearly in sight.
Custom Entry Marker: A precise shape (▲) appears below the bar where the trade entry was actually executed, pinpointing the start of the position.
On-Chart Info Table (HUD): A clean, customizable Heads-Up Display appears when a trade is active, showing vital information at a glance:
Entry Price: Your position's average cost basis.
TP Target: The calculated price level for your Take Profit exit.
Current PnL%: Real-time Profit/Loss percentage for the open trade.
Full Customization: Nearly every aspect is configurable via the settings menu:
RSI Period & Crossover Level
Take Profit Percentage
Toggle ALL visual enhancements on/off individually
Position the Info Table wherever you prefer on the chart.
How to Use RSI Pro+:
Add to Chart: Apply the "RSI Pro+ (Bear market...)" strategy to your TradingView chart. Ensure any previous versions are removed.
Access Settings: Click the cogwheel icon (⚙️) next to the strategy name on your chart.
Configure Inputs (Crucial Step):
RSI Crossover Level: This is key. The default (30) targets standard oversold conditions. In severe downturns, you might experiment with lower levels (e.g., 25, 20) or higher ones (e.g., 40) depending on the asset and timeframe. Observe where RSI(11) typically bottoms out on your chart.
Take Profit Percentage (%): Define your desired profit target per trade (e.g., enter 0.5 for 0.5%, 1.0 for 1%). The default is a very small 0.11%.
RSI Period: While default is 11, you can adjust this (e.g., the standard 14).
Visual Enhancements: Enable or disable the visual features (background highlights, bar coloring, lines, markers, table) according to your preference using the checkboxes. Adjust table position.
Observe & Backtest: Watch how the strategy behaves on your chosen asset and timeframe. Use TradingView's Strategy Tester to analyze historical performance based on your settings. No strategy works perfectly everywhere; testing is essential.
Important Considerations:
Risk Management: This specific script version focuses on a Take Profit exit. It does not include an explicit Stop Loss. You MUST manage risk through appropriate position sizing, potentially adding a Stop Loss manually, or by modifying the script.
Oversold ≠ Reversal: An RSI crossover is an indicator of potential exhaustion, not a guarantee of a price reversal.
Fixed TP: A fixed percentage TP ensures small wins but may exit before larger potential moves.
Backtesting Limitations: Past performance does not guarantee future results.
RSI Pro+ strips away complexity to focus on a robust, time-honored principle, enhanced with modern visuals for the discerning trader navigating today's (and tomorrow's) challenging markets
Multi-MA Strategy Analyzer with BacktestMulti-MA Strategy Analyzer with Backtest
This TradingView Pine Script indicator is designed to analyze multiple moving averages (SMA or EMA) dynamically and identify the most profitable one based on historical performance.
Features
Dynamic MA Range:
Specify a minLength, maxLength, and step size.
Automatically calculates up to 20 MAs.
Custom MA Calculation:
Uses custom SMA and EMA implementations to support dynamic length values.
Buy/Sell Logic:
Buy when price crosses above a MA.
Sell when price crosses below.
Supports both long and short trades.
Performance Tracking:
Tracks PnL, number of trades, win rate, average profit, and drawdown.
Maintains individual stats for each MA.
Best MA Detection:
Automatically highlights the best-performing MA.
Optional showBestOnly toggle to focus only on the best line and its stats.
Visualization:
Up to 20 plot() calls (static) for MAs.
Green highlight for the best MA.
Color-coded result table and chart.
Table View
When showBestOnly = false, the table displays all MAs with stats.
When showBestOnly = true, the table displays only the best MA with a summary row.
Includes:
Best MA length
Total PnL
Number of trades
Win rate
Avg PnL per trade
Max Drawdown
Configuration
minLength (default: 10)
maxLength (default: 200)
step (default: 10)
useEMA: Toggle between EMA and SMA
showBestOnly: Focus on best-performing MA only
Notes
MA plotting is static, limited to 20 total.
Table supports highlighting and is optimized for performance.
Script is structured to run efficiently using arrays and simple int where required.
Potential Extensions
Add visual buy/sell arrows
Export stats to CSV
Strategy tester conversion
Custom date range filtering for backtesting
Author: Muhammad Wasim
Version: 1.0
UM Futures Dashboard with Moving Average DirectionUM Futures Dashboard with Moving Average Direction
Description :
This futures dashboard gives you quick glance of all “major” futures prices and percentage changes. The text color and trends are based on your configured moving average type and length. The dashboard will display LONG in green text when the configure MA is trending higher and SHORT in red when the configured MA is trending lower. The dashboard also includes the VIX futures roll yield and VIX futures status of Contango or Backwardation.
I have included the indicator twice on the sample chart to illustrate different table settings. I also included an 8 period WMA overlay on the price chart since this is the default of the dashboard. (The Moving Average color change is another one of my indicators titled “UM EMA SMA WMA HMA with Directional Color Change”)
Defaults and Configuration :
The default MA type is the Weighted Moving Average, (WMA) with a daily setting of 8. Choices include WMA, SMA, and EMA. The table location defaults to the upper right corner in landscape mode. It can also be set to “flip” to portrait mode. I have added the table to the chart twice to illustrate the table orientations.
Table location, orientation, timeframe, moving average type and length are user-configurable. The configured dashboard timeframe is independent of the chart timeframe. Percentage changes and Moving Averages are based on the configured dashboard timeframe.
Alerts :
Alerts can be configured on the directional change of the dashboard moving average. For example, if the daily 8 period weighted moving average begins trending higher it will turn from red to green. This color change would fire a LONG alert. A color trend change of the weighted moving average from green to red would fire a SHORT alert. Alerts are disabled by default but can be set for any or all of the futures contracts included.
Suggested Uses :
If you follow or trade futures, add this dashboard indicator to your chart layout. Configure your favorite moving average. Use this to quickly see where all the major futures are trading. This saved me from thumbing through the CNBC app on my phone.
One thing I do is to “stretch” moving average to a smaller timeframe. For example, if you like the 8 period WMA on the daily, try the 192 WMA on the hourly. ( The daily 8 period WMA is roughly a 192 WMA on an hourly chart) This can smooth out some of the violent price action and give better entries/exits.
Setup a FUTURES indicator template. I do this with the dashboard and couple other of my favorite indicators.
Suggested Settings :
Daily charts: 8 WMA
Buy on 5% dip strategy with time adjustment
This script is a strategy called "Buy on 5% Dip Strategy with Time Adjustment 📉💡," which detects a 5% drop in price and triggers a buy signal 🔔. It also automatically closes the position once the set profit target is reached 💰, and it has additional logic to close the position if the loss exceeds 14% after holding for 230 days ⏳.
Strategy Explanation
Buy Condition: A buy signal is triggered when the price drops 5% from the highest price reached 🔻.
Take Profit: The position is closed when the price hits a 1.22x target from the average entry price 📈.
Forced Sell Condition: If the position is held for more than 230 days and the loss exceeds 14%, the position is automatically closed 🚫.
Leverage & Capital Allocation: Leverage is adjustable ⚖️, and you can set the percentage of capital allocated to each trade 💸.
Time Limits: The strategy allows you to set a start and end time ⏰ for trading, making the strategy active only within that specific period.
Code Credits and References
Credits: This script utilizes ideas and code from @QuantNomad and jangdokang for the profit table and algorithm concepts 🔧.
Sources:
Monthly Performance Table Script by QuantNomad:
ZenAndTheArtOfTrading's Script:
Strategy Performance
This strategy provides risk management through take profit and forced sell conditions and includes a performance table 📊 to track monthly and yearly results. You can compare backtest results with real-time performance to evaluate the strategy's effectiveness.
The performance numbers shown in the backtest reflect what would have happened if you had used this strategy since the launch date of the SOXL (the Direxion Daily Semiconductor Bull 3x Shares ETF) 📅. These results are not hypothetical but based on actual performance from the day of the ETF’s launch 📈.
Caution ⚠️
No Guarantee of Future Results: The results are based on historical performance from the launch of the SOXL ETF, but past performance does not guarantee future results. It’s important to approach with caution when applying it to live trading 🔍.
Risk Management: Leverage and capital allocation settings are crucial for managing risk ⚠️. Make sure to adjust these according to your risk tolerance ⚖️.
Multi-Anchored Linear Regression Channels [TANHEF]█ Overview:
The 'Multi-Anchored Linear Regression Channels ' plots multiple dynamic regression channels (or bands) with unique selectable calculation types for both regression and deviation. It leverages a variety of techniques, customizable anchor sources to determine regression lengths, and user-defined criteria to highlight potential opportunities.
Before getting started, it's worth exploring all sections, but make sure to review the Setup & Configuration section in particular. It covers key parameters like anchor type, regression length, bias, and signal criteria—essential for aligning the tool with your trading strategy.
█ Key Features:
⯁ Multi-Regression Capability:
Plot up to three distinct regression channels and/or bands simultaneously, each with customizable anchor types to define their length.
⯁ Regression & Deviation Methods:
Regressions Types:
Standard: Uses ordinary least squares to compute a simple linear trend by averaging the data and deriving a slope and endpoints over the lookback period.
Ridge: Introduces L2 regularization to stabilize the slope by penalizing large coefficients, which helps mitigate multicollinearity in the data.
Lasso: Uses L1 regularization through soft-thresholding to shrink less important coefficients, yielding a simpler model that highlights key trends.
Elastic Net: Combines L1 and L2 penalties to balance coefficient shrinkage and selection, producing a robust weighted slope that handles redundant predictors.
Huber: Implements the Huber loss with iteratively reweighted least squares (IRLS) and EMA-style weights to reduce the impact of outliers while estimating the slope.
Least Absolute Deviations (LAD): Reduces absolute errors using iteratively reweighted least squares (IRLS), yielding a slope less sensitive to outliers than squared-error methods.
Bayesian Linear: Merges prior beliefs with weighted data through Bayesian updating, balancing the prior slope with data evidence to derive a probabilistic trend.
Deviation Types:
Regressive Linear (Reverse): In reverse order (recent to oldest), compute weighted squared differences between the data and a line defined by a starting value and slope.
Progressive Linear (Forward): In forward order (oldest to recent), compute weighted squared differences between the data and a line defined by a starting value and slope.
Balanced Linear: In forward order (oldest to newest), compute regression, then pair to source data in reverse order (newest to oldest) to compute weighted squared differences.
Mean Absolute: Compute weighted absolute differences between each data point and its regression line value, then aggregate them to yield an average deviation.
Median Absolute: Determine the weighted median of the absolute differences between each data point and its regression line value to capture the central tendency of deviations.
Percent: Compute deviation as a percentage of a base value by multiplying that base by the specified percentage, yielding symmetric positive and negative deviations.
Fitted: Compare a regression line with high and low series values by computing weighted differences to determine the maximum upward and downward deviations.
Average True Range: Iteratively compute the weighted average of absolute differences between the data and its regression line to yield an ATR-style deviation measure.
Bias:
Bias: Applies EMA or inverse-EMA style weighting to both Regression and/or Deviation, emphasizing either recent or older data.
⯁ Customizable Regression Length via Anchors:
Anchor Types:
Fixed: Length.
Bar-Based: Bar Highest/Lowest, Volume Highest/Lowest, Spread Highest/Lowest.
Correlation: R Zero, R Highest, R Lowest, R Absolute.
Slope: Slope Zero, Slope Highest, Slope Lowest, Slope Absolute.
Indicator-Based: Indicators Highest/Lowest (ADX, ATR, BBW, CCI, MACD, RSI, Stoch).
Time-Based: Time (Day, Week, Month, Quarter, Year, Decade, Custom).
Session-Based: Session (Tokyo, London, New York, Sydney, Custom).
Event-Based: Earnings, Dividends, Splits.
External: Input Source Highest/Lowest.
Length Selection:
Maximum: The highest allowed regression length (also fixed value of “Length” anchor).
Minimum: The shortest allowed length, ensuring enough bars for a valid regression.
Step: The sampling interval (e.g., 1 checks every bar, 2 checks every other bar, etc.). Increasing the step reduces the loading time, most applicable to “Slope” and “R” anchors.
Adaptive lookback:
Adaptive Lookback: Enable to display regression regardless of too few historical bars.
⯁ Selecting Bias:
Bias applies separately to regression and deviation.
Positive values emphasize recent data (EMA-style), negative invert, and near-zero maintains balance. (e.g., a length 100, bias +1 gives the newest price ~7× more weight than the oldest).
It's best to apply bias to both (regression and deviation) or just the deviation. Biasing only regression may distort deviation visually, while biasing both keeps their relationship intuitive. Using bias only for deviation scales it without altering regression, offering unique analysis.
⯁ Scale Awareness:
Supports linear and logarithmic price scaling, the regression and deviations adjust accordingly.
⯁ Signal Generation & Alerts:
Customizable entry/exit signals and alerts, detailed in the dedicated section below.
⯁ Visual Enhancements & Real-World Examples:
Optional on-chart table display summarizing regression input criteria (display type, anchor type, source, regression type, regression bias, deviation type, deviation bias, deviation multiplier) and key calculated metrics (regression length, slope, Pearson’s R, percentage position within deviations, etc.) for quick reference.
█ Understanding R (Pearson Correlation Coefficient):
Pearson’s R gauges data alignment to a straight-line trend within the regression length:
Range: R varies between –1 and +1.
R = +1 → Perfect positive correlation (strong uptrend).
R = 0 → No linear relationship detected.
R = –1 → Perfect negative correlation (strong downtrend).
This script uses Pearson’s R as an anchor, adjusting regression length to target specific R traits. Strong R (±1) follows the regression channel, while weak R (0) shows inconsistency.
█ Understanding the Slope:
The slope is the direction and rate at which the regression line rises or falls per bar:
Positive Slope (>0): Uptrend – Steeper means faster increase.
Negative Slope (<0): Downtrend – Steeper means sharper drop.
Zero or Near-Zero Slope: Sideways – Indicating range-bound conditions.
This script uses highest and lowest slope as an anchor, where extremes highlight strong moves and trend lines, while values near zero indicate sideways action and possible support/resistance.
█ Setup & Configuration:
Whether you’re new to this script or want to quickly adjust all critical parameters, the panel below shows the main settings available. You can customize everything from the anchor type and maximum length to the bias, signal conditions, and more.
Scale (select Log Scale for logarithmic, otherwise linear scale).
Display (regression channel and/or bands).
Anchor (how regression length is determined).
Length (control bars analyzed):
• Max – Upper limit.
• Min – Prevents regression from becoming too short.
• Step – Controls scanning precision; increasing Step reduces load time.
Regression:
• Type – Calculation method.
• Bias – EMA-style emphasis (>0=new bars weighted more; <0=old bars weighted more).
Deviation:
• Type – Calculation method.
• Bias – EMA-style emphasis (>0=new bars weighted more; <0=old bars weighted more).
• Multiplier - Adjusts Upper and Lower Deviation.
Signal Criteria:
• % (Price vs Deviation) – (0% = lower deviation, 50% = regression, 100% = upper deviation).
• R – (0 = no correlation, ±1 = perfect correlation; >0 = +slope, <0 = -slope).
Table (analyze table of input settings, calculated results, and signal criteria).
Adaptive Lookback (display regression while too few historical bars).
Multiple Regressions (steps 2 to 7 apply to #1, #2, and #3 regressions).
█ Signal Generation & Alerts:
The script offers customizable entry and exit signals with flexible criteria and visual cues (background color, dots, or triangles). Alerts can also be triggered for these opportunities.
Percent Direction Criteria:
(0% = lower deviation, 50% = regression line, 100% = upper deviation)
Above %: Triggers if price is above a specified percent of the deviation channel.
Below %: Triggers if price is below a specified percent of the deviation channel.
(Blank): Ignores the percent‐based condition.
Pearson's R (Correlation) Direction Criteria:
(0 = no correlation, ±1 = perfect correlation; >0 = positive slope, <0 = negative slope)
Above R / Below R: Compares the correlation to a threshold.
Above│R│ / Below│R│: Uses absolute correlation to focus on strength, ignoring direction.
Zero to R: Checks if R is in the 0-to-threshold range.
(Blank): Ignores correlation-based conditions.
█ User Tips & Best Practices:
Choose an anchor type that suits your strategy, “Bar Highest/Lowest” automatically spots commonly used regression zones, while “│R│ Highest” targets strong linear trends.
Consider enabling or disabling the Adaptive Lookback feature to ensure you always have a plotted regression if your chart doesn’t meet the maximum-length requirement.
Use a small Step size (1) unless relying on R-correlation or slope-based anchors as the are time-consuming to calculate. Larger steps speed up calculations but reduce precision.
Fine-tune settings such as lookback periods, regression bias, and deviation multipliers, or trend strength. Small adjustments can significantly affect how channels and signals behave.
To reduce loading time , show only channels (not bands) and disable signals, this limits calculations to the last bar and supports more extreme criteria.
Use the table display to monitor anchor type, calculated length, slope, R value, and percent location at a glance—especially if you have multiple regressions visible simultaneously.
█ Conclusion:
With its blend of advanced regression techniques, flexible deviation options, and a wide range of anchor types, this indicator offers a highly adaptable linear regression channeling system. Whether you're anchoring to time, price extremes, correlation, slope, or external events, the tool can be shaped to fit a variety of strategies. Combined with customizable signals and alerts, it may help highlight areas of confluence and support a more structured approach to identifying potential opportunities.
StatPivot- Dynamic Range Analyzer - indicator [PresentTrading]Hello everyone! In the following few open scripts, I would like to share various statistical tools that benefit trading. For this time, it is a powerful indicator called StatPivot- Dynamic Range Analyzer that brings a whole new dimension to your technical analysis toolkit.
This tool goes beyond traditional pivot point analysis by providing comprehensive statistical insights about price movements, helping you identify high-probability trading opportunities based on historical data patterns rather than subjective interpretations. Whether you're a day trader, swing trader, or position trader, StatPivot's real-time percentile rankings give you a statistical edge in understanding exactly where current price action stands within historical contexts.
Welcome to share your opinions! Looking forward to sharing the next tool soon!
█ Introduction and How it is Different
StatPivot is an advanced technical analysis tool that revolutionizes retracement analysis. Unlike traditional pivot indicators that only show static support/resistance levels, StatPivot delivers dynamic statistical insights based on historical pivot patterns.
Its key innovation is real-time percentile calculation - while conventional tools require new pivot formations before updating (often too late for trading decisions), StatPivot continuously analyzes where current price stands within historical retracement distributions.
Furthermore, StatPivot provides comprehensive statistical metrics including mean, median, standard deviation, and percentile distributions of price movements, giving traders a probabilistic edge by revealing which price levels represent statistically significant zones for potential reversals or continuations. By transforming raw price data into statistical insights, StatPivot helps traders move beyond subjective price analysis to evidence-based decision making.
█ Strategy, How it Works: Detailed Explanation
🔶 Pivot Point Detection and Analysis
The core of StatPivot's functionality begins with identifying significant pivot points in the price structure. Using the parameters left and right, the indicator locates pivot highs and lows by examining a specified number of bars to the left and right of each potential pivot point:
Copyp_low = ta.pivotlow(low, left, right)
p_high = ta.pivothigh(high, left, right)
For a point to qualify as a pivot low, it must have left higher lows to its left and right higher lows to its right. Similarly, a pivot high must have left lower highs to its left and right lower highs to its right. This approach ensures that only significant turning points are recognized.
🔶 Percentage Change Calculation
Once pivot points are identified, StatPivot calculates the percentage changes between consecutive pivot points:
For drops (when a pivot low is lower than the previous pivot low):
CopydropPercent = (previous_pivot_low - current_pivot_low) / previous_pivot_low * 100
For rises (when a pivot high is higher than the previous pivot high):
CopyrisePercent = (current_pivot_high - previous_pivot_high) / previous_pivot_high * 100
These calculations quantify the magnitude of each market swing, allowing for statistical analysis of historical price movements.
🔶 Statistical Distribution Analysis
StatPivot computes comprehensive statistics on the historical distribution of drops and rises:
Average (Mean): The arithmetic mean of all recorded percentage changes
CopyavgDrop = array.avg(dropValues)
Median: The middle value when all percentage changes are arranged in order
CopymedianDrop = array.median(dropValues)
Standard Deviation: Measures the dispersion of percentage changes from the average
CopystdDevDrop = array.stdev(dropValues)
Percentiles (25th, 75th): Values below which 25% and 75% of observations fall
Copyq1 = array.get(sorted, math.floor(cnt * 0.25))
q3 = array.get(sorted, math.floor(cnt * 0.75))
VaR95: The maximum expected percentage drop with 95% confidence
Copyvar95D = array.get(sortedD, math.floor(nD * 0.95))
Coefficient of Variation (CV): Measures relative variability
CopycvD = stdDevDrop / avgDrop
These statistics provide a comprehensive view of market behavior, enabling traders to understand the typical ranges and extreme moves.
🔶 Real-time Percentile Ranking
StatPivot's most innovative feature is its real-time percentile calculation. For each current price, it calculates:
The percentage drop from the latest pivot high:
CopycurrentDropPct = (latestPivotHigh - close) / latestPivotHigh * 100
The percentage rise from the latest pivot low:
CopycurrentRisePct = (close - latestPivotLow) / latestPivotLow * 100
The percentile ranks of these values within the historical distribution:
CopyrealtimeDropRank = (count of historical drops <= currentDropPct) / total drops * 100
This calculation reveals exactly where the current price movement stands in relation to all historical movements, providing crucial context for decision-making.
🔶 Cluster Analysis
To identify the most common retracement zones, StatPivot performs a cluster analysis by dividing the range of historical drops into five equal intervals:
CopyrangeSize = maxVal - minVal
For each interval boundary:
Copyboundaries = minVal + rangeSize * i / 5
By counting the number of observations in each interval, the indicator identifies the most frequently occurring retracement zones, which often serve as significant support or resistance areas.
🔶 Expected Price Targets
Using the statistical data, StatPivot calculates expected price targets:
CopytargetBuyPrice = close * (1 - avgDrop / 100)
targetSellPrice = close * (1 + avgRise / 100)
These targets represent statistically probable price levels for potential entries and exits based on the average historical behavior of the market.
█ Trade Direction
StatPivot functions as an analytical tool rather than a direct trading signal generator, providing statistical insights that can be applied to various trading strategies. However, the data it generates can be interpreted for different trade directions:
For Long Trades:
Entry considerations: Look for price drops that reach the 70-80th percentile range in the historical distribution, suggesting a statistically significant retracement
Target setting: Use the Expected Sell price or consider the average rise percentage as a reasonable target
Risk management: Set stop losses below recent pivot lows or at a distance related to the statistical volatility (standard deviation)
For Short Trades:
Entry considerations: Look for price rises that reach the 70-80th percentile range, indicating an unusual extension
Target setting: Use the Expected Buy price or average drop percentage as a target
Risk management: Set stop losses above recent pivot highs or based on statistical measures of volatility
For Range Trading:
Use the most common drop and rise clusters to identify probable reversal zones
Trade bounces between these statistically significant levels
For Trend Following:
Confirm trend strength by analyzing consecutive higher pivot lows (uptrend) or lower pivot highs (downtrend)
Use lower percentile retracements (20-30th percentile) as entry opportunities in established trends
█ Usage
StatPivot offers multiple ways to integrate its statistical insights into your trading workflow:
Statistical Table Analysis: Review the comprehensive statistics displayed in the data table to understand the market's behavior. Pay particular attention to:
Average drop and rise percentages to set reasonable expectations
Standard deviation to gauge volatility
VaR95 for risk assessment
Real-time Percentile Monitoring: Watch the real-time percentile display to see where the current price movement stands within the historical distribution. This can help identify:
Extreme movements (90th+ percentile) that might indicate reversal opportunities
Typical retracements (40-60th percentile) that might continue further
Shallow pullbacks (10-30th percentile) that might represent continuation opportunities in trends
Support and Resistance Identification: Utilize the plotted pivot points as key support and resistance levels, especially when they align with statistically significant percentile ranges.
Target Price Setting: Use the expected buy and sell prices calculated from historical averages as initial targets for your trades.
Risk Management: Apply the statistical measurements like standard deviation and VaR95 to set appropriate stop loss levels that account for the market's historical volatility.
Pattern Recognition: Over time, learn to recognize when certain percentile levels consistently lead to reversals or continuations in your specific market, and develop personalized strategies based on these observations.
█ Default Settings
The default settings of StatPivot have been carefully calibrated to provide reliable statistical analysis across a variety of markets and timeframes, but understanding their effects allows for optimal customization:
Left Bars (30) and Right Bars (30): These parameters determine how pivot points are identified. With both set to 30 by default:
A pivot low must be the lowest point among 30 bars to its left and 30 bars to its right
A pivot high must be the highest point among 30 bars to its left and 30 bars to its right
Effect on performance: Larger values create fewer but more significant pivot points, reducing noise but potentially missing important market structures. Smaller values generate more pivot points, capturing more nuanced movements but potentially including noise.
Table Position (Top Right): Determines where the statistical data table appears on the chart.
Effect on performance: No impact on analytical performance, purely a visual preference.
Show Distribution Histogram (False): Controls whether the distribution histogram of drop percentages is displayed.
Effect on performance: Enabling this provides visual insight into the distribution of retracements but can clutter the chart.
Show Real-time Percentile (True): Toggles the display of real-time percentile rankings.
Effect on performance: A critical setting that enables the dynamic analysis of current price movements. Disabling this removes one of the key advantages of the indicator.
Real-time Percentile Display Mode (Label): Chooses between label display or indicator line for percentile rankings.
Effect on performance: Labels provide precise information at the current price point, while indicator lines show the evolution of percentile rankings over time.
Advanced Considerations for Settings Optimization:
Timeframe Adjustment: Higher timeframes generally benefit from larger Left/Right values to identify truly significant pivots, while lower timeframes may require smaller values to capture shorter-term swings.
Volatility-Based Tuning: In highly volatile markets, consider increasing the Left/Right values to filter out noise. In less volatile conditions, lower values can help identify more potential entry and exit points.
Market-Specific Optimization: Different markets (forex, stocks, commodities) display different retracement patterns. Monitor the statistics table to see if your market typically shows larger or smaller retracements than the current settings are optimized for.
Trading Style Alignment: Adjust the settings to match your trading timeframe. Day traders might prefer settings that identify shorter-term pivots (smaller Left/Right values), while swing traders benefit from more significant pivots (larger Left/Right values).
By understanding how these settings affect the analysis and customizing them to your specific market and trading style, you can maximize the effectiveness of StatPivot as a powerful statistical tool for identifying high-probability trading opportunities.
Multi-Indicator Trading DashboardMulti-Indicator Trading Dashboard: Comprehensive Analysis and Actionable Signals
This Pine Script indicator, "Multi-Indicator Trading Dashboard," provides a comprehensive overview of key market indicators and generates actionable trading signals, all presented in a clear, easy-to-read table format on your TradingView chart.
Key Features:
Real-time Indicator Analysis: The dashboard displays real-time values and signals for:
RSI (Relative Strength Index): Tracks overbought and oversold conditions.
MACD (Moving Average Convergence Divergence): Identifies trend changes and momentum.
ADX (Average Directional Index): Measures trend strength.
Volatility (ATR-based): Estimates volatility as a percentage, acting as a VIX proxy for single-symbol charts.
Trend Determination: Analyzes 20, 50, and 200-period EMAs to provide a clear trend assessment (Strong Bullish, Cautious Bullish, Cautious Bearish, Strong Bearish).
Combined Trading Signals: Integrates signals from RSI, MACD, ADX, and trend analysis to generate a combined "Buy," "Sell," or "Neutral" action signal.
User-Friendly Table Display: Presents all information in a neatly organized table, positioned at the top-right of your chart.
Visual Chart Overlays: Plots 20, 50, and 200-period EMAs directly on the chart for visual trend confirmation.
Background Color Alerts: Colors the chart's background based on the "Buy" or "Sell" action signal for quick visual cues.
Customizable Inputs: Allows you to adjust key parameters like RSI lengths, MACD settings, ADX thresholds, and EMA periods.
How It Works:
Indicator Calculations: The script calculates RSI, MACD, ADX, and a volatility proxy (ATR) using standard Pine Script functions.
Trend Analysis: It compares 20, 50, and 200-period EMAs to determine the overall trend direction.
Individual Signal Generation: It generates individual "Buy," "Sell," or "Neutral" signals based on RSI, MACD, and ADX values.
Combined Signal Logic: It combines the individual signals and trend analysis, assigning a "Buy" or "Sell" action only when at least two indicators align.
Table Display: It creates a table and populates it with the calculated values, signals, and trend information.
Chart Overlays: It plots the EMAs on the chart and colors the background based on the combined action signal.
Use Cases:
Quick Market Overview: Get a snapshot of key market indicators and trend direction at a glance.
Confirmation Tool: Use the combined signals to confirm your existing trading strategies.
Educational Purpose: Learn how different indicators interact and influence trading decisions.
Automated Alerting: Set up alerts based on the "Buy" or "Sell" action signals.
Customization:
Adjust the input parameters to fine-tune the indicator's sensitivity to your trading style and the specific market you're analyzing.
Disclaimer:
This indicator is for informational and educational purposes only and should not be considered financial advice. Always conduct thorough research and consult with 1 a qualified professional before making any 2 trading decisions.
Power Balance Bull&Bear - CoffeeKillerPower Balance Bull&Bear - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the Power Balance Bull&Bear indicator, a unique and powerful market analysis tool developed by CoffeeKiller that visualizes the ongoing battle between buyers and sellers in any market.
Core Concept: Buyers vs. Sellers
The foundation of this indicator rests on a simple yet profound concept: every price movement in the market represents a battle between buyers and sellers.
Positive Green Line: Buyer Power
- Represents cumulative buying pressure in the market
- Tracks positive directional movement over a specified period
- Rising positive line indicates increasing buying momentum
- Peaks in the positive line show moments of maximum buyer dominance
Negative Red Line: Seller Power
- Represents cumulative selling pressure in the market
- Tracks negative directional movement over a specified period
- Falling negative line indicates increasing selling momentum
- Troughs in the negative line show moments of maximum seller dominance
Master Line: Market Balance
- Calculated as the difference between positive and negative movements
- Above zero: buyers are in control
- Below zero: sellers are in control
- Peaks and troughs: moments of extreme buyer or seller dominance
Core Components
1. Directional Movement Analysis
- Cumulative measurement of price changes in both directions
- Normalization for consistent visualization
- Optional smoothing for clearer signals
- Custom box size for sensitivity control
2. Distance Measurement
- Calculation of separation between buyer and seller lines
- Convergence and divergence thresholds
- Dynamic fill coloring based on distance trends
- Distance trend visualization
3. Peak Detection System
- Identification of local maxima and minima in buyer/seller dominance
- Background highlighting of significant peaks
- Zero-line cross detection for trend changes
- Visual cues for market extremes
4. Trend Analysis
- Buyer/seller line crossovers for major trend signals
- Distance trending for momentum confirmation
- Status monitoring (Near, Far, Normal)
- Direction tracking for both buyer and seller lines
Main Features
Time Resolution Settings
- Normal mode: calculations based on chart timeframe
- Custom resolution mode: calculations based on specified timeframe
- Multi-timeframe analysis capabilities
- Flexible time projection options
Visual Elements
- Color-coded buyer and seller lines
- Dynamic fill coloring based on convergence/divergence
- Background highlighting for significant peaks
- Distance line with threshold markers
Signal Generation
- Buyer/seller crossover alerts
- Convergence/divergence notifications
- Peak detection signals
- Status change alerts
Analysis Table(I personally don't use the table it was coded to take longer signals to show strength or weakness in overall trend)
- Current distance measurement
- Distance trend indication
- Status monitoring (Near, Far, Normal)
- Buyer and seller line trend tracking
Trading Applications
1. Trend Identification
- Buyer line crossing above seller line: bullish trend beginning
- Seller line crossing above buyer line: bearish trend beginning
- Distance between lines: trend strength
- Distance trending: momentum confirmation
2. Reversal Detection
- Peak formation after extended trend: potential exhaustion
- Buyer/seller line convergence: decreasing trend strength
- Distance falling below convergence threshold: potential trend change
- Background highlighting: visual cue for significant peaks
3. Momentum Analysis
- Increasing distance: accelerating trend
- Decreasing distance: decelerating trend
- Distance above divergence threshold: strong momentum
- Distance below convergence threshold: weak momentum
4. Market Balance Assessment
- Buyer line trend: indicates strength/weakness of bulls
- Seller line trend: indicates strength/weakness of bears
- Master line position relative to zero: overall market bias
- Distance between lines: consensus or disagreement in the market
Optimization Guide
1. Period Settings
- Longer period: smoother signals, less noise, fewer false signals
- Shorter period: more responsive, captures minor moves, potentially more noise
- Default (20): balanced approach for most timeframes
2. Box Size Parameter
- Smaller box size: more sensitive to price changes
- Larger box size: less sensitive, focuses on major moves
- Default (0.001): calibrated for typical price ranges
3. Distance Thresholds
- Convergence threshold: determines when lines are considered "near"
- Divergence threshold: determines when lines are considered "far"
- Adjusting these based on volatility of the instrument
4. Color Customization
- Positive Green line: representing buyer strength
- Negative Red line: representing seller strength
- Diverging fill: when the gap between buyers and sellers is increasing
- Converging fill: when buyers and sellers are moving closer together
Best Practices
1. Signal Confirmation
- Wait for buyer/seller crossovers to confirm
- Look for background highlighting at peaks
- Check distance trends for momentum confirmation
- Use the analysis table for additional context
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Custom resolution: allows comparison across timeframes
- Consider using multiple timeframes for confirmation
3. Market Context
- Strong buyer line rising + weak seller line: very bullish
- Strong seller line falling + weak buyer line: very bearish
- Both lines rising: volatile uptrend
- Both lines falling: volatile downtrend
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with oscillators for overbought/oversold conditions
- Combine with volume analysis for validation
- Consider support/resistance levels when peaks form
Advanced Trading Strategies
1. Buyer/Seller Balance Strategy
- Enter long when buyer line crosses above seller line
- Enter short when seller line crosses above buyer line
- Use distance trend for filtering quality of signals
- Exit when distance falls below convergence threshold
2. Peak Trading Strategy
- Identify significant peaks with background highlighting
- Look for consecutive lower peaks in buyer line for shorting opportunities
- Look for consecutive higher troughs in seller line for buying opportunities
- Use master line crosses through zero as confirmation
3. Convergence/Divergence Strategy
- Enter positions when distance exceeds divergence threshold (strong trend)
- Take partial profits when distance starts decreasing
- Exit fully when distance falls below convergence threshold
- Re-enter when a new trend forms with increasing distance
4. Line Trend Combination Strategy
- Strongest bullish signal: Rising buyer line + falling seller line + increasing distance
- Strongest bearish signal: Falling buyer line + rising seller line + increasing distance
- Potential reversal signal: Decreasing distance + peak formation + line trend change
- Continuation signal: Consistent buyer/seller dominance + increasing distance after consolidation
Practical Analysis Examples
Bullish Market Scenario
- Buyer line trends upward as buying pressure increases
- Seller line remains flat or trends downward as selling pressure decreases
- Distance between lines expands, showing divergence (strong trend)
- Positive background highlights appear at new peaks in buyer dominance
- Master line moves further above zero
Bearish Market Scenario
- Seller line trends downward as selling pressure increases
- Buyer line remains flat or trends downward as buying pressure decreases
- Distance between lines expands, showing divergence (strong trend)
- Negative background highlights appear at new troughs in seller dominance
- Master line moves further below zero
Consolidation Scenario
- Buyer and seller lines move sideways
- Distance between lines narrows, showing convergence
- Few or no new peak highlights appear
- Master line oscillates close to the zero line
- Analysis table shows "Stable" trends for both buyer and seller lines
Understanding Market Dynamics Through Power Balance
At its core, this indicator provides a unique lens to visualize the ongoing battle between bulls and bears:
1. **Relative Strength**: When the buyer line rises faster than the seller line, bulls are gaining strength relative to bears - a bullish signal. When the seller line falls faster than the buyer line, bears are dominating - a bearish signal.
2. **Market Consensus**: Convergence between lines suggests market participants are reaching consensus about price direction. Divergence suggests growing disagreement and potential for stronger moves.
3. **Exhaustion Signals**: Major peaks in either line that are highlighted by background colors suggest moments where one side (buyers or sellers) has reached maximum strength - often precursors to reversals.
4. **Trend Confirmation**: The status indicators (Near, Far, Normal) provide context about the current market phase, helping confirm whether a trend is establishing, continuing strongly, or potentially fading.
Remember:
- Combine signals from buyer/seller lines, distance measurements, and peak formations
- Use appropriate timeframe settings for your trading style
- Monitor the analysis table for additional context
- Consider market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
**DISCLAIMER**: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
Dynamic Timeframe Trend AnalyzerPurpose and Core Logic
This indicator automatically adjusts its calculations based on the current chart’s timeframe, allowing traders to analyze trends, momentum, and mean reversion opportunities without manually changing indicator settings for each interval. It detects potential long or short setups by combining several techniques:
Dynamic Timeframe Factor
The script compares the current timeframe to a base (e.g., 5 minutes) and calculates a “factor” to scale certain parameters, such as EMA lengths or ATR settings. This reduces the need to reconfigure indicators when switching timeframes.
Regime Detection
It uses ADX (Average Directional Index) to classify the market as strongly trending, moderately trending, choppy, or in a potential mean-reversion phase.
RSI (Relative Strength Index) is also monitored for extreme levels (e.g., overbought/oversold) to detect potential reversal zones.
Volume is compared to a moving average to confirm or refute volatility conditions.
Trend & Mean Reversion Signals
EMA Alignment (8/21/55) helps identify bullish or bearish phases (strong bull if all EMAs align upward, strong bear if aligned downward).
For mean reversion opportunities, the script checks if ADX is sufficiently low (indicating weak or no trend) while price and RSI are at extreme levels—suggesting a snapback or countertrend move may occur.
Dynamic Stop Loss & Take Profit
Uses ATR (Average True Range) to set initial stop-loss (SL) and take-profit (TP) levels, then adjusts these levels further with “regime multipliers” based on whether the market is in a high-volatility trend or a quieter mean-reversion environment.
This approach aims to place stops and targets in a more adaptive way, reflecting current market conditions rather than a one-size-fits-all approach.
Visual Aids
Color-coded chart backgrounds (e.g., greenish for bullish trend, red for bearish, yellow/orange for mean reversion).
Triangles to show recent bullish/bearish signals.
A status table in the top-right corner (optional) displaying key metrics like ADX, RSI, dynamic thresholds, current SL/TP levels, and whether a stop loss has been hit.
How It Works Internally
ADX & Dynamic Thresholds:
A moving average (adx_mean) and standard deviation (adx_std) of the ADX are calculated over a lookback period to define “strong” vs. “weak” ADX thresholds.
This allows the script to adapt to changing volatility and trend strength in different markets or timeframes.
Mean Reversion Criteria:
The indicator checks if price deviates significantly from its own moving average, alongside RSI extremes. If ADX suggests no strong directional push (i.e., the market is “quiet”), it may classify conditions as mean-reverting.
Regime Multipliers:
Once the script identifies the market regime (e.g., strong uptrend, choppy, mean reversion), it applies different multipliers to the user-defined base values for stop-loss and take-profit. For instance, strong trending conditions might allow for wider stops to handle volatility, while mean reversion signals use tighter exits to capture quick reversals.
How to Use It
Timeframe Agnostic
Simply apply it to any timeframe (from 1-minute up to daily or weekly). The “Dynamic Timeframe Factor” will scale the indicator parameters automatically.
Look for Buy/Sell Triangles
When the script detects a valid bullish trend shift or a mean-reversion long setup, it plots a green triangle under the price bar. Conversely, it plots a red triangle above the price bar for bearish or mean-reversion short setups.
Check the Status Table
The table in the top-right corner summarizes the indicator’s current readings: ADX, RSI, volume trends, and the market regime classification.
The table also shows if a stop loss has been hit (SL Hit) and displays recommended SL/TP levels if a signal is active.
Stop Loss & Take Profit
The script plots lines for SL and TP on your chart after a new signal. These lines are automatically adjusted based on ATR, volume conditions, and ADX-derived multipliers.
Mean Reversion vs. Trend-Following
If you see a “Mean Rev” state in the table or the background turning yellow/orange, it suggests potential countertrend trades. Conversely, “STRONG BULL” or “STRONG BEAR” states favor momentum-based entries in the prevailing direction.
Originality & Benefits
Adaptive to Timeframe: Many indicators require reconfiguration when switching from short to long timeframes. This script automates that process using the “timeframe factor” logic.
Regime-Based SL/TP: Instead of fixed risk parameters, the script dynamically tunes stop and target levels depending on whether the market is trending or reverting.
Comprehensive Market View: It combines multiple factors—ADX, RSI, volume, moving averages, and volatility measurements—into a single, integrated framework that categorizes the market regime in real time.
Best Practices & Notes
Timeframes: It typically performs well on intraday timeframes (5m, 15m, 1H) but can also be used for swing trading on 4H or Daily charts.
Settings: The defaults are a good starting point, but you can adjust the base ATR multiplier or ADX lookbacks if you prefer a different balance between sensitivity and stability.
Risk Management: This indicator is not a guarantee of any specific results. Always use proper risk management (position sizing, stop-losses, and diversified strategies).
Alert Conditions: Built-in alert conditions can notify you when a new long or short signal appears, or when a stop loss is triggered.
ALN Sessions - for NQ2/24/25 - v1
This script does not calculate any stats.
It uses the sessions and stats from NQStats/ALNSessions
Option to draw boxes around the session times.
Options to adjust the table text/background colors/position.
The logic will determine how the Asia and London sessions interact.
Once the New York session starts (8am), it will then display the appropriate stats.
Script quirk...fyi. The script removes the stats table at 6PM.
That's just how it works. I used grok to assist with the code, and it got funky. It works, so I left it that way.
The appropriate stats table will then be displayed when the next New York session begins.
---
There is another table I used just for troubleshooting to show the values of the Asia/London session highs/lows. This can just be ignored.
3/3/25 - republished.
Volume Stack US Top 40 [Pt]█ Overview
Volume Stack US Top 40 is a versatile TradingView indicator designed to give you an at-a-glance view of market sentiment and volume dynamics across the top 40 U.S. large-cap stocks. Inspired by the popular Saty Volume Stack, this enhanced version aggregates essential volume and price strength data from major tickers on both the NYSE and NASDAQ, and works seamlessly on all timeframes.
█ Key Features
Dynamic Buy / Sell Volume Stack: This indicator dynamically stacks the volume bars so that the side with higher volume appears on top. For example, green over red signals more buy-side volume, while red over green indicates greater sell-side volume.
Cross-Market Analysis: Easily toggle between NYSE and NASDAQ to analyze the most influential U.S. stocks. The indicator automatically loads the correct set of tickers based on your selection.
Flexible Coverage: Choose from Top 10, Top 20, Top 30, or Top 40 tickers to tailor the tool to your desired scope of analysis.
Dynamic Table Display: A neat on-chart table lists the selected ticker symbols along with visual cues that reflect each stock’s strength. You can even remove exchange prefixes for a cleaner look.
█ Inputs & Settings
Market Selector: Choose whether to view data from the NYSE or NASDAQ; the indicator automatically loads the corresponding list of top tickers.
Number of Tickers: Select from ‘Top 10’, ‘Top 20’, ‘Top 30’, or ‘Top 40’ stocks to define the breadth of your analysis.
Color Options: Customize the colors for bullish and bearish histogram bars to suit your personal style.
Table Preferences: Adjust the on-chart table’s display style (grid or one row), text size, and decide whether to show exchange information alongside ticker symbols.
█ Usage & Benefits
Volume Stack US Top 40 is ideal for traders and investors who need a clear yet powerful tool to gauge overall market strength. By combining volume and price action data across multiple major stocks, it helps you:
Quickly assess whether the market sentiment is bullish or bearish.
Confirm trends by comparing volume patterns against intraday price movements.
Enhance your trading decisions with a visual representation of market breadth and dynamic buy/sell volume stacking.
Its intuitive design means you spend less time adjusting complex settings and more time making confident, informed decisions.
Casa_VolumeProfileSessionLibrary "Casa_VolumeProfileSession"
Analyzes price and volume during regular trading hours to provide a session volume profile,
including Point of Control (POC), Value Area High (VAH), and Value Area Low (VAL).
Calculates and displays these levels historically and for the developing session.
Offers customizable visualization options for the Value Area, POC, histogram, and labels.
Uses lower timeframe data for increased accuracy and supports futures sessions.
The number of rows used for the volume profile can be fixed or dynamically calculated based on the session's price range and the instrument's minimum tick increment, providing optimal resolution.
calculateEffectiveRows(configuredRows, dayHigh, dayLow)
Determines the optimal number of rows for the volume profile, either using the configured value or calculating dynamically based on price range and tick size
Parameters:
configuredRows (int) : User-specified number of rows (0 means auto-calculate)
dayHigh (float) : Highest price of the session
dayLow (float) : Lowest price of the session
Returns: The number of rows to use for the volume profile
debug(vp, position)
Helper function to write some information about the supplied SVP object to the screen in a table.
Parameters:
vp (Object) : The SVP object to debug
position (string) : The position.* to place the table. Defaults to position.bottom_center
getLowerTimeframe()
Depending on the timeframe of the chart, determines a lower timeframe to grab volume data from for the analysis
Returns: The timeframe string to fetch volume for
get(volumeProfile, lowerTimeframeHigh, lowerTimeframeLow, lowerTimeframeVolume, lowerTimeframeTime, lowerTimeframeSessionIsMarket)
Populated the provided SessionVolumeProfile object with vp data on the session.
Parameters:
volumeProfile (Object) : The SessionVolumeProfile object to populate
lowerTimeframeHigh (array) : The lower timeframe high values
lowerTimeframeLow (array) : The lower timeframe low values
lowerTimeframeVolume (array) : The lower timeframe volume values
lowerTimeframeTime (array) : The lower timeframe time values
lowerTimeframeSessionIsMarket (array) : The lower timeframe session.ismarket values (that are futures-friendly)
drawPriorValueAreas(todaySessionVolumeProfile, extendYesterdayOverToday, showLabels, labelSize, pocColor, pocStyle, pocWidth, vahlColor, vahlStyle, vahlWidth, vaColor)
Given a SessionVolumeProfile Object, will render the historical value areas for that object.
Parameters:
todaySessionVolumeProfile (Object) : The SessionVolumeProfile Object to draw
extendYesterdayOverToday (bool) : Defaults to true
showLabels (bool) : Defaults to true
labelSize (string) : Defaults to size.small
pocColor (color) : Defaults to #e500a4
pocStyle (string) : Defaults to line.style_solid
pocWidth (int) : Defaults to 1
vahlColor (color) : The color of the value area high/low lines. Defaults to #1592e6
vahlStyle (string) : The style of the value area high/low lines. Defaults to line.style_solid
vahlWidth (int) : The width of the value area high/low lines. Defaults to 1
vaColor (color) : The color of the value area background. Defaults to #00bbf911)
drawHistogram(volumeProfile, bgColor, showVolumeOnHistogram)
Given a SessionVolumeProfile object, will render the histogram for that object.
Parameters:
volumeProfile (Object) : The SessionVolumeProfile object to draw
bgColor (color) : The baseline color to use for the histogram. Defaults to #00bbf9
showVolumeOnHistogram (bool) : Show the volume amount on the histogram bars. Defaults to false.
Object
Object Contains all settings and calculated values for a Volume Profile Session analysis
Fields:
numberOfRows (series int) : Number of price levels to divide the range into. If set to 0, auto-calculates based on price range and tick size
valueAreaCoverage (series int) : Percentage of total volume to include in the Value Area (default 70%)
trackDevelopingVa (series bool) : Whether to calculate and display the Value Area as it develops during the session
valueAreaHigh (series float) : Upper boundary of the Value Area - price level containing specified % of volume
pointOfControl (series float) : Price level with the highest volume concentration
valueAreaLow (series float) : Lower boundary of the Value Area
startTime (series int) : Session start time in Unix timestamp format
endTime (series int) : Session end time in Unix timestamp format
dayHigh (series float) : Highest price of the session
dayLow (series float) : Lowest price of the session
step (series float) : Size of each price row (calculated as price range divided by number of rows)
pointOfControlLevel (series int) : Index of the row containing the Point of Control
valueAreaHighLevel (series int) : Index of the row containing the Value Area High
valueAreaLowLevel (series int) : Index of the row containing the Value Area Low
lastTime (series int) : Tracks the most recent timestamp processed
volumeRows (map) : Stores volume data for each price level row (key=row number, value=volume)
ltfSessionHighs (array) : Stores high prices from lower timeframe data
ltfSessionLows (array) : Stores low prices from lower timeframe data
ltfSessionVols (array) : Stores volume data from lower timeframe data
Bar Color - Moving Average Convergence Divergence [nsen]The Pine Script you've provided creates a custom indicator that utilizes the MACD (Moving Average Convergence Divergence) and displays various outputs, such as bar color changes based on MACD signals, and a table of data from multiple timeframes. Here's a breakdown of how the script works:
1. Basic Settings (Input)
• The script defines several user-configurable parameters, such as the MACD values, bar colors, the length of the EMA (Exponential Moving Average) periods, and signal smoothing.
• Users can also choose timeframes to analyze the MACD values, like 5 minutes, 15 minutes, 1 hour, 4 hours, and 1 day.
2. MACD Calculation
• It uses the EMA of the close price to calculate the MACD value, with fast_length and slow_length representing the fast and slow periods. The signal_length is used to calculate the Signal Line.
• The MACD value is the difference between the fast and slow EMA, and the Signal Line is the EMA of the MACD.
• The Histogram is the difference between the MACD and the Signal Line.
3. Plotting the Histogram
• The Histogram values are plotted with colors that change based on the value. If the Histogram is positive (rising), it is colored differently than if it's negative (falling). The colors are determined by the user inputs, for example, green for bullish (positive) signals and red for bearish (negative) signals.
4. Bar Coloring
• The bar color changes based on the MACD's bullish or bearish signal. If the MACD is bullish (MACD > Signal), the bar color will change to the color defined for bullish signals, and if it's bearish (MACD < Signal), the bar color will change to the color defined for bearish signals.
5. Multi-Timeframe Data Table
• The script includes a table displaying the MACD trend for different timeframes (e.g., 5m, 15m, 1h, 4h, 1d).
• Each timeframe will show a colored indicator: green (🟩) for bullish and red (🟥) for bearish, with the background color changing based on the trend.
6. Alerts
• The script has alert conditions to notify the user when the MACD shows a bullish or bearish entry:
• Bullish Entry: When the MACD turns bullish (crosses above the Signal Line).
• Bearish Entry: When the MACD turns bearish (crosses below the Signal Line).
• Alerts are triggered with custom messages such as "🟩 MACD Bullish Entry" and "🟥 MACD Bearish Entry."
Key Features:
• Customizable Inputs: Users can adjust the MACD settings, histogram colors, and timeframe options.
• Visual Feedback: The color changes of the histogram and bars provide instant visual cues for bullish or bearish trends.
• Multi-Timeframe Analysis: The table shows the MACD trend across multiple timeframes, helping traders monitor trends in different timeframes.
• Alert Conditions: Alerts notify users when key MACD crossovers occur.
MTF Signal XpertMTF Signal Xpert – Detailed Description
Overview:
MTF Signal Xpert is a proprietary, open‑source trading signal indicator that fuses multiple technical analysis methods into one cohesive strategy. Developed after rigorous backtesting and extensive research, this advanced tool is designed to deliver clear BUY and SELL signals by analyzing trend, momentum, and volatility across various timeframes. Its integrated approach not only enhances signal reliability but also incorporates dynamic risk management, helping traders protect their capital while navigating complex market conditions.
Detailed Explanation of How It Works:
Trend Detection via Moving Averages
Dual Moving Averages:
MTF Signal Xpert computes two moving averages—a fast MA and a slow MA—with the flexibility to choose from Simple (SMA), Exponential (EMA), or Hull (HMA) methods. This dual-MA system helps identify the prevailing market trend by contrasting short-term momentum with longer-term trends.
Crossover Logic:
A BUY signal is initiated when the fast MA crosses above the slow MA, coupled with the condition that the current price is above the lower Bollinger Band. This suggests that the market may be emerging from a lower price region. Conversely, a SELL signal is generated when the fast MA crosses below the slow MA and the price is below the upper Bollinger Band, indicating potential bearish pressure.
Recent Crossover Confirmation:
To ensure that signals reflect current market dynamics, the script tracks the number of bars since the moving average crossover event. Only crossovers that occur within a user-defined “candle confirmation” period are considered, which helps filter out outdated signals and improves overall signal accuracy.
Volatility and Price Extremes with Bollinger Bands
Calculation of Bands:
Bollinger Bands are calculated using a 20‑period simple moving average as the central basis, with the upper and lower bands derived from a standard deviation multiplier. This creates dynamic boundaries that adjust according to recent market volatility.
Signal Reinforcement:
For BUY signals, the condition that the price is above the lower Bollinger Band suggests an undervalued market condition, while for SELL signals, the price falling below the upper Bollinger Band reinforces the bearish bias. This volatility context adds depth to the moving average crossover signals.
Momentum Confirmation Using Multiple Oscillators
RSI (Relative Strength Index):
The RSI is computed over 14 periods to determine if the market is in an overbought or oversold state. Only readings within an optimal range (defined by user inputs) validate the signal, ensuring that entries are made during balanced conditions.
MACD (Moving Average Convergence Divergence):
The MACD line is compared with its signal line to assess momentum. A bullish scenario is confirmed when the MACD line is above the signal line, while a bearish scenario is indicated when it is below, thus adding another layer of confirmation.
Awesome Oscillator (AO):
The AO measures the difference between short-term and long-term simple moving averages of the median price. Positive AO values support BUY signals, while negative values back SELL signals, offering additional momentum insight.
ADX (Average Directional Index):
The ADX quantifies trend strength. MTF Signal Xpert only considers signals when the ADX value exceeds a specified threshold, ensuring that trades are taken in strongly trending markets.
Optional Stochastic Oscillator:
An optional stochastic oscillator filter can be enabled to further refine signals. It checks for overbought conditions (supporting SELL signals) or oversold conditions (supporting BUY signals), thus reducing ambiguity.
Multi-Timeframe Verification
Higher Timeframe Filter:
To align short-term signals with broader market trends, the script calculates an EMA on a higher timeframe as specified by the user. This multi-timeframe approach helps ensure that signals on the primary chart are consistent with the overall trend, thereby reducing false signals.
Dynamic Risk Management with ATR
ATR-Based Calculations:
The Average True Range (ATR) is used to measure current market volatility. This value is multiplied by a user-defined factor to dynamically determine stop loss (SL) and take profit (TP) levels, adapting to changing market conditions.
Visual SL/TP Markers:
The calculated SL and TP levels are plotted on the chart as distinct colored dots, enabling traders to quickly identify recommended exit points.
Optional Trailing Stop:
An optional trailing stop feature is available, which adjusts the stop loss as the trade moves favorably, helping to lock in profits while protecting against sudden reversals.
Risk/Reward Ratio Calculation:
MTF Signal Xpert computes a risk/reward ratio based on the dynamic SL and TP levels. This quantitative measure allows traders to assess whether the potential reward justifies the risk associated with a trade.
Condition Weighting and Signal Scoring
Binary Condition Checks:
Each technical condition—ranging from moving average crossovers, Bollinger Band positioning, and RSI range to MACD, AO, ADX, and volume filters—is assigned a binary score (1 if met, 0 if not).
Cumulative Scoring:
These individual scores are summed to generate cumulative bullish and bearish scores, quantifying the overall strength of the signal and providing traders with an objective measure of its viability.
Detailed Signal Explanation:
A comprehensive explanation string is generated, outlining which conditions contributed to the current BUY or SELL signal. This explanation is displayed on an on‑chart dashboard, offering transparency and clarity into the signal generation process.
On-Chart Visualizations and Debug Information
Chart Elements:
The indicator plots all key components—moving averages, Bollinger Bands, SL and TP markers—directly on the chart, providing a clear visual framework for understanding market conditions.
Combined Dashboard:
A dedicated dashboard displays key metrics such as RSI, ADX, and the bullish/bearish scores, alongside a detailed explanation of the current signal. This consolidated view allows traders to quickly grasp the underlying logic.
Debug Table (Optional):
For advanced users, an optional debug table is available. This table breaks down each individual condition, indicating which criteria were met or not met, thus aiding in further analysis and strategy refinement.
Mashup Justification and Originality
MTF Signal Xpert is more than just an aggregation of existing indicators—it is an original synthesis designed to address real-world trading complexities. Here’s how its components work together:
Integrated Trend, Volatility, and Momentum Analysis:
By combining moving averages, Bollinger Bands, and multiple oscillators (RSI, MACD, AO, ADX, and an optional stochastic), the indicator captures diverse market dynamics. Each component reinforces the others, reducing noise and filtering out false signals.
Multi-Timeframe Analysis:
The inclusion of a higher timeframe filter aligns short-term signals with longer-term trends, enhancing overall reliability and reducing the potential for contradictory signals.
Adaptive Risk Management:
Dynamic stop loss and take profit levels, determined using ATR, ensure that the risk management strategy adapts to current market conditions. The optional trailing stop further refines this approach, protecting profits as the market evolves.
Quantitative Signal Scoring:
The condition weighting system provides an objective measure of signal strength, giving traders clear insight into how each technical component contributes to the final decision.
How to Use MTF Signal Xpert:
Input Customization:
Adjust the moving average type and period settings, ATR multipliers, and oscillator thresholds to align with your trading style and the specific market conditions.
Enable or disable the optional stochastic oscillator and trailing stop based on your preference.
Interpreting the Signals:
When a BUY or SELL signal appears, refer to the on‑chart dashboard, which displays key metrics (e.g., RSI, ADX, bullish/bearish scores) along with a detailed breakdown of the conditions that triggered the signal.
Review the SL and TP markers on the chart to understand the associated risk/reward setup.
Risk Management:
Use the dynamically calculated stop loss and take profit levels as guidelines for setting your exit points.
Evaluate the provided risk/reward ratio to ensure that the potential reward justifies the risk before entering a trade.
Debugging and Verification:
Advanced users can enable the debug table to see a condition-by-condition breakdown of the signal generation process, helping refine the strategy and deepen understanding of market dynamics.
Disclaimer:
MTF Signal Xpert is intended for educational and analytical purposes only. Although it is based on robust technical analysis methods and has undergone extensive backtesting, past performance is not indicative of future results. Traders should employ proper risk management and adjust the settings to suit their financial circumstances and risk tolerance.
MTF Signal Xpert represents a comprehensive, original approach to trading signal generation. By blending trend detection, volatility assessment, momentum analysis, multi-timeframe alignment, and adaptive risk management into one integrated system, it provides traders with actionable signals and the transparency needed to understand the logic behind them.
Day of Week Performance█ OVERVIEW
The Day of Week Performance indicator is designed to visualise and compare the cumulative percentage change for each day of the week. This indicator explores one of the many calendar based anomalies in financial markets.
In financial analysis, a calendar based anomaly refers to recurring patterns or tendencies associated with specific time periods, such as days of the week. By calculating the cumulative percentage change for each day (Monday through Friday) and displaying the results both graphically and in a summary table, this indicator helps identify whether certain days consistently outperform others.
█ FEATURES
Customisable time window via Time Settings.
Calculates cumulative percentage change for each day (Monday to Friday) separately.
Option to use Sunday instead of Friday for CFDs and Futures analysis.
Distinct visual representation for each day using unique colours.
Customisable table settings including position and font size.
Built-in error checks to ensure the indicator is applied on a Daily timeframe.
█ HOW TO USE
Add the indicator to a chart set to a Daily timeframe.
Select your desired Start Time and End Time in the Time Settings.
Toggle the performance table on or off in the Table Settings.
Adjust the table’s location and font size as needed.
Use the "Use Sunday instead of Friday" option if your market requires it.
View the cumulative performance plotted in distinct colours.
Colour Scheme:
Monday: Blue
Tuesday: Red
Wednesday: Green
Thursday: Orange
Friday: Purple
Uptrick: FRAMA Matrix RSIUptrick: FRAMA Matrix RSI
Introduction
The Uptrick: FRAMA Matrix RSI is a momentum-based indicator that integrates the Relative Strength Index (RSI) with the Fractal Adaptive Moving Average (FRAMA). By applying FRAMA's adaptive smoothing to RSI—and further refining it with a Zero-Lag Moving Average (ZLMA)—this script creates a refined and reliable momentum oscillator. The indicator now includes enhanced divergence detection, potential reversal signals, customizable buy/sell signal options, an internal stats table, and a fully customizable bar coloring system for an enhanced visual trading experience.
Why Combine RSI with FRAMA
Traditional RSI is a well-known momentum indicator but has several limitations. It is highly sensitive to price fluctuations, often generating false signals in choppy or volatile markets. FRAMA, in contrast, adapts dynamically to price changes by adjusting its smoothing factor based on market conditions.
By integrating FRAMA into RSI calculations, this indicator reduces noise while preserving RSI's ability to track momentum, adapts to volatility by reducing lag in trending markets and smoothing out choppiness in ranging conditions, enhances trend-following capability for more reliable momentum shifts, and refines overbought and oversold signals by adjusting to the current market structure.
With the new enhancements, such as a manual alpha input, noise filtering, divergence detection, and multiple buy/sell signal options, the indicator offers even greater flexibility and precision for traders. This combination improves the standard RSI by making it more adaptive and responsive to market changes.
Originality
This indicator is unique because it applies FRAMA's adaptive smoothing technique to RSI, creating a dynamic momentum oscillator that adjusts to different market conditions. Many traditional RSI-based indicators either use fixed smoothing methods like exponential moving averages or employ basic RSI calculations without adjusting for volatility.
This script stands out by integrating several elements, including the fractal dimension-based smoothing of FRAMA to reduce noise while retaining responsiveness, the use of Zero-Lag Moving Average smoothing to enhance trend sensitivity and reduce lag, divergence detection to highlight mismatches between price action and RSI momentum, a noise filter and manual alpha option to prevent minor fluctuations from generating false signals, customizable buy/sell signal options that let traders choose between ZLMA-based or FRAMA RSI-based signals, an internal stats table displaying real-time FRAMA calculations such as fractal dimension and the adaptive alpha factor, and a fully customizable bar coloring system to visually distinguish bullish, bearish, and neutral conditions.
Features
Adaptive FRAMA RSI
The indicator applies FRAMA to RSI values, making the momentum oscillator adaptive to volatility while filtering out noise. Unlike a traditional RSI that reacts equally to all price movements, FRAMA RSI adjusts its smoothing factor based on market structure, making it more effective for identifying true momentum shifts.
Zero-Lag Moving Average (ZLMA)
A smoothing technique that minimizes lag while preserving the responsiveness of price movements. It is applied to the FRAMA RSI to further refine signals and ensure smoother trend detection.
Bullish and Bearish Threshold Crossovers
This system compares FRAMA RSI to a user-defined threshold (default is 50). When FRAMA RSI moves above the threshold, it indicates bullish momentum, while movement below signals bearish conditions. The enhanced noise filter ensures that only significant moves trigger signals.
Noise Filter and Manual Alpha
A new noise filter input prevents tiny fluctuations from triggering false signals. In addition, a manual alpha option allows traders to override the automatically computed smoothing factor with a custom value, providing extra control over the indicator’s sensitivity.
Divergence Detection
The indicator identifies divergence patterns by comparing FRAMA RSI pivots to price action. Bullish divergence occurs when price makes a lower low while FRAMA RSI makes a higher low, and bearish divergence occurs when price makes a higher high while FRAMA RSI makes a lower high. These signals can help traders anticipate potential reversals.
Reversal Signals
Labels appear on the chart when FRAMA RSI confirms classic RSI overbought (70) or oversold (30) conditions, providing visual cues for potential trend reversals.
Buy and Sell Signal Options
Traders can now choose between two signal-generation methods. ZLMA-based signals trigger when the ZLMA of FRAMA RSI crosses key overbought (70) or oversold (30) levels, while FRAMA RSI-based signals trigger when FRAMA RSI itself crosses these levels. This added flexibility allows users to tailor the indicator to their preferred trading style.
ZLMA:
FRAMA:
Customizable Alerts
Alerts notify traders when FRAMA RSI crosses key levels, divergence signals occur, reversal conditions are met, or buy/sell signals trigger. This ensures that important trading events are not missed.
Fully Customizable Bar Coloring System
Users can color bars based on different conditions, enhancing visual clarity. Bar coloring modes include: FRAMA RSI threshold (bars change color based on whether FRAMA RSI is above or below the threshold), ZLMA crossover (bars change when ZLMA crosses overbought or oversold levels), buy/sell signals (bars change when official signals trigger), divergence (bars highlight when bullish or bearish divergence is detected), and reversals (bars indicate when RSI reaches overbought or oversold conditions confirmed by FRAMA RSI). The system also remembers the last applied bar color, ensuring a smooth visual transition.
Input Parameters and Features
Core Inputs
RSI Length (default: 14) defines the period for RSI calculations.
FRAMA Lookback (default: 16) determines the length for the FRAMA smoothing function.
RSI Bull Threshold (default: 50) sets the level above which the market is considered bullish and below which it is bearish.
Noise Filter (default: 1.0) ensures that small fluctuations do not trigger false bullish or bearish signals.
Additional Features
Show Bull and Bear Alerts (default: true) enables notifications when FRAMA RSI crosses the threshold.
Enable Divergence Detection (default: false) highlights bullish and bearish divergences based on price and FRAMA RSI pivots.
Show Potential Reversal Signals (default: false) identifies overbought (70) and oversold (30) levels as possible trend reversal points.
Buy and Sell Signal Option (default: ZLMA) allows traders to choose between ZLMA-based signals or FRAMA RSI-based signals for trade entry.
ZLMA Enhancements
ZLMA Length (default: 14) determines the period for the Zero-Lag Moving Average applied to FRAMA RSI.
Visualization Options
Show Internal Stats Table (default: false) displays real-time FRAMA calculations, including fractal dimension and the adaptive alpha smoothing factor.
Show Threshold FRAMA Signals (default: false) plots buy and sell labels when FRAMA RSI crosses the threshold level.
How It Works
FRAMA Calculation
FRAMA dynamically adjusts smoothing based on the price fractal dimension. The alpha smoothing factor is derived from the fractal dimension or can be set manually to maintain responsiveness.
RSI with FRAMA Smoothing
RSI is calculated using the user-defined lookback period. FRAMA is then applied to the RSI to make it more adaptive to volatility. Optionally, ZLMA is applied to further refine the signals and reduce lag.
Bullish and Bearish Threshold Crosses
A bullish condition occurs when FRAMA RSI crosses above the threshold, while a bearish condition occurs when it falls below. The noise filter ensures that only significant trend shifts generate signals.
Buy and Sell Signal Options
Traders can choose between ZLMA crossovers or FRAMA RSI crossovers as the basis for buy and sell signals, offering flexibility in trade entry timing.
Divergence Detection
The indicator identifies divergences where price action and FRAMA RSI momentum do not align, potentially signaling upcoming reversals.
Reversal Signal Labels
When classic RSI overbought or oversold levels are confirmed by FRAMA RSI conditions, reversal labels are added on the chart to highlight potential exhaustion points.
Bar Coloring System
Bars are dynamically colored based on various conditions such as RSI thresholds, ZLMA crossovers, buy/sell signals, divergence, and reversals, allowing traders to quickly interpret market sentiment.
Alerts and Internal Stats
Customizable alerts notify traders of key events, and an optional internal stats table displays real-time calculations (fractal dimension, alpha value, and RSI values) to help users understand the underlying dynamics of the indicator.
Summary
The Uptrick: FRAMA Matrix RSI offers an enhanced approach to momentum analysis by combining RSI with adaptive FRAMA smoothing and additional layers of signal refinement. The indicator now includes adaptive RSI smoothing to reduce noise and improve responsiveness, Zero-Lag Moving Average filtering to minimize lag, divergence and reversal detection to identify potential turning points, customizable buy/sell signal options that let traders choose between different signal methodologies, a fully customizable bar coloring system to visually distinguish market conditions, and an internal stats table for real-time insight into FRAMA calculation parameters.
Whether used for trend confirmation, divergence detection, or momentum-based strategies, this indicator provides a powerful and adaptive approach to trading.
Disclaimer
This script is for informational and educational purposes only. Trading involves risk, and past performance does not guarantee future results. Always conduct proper research and consult with a financial advisor before making trading decisions.
Multi-indicator Signal Builder [Skyrexio]Overview
Multi-Indicator Signal Builder is a versatile, all-in-one script designed to streamline your trading workflow by combining multiple popular technical indicators under a single roof. It features a single-entry, single-exit logic, intrabar stop-loss/take-profit handling, an optional time filter, a visually accessible condition table, and a built-in statistics label. Traders can choose any combination of 12+ indicators (RSI, Ultimate Oscillator, Bollinger %B, Moving Averages, ADX, Stochastic, MACD, PSAR, MFI, CCI, Heikin Ashi, and a “TV Screener” placeholder) to form entry or exit conditions. This script aims to simplify strategy creation and analysis, making it a powerful toolkit for technical traders.
Indicators Overview
1. RSI (Relative Strength Index)
Measures recent price changes to evaluate overbought or oversold conditions on a 0–100 scale.
2. Ultimate Oscillator (UO)
Uses weighted averages of three different timeframes, aiming to confirm price momentum while avoiding false divergences.
3. Bollinger %B
Expresses price relative to Bollinger Bands, indicating whether price is near the upper band (overbought) or lower band (oversold).
4. Moving Average (MA)
Smooths price data over a specified period. The script supports both SMA and EMA to help identify trend direction and potential crossovers.
5. ADX (Average Directional Index)
Gauges the strength of a trend (0–100). Higher ADX signals stronger momentum, while lower ADX indicates a weaker trend.
6. Stochastic
Compares a closing price to a price range over a given period to identify momentum shifts and potential reversals.
7. MACD (Moving Average Convergence/Divergence)
Tracks the difference between two EMAs plus a signal line, commonly used to spot momentum flips through crossovers.
8. PSAR (Parabolic SAR)
Plots a trailing stop-and-reverse dot that moves with the trend. Often used to signal potential reversals when price crosses PSAR.
9. MFI (Money Flow Index)
Similar to RSI but incorporates volume data. A reading above 80 can suggest overbought conditions, while below 20 may indicate oversold.
10. CCI (Commodity Channel Index)
Identifies cyclical trends or overbought/oversold levels by comparing current price to an average price over a set timeframe.
11. Heikin Ashi
A type of candlestick charting that filters out market noise. The script uses a streak-based approach (multiple consecutive bullish or bearish bars) to gauge mini-trends.
12. TV Screener
A placeholder condition designed to integrate external buy/sell logic (like a TradingView “Buy” or “Sell” rating). Users can override or reference external signals if desired.
Unique Features
1. Multi-Indicator Entry and Exit
You can selectively enable any subset of 12+ classic indicators, each with customizable parameters and conditions. A position opens only if all enabled entry conditions are met, and it closes only when all enabled exit conditions are satisfied, helping reduce false triggers.
2. Single-Entry / Single-Exit with Intrabar SL/TP
The script supports a single position at a time. Once a position is open, it monitors intrabar to see if the price hits your stop-loss or take-profit levels before the bar closes, making results more realistic for fast-moving markets.
3. Time Window Filter
Users may specify a start/end date range during which trades are allowed, making it convenient to focus on specific market cycles for backtesting or live trading.
4. Condition Table and Statistics
A table at the bottom of the chart lists all active entry/exit indicators. Upon each closed trade, an integrated statistics label displays net profit, total trades, win/loss count, average and median PnL, etc.
5. Seamless Alerts and Automation
Configure alerts in TradingView using “Any alert() function call.”
The script sends JSON alert messages you can route to your own webhook.
The indicator can be integrated with Skyrexio alert bots to automate execution on major cryptocurrency exchanges
6. Optional MA/PSAR Plots
For added visual clarity, optionally plot the chosen moving averages or PSAR on the chart to confirm signals without stacking multiple indicators.
Methodology
1. Multi-Indicator Entry Logic
When multiple entry indicators are enabled (e.g., RSI + Stochastic + MACD), the script requires all signals to align before generating an entry. Each indicator can be set for crossovers, crossunders, thresholds (above/below), etc. This “AND” logic aims to filter out low-confidence triggers.
2. Single-Entry Intrabar SL/TP
One Position At a Time: Once an entry signal triggers, a trade opens at the bar’s close.
Intrabar Checks: Stop-loss and take-profit levels (if enabled) are monitored on every tick. If either is reached, the position closes immediately, without waiting for the bar to end.
3. Exit Logic
All Conditions Must Agree: If the trade is still open (SL/TP not triggered), then all enabled exit indicators must confirm a closure before the script exits on the bar’s close.
4. Time Filter
Optional Trading Window: You can activate a date/time range to constrain entries and exits strictly to that interval.
Justification of Methodology
Indicator Confluence: Combining multiple tools (RSI, MACD, etc.) can reduce noise and false signals.
Intrabar SL/TP: Capturing real-time spikes or dips provides a more precise reflection of typical live trading scenarios.
Single-Entry Model: Straightforward for both manual and automated tracking (especially important in bridging to bots).
Custom Date Range: Helps refine backtesting for specific market conditions or to avoid known irregular data periods.
How to Use
1. Add the Script to Your Chart
In TradingView, open Indicators , search for “Multi-indicator Signal Builder”.
Click to add it to your chart.
2. Configure Inputs
Time Filter: Set a start and end date for trades.
Alerts Messages: Input any JSON or text payload needed by your external service or bot.
Entry Conditions: Enable and configure any indicators (e.g., RSI, MACD) for a confluence-based entry.
Close Conditions: Enable exit indicators, along with optional SL (negative %) and TP (positive %) levels.
3. Set Up Alerts
In TradingView, select “Create Alert” → Condition = “Any alert() function call” → choose this script.
Entry Alert: Triggers on the script’s entry signal.
Close Alert: Triggers on the script’s close signal (or if SL/TP is hit).
Skyrexio Alert Bots: You can route these alerts via webhook to Skyrexio alert bots to automate order execution on major crypto exchanges (or any other supported broker).
4. Visual Reference
A condition table at the bottom summarizes active signals.
Statistics Label updates automatically as trades are closed, showing PnL stats and distribution metrics.
Backtesting Guidelines
Symbol/Timeframe: Works on multiple assets and timeframes; always do thorough testing.
Realistic Costs: Adjust commissions and potential slippage to match typical exchange conditions.
Risk Management: If using the built-in stop-loss/take-profit, set percentages that reflect your personal risk tolerance.
Longer Test Horizons: Verify performance across diverse market cycles to gauge reliability.
Example of statistic calculation
Test Period: 2023-01-01 to 2025-12-31
Initial Capital: $1,000
Commission: 0.1%, Slippage ~5 ticks
Trade Count: 468 (varies by strategy conditions)
Win rate: 76% (varies by strategy conditions)
Net Profit: +96.17% (varies by strategy conditions)
Disclaimer
This indicator is provided strictly for informational and educational purposes .
It does not constitute financial or trading advice.
Past performance never guarantees future results.
Always test thoroughly in demo environments before using real capital.
Enjoy exploring the Multi-Indicator Signal Builder! Experiment with different indicator combinations and adjust parameters to align with your trading preferences, whether you trade manually or link your alerts to external automation services. Happy trading and stay safe!
