SPY200SMA (+4%/-3%) TQQQ/QQQ STRATEGYSummary of the Improved Strategy: When the price of AMEX:SPY is +4% above the 200SMA BUY NASDAQ:TQQQ and when the price of SPY drops to -3% under the SPY 200SMA SELL everything and slowly DCA into NASDAQ:QQQ over the next 6-12 months or until price returns to +4% above the SPY 200SMA at which point you will go back into 100% TQQQ.
Note: (if the price of QQQ goes 30% above the 200SMA of QQQ deleverage to QQQ or Sell to protect yourself from dot com level event)
More info and stats -https://www.reddit.com/r/LETFs/comments/1nhye66/spy_200sma_43_tqqqqqq_long_term_investment/
Gestão de carteira
AlphaRank - Relative Strength Portfolio StrategyWHAT IS ALPHARANK?
AlphaRank is a multi-asset relative strength portfolio system that identifies the strongest performing assets within a customizable universe of 10 instruments through pairwise comparison analysis. Unlike traditional relative strength indicators that simply compare price ratios, AlphaRank employs a tournament-style evaluation system using 7 distinct technical indicators to determine true relative strength.
METHODOLOGY - HOW IT WORKS
Core Concept: Pairwise Tournament Analysis
AlphaRank compares every asset against every other asset in your universe (45 unique pairs for 10 assets). For each pair, the system evaluates relative strength using 7 independent indicators:
- RSI (35-period) - Momentum comparison
- Rate of Change (31-period) - Price velocity analysis
- Z-Score (44-period) - Statistical deviation from mean
- Omega Ratio (30-period, smoothed) - Risk-adjusted returns using imported ratio library
- Linear Regression ROC (30-period linreg, 14-period ROC) - Trend strength and acceleration
- Kijun Sen Base (44-period SMA) - Ichimoku-style baseline comparison
- RSI ROC (45-period RSI, 15-period ROC) - Momentum acceleration
Scoring System:
For each pairwise comparison (e.g., ETH vs SOL), the system calculates all 7 indicators on the price ratio (ETH/SOL). Each indicator returns a binary signal (1 or 0). These are summed to create a pair score from 0-7.
If pair score > 3: The numerator asset (ETH) is considered relatively stronger
If pair score ≤ 3: The denominator asset (SOL) is considered relatively stronger
This creates a decisive winner for each pair (no neutral outcomes due to the odd number of indicators).
Final Ranking:
Each asset accumulates points for every pairwise comparison it wins. With 10 assets, each asset faces 9 competitors. Final scores range from 0 (lost all comparisons) to 9 (won all comparisons).
ORIGINALITY - WHY THIS IS DIFFERENT
Traditional Relative Strength:
- Compares assets to a benchmark (like SPY)
- Uses single indicator (usually RSI or price ratio)
- Binary strong/weak classification
AlphaRank Approach:
- Round-robin tournament: every asset vs every other asset
- Multi-indicator consensus (7 indicators, not 1)
- Granular ranking from 0-9 showing exact relative positioning
- Real-time tournament matrix visualization showing all head-to-head results
- Integrated backtesting with position sizing
Key Innovation: By using 7 uncorrelated indicators in a consensus model, AlphaRank reduces false signals from any single indicator's weaknesses. An asset must demonstrate strength across multiple analytical dimensions (momentum, trend, volatility, acceleration) to rank highly.
VISUAL COMPONENTS
Tournament Matrix (Top Right):
Shows every head-to-head matchup
Green dots = asset won that comparison
Red dots = asset lost that comparison
Instantly see which assets dominate across the board
RSPS Score Table (Right side of matrix):
Final relative strength scores (0-9)
Color-coded gradient showing strength hierarchy
Top Assets Table (Bottom Center):
Displays your top N ranked assets
Updates dynamically as rankings change
Equity Curve (Main Chart):
Shows backtested portfolio performance
Compares system returns vs buy-and-hold
Performance Metrics (Bottom):
Sharpe ratio, Sortino ratio, Omega ratio
Maximum drawdown
Individual asset and portfolio metrics
HOW TO USE
Setup:
Choose your 10 assets in the settings (crypto, stocks, indices, etc.)
Set your desired number of top assets to hold (default: 2)
Configure backtest start date and leverage
Interpretation:
Score 7-9: Extremely strong relative to peers - high confidence holdings
Score 4-6: Moderate relative strength - proceed with caution
Score 0-3: Weak relative to peers - avoid or consider shorting
Trading Strategy:
The system automatically allocates capital equally among the top-ranked assets and rebalances when rankings change. This creates a rotation strategy that systematically favors the strongest performers.
TECHNICAL SPECIFICATIONS
Timeframe: Works on all timeframes (1H, 4H, 1D recommended for crypto)
Assets: Fully customizable 10-asset universe
Rebalancing: Automatic when rankings change
SETTINGS EXPLAINED
Leverage Amount: Apply leverage to position sizing (1.0 = no leverage)
Startdate: When to begin backtesting calculations
Highlight Top Assets: How many top-ranked assets to hold (2-5 recommended)
Show Combined Matrix: Toggle the tournament visualization
Show Detailed Metrics: Individual asset performance statistics
Show Small Metrics Table: Simplified performance summary
BACKTESTING METHODOLOGY
The indicator includes full backtesting capabilities. It calculates:
Individual Asset Performance: Each asset's returns if held in isolation
Portfolio Performance: Combined returns of top-ranked assets
Buy & Hold Benchmark: Equal-weight portfolio of all 10 assets
Risk Metrics: Sharpe, Sortino, Omega ratios for all strategies
This allows you to validate the relative strength rotation strategy against simple buy-and-hold.
IMPORTANT NOTES
This is a rotation strategy - it does not predict absolute direction, only relative strength
Works best with correlated assets (e.g., all crypto, all tech stocks)
Requires sufficient history for indicator calculations (minimum 60 bars)
Backtesting uses historical data; future performance may differ
Not financial advice - use for educational purposes
Ekoparaloji Cyrpto StrategyEkoparaloji Crypto Strategy - User Information Document
📊 Strategy Overview
This strategy provides long-term position management in cryptocurrency markets using the averaging down (pyramiding) technique. The basic logic is to controllably grow positions as prices decline and exit when specific profit targets are reached.
🎯 Key Features
✅ Automatic Entry System
Market direction is determined using a proprietary trend identification algorithm
Trades are only opened in uptrends
Initial position opens automatically when specific conditions are met
📈 Pyramiding Mechanism
New positions are automatically added as price decreases
Up to 10 positions can be added maximum
Each addition occurs at predetermined decline levels
Risk management through dynamic position sizing
💰 Profit and Loss Management
Take Profit: All positions close when the specified percentage above average cost is reached
Stop Loss (Optional): Protects a specified percentage of total capital
A certain ratio of available capital is used in each trade
📊 Visual Tracking System
The following information is displayed in real-time on the chart:
✅ Average cost level
✅ Profit target level
✅ Stop loss level (if active)
✅ Next pyramiding level
✅ Liquidation (capital reset) level
✅ Trend indicator
🛡️ Risk Management Features
1. Dynamic Capital Protection
Automatic exit when losses exceed a specified percentage of total capital
Complete loss scenario can be previewed through liquidation level calculation
2. Position Control System
Protection preventing multiple trades on the same bar
Double trigger prevention mechanism
Maximum position limit
3. Time Filter
Optional trading within a date range
Ideal for testing on historical data
📱 Information Panel
Information table always visible in the upper right corner of the strategy:
When Position is Open:
Number of active positions
Average cost
Current price
Total capital status
Capital loss percentage
Profit target
Stop loss level and distance
Next entry level
Liquidation level and distance
When No Position:
Market trend (Uptrend/Downtrend)
Ready to trade?
Reason for waiting
Initial position size
Target profit percentage
⚙️ Adjustable Parameters
Customizable by user:
💵 Capital Amount: Base amount to be used for each position
📊 Profit Target: Profit percentage at which to exit
🛑 Stop Loss: Usage status and maximum loss percentage
📅 Time Filter: Start and end dates for testing
💬 Trade Comments: Custom labels for each trade
📘 Understanding Leverage Effect
1. What is the Leverage Effect?
Although there's no real leverage in the spot market, when Capital Amount is increased, capital usage works like leverage:
Capital Amount 5% (1.0x): 100% capital usage with full pyramiding = All your money in trades
Capital Amount 10% (2.0x): 200% capital usage with full pyramiding = Attempting to open trades worth 2x your capital
Capital Amount 15% (3.0x): 300% capital usage with full pyramiding = Attempting to open trades worth 3x your capital
⚠️ IMPORTANT: If your capital runs out in the spot market, you cannot open new positions, therefore it's recommended to keep Capital Amount at 5% or below!
⚠️ Important Warnings
Pyramiding Risk: If price continues to decline, position grows and risk increases
Capital Requirements: Up to 10 positions can be added, requiring sufficient capital
Trend Dependency: Only works in uptrends
Backtest Results: Past performance is not a guarantee of future results
Real Trading Risks: Slippage, commissions, and market conditions can affect results
🎓 How to Use
Add the strategy to your chart
Adjust parameters according to your risk appetite
Examine past performance by backtesting
Optionally set up alerts to activate notifications
Test with paper trading first
This strategy is for educational purposes. Do your own research and only trade with capital you can afford to lose.
Disclaimer: This strategy is not financial advice. All investment decisions are the user's responsibility.
Happy trading! 📊
Days Without -x% Move (Within x Days)Days Without X% Move
This indicator tracks consecutive days without a significant price drop, helping traders monitor market stability and potential risk buildup.
How It Works:
- Monitors a rolling window (default: 3 days) for the maximum drawdown
- Resets the counter when price drops by the specified percentage (default: 15%)
- Counts consecutive days where the threshold hasn't been breached
- Higher values indicate extended periods without significant corrections
Key Features:
- Configurable Drop Threshold: Set the percentage drop that resets the counter
- Adjustable Window: Define the lookback period for measuring drawdowns
- Wick Analysis: Option to include or exclude wicks in calculations
- Visual Display: Red area plot shows the current streak length
Use Cases:
- Risk management: Identify when markets are "overdue" for a correction
- Market regime analysis: Compare calm vs volatile periods
- Position sizing: Adjust exposure based on streak length
- Entry timing: Higher streak values may indicate increased correction risk
Ekoparaloji Strategy Crypto Ekoparaloji Crypto Strategy - User Information Document
📊 Strategy Overview
This strategy provides long-term position management in cryptocurrency markets using the averaging down (pyramiding) technique. The basic logic is to controllably grow positions as prices decline and exit when specific profit targets are reached.
🎯 Key Features
✅ Automatic Entry System
Market direction is determined using a proprietary trend identification algorithm
Trades are only opened in uptrends
Initial position opens automatically when specific conditions are met
📈 Pyramiding Mechanism
New positions are automatically added as price decreases
Up to 10 positions can be added maximum
Each addition occurs at predetermined decline levels
Risk management through dynamic position sizing
💰 Profit and Loss Management
Take Profit: All positions close when the specified percentage above average cost is reached
Stop Loss (Optional): Protects a specified percentage of total capital
A certain ratio of available capital is used in each trade
📊 Visual Tracking System
The following information is displayed in real-time on the chart:
✅ Average cost level
✅ Profit target level
✅ Stop loss level (if active)
✅ Next pyramiding level
✅ Liquidation (capital reset) level
✅ Trend indicator
🛡️ Risk Management Features
1. Dynamic Capital Protection
Automatic exit when losses exceed a specified percentage of total capital
Complete loss scenario can be previewed through liquidation level calculation
2. Position Control System
Protection preventing multiple trades on the same bar
Double trigger prevention mechanism
Maximum position limit
3. Time Filter
Optional trading within a date range
Ideal for testing on historical data
📱 Information Panel
Information table always visible in the upper right corner of the strategy:
When Position is Open:
Number of active positions
Average cost
Current price
Total capital status
Capital loss percentage
Profit target
Stop loss level and distance
Next entry level
Liquidation level and distance
When No Position:
Market trend (Uptrend/Downtrend)
Ready to trade?
Reason for waiting
Initial position size
Target profit percentage
⚙️ Adjustable Parameters
Customizable by user:
💵 Capital Amount: Base amount to be used for each position
📊 Profit Target: Profit percentage at which to exit
🛑 Stop Loss: Usage status and maximum loss percentage
📅 Time Filter: Start and end dates for testing
💬 Trade Comments: Custom labels for each trade
📘 Understanding Leverage Effect
1. What is the Leverage Effect?
Although there's no real leverage in the spot market, when Capital Amount is increased, capital usage works like leverage:
Capital Amount 5% (1.0x): 100% capital usage with full pyramiding = All your money in trades
Capital Amount 10% (2.0x): 200% capital usage with full pyramiding = Attempting to open trades worth 2x your capital
Capital Amount 15% (3.0x): 300% capital usage with full pyramiding = Attempting to open trades worth 3x your capital
⚠️ IMPORTANT: If your capital runs out in the spot market, you cannot open new positions, therefore it's recommended to keep Capital Amount at 5% or below!
⚠️ Important Warnings
Pyramiding Risk: If price continues to decline, position grows and risk increases
Capital Requirements: Up to 10 positions can be added, requiring sufficient capital
Trend Dependency: Only works in uptrends
Backtest Results: Past performance is not a guarantee of future results
Real Trading Risks: Slippage, commissions, and market conditions can affect results
🎓 How to Use
Add the strategy to your chart
Adjust parameters according to your risk appetite
Examine past performance by backtesting
Optionally set up alerts to activate notifications
Test with paper trading first
This strategy is for educational purposes. Do your own research and only trade with capital you can afford to lose.
Disclaimer: This strategy is not financial advice. All investment decisions are the user's responsibility.
Bubble ChartBubble Chart- Visual Market Intelligence
⸻
⚡ Quick Start - Here is how you get started in 30 seconds
Default view (Y-axis: None) = market heatmap
X-axis always = performance
Bubble size = importance (your choice of metric)
Hover any bubble for details
Switch timeframes to change the measurement window
Pick any stock ticker to see their friends
Pick one of the 143 etfs listed below and see their top constituents
That's it. Everything else is deeper cuts of data
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Overview
The Bubble Chart is a market-wide visual map designed to instantly reveal how thousands of stocks and ETFs are performing relative to their peers, all in a single glance.
It dynamically builds relationships between ~3,400 stocks and 143 ETFs , each with its own “friends list” of most-connected tickers. It’s a bit unlike all the other indicators, which you’ll see shortly. It’s a very Tops Down, then Sideways view of the market.
The 144 ETFs covered in the Bubble Chart indicator are listed here in this watchlist: www.tradingview.com
Each bubble represents a security.
X-axis → performance (% change)
Y-axis → variable (you choose the insight)
Bubble size → market cap, relative weight, or %volume
Color → relative performance (green up, red down)
Border → sector color
Your current chart’s timeframe determines the measurement window:
Intraday chart → today so far
Daily chart → week-to-date (WTD)
Weekly chart → month-to-date (MTD)
Monthly chart → year-to-date (YTD)
Everything is relative to that timeframe’s performance window — making it as useful for morning scans as for long-term sector rotations. I recommend starting with an intraday chart. The bubbles represent the day so far on this timeframe.
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📦 Version Differences
Bubble Chart Lite (Free):
✓ All features and dimensions
✓ Up to 5 bubbles displayed
✓ Perfect for tracking top movers
Bubble Chart (Invite-Only):
✓ All features and dimensions
✓ Up to 38 bubbles displayed
✓ See actual market breadth and structure
✓ Indicator name: “Bubble Chart”
✓ Available under the indicator “Bubble Chart” (Invite-Only) — details on my profile
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📊 Y-Axis Options
1. “None” - Heatmap Mode
By default, the Y-axis is set to “None”.
In this mode, the chart functions as a market heatmap, with:
Left-to-right representing relative performance (% change)
Bubble color indicating gain/loss
Bubble size reflecting your chosen metric (Market Cap, Weight, or %Volume)
Up-down randomized just for bubble separation
Think of it as a fancy heatmap with extra context — sector coloring, bubble sizing, and tooltips that surface live data.
Perfect for a quick snapshot of the day’s winners and losers across your selected universe.
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1. %Turnover
This measures conviction behind each move.
Turnover = current money flow vs. average money flow over your lookback window.
A large % move with low turnover = a weak move with little backing.
A moderate % move with high turnover = strong participation, higher conviction.
This is my personal favorite morning setup — it instantly reveals where real buying and selling pressure is emerging as the session unfolds.
A horizontal line across your selected ticker acts as a benchmark, so you can compare others’ conviction levels relative to it.
Any %turnover score >100 means more money than average is flowing in and out of this name. In the example above, ELS, AMT, SUI, and PSA were positive on the day and saw more than the average amount of money being transacted on these tickers today. Do the same for the negative (KIM, ESS, HST, etc), and you know where the money is going. Below 100, the move lacked conviction.
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2. %ATR
Measures range expansion or compression relative to average volatility.
A stock can move big in price but stay inside a tight range → no expansion.
A stock can move little but break its typical volatility boundary → range expansion.
Expansion often signals momentum continuation; compression after large moves can precede turnarounds or consolidations.
This view helps you spot early volatility inflection points.
In the example above, in XLRE, you can see there are a lot of companies that are experiencing a range expansion to the downside. These stocks are now short setup stocks, as the power is pretty overwhelming (number of top companies as well as magnitude over the 100 index). However, there are 3 Stocks that are doing something completely different than the rest. AMT, SBAC, and CCI are experiencing range expansion (volatility) to the upside. These may become the new leaders. You would have to inspect each ticker to see what’s going on.
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3. ROC(5) Z-Score
Z-Score quantifies how far a data point deviates from its mean, measured in standard deviations.
Here it’s applied to 5-period Rate of Change (ROC5).
A high positive Z-Score = performance far above its historical average.
A low (negative) Z-Score = deeply oversold vs. history.
Use this view to identify stretched momentum or mean-reversion candidates:
Stocks high on the Y-axis and green = extended upside momentum
Stocks high but red = potential reversal zones
Stocks low and red = extreme washouts that may soon rebound
This makes it a powerful stock-picking lens for traders who look for reversions or contrarian entries.
The following is the XLU and its 5 top holdings. Looked at on the daily timeframe, which means the ROC(5) score is for its weekly ROC (see timeframe discussion above).
What you can see here is most stocks are within their normal acceleration band. However BIIB is very close to -200. This is uncommon.As you can see from the chart of BIIB with it’s ROC(5) graphed below it, this does indicate a short term turn, and is a high probability long setup.
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4. RSI(15) Z-Score
Similar to the ROC version, but based on RSI(15).
It contextualizes RSI against its own historical distribution, not the fixed 0–100 scale.
When RSI’s Z-Score is above +100 → historically overbought.
Below -100 → historically oversold.
A stock with a high RSI Z-Score but negative performance may be starting to roll over.
A stock with a low RSI Z-Score but positive performance could be beginning a rebound.
This lens is especially powerful for early spotting of turning points in swing and position trades.
In this view, we can see a bunch of stocks that are at or below their -200 Z-Score which suggests RSI is going to increase soon. Taking a look at KKR, we see that it is indeed an area where we might want to look for a short term bounce. .
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5. %52-Week High / %52-Week Low
These two let you visualize positioning within the broader yearly range.
%52-Week High:
Shows how close each ticker is to its highs. Stocks near the top may be in breakout mode.
%52-Week Low:
Shows distance from the lows. Watching these can highlight potential recovery trades — many reversals start when beaten-down stocks begin to cluster and climb from their lows.
Are you really going to want to mess around with VZ? Other companies are winning the race
⸻
⚙️ Bubble Size Options
Market Cap-
Larger companies = larger bubbles.
Ideal for weighting visibility by overall size of influence in the market or sector.
ETF/Friend Weight-
Scales bubbles by their relationship weight to the target ETF or stock.
This helps identify which peers or constituents exert the most pull within the current context.
%Volume-
This scales by relative volume to average volume.
Big bubbles here mean unusual activity, perfect for spotting where participation is surging.
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👥 Friends — Relationship Mapping
Every ticker on the chart has its own “friends list.”
These aren’t arbitrary. They’re discovered through a multi-stage algorithm that analyzes co-occurrence of holdings across ETFs and sectors, roughly like social network analysis for stocks. This is what allows a chart of one stock to intelligently surface others that behave like it, whether through shared ETFs, sector overlap, or statistical co-presence.
Why Friends Matter: When you load AAPL, the chart doesn't just show random stocks. It shows AAPL's "friends", the tickers most connected to it through:
Shared ETF holdings
Sector relationships
Statistical co-movement
This means you're seeing AAPL's context, not just AAPL. Example: AAPL up 2% might look strong, but if all its friends are up 3-4%, AAPL is actually lagging. The chart reveals this instantly.
In this friendship look, you can see companies that are in better (and worse) shape for the month (we are looking at it on the “W” timeframe). If I didn’t own ORCL, INTC, or MU (hidden use tooltip), I should start looking at them.
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Common Setups - do these today
Morning Momentum Scan: - Y-axis: %Turnover - Bubble Size: %Volume - Look for: Top-right quadrant (high performance + high conviction)
Reversal Hunting: - Y-axis: RSI(15) Z-Score - Look for: Red bubbles above +100 (overbought rolling over) Green bubbles below -100 (oversold bouncing)
Sector Rotation: - Y-axis: None (heatmap mode) - Bubble Size: Market Cap - Look for: Color clustering by sector (border colors)
⸻
🧩 Data Sources
ETF Constituents:
ETF holdings are derived from information filed with the SEC’s EDGAR database, specifically N-PORT-P filings. These filings are public records submitted by ETF issuers.
Because EDGAR data can vary in structure and naming conventions, additional parsing, fuzzy matching, and ticker reconciliation logic were applied. Some inconsistencies may remain, and minor inaccuracies are possible.
EDGAR filings can also lag slightly behind real-time changes to ETF portfolios; however, for this visualization tool, that level of latency does not materially affect its purpose or insights.
Exchange & Share Count Data:
Information on exchanges and outstanding shares primarily comes from the SEC Company Facts API.
When unavailable, supplemental values are inferred from public SEC filings such as 8-K, 10-Q, and 10-K reports, and the SEC Company Submissions API for general company metadata.
All such data is publicly accessible through the SEC’s online systems.
I will update the SEC information on the ETFs once every 3 months to ensure etf constituent accuracy.
Sector & Industry Classification:
Sector and industry classifications were developed through a custom workflow that combines automated and human-reviewed methods.
An internal AI system analyzed each company’s publicly available website information to summarize business activities and assign one of 144 custom-defined industry categories.
Results were cross-checked by multiple independent classification models, and any uncertain outputs were manually reviewed for accuracy.
To improve interpretive consistency, publicly available information from StockAnalysis.com was also referenced (not republished) to inform final classifications.
Their content was used in accordance with their stated policy allowing limited reference with attribution — no full content or proprietary data was reproduced.
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🚀 How to Use It
Load the Bubble Chart on any stock, ETF, or futures symbol.
Choose your Y-axis insight — start with “None” for the heatmap.
Adjust bubble size to highlight capital weight or activity.
Switch timeframes to shift context (today, this week, month, or year).
Hover bubbles for details: sector, turnover, z-scores, %volume, and more.
⸻
❓ Frequently Asked Questions
Q: Why do I only see 5 bubbles?
A: You're using Bubble Chart Lite. The full version shows up to 39 bubbles simultaneously for complete market breadth..
To get access:
Find the "Bubble Chart" (invite-only) indicator on TradingView
Read the description for access instructions
Or visit my TradingView profile for details
Q: Can I customize which tickers appear?
A: The indicator automatically selects the most relevant tickers based on the current chart's symbol and the friends algorithm. This ensures you're seeing context, not random stocks.
Q: What timeframe should I use?
A: Any timeframe works. The chart adapts: - Intraday = today's performance - Daily = week-to-date - Weekly = month-to-date - Monthly = year-to-date
Q: How often does the friends list update?
A: Friends relationships are recalculated periodically as ETF holdings change (once every 3 months). The relationships are stable enough that daily changes are minimal.
Q: Does this work on crypto/forex?
A: Currently optimized for US equities and ETFs. Other asset classes may show limited friends data.
Q: The chart looks cluttered. Help?
A: Start with Y-axis: None and Bubble Size: Market Cap. You can also choose to pick less number of bubbles which will clear up the chart
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The Bubble Chart is a market topology engine that visualizes participation, conviction, volatility, and sentiment in real time.
Whether you’re scanning morning momentum, identifying exhausted moves, or exploring ETF ecosystems, it gives you a spatial view of where the action really is.
Make & Track An Index — Custom Weighted (by Quinn Millegan)Fixed pinescript security call issue limiting to 40 calls
Uptrick: Relative Strength Rotation SystemIntroduction
The Uptrick: Relative Strength Rotation System is an indicator engineered to implement a regime-aware tactical allocation strategy across a predefined set of user-specified assets. It visualizes a simulated equity curve produced by a closed, managed rotation engine. The system is designed to identify relative strength relationships dynamically and rotate into stronger-performing assets, while offering an optional fallback into a defensive state when market conditions are deemed unfavorable by the logic.
Overview
This indicator allocates capital by continuously evaluating the relative strength between all asset pairs within the selected group. Unlike simplistic momentum models or rank-based selectors, this system uses internally calculated scores that compare each asset across multiple dimensions, forming a comprehensive decision matrix. These scores are evaluated through a regime-aware layer that determines whether the system should remain invested or move into an idle allocation. The rotation logic is implemented through a rebalancing structure that maintains exposure to a single asset at any time, or transitions into a fallback asset such as cash or PAXG based on internal conditions. Outputs include a dynamically colored equity curve, context-sensitive labels, and optional overlays comparing buy-and-hold performance of the selected assets.
Originality
The indicator utilizes a scoring matrix based on custom asset-to-asset comparative ratios, resulting in a relational framework that evaluates assets in the context of each other rather than in isolation. Each asset is analyzed through multiple statistical dimensions, including trend strength and normalized deviation using Z-score calculations. These metrics form the foundation of an adaptive matrix used to derive consensus leadership. A key differentiator lies in the optional routing of idle allocations to PAXG—a tokenized gold asset—offering a non-cash defensive alternative that introduces both diversification and risk modulation not typically seen in rotation models. The engine also includes an override layer that filters decisions through market state awareness, adding tactical discipline during ambiguous or bearish regimes. Taken together, these features form a self-contained rotation mechanism with multiple embedded controls and fallback logic, all of which are abstracted from the user.
Inputs and Features
Exponential Length (EMA Length)
Specifies the smoothing length used by one of the internal scoring models. Lower values allow for more responsive asset comparisons, while longer values smooth out short-term volatility in score changes.
Z Score
Controls the statistical lookback length used for normalized relative comparisons. This Z-score is a cornerstone of the system’s comparative matrix, standardizing inter-asset ratio behaviors to detect statistically significant deviations from recent behavior. It allows the rotation engine to isolate and prioritize sustained leadership across assets, regardless of price volatility.
Rebalance Every N Bars
Sets how frequently the system evaluates potential changes in leadership. This controls the cadence of reallocation and can be tuned for faster or slower responsiveness.
When Bearish / Neutral, go to
Lets the user select how the system behaves during non-confirmed or bearish conditions. It can either route to a flat cash-equivalent state or into a user-defined defensive asset (such as PAXG), introducing an added layer of optional protection.
Cash Filter
Activates an override that forces the system into an idle state during unfavorable market regimes, even if a leader is otherwise present. This regime-aware mechanism adds another layer of conditional control to mitigate exposure risk.
Start Date
Defines the point in history from which the equity simulation begins. All calculations and equity values prior to this point are excluded.
Asset Inputs (Asset 1 to Asset 4)
Allow the user to specify up to four assets to be evaluated within the rotation universe. These may include crypto, forex, or other tradable symbols supported by TradingView.
PAXG Fallback Asset
Specifies the asset used as a fallback when the idle state is active and the defensive mode is set to PAXG rather than cash.
Color Settings
Users can customize the chart color palette for each asset and idle condition for enhanced clarity.
HODL Curve Toggles
Enable buy-and-hold equity curves for each input asset to be plotted for direct performance comparison with the system’s output.
Simple Mode
Reduces visual noise by simplifying the chart’s appearance and removing optional elements.
Background Color and Shadow Equity Fill
Offer additional styling options that reflect the system's current allocation, enhancing chart readability.
COLORED EQUITY CURVE - PAXG
COLORED EQUITY CURVE - CASH
SYSTEM
Current System Text Color
Allows further customization of label text for visibility across different asset themes.
Summary
The Uptrick: Relative Strength Rotation System is a rotation engine that leverages a proprietary scoring matrix to simulate tactical asset allocation. It analyzes inter-asset behavior through pairwise ratio metrics and statistically normalized scoring methods, enabling it to identify leadership dynamics within a defined universe. The inclusion of PAXG as a defensive fallback, regime-aware cash filtering, and customizable rebalancing cadence gives the system adaptability beyond traditional relative strength models. Users are provided with transparent visual feedback through an equity curve, contextual labels, buy-and-hold overlays, and real-time equity statistics. The system is not designed to disclose its internal mechanics, but it enables full visualization of its output and decisions for comparative analysis.
Disclaimer
This script is intended solely for educational and informational purposes. It does not constitute financial advice, trading signals, or an offer to buy or sell any financial instrument. Trading and investing carry risk, and past performance does not guarantee future outcomes. Users should perform their own research and consult a licensed financial advisor before making trading decisions.
NQ → NAS100 Converter by Dr WThis indicator allows traders to quickly and accurately convert stop levels from NQ (E-mini Nasdaq futures) to NAS100 (CFD) values, helping users who trade across different instruments to manage risk consistently.
Key Features:
Real-time Price Conversion:
Displays the current NQ futures price and the corresponding NAS100 price on your chart, updated every bar.
Stop Distance Conversion:
Converts a user-defined stop distance in NQ points into the equivalent NAS100 stop level using proportional scaling based on current market prices.
Customizable Labels:
Choose between Candle-attached labels (appearing near the bar) or Chart-fixed labels (HUD style).
Adjust label position, background color, text color, and label style (left, right, center).
Flexible Display Options:
Show/hide NQ price, NAS100 price, and converted stop independently.
Perfect for traders who want a quick visual reference without cluttering the chart.
Trading Direction Support:
Select Long or Short trades, and the stop conversion automatically adapts to the trade direction.
How It Works:
The indicator requests the latest NQ and NAS100 prices at your chart’s timeframe.
It calculates the NAS100 stop using the formula:
NAS_Stop = NAS_Price ± (Stop_NQ_Points / NQ_Price * NAS_Price)
+ is used for short trades, - for long trades.
The converted stop, along with the underlying prices, is displayed according to your label settings.
Use Cases:
Risk management for cross-instrument traders.
Quickly visualizing equivalent stops when trading NQ futures vs NAS100 CFDs.
An educational tool to understand proportional stop sizing between instruments.
TradingView Policy Compliance Notes:
The indicator does not provide trading advice or signals; it only performs calculations and visualizations.
It does not execute trades or connect to brokerage accounts.
All values displayed are informational only; users should independently verify stop levels before placing trades.
MNQ TopStep 50K | Ultra Quality v3.0MNQ TopStep 50K | Ultra Quality v3.0 - Publish Summary
📊 Overview
A professional-grade trading indicator designed specifically for MNQ futures traders using TopStep funded accounts. Combines 7 technical confirmations with 5 advanced safety filters to deliver high-quality trade signals while managing drawdown risk.
🎯 Key Features
Core Signal System
7-Point Confirmation: VWAP, EMA crossovers, 15-min HTF trend, MACD, RSI, ADX, and Volume
Signal Grading: Each signal is rated A+ through D based on 7 quality factors
Quality Threshold: Adjustable minimum grade requirement (A+, A, B, C, D)
Advanced Safety Filters (Customizable)
Mean Reversion Filter - Prevents chasing extended moves beyond VWAP bands
ATR Spike Filter - Avoids trading during extreme volatility events
EMA Spacing Filter - Ensures proper trend separation (optional)
Momentum Filter - Requires consecutive directional bars (optional)
Multi-Timeframe Confirmation - Aligns with 15-min trend (optional)
TopStep Risk Management
Real-time drawdown tracking
Position sizing calculator based on remaining cushion
Daily loss limit monitoring
Consecutive loss protection
Max trades per day limiter
Visual Components
VWAP with 1σ, 2σ, 3σ bands
EMA 9/21 with cloud fill
15-min EMA 50 for HTF trend
Comprehensive metrics dashboard
Risk management panel
Filter status panel
Detailed trade labels with entry, stops, and targets
⚙️ Default Settings (Balanced for Regular Signals)
Technical Indicators
Fast EMA: 9 | Slow EMA: 21 | HTF EMA: 50 (15-min)
MACD: 10/22/9
RSI: 14 period | Thresholds: 52 (buy) / 48 (sell)
ADX: 14 period | Minimum: 20
ATR: 14 period | Stop: 2x | TP1: 2x | TP2: 3x
Volume: 1.2x average required
Session Settings
Default: 9:30 AM - 11:30 AM ET (adjustable)
Avoids first 15 minutes after market open
Customizable trading hours
Safety Filters (Default Configuration)
✅ Mean Reversion: Enabled (2.5σ max from VWAP)
✅ ATR Spike: Enabled (2.0x threshold)
❌ EMA Spacing: Disabled (can enable for quality)
❌ Momentum: Disabled (can enable for quality)
❌ MTF Confirmation: Disabled (can enable for quality)
Risk Controls
Minimum Signal Quality: C (adjustable to A+ for fewer/better signals)
Min Bars Between Signals: 10
Max Trades Per Day: 5
Stop After Consecutive Losses: 2
📈 Expected Performance
With Default Settings:
Signals per week: 10-15 trades
Estimated win rate: 55-60%
Risk-Reward: 1:2 (TP1) and 1:3 (TP2)
With Aggressive Settings (Min Quality = D, All Filters Off):
Signals per week: 20-25 trades
Estimated win rate: 50-55%
With Conservative Settings (Min Quality = A, All Filters On):
Signals per week: 3-5 trades
Estimated win rate: 65-70%
🚀 How to Use
Basic Setup:
Add indicator to MNQ 5-minute chart
Adjust TopStep account settings in inputs
Set your risk per trade percentage (default: 0.5%)
Configure trading session hours
Set minimum signal quality (Start with C for balanced results)
Signal Interpretation:
Green Triangle (BUY): Long signal - all confirmations aligned
Red Triangle (SELL): Short signal - all confirmations aligned
Label Details: Shows entry, stop loss, take profit levels, position size, and signal grade
Signal Grade: A+ = Elite (6-7 points) | A = Strong (5) | B = Good (4) | C = Fair (3)
Dashboard Monitoring:
Top Right: Technical metrics and market conditions
Top Left: Filter status (which filters are passing/blocking)
Bottom Right: TopStep risk metrics and position sizing
⚡ Customization Tips
For More Signals:
Lower "Minimum Signal Quality" to D
Decrease ADX threshold to 18-20
Lower RSI thresholds to 50/50
Reduce Volume multiplier to 1.1x
Disable additional filters
For Higher Quality (Fewer Signals):
Raise "Minimum Signal Quality" to A or A+
Increase ADX threshold to 25-30
Enable all 5 advanced filters
Tighten VWAP distance to 2.0σ
Increase momentum requirement to 3-4 bars
For TopStep Compliance:
Adjust "Max Total Drawdown" and "Daily Loss Limit" to match your account
Update "Already Used Drawdown" daily
Monitor the Risk Panel for cushion remaining
Use recommended contract sizing
🛡️ Risk Disclaimer
IMPORTANT: This indicator is for educational and informational purposes only.
Past performance does not guarantee future results
All trading involves substantial risk of loss
Use proper risk management and position sizing
Test thoroughly in paper trading before live use
The indicator does not guarantee profitable trades
Adjust settings based on your risk tolerance and trading style
Always comply with your broker's and TopStep's rules
Liquidity Hunter | LucentCapitalFor LucentCapital Team Members
Translates the order book in a visual, historical & data-driven format.
Highlights Liquidity Depth, your visual guide to the order book. See where leveraged traders are most exposed and define your edge.
Levels are based on leverage onto positions & is adaptive based on the security, factoring in naturally leveraged products available to all traders globally.
Piotroski F-Score المنهج العلمي: ما هو نموذج بيوتروسكي F-Score؟
نموذج F-Score هو نظام تصنيف رقمي تم تطويره في عام 2000 من قبل جوزيف بيوتروسكي (Joseph Piotroski)، أستاذ المحاسبة في جامعة ستانفورد. الهدف من هذا النموذج هو قياس القوة المالية للشركات ذات القيمة (Value Stocks)، وتحديداً تلك التي لديها نسبة "القيمة الدفترية إلى القيمة السوقية" (Book-to-Market) مرتفعة.
الفكرة الأساسية هي فرز الشركات "الرخيصة" ظاهرياً، والتمييز بين تلك التي تتحسن أساسياتها المالية (الرابحون) وتلك التي تتدهور (الخاسرون).
يعتمد النموذج على تسعة معايير بسيطة، مقسمة إلى ثلاث فئات رئيسية. تحصل الشركة على نقطة واحدة عن كل معيار تحققه، ولا تحصل على شيء إذا لم تحققه. النتيجة النهائية هي مجموع هذه النقاط، وتتراوح من 0 (الأسوأ) إلى 9 (الأفضل).
المعايير التسعة (كيف يتم حساب النقاط):
أ) الربحية (Profitability) - (4 نقاط محتملة)
صافي الدخل إيجابي (ROA > 0): هل حققت الشركة ربحاً في العام الأخير؟ (نقطة واحدة)
التدفق النقدي التشغيلي إيجابي: هل ولّدت الشركة نقداً من عملياتها الأساسية؟ (نقطة واحدة)
جودة الأرباح (التدفق النقدي > صافي الدخل): هل التدفق النقدي التشغيلي أعلى من صافي الدخل؟ هذا يشير إلى أن الأرباح ليست مجرد قيود محاسبية. (نقطة واحدة)
تحسن العائد على الأصول (ROA): هل العائد على الأصول هذا العام أفضل من العام الماضي؟ (نقطة واحدة)
ب) الرافعة المالية والسيولة (Leverage & Liquidity) - (3 نقاط محتملة)
5. انخفاض الرافعة المالية: هل انخفضت نسبة الدين طويل الأجل إلى الأصول هذا العام مقارنة بالعام الماضي؟ (نقطة واحدة)
6. تحسن النسبة الحالية (Current Ratio): هل تحسنت سيولة الشركة قصيرة الأجل هذا العام؟ (نقطة واحدة)
7. عدم إصدار أسهم جديدة: هل قامت الشركة بتخفيف ملكية المساهمين الحاليين عن طريق إصدار أسهم جديدة خلال العام؟ (تحصل على نقطة إذا لم تصدر أسهماً جديدة).
ج) الكفاءة التشغيلية (Operating Efficiency) - (2 نقطة محتملة)
8. تحسن هامش الربح الإجمالي: هل زاد هامش الربح الإجمالي هذا العام مقارنة بالعام الماضي؟ (نقطة واحدة)
9. تحسن معدل دوران الأصول: هل زادت كفاءة الشركة في استخدام أصولها لتوليد المبيعات هذا العام؟ (نقطة واحدة)
تفسير النتائج:
نتيجة قوية (8-9 نقاط): تشير إلى أن الشركة في وضع مالي قوي جداً وأساسياتها تتحسن بشكل ملحوظ.
نتيجة محايدة (3-7 نقاط): وضع الشركة مستقر ولكن لا توجد إشارات قوية على تحسن أو تدهور كبير.
نتيجة ضعيفة (0-2 نقاط): تشير إلى أن أساسيات الشركة المالية ضعيفة وقد تكون في مسار تدهور.
2. كيفية استخدام المؤشر على TradingView
الكود الذي قدمته يجعل من السهل تطبيق هذا التحليل المعقد بنقرة زر.
التطبيق على الرسم البياني:
أضف المؤشر إلى الرسم البياني. سيظهر في نافذة منفصلة أسفله، ويعرض خطاً يمثل قيمة F-Score عبر الزمن.
فهم المدخلات (الإعدادات):
Symbol (الرمز): كما في المؤشر السابق، اتركه فارغاً لتحليل السهم الحالي، أو أدخل رمز سهم آخر للمقارنة.
Period (الفترة): يتيح لك اختيار الفترة المالية التي يتم على أساسها حساب المعايير التسعة. FY (سنوي) هو الخيار الأكثر شيوعاً لأنه يقارن أداء الشركة على أساس سنوي، وهو ما يتوافق مع تصميم النموذج الأصلي.
قراءة المخرجات البصرية:
خط F-Score: يوضح قيمة المؤشر تاريخياً. هل كانت الشركة قوية مالياً في الماضي؟ هل تحسنت مؤخراً؟
الخطوط المتقطعة: الخط الأخضر عند 8 والخط الأحمر عند 2 يمثلان حدود المناطق القوية والضعيفة.
الخلفية الملونة: تقدم ملخصاً بصرياً سريعاً:
أخضر: الشركة قوية جداً (F-Score ≥ 8).
أحمر: الشركة ضعيفة (F-Score ≤ 2).
بدون لون: الشركة في المنطقة المحايدة.
الاستخدام العملي في التحليل:
فلترة الأسهم القيمة: الاستخدام الأساسي للنموذج هو فلترة الأسهم التي تبدو "رخيصة" (مثلاً، لديها نسبة سعر إلى ربح منخفضة). سهم رخيص مع F-Score مرتفع (8 أو 9) هو مرشح استثماري واعد. سهم رخيص مع F-Score منخفض (0-2) هو على الأرجح "فخ قيمة" (value trap) يجب تجنبه.
تتبع التحولات: راقب الشركات التي ينتقل مؤشرها من المنطقة الضعيفة إلى المنطقة المحايدة أو القوية. هذا قد يكون مؤشراً مبكراً على تحول إيجابي في أداء الشركة.
تجنب المخاطر: الشركات التي لديها F-Score منخفض باستمرار هي شركات يجب التعامل معها بحذر شديد، حتى لو بدت أسعارها مغرية.
أداة تكميلية: F-Score هو أداة كمية ممتازة، لكن يجب دمجها دائماً مع تحليل نوعي (فهم نموذج عمل الشركة، إدارتها، وميزتها التنافسية).
In English
1. The Scientific Method: What is the Piotroski F-Score?
The F-Score is a numerical scoring system developed in 2000 by Joseph Piotroski, an accounting professor at Stanford University. The model's purpose is to measure the financial strength of value stocks, specifically those with a high book-to-market ratio.
The core idea is to sift through seemingly "cheap" companies and distinguish between those whose financial fundamentals are improving (the "winners") and those whose fundamentals are deteriorating (the "losers").
The model is based on nine simple criteria, divided into three main categories. A company earns one point for each criterion it meets and zero if it doesn't. The final score is the sum of these points, ranging from 0 (worst) to 9 (best).
The Nine Criteria (How Points are Scored):
A) Profitability (4 possible points)
Positive Net Income (ROA > 0): Did the company make a profit in the last year? (1 point)
Positive Operating Cash Flow: Did the company generate cash from its core operations? (1 point)
Quality of Earnings (Cash Flow > Net Income): Is operating cash flow higher than net income? This suggests earnings are not just accounting-driven. (1 point)
Improving Return on Assets (ROA): Is this year's ROA better than last year's? (1 point)
B) Leverage & Liquidity (3 possible points)
5. Lower Leverage: Did the long-term debt-to-assets ratio decrease this year compared to last year? (1 point)
6. Improving Current Ratio: Has the company's short-term liquidity improved this year? (1 point)
7. No New Share Issuance: Did the company dilute existing shareholders by issuing new shares during the year? (1 point is awarded if it did not issue new shares).
C) Operating Efficiency (2 possible points)
8. Improving Gross Margin: Did the gross profit margin increase this year compared to last year? (1 point)
9. Improving Asset Turnover: Did the company's efficiency in using its assets to generate sales improve this year? (1 point)
Interpreting the Score:
Strong Score (8-9 points): Indicates the company is in a very strong financial position and its fundamentals are improving significantly.
Neutral Score (3-7 points): The company's situation is stable, but there are no strong signals of major improvement or deterioration.
Weak Score (0-2 points): Indicates the company's financial fundamentals are weak and may be on a deteriorating path.
2. How to Use the Indicator on TradingView
The code you provided makes applying this complex analysis as simple as a click.
Applying to the Chart:
Add the indicator to a chart. It will appear in a separate pane below, displaying a line representing the F-Score's value over time.
Understanding the Inputs (Settings):
Symbol: As with the previous indicator, leave it blank to analyze the current stock, or enter another ticker for comparison.
Period: This allows you to select the fiscal period on which the nine criteria are based. FY (Fiscal Year) is the most common choice as it compares the company's performance on a year-over-year basis, which aligns with the model's original design.
Reading the Visual Outputs:
F-Score Line: Shows the historical value of the score. Was the company financially strong in the past? Has it improved recently?
Dashed Lines: The green line at 8 and the red line at 2 mark the thresholds for the strong and weak zones.
Colored Background: Provides a quick visual summary:
Green: The company is very strong (F-Score ≥ 8).
Red: The company is weak (F-Score ≤ 2).
No Color: The company is in the neutral zone.
Practical Use in Analysis:
Filtering Value Stocks: The model's primary use is to filter stocks that appear "cheap" (e.g., have a low P/E ratio). A cheap stock with a high F-Score (8 or 9) is a promising investment candidate. A cheap stock with a low F-Score (0-2) is likely a "value trap" and should be avoided.
Tracking Turnarounds: Keep an eye on companies whose score moves from the weak zone into the neutral or strong zone. This could be an early indicator of a positive turnaround in the company's performance.
Risk Avoidance: Companies with a persistently low F-Score are ones to be very cautious about, even if their prices look tempting.
A Complementary Tool: The F-Score is an excellent quantitative tool, but it should always be combined with qualitative analysis (understanding the business model, management, and competitive landscape)
Altman Z-Score Indicator
1. المنهج العلمي: ما هو نموذج ألتمان Z-Score؟
نموذج Z-Score هو صيغة إحصائية متعددة المتغيرات تم تطويرها في عام 1968 من قبل البروفيسور إدوارد ألتمان (Edward Altman)، أستاذ التمويل في جامعة نيويورك. الهدف الأساسي للنموذج هو التنبؤ باحتمالية إفلاس شركة مساهمة عامة خلال العامين التاليين.
يعتمد النموذج على دمج خمس نسب مالية أساسية، يتم استخلاصها من القوائم المالية للشركة (قائمة الدخل والميزانية العمومية). يتم ضرب كل نسبة في معامل (وزن) محدد، ثم يتم جمع النتائج للحصول على قيمة واحدة هي "Z-Score".
المعادلة الأساسية للشركات الصناعية العامة (وهي التي يطبقها الكود):
`Z = 1.2 X₁ + 1.4 X₂ + 3.3 X₃ + 0.6 X₄ + 1.0 X₅`
حيث أن:
X₁ = (رأس المال العامل / إجمالي الأصول): يقيس سيولة الشركة على المدى القصير. رأس المال العامل المرتفع يعني أن الشركة لديها أصول متداولة كافية لتغطية التزاماتها قصيرة الأجل.
X₂ = (الأرباح المحتجزة / إجمالي الأصول): يقيس الربحية التراكمية للشركة وقدرتها على تمويل أصولها من أرباحها الخاصة بدلاً من الديون.
X₃ = (الأرباح قبل الفوائد والضرائب (EBIT) / إجمالي الأصول): يقيس كفاءة الشركة في تحقيق أرباح من أصولها قبل احتساب تكاليف التمويل والضرائب. إنها مؤشر قوي على الربحية التشغيلية.
X₄ = (القيمة السوقية لحقوق الملكية / إجمالي الالتزامات): يقيس الرافعة المالية للشركة. كلما انخفضت قيمة الشركة السوقية مقارنة بديونها، زاد خطر الإفلاس.
X₅ = (إجمالي الإيرادات (المبيعات) / إجمالي الأصول): يعرف بـ "معدل دوران الأصول". يقيس مدى كفاءة الشركة في استخدام أصولها لتوليد المبيعات.
تفسير النتائج (مناطق التصنيف):
قام ألتمان بتحديد ثلاث مناطق لتصنيف الشركات بناءً على قيمة Z-Score:
1. منطقة الخطر (Distress Zone) | Z < 1.81: الشركات التي تقع في هذه المنطقة لديها احتمالية عالية جداً لمواجهة صعوبات مالية قد تؤدي إلى الإفلاس.
2. المنطقة الرمادية (Grey Zone) | 1.81 ≤ Z ≤ 2.99: الشركات في هذه المنطقة تقع في وضع غير مؤكد. لا يمكن تصنيفها بأنها آمنة أو في خطر وشيك، وتتطلب تحليلاً أعمق.
3. المنطقة الآمنة (Safe Zone) | Z > 2.99: الشركات التي تحقق نتيجة في هذه المنطقة تعتبر في وضع مالي سليم ومستقر، واحتمالية إفلاسها منخفضة جداً.
2. كيفية استخدام المؤشر على TradingView
الكود الذي قمت بتطويره يجعل استخدام هذا النموذج سهلاً للغاية. إليك كيفية استخدامه بفعالية:
1. التطبيق على الرسم البياني:
أضف المؤشر إلى الرسم البياني لأي سهم ترغب في تحليله. سيظهر المؤشر في نافذة منفصلة أسفل الرسم البياني للسعر.
2. فهم المدخلات (الإعدادات):
Symbol (الرمز): يمكنك ترك هذا الحقل فارغاً ليقوم المؤشر بتحليل السهم الحالي على الرسم البياني تلقائياً. أو يمكنك إدخال رمز سهم آخر (مثلاً `AAPL` أو `MSFT`) لتحليل تلك الشركة ومقارنتها بالشركة الحالية.
Fiscal Period (الفترة المالية): هذا هو أهم إعداد. يتيح لك اختيار البيانات التي سيعتمد عليها التحليل:
`FY` (سنوي): يستخدم بيانات آخر سنة مالية كاملة. هذا هو الخيار الأكثر شيوعاً واستقراراً.
`FQ` (ربع سنوي): يستخدم بيانات آخر ربع مالي. هذا الخيار أكثر حساسية للتغيرات قصيرة المدى.
`TTM` (آخر 12 شهراً): يستخدم البيانات المجمعة لآخر 12 شهراً. يوفر نظرة حديثة ومستمرة.
3. قراءة المخرجات البصرية:
خط Z-Score: هو الخط الرئيسي للمؤشر. حركته عبر الزمن توضح كيف يتغير الوضع المالي للشركة. هل يتحسن (الخط يرتفع) أم يتدهور (الخط ينخفض)؟
الخطوط المتقطعة: الخط الأخضر عند `2.99` والخط الأحمر عند `1.81` يمثلان حدود المناطق (الآمنة والخطر). عبور خط Z-Score لهذه الحدود يعتبر إشارة هامة.
الخلفية الملونة: هي أسرع طريقة لمعرفة وضع الشركة الحالي:
أخضر: الشركة في المنطقة الآمنة.
أصفر (رمادي): الشركة في المنطقة الرمادية.
أحمر: الشركة في منطقة الخطر.
4. الاستخدام العملي في التحليل:
التحليل الاتجاهي: لا تنظر فقط إلى القيمة الحالية. راقب اتجاه خط Z-Score على مدى عدة سنوات. شركة يرتفع مؤشرها باستمرار من 1.5 إلى 2.5 هي في مسار تحسن، بينما شركة ينخفض مؤشرها من 4.0 إلى 3.1 قد تكون في بداية مسار تدهور.
إشارات الإنذار المبكر: إذا انخفض Z-Score لشركة ما تحت 2.99 ودخل المنطقة الرمادية، فهذه دعوة للبدء في تحليل أعمق لأسباب هذا الانخفاض. إذا انخفض تحت 1.81، فهذه إشارة خطر واضحة يجب أخذها على محمل الجد.
المقارنة بين الشركات: استخدم حقل `Symbol` لمقارنة الصحة المالية لشركتين في نفس القطاع. أي منهما لديها Z-Score أعلى وأكثر استقراراً؟
تأكيد التحليل الأساسي: استخدم هذا المؤشر كأداة مساعدة بجانب تحليلاتك الأخرى، وليس كأداة وحيدة لاتخاذ القرار. فهو لا يأخذ في الاعتبار عوامل مثل الإدارة، الميزة التنافسية، أو ظروف السوق الكلية.
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In English
1. The Scientific Method: What is the Altman Z-Score Model?
The Z-Score model is a multivariate statistical formula developed in 1968 by Dr. Edward Altman, a Professor of Finance at New York University. The primary objective of the model is to predict the probability of a publicly traded company going bankrupt within the next two years.
The model works by combining five key financial ratios derived from a company's financial statements (the income statement and balance sheet). Each ratio is multiplied by a specific coefficient (weight), and the results are summed up to produce a single value: the "Z-Score."
The Original Formula for Public Manufacturing Companies (which your code implements):
`Z = 1.2 X₁ + 1.4 X₂ + 3.3 X₃ + 0.6 X₄ + 1.0 X₅`
Where:
X₁ = (Working Capital / Total Assets): Measures the company's short-term liquidity. High working capital indicates the company has sufficient current assets to cover its short-term liabilities.
X₂ = (Retained Earnings / Total Assets): Measures the company's cumulative profitability and its ability to finance its assets with its own profits instead of debt.
X₃ = (Earnings Before Interest and Taxes (EBIT) / Total Assets): Measures the company's efficiency in generating profits from its assets before accounting for financing costs and taxes. It's a strong indicator of operational profitability.
X₄ = (Market Value of Equity / Total Liabilities): Measures the company's financial leverage. The more a company's market value declines relative to its debt, the higher the bankruptcy risk.
X₅ = (Total Revenue (Sales) / Total Assets): Known as "Asset Turnover." It measures how efficiently the company is using its assets to generate sales.
Interpreting the Score (The Zones of Discrimination):
Altman identified three zones to classify companies based on their Z-Score:
1. Distress Zone | Z < 1.81: Companies in this zone have a very high probability of facing financial distress that could lead to bankruptcy.
2. Grey Zone | 1.81 ≤ Z ≤ 2.99: Companies here are in an uncertain position. They cannot be classified as either safe or in imminent danger and require deeper analysis.
3. Safe Zone | Z > 2.99: Companies with a score in this zone are considered to be in a sound and stable financial position, with a very low probability of bankruptcy.
2. How to Use the Indicator on TradingView
The code you've developed makes using this model incredibly easy. Here is how to use it effectively:
1. Applying to the Chart:
Add the indicator to the chart of any stock you wish to analyze. The indicator will appear in a separate pane below the price chart.
2. Understanding the Inputs (Settings):
Symbol: You can leave this blank for the indicator to automatically analyze the current stock on the chart. Alternatively, you can enter another stock ticker (e.g., `AAPL` or `MSFT`) to analyze that company and compare it to the current one.
Fiscal Period: This is the most important setting. It lets you choose the data on which the analysis is based:
`FY` (Fiscal Year): Uses data from the last full fiscal year. This is the most common and stable option.
`FQ` (Fiscal Quarter): Uses data from the last fiscal quarter. This option is more sensitive to short-term changes.
`TTM` (Trailing Twelve Months): Uses aggregated data from the last 12 months, providing a recent and rolling view.
3. Reading the Visual Outputs:
Z-Score Line: This is the main plot of the indicator. Its movement over time shows how the company's financial health is evolving. Is it improving (line goes up) or deteriorating (line goes down)?
Dashed Lines: The green line at `2.99` and the red line at `1.81` represent the thresholds for the Safe and Distress zones. The Z-Score line crossing these thresholds is a significant signal.
Colored Background: This is the quickest way to see the company's current status:
Green: The company is in the Safe Zone.
Yellow (Grey): The company is in the Grey Zone.
Red: The company is in the Distress Zone.
4. Practical Use in Analysis:
Trend Analysis: Don't just look at the current value. Observe the trend of the Z-Score line over several years. A company whose score is consistently rising from 1.5 to 2.5 is on an improving path, whereas a company whose score is falling from 4.0 to 3.1 may be at the beginning of a deteriorating path.
Early Warning Signals: If a company's Z-Score drops below 2.99 into the Grey Zone, it's a call to start a deeper analysis into the reasons for this decline. If it drops below 1.81, it is a clear danger signal that must be taken seriously.
Peer Comparison: Use the `Symbol` input field to compare the financial health of two companies in the same sector. Which one has a higher and more stable Z-Score?
Fundamental Analysis Confirmation: Use this indicator as a supplementary tool alongside your other analyses, not as a sole decision-making tool. It does not account for factors like management quality, competitive advantage, or macroeconomic conditions.
Risk-Reward Position SizerRisk-Reward Position Sizer – Features Checklist
Purpose:
A visual calculator and position sizing tool for day traders, providing realistic risk, stop-loss, take-profit, and reward-to-risk information based on account size and position constraints.
Features:
Flexible Risk Settings
Set risk as a percentage of your account or a fixed dollar amount per trade.
Automatically calculates position size based on desired risk and stop distance.
Stop Loss Options
Stop distance can be defined as a percent of entry price or a fixed price.
Automatically adjusts stop distance when position is cash-limited to achieve your target risk.
Take Profit Options
TP can be defined as a fixed R multiple (e.g., 2R) or fixed absolute price.
Cash-Limited Position Handling
Optional “Cap Position to Account Size” prevents buying more shares than your cash allows.
Shows actual achievable risk if your cash limits position size.
Realistic Risk / Reward Calculations
Calculates Actual Risk $ based on position size and stop distance.
Calculates Projected Win $ based on take profit and position size.
Calculates Actual Reward-to-Risk (R:R) ratio using actual stop and TP.
Position Metrics
Estimated quantity of shares/contracts to buy.
Estimated position value.
Estimated leverage used relative to account size.
Top-Right Table Display
Clear, compact table showing:
Account size
Target risk $
Actual risk $
Stop distance
Quantity
Position value
Take profit and stop-loss prices
Projected win $ and %
Projected loss %
Actual R:R
Leverage
Trading Decision Aid
Gives traders a realistic snapshot of achievable risk and reward before entering a trade.
Helps avoid the common trap of setting tight stops that don’t actually match desired account risk.
Why It’s Useful:
This indicator turns abstract risk/reward concepts into concrete, actionable numbers, helping day traders size positions safely, plan stops and targets realistically, and maintain consistent risk management across trades.
21day Structure + 1xATR Extension LineThis is a 21-day structure script that is used by Alex Desjardins (Prime Trading) along with a 1xATR line to make sure entries aren't bought extended from this structure.
ATR Exposure Sizer — € per ATR (no SL, EUR conversion)Helps you to size your lot based on ATR for a strategy with dynamic SL
Put in input what you want in risk/ATR (euro)
1 for little accounts, 100 for big ones
The tool informs you about the lot you have to put.
Relative Strength Peers -> PROFABIGHI_CAPITAL🌟 Overview
This indicator evaluates relative strength among a customizable group of assets by comparing their smoothed RSI values, identifying outperformers and underperformers through a scoring matrix. It generates visual tables to rank assets based on peer performance, aiding traders in spotting momentum leaders for potential allocation or rotation strategies.
⚙️ Settings
- Adjustable number of assets for analysis, balancing depth with performance
- RSI calculation period for momentum sensitivity
- Primary moving average type and length for initial RSI smoothing
- Optional secondary moving average type and length for advanced comparison
- Toggle for dual moving average scoring versus threshold-based evaluation
- Volatility lookback for adaptive smoothing in variable market conditions
- Table customization options like text size, header visibility, and input summaries
- Highlighting preferences for trends, top performers, and visual emphasis methods
- Enable/disable switches for RSI computations, table displays, and asset inputs
📊 Data Acquisition & Preparation
- Fetches real-time closing prices from selected asset tickers using security requests
- Cleans ticker symbols by removing exchange prefixes for consistent labeling
- Limits analysis to specified asset count to optimize processing speed
- Stores prices in dedicated variables per asset for efficient relative calculations
- Validates data integrity by detecting constant or invalid sources
- Builds an array of user-defined assets, supporting up to 40 cryptocurrency pairs
- Updates prices only on confirmed bars to ensure reliable historical alignment
📈 RSI Smoothing & Scoring Logic
- Computes base RSI on asset prices normalized against each peer for relative momentum
- Applies user-selected smoothing to RSI using various moving average methods
- Supports simple averages like SMA and EMA for basic trend filtering
- Includes advanced options such as HMA for reduced lag and VIDYA for volatility adaptation
- Handles double smoothing with optional second MA for crossover-based signals
- Assigns binary scores: outperforming (1) if smoothed RSI exceeds neutral threshold or faster MA leads slower one
- Aggregates scores across all peers into per-asset totals for overall strength ranking
- Ranks assets by descending sum, with ties preserved in top performer lists
📋 Matrix & Ranking Computation
- Constructs a comprehensive score matrix comparing each asset against every other
- Populates rows and columns with directional indicators for quick outperformance scans
- Sums row values to quantify an asset's dominance over the peer group
- Derives ranks through pairwise comparisons, prioritizing higher total scores
- Manages ties in rankings to ensure fair representation in leaderboards
- Combines matrix data into a flattened array for efficient table rendering
- Filters computations to active asset count, avoiding unnecessary overhead
📉 Visualization
- Renders a main table as a heatmap-style matrix with rocket (🚀) for outperformance and down arrow (📉) for underperformance
- Displays asset labels along axes, with diagonal blanks to avoid self-comparisons
- Includes summary columns for total scores and final ranks, with optional gradient highlighting
- Positions a compact top assets table in the upper right, listing leaders with points allocation
- Customizes appearance via text sizing, background/text emphasis, and header toggles
- Shows input parameters summary row for quick reference without menu access
- Updates visuals only on the last bar for real-time relevance without repainting
🛠 Performance & Customization
- Conditional enabling of features like RSI analysis to reduce computational load
- Modular functions for price fetching, smoothing, and scoring to enhance maintainability
- Array-based storage for scalable handling of up to 40 assets without code bloat
- Inline options for MA configurations to streamline user interface
- Tooltip guidance on each input for contextual help during setup
- Fixed table positions (bottom center for main, top right for leaders) for consistent viewing
- Handles edge cases like zero volatility or missing data with fallback logic
✅ Key Takeaways
- Delivers peer-relative momentum insights through RSI-driven scoring and visual matrices
- Flexible smoothing and dual-MA modes adapt to diverse trading styles and sensitivities
- Prioritizes top performers with ranked tables, easing asset rotation decisions
- Optimizes for performance with toggles and limits, suitable for live trading dashboards
- Combines quantitative ranks with intuitive symbols for rapid market scanning
Market Regime IndexThe Market Regime Index is a top-down macro regime nowcasting tool that offers a consolidated view of the market’s risk appetite. It tracks 32 of the world’s most influential markets across asset classes to determine investor sentiment by applying trend-following signals to each independent asset. It features adjustable parameters and a built-in alert system that notifies investors when conditions transition between Risk-On and Risk-Off regimes. The selected markets are grouped into equities (7), fixed income (9), currencies (7), commodities (5), and derivatives (4):
Equities = S&P 500 E-mini Index Futures, Nasdaq-100 E-mini Index Futures, Russell 2000 E-mini Index Futures, STOXX Europe 600 Index Futures, Nikkei 225 Index Futures, MSCI Emerging Markets Index Futures, and S&P 500 High Beta (SPHB)/Low Beta (SPLV) Ratio.
Fixed Income = US 10Y Treasury Yield, US 2Y Treasury Yield, US 10Y-02Y Yield Spread, German 10Y Bund Yield, UK 10Y Gilt Yield, US 10Y Breakeven Inflation Rate, US 10Y TIPS Yield, US High Yield Option-Adjusted Spread, and US Corporate Option-Adjusted Spread.
Currencies = US Dollar Index (DXY), Australian Dollar/US Dollar, Euro/US Dollar, Chinese Yuan/US Dollar, Pound Sterling/US Dollar, Japanese Yen/US Dollar, and Bitcoin/US Dollar.
Commodities = ICE Brent Crude Oil Futures, COMEX Gold Futures, COMEX Silver Futures, COMEX Copper Futures, and S&P Goldman Sachs Commodity Index (GSCI) Futures.
Derivatives = CBOE S&P 500 Volatility Index (VIX), ICE US Bond Market Volatility Index (MOVE), CBOE 3M Implied Correlation Index, and CBOE VIX Volatility Index (VVIX)/VIX.
All assets are directionally aligned with their historical correlation to the S&P 500. Each asset contributes equally based on its individual bullish or bearish signal. The overall market regime is calculated as the difference between the number of Risk-On and Risk-Off signals divided by the total number of assets, displayed as the percentage of markets confirming each regime. Green indicates Risk-On and occurs when the number of Risk-On signals exceeds Risk-Off signals, while red indicates Risk-Off and occurs when the number of Risk-Off signals exceeds Risk-On signals.
Bullish Signal = (Fast MA – Slow MA) > (ATR × ATR Margin)
Bearish Signal = (Fast MA – Slow MA) < –(ATR × ATR Margin)
Market Regime = (Risk-On signals – Risk-Off signals) ÷ Total assets
This indicator is designed with flexibility in mind, allowing users to include or exclude individual assets that contribute to the market regime and adjust the input parameters used for trend signal detection. These parameters apply to each independent asset, and the overall regime signal is smoothed by the signal length to reduce noise and enhance reliability. Investors can position according to the prevailing market regime by selecting factors that have historically outperformed under each regime environment to minimise downside risk and maximise upside potential:
Risk-On Equity Factors = High Beta > Cyclicals > Low Volatility > Defensives.
Risk-Off Equity Factors = Defensives > Low Volatility > Cyclicals > High Beta.
Risk-On Fixed Income Factors = High Yield > Investment Grade > Treasuries.
Risk-Off Fixed Income Factors = Treasuries > Investment Grade > High Yield.
Risk-On Commodity Factors = Industrial Metals > Energy > Agriculture > Gold.
Risk-Off Commodity Factors = Gold > Agriculture > Energy > Industrial Metals.
Risk-On Currency Factors = Cryptocurrencies > Foreign Currencies > US Dollar.
Risk-Off Currency Factors = US Dollar > Foreign Currencies > Cryptocurrencies.
In summary, the Market Regime Index is a comprehensive macro risk-management tool that identifies the current market regime and helps investors align portfolio risk with the market’s underlying risk appetite. Its intuitive, color-coded design makes it an indispensable resource for investors seeking to navigate shifting market conditions and enhance risk-adjusted performance by selecting factors that have historically outperformed. While it has proven historically valuable, asset-specific characteristics and correlations evolve over time as market dynamics change.
Risk Recommender — (Heatmap)📊 Risk Recommender — Per-Trade & Annualized (Heatmap Columns)
Estimate the optimal risk percentage for any market regime.
This tool dynamically recommends how much of your account equity to risk — either per trade or at a portfolio (annualized) level — using volatility as the guide.
⚙️ How it works
Two distinct modes give you flexibility:
1️⃣ Per-Trade (ATR-based)
• Calculates the current Average True Range (ATR) compared to its long-term baseline.
• When volatility is high (ATR ↑), risk per trade decreases to maintain constant dollar risk.
• When volatility is low (ATR ↓), risk per trade increases within your defined floor and ceiling.
• The display is normalized by stop distance (× ATR) and smoothed to avoid noise.
2️⃣ Annualized (Volatility Targeting)
• Computes realized volatility (standard deviation of log returns) and an EWMA forecast of future volatility.
• Blends current and forecast volatilities to estimate “effective” volatility.
• Scales your base risk so that portfolio volatility converges toward your chosen annual target (e.g., 20%).
• Useful for portfolio-level or systematic strategies that maintain constant volatility exposure.
🎨 Heatmap Visualization
The vertical column graph acts like a thermometer:
• 🟥 Red → “Reduce risk” (volatility high).
• 🟩 Green → “Increase risk” (volatility low).
• Smoothed and bounded between your Floor and Ceiling risk levels.
• Optional dotted guides mark those bounds.
• Label shows the current mode, recommended risk %, and key metrics (ATR ratio or effective volatility).
🔧 Key Inputs
• Base max risk per trade (%) — your normal per-trade risk budget.
• ATR length / Baseline ATR length — control sensitivity to short- vs. long-term volatility.
• Target annualized volatility (%) — portfolio volatility target for quant mode.
• λ (lambda) — smoothing factor for the EWMA volatility forecast (0.90–0.99 typical).
• Floor & Ceiling — clamps the output to avoid extreme sizing.
• Smoothing & Hysteresis — prevent rapid changes in risk recommendations.
🧮 Interpreting the Output
• “Recommended Risk (%)” = suggested portion of equity to risk on the next trade (or current exposure).
• In Per-Trade mode: reflects current ATR ÷ baseline ATR .
• In Annualized mode: reflects target volatility ÷ effective volatility .
• Use the color and height of the column as a quick visual cue for aggressiveness.
💡 Typical Use Cases
• Position-sizing overlay for discretionary traders.
• Volatility-targeting component for algorithmic or multi-asset systems.
• Educational tool to understand how volatility governs prudent risk management.
📘 Notes
• This indicator provides risk suggestions only ; it does not place trades.
• Works on any symbol or timeframe.
• Combine with your own strategy or alerts for full automation.
• All calculations use built-in Pine functions; no proprietary logic.
Tags:
#RiskManagement #ATR #Volatility #Quant #PositionSizing #SystematicTrading #AlgorithmicTrading #Portfolio #TradingStrategy #Heatmap #EWMA #Risk
15-Min RSI Scalper [SwissAlgo]15-Min RSI Scalper
Tracks RSI Momentum Loss and Gain to Generate Signals
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WHAT THIS INDICATOR CALCULATES
This indicator attempts to identify RSI directional changes (RSI momentum) using a step-by-step "ladder" method. It reads RSI(14) from the next higher timeframe relative to your chart. On a 15-minute chart, it uses 1-hour RSI. On a 5-minute chart, it uses 15-minute RSI, and so on.
How the ladder logic works:
The indicator doesn't track RSI all the time. It only starts tracking when RSI crosses into potentially extreme territory (these are called "events" in the code):
For sell signals : when RSI crosses above a dynamic upper threshold (typically between 60-80, calculated as the 90th percentile of recent RSI)
For buy signals : when RSI crosses below a dynamic lower threshold (typically between 20-40, calculated as the 10th percentile of recent RSI)
Once tracking begins, RSI movement is divided into 2-point steps (boxes). The indicator counts how many boxes RSI climbs or falls.
A signal generates only when:
RSI reverses direction by at least 2 boxes (4 RSI points) from its extreme
RSI holds that reversal for 3 consecutive confirmed bars
Example: Dynamic threshold is at 68. RSI crosses above 68 → tracking starts. RSI climbs to 76 (4 boxes up). Then it drops back to 72 and stays below that level for 3 bars → sell signal prints. The buy signal works the same way in reverse.
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SIGNAL GENERATION METHODOLOGY
Sell Signal (Red Triangle)
RSI crosses above a dynamic start level (calculated as the 90th percentile of the last 1000 bars, constrained between 60-80)
Indicator tracks upward progression in 2-point boxes
RSI reverses and drops below a boundary 2 boxes below the highest box reached
RSI remains below that boundary for 3 confirmed bars
Red triangle plots above price
Reset condition: RSI returns below 50
Buy Signal (Green Triangle)
RSI crosses below a dynamic start level (10th percentile of last 1000 bars, constrained between 20-40)
Indicator tracks downward progression in 2-point boxes
RSI reverses and rises above a boundary 2 boxes above the lowest box reached
RSI remains above that boundary for 3 confirmed bars
Green triangle plots below price
Reset condition: RSI returns above 50
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TECHNICAL PARAMETERS
All parameters are hardcoded:
RSI Period: 14
Box Size: 2 RSI points
Reversal Threshold: 2 boxes (4 RSI points)
Confirmation Period: 3 bars
Reset Level: RSI 50
Sell Start Range: 60-80 (dynamic)
Buy Start Range: 20-40 (dynamic)
Lookback for Percentile: 1000 bars
Note: Since the code is open source, users can modify these hardcoded values directly in the script to adjust sensitivity. For example, increasing the confirmation period from 3 to 5 bars will produce fewer but more conservative signals. Decreasing the box size from 2 to 1 will make the indicator more responsive to smaller RSI movements.
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KEY FEATURES
Automatic Higher Timeframe RSI
When applied to a 15-minute chart, the indicator automatically reads 1-hour RSI data. This is the next standard timeframe above 15 minutes in the indicator's logic.
Dynamic Adaptive Start Levels
Sell signals use the 90th percentile of RSI over the last 1000 bars, constrained between 60-80. Buy signals use the 10th percentile, constrained between 20-40. These thresholds recalculate on each bar based on recent data.
Ladder Box System
RSI movements are tracked in 2-point boxes. The indicator requires a 2-box reversal followed by 3 consecutive bars maintaining that reversal before generating a signal.
Dual Signal Output
Red down-triangles plot above price when the sell signal conditions are met. Green up-triangles plot below the price when buy signal conditions are met.
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REPAINTING
This indicator does not repaint. All calculations use "barstate.isconfirmed" to ensure signals appear only on closed bars. The request.security() call uses lookahead=barmerge.lookahead_off to prevent forward-looking bias.
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INTENDED CHART TIMEFRAME
This indicator is designed for use on 15-minute charts. The visual reminder table at the top of the chart indicates this requirement.
On a 15-minute chart:
RSI data comes from the 1-hour timeframe
Signals reflect 1-hour momentum shifts
3-bar confirmation equals 45 minutes of price action
Using it on other timeframes will change the higher timeframe RSI source and may produce different behavior.
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WHAT THIS INDICATOR DOES NOT DO
Does not predict future price movements
Does not provide entry or exit advice
Does not guarantee profitable trades
Does not replace comprehensive technical analysis
Does not account for fundamental factors, news events, or market structure
Does not adapt to all market conditions equally
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EDUCATIONAL USE
This indicator demonstrates one approach to momentum reversal detection using:
Multi-timeframe analysis
Adaptive thresholds via percentile calculation
Step-wise momentum tracking
Multi-bar confirmation logic
It is designed as a technical study, not a trading system. Signals represent calculated conditions based on RSI behavior, not trade recommendations. Always do your own analysis before taking market positions.
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RISK DISCLOSURE
Trading involves substantial risk of loss. This indicator:
Is for educational and informational purposes only
Does not constitute financial, investment, or trading advice
Should not be used as the sole basis for trading decisions
Has not been tested across all market conditions
May produce false signals, late signals, or no signals in certain conditions
Past performance of any indicator does not predict future results. Users must conduct their own analysis and risk assessment before making trading decisions. Always use proper risk management, including stop losses and position sizing appropriate to your account and risk tolerance.
MIT LICENSE
This code is open source and provided as-is without warranties of any kind. You may use, modify, and distribute it freely under the MIT License.
RS Alpha w/ Confidence Period | viResearchRS Alpha α w/ Confidence Period | viResearch
Conceptual Foundation and Innovation
The RS Alpha α w/ Confidence Period indicator from viResearch is a comprehensive multi-asset allocation and momentum-ranking system that integrates alpha–beta analysis, pairwise relative strength comparison, and volatility-adjusted confidence filtering.
Its primary objective is to identify dominant crypto assets during “safe” investment periods while dynamically reallocating exposure based on a calculated relative strength hierarchy.
At its core, RS Alpha α measures the systematic (β) and idiosyncratic (α) performance of each asset relative to Bitcoin (as the benchmark), combining these measures with inter-asset ratio trends to determine which assets exhibit superior momentum and market leadership.
The “Confidence Period” module introduces an additional dimension of market phase assessment, identifying safe and unsafe allocation windows based on historical equity peaks and troughs. This dynamic filter enhances portfolio resilience by restricting allocation to favorable trend conditions while avoiding high-risk market phases.
This integration of alpha–beta decomposition, relative strength comparison, and confidence-state filtering represents a quantitative evolution of traditional relative strength analysis, designed for adaptive asset rotation across major cryptocurrencies.
Technical Composition and Calculation
The indicator is structured around three major analytical layers:
1. Alpha–Beta Decomposition
-Each asset’s return is decomposed into systematic (beta) and idiosyncratic (alpha) components relative to Bitcoin using a covariance-based regression model.
-Assets with positive alpha above the median are considered outperformers and eligible for allocation.
2. Pairwise Ratio-Based Momentum Matrix
-Every asset is compared against all others through a ratio-trend matrix, where CCI-derived trend scores quantify the directional momentum between each pair.
-This matrix produces a relative strength score for each asset, reflecting its aggregate dominance in the group.
3. Confidence Period Logic (Dynamic Market Phases)
-Using the system’s internal equity curve, the script identifies peak (safe) and nadir (unsafe) periods.
-Allocation is only active during safe confidence phases, ensuring capital exposure aligns with favorable equity momentum.
-When enabled, the model can shift unallocated capital into PAXG (Gold-backed token) as a defensive asset.
By combining these layers, RS Alpha α w/ Confidence Period determines not only which assets to hold but also when to be invested, applying a systematic market-timing overlay to multi-asset selection.
Features and User Inputs
The indicator includes a rich set of customizable parameters to support portfolio and risk management preferences:
Start Date Filter – Defines the beginning of live strategy evaluation.
Display Options – Toggle drawdown metrics, background colorization, and intra-bar updates for visual customization.
Allocation Filters – Enable or disable intra-trend validation, trend source confirmation, or fallback to PAXG during cash periods.
Confidence Period Controls – Adjust the peak and nadir lookback lengths that govern safe/unsafe phase detection.
Asset Selection – Modify or replace up to seven crypto assets in the ranking matrix, including BTC, ETH, SOL, SUI, XRP, BNB, and PAXG.
Each module operates cohesively to maintain analytical transparency while allowing user-level control over system sensitivity and behavior.
Practical Applications
The RS Alpha α w/ Confidence Period indicator is suitable for both systematic traders and quantitative portfolio managers seeking dynamic asset rotation frameworks.
Key applications include:
Market Regime Detection: Identify and visualize transitions between “safe” and “unsafe” market environments using confidence overlays.
Alpha-Focused Asset Selection: Highlight crypto assets demonstrating statistically significant outperformance relative to Bitcoin.
Portfolio Rotation: Dynamically reallocate exposure toward leading assets while reducing capital risk during weak phases.
Risk-Managed Trend Participation: Utilize the confidence-state model to align exposure with favorable market momentum only.
This framework bridges quantitative finance with market regime analytics, enabling a disciplined and data-driven approach to crypto asset allocation.
Advantages and Strategic Value
RS Alpha α extends beyond traditional relative strength indicators by incorporating multi-asset covariance analysis, ratio-based dominance scoring, and volatility-aware regime filtering.
Its three-tier analytical framework — combining trend quality, performance attribution, and confidence-state validation — enhances the reliability of trend-following and rotation signals.
The system is particularly valuable for traders aiming to:
Reduce drawdowns during volatile phases.
Identify consistent outperformers early in developing market trends.
Maintain exposure only when statistical conditions indicate high confidence.
The integrated drawdown monitor, visual allocation tables, and dynamic alert system make RS Alpha α both powerful and transparent, suitable for discretionary and automated strategy workflows alike.
Alerts and Visualization
The script provides clear visual and alert-based feedback mechanisms:
Color-coded background zones differentiate safe vs. unsafe investment periods.
Allocation labels and tables display current dominant assets and their strength scores in real-time.
Max Drawdown Display offers ongoing performance diagnostics.
Alert System automatically notifies users when allocations change (e.g., “50% ETH / 50% SOL” or “100% CASH”).
These visualization features make the indicator not only analytically robust but also intuitively interpretable, even in live market environments.
Summary and Usage Tips
The RS Alpha α w/ Confidence Period | viResearch indicator represents a sophisticated evolution of relative strength analysis — combining alpha–beta decomposition, multi-asset momentum ranking, and dynamic confidence filtering to provide a structured, risk-aware framework for crypto asset rotation.
By integrating market regime awareness with systematic selection logic, it helps traders identify when to participate, what to hold, and when to stay defensive.
For best results, apply on the 1D timeframe as recommended, and use it alongside other viResearch systematic models for portfolio-level insight and tactical confirmation.
Note: Past performance does not guarantee future results. The indicator is intended for research and educational purposes within TradingView.
Ajay R5.41🔻 Ajay Gold 3H Sell Power Indicator 🔻
Precision-Based Smart Sell System for Gold (XAU/USD)
💡 Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
⚙️ Technical Foundation
The indicator uses multiple advanced confirmations:
📉 EMA Trend Filter → Confirms downtrend
💪 RSI Overbought Rejection → Momentum reversal signal
📊 MACD Bearish Cross → Confirms trend strength
🕯️ Bearish Candle Structure → Price action validation
When all conditions align, a clear 🔻 Sell Signal is plotted on the chart.
💎 Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart — fully automated internal logic.
📆 Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
📈 How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the 🔻 Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
⚠️ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate — always backtest and demo trade before using in real trading.
💬 Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
