Massive Market Order Detector by GSK-VIZAG-AP-INDIA
Massive Market Order Detector by GSK-VIZAG-AP-INDIA
Purpose of the Indicator:
This indicator is designed to detect massive market orders (high-volume trades) in real-time, helping traders identify potential accumulation or distribution zones. It highlights sudden spikes in volume that exceed a calculated threshold, signaling strong buying or selling pressure.
Core Logic & Unique Aspects:
Volume Spike Detection: Compares the current volume to the average volume over a user-defined lookback period. If the volume exceeds the threshold (calculated using a multiplier), it is classified as a Massive Order.
Buy vs. Sell Order Identification: Determines whether the detected massive order is a buy (green marker) or a sell (red marker) based on candlestick price action.
Time Zone Adjustment: Allows traders to adjust the timestamp according to their local timezone, ensuring accurate interpretation of order timings.
Table Display of Recent Orders: A table is created within the chart to list the last 15 detected massive orders, showing key details such as time, volume, type (buy/sell), price, and volume percentage change.
How It Works:
The indicator calculates the average volume over a lookback period (default: 20 bars).
If the current volume exceeds the threshold (average volume × multiplier), it is marked as a Massive Order.
The order is classified as:
Massive Buy Order (MB) → If the closing price is higher than the opening price.
Massive Sell Order (MS) → If the closing price is lower than the opening price.
The detected orders are visually represented as green (MB) and red (MS) labels on the chart.
The most recent 15 massive orders are logged in a table for easy reference.
Intended Use Cases:
🔹 Scalping & Intraday Trading – Spot unusual market activity to enter or exit trades quickly.
🔹 Swing Trading – Identify strong buying or selling pressure at key support/resistance levels.
🔹 Breakout Confirmation – Validate if price breakouts are backed by significant volume.
🔹 Market Manipulation Detection – Recognize potential institutional buying/selling activity.
Input settings:
Lookback Period: Adjust the number of bars to calculate average volume.
Volume Multiplier: Set the threshold as 1/2/3 for defining a massive order.
Time Zone Offset: Modify timestamps to match your local market time.
Max Signals in Table: Control how many signals are displayed in the table.
Why Use This Indicator?
✅ Identifies smart money activity
✅ Works across multiple timeframes (5m, 15m, 1H, Daily, etc.)
✅ No repainting – Reliable real-time signals
✅ Easy-to-read visual cues & table logs
Disclaimer:
"This indicator is for educational and informational purposes only and should not be considered financial advice. Always do your own research (DYOR) and consult with a qualified financial professional before making investment decisions. Trading involves significant risk, and past performance does not guarantee future results. I am not a licensed financial advisor and hold no liability for any losses incurred. This indicator may not work in all market conditions, and results are based on backtesting or hypothetical scenarios. Use at your own discretion and ensure compliance with local regulations."
Statistics
Extreme Areas with MTF Screener by QTX Algo SystemsStatistically Extreme Areas with MTF Screener by QTX Algo Systems
Overview
This indicator is designed to automatically highlight zones where prices become statistically overextended, signaling potential reversal opportunities. Enhanced with a Multi Time Frame (MTF) Screener, it verifies these extremes across several timeframes for a comprehensive, multi-dimensional view of market conditions.
How It Works
Baseline Statistical Analysis:
The indicator establishes a baseline price range using historical data through a statistical percentile approach. This baseline reflects typical price extremes over time.
Volatility and Momentum Filters:
It incorporates a Bollinger Band Width Percentile (BBWP) to measure real-time volatility and combines this with a double‐smoothed SMI and a Price – Moving Average Ratio (PMARP) to assess short-term momentum. This dual-filter system ensures that signals are generated only when both volatility and momentum conditions are satisfied.
Directional Oscillator (BBO) Analysis:
A Bollinger Band Oscillator (BBO) is used to evaluate the slopes of the upper and lower bands, adding an extra layer of confirmation for identifying true market extremes.
MTF Screener Integration:
The added MTF Screener scans multiple timeframes, confirming that the statistically extreme conditions are not isolated events. This cross-verification provides a more robust signal, ensuring that the identified reversal zones are consistent across the market.
Customizable Visual Alerts:
The indicator allows for customizable color coding for various conditions (e.g., extreme low warnings, extreme high warnings, and potential reversals), offering clear, visual guidance for traders.
Why It’s Different and Valuable
This tool is more than just a simple merger of common indicators—it’s a carefully integrated system that validates price extremes across several dimensions. By combining statistical analysis with real-time volatility, momentum verification, and multi-timeframe confirmation, it provides a dynamic framework that helps traders identify high-probability reversal zones while minimizing false signals. The added MTF Screener ensures that these signals are consistent and reliable across different market views, enhancing the overall decision-making process.
How to Use
Monitor Visual Cues: Look for the color-coded signals that indicate statistically extreme price levels.
Confirm Across Timeframes: Use the MTF Screener component to ensure that the extreme conditions appear consistently across various timeframes.
Integrate with Your Strategy: Use this indicator alongside other technical tools to refine entry, exit, and stop-loss decisions.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading analysis. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and conduct your own analysis before trading.
Continuation Opportunity with MTF Screener by QTX Algo SystemsContinuation Opportunity Indicator with MTF Screener by QTX Algo Systems
Overview
This enhanced indicator is designed to pinpoint key moments when an established trend is likely to continue. By combining traditional momentum analysis with dual volatility measures—and now integrating a powerful Multi Time Frame (MTF) Screener—it offers a multi-dimensional view of trend behavior. This tool not only detects when a pullback is simply a temporary consolidation (characterized by reduced volatility) but also confirms that the overall trend is poised to resume, validated across several timeframes.
How It Works
Core Methodology:
The base indicator uses a double‐smoothed Stochastic Momentum Index (SMI) combined with a Price – Moving Average Ratio (PMARP) to detect momentum crossovers that signal trend continuation. It also uses volatility filters to ensure that the signals occur only when market activity is strong.
Dual Volatility Analysis:
A Bollinger Band Width Percentile (BBWP) measure and historical volatility metrics work together to ensure that only meaningful pullbacks trigger signals—distinguishing between noise and genuine consolidation.
MTF Screener Integration:
The new MTF Screener feature extends the analysis beyond a single timeframe. It scans multiple assets and timeframes concurrently, confirming that a detected pullback or resumption signal appears consistently across the broader market view. This cross-verification minimizes false signals and provides traders with confidence that the trend continuation is robust.
Enhanced Visual Cues:
Color-coded backgrounds and well-defined signal triggers help traders quickly interpret when a pullback is likely just a consolidation phase and when increased volatility signals the trend’s resumption.
Why It’s Different and Valuable
Unlike a simple combination of separate indicators, this tool integrates each element in a systematic, layered approach. The MTF Screener adds an extra dimension by validating signals across different timeframes—ensuring that traders are not basing decisions on isolated, potentially misleading data. This cohesive design enhances overall accuracy and provides actionable insights that are more robust than what individual indicators would offer on their own.
How to Use
Monitor Visual Signals: Look for color-coded cues and momentum crossovers that appear after a pullback.
Validate Across Timeframes: Use the MTF Screener’s output to confirm that the continuation signal is consistent across various timeframes.
Integrate with Other Tools: Combine these signals with your existing technical analysis methods to refine your entry and exit points.
Disclaimer
This indicator is provided for educational purposes only and is intended to support your trading analysis. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
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.
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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.
Multi-MA RibbonMulti-MA Ribbon is a dynamic and highly customizable indicator designed to visually compare and analyze up to 12 moving average bands simultaneously — across two different moving average (MA) types. This allows traders to study how various MAs behave relative to one another in real time, improving market analysis and trade precision.
The script supports EMA, SMA, HMA, RMA, WMA, VWMA, SWMA, and ALMA, with full user control over periods, ribbon thickness, color, and gradient direction.
Key Features:
Dual Moving Average Ribbon System — Compare two independent MA types side by side on the same price chart.
12 User-Defined Period Bands — Visualize short to long-term trend layers, fully adjustable.
Gradient Coloring with Direction Control — Choose whether fast or slow bands are brightest for quick visual focus.
Customizable Thickness and Colors — Adapt the visualization to fit any chart theme or preference.
Supports All Major MAs — Including EMA, SMA, HMA, RMA, WMA, VWMA, SWMA, ALMA.
Overlay-Friendly — Plots directly over price action for seamless market context.
Analytical and Statistical Value:
Visual Sensitivity Comparison: See how fast-reacting MAs (e.g., EMA, HMA) compare to slower, smoother MAs (e.g., SMA, ALMA) over the same periods — critical for understanding market momentum and lag.
Trend Strength and Consensus Detection: When two ribbons align tightly, the trend is strong and consistent; when they diverge, it signals potential reversal or market indecision.
Momentum Shift Identification: Fast MA ribbons breaking while slow MA ribbons hold indicate early momentum shifts or trap moves.
Trade Filtering and Confirmation: Only trade when both ribbons agree in direction, helping avoid false signals and improving entry/exit confidence.
Quantitative MA Efficiency Testing: Visually backtest and analyze which MA types work best for specific assets or strategies.
Use Cases:
Trend Following: Confirm trend strength by aligning both ribbons.
Reversal Anticipation: Spot divergence between ribbons as early reversal signals.
Momentum Trading: Use fast ribbons for early signals and slow ribbons for confirmation.
Breakout & Pullback Strategy: Analyze whether breakouts are sustained across different MA methodologies.
Backtesting and Optimization: Visually test combinations like EMA vs. HMA or VWMA vs. SMA to optimize strategies for specific assets.
Example MA Comparisons You Can Analyze:
Price Action vs. Volume-weighted: EMA vs. VWMA
Fast-reactive vs. Smooth: HMA vs. SMA
Minimal Lag vs. Standard: ALMA vs. EMA
Weighted vs. Wilder's (RMA): WMA vs. RMA
This is NOT:
A recommendation for what you should personally do.
Investment advice.
Intended solely for qualified investors.
Witchcraft or wizardry.
The only certainty is uncertainty
*Auto Backtest & Optimize EngineFull-featured Engine for Automatic Backtesting and parameter optimization. Allows you to test millions of different combinations of stop-loss and take profit parameters, including on any connected indicators.
⭕️ Key Futures
Quickly identify the optimal parameters for your strategy.
Automatically generate and test thousands of parameter combinations.
A simple Genetic Algorithm for result selection.
Saves time on manual testing of multiple parameters.
Detailed analysis, sorting, filtering and statistics of results.
Detailed control panel with many tooltips.
Display of key metrics: Profit, Win Rate, etc..
Comprehensive Strategy Score calculation.
In-depth analysis of the performance of different types of stop-losses.
Possibility to use to calculate the best Stop-Take parameters for your position.
Ability to test your own functions and signals.
Customizable visualization of results.
Flexible Stop-Loss Settings:
• Auto ━ Allows you to test all types of Stop Losses at once(listed below).
• S.VOLATY ━ Static stop based on volatility (Fixed, ATR, STDEV).
• Trailing ━ Classic trailing stop following the price.
• Fast Trail ━ Accelerated trailing stop that reacts faster to price movements.
• Volatility ━ Dynamic stop based on volatility indicators.
• Chandelier ━ Stop based on price extremes.
• Activator ━ Dynamic stop based on SAR.
• MA ━ Stop based on moving averages (9 different types).
• SAR ━ Parabolic SAR (Stop and Reverse).
Advanced Take-Profit Options:
• R:R: Risk/Reward ━ sets TP based on SL size.
• T.VOLATY ━ Calculation based on volatility indicators (Fixed, ATR, STDEV).
Testing Modes:
• Stops ━ Cyclical stop-loss testing
• Pivot Point Example ━ Example of using pivot points
• External Example ━ Built-in example how test functions with different parameters
• External Signal ━ Using external signals
⭕️ Usage
━ First Steps:
When opening, select any point on the chart. It will not affect anything until you turn on Manual Start mode (more on this below).
The chart will immediately show the best results of the default Auto mode. You can switch Part's to try to find even better results in the table.
Now you can display any result from the table on the chart by entering its ID in the settings.
Repeat steps 3-4 until you determine which type of Stop Loss you like best. Then set it in the settings instead of Auto mode.
* Example: I flipped through 14 parts before I liked the first result and entered its ID so I could visually evaluate it on the chart.
Then select the stop loss type, choose it in place of Auto mode and repeat steps 3-4 or immediately follow the recommendations of the algorithm.
Now the Genetic Algorithm at the bottom right will prompt you to enter the Parameters you need to search for and select even better results.
Parameters must be entered All at once before they are updated. Enter recommendations strictly in fields with the same names.
Repeat steps 5-6 until there are approximately 10 Part's left or as you like. And after that, easily pour through the remaining Parts and select the best parameters.
━ Example of the finished result.
━ Example of use with Takes
You can also test at the same time along with Take Profit. In this example, I simply enabled Risk/Reward mode and immediately specified in the TP field Maximum RR, Minimum RR and Step. So in this example I can test (3-1) / 0.1 = 20 Takes of different sizes. There are additional tips in the settings.
━
* Soon you will start to understand how the system works and things will become much easier.
* If something doesn't work, just reset the engine settings and start over again.
* Use the tips I have left in the settings and on the Panel.
━ Details:
Sort ━ Sorting results by Score, Profit, Trades, etc..
Filter ━ Filtring results by Score, Profit, Trades, etc..
Trade Type ━ Ability to disable Long\Short but only from statistics.
BackWin ━ Backtest Window Number of Candle the script can test.
Manual Start ━ Enabling it will allow you to call a Stop from a selected point. which you selected when you started the engine.
* If you have a real open position then this mode can help to save good Stop\Take for it.
1 - 9 Сheckboxs ━ Allow you to disable any stop from Auto mode.
Ex Source - Allow you to test Stops/Takes from connected indicators.
Connection guide:
//@version=6
indicator("My script")
rsi = ta.rsi(close, 14)
buy = not na(rsi) and ta.crossover (rsi, 40) // OS = 40
sell = not na(rsi) and ta.crossunder(rsi, 60) // OB = 60
Signal = buy ? +1 : sell ? -1 : 0
plot(Signal, "🔌Connector🔌", display = display.none)
* Format the signal for your indicator in a similar style and then select it in Ex Source.
⭕️ How it Works
Hypothesis of Uniform Distribution of Rare Elements After Mixing.
'This hypothesis states that if an array of N elements contains K valid elements, then after mixing, these valid elements will be approximately uniformly distributed.'
'This means that in a random sample of k elements, the proportion of valid elements should closely match their proportion in the original array, with some random variation.'
'According to the central limit theorem, repeated sampling will result in an average count of valid elements following a normal distribution.'
'This supports the assumption that the valid elements are evenly spread across the array.'
'To test this hypothesis, we can conduct an experiment:'
'Create an array of 1,000,000 elements.'
'Select 1,000 random elements (1%) for validation.'
'Shuffle the array and divide it into groups of 1,000 elements.'
'If the hypothesis holds, each group should contain, on average, 1~ valid element, with minor variations.'
* I'd like to attach more details to My hypothesis but it won't be very relevant here. Since this is a whole separate topic, I will leave the minimum part for understanding the engine.
Practical Application
To apply this hypothesis, I needed a way to generate and thoroughly mix numerous possible combinations. Within Pine, generating over 100,000 combinations presents significant challenges, and storing millions of combinations requires excessive resources.
I developed an efficient mechanism that generates combinations in random order to address these limitations. While conventional methods often produce duplicates or require generating a complete list first, my approach guarantees that the first 10% of possible combinations are both unique and well-distributed. Based on my hypothesis, this sampling is sufficient to determine optimal testing parameters.
Most generators and randomizers fail to accommodate both my hypothesis and Pine's constraints. My solution utilizes a simple Linear Congruential Generator (LCG) for pseudo-randomization, enhanced with prime numbers to increase entropy during generation. I pre-generate the entire parameter range and then apply systematic mixing. This approach, combined with a hybrid combinatorial array-filling technique with linear distribution, delivers excellent generation quality.
My engine can efficiently generate and verify 300 unique combinations per batch. Based on the above, to determine optimal values, only 10-20 Parts need to be manually scrolled through to find the appropriate value or range, eliminating the need for exhaustive testing of millions of parameter combinations.
For the Score statistic I applied all the same, generated a range of Weights, distributed them randomly for each type of statistic to avoid manual distribution.
Score ━ based on Trade, Profit, WinRate, Profit Factor, Drawdown, Sharpe & Sortino & Omega & Calmar Ratio.
⭕️ Notes
For attentive users, a little tricks :)
To save time, switch parts every 3 seconds without waiting for it to load. After 10-20 parts, stop and wait for loading. If the pause is correct, you can switch between the rest of the parts without loading, as they will be cached. This used to work without having to wait for a pause, but now it does slower. This will save a lot of time if you are going to do a deeper backtest.
Sometimes you'll get the error “The scripts take too long to execute.”
For a quick fix you just need to switch the TF or Ticker back and forth and most likely everything will load.
The error appears because of problems on the side of the site because the engine is very heavy. It can also appear if you set too long a period for testing in BackWin or use a heavy indicator for testing.
Manual Start - Allow you to Start you Result from any point. Which in turn can help you choose a good stop-stick for your real position.
* It took me half a year from idea to current realization. This seems to be one of the few ways to build something automatic in backtest format and in this particular Pine environment. There are already better projects in other languages, and they are created much easier and faster because there are no limitations except for personal PC. If you see solutions to improve this system I would be glad if you share the code. At the moment I am tired and will continue him not soon.
Also You can use my previosly big Backtest project with more manual settings(updated soon)
Clustering Volatility (ATR-ADR-ChaikinVol) [Sam SDF-Solutions]The Clustering Volatility indicator is designed to evaluate market volatility by combining three widely used measures: Average True Range (ATR), Average Daily Range (ADR), and the Chaikin Oscillator.
Each indicator is normalized using one of the available methods (MinMax, Rank, or Z-score) to create a unified metric called the Score. This Score is further smoothed with an Exponential Moving Average (EMA) to reduce noise and provide a clearer view of market conditions.
Key Features:
Multi-Indicator Integration: Combines ATR, ADR, and the Chaikin Oscillator into a single Score that reflects overall market volatility.
Flexible Normalization: (Supports three normalization methods)
MinMax: Scales values between the observed minimum and maximum.
Rank: Normalizes based on the relative rank within a moving window.
Z-score: Standardizes values using mean and standard deviation.
Dynamic Window Selection: Offers an automatic window selection option based on a specified lookback period, or a fixed window size can be used.
Customizable Weights: Allows the user to assign individual weights to ATR, ADR, and the Chaikin Oscillator. Optionally, weights can be normalized to sum to 1.
Score Smoothing: Applies an EMA to the computed Score to smooth out short-term fluctuations and reduce market noise.
Cluster Visualization: Divides the smoothed Score into a number of clusters, each represented by a distinct color. These colors can be applied to the price bars (if enabled) for an immediate visual indication of the current volatility regime.
How It Works:
Input & Window Setup: Users set parameters for indicator periods, normalization methods, weights, and window size. The indicator can automatically determine the analysis window based on the number of lookback days.
Calculation of Metrics: The indicator computes the ATR, ADR (as the average of bar ranges), and the Chaikin Oscillator (based on the difference between short and long EMAs of the Accumulation/Distribution line).
Normalization & Scoring: Each indicator’s value is normalized and then weighted to form a raw Score. This raw Score is scaled to a range using statistics from the chosen window.
Smoothing & Clustering: The raw Score is smoothed using an EMA. The resulting smoothed Score is then multiplied by the number of clusters to assign a cluster index, which is used to choose a color for visual signals.
Visualization: The smoothed Score is plotted on the chart with a color that changes based on its value (e.g., lime for low, red for high, yellow for intermediate values). Optionally, the price bars are colored according to the assigned cluster.
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This indicator is ideal for traders seeking a quick and clear assessment of market volatility. By integrating multiple volatility measures into one comprehensive Score, it simplifies analysis and aids in making more informed trading decisions.
For more detailed instructions, please refer to the guide here:
Statistically Extreme Areas by QTX Algo SystemsStatistically Extreme Areas by QTX Algo Systems
Overview
This indicator helps traders pinpoint potential reversal zones by detecting when prices become statistically overextended. By combining advanced statistical analysis with volatility and momentum metrics—including BBWP, SMI, PMARP, and Bollinger Band Oscillator (BBO) slope analysis—it provides clear visual cues for identifying market extremes and managing risk.
How It Works
Baseline Statistical Calculation:
The indicator starts by establishing a baseline price range using historical data through a statistical percentile approach. This captures the typical extremes over a significant period and forms the foundation for further analysis.
Volatility Adjustment:
A Bollinger Band Width Percentile (BBWP) measure is used to assess recent price variability. This dynamic volatility factor adjusts the baseline, ensuring that signals are only generated when overall market volatility exceeds a minimum threshold.
Momentum and Trend Verification:
A double‐smoothed Stochastic Momentum Index (SMI) captures short-term momentum, while a Price – Moving Average Ratio (PMARP) confirms the prevailing trend's strength. Additionally, a Bollinger Band Oscillator (BBO) calculates the slopes of the upper and lower bands to further refine the detection of extreme conditions without relying solely on a simple mashup of standard indicators.
Why It's Different
Rather than merely merging common indicators, this tool integrates distinct layers of analysis to produce a cohesive and dynamic framework. The synthesis of statistical extremes, real-time volatility adjustments, and momentum/trend verification helps filter out noise and false signals, offering traders a robust method to identify reversal zones and set precise stop-loss levels. This multi-dimensional approach delivers actionable insights that go beyond what traditional support/resistance or momentum indicators can offer on their own.
How to Use
Interpret the Visual Cues:
Watch for the color-coded background changes that signal statistically extreme conditions.
Integrate with Your Analysis:
Use these visual alerts alongside other technical tools to refine your entry and exit decisions and to enhance your overall risk management.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading analysis. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
Statistical Price Bands with Trend Filtering by QTX Algo SystemsStatistical Price Bands with Trend Filtering by QTX Algo Systems
Overview
This indicator generates adaptive support and resistance bands by fusing statistical analysis with real-time volatility and trend measurements. It highlights areas where prices appear overextended, providing traders with clear visual cues for potential reversals or risk management adjustments.
How It Works
Baseline Statistical Calculation:
The indicator begins by deriving a baseline price range from historical data using a statistical percentile approach. This percentile reflects the typical extremes observed over a significant period, forming the foundation for the bands.
Volatility Adjustment:
A dynamic volatility factor is then calculated by comparing the moving standard deviation of price to its moving average. This factor adjusts the baseline, ensuring that the bands reflect current market variability. The use of both a long-term dispersion measure and a short-term percentile-based volatility metric helps confirm that overall market volatility remains above a minimum threshold.
Trend Filtering:
In parallel, the indicator assesses trend direction by comparing the current price to a volume-weighted moving average (VWMA). This trend component shifts the bands in the direction of the prevailing market bias—moving the bands upward during uptrends and downward during downtrends.
Why It’s Different
Unlike traditional static support/resistance tools, this indicator integrates multiple layers of analysis—statistical extremes, real-time volatility, and trend direction—to create bands that continuously adapt to market conditions. This synthesis produces a dynamic framework that not only identifies potential overextended price areas but also provides practical stop loss levels, setting it apart from other basic band or moving average models.
How to Use
Customize the baseline statistical setting to match your trading style. Use the dynamically adjusted bands as visual cues for potential reversal zones or as guides for setting stop losses. Combine these insights with other technical tools to refine your entry and exit decisions.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading strategy. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
Volatility Based SMI with Dynamic Bands by QTX Algo SystemsVolatility Based SMI with Dynamic Bands by QTX Algo Systems
Overview
This advanced oscillator redefines the classic Stochastic Momentum Index (SMI) by incorporating adaptive volatility scaling and dynamically tilting its overbought and oversold levels based on market trends. The result is a context-sensitive momentum tool that adjusts its thresholds in real time, helping traders identify potential reversals or trend continuations more effectively.
How It Works
Enhanced SMI Calculation:
The indicator starts by computing a double‐smoothed SMI. Two layers of exponential moving averages—controlled by the “Smoothing K” and “Smoothing D” inputs—are applied to both the relative price range and the overall range (difference between the highest high and lowest low) over a fixed period. This process reduces short-term noise and isolates the underlying momentum.
Adaptive Volatility Scaling:
A normalized volatility measure is derived using a fixed Bollinger Band Width Percentile (BBWP) approach. This volatility metric is used to create an adaptive adjustment factor that scales the SMI, ensuring that the oscillator’s sensitivity reflects current market conditions without being distorted by temporary extremes.
Dynamic Threshold Adjustment:
The indicator then calculates trend strength using a lookback period (set by the “Trend Lookback Period” input) that compares the current price to a volume-weighted moving average (VWMA). This trend strength is used to adjust the base overbought and oversold levels (fixed at 50 and –50) through two mechanisms:
Band Tilt Strengths:
The “Upper Band Tilt Strength” and “Lower Band Tilt Strength” inputs determine how aggressively the respective thresholds are shifted in response to the prevailing trend. In an uptrend, for example, the oversold level is raised more noticeably, while in a downtrend, the overbought level is lowered.
Opposite Band Compression:
The “Opposite Band Compression Strength” input further refines this adjustment by accelerating the contraction of the opposite band during trend reversals, enhancing the indicator’s responsiveness.
How to Use and Input Adjustments
Smoothing K & Smoothing D:
Adjust these to control the degree of smoothing in the SMI calculation. Lower values provide quicker, albeit noisier, responses, while higher values yield smoother signals.
SMI EMA Length:
This sets the sensitivity of the moving average applied to the SMI, affecting how promptly crossover signals are generated.
Trend Lookback Period:
Defines the historical window for assessing trend strength. A longer period gives a more stable trend, while a shorter period increases responsiveness.
Upper/Lower Band Tilt Strength:
These parameters determine how much the overbought and oversold levels shift in response to the market’s trend. Increasing these values results in more pronounced threshold adjustments.
Opposite Band Compression Strength:
This setting influences how quickly the opposite band compresses during trend reversals, thereby fine-tuning the dynamic nature of the oscillator’s thresholds.
What Makes It Proprietary
Traditional SMI indicators typically rely on fixed thresholds for overbought and oversold conditions. Our approach is proprietary because it seamlessly integrates adaptive volatility scaling with dynamic, trend-based threshold adjustments. This fusion produces an oscillator that is acutely sensitive to current market conditions, offering a more nuanced and context-aware view of momentum that stands apart from conventional methods.
How to Use
Monitor the oscillator for crossovers between the SMI and its EMA, which serve as potential signals for reversals or confirmations of trend continuation. Fine-tune the input parameters to match your market conditions and trading style, and use the dynamically adjusted thresholds in conjunction with other technical analysis tools to refine your entry and exit decisions.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading strategy. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
CAM| Bar volatility and statsCAPRICORN ASSETS MANAGEMENT
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CAM | Bar Volatility and Stats Indicator
The CAM | Bar Volatility and Stats indicator is designed to track historical price movements, analyzing bar volatility and key statistical trends in financial instruments. By evaluating past bars, it provides insights into market dynamics, helping traders assess volatility, trend strength, and momentum patterns.
Key Features & Functionality:
✅ Volatility Analysis – Measures historical volatility by calculating the average price range per bar and displaying it in pips.
✅ Bull & Bear Bar Statistics – Tracks the number of bullish and bearish bars within a given lookback period, including their respective percentages.
✅ Consecutive Bar Sequences – Identifies and records the longest streaks of consecutive bullish or bearish bars, providing insights into market trends.
✅ Average Volatility by Trend – Computes separate volatility values for bullish and bearish bars, helping traders understand trend-based price behavior.
✅ Real-Time Labeling – Displays a live statistics summary directly on the chart, updating dynamically with each new bar.
Benefits for Traders:
📊 Enhanced Market Insight – Quickly assess market conditions, determining whether volatility is increasing or decreasing.
📈 Trend Strength Identification – Identify strong bullish or bearish sequences to improve trade timing and strategy development.
⏳ Better Risk Management – Use historical volatility metrics to fine-tune stop-loss and take-profit levels.
🛠 Customizable Analysis – Adjustable lookback period and display options allow traders to focus on the data that matters most.
This indicator is an essential tool for traders looking to refine their decision-making process by leveraging volatility-based statistics. Whether trading Forex, stocks, or commodities, it provides valuable insights into price action trends and market conditions.
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Broad Market MOEX### **Broad Market for Russia**
The **Broad Market for Russia** indicator provides a comparative analysis of the price deviation of major Russian stocks relative to their average closing price over a customizable lookback period. This tool helps traders identify market trends and detect relative strength or weakness among different assets.
### **How It Works:**
- The indicator calculates the **percentage deviation** of each stock’s current price from its **simple moving average (SMA)** over the defined **lookback period (in hours).**
- The **default lookback period is 24 hours**, but it can be adjusted based on the trader’s needs.
- It tracks major Russian assets, including **Gazprom, Sberbank, Lukoil, Rosneft, Norilsk Nickel, Yandex, and others**, alongside the currently selected instrument.
- Each stock’s deviation is plotted on a separate panel, allowing for quick visual comparison.
- **Positive deviation** indicates that the price is trading above its average, signaling potential **bullish momentum**.
- **Negative deviation** suggests the price is below its average, possibly indicating **bearish conditions**.
This indicator is particularly useful for traders in the Russian stock market who want to gauge broader market strength and detect divergence patterns across multiple assets.
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### **Broad Market for Russia**
Индикатор **Broad Market for Russia** предоставляет сравнительный анализ отклонения цены крупнейших российских акций относительно их среднего значения за настраиваемый период. Этот инструмент помогает трейдерам выявлять рыночные тренды и определять относительную силу или слабость активов.
### **Как это работает:**
- Индикатор рассчитывает **процентное отклонение** текущей цены каждой акции от её **простого скользящего среднего (SMA)** за заданный **период анализа (в часах).**
- **Период анализа по умолчанию — 24 часа**, но его можно изменять в зависимости от предпочтений трейдера.
- В индикаторе отслеживаются **крупнейшие российские активы**, такие как **Газпром, Сбербанк, Лукойл, Роснефть, Норникель, Яндекс и другие**, а также текущий выбранный инструмент.
- Отклонение каждой акции отображается на отдельной панели, что позволяет быстро проводить визуальное сравнение.
- **Положительное отклонение** означает, что цена торгуется выше своего среднего значения, что может сигнализировать о **бычьем тренде**.
- **Отрицательное отклонение** указывает, что цена ниже своего среднего значения, что может свидетельствовать о **медвежьей тенденции**.
Этот индикатор особенно полезен для трейдеров российского фондового рынка, которые хотят оценить силу всего рынка и выявлять расхождения между различными активами.
Broad Market for Crypto**Broad Market for Crypto** indicator provides a comparative analysis of the price deviation of multiple major cryptocurrencies relative to their average closing price over a customizable lookback period. This tool helps traders identify market trends and spot relative strength or weakness among different assets.
### **How It Works:**
- The indicator calculates the percentage deviation of each cryptocurrency’s current price from its simple moving average (SMA) over the defined **lookback period (in hours).**
- The **default lookback period is 24 hours**, but it can be adjusted according to the trader's preference.
- It tracks major crypto assets, including **BTC, ETH, BNB, SOL, XRP, ADA, AVAX, LINK, DOGE, and TRX**, alongside the currently selected instrument.
- Each cryptocurrency’s deviation is plotted on a separate panel, allowing for quick visual comparison.
- Positive deviation indicates that the price is trading above its average, signaling potential bullish momentum.
- Negative deviation suggests the price is below its average, possibly indicating bearish conditions.
This indicator is particularly useful for crypto traders who want to gauge the broader market’s strength and detect divergence patterns across multiple assets.
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**Broad Market for Crypto - Описание индикатора**
Индикатор **Broad Market for Crypto** предоставляет сравнительный анализ отклонения цены различных крупных криптовалют относительно их среднего значения за настраиваемый период. Этот инструмент помогает трейдерам выявлять рыночные тренды и определять относительную силу или слабость активов.
### **Как это работает:**
- Индикатор рассчитывает **процентное отклонение** текущей цены каждой криптовалюты от её **простого скользящего среднего (SMA)** за заданный **период анализа (в часах)**.
- **Период анализа по умолчанию — 24 часа**, но его можно изменять в зависимости от предпочтений трейдера.
- В индикаторе отслеживаются основные криптоактивы: **BTC, ETH, BNB, SOL, XRP, ADA, AVAX, LINK, DOGE и TRX**, а также текущий выбранный инструмент.
- Отклонение каждой криптовалюты отображается на отдельной панели, что позволяет быстро проводить визуальное сравнение.
- **Положительное отклонение** означает, что цена торгуется выше своего среднего значения, что может сигнализировать о **бычьем тренде**.
- **Отрицательное отклонение** указывает, что цена ниже своего среднего значения, что может свидетельствовать о **медвежьей тенденции**.
Этот индикатор особенно полезен для криптотрейдеров, желающих оценить силу всего рынка и выявлять расхождения между различными активами.
Round NumbersTries to only show major round numbers regardless of whether you're looking at something priced in the thousands or under a dollar.
Relative Strength RatioWhen comparing a stock’s strength against NIFTY 50, the Relative Strength (RS) is calculated to measure how the stock is performing relative to the index. This is different from the RSI but is often used alongside it.
How It Works:
Relative Strength (RS) Calculation:
𝑅
𝑆
=
Stock Price
NIFTY 50 Price
RS=
NIFTY 50 Price
Stock Price
This shows how a stock is performing relative to the NIFTY 50 index.
Relative Strength Ratio Over Time:
If the RS value is increasing, the stock is outperforming NIFTY 50.
If the RS value is decreasing, the stock is underperforming NIFTY 50.
Liquidity Depth [AlgoAlpha]OVERVIEW
This script visualizes market liquidity by identifying key price levels where significant volume has transacted. It highlights zones of high buying and selling interest, helping traders understand where liquidity is accumulating and how price may respond to these areas. By dynamically tracking volume at highs and lows, the script builds a real-time liquidity profile, making it a powerful tool for identifying potential support and resistance levels.
CONCEPTS
Liquidity depth analysis helps traders determine how price interacts with supply and demand at different levels. The script processes historical volume data to distinguish between high-liquidity and low-liquidity zones. It assigns transparency levels to plotted lines , ensuring that more relevant liquidity areas stand out visually. The script adds a profile to show the depth of liquidity (derived from historical volume data) for levels above and below the current price
FEATURES
Liquidity Levels: Tracks liquidity levels based on volume concentration at price high and lows.
Volume-Based Transparency: More significant liquidity levels are displayed with higher visibility, showing their significance.
Interpolation: interpolates the bullish and bearish liquidity depth at a user defined range away from the price, helping in comparing the liquidity amounts between bullish and bearish.
Depth Profile: Allows traders to visualize depth of liquidity in a more quantitative and clearer way than the liquidity levels/list]
USAGE
This indicator is best used to track liquidity levels and potential price reaction areas. Traders can adjust the Liquidity Lookback setting to analyze past liquidity levels over different historical periods. The Profile Resolution setting controls the granularity of liquidity depth visualization, with higher values providing more detail. The script can be applied across different timeframes, from intraday scalping to swing trading analysis. The plotted liquidity zones provide traders with insights into where price may encounter strong support, resistance, or potential liquidity-driven reversals.
PnL MonitorThe PnL Monitor is a customizable tool designed to help traders track the Profit and Loss (PnL) of up to 20 currency pairs or assets in real-time. This script provides a clear and organized table that displays the entry price, and PnL percentage for each pair, making it an essential tool for monitoring open positions or tracking potential trades.
Key Features:
Multi-Asset Tracking:
Monitor up to 20 currency pairs or assets simultaneously. Simply input the pair symbol and your entry price, and the script will calculate the PnL in real-time.
Dynamic Table Positioning:
Choose where the table appears on your chart with the Table Position input. Options include:
Top Left
Top Right
Bottom Left
Bottom Right
Real-Time PnL Calculation:
The script fetches the current price of each pair and calculates the PnL percentage based on your entry price. Positive PnL is highlighted in green, while negative PnL is highlighted in red.
Exchange and Pair Separation:
The script automatically separates the exchange name (if provided) from the pair symbol, making it easier to identify the source of the data.
Customizable Inputs:
Add or remove pairs as needed.
Leave the price field blank for pairs you don’t want to track.
How to Use:
Input Your Pairs:
In the script settings, input the symbol of the pair (e.g., NASDAQ:AAPL or BTCUSD) and your entry price. Leave the price field blank for pairs you don’t want to track.
Choose Table Position:
Select where you want the table to appear on your chart.
Monitor PnL:
The table will automatically update with the current price and PnL percentage for each pair.
Why Use This Script?
Efficiency: Track multiple pairs in one place without switching charts.
Clarity: Easily identify profitable and losing positions at a glance.
Flexibility: Customize the table to fit your trading style and preferences.
Ideal For:
Forex, crypto, and stock traders managing multiple positions.
Uptrick: Portfolio Allocation DiversificationIntro
The Uptrick: Portfolio Allocation Diversification script is designed to help traders and investors manage multiple assets simultaneously. It generates signals based on various trading systems, allocates capital using different diversification methods, and displays real-time metrics and performance tables on the chart. The indicator compares active trading strategies with a separate long-term holding (HODL) simulation, allowing you to see how a systematic trading approach stacks up against a simple buy-and-hold strategy.
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Trading System Selection
1. No signals (none)
In this mode, the script does not produce bullish or bearish indicators; every asset stays in a neutral stance. This setup is useful if you prefer to observe how capital might be distributed based solely on the chosen diversification method, with no influence from directional signals.
2. rsi – neutral
This mode uses an index-based measure of whether an asset appears overbought or oversold. It generates a bearish signal if market conditions point to overbought territory, and a bullish signal if they indicate oversold territory. If neither extreme surfaces, it remains neutral. Some traders apply this in sideways or range-bound conditions, where overbought and oversold levels often hint at possible turning points. It does not specifically account for divergence patterns.
3. rsi – long only
In this setting, the system watches for instances where momentum readings strengthen even if the asset’s price is still under pressure or setting new lows. It also considers oversold levels as potential signals for a bullish setup. When such conditions emerge, the script flags a possible move to the upside, ignoring indications that might otherwise suggest a bearish trend. This approach is generally favored by those who want to concentrate exclusively on identifying price recoveries.
4. rsi – short only
Here, the script focuses on spotting signs of deteriorating momentum while an asset’s price remains relatively high or attempts further gains. It also checks whether the market is drifting into overbought territory, suggesting a potential decline. Under such conditions, it issues a bearish signal. It provides no bullish alerts, making it particularly suitable for traders who look to take advantage of overvalued scenarios or protect themselves against sudden downward moves.
5. Deviation from fair value
Under this system, the script judges how far the current price may have strayed from what is considered typical, taking into account normal fluctuations. If the asset appears to be trading at an unusually low level compared to that reference, it is flagged as bullish. If it seems abnormally high, a bearish signal is issued. This can be applied in various market environments to seek opportunities that arise from perceived mispricing.
6. Percentile channel valuation
In this mode, the script determines where an asset's price stands within a historical distribution, highlighting whether it has reached unusually high or low territory compared to its recent past. When the price reaches what is deemed an extreme reading, it may indicate that a reversal is more likely. This approach is often used by traders who watch for statistical outliers and potential reversion to a more typical trading range.
7. ATH valuation
This technique involves comparing an asset's current price with its previously recorded peak values. The script then interprets whether the price is positioned so far below the all-time high that it looks discounted, or so close to that high that it could be overextended. Such perspective is favored by market participants who want to see if an asset still has ample room to climb before matching historic extremes, or if it is nearing a possible ceiling.
8. Z-score system
Here, the script measures how far above or below a standard reference average an asset's price may be, translated into standardized units. Substantial negative readings can suggest a price that might be unusually weak, prompting a bullish indication, while large positive readings could signal overextension and lead to a bearish call. This method is useful for traders watching for abrupt deviations from a norm that often invite a reversion to more balanced levels.
RSI Divergence Period
This input is particularly relevant for the RSI - Long Only and RSI - Short Only modes. The period determines how many bars in the past you compare RSI values to detect any divergences.
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Diversification Method
Once the script has determined a bullish, bearish, or neutral stance for each asset, it then calculates how to distribute capital among all included assets. The diversification method sets the weighting logic.
1. None
Gives each asset an equal weight. For example, if you have five included assets, each might get 20 percent. This is a simple baseline.
2. Risk-Adjusted Expected Return Using Volatility Clustering
Emphasizes each asset’s average returns relative to its observed risk or volatility tendencies. Assets that exhibit good risk-adjusted returns combined with moderate or lower volatility may receive higher weights than more volatile or less appealing assets. This helps steer capital toward assets that have historically provided a better ratio of return to risk.
3. Relative Strength
Allocates more capital to assets that show stronger price strength compared to a reference (for example, price above a long-term moving average plus a higher RSI). Assets in clear uptrends may be given higher allocations.
4. Trend-Following Indicators
Examines trend-based signals, like positive momentum measurements or upward-trending strength indicators, to assign more weight to assets demonstrating strong directional moves. This suits those who prefer to latch onto trending markets.
5. Volatility-Adjusted Momentum
Looks for assets that have strong price momentum but relatively subdued volatility. The script tends to reward assets that are trending well yet are not too volatile, aiming for stable upward performance rather than massive swings.
6. Correlation-Based Risk Parity
Attempts to weight assets in such a way that the overall portfolio risk is more balanced. Although it is not an advanced correlation matrix approach in a strict sense, it conceptually scales each asset’s weight so no single outlier heavily dominates.
7. Omega Ratio Maximization
Gives preference to assets with higher omega ratios. This ratio can be interpreted as the probability-weighted gains versus losses. Assets with a favorable skew are given more capital.
8. Liquidity-Weighted Valuation
Considers each asset’s average trading liquidity, such as the combination of volume and price. More liquid assets typically receive a higher allocation because they can be entered or exited with lower slippage. If the trading system signals bullishness, that can further boost the allocation, and if it signals bearishness, the allocation might be set to zero or reduced drastically.
9. Drawdown-Controlled Allocation (DCA)
Examines each asset’s maximum drawdown over a recent window. Assets experiencing lighter drawdowns (thus indicating somewhat less downside volatility) receive higher allocations, aiming for a smoother overall equity curve.
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Portfolio and Allocation Settings
Portfolio Value
Defines how much total capital is available for the strategy-based investment portion. For example, if set to 10,000, then each asset’s monetary allocation is determined by the percentage weighting times 10,000.
Use Fixed Allocation
When enabled, the script calculates the initial allocation percentages after 50 bars of data have passed. It then locks those percentages for the remainder of the backtest or real-time session. This feature allows traders to test a static weighting scenario to see how it differs from recalculating weights at each bar.
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HODL Simulator
The script has a separate simulation that accumulates positions in an asset whenever it appears to be recovering from an undervalued state. This parallel tracking is intended to contrast a simple buy-and-hold approach with the more adaptive allocation methods used elsewhere in the script.
HODL Buy Quantity
Each time an asset transitions from an undervalued state to a recovery phase, the simulator executes a purchase of a predefined quantity. For example, if set to 0.5 units, the system will accumulate this amount whenever conditions indicate a shift away from undervaluation.
HODL Buy Threshold
This parameter determines the level at which the simulation identifies an asset as transitioning out of an undervalued state. When the asset moves above this threshold after previously being classified as undervalued, a buy order is triggered. Over time, the performance of these accumulated positions is tracked, allowing for a comparison between this passive accumulation method and the more dynamic allocation strategy.
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Asset Table and Display Settings
The script displays data in multiple tables directly on your chart. You can toggle these tables on or off and position them in various corners of your TradingView screen.
Asset Info Table Position
This table provides key details for each included asset, displaying:
Symbol – Identifies the trading pair being monitored. This helps users keep track of which assets are included in the portfolio allocation process.
Current Trading Signal – Indicates whether the asset is in a bullish, bearish, or neutral state based on the selected trading system. This assists in quickly identifying which assets are showing potential trade opportunities.
Volatility Approximation – Represents the asset’s historical price fluctuations. Higher volatility suggests greater price swings, which can impact risk management and position sizing.
Liquidity Estimate – Reflects the asset’s market liquidity, often based on trading volume and price activity. More liquid assets tend to have lower transaction costs and reduced slippage, making them more favorable for active strategies.
Risk-Adjusted Return Value – Measures the asset’s returns relative to its risk level. This helps in determining whether an asset is generating efficient returns for the level of volatility it experiences, which is useful when making allocation decisions.
2. Strategy Allocation Table Position
Displays how your selected diversification method converts each asset into an allocation percentage. It also shows how much capital is being invested per asset, the cumulative return, standard performance metrics (for example, Sharpe ratio), and the separate HODL return percentage.
Symbol – Displays the asset being analyzed, ensuring clarity in allocation distribution.
Allocation Percentage – Represents the proportion of total capital assigned to each asset. This value is determined by the selected diversification method and helps traders understand how funds are distributed within the portfolio.
Investment Amount – Converts the allocation percentage into a dollar value based on the total portfolio size. This shows the exact amount being invested in each asset.
Cumulative Return – Tracks the total return of each asset over time, reflecting how well it has performed since the strategy began.
Sharpe Ratio – Evaluates the asset’s return in relation to its risk by comparing excess returns to volatility. A higher Sharpe ratio suggests a more favorable risk-adjusted performance.
Sortino Ratio – Similar to the Sharpe ratio, but focuses only on downside risk, making it more relevant for traders who prioritize minimizing losses.
Omega Ratio – Compares the probability of achieving gains versus losses, helping to assess whether an asset provides an attractive risk-reward balance.
Maximum Drawdown – Measures the largest percentage decline from an asset’s peak value to its lowest point. This metric helps traders understand the worst-case loss scenario.
HODL Return Percentage – Displays the hypothetical return if the asset had been bought and held instead of traded actively, offering a direct comparison between passive accumulation and the active strategy.
3. Profit Table
If the Profit Table is activated, it provides a summary of the actual dollar-based gains or losses for each asset and calculates the overall profit of the system. This table includes separate columns for profit excluding HODL and the combined total when HODL gains are included. As seen in the image below, this allows users to compare the performance of the active strategy against a passive buy-and-hold approach. The HODL profit percentage is derived from the Portfolio Value input, ensuring a clear comparison of accumulated returns.
4. Best Performing Asset Table
Focuses on the single highest-returning or highest-profit asset at that moment. It highlights the symbol, the asset’s cumulative returns, risk metrics, and other relevant stats. This helps identify which asset is currently outperforming the rest.
5. Most Profitable Asset
A simpler table that underscores the asset producing the highest absolute dollar profit across the portfolio.
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Multi Asset Selection
You can include up to ten different assets (such as BTCUSDT, ETHUSDT, ADAUSDT, and so on) in this script. Each asset has two inputs: one to enable or disable its inclusion, and another to select its trading pair symbol. Once you enable an asset, the script requests the relevant market data from TradingView.
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Uniqness and Features
1. Multiple Data Fetches
Each asset is pulled from the chart’s timeframe, along with various metrics such as RSI, volatility approximations, and trend indicators.
2. Various Risk and Performance Metrics
The script internally keeps track of different measures, like Sharpe ratio (a measure of average return adjusted for risk), Sortino ratio (which focuses on downside volatility), Omega ratio, and maximum drawdown. These metrics feed into the strategy allocation table, helping you quickly assess the risk-and-return profile of each asset.
3. Real-Time Tables
Instead of having to set up complex spreadsheets or external dashboards, the script updates all tables on every new bar. The color schemes in these tables are designed to draw attention to bullish or bearish signals, positive or negative returns, and so forth.
4. HODL Comparison
You can visually compare the active strategy’s results to a separate continuous buy-on-dips accumulation strategy. This allows for insight into whether your dynamic approach truly beats a simpler, more patient method.
5. Locking Allocations
The Use Fixed Allocation input is convenient for those who want to see how holding a fixed distribution of capital performs over time. It helps in distinguishing between constant rebalancing vs a fixed, set-and-forget style.
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How to use
1. Add the Script to Your Chart
Once added, open the settings panel to configure your asset list, choose a trading system, and select the diversification approach.
2. Select Assets
Pick up to ten symbols to monitor. Disable any you do not want included. Each included asset is then handled for signals, diversification, and performance metrics.
3. Choose Trading System
Decide if you prefer RSI-based signals, a fair-value approach, or a percentile-based method, among others. The script will then flag assets as bullish, bearish, or neutral according to that selection.
4. Pick a Diversification Method
For example, you might choose Trend-Following Indicators if you believe momentum stocks or cryptocurrencies will continue their trends. Or you could use the Omega Ratio approach if you want to reward assets that have had a favorable upside probability.
5. Set Portfolio Value and HODL Parameters
Enter how much capital you want to allocate in total (for the dynamic strategy) and adjust HODL buy quantities and thresholds as desired. (HODL Profit % is calculated from the Portfolio Value)
6. Inspect the Tables
On the chart, the script can display multiple tables showing your allocations, returns, risk metrics, and which assets are leading or lagging. Monitor these to make decisions about capital distribution or see how the strategy evolves.
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Additional Remarks
This script aims to simplify multi-asset portfolio management in a single tool. It emphasizes user-friendliness by color-coding the data in tables, so you do not need extra spreadsheets. The script is also flexible in letting you lock allocations or compare dynamic updates.
Always remember that no script can guarantee profitable outcomes. Real markets involve unpredictability, and real trading includes fees, slippage, and liquidity constraints not fully accounted for here. The script uses real-time and historical data for demonstration and educational purposes, providing a testing environment for various systematic strategies.
Performance Considerations
Due to the complexity of this script, users may experience longer loading times, especially when handling multiple assets or using advanced allocation methods. In some cases, calculations may time out if too many settings are adjusted simultaneously. If this occurs, removing and reapplying the indicator to the chart can help reset the process. Additionally, it is recommended to configure inputs gradually instead of adjusting all parameters at once, as excessive changes can extend the script’s loading duration beyond TradingView’s processing limits.
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Originality
This script stands out by integrating multiple asset management techniques within a single indicator, eliminating the need for multiple scripts or external portfolio tools. Unlike traditional single-asset strategies, it simultaneously evaluates multiple assets, applies systematic allocation logic, and tracks risk-adjusted performance in real time. The script is designed to function within TradingView’s script limitations while still allowing for complex portfolio simulations, making it an efficient tool for traders managing diverse holdings. Additionally, its combination of systematic trading signals with allocation-based diversification provides a structured approach to balancing exposure across different market conditions. The dynamic interplay between adaptive trading strategies and passive accumulation further differentiates it from conventional strategy indicators that focus solely on directional signals without considering capital allocation.
Conclusion
Uptrick: Portfolio Allocation Diversification pulls multiple assets into one efficient workflow, where each asset’s signal, volatility, and performance is measured, then assigned a share of capital according to your selected diversification method. The script accommodates both dynamic rebalancing and a locked allocation style, plus an ongoing HODL simulation for passive accumulation comparison. It neatly visualizes the entire process through on-chart tables that are updated every bar.
Traders and investors looking for ways to manage multiple assets under one unified framework can explore the different modules within this script to find what suits their style. Users can quickly switch among trading systems, vary the allocation approach, or review side-by-side performance metrics to see which method aligns best with their risk tolerance and market perspective.
OHLC LoggerOHLC OG - 10 Candles
The OHLC OG - 10 Candles indicator provides a clear visualization of price action by analyzing the Open, High, Low, and Close (OHLC) data of the last 10 candles. Designed for traders who rely on structured price patterns, this indicator helps in identifying market trends, key support and resistance zones, and potential breakout points.
Features:
✅ Tracks the last 10 candles to highlight significant price movements.
✅ Visualizes Open, High, Low, and Close levels for improved market analysis.
✅ Customizable settings for enhanced adaptability to different strategies.
✅ Works across all timeframes and assets (forex, stocks, crypto, etc.).
✅ Ideal for price action traders looking for structured market insights.
This indicator is perfect for traders who prefer clean and reliable price action analysis without unnecessary complexity. Whether you trade breakouts, trend reversals, or continuation patterns, OHLC OG - 10 Candles helps you stay ahead of the market.
🔹 How to Use:
Apply the indicator to your chart and observe how the OHLC levels react to price movements.
Use it to confirm trends, identify potential breakout zones, or refine entry/exit points.
Combine it with other indicators or strategies for a more comprehensive trading approach.
📌 Disclaimer: This indicator is for educational purposes only. Always conduct proper risk management before trading.
QSL Upside/DownsideThe QSL Upside/Downside Indicator helps traders estimate potential gains and losses using Conditional Value at Risk (cVaR), a statistical measure that assesses both downside risk and upside potential beyond standard volatility. Instead of fixed timeframes (daily, weekly, etc.), traders can set a custom lookback period (in days) to analyze market behavior over their preferred time frame.
How It Works
The indicator calculates cVaR over the chosen period to determine how much an investment could move up or down based on past price behavior. It does this by:
• Mean Return – The average price movement over the period.
• Standard Deviation – Measures price fluctuations from the average.
• cVaR Confidence Interval (95%) – Estimates worst-case losses, meaning the downside projection reflects the worst 5% of expected losses.
• Upside Potential (Best 5%) – Instead of only considering risk, this indicator also calculates the potential upside by measuring returns in the top 5% of past price movements.
This provides a more complete view of what traders can expect—both in terms of risk and potential reward.
Key Features
✅ Custom Lookback Period – Set any number of days to analyze.
✅ cVaR Calculation (95% Confidence Interval) – Identifies extreme downside risks.
✅ Upside Potential (Best 5%) – Estimates how much an investment could rise in a best-case scenario.
✅ Clear Table Display – Quickly see projected best and worst-case portfolio values.
Understanding Probabilities: Upside & Downside Potential
Most traders focus on risk, but it’s equally important to understand potential gains. This indicator provides a probability-based view of expected market moves:
• 95% Confidence Interval (Downside cVaR) – There’s a 5% chance that losses could exceed this level.
• 95% Confidence Interval (Upside cVaR) – There’s a 5% chance that gains could be greater than this level.
• The remaining 90% of expected returns fall between these two extremes.
By knowing both potential losses and gains, traders can make more balanced, data-driven decisions rather than only focusing on worst-case scenarios.
Why Use This Indicator?
🔹 Better Risk & Reward Assessment – Understand both downside risk and upside potential.
🔹 More Realistic Market Projections – Uses probabilities instead of simple historical averages.
🔹 Flexible & Customizable – Works with any asset and any time period.
With this tool, QSL members can strategically plan trades, knowing the expected best and worst-case outcomes with a 95% probability range. 🚀
Date Display with Bar Counter and EMA===== ENGLISH DESCRIPTION =====
OVERVIEW:
This is a multi-function indicator that combines three useful tools in one script:
1. Date Display - Shows current date and symbol information in a customizable table
2. Bar Counter - Displays sequential bar numbers at specified intervals
3. EMA (Exponential Moving Average) - Plots an EMA line with customizable settings
FEATURES:
1. DATE DISPLAY:
- Shows date in full format (e.g., "Mon ∙ January 1, 2023") or short format (e.g., "Mon ∙ 01.01.23")
- Option to show/hide day of week
- Option to show/hide symbol and timeframe information
- Customizable table position (top/middle/bottom, left/center/right)
- Automatic color adjustment based on chart background
2. BAR COUNTER:
- Displays sequential bar numbers below price bars
- Customizable display frequency (every X bars)
- Special handling for Hong Kong futures (resets at market open)
- Different reset logic based on timeframe (daily, weekly, monthly)
- Customizable text size and color
3. EMA INDICATOR:
- Customizable period length (default: 20)
- Option to use different timeframe for calculation
- Option to wait for timeframe close for more stable signals
- Customizable line color
USAGE INSTRUCTIONS:
- After adding the indicator to your chart, customize settings in the "Format" panel
- The Date Display table will appear at your chosen position on the chart
- Bar numbers will appear below price bars at your specified frequency
- The EMA line will be plotted on the chart with your chosen settings
- Colors automatically adjust to light/dark chart themes
===== 中文说明 =====
概述：
这是一个多功能指标，将三个实用工具合并为一个脚本：
1. 日期显示 - 在可自定义的表格中显示当前日期和交易品种信息
2. K线计数器 - 按指定间隔显示K线序号
3. EMA指数移动平均线 - 绘制可自定义设置的EMA线
功能特点：
1. 日期显示：
- 支持完整格式（如"Mon ∙ January 1, 2023"）或简短格式（如"Mon ∙ 01.01.23"）
- 可选择显示/隐藏星期几
- 可选择显示/隐藏交易品种和时间周期信息
- 可自定义表格位置（顶部/中部/底部，左侧/中间/右侧）
- 根据图表背景自动调整颜色
2. K线计数器：
- 在价格K线下方显示序号
- 可自定义显示频率（每X根K线）
- 对香港期货有特殊处理（在开市时重置）
- 根据时间周期（日线、周线、月线）使用不同的重置逻辑
- 可自定义文字大小和颜色
3. EMA指标：
- 可自定义周期长度（默认：20）
- 可选择使用不同的时间周期进行计算
- 可选择等待时间周期结束以获得更稳定的信号
- 可自定义线条颜色
使用说明：
- 将指标添加到图表后，在"格式"面板中自定义设置
- 日期显示表格将出现在您选择的图表位置
- K线序号将按您指定的频率显示在价格K线下方
- EMA线将根据您选择的设置绘制在图表上
- 颜色会根据浅色/深色图表主题自动调整
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Machine Learning + Geometric Moving Average 250/500Indicator Description - Machine Learning + Geometric Moving Average 250/500
This indicator combines password-protected market analysis levels with two powerful Geometric Moving Averages (GMA 250 & GMA 500).
🔒 Password-Protected Custom Levels
Access pre-defined long and short price levels for select assets (crypto, stocks, and more) by entering the correct password in the indicator settings.
Once the correct password is entered, the indicator automatically displays:
Green horizontal lines for long entry zones.
Red horizontal lines for short entry zones.
If the password is incorrect, a warning label will appear on the chart.
📈 Geometric Moving Averages (GMA)
This indicator calculates GMA 250 and GMA 500, two long-term trend-following tools.
Unlike traditional moving averages, GMAs use logarithmic smoothing to better handle exponential price growth, making them especially useful for assets with strong trends (e.g., crypto and tech stocks).
GMA 250 (white line) tracks the medium-term trend.
GMA 500 (gold line) tracks the long-term trend.
⚙️ Customizable & Flexible
Works on multiple assets, including cryptocurrencies, equities, and more.
Adaptable to different timeframes and trading styles — ideal for both swing traders and long-term investors.
This indicator is ideal for traders who want to blend custom support/resistance levels with advanced geometric trend analysis to better navigate both volatile and trending markets.
MacroJP: US Macro Conditions & Forward GuidanceMacroJP is a comprehensive, free-to-use TradingView indicator designed to provide a clear snapshot of the US macroeconomic environment. It consolidates key economic metrics into a single, interactive dashboard, allowing traders and investors to quickly assess current conditions and adjust their portfolio biases accordingly.
How It Works:
• Data Aggregation:
The indicator pulls monthly data from reputable free economic sources—specifically, ISM Manufacturing PMI, US CPI YoY, US M2 Money Supply, and US Treasury yields (10-year and 2-year). This robust dataset forms the backbone of the analysis.
• Composite Calculations:
By calculating a Composite Inflation Indicator (the average of CPI YoY and the yield spread) and evaluating the year-over-year change in M2, MacroJP gauges both the inflationary pressures and liquidity trends in the economy. These composite metrics offer a nuanced view that goes beyond single-indicator analysis.
Regime Classification:
The core strength of MacroJP lies in its quadrant classification system. It categorises the macro environment into four distinct regimes based on the direction of economic growth (derived from PMI) and inflation (from the Composite Inflation Indicator):
• Expansion (Reflation): Indicative of a recovering economy with rising production and moderate inflation—ideal for a bullish equity bias.
• Stagflation Risk: A scenario of weak growth coupled with high inflation, where a defensive posture is recommended.
• Slowdown (Deflationary): Characterised by contracting economic activity and falling prices, suggesting a move towards cash or high-quality bonds.
• Disinflationary Boom: Reflects strong growth with stable or falling inflation—an optimal environment for equities with some bond diversification.
Forward Guidance:
To enhance its predictive capability, MacroJP incorporates leading indicators by shifting key data points. For instance, it uses a forward-shifted M2 YoY value and a one-month shifted CPI proxy to offer insights into near-term trends. This approach helps in anticipating changes, providing a sort of “forward guidance” that can inform strategic asset allocation.
User Education:
The indicator features an intuitive table with on-hover tooltips that explain each metric, its relevance, and recommended investment biases. This educational layer is designed to empower users to not only monitor the economic pulse but also to understand the ‘why’ behind each reading, making it a valuable tool for both novice and experienced investors.
MacroJP brings clarity to complex macroeconomic dynamics, allowing users to make more informed decisions in volatile markets. Its seamless integration of free public data and detailed on-chart annotations makes it an indispensable tool for anyone looking to understand the broader economic context impacting their investments.
— Jaroslav
Pearson Correlation Best MA [victhoreb]Pearson Correlation Best MA is an innovative indicator designed to dynamically select the moving average that best aligns with price action based on the Pearson correlation coefficient. Here’s what it does:
- Multiple MA Evaluation: The indicator computes eight different moving averages — SMA, EMA, DEMA, TEMA, LSMA, RMA, WMA, and VWMA — using a user-defined period.
- Correlation Analysis: For each moving average, it calculates the Pearson correlation with the price (using the average of high and low) over a specified correlation length, then identifies the one with the highest correlation.
- Optional Smoothing: Users can opt to further smooth the selected best moving average for an even more refined signal.
- Visual Cues: The indicator plots the “Best MA” on the chart, colors it based on its direction (bullish or bearish), and also displays the correlation value. Additionally, it can color the price candles to reflect the trend indicated by the best moving average.
- Customizability: All key parameters such as moving average length, correlation length, smoothing options, and color settings are fully customizable.
This tool helps traders by automatically adapting to market conditions—highlighting the moving average that is most in sync with current price trends, potentially improving trade timing and decision-making.
