Custom Portfolio [BackQuant]Custom Portfolio {BackQuant]
Overview
This script turns TradingView into a lightweight portfolio optimizer with institutional-grade analytics and real-time position management capabilities.
Rank up to 15 tickers every bar using a pair-wise relative-strength "league table" that compares each asset against all others through your choice of 12 technical indicators.
Auto-allocate 100% of capital to the single strongest asset and optionally apply dynamic leverage when the aggregate market is trending, with full position tracking and rebalancing logic.
Track performance against a custom buy-and-hold benchmark while watching a fully fledged stats dashboard update in real time, including 15 professional risk metrics.
How it works
Relative-strength engine – Each asset is compared against every other asset with a user-selectable indicator (default: 9/21 EMA cross). The system generates a complete comparison matrix where Asset A vs Asset B, Asset A vs Asset C, and so on, creating strength scores. The summed scores crown a weekly/daily/hourly "winner" that receives the full allocation.
Regime filter – A second indicator applied to TOTAL crypto-market cap (or any symbol you choose) classifies the environment as trending or mean-reverting . Leverage activates only in trending regimes, protecting capital during choppy or declining markets. Choose from indicators like Universal Trend Model, Relative Strength Overlay, Momentum Velocity, or Custom RSI for regime detection.
Capital & position logic – Equity grows linearly when flat and multiplicatively while invested. The system tracks entry prices, calculates returns including leverage adjustments, and handles position transitions seamlessly. Optional intra-trade leverage rebalancing keeps exposure in sync with market conditions, recalculating position sizes as regime conditions change.
Risk & performance analytics – Every confirmed bar records return, drawdown, VaR/CVaR, Sharpe, Sortino, alpha/beta vs your benchmark, gain-to-pain, Calmar, win-rate, Omega ratio, portfolio variance, skewness, and annualized statistics. All metrics render in a professional table for instant inspection with proper annualization based on your selected trading days (252 for traditional markets, 365 for crypto).
Key inputs
Backtest window – Hard-code a start date or let the script run from series' inception with full date range validation.
Asset list (15 slots) – Works with spot, futures, indices, even synthetic spreads (e.g., BYBIT:BTCUSDT.P). The script automatically cleans ticker symbols for display.
Indicator universe – Switch the comparative metric to DEMA, BBPCT, LSMAz adaptive scores, Volatility WMA, DEMA ATR, Median Supertrend, and more proprietary indicators.
With more always being added!
Leverage settings – Max leverage from 1x to any multiple, auto-rebalancing toggle, trend/reversion thresholds with precision controls.
Visual toggles – Show/hide equity curve, rolling drawdown heat-map, daily PnL spikes, position label, advanced metrics table, buy-and-hold comparison equity.
Risk-free rate input – Customize the risk-free rate for accurate Sharpe ratio calculations, supporting both percentage and decimal inputs.
On-chart visuals
Color-coded equity curve with "shadow" offset for depth perception that changes from green (profitable) to red (losing) based on recent performance momentum.
Rolling drawdown strip that fades from light to deep red as losses widen, with customizable maximum drawdown scaling for visual clarity.
Optional daily-return histogram line and zero reference for understanding day-to-day volatility patterns.
Bottom-center table prints the current winning ticker in real time with clean formatting.
Top-right metrics grid updates every bar with 15 key performance indicators formatted to three decimal places for precision.
Benchmark overlay showing buy-and-hold performance of your selected index (default: SPX) for relative performance comparison.
Typical workflow
Add the indicator on a blank chart (overlay off).
Populate ticker slots with the assets you actually trade from your broker's symbol list.
Pick your momentum or mean-reversion metric and a regime filter that matches your market hypothesis.
Set max leverage (1 = spot only) and decide if you want dynamic rebalancing.
Press the little " L " on the price axis to view the equity curve in log scale for better long-term visualization.
Enable the metrics table to monitor Sharpe, Sortino, and drawdown in real time.
Iterate through different asset combinations and indicator settings; compare performance vs buy-and-hold; refine until you find robust parameters.
Who is it for?
Systematic crypto traders looking for a one-click, cross-sectional rotation model with professional risk management.
Portfolio quants who need rapid prototyping without leaving TradingView or exporting to Python/R.
Swing traders wanting an at-a-glance health check of their multi-coin basket with instant position signals.
Fund managers requiring detailed performance attribution and risk metrics for client reporting.
Researchers backtesting momentum and mean-reversion strategies across multiple assets simultaneously.
Important notes & tips
Set Trading Days in a Year to 252 for traditional markets; 365 for 24/7 crypto to ensure accurate annualization.
CAGR and Sharpe assume the backtest start date you choose—short windows can inflate stats, so test across multiple market cycles.
Leverage is theoretical; always confirm your broker's margin rules and account for funding costs not modeled here.
The script is computationally heavy at 15 assets due to the N×N comparison matrix—reduce the list or lengthen the timeframe if you hit execution limits.
Best results often come from mixing assets with different volatility profiles rather than highly correlated instruments.
The regime filter symbol can be changed from CRYPTOCAP:TOTAL to any broad market index that represents your asset universe.
Search in scripts for "profitable"
TrendZonesTrendZones
This is an indicator which I use, have tested, tweaked and added features to for use in my trend following investing system. I got the idea for it when for some reason I was looking for a dynamic reference to measure the height of a channel or something. In search of this I made MA’s of the high and low borders of a Donchian channel which turned out to be two near parallel and stunningly smooth curves. This visual was so appealing that I immediately tried to turn it into a replacement for the KeltCOG which I previously used in my system. First I created a curve in the middle of the upper and lower curves, which I called COG (Center Of Gravity). Then I decided to enter only one lookback and let the script create a Donchian channel with half the lookback and use this to create the curves with an MA of whole lookback. For this reason the minimum lookback is set to 14, enough room for the Donchian Channel of 7 periods. This Donchian ChanneI has a special way of calculating the borders, involving a 5 period Median value. Thanks to this these borders are really a resistance and support level, which won’t change at a whim, e.g. when a ‘dead cat bounce’ occurs. I prevented the Donchian channel to show itself between the curves and only pop out from behind these. These pop outs now function as “strong trend zones”. I gave it colors (blue:-strong up, green: moderate up, orange: moderate down, red: strong down, near COG: gray, curves horizontal: gray) and it looked very appealing. I tested it in different time frames. In some weekend, when I was bored, I observed for a few hours the minute chart of bitcoin. It turned out that you can reliably tell that an uptrend ends when the candles go under the COG beginning a downtrend. Uptrend starts again once the candles go above COG. As Trends on minute charts only last around half an hour, this entertainment made the potential of this indicator very clear to me in just one afternoon.
Risk Management, Safe Level and Logical Stops.
In the inputs are settings for “Risk Tolerance”, and to activate “Show Logical Stop Level” (activated in example chart) and “Show Safe Level”. As a rule of thump a trade should not expose the invested capital to a risk of losing more than 2 percent. I divided my investment capital in ten equal parts which are allocated to ten different stocks or other instruments or kept liquid. This means that when a position is closed by triggering a Stop with a loss of 20 percent, the invested capital suffers only 2 percent (20% x 10% = 2%). This is why the value for “Risk Tolerance” has a default of 20. Because I put my Stops on the lower curve, a “Safe Level” can be calculated such that when you buy for a price below or at this level, the stop will protect the position sufficiently. Because I only buy when the instrument is in uptrend, the buying price should be between COG and Safe Level. Although I never do that, putting the stop at other curves is feasible and when you want to widen the stop (I never lower my stops btw) in a downtrend situation, even 1 ATR below the “Low Border”. I call these “Logical Stop Levels”, marked with dark green circles on the lower curve when safe buying by placing the Stoploss on this curve is possible, gray circles on the other curves, on the Upper Curve navy when price enters very profitable level. In a downtrend situation maroon circles appear.
Target lines
When I open a position I always set a Stoploss and a Target, for this purpose two types of Target values can be set and corresponding Target lines activated. These lines are drawn above the “High Border” at the set distance. If one expects some price to be used, differences will occur.
Other Features
Support Zone, this is 1 ATR below the “Low Border”, the maroon circles of the “Logal Stops” are placed on this “Support level”.
Stop distance and Channel Width. (activated in example chart) These are reported in a two cell table in the right lower corner of the main panel. I created this because I want to be able to check the volatility, whether the channel shows a situation in which safe buying in most levels of the channel is possible or what risk you take when you buy now and set the Stop at the nearest logical level (which is not always the “Lower curve”). This feature comes in handy for creating a setup I propose in the “Day Trading Fantasy” below.
Some General and User Settings. I never activate this, perhaps you will.
Use Of TrendZones In My System.
Create a list of stocks in uptrend. I define ‘stock in uptrend’ as in uptrend zone in all three monthly, weekly and daily charts, all three should at the same time be in uptrend. The advantage of TrendZones is that you can immediately see in which zone the candle moves.
Opening a position in a stock from the above list. I do this only when in both the daily and weekly the green dot on the lower curve indicates a buying opportunity. This is usually not the case in most of the items of the list, this feature thus provides a good timing for opening a position. Sometimes you need to wait a few weeks for this to happen.
Setting a target over a position. For this I use the Target percent line of the weekly chart with the default value of 10.
Updating the Stoploss and Target values. Every week or two weeks I set these to the new values of the “Lower Curve” and the Target line of the weekly. Attention: never shift down Stops, only up or let them stay the same when the curve moves down. I never use Stop levels on other curves.
I Check the charts whenever I like to do this. Close the position when the uptrend obviously shifts down. Otherwise I let the profits run until the Target triggers which closes the position with some profit.
For selecting stocks an checking charts for volume events, I also use a subpanel indicator called “TZanalyser”, which borrows the visual of my “Fibonacci Zone Oscillator”, is based on TrendZones and includes code from my REVE indicators. I intend to publish that as well.
Day Trading Fantasy.
Day trading is an attempt to earn a dime by opening a position in the morning and close it during the day again with a profit (or a loss). Before the market closes, you close all day trading positions.
In my fantasy the “Logical Stop Level” is repurposed for use as entry point and the ATR-based Target line is used to provide a target setting in an intraday chart, like e.g. 15 minute. To do this the “Safe Level” should be limited to between Channel width and COG. This can be done by showing “Safe Level” and “Channel Width” and then set “Risk Tolerance” to around the shown Channel Width. In this setting you can then wait for the green circle to show up for entering your trade and protect it with the stop.
I don’t know if this works fine or if it’s better than other day trade systems, because I don’t do day trading.
Take care and have fun.
Bitcoin Institutional Volume AnchorsBitcoin Institutional Volume Anchors
Indicator Overview:
The Bitcoin Institutional Volume Anchors indicator is a professional-grade VWAP analysis tool designed for sophisticated Bitcoin trading strategies. It tracks two critical volume-weighted average price levels anchored to fundamental market structure events that drive Bitcoin's multi-year cycles.
-Orange Line (Halving Anchor): Volume-weighted average price from April 19, 2024 halving event
-Blue Line (Cycle Low Anchor): Volume-weighted average price from November 21, 2022 cycle bottom
These anchors represent the average price institutional and professional traders have paid since Bitcoin's most significant supply-side catalyst (halving) and demand-side reset (cycle low).
Market Interpretation Framework:
Price Above Both Anchors - Institutional Bullish
-Strong institutional accumulation confirmed
-Majority of professional money profitable since key events
-Optimal environment for long-term position building
-Risk-on institutional sentiment
Price Between Anchors - Transition Phase
-Mixed institutional signals requiring careful analysis
-Appropriate for reduced position sizing
-Monitor for directional confirmation
-Tactical rebalancing opportunity
Price Below Both Anchors - Institutional Bearish
-Professional money underperforming key levels
-Heightened risk management protocols required
-Defensive positioning appropriate
-Await institutional re-accumulation signals
Standard Deviation Band Analysis:
Gray Bands (2σ): Statistical volatility boundaries
-Represent normal price excursions from institutional fair value
-Used for tactical profit-taking and position scaling
-Indicate elevated but manageable risk levels
Colored Bands (3σ): Extreme volatility boundaries
-Orange/Blue bands corresponding to respective VWAP anchors
-Represent statistically extreme price extensions
-High-probability reversal or exhaustion zones
-Critical risk management triggers
Professional Trading Applications:
Portfolio Allocation Framework
Maximum Allocation (70-100%)
-Price above both anchors with upward trending VWAPs
-Recent bounce from either anchor level
-Recovery to fair value after extreme extension
Standard Allocation (40-70%)
-Price above anchors but approaching 2σ bands
-Consolidation near anchor levels
-Confirmed institutional trend changes
Reduced Allocation (20-40%)
-Price at 2σ extension levels
-Below one anchor but above the other
-Conflicting VWAP trend signals
Defensive Allocation (10-25%)
-Price at 3σ extreme levels
-Below both institutional anchors
-Overextended risk conditions (>30-35% above anchors)
Entry Signal Hierarchy:
Tier 1 Signals (Highest Probability)
-Bounce from Cycle Low Anchor during uptrend
-Cross above both anchors with volume confirmation
-Recovery to fair value after 20%+ extension
Tier 2 Signals (Standard Probability)
-Bounce from Halving Anchor during uptrend
-Trend change confirmation in VWAP slope
-2σ band rejection with momentum
Tier 3 Signals (Lower Probability)
-Entries near 2σ extension levels
-Counter-trend plays against institutional flow
-High-risk momentum trades at extremes
Risk Management Protocol:
Stop Loss Guidelines
-Halving Anchor entries: 3% below anchor level
-Cycle Low Anchor entries: 4% below anchor level
-Extension trades: 2% below current level
-Trend change trades: Below invalidation anchor
Profit Taking Strategy
-25-40% profits at 2σ bands
-50-70% profits at 3σ bands
-Trailing stops below higher timeframe anchor levels
-Complete exits on institutional trend reversals
Alert System Integration:
The indicator provides institutional-grade alert notifications with:
-Precise entry and exit levels
-Position sizing recommendations
-Historical win rate data
-Risk/reward calculations
-Stop loss and target guidelines
-Timeframe expectations
-Volume confirmation requirements
Implementation Notes
-Timeframe Suitability: Daily charts recommended for primary analysis
-Asset Specificity: Optimized exclusively for Bitcoin spot markets
-Volume Consideration: Higher volume enhances signal reliability
-Market Context: Most effective during trending market conditions
-Institutional Alignment: Designed for professional risk management standards
-Key Performance Metrics
Based on historical backtesting:
-Overall Win Rate: 74% for primary signals
-Risk Reduction: 31% drawdown improvement vs buy-and-hold
-Signal Accuracy: 85% at extreme (3σ) levels
-Optimal Timeframe: 1-12 week holding periods
-Best Performance: April 2024 - January 2025 period
This indicator is designed for professional traders and institutional investors who require sophisticated market analysis tools with quantified risk parameters and historically validated performance metrics.
GCM Bull Bear RiderGCM Bull Bear Rider (GCM BBR)
Your Ultimate Trend-Riding Companion
GCM Bull Bear Rider is a comprehensive, all-in-one trend analysis tool designed to eliminate guesswork and provide a crystal-clear view of market direction. By leveraging a highly responsive Jurik Moving Average (JMA), this indicator not only identifies bullish and bearish trends with precision but also tracks their performance in real-time, helping you ride the waves of momentum from start to finish.
Whether you are a scalper, day trader, or swing trader, the GCM BBR adapts to your style, offering a clean, intuitive, and powerful visual guide to the market's pulse.
Key Features
JMA-Powered Trend Lines (UTPL & DTPL): The core of the indicator. A green "Up Trend Period Line" (UTPL) appears when the JMA's slope turns positive (buyers are in control), and a red "Down Trend Period Line" (DTPL) appears when the slope turns negative (sellers are in control). The JMA is used for its low lag and superior smoothing, giving you timely and reliable trend signals.
Live Profit Tracking Labels: This is the standout feature. As soon as a trend period begins, a label appears showing the real-time profit (P:) from the trend's starting price. This label moves with the trend, giving you instant feedback on its performance and helping you make informed trade management decisions.
Historical Performance Analysis: The profit labels remain on the chart for completed trends, allowing you to instantly review past performance. See at a glance which trends were profitable and which were not, aiding in strategy refinement and backtesting.
Automatic Chart Decluttering: To keep your chart clean and focused on significant moves, the indicator automatically removes the historical profit label for any trend that fails to achieve a minimum profit threshold (default is 0.5 points).
Dual-Ribbon Momentum System:
JMA / Short EMA Ribbon: Visualizes short-term momentum. A green fill indicates immediate bullish strength, while a red fill shows bearish pressure.
Short EMA / Long EMA Ribbon: Acts as a long-term trend filter, providing broader market context for your decisions.
"GCM Hunt" Entry Signals: The indicator includes optional pullback entry signals (green and red triangles). These appear when the price pulls back to a key moving average and then recovers in the direction of the primary trend, offering high-probability entry opportunities.
How to Use
Identify the Trend: Look for the appearance of a solid green line (UTPL) for a bullish bias or a solid red line (DTPL) for a bearish bias. Use the wider EMA ribbon for macro trend confirmation.
Time Your Entry: For aggressive entries, you can enter as soon as a new trend line appears. For more conservative entries, wait for a "GCM Hunt" triangle signal, which confirms a successful pullback.
Ride the Trend & Manage Your Trade: The moving profit label (P:) is your guide. As long as the trend line continues and the profit is increasing, you can confidently stay in the trade. A flattening JMA or a decreasing profit value can signal that the trend is losing steam.
Focus Your Strategy: Use the Display Mode setting to switch between "Buyers Only," "Sellers Only," or both. This allows you to completely hide opposing signals and focus solely on long or short opportunities.
Core Settings
Display Mode: The master switch. Choose to see visuals for "Buyers & Sellers," "Buyers Only," or "Sellers Only."
JMA Settings (Length, Phase): Fine-tune the responsiveness of the core JMA engine.
EMA Settings (Long, Short): Adjust the lengths of the moving averages that define the ribbons and "Hunt" signals.
Label Offset (ATR Multiplier): Customize the gap between the trend lines and the profit labels to avoid overlap with candles.
Filters (EMA, RSI, ATR, Strong Candle): Enable or disable various confirmation filters to strengthen the "Hunt" entry signals according to your risk tolerance.
Add the GCM Bull Bear Rider to your chart today and transform the way you see and trade the trend!
ENJOY
Economic Event Timer & Alerts [AlgoXcalibur]Stay ahead of market-moving news with this real-time event tracker and countdown alert system.
This essential algorithm displays critical scheduled events that may influence sudden spikes in market volatility, helping you stay aware and reduce exposure to unpredictable moves before they even happen. Featuring a captivating on-chart display with event titles, adjustable time zone, real-time countdowns, and live alert notifications — you’ll always know what’s ahead — so you can prepare, not react.
🧠 Algorithm Logic
The Economic Event Timer & Alerts system delivers critical market awareness through an array of integrated functions. At its core, a live countdown table provides real-time updates on the day’s scheduled economic events, with dynamic, color-coded countdowns that ensure fast and easy interpretation at a glance. Complementing the table, Countdown Alerts notify you 30 minutes, 10 minutes, and 1 minute prior to each event—giving you clear, timely reminders without the need to constantly monitor your chart. The adjustable time zone input supports ET, CT, MT, PT, or UTC, so the displayed time-of-event aligns with your trading session. Rigorously refined, the algorithm updates the table daily—and clearly displays No Scheduled Events Today to provide certainty and reassurance on days without scheduled events. Packaged in a minimalist, unobtrusive design, the tool remains visually clean and focused for serious traders.
Updated automatically for hassle-free peace of mind.
⚙️ Features
• Time Zone Selector: Easily toggle between time zones to match your trading session.
• Countdown Alerts: Enable real-time notifications to keep you informed and aware of events without having to monitor the chart.
• Update & Expiration Awareness Feature:
This innovative feature includes a simple visual and alert system that prompts you when it’s time to reload the indicator & recreate alerts — ensuring your alerts are always tied to the latest data update.
🔄 Update Available
On the final day of current event data, the indicator will:
• Display Update Available on the indicator’s table
• Send an alert at 4:00 PM ET reminding you to reload & recreate alerts
You can load the updated version anytime that day.
⛔ Expired
If not reloaded, the next day the indicator will:
• Display an EXPIRED banner on the indicator’s table
• Send a Data Expired alert every day at 8:30 AM ET that prompts you to recreate alerts, until you do or disable the alert.
This prevents missing event alerts unknowingly.
Why is this feature necessary?
Even though the indicator is updated when necessary (typically every 2–4 weeks) to provide upcoming event data automatically, TradingView alerts do not auto-update —they stay tied to the version of the script that was active when the alert was created.
This thoughtful refinement is designed to ensure your alerts remain synced to current events and ready for when it matters most.
🚨 Protect Your Capital
At AlgoXcalibur, we understand that the best way to be profitable is to avoid unnecessary risk.
Dedicated to empowering traders with insight that matters, we designed this tool to transform inconvenient economic calendars into effortless, essential information—displayed directly on your chart. Whether you’re managing open positions or timing new trades, knowing when impactful events are about to hit is crucial to being proactive, protecting capital, and trading with confidence. This is not a technical analysis indicator—this is a risk management tool that provides traders with a fundamental edge.
Built for traders who value risk management, market awareness, and algorithm automation.
🔐 To get access or learn more, visit the Author’s Instructions section.
unprofitable stratThe indicator is a comprehensive trend-following indicator for TradingView. It's designed to identify and trade in the direction of the market's primary trend while using a dynamic, volatility-based system for exits. It filters out counter-trend noise and provides a clear visual dashboard of market conditions.
Core Trading Strategy
The indicator's logic is based on a two-part confirmation system to ensure trades are only taken in favorable conditions.
Master Trend Filter: The indicator first determines the "master trend" by checking if the price is above or below a long-term (200-period) Exponential Moving Average (EMA). It will only look for BUY signals when the price is above this EMA (in a master bullish trend) and only look for SELL signals when the price is below it. This prevents fighting the main market current.
Entry Trigger: Once the master trend is confirmed, the indicator doesn't enter immediately. It waits for a secondary confirmation: a breakout above a recent swing high (for a BUY) or a breakdown below a recent swing low. This ensures that short-term momentum has aligned with the long-term trend before a signal is generated.
Dynamic Exit Strategy
Exits are not based on a fixed target. Instead, the indicator uses a professional-grade ATR-based Trailing Stop Loss.
This "smart" stop loss automatically trails behind a profitable trade. It moves up to lock in gains during a BUY trade but never moves down.
The distance of the stop from the price is determined by the Average True Range (ATR), meaning it gives the trade more room to breathe in volatile markets and tightens up to protect profits in calm markets.
An "EXIT" signal appears on the chart when the price finally pulls back and hits this trailing stop line.
Visual Features on the Chart
The indicator provides several visual aids to make the trading process clear and intuitive.
Custom-Plotted Candles: The indicator draws its own candlesticks that are colored based on the trade status:
Blue: An active BUY trade is in progress.
Purple: An active SELL trade is in progress.
Gray: The indicator is flat with no active trade.
Signal Labels: Clear "BUY", "SELL", and "EXIT" labels are plotted directly on the chart at the moment they occur.
Trailing Stop Line: A bright orange line appears and follows the price during a trade, showing you the exact level of your trailing stop loss.
Multi-Timeframe Table: An optional dashboard in the top-right corner displays the master trend status ("Bullish" or "Bearish") on the 1m, 5m, 15m, 1-hour, and 4-hour timeframes simultaneously.
Trend Background: An optional feature allows you to color the entire chart background light blue or purple to match the master trend direction.
cd_secret_candlestick_patterns_CxHi traders,
With this indicator, we aim to uncover secret candlestick formations that even advanced traders may miss—especially those that can't be detected by classic pattern indicators, unless you're a true master of candlestick patterns or candle math.
________________________________________
General Idea:
We'll try to identify candlestick patterns by regrouping candles into custom-sized segments that you define.
You might ask: “Why do I need this? I can just look at different timeframes and spot the structure anyway.” But it’s not the same.
For example, if you're using a 1-minute chart and add a higher-timeframe candle overlay (like 5-minute), the candles you see start at fixed timestamps like 0, 5, 10, etc.
However, in this indicator, we redraw new candles by grouping them from the current candle backward in batches of five.
These candles won't match the standard view—only when aligned with exact time multiples (e.g., 0 and 5 minutes) will they look the same.
In classic charts:
• You see 5-minute candles that begin every 0 and 5 minutes.
In this tool:
• You see a continuously updating set of 5 merged 1-minute candles redrawn every minute.
What about the structures forming in between those fixed timeframes?
That’s exactly what we’ll be able to detect—while also making the lower timeframe chart more readable.
________________________________________
Candle Merging:
Let’s continue with an example.
Assume we choose to merge 5 candles. Then the new candle will be formed using:
open = open
close = close
high = math.max(high , high , high , high , high)
low = math.min(low , low , low , low , low)
This logic continues backward on the chart, creating merged candles in groups of 5.
Since the selected patterns are made up of 3, 4, or 5 candles, we redraw 5 such merged candles to analyze.
________________________________________
Which Patterns Are Included?
A total of 18 bullish and bearish patterns are included.
You’ll find both widely known formations and a few personal ones I use, marked as (MeReT).
You can find the pattern list and visual reference here:
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Entry and Filtering Suggestions:
Let me say this clearly:
Entering a trade every time a pattern forms will not make you profitable in the long run.
You need a clear trade plan and should only act when you can answer questions like:
• Where did the pattern appear?
• When and under what conditions?
It’s more effective to trade in the direction of the trend and look for setups around support/resistance, supply/demand zones, key levels, or areas confirmed by other indicators.
Whether you enter immediately after the pattern or wait for a retest is a personal choice—but risk management is non-negotiable.
One of the optional filters I’ve included is a Higher Timeframe (HTF) condition, which is my personal preference:
When enabled, the highest or lowest price among the pattern candles must match the high or low of the current HTF candle.
You can see in the image below the decrease in the number of detected patterns on the 1-minute chart when using no filter (blue labels) compared to when the 1-hour timeframe filter is applied (red labels).
Additionally, I’ve added a “protected” condition for engulfing patterns to help filter out weak classic engulf patterns.
________________________________________
Settings:
From the menu, you can configure:
• Number of candles for regrouping
• Distance between the last candle and newly drawn candles
• Show/hide options
• HTF filter toggle and timeframe selection
• Color, label placement, and text customization
• Pattern list (select which to display or trigger alerts for)
My preferred setup:
While trading on the 1-minute chart, I typically set the higher timeframe to 15m or 1H, and switch the candle count between 2 and 3 depending on the situation.
⚠️ Important note:
The “Show” and “Alert” options are controlled by a single command.
Alerts are automatically created for any pattern you choose to display.
________________________________________
What’s Next?
In future updates, I plan to add:
• Pattern success rate statistics
• Multi-broker confirmation for pattern validation
Lastly, keep in mind:
The more candles a pattern is based on, the more reliable it may be.
I'd love to hear your feedback and suggestions.
Cheerful trading! 🕊️📈
Breakouts with Trailing Stops V6 + AlertsBreakouts with Trailing Stops in Trading
Breakout trading is a strategy where traders aim to profit from an asset's price moving outside a defined support or resistance level, signaling a potential new trend. Trailing stops are a key risk management tool often used with breakouts to protect profits and limit potential losses.
What is a breakout?
A breakout occurs when an asset's price moves decisively above a resistance level (for a bullish breakout) or below a support level (for a bearish breakdown). This often signals increased momentum and potential for a significant price movement in the direction of the breakout.
Why use trailing stops with breakouts?
Trailing stops are particularly useful in breakout trading because they allow traders to capture potential profits as the price moves in their favor, while automatically adjusting to protect against sudden reversals.
How do trailing stops work with breakouts?
Initial Stop-Loss: When entering a breakout trade, a traditional stop-loss order is placed at a predetermined level to limit potential losses if the price reverses. For example, in a long position after a resistance breakout, the initial stop-loss might be placed below the former resistance level (which can now act as support).
Trailing Stop Activation: Once the price moves a favorable distance beyond the entry point, the trailing stop loss is activated. As highlighted by StoneX, it is a dynamic order that follows the price as it continues to move in the desired direction, maintaining a set distance below (for a long position) or above (for a short position) the current market price.
Profit Locking: If the price continues to rise (or fall for a short position), the trailing stop will move with it, "locking in" profits by raising the stop-loss level.
Exit Strategy: If the price reverses and hits the trailing stop, the position is automatically closed, ensuring that the trader retains a portion of the gains made while in the trade.
Advantages of using trailing stops with breakouts:
Locks in profits: Trailing stops help protect profits generated from successful breakout trades.
Automates exits: They automate the exit process, helping traders avoid emotional decision-making when the price reverses.
Allows for potential gains: They allow traders to stay in profitable trades as long as the trend continues.
Disadvantages of using trailing stops with breakouts:
Whipsaw risk: In volatile markets, the trailing stop may be triggered prematurely by minor price fluctuations.
Potential for missed gains: If the trailing stop is set too tightly, it may prevent the trader from capturing the maximum potential gains if the price experiences a minor pullback before continuing in the desired direction.
Tips for using trailing stops with breakouts:
Consider the asset's volatility: Adjust the trailing stop distance based on the asset's volatility to minimize the risk of premature stops.
Test different trailing stop methods: Experiment with different trailing stop methods to find what works best for your trading style and the specific asset you are trading.
Backtest your strategy: Before applying a trailing stop strategy to live trading, backtest it on historical data to evaluate its performance under different market conditions.
Combine with other indicators: Use other technical indicators, such as volume or momentum oscillators, to confirm the validity of breakouts and improve the effectiveness of your trailing stop strategy.
By carefully considering the market dynamics, using appropriate indicators, and implementing proper risk management techniques, traders can effectively utilize trailing stops with breakouts to capture potential profits while minimizing risk.
Have a good trade.
Wavelet-Trend ML Integration [Alpha Extract]Alpha-Extract Volatility Quality Indicator
The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Hidden Markov Model [Extension] | FractalystWhat's the indicator's purpose and functionality?
The Hidden Markov Model is specifically designed to integrate with the Quantify Trading Model framework, serving as a probabilistic market regime identification system for institutional trading analysis.
Hidden Markov Models are particularly well-suited for market regime detection because they can model the unobservable (hidden) state of the market, capture probabilistic transitions between different states, and account for observable market data that each state generates.
The indicator uses Hidden Markov Model mathematics to automatically detect distinct market regimes such as low-volatility bull markets, high-volatility bear markets, or range-bound consolidation periods.
This approach provides real-time regime probabilities without requiring optimization periods that can lead to overfitting, enabling systematic trading based on genuine probabilistic market structure.
How does this extension work with the Quantify Trading Model?
The Hidden Markov Model | Fractalyst serves as a probabilistic state estimation engine for systematic market analysis.
Instead of relying on traditional technical indicators, this system automatically identifies market regimes using forward algorithm implementation with three-state probability calculation (bullish/neutral/bearish), Viterbi decoding process for determining most likely regime sequence without repainting, online parameter learning with adaptive emission probabilities based on market observations, and multi-feature analysis combining normalized returns, volatility comprehensive regime assessment.
The indicator outputs regime probabilities and confidence levels that can be used for systematic trading decisions, portfolio allocation, or risk management protocols.
Why doesn't this use optimization periods like other indicators?
The Hidden Markov Model | Fractalyst deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance.
The system uses a fixed mathematical framework based on Hidden Markov Model theory rather than optimized parameters, probabilistic state estimation using forward algorithm calculations that work across all market conditions, online learning methodology with adaptive parameter updates based on real-time market observations, and regime persistence modeling using fixed transition probabilities with 70% diagonal bias for realistic regime behavior.
This approach ensures the regime detection signals remain robust across different market cycles without the performance degradation typical of over-optimized traditional indicators.
Can this extension be used independently for discretionary trading?
No, the Hidden Markov Model | Fractalyst is specifically engineered for systematic implementation within institutional trading frameworks.
The indicator is designed to provide regime filtering for systematic trading algorithms and risk management systems, enable automated backtesting through mathematical regime identification without subjective interpretation, and support institutional-level analysis when combined with systematic entry/exit models.
Using this indicator independently would miss the primary value proposition of systematic regime-based strategy optimization that institutional frameworks provide.
How do I integrate this with the Quantify Trading Model?
Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation:
- Add both HMM Extension and Quantify Trading Model to your chart
- Select HMM Extension as the bias source using input.source()
- Quantify automatically uses the extension's bias signals for entry/exit analysis
- The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, and market structure patterns identified by the extension
The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation
What markets and assets does the indicator Extension work best on?
The Hidden Markov Model | Fractalyst performs optimally on markets with sufficient price movement since the system relies on statistical analysis of returns, volatility, and momentum patterns for regime identification.
Recommended asset classes include major forex pairs (EURUSD, GBPUSD, USDJPY) with high liquidity and clear regime transitions, stock index futures (ES, NQ, YM) providing consistent regime behavior patterns, individual equities (large-cap stocks with sufficient volatility for regime detection), cryptocurrency markets (BTC, ETH with pronounced regime characteristics), and commodity futures (GC, CL showing distinct market cycles and regime transitions).
These markets provide sufficient statistical variation in returns and volatility patterns, ensuring the HMM system's mathematical framework can effectively distinguish between bullish, neutral, and bearish regime states.
Any timeframe from 15-minute to daily charts provides sufficient data points for regime calculation, with higher timeframes (4H, Daily) typically showing more stable regime identification with fewer false transitions, while lower timeframes (30m, 1H) provide more responsive regime detection but may show increased noise.
Acceptable Timeframes and Portfolio Integration:
- Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation.
Legal Disclaimers and Risk Acknowledgments
Trading Risk Disclosure
The HMM Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns.
Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate analysis. The extension's performance depends on accurate data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy.
System Dependency Acknowledgment
The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior.
Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance.
Intellectual Property Protection
The HMM Extension, including all proprietary algorithms, classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action.
Liability Limitation
By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension.
Past performance of bias detection accuracy, classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst.
User Responsibility Statement
Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection.
This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate analysis assumptions.
Terms of Service Acceptance
Continued use of the HMM Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
Quantum Market Intelligence (QMI)Quantum Market Intelligence (QMI) Indicator
The Quantum Market Intelligence (QMI) is a sophisticated multi-factor technical indicator that combines four key market analysis components into a single composite score. This indicator provides traders with a comprehensive market assessment tool that adapts to changing market conditions. The QMI score oscillates between -100 and +100, offering clear visual signals through color-coded plotting and an informative dashboard display.
The indicator analyzes markets through four distinct lenses: Trend Analysis (using EMAs and volatility-adjusted momentum), Momentum Analysis (combining RSI, Stochastic, and Williams %R), Volume Analysis (incorporating volume ratios and Accumulation/Distribution), and Volatility Analysis (utilizing ATR and Bollinger Bands). These components are intelligently weighted based on detected market regimes - whether trending, volatile, or range-bound. The adaptive mode feature continuously evaluates the indicator's recent performance and adjusts sensitivity accordingly, making it responsive to evolving market dynamics.
Traders can utilize the QMI's signal system which generates four types of alerts: Strong Buy (above 70 and rising), Buy (crossing above 30), Strong Sell (below -70 and falling), and Sell (crossing below -30). The visual presentation includes triangular markers for strong signals, circular markers for regular signals, and background shading that indicates the current market regime. The information table displays real-time metrics including the QMI score, individual component scores, detected market regime, and performance ratio, providing traders with a complete analytical dashboard for informed decision-making.
Important Notice:
The use of this technical indicator does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data before applying them in live trading scenarios.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research before making any trading decisions.
VWAP/VOL [Extension] | FractalystWhat's the indicator's purpose and functionality?
The VWAP/VOL Extension is designed specifically as a bias identification system for the Quantify Trading Model.
This extension uses volume-weighted average price analysis combined with institutional volume classification to automatically detect market bias without requiring optimization periods that lead to overfitting.
The system provides real-time bias signals (bullish/bearish/neutral) that integrate directly with Quantify's machine learning algorithms, enabling institutional-level backtesting and automated entry/exit identification based on genuine market structure rather than curve-fitted parameters.
How does this extension work with the Quantify Trading Model?
The VWAP/VOL Extension serves as the bias detection engine for Quantify's automated trading system.
Instead of manually selecting bias direction, this extension automatically identifies market bias using:
- Volume-weighted VWAP analysis with three-state detection (bullish/bearish/neutral)
- Institutional volume classification using relative volume thresholds without optimization
- Non-repainting architecture ensuring consistent bias signals for Quantify's machine learning
The extension outputs bias signals that Quantify uses as input through the `input.source()` function, allowing the Trading Model to focus on optimal entry/exit timing while the extension handles bias identification.
Why doesn't this use optimization periods like other indicators?
The VWAP/VOL Extension deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance. The system uses:
- Fixed mathematical thresholds based on market structure principles rather than optimized parameters
- Relative volume analysis using standard 2.0x/0.5x ratios that work across all market conditions
- VWAP distance calculations based on percentage thresholds without curve-fitting
- Gap enforcement using fixed 5-bar minimums for disciplined bias detection
This approach ensures the bias signals remain robust across different market regimes without the performance degradation typical of over-optimized systems.
Can this extension be used independently for discretionary trading?
No, the VWAP/VOL Extension is specifically engineered to work as a component within the Quantify ecosystem. The extension is designed to:
- Provide bias input for Quantify's machine learning algorithms
- Enable automated backtesting through systematic bias identification
- Support institutional-level analysis when combined with Quantify's ML entry model
Using this extension independently would miss the primary value proposition of systematic entry/exit optimization that Quantify provides.
The extension handles bias detection so Quantify can focus on probability-based trade timing and risk management.
How does this enable institutional-level backtesting?
The extension transforms discretionary bias identification into systematic institutional analysis by:
- Eliminating subjective bias selection through automated VWAP/volume analysis
- Providing consistent historical signals with non-repainting architecture for accurate backtesting
- Integrating with Quantify's algorithms to identify optimal entry patterns based on objective bias states
- Enabling performance analysis across multiple market regimes without optimization bias
This combination allows Quantify to run institutional-grade backtests with consistent bias identification, generating reliable performance statistics and risk metrics that reflect genuine market edge rather than curve-fitted results.
How do I integrate this with the Quantify Trading Model?
Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation:
- Add both VWAP/VOL Extension and Quantify Trading Model to your chart
- Select VWAP/VOL Extension as the bias source using input.source()
- Quantify automatically uses the extension's bias signals for entry/exit analysis
- The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, volume conviction, and market structure patterns identified by the extension
The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation
What markets and assets does the VWAP/VOL Extension work best on?
The VWAP/VOL Extension performs optimally on markets with consistent, high-volume participation since the system relies on institutional volume analysis for bias detection. Futures markets provide the most reliable performance due to their centralized volume data and continuous institutional participation.
Recommended Futures Markets:
- ES (S&P 500 E-mini) - Over 2 million contracts daily volume, excellent liquidity depth
- NQ (NASDAQ-100 E-mini) - Around 600,000 contracts daily, strong tech sector representation
- YM (Dow Jones E-mini) - Consistent institutional flow and volume patterns
- RTY (Russell 2000 E-mini) - Small-cap exposure with reliable volume data
- GC (Gold Futures) - High volume commodity with institutional participation
- CL (Crude Oil Futures) - Energy sector representation with strong volume consistency
Why Futures Markets Excel:
- Futures markets provide centralized volume reporting, ensuring the extension's volume classification system receives accurate institutional participation data. The standardized contract specifications and continuous trading hours create consistent volume patterns that the extension's algorithms can analyze effectively.
Acceptable Timeframes and Portfolio Integration:
- Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation.
The extension is specifically designed to integrate with Quantify's portfolio management system, allowing multiple strategies across different timeframes and assets to operate simultaneously while maintaining consistent bias identification methodology across the entire automated trading portfolio.
Legal Disclaimers and Risk Acknowledgments
Trading Risk Disclosure
The VWAP/VOL Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides volume-weighted institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns.
Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate volume-based analysis. The extension's performance depends on accurate volume data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy.
System Dependency Acknowledgment
The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate volume reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior.
Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange volume reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, volume reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance.
Intellectual Property Protection
The VWAP/VOL Extension, including all proprietary algorithms, volume classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action.
Liability Limitation
By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension.
Past performance of bias detection accuracy, volume classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, volume pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst.
User Responsibility Statement
Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection.
This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate volume-based analysis assumptions.
Terms of Service Acceptance
Continued use of the VWAP/VOL Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
PineConnector [Extension] | FractalystWhat is the PineConnector Extension?
The PineConnector Extension is a sophisticated bridge indicator designed to seamlessly connect Quantify trading signals with PineConnector's automated execution system.
This extension transforms manual signal monitoring into fully automated trading by interpreting Quantify's signal outputs and converting them into executable PineConnector commands.
Unlike standalone trading indicators, this extension serves as a communication layer between your signal generation (Quantify indicator) and trade execution (PineConnector), enabling hands-free trading across multiple timeframes and instruments.
How does the signal processing work?
The extension processes four distinct signal types from Quantify indicators:
Signal Values:
1 = Buy/Long signal - Opens bullish positions
-1 = Sell/Short signal - Opens bearish positions
0.5 = Close Long - Closes all long positions
-0.5 = Close Short - Closes all short positions
The script continuously monitors the "Signal Source" input, which should be connected to any Quantify indicator's output. When a signal is detected, the extension automatically generates the corresponding PineConnector command with your configured parameters.
What are the available order types and how do they work?
The extension supports three order execution modes:
Market Orders:
- Execute immediately at current market price
- Highest execution probability
- Subject to slippage during volatile conditions
Limit Orders:
- Execute only when price reaches a more favorable level
- Buy limits placed below current price
- Sell limits placed above current price
- Dynamic pip offset calculated using ATR-based volatility
Stop Orders:
- Execute when price breaks beyond specified levels
- Buy stops placed above current price
- Sell stops placed below current price
- Useful for breakout strategies
Dynamic Pricing Calculation:
The extension calculates optimal entry prices using volatility-adjusted pip offsets:
priceVolatility = ta.atr(14) / close * 100
volatilityFactor = math.min(math.max(priceVolatility / 0.1, 0.5), 2.0)
pipsOffset = 10 * volatilityFactor
How does the risk management system work?
Risk Percentage:
The extension uses percentage-based position sizing where you specify the risk per trade (0.1% to 10.0%). This value is passed to PineConnector, which calculates the exact position size based on:
- Account balance
- Stop loss distance
- Instrument specifications
- Broker settings
Stop Loss Integration:
- The "Stop Source" input connects to external stop loss levels from Quantify or other indicators. - This ensures:
- Consistent risk-reward ratios
- Dynamic stop placement based on market structure
- Automatic position sizing calculations
Multi-Asset Compatibility:
The extension automatically detects instrument types and adjusts pip calculations:
Forex: mintick * 10
Crypto: mintick * 10
Other assets: mintick * 1
What does the information display table show?
The real-time status table provides essential configuration monitoring:
Status Indicators:
- License: Shows PineConnector license ID status (Blue = Set, Red = Missing)
- Security: Displays secret key status (Blue = Set, Orange = Disabled)
- Comment: Shows trade comment or timeframe if empty
- Symbol: Current trading symbol (manual override or chart symbol)
- Order Type: Active execution mode (Market/Limit/Stop)
- Risk: Risk percentage with color coding (Blue ≤1%, Orange >1%)
- Signal: Connection status (Blue = Connected, Red = Not Set)
- Stop: Stop loss source status (Blue = Connected, Red = Not Set)
Color Coding System:
Blue: Optimal/Connected
Orange: Warning/Moderate risk
Red: Error/Not configured
How do I connect this to my Quantify indicator?
Step-by-Step Connection:
Add the PineConnector Extension to your chart containing Quantify indicator
Configure Signal Source:
In the extension settings, locate "Signal Source"
Click the dropdown and select your Quantify indicator's signal output
The extension will automatically detect custom sources vs. default price data
Configure Stop Source:
Connect "Stop Source" to your Quantify indicator's stop loss output
This enables dynamic position sizing based on stop distance
Verify Connection:
Check the information table for "Signal" and "Stop" status
Blue indicates successful connection
Red indicates default price data (not connected)
Compatible Quantify Indicators:
- Quantify Trading Model
- Any indicator outputting standardized signals (1, -1, 0.5, -0.5)
What PineConnector setup is required?
Prerequisites:
- Active PineConnector License - Required for all functionality
- MetaTrader 4/5 or supported broker platform
- PineConnector EA installed and configured
- TradingView Pro/Pro+/Premium for alert functionality
Configuration Steps:
- License ID: Enter your PineConnector license ID in the extension
- Secret Key: Optional security layer for command verification
- Symbol Mapping: Ensure symbol names match between TradingView and broker
- Alert Setup: Create TradingView alerts using this indicator
- Webhook Configuration: Point alerts to your PineConnector webhook URL
Security Features:
- Optional secret key encryption
- Symbol-specific commands
- Debug mode for testing and validation
What makes this extension unique?
Seamless Integration:
- Unlike manual signal copying, this extension provides:
- Zero-latency signal translation
- Automated parameter passing
- Consistent execution across timeframes
- No human intervention required
Dynamic Adaptability:
Volatility-adjusted pricing for limit/stop orders
Automatic symbol detection and conversion
Multi-asset pip calculations
Intelligent timeframe formatting
Professional Risk Management:
- Percentage-based position sizing
- External stop loss integration
- Multi-order type support
- Real-time status monitoring
Robust Architecture:
- Error-resistant signal processing
- Comprehensive input validation
- Debug and testing capabilities
- Security features for live trading
Installation and Setup Guide
Quick Start:
- Add "PineConnector | Fractalyst" to your chart
- Configure your PineConnector license ID
- Connect Signal Source to your Quantify indicator
- Connect Stop Source to your stop loss indicator
- Set your preferred risk percentage
- Choose order type (Market recommended for beginners)
- Create TradingView alert using this indicator
- Ensure PineConnector EA is running on your trading platform
Advanced Configuration:
- Custom symbol mapping for cross-platform trading
- Secret key implementation for enhanced security
- Comment customization for trade tracking
- Debug mode for strategy validation
Legal Disclaimers and Risk Acknowledgments
Trading Risk Disclosure
This PineConnector Extension is provided for informational, educational, and automation purposes only and should not be construed as financial, investment, or trading advice. The extension facilitates automated trading connections but does not guarantee profitable outcomes, successful trade execution, or positive investment returns.
Automated trading systems carry substantial risks including but not limited to total capital loss, system failures, connectivity issues, and adverse market conditions. The extension's performance depends on multiple third-party services including PineConnector, MetaTrader platforms, TradingView infrastructure, and broker execution quality, any of which may experience downtime, technical failures, or service interruptions that could affect trading performance.
System Dependency Acknowledgment
The extension requires continuous operation of multiple interconnected systems: TradingView charts and alerts, PineConnector services and Expert Advisors, MetaTrader platforms, broker connectivity, and stable internet connections. Any interruption or malfunction in these systems may result in missed signals, failed executions, or unexpected trading behavior.
Users acknowledge that neither the seller nor the creator of this extension has control over these third-party services and cannot guarantee their availability, accuracy, or performance. Market conditions, broker execution policies, slippage, and technical factors may significantly affect actual trading results compared to theoretical or backtested performance.
Liability Limitation
By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from the use of this automated trading system. Neither the seller nor the creator shall be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension.
Past performance of connected indicators, strategies, or the extension itself does not guarantee future results. Trading outcomes depend on numerous factors including market conditions, economic events, broker execution quality, network connectivity, and proper system configuration, all of which are beyond the control of the extension creator.
User Responsibility Statement
Users are solely responsible for understanding the risks associated with automated trading, properly configuring all system components, maintaining adequate capitalization and risk management, and regularly monitoring system performance. Users should thoroughly test the extension in demo environments before live deployment and should never risk more capital than they can afford to lose.
This extension is designed to automate signal execution but does not replace the need for proper risk management, market understanding, and trading discipline. Users should maintain active oversight of their automated trading systems and be prepared to intervene manually when necessary.
X-Day Capital Efficiency ScoreThis indicator helps identify the Most Profitable Movers for Your fixed Capital (ie, which assets offer the best average intraday profit potential for a fixed capital).
Unlike traditional volatility indicators (like ATR or % change), this script calculates how much real dollar profit you could have made each day over a custom lookback period — assuming you deployed your full capital into that ticker daily.
How it works:
Calculates the daily intraday range (high − low)
Filters for clean candles (where body > 60% of the candle range)
Assumes you invested the full amount of capital ($100K set as default) on each valid day
Computes an average daily profit score based on price action over the selected period (default set to 20 days)
Plots the score in dollars — higher = more efficient use of capital
Why It’s Useful:
Compare tickers based on real dollar return potential — not just % volatility
Spot low-priced, high-volatility stocks that are better suited for intraday or momentum trading
Inputs:
Capital ($): Amount you're hypothetically deploying (e.g., 100,000)
Look Back Period: Number of past days to average over (e.g., 20)
Haven Average Daily RangeOverview
This indicator is an enhanced version of the traditional ADR tool that adapts to intraday price movements. Unlike static ADR levels, this indicator dynamically adjusts its range boundaries based on real-time price action while maintaining the original ADR calculation framework.
Key Features
ADR calculation based on multiple periods (5, 10, and 20 days)
ADR levels displayed with automatic style changes upon range reach
Customizable display settings (color, line style)
Price labels for better visualization
The indicator helps traders assess the instrument's volatility, identify potential reversal zones, and plan daily trading targets.
Suitable for all timeframes up to D1 and any trading instrument.
How It Works
Session Start (UTC+0): Calculates ADR based on historical data and sets initial High/Low levels
Dynamic Phase: Monitors price action and adjusts the opposite boundary (ADR Low or High) when new extremes are reached.
When price creates new Day high price above the opening price, the ADR Low level moves upward proportionally.
When price creates new Day low price below the opening price, the ADR High level moves downward proportionally.
Completion Phase: Stops adjustments and highlights breach when price reaches either boundary
Trading Application
Entry and Exit Signals
The ADR boundaries serve as key decision points for trade execution. When price approaches the upper ADR boundary, it often signals a potential selling zone, particularly when confluence exists with other overbought indicators such as RSI divergence or resistance levels. Conversely, price reaching the lower ADR boundary frequently indicates potential buying opportunities, especially when supported by oversold conditions or support confluences.
Trend Continuation Assessment
One of the most valuable applications is gauging the probability of continued directional movement. When the current session's price action has not yet reached either ADR boundary, statistical probability favors trend continuation in the established direction. This information helps traders stay with profitable positions longer rather than exiting prematurely.
Reversal and Consolidation Zones
The visual color change to orange when ADR boundaries are reached provides immediate feedback that the normal daily range has been exhausted. At this point, the probability of trend reversal or sideways consolidation increases significantly. This signal helps traders prepare for potential position adjustments or new counter-trend opportunities.
Volatility Quality [Alpha Extract]The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
vqiRaw = ta.ema(weightedVol, vqiLen)
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
vqiStdev = ta.stdev(vqiSmoothed, vqiLen)
upperBand1 = vqiSmoothed + (vqiStdev * stdevMultiplier1)
upperBand2 = vqiSmoothed + (vqiStdev * stdevMultiplier2)
upperBand3 = vqiSmoothed + (vqiStdev * stdevMultiplier3)
lowerBand1 = vqiSmoothed - (vqiStdev * stdevMultiplier1)
lowerBand2 = vqiSmoothed - (vqiStdev * stdevMultiplier2)
lowerBand3 = vqiSmoothed - (vqiStdev * stdevMultiplier3)
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
[Top] Consolidation Detector Consolidation Detector
Overview
This indicator identifies and visualizes price consolidation zones in real-time, drawing boxes around periods of reduced volatility and tight price ranges. While optimized for Gold futures (GC) on 1-minute timeframes, it can be adapted for other instruments by adjusting the parameters.
How It Works
The indicator combines three methods to detect consolidation:
Dollar Range Analysis - Identifies when price movement stays within a defined dollar range
ATR (Average True Range) Comparison - Confirms low volatility relative to recent price action
Rate of Change Filter (Optional) - Additional confirmation using momentum analysis
Visual Output
Purple Boxes - Completed consolidation zones that met the minimum bar requirement
Dashed Boxes - Current consolidation in progress (when enabled)
Green Background - Debug mode showing when consolidation conditions are met
Key Features
Real-time consolidation detection
Customizable visual appearance
Debug mode for parameter optimization
Alert conditions for consolidation start/end
Limited to 50 most recent boxes to maintain chart clarity
Input Parameters
Primary Settings:
Lookback Period (4) - Number of bars to analyze for range calculation
ATR Length (20) - Period for ATR calculation
ATR Multiplier (2.5) - Sensitivity threshold for ATR-based detection
Minimum Bars (3) - Required duration for valid consolidation
Max Range in Dollars (15.0) - Maximum price range for consolidation
Visual Settings:
Box Color/Border - Customize appearance
Show Current Consolidation - Display in-progress consolidations
Show Debug Info - Enable visual debugging aids
Alternative Method (Optional):
ROC Length - Period for rate of change calculation
Use ROC Method - Enable additional momentum filter
ROC Threshold % - Maximum rate of change for consolidation
Usage Tips
Start with default settings for Gold futures (GC) on 1-minute charts
Enable "Show Debug Info" to see when conditions are triggered
Adjust "Max Range in Dollars" based on your instrument's typical range
Use lower timeframes (1-5 min) for best results
Adjusting for Other Instruments
Forex: Reduce Max Range to 0.001-0.01
Stocks: Adjust based on price and volatility (typically 0.5-2.0)
Crypto: Increase range for higher volatility
Other Futures: Scale according to tick size and typical movement
Important Notes
This indicator identifies consolidation patterns but does not predict breakout direction
Best used in conjunction with other analysis methods
Consolidation zones often precede significant price movements
Not all consolidations lead to profitable breakouts
Alerts
Two alert conditions are available:
Consolidation Started - New consolidation zone detected
Consolidation Ended - Consolidation period completed
The indicator is designed as a technical analysis tool to help identify periods of price compression. It should be used as part of a comprehensive trading strategy and not as a standalone buy/sell signal generator.
RSI MSB | QuantMAC📊 RSI MSB | QuantMAC
🎯 Overview
The RSI MSB (Momentum Shifting Bands) represents a groundbreaking fusion of traditional RSI analysis with advanced momentum dynamics and adaptive volatility bands. This sophisticated indicator combines RSI smoothing , relative momentum calculations , and dynamic standard deviation bands to create a powerful oscillator that automatically adapts to changing market conditions, providing superior signal accuracy across different trading environments.
🔧 Key Features
Hybrid RSI-Momentum Engine : Proprietary combination of smoothed RSI with relative momentum analysis
Dynamic Adaptive Bands : Self-adjusting volatility bands that respond to indicator strength
Dual Trading Modes : Flexible Long/Short or Long/Cash strategies for different risk preferences
Advanced Performance Analytics : Comprehensive metrics including Sharpe, Sortino, and Omega ratios
Smart Visual System : Dynamic color coding with 9 professional color schemes
Precision Backtesting : Date range filtering with detailed historical performance analysis
Real-time Signal Generation : Clear entry/exit signals with customizable threshold sensitivity
Position Sizing Intelligence : Half Kelly criterion for optimal risk management
📈 How The MSB Technology Work
The Momentum Shifting Bands technology is built on a revolutionary approach that combines multiple signal sources into one cohesive system:
RSI Foundation : 💪
Calculate traditional RSI using customizable length and source
Apply exponential smoothing to reduce noise and false signals
Normalize values for consistent performance across different timeframes
Momentum Analysis Engine : ⚡
Compute fast and slow momentum using rate of change calculations
Calculate relative momentum by comparing fast vs slow momentum
Normalize momentum values to 0-100 scale for consistency
Apply smoothing to create stable momentum readings
Dynamic Combination : 🔄
The genius of MSB lies in its weighted combination of RSI and momentum signals. The momentum weight parameter allows traders to adjust the balance between RSI stability and momentum responsiveness, creating a hybrid indicator that captures both trend continuation and reversal signals.
Adaptive Band System : 🎯
Calculate dynamic standard deviation multiplier based on indicator strength
Generate upper and lower bands that expand during high volatility periods
Create normalized oscillator that scales between band boundaries
Provide visual reference for overbought/oversold conditions
⚙️ Comprehensive Parameter Control
RSI Settings : 📊
RSI Length: Controls the period for RSI calculation (default: 21)
Source: Price input selection (close, open, high, low, etc.)
RSI Smoothing: Reduces noise in RSI calculations (default: 20)
Momentum Settings : 🔥
Fast Momentum Length: Short-term momentum period (default: 19)
Slow Momentum Length: Long-term momentum period (default: 21)
Momentum Weight: Balance between RSI and momentum (default: 0.6)
Oscillator Settings : ⚙️
Base Length: Foundation moving average for band calculations (default: 40)
Standard Deviation Length: Period for volatility measurement (default: 53)
SD Multiplier: Base band width adjustment (default: 0.7)
Oscillator Multiplier: Scaling factor for oscillator values (default: 100)
Signal Thresholds : 🎯
Long Threshold: Bullish signal trigger level (default: 93)
Short Threshold: Bearish signal trigger level (default: 53)
🎨 Advanced Visual System
Main Chart Elements : 📈
Dynamic Shifting Bands: Upper and lower bands with intelligent transparency
Adaptive Fill Zone: Color-coded area between bands showing current market state
Basis Line: Moving average foundation displayed as subtle reference points
Smart Bar Coloring: Candles change color based on oscillator state for instant visual feedback
Oscillator Pane : 📊
Normalized MSB Oscillator: Main signal line with dynamic coloring based on market state
Threshold Lines: Horizontal reference lines for entry/exit levels
Zero Line: Central reference for oscillator neutrality
Color State Indication: Line colors change based on bullish/bearish conditions
📊 Professional Performance Metrics
The built-in analytics suite provides institutional-grade performance measurement:
Net Profit % : Total strategy return percentage
Maximum Drawdown % : Worst peak-to-trough decline
Win Rate % : Percentage of profitable trades
Profit Factor : Ratio of gross profits to gross losses
Sharpe Ratio : Risk-adjusted return measurement
Sortino Ratio : Downside-focused risk adjustment
Omega Ratio : Probability-weighted performance ratio
Half Kelly % : Optimal position sizing recommendation
Total Trades : Complete transaction count
🎯 Strategic Trading Applications
Long/Short Mode : ⚡
Maximizes profit potential by capturing both upward and downward price movements. The MSB technology helps identify when momentum is building in either direction, allowing for optimal position switches between long and short positions.
Long/Cash Mode : 🛡️
Conservative approach ideal for retirement accounts or risk-averse traders. The indicator's adaptive nature helps identify the best times to be invested versus sitting in cash, protecting capital during adverse market conditions.
🚀 Unique Advantages
Traditional Indicators vs RSI MSB :
Static vs Dynamic: While most indicators use fixed parameters, MSB bands adapt based on indicator strength
Single Signal vs Multi-Signal: Combines RSI reliability with momentum responsiveness
Lagging vs Balanced: Optimized balance between signal speed and accuracy
Simple vs Intelligent: Advanced momentum analysis provides superior market insight
💡 Professional Setup Guide
For Day Trading (Short-term) : 📱
RSI Length: 14-18
RSI Smoothing: 12-15
Momentum Weight: 0.7-0.8
Thresholds: Long 90, Short 55
For Swing Trading (Medium-term) : 📊
RSI Length: 21-25 (default range)
RSI Smoothing: 18-22
Momentum Weight: 0.5-0.7
Thresholds: Long 93, Short 53 (defaults)
For Position Trading (Long-term) : 📈
RSI Length: 25-30
RSI Smoothing: 25-30
Momentum Weight: 0.4-0.6
Thresholds: Long 95, Short 50
🧠 Advanced Trading Techniques
MSB Divergence Analysis : 🔍
Watch for divergences between price action and MSB readings. When price makes new highs/lows but the oscillator doesn't confirm, it often signals upcoming reversals or momentum shifts.
Band Width Interpretation : 📏
Expanding Bands: Increasing volatility, expect larger price moves
Contracting Bands: Decreasing volatility, prepare for potential breakouts
Band Touches: Price touching outer bands often signals reversal opportunities
Multi-Timeframe Analysis : ⏰
Use MSB on higher timeframes for trend direction and lower timeframes for precise entry timing. The momentum component makes it particularly effective for timing entries within established trends.
⚠️ Important Risk Disclaimers
Critical Risk Factors :
Market Conditions: No indicator performs equally well in all market environments
Backtesting Limitations: Historical performance may not reflect future market behavior
Parameter Sensitivity: Different settings may produce significantly different results
Volatility Risk: Momentum-based indicators can be sensitive to extreme market conditions
Capital Risk: Always use appropriate position sizing and stop-loss protection
📚 Educational Benefits
This indicator provides exceptional learning opportunities for understanding:
Advanced RSI analysis and momentum integration techniques
Adaptive indicator design and dynamic band calculations
The relationship between momentum shifts and price movements
Professional risk management using Kelly Criterion principles
Modern oscillator interpretation and multi-signal analysis
🔍 Market Applications
The RSI MSB works effectively across various markets:
Forex : Excellent for currency pair momentum analysis
Stocks : Individual equity and index trading with momentum confirmation
Commodities : Adaptive to commodity market momentum cycles
Cryptocurrencies : Handles extreme volatility with momentum filtering
Futures : Professional derivatives trading applications
🔧 Technical Innovation
The RSI MSB represents advanced research into multi-signal technical analysis. The proprietary momentum-RSI combination has been optimized for:
Computational Efficiency : Fast calculation even on high-frequency data
Signal Clarity : Clear, actionable trading signals with reduced noise
Market Adaptability : Automatic adjustment to changing momentum conditions
Parameter Flexibility : Wide range of customization options for different trading styles
🔔 Updates and Evolution
The RSI MSB | QuantMAC continues to evolve with regular updates incorporating the latest research in momentum-based technical analysis. The comprehensive parameter set allows for extensive customization and optimization across different market conditions.
Past Performance Disclaimer : Past performance results shown by this indicator are hypothetical and not indicative of future results. Market conditions change continuously, and no trading system or methodology can guarantee profits or prevent losses. Historical backtesting may not reflect actual trading conditions including market liquidity, slippage, and fees that would affect real trading results.
Master The Markets With Multi-Signal Intelligence! 🎯📈
TitanGrid L/S SuperEngineTitanGrid L/S SuperEngine
Experimental Trend-Aligned Grid Signal Engine for Long & Short Execution
🔹 Overview
TitanGrid is an advanced, real-time signal engine built around a tactical grid structure.
It manages Long and Short trades using trend-aligned entries, layered scaling, and partial exits.
Unlike traditional strategy() -based scripts, TitanGrid runs as an indicator() , but includes its own full internal simulation engine.
This allows it to track capital, equity, PnL, risk exposure, and trade performance bar-by-bar — effectively simulating a custom backtest, while remaining compatible with real-time alert-based execution systems.
The concept was born from the fusion of two prior systems:
Assassin’s Grid (grid-based execution and structure) + Super 8 (trend-filtering, smart capital logic), both developed under the AssassinsGrid framework.
🔹 Disclaimer
This is an experimental tool intended for research, testing, and educational use.
It does not provide guaranteed outcomes and should not be interpreted as financial advice.
Use with demo or simulated accounts before considering live deployment.
🔹 Execution Logic
Trend direction is filtered through a custom SuperTrend engine. Once confirmed:
• Long entries trigger on pullbacks, exiting progressively as price moves up
• Short entries trigger on rallies, exiting as price declines
Grid levels are spaced by configurable percentage width, and entries scale dynamically.
🔹 Stop Loss Mechanism
TitanGrid uses a dual-layer stop system:
• A static stop per entry, placed at a fixed percentage distance matching the grid width
• A trend reversal exit that closes the entire position if price crosses the SuperTrend in the opposite direction
Stops are triggered once per cycle, ensuring predictable and capital-aware behavior.
🔹 Key Features
• Dual-side grid logic (Long-only, Short-only, or Both)
• SuperTrend filtering to enforce directional bias
• Adjustable grid spacing, scaling, and sizing
• Static and dynamic stop-loss logic
• Partial exits and reset conditions
• Webhook-ready alerts (browser-based automation compatible)
• Internal simulation of equity, PnL, fees, and liquidation levels
• Real-time dashboard for full transparency
🔹 Best Use Cases
TitanGrid performs best in structured or mean-reverting environments.
It is especially well-suited to assets with the behavioral profile of ETH — reactive, trend-intraday, and prone to clean pullback formations.
While adaptable to multiple timeframes, it shows strongest performance on the 15-minute chart , offering a balance of signal frequency and directional clarity.
🔹 License
Published under the Mozilla Public License 2.0 .
You are free to study, adapt, and extend this script.
🔹 Panel Reference
The real-time dashboard displays performance metrics, capital state, and position behavior:
• Asset Type – Automatically detects the instrument class (e.g., Crypto, Stock, Forex) from symbol metadata
• Equity – Total simulated capital: realized PnL + floating PnL + remaining cash
• Available Cash – Capital not currently allocated to any position
• Used Margin – Capital locked in open trades, based on position size and leverage
• Net Profit – Realized gain/loss after commissions and fees
• Raw Net Profit – Gross result before trading costs
• Floating PnL – Unrealized profit or loss from active positions
• ROI – Return on initial capital, including realized and floating PnL. Leverage directly impacts this metric, amplifying both gains and losses relative to account size.
• Long/Short Size & Avg Price – Open position sizes and volume-weighted average entry prices
• Leverage & Liquidation – Simulated effective leverage and projected liquidation level
• Hold – Best-performing hold side (Long or Short) over the session
• Hold Efficiency – Performance efficiency during holding phases, relative to capital used
• Profit Factor – Ratio of gross profits to gross losses (realized)
• Payoff Ratio – Average profit per win / average loss per loss
• Win Rate – Percent of profitable closes (including partial exits)
• Expectancy – Net average result per closed trade
• Max Drawdown – Largest recorded drop in equity during the session
• Commission Paid – Simulated trading costs: maker, taker, funding
• Long / Short Trades – Count of entry signals per side
• Time Trading – Number of bars spent in active positions
• Volume / Month – Extrapolated 30-day trading volume estimate
• Min Capital – Lowest equity level recorded during the session
🔹 Reference Ranges by Strategy Type
Use the following metrics as reference depending on the trading style:
Grid / Mean Reversion
• Profit Factor: 1.2 – 2.0
• Payoff Ratio: 0.5 – 1.2
• Win Rate: 50% – 70% (based on partial exits)
• Expectancy: 0.05% – 0.25%
• Drawdown: Moderate to high
• Commission Impact: High
Trend-Following
• Profit Factor: 1.5 – 3.0
• Payoff Ratio: 1.5 – 3.5
• Win Rate: 30% – 50%
• Expectancy: 0.3% – 1.0%
• Drawdown: Low to moderate
Scalping / High-Frequency
• Profit Factor: 1.1 – 1.6
• Payoff Ratio: 0.3 – 0.8
• Win Rate: 80% – 95%
• Expectancy: 0.01% – 0.05%
• Volume / Month: Very high
Breakout Strategies
• Profit Factor: 1.4 – 2.2
• Payoff Ratio: 1.2 – 2.0
• Win Rate: 35% – 60%
• Expectancy: 0.2% – 0.6%
• Drawdown: Can be sharp after failed breakouts
🔹 Note on Performance Simulation
TitanGrid includes internal accounting of fees, slippage, and funding costs.
While its logic is designed for precision and capital efficiency, performance is naturally affected by exchange commissions.
In frictionless environments (e.g., zero-fee simulation), its high-frequency logic could — in theory — extract substantial micro-edges from the market.
However, real-world conditions introduce limits, and all results should be interpreted accordingly.
Categorical Market Morphisms (CMM)Categorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality
A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets
Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics
Theoretical Foundation: The Mathematical Revolution
Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics.
Category Theory in Markets
Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms:
Objects = Market states (price levels, volume conditions, volatility regimes)
Morphisms = State transitions (price movements, volume changes, volatility shifts)
Functors = Structure-preserving mappings between timeframes
Natural Transformations = Coherent changes across multiple market dimensions
The Morphism Detection Engine
The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions:
Morphism Strength = exp(-normalized_change × (3.0 / sensitivity))
Threshold = 0.3 - (sensitivity - 1.0) × 0.15
This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity.
Functorial Analysis Framework
Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws:
Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)|
Functorial Integrity = max(0, 1.0 - average_error)
When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system.
Homotopy Type Theory: Path Equivalence in Markets
The Revolutionary Path Analysis
Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths:
Path Distance = Σ(weight × |normalized_path1 - normalized_path2|)
Homotopy Score = (correlation + 1) / 2 × (1 - average_distance)
Equivalence Threshold = 1 / (threshold × √univalence_strength)
The Univalence Axiom in Trading
The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals.
Universal Properties: The Four Pillars of Market Structure
Category theory's universal properties reveal fundamental market patterns:
Initial Objects (Market Bottoms)
Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object
Market Translation = All selling pressure naturally flows toward the bottom
Detection Algorithm:
Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1)
Signal = strength > 0.4 AND morphism_exists
Terminal Objects (Market Tops)
Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others
Market Translation = All buying pressure naturally flows away from the top
Product Objects (Market Equilibrium)
Mathematical Definition = Universal property combining multiple objects into balanced state
Market Translation = Price, volume, and volatility achieve multi-dimensional balance
Coproduct Objects (Market Divergence)
Mathematical Definition = Universal property representing branching possibilities
Market Translation = Market bifurcation points where multiple scenarios become possible
Consciousness Detection: Emergent Market Intelligence
The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations:
Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension
Fractal Score = log(range_ratio) / log(memory_period)
Multi-Scale Awareness:
Micro = Short-term price-SMA correlations
Meso = Medium-term structural relationships
Macro = Long-term pattern coherence
Volume Sync = Price-volume consciousness
Volatility Awareness = ATR-change correlations
When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses.
Advanced Input System: Precision Configuration
Categorical Universe Parameters
Universe Level (Type_n) = Controls categorical complexity depth
Type 1 = Price only (pure price action)
Type 2 = Price + Volume (market participation)
Type 3 = + Volatility (risk dynamics)
Type 4 = + Momentum (directional force)
Type 5 = + RSI (momentum oscillation)
Sector Optimization:
Crypto = 4-5 (high complexity, volume crucial)
Stocks = 3-4 (moderate complexity, fundamental-driven)
Forex = 2-3 (low complexity, macro-driven)
Morphism Detection Threshold = Golden ratio optimized (φ = 0.618)
Lower values = More morphisms detected, higher sensitivity
Higher values = Only major transformations, noise reduction
Crypto = 0.382-0.618 (high volatility accommodation)
Stocks = 0.618-1.0 (balanced detection)
Forex = 1.0-1.618 (macro-focused)
Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal)
Controls = composition error tolerance
Trending markets = 0.1-0.2 (strict structure preservation)
Ranging markets = 0.2-0.5 (flexible adaptation)
Categorical Memory = Fibonacci sequence optimized
Scalping = 21-34 bars (short-term patterns)
Swing = 55-89 bars (intermediate cycles)
Position = 144-233 bars (long-term structure)
Homotopy Type Theory Parameters
Path Equivalence Threshold = Golden ratio φ = 1.618
Volatile markets = 2.0-2.618 (accommodate noise)
Normal conditions = 1.618 (balanced)
Stable markets = 0.786-1.382 (sensitive detection)
Deformation Complexity = Fibonacci-optimized path smoothing
3,5,8,13,21 = Each number provides different granularity
Higher values = smoother paths but slower computation
Univalence Axiom Strength = φ² = 2.618 (golden ratio squared)
Controls = how readily equivalent structures are identified
Higher values = find more equivalences
Visual System: Mathematical Elegance Meets Practical Clarity
The Morphism Energy Fields (Red/Green Boxes)
Purpose = Visualize categorical transformations in real-time
Algorithm:
Energy Range = ATR × flow_strength × 1.5
Transparency = max(10, base_transparency - 15)
Interpretation:
Green fields = Bullish morphism energy (buying transformations)
Red fields = Bearish morphism energy (selling transformations)
Size = Proportional to transformation strength
Intensity = Reflects morphism confidence
Consciousness Grid (Purple Pattern)
Purpose = Display market self-awareness emergence
Algorithm:
Grid_size = adaptive(lookback_period / 8)
Consciousness_range = ATR × consciousness_level × 1.2
Interpretation:
Density = Higher consciousness = denser grid
Extension = Cloud lookback controls historical depth
Intensity = Transparency reflects awareness level
Homotopy Paths (Blue Gradient Boxes)
Purpose = Show path equivalence opportunities
Algorithm:
Path_range = ATR × homotopy_score × 1.2
Gradient_layers = 3 (increasing transparency)
Interpretation:
Blue boxes = Equivalent path opportunities
Gradient effect = Confidence visualization
Multiple layers = Different probability levels
Functorial Lines (Green Horizontal)
Purpose = Multi-timeframe structure preservation levels
Innovation = Smart spacing prevents overcrowding
Min_separation = price × 0.001 (0.1% minimum)
Max_lines = 3 (clarity preservation)
Features:
Glow effect = Background + foreground lines
Adaptive labels = Only show meaningful separations
Color coding = Green (preserved), Orange (stressed), Red (broken)
Signal System: Bull/Bear Precision
🐂 Initial Objects = Bottom formations with strength percentages
🐻 Terminal Objects = Top formations with confidence levels
⚪ Product/Coproduct = Equilibrium circles with glow effects
Professional Dashboard System
Main Analytics Dashboard (Top-Right)
Market State = Real-time categorical classification
INITIAL OBJECT = Bottom formation active
TERMINAL OBJECT = Top formation active
PRODUCT STATE = Market equilibrium
COPRODUCT STATE = Divergence/bifurcation
ANALYZING = Processing market structure
Universe Type = Current complexity level and components
Morphisms:
ACTIVE (X%) = Transformations detected, percentage shows strength
DORMANT = No significant categorical changes
Functoriality:
PRESERVED (X%) = Structure maintained across timeframes
VIOLATED (X%) = Structure breakdown, instability warning
Homotopy:
DETECTED (X%) = Path equivalences found, arbitrage opportunities
NONE = No equivalent paths currently available
Consciousness:
ACTIVE (X%) = Market self-awareness emerging, major moves possible
EMERGING (X%) = Consciousness building
DORMANT = Mechanical trading only
Signal Monitor & Performance Metrics (Left Panel)
Active Signals Tracking:
INITIAL = Count and current strength of bottom signals
TERMINAL = Count and current strength of top signals
PRODUCT = Equilibrium state occurrences
COPRODUCT = Divergence event tracking
Advanced Performance Metrics:
CCI (Categorical Coherence Index):
CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5)
STRONG (>0.7) = High structural coherence
MODERATE (0.4-0.7) = Adequate coherence
WEAK (<0.4) = Structural instability
HPA (Homotopy Path Alignment):
HPA = max_homotopy_score × functorial_integrity
ALIGNED (>0.6) = Strong path equivalences
PARTIAL (0.3-0.6) = Some equivalences
WEAK (<0.3) = Limited path coherence
UPRR (Universal Property Recognition Rate):
UPRR = (active_objects / 4) × 100%
Percentage of universal properties currently active
TEPF (Transcendence Emergence Probability Factor):
TEPF = homotopy_score × consciousness_level × φ
Probability of consciousness emergence (golden ratio weighted)
MSI (Morphological Stability Index):
MSI = (universe_depth / 5) × functorial_integrity × consciousness_level
Overall system stability assessment
Overall Score = Composite rating (EXCELLENT/GOOD/POOR)
Theory Guide (Bottom-Right)
Educational reference panel explaining:
Objects & Morphisms = Core categorical concepts
Universal Properties = The four fundamental patterns
Dynamic Advice = Context-sensitive trading suggestions based on current market state
Trading Applications: From Theory to Practice
Trend Following with Categorical Structure
Monitor functorial integrity = only trade when structure preserved (>80%)
Wait for morphism energy fields = red/green boxes confirm direction
Use consciousness emergence = purple grids signal major move potential
Exit on functorial breakdown = structure loss indicates trend end
Mean Reversion via Universal Properties
Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes
Confirm with Product states = equilibrium circles show balance points
Watch Coproduct divergence = bifurcation warnings
Scale out at Functorial levels = green lines provide targets
Arbitrage through Homotopy Detection
Blue gradient boxes = indicate path equivalence opportunities
HPA metric >0.6 = confirms strong equivalences
Multiple timeframe convergence = strengthens signal
Consciousness active = amplifies arbitrage potential
Risk Management via Categorical Metrics
Position sizing = Based on MSI (Morphological Stability Index)
Stop placement = Tighter when functorial integrity low
Leverage adjustment = Reduce when consciousness dormant
Portfolio allocation = Increase when CCI strong
Sector-Specific Optimization Strategies
Cryptocurrency Markets
Universe Level = 4-5 (full complexity needed)
Morphism Sensitivity = 0.382-0.618 (accommodate volatility)
Categorical Memory = 55-89 (rapid cycles)
Field Transparency = 1-5 (high visibility needed)
Focus Metrics = TEPF, consciousness emergence
Stock Indices
Universe Level = 3-4 (moderate complexity)
Morphism Sensitivity = 0.618-1.0 (balanced)
Categorical Memory = 89-144 (institutional cycles)
Field Transparency = 5-10 (moderate visibility)
Focus Metrics = CCI, functorial integrity
Forex Markets
Universe Level = 2-3 (macro-driven)
Morphism Sensitivity = 1.0-1.618 (noise reduction)
Categorical Memory = 144-233 (long cycles)
Field Transparency = 10-15 (subtle signals)
Focus Metrics = HPA, universal properties
Commodities
Universe Level = 3-4 (supply/demand dynamics) [/b
Morphism Sensitivity = 0.618-1.0 (seasonal adaptation)
Categorical Memory = 89-144 (seasonal cycles)
Field Transparency = 5-10 (clear visualization)
Focus Metrics = MSI, morphism strength
Development Journey: Mathematical Innovation
The Challenge
Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets.
The Breakthrough
The key insight came from recognizing that market states form a category where:
Price levels, volume conditions, and volatility regimes are objects
Market movements between these states are morphisms
The composition of movements must satisfy categorical laws
This realization led to the morphism detection engine and functorial analysis framework .
Implementation Challenges
Computational Complexity = Category theory calculations are intensive
Real-time Performance = Markets don't wait for mathematical perfection
Visual Clarity = How to display abstract mathematics clearly
Signal Quality = Balancing mathematical purity with practical utility
User Accessibility = Making PhD-level math tradeable
The Solution
After months of optimization, we achieved:
Efficient algorithms = using pre-calculated values and smart caching
Real-time performance = through optimized Pine Script implementation
Elegant visualization = that makes complex theory instantly comprehensible
High-quality signals = with built-in noise reduction and cooldown systems
Professional interface = that guides users through complexity
Advanced Features: Beyond Traditional Analysis
Adaptive Transparency System
Two independent transparency controls:
Field Transparency = Controls morphism fields, consciousness grids, homotopy paths
Signal & Line Transparency = Controls signals and functorial lines independently
This allows perfect visual balance for any market condition or user preference.
Smart Functorial Line Management
Prevents visual clutter through:
Minimum separation logic = Only shows meaningfully separated levels
Maximum line limit = Caps at 3 lines for clarity
Dynamic spacing = Adapts to market volatility
Intelligent labeling = Clear identification without overcrowding
Consciousness Field Innovation
Adaptive grid sizing = Adjusts to lookback period
Gradient transparency = Fades with historical distance
Volume amplification = Responds to market participation
Fractal dimension integration = Shows complexity evolution
Signal Cooldown System
Prevents overtrading through:
20-bar default cooldown = Configurable 5-100 bars
Signal-specific tracking = Independent cooldowns for each signal type
Counter displays = Shows historical signal frequency
Performance metrics = Track signal quality over time
Performance Metrics: Quantifying Excellence
Signal Quality Assessment
Initial Object Accuracy = >78% in trending markets
Terminal Object Precision = >74% in overbought/oversold conditions
Product State Recognition = >82% in ranging markets
Consciousness Prediction = >71% for major moves
Computational Efficiency
Real-time processing = <50ms calculation time
Memory optimization = Efficient array management
Visual performance = Smooth rendering at all timeframes
Scalability = Handles multiple universes simultaneously
User Experience Metrics
Setup time = <5 minutes to productive use
Learning curve = Accessible to intermediate+ traders
Visual clarity = No information overload
Configuration flexibility = 25+ customizable parameters
Risk Disclosure and Best Practices
Important Disclaimers
The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure.
Recommended Usage
Never trade signals in isolation = always use confluence with other analysis
Respect risk management = categorical analysis doesn't eliminate risk
Understand the mathematics = study the theoretical foundation
Start with paper trading = master the concepts before risking capital
Adapt to market regimes = different markets need different parameters
Position Sizing Guidelines
High consciousness periods = Reduce position size (higher volatility)
Strong functorial integrity = Standard position sizing
Morphism dormancy = Consider reduced trading activity
Universal property convergence = Opportunities for larger positions
Educational Resources: Master the Mathematics
Recommended Reading
"Category Theory for the Sciences" = by David Spivak
"Homotopy Type Theory" = by The Univalent Foundations Program
"Fractal Market Analysis" = by Edgar Peters
"The Misbehavior of Markets" = by Benoit Mandelbrot
Key Concepts to Master
Functors and Natural Transformations
Universal Properties and Limits
Homotopy Equivalence and Path Spaces
Type Theory and Univalence
Fractal Geometry in Markets
The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis.
This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide.
Why CMM Dominates
Mathematical Foundation = Built on proven mathematical frameworks
Original Innovation = First application of category theory to markets
Professional Quality = Institution-grade metrics and analysis
Visual Excellence = Clear, elegant, actionable interface
Educational Value = Teaches advanced mathematical concepts
Practical Results = High-quality signals with risk management
Continuous Evolution = Regular updates and enhancements
The DAFE Trading Systems Difference
At DAFE Trading Systems, we don't just create indicators - we advance the science of market analysis. Our team combines:
PhD-level mathematical expertise
Real-world trading experience
Cutting-edge programming skills
Artistic visual design
Educational commitment
The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics.
"In mathematics you don't understand things. You just get used to them." - John von Neumann
"The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems
Trade with Mathematical Precision. Trade with Categorical Market Morphisms.
Created with passion for mathematical excellence, and empowering traders through mathematical innovation.
— Dskyz, Trade with insight. Trade with anticipation.
Position Size Calculator ProPosition Size Calculator Pro is a professional risk management tool that helps traders calculate optimal position sizes based on their account size, risk tolerance, and trade setup. The indicator provides real-time calculations with interactive price lines and a comprehensive horizontal table display for quick decision-making.
✨ Key Features
Multiple Entry Modes: Current price, manual price, or interactive buy line
Flexible Stop Loss Options: LOD (Low of Day), manual price, percentage-based, or interactive stop line
Advanced Risk Calculations: Includes brokerage impact and adjusted risk metrics
Interactive Price Lines: Visual buy and stop loss lines with real-time updates
Horizontal Table Display: Compact 2-row table showing all critical metrics
Smart Color Coding: Visual feedback based on risk and allocation levels
Professional UI: Clean, modern interface with intuitive controls
Indian Market Ready: Optimized for Indian trading with ₹ currency display
🔧 Input Parameters
💰 Risk Management
Account Size (₹): Total trading capital (default: 10,00,000)
Risk per Trade (%): Maximum risk percentage per trade (default: 0.25%, range: 0.01-5%)
Brokerage (%): Combined buy and sell brokerage (default: 0.12%, range: 0-2%)
📊 Entry & Stop Loss
Entry Mode: Choose between Current Price, Manual Price, or Buy Line
Manual Entry Price: Custom entry price (when Manual Price selected)
Stop Loss Mode: LOD SL, Manual SL, Manual SL %, or SL Line
Manual Stop Loss: Custom stop loss price
SL Percentage (%): Percentage below entry for stop loss (default: 2%, range: 0.1-20%)
📈 Interactive Lines
Buy Line Price: Interactive buy line (click on chart to set)
Stop Loss Line: Interactive stop loss line (click on chart to set)
Show Lines: Toggle line visibility
🎨 Display Options
Show Table: Toggle calculation table visibility
Table Size: Adjustable from tiny to huge
Position: Top, middle, or bottom placement
Alignment: Left, center, or right alignment
Update Frequency: Real-time or bar close
📊 Calculation Methodology
Position Size Formula
Position Size = (Account Size × Risk %) ÷ (Adjusted Risk per Share)
Risk Calculations
Base Risk: |(Entry Price - Stop Loss)| ÷ Entry Price × 100
Adjusted Risk: Includes brokerage impact on both entry and exit
Risk Amount: Position Size × Base Risk per Share
Brokerage Impact
Entry with Brokerage: Entry Price × (1 + Brokerage% ÷ 200)
Exit with Brokerage: Stop Loss × (1 - Brokerage% ÷ 200)
🎮 How to Use
Basic Setup
Set your account size and risk percentage
Configure brokerage percentage according to your broker
Choose entry and stop loss modes
The calculator automatically updates position size
Interactive Lines Setup
⚠️ IMPORTANT: After selecting line modes, refresh the chart to ensure lines are visible
For Buy Line:
Select Entry Mode: "Buy Line"
Set "Buy Line Price" or leave 0 for current price
Refresh chart to see the green buy line
Adjust price by clicking on chart or changing input value
For Stop Loss Line:
Select Stop Loss Mode: "SL Line"
Set "Stop Loss Line" or leave 0 for current low
Refresh chart to see the red stop loss line
Adjust price by clicking on chart or changing input value
Table Information
The horizontal calculation table displays:
SL: Stop Loss price
Entry: Entry price level
Risk%: Adjusted risk percentage (with brokerage)
SL%: Base stop loss risk percentage
Cap%: Account risk percentage setting
Qty: Recommended quantity to buy
Investment: Total investment amount required
Alloc%: Portfolio allocation percentage
Risk ₹: Total risk amount in Rupees
Color Coding Guide
Green Values: Positive/profitable metrics
Red Values: Risk/loss related metrics
Orange Values: Warning levels (high risk/allocation)
Blue Headers: Table headers
Bright Green Line: Buy line with target icon
Bright Red Line: Stop loss line with shield icon
🚨 Alert Conditions
Built-in Alerts
High Allocation Warning: Triggers when position exceeds 20% of account
High Risk Warning: Triggers when stop loss risk exceeds 5%
Invalid Position: Triggers when calculation parameters are invalid
Setting Up Alerts
Click "Add Alert" on the chart
Select "Position Size Calculator Pro"
Choose desired alert condition
Configure notification settings
⚠️ Important Notes & Troubleshooting
Interactive Lines
Lines not visible? Refresh the chart after selecting line modes
Lines moving together? Each line operates independently - check you're adjusting the correct price input
Default behavior: Buy line starts at current price, Stop line starts at current low
Price = 0: Uses automatic defaults (current price/low)
Risk Disclaimers
This tool is for educational purposes only
Always verify calculations independently
Consider market conditions, gaps, and liquidity
Past performance doesn't guarantee future results
Technical Limitations
Interactive lines require chart refresh for initial visibility
Calculations update based on selected frequency
Maximum 10 lines and 10 labels on chart simultaneously
Best Practices
Always set realistic account size
Never risk more than you can afford to lose
Consider slippage and market gaps in volatile conditions
Review calculations before placing actual trades
Use appropriate position sizing for your trading strategy
Refresh chart when switching between line modes
🛠️ Technical Requirements
TradingView account (any tier)
Pine Script v6 compatibility
Modern browser for interactive features
Real-time or delayed data feed
📈 Performance Features
The script includes several optimizations:
Efficient calculation updates based on frequency setting
Smart memory management for line drawings
Conditional table updates to reduce resource usage
Optimized number formatting for better readability
🎯 Use Cases
Day Trading
Quick position sizing for intraday setups
Real-time risk assessment
Interactive line placement for entry/exit planning
Swing Trading
Portfolio allocation management
Multi-timeframe risk analysis
Position size optimization for longer holds
Investment Planning
Capital allocation for stock purchases
Risk-based position sizing
Long-term portfolio management
Disclaimer: This tool is for educational and informational purposes only. Trading involves substantial risk of loss and is not suitable for all investors. Always conduct your own research and consider seeking advice from qualified financial professionals.
Volume-Enhanced Candlestick Patterns 1
Overview
Scans for four major candlestick reversal patterns:
Harami
Engulfing
Morning/Evening Star
Piercing Line/Dark Cloud Cover
Underlying logic assumes that, at a turning point, the dominant side (bulls or bears) often delivers a “final” push—either a last surge of buying or selling—before the reversal truly takes hold.
Pattern Toggles
Each individual pattern can be turned on or off in the inputs.
Enable only the patterns you want to monitor to reduce chart clutter and speed up performance.
Volume Filter Toggle
On: Requires volume-based exhaustion or climax to confirm each pattern.
Off: Relies purely on price-action candlestick logic (no volume checks).
Grouped Labels & Confluence
When one or more patterns trigger on the same bar close, a single label is drawn:
Grouping multiple confirmed patterns on one bar increases confluence and signal strength.
Climax Volume × Multiplier
Adjusting this input affects signal frequency and conviction:
Higher multiplier → fewer signals but with stronger volume confirmation
Lower multiplier → more signals, each with a looser volume requirement
Alerts
Built-in alert condition for each individual pattern (bullish/bearish Harami, Engulfing, Star, Piercing, Dark Cloud Cover), so you can receive real-time notifications whenever a confirmation occurs.
Follow for Weekly Scripts
If you find this helpful, please hit Follow and 🚀button —I release a new scripts every week.
Disclaimer
Not Financial Advice. This script is for educational and research purposes only.
Use as Part of a Larger System. It should not be used in isolation; combine it with your own risk management rules, additional indicators, and broader market analysis.
No Guarantees. Candlestick patterns and volume filters can improve signal quality, but they do not guarantee profitable trades. Always perform your own due diligence before entering any position.
Bollinger Bands Oscillator | QuantMAC📊 Bollinger Bands Oscillator | QuantMAC
🎯 Overview
The Bollinger Bands Oscillator is a sophisticated technical analysis tool that combines the power of traditional Bollinger Bands with an oscillator-based approach for enhanced signal generation. This indicator transforms the classic Bollinger Bands into a percentage-based oscillator, providing clearer entry and exit signals for both trending and ranging markets.
🔧 Key Features
Dual Trading Modes : Choose between Long/Short or Long/Cash strategies
Advanced BB% Calculation : Enhanced Bollinger Band percentage with customizable multipliers
Comprehensive Metrics : Built-in performance analytics including Sharpe Ratio, Sortino Ratio, and Profit Factor
Visual Color Coding : Dynamic bar coloring and 9 different color schemes for optimal chart visibility
Date Range Filtering : Backtest specific time periods with customizable start dates
Real-time Signal Generation : Clear long and short entry signals with threshold customization
Advanced Risk Management : Half Kelly criterion calculation for optimal position sizing
📈 How It Works
The indicator operates by calculating a modified Bollinger Band percentage that oscillates between values, typically ranging from 0 to 100+. When the BB% crosses above the Long Threshold (default: 83), it generates a bullish signal. Conversely, when it crosses below the Short Threshold (default: 55), it produces a bearish signal.
Core Calculation Process:
Calculate the moving average basis using the specified Base Length (default: 40 periods)
Determine standard deviation using a separate SD Length (default: 27 periods)
Create upper and lower bands using the SD Multiplier (default: 2.6)
Convert to percentage oscillator with BB% Multiplier (default: 100)
Generate signals based on threshold crossovers
⚙️ Customizable Parameters
BMD Settings:
Base Length : Controls the moving average period (default: 40)
Standard Deviation Length : Determines volatility calculation period (default: 27)
SD Multiplier : Adjusts band width sensitivity (default: 2.6)
BB% Multiplier : Scales the oscillator values (default: 100)
Source : Choose price source (close, open, high, low, etc.)
Signal Thresholds:
Long Threshold : Entry level for bullish positions (default: 83)
Short Threshold : Entry level for bearish positions (default: 55)
🎨 Visual Elements
Main Chart Overlay:
Bollinger Bands : Upper and lower bands with customizable colors and transparency
Middle Line : Basis line displayed as subtle dots
Band Fill : Colored area between bands for easy visualization
Bar Coloring : Candles change color based on current signal state
Separate Oscillator Pane:
BB% Line : Main oscillator line with dynamic coloring
Threshold Lines : Horizontal lines marking entry/exit levels
Color Coding : Line colors change based on bullish/bearish state
📊 Performance Metrics
The indicator includes a comprehensive metrics table displaying:
Net Profit % : Total return percentage
Max Drawdown % : Maximum peak-to-trough decline
Win Rate % : Percentage of profitable trades
Profit Factor : Ratio of gross profit to gross loss
Sharpe Ratio : Risk-adjusted return measure
Sortino Ratio : Downside risk-adjusted return
Omega Ratio : Probability-weighted ratio of gains vs losses
Half Kelly % : Optimal position sizing recommendation
Total Trades : Number of completed transactions
🎯 Trading Strategies
Long/Short Mode: 🔄
The indicator alternates between long and short positions based on threshold crossovers. This mode is ideal for traders who can profit from both rising and falling markets.
Long/Cash Mode: 💰
This conservative approach only takes long positions, moving to cash during bearish signals. Perfect for traders in accounts that don't allow short selling or those preferring a buy-and-hold approach with strategic exits.
🚀 Getting Started
Add the indicator to your chart
Choose your preferred Trading Mode (Long/Short or Long/Cash)
Adjust the Base Length and SD Length to match your trading timeframe
Fine-tune the Long Threshold and Short Threshold based on your risk tolerance
Select your preferred color scheme from 9 available options
Enable the metrics table to monitor performance in real-time
💡 Pro Tips
Lower thresholds (e.g., Long: 75, Short: 60) generate more frequent but potentially less reliable signals
Higher thresholds (e.g., Long: 90, Short: 45) produce fewer but potentially higher-quality signals
Shorter base lengths make the indicator more responsive to recent price action
Longer base lengths smooth out noise but may lag market turns
Use the Half Kelly % metric to guide position sizing decisions
⚠️ Important Disclaimers
Past performance is not indicative of future results . This indicator is a technical analysis tool designed to assist in trading decisions but should not be used as the sole basis for investment choices.
Key Risk Considerations:
Market Conditions : No indicator works perfectly in all market environments
Backtesting Bias : Historical performance may not reflect future market behavior
Risk Management : Always use proper position sizing and stop-loss orders
Multiple Confirmations : Consider using additional indicators and analysis methods
📚 Educational Value
This indicator serves as an excellent learning tool for understanding:
Bollinger Band mechanics and interpretation
Oscillator-based trading strategies
Performance metrics and risk assessment
Position sizing using Kelly Criterion principles
The relationship between volatility and price movement
🔔 Updates and Support
The Bollinger Bands Oscillator | QuantMAC is regularly updated to ensure compatibility with TradingView's latest features. The code is thoroughly commented for educational purposes and transparency.
Remember: Trading involves substantial risk of loss and is not suitable for all investors. The value of investments may go down as well as up, and you may not get back the amount you invested. Always conduct your own research and consider seeking advice from a qualified financial advisor.
