Finlu CONTINUACION PROFinlu CONTINUACIÓN PRO is an oscillator designed to detect trend continuation signals after a pullback.
The logic is based on:
A normalized momentum similar to Finlu Momentum PRO.
A central neutral zone: when momentum pulls back into this zone without fully changing direction, it is treated as a pullback within the trend.
Internal impulse levels (1, 2 and 3) to distinguish mild pullbacks from strong impulses.
A signal line used to confirm crossovers or separation between the main line and the signal.
An optional directional filter (DMI/ADX-style) that checks trend strength before allowing a signal.
Typical usage conditions:
Bullish continuation signals when there is prior upside momentum, the oscillator pulls back into the neutral zone and then turns up again, meeting the crossover/separation condition and the directional filter.
Bearish continuation signals in the opposite scenario.
The colored background shows the dominant side of momentum and helps visualize which sections of the chart favor long or short setups.
This indicator is intended as a support tool for traders already working with market structure and supply/demand zones. It does not guarantee results and does not replace risk management or the trader’s own judgement.
Educational
Finlu Momentum PROFinlu Momentum PRO is a momentum oscillator designed to detect exhaustion zones and potential short-term reversals.
The indicator calculates a smoothed momentum from price changes and normalizes it around 0. On top of that momentum, it builds:
Overbought and oversold levels: when the main line enters these zones, it highlights extreme momentum conditions.
Central neutral zone: helps distinguish strong momentum phases from consolidation phases.
Signal line: a moving average of the momentum itself, used to confirm crossovers and exits from extreme zones.
Repetition filters: limit the number of consecutive signals to reduce noise when the market is ranging.
Reversal detection: additional conditions that require momentum to turn from extreme zones before enabling a signal.
Divergences: compares price highs and lows with the momentum line to highlight potential exhaustion of the move.
Basic usage:
Sell signals when momentum comes from overbought, loses strength and crosses below the signal line, while passing the reversal and repetition filters.
Buy signals when the opposite occurs from oversold levels.
Bearish divergences appear when price makes a higher high, but momentum makes a lower high.
Bullish divergences appear when price makes lower lows, but momentum makes higher lows.
This indicator is designed to be combined with your own price-action and market structure analysis. It is not a buy/sell recommendation or a standalone automated system. The user remains fully responsible for risk management, instrument selection and timeframe choice.
Thick Wick OverlayI have a hard time seeing the wick and made a simple overlay indicator to create a "thicker wick". You can change the thickness and wick color to your desired color and thickness.
Volatility Term Structure IndexVolatility Term Structure Index
The Volatility Term Structure Index represents a systematic approach to measuring market stress and complacency through the analysis of volatility derivatives and their term structure relationships. This indicator draws conceptual inspiration from academic research on volatility forecasting and the informational content embedded in options markets.
The theoretical foundation rests on decades of research documenting the relationship between implied volatility patterns and subsequent market returns. Black (1976) first documented the inverse relationship between equity returns and volatility changes, establishing a fundamental principle in financial economics. Whaley (2000) demonstrated how volatility indices reflect aggregate market fear and uncertainty, with systematic patterns preceding major market dislocations. Engle (2004) provided foundational work on volatility modeling that underpins modern risk measurement approaches.
Unlike momentum strategies that follow price trends or contrarian approaches that bet against prevailing sentiment, this indicator operates on regime-identification principles. The relationship between short-term and long-term implied volatility reveals market expectations about risk evolution. When markets expect calm conditions to persist, the volatility term structure typically exhibits an upward slope. When stress emerges, this relationship inverts as near-term uncertainty exceeds longer-term expectations. This structural information reflects the aggregate positioning of sophisticated derivatives market participants.
Methodology and calculation framework
The methodology incorporates statistical normalization techniques that transform raw volatility data into comparable standardized scores. Each component factor undergoes robust z-score calculation using median absolute deviation to reduce sensitivity to outliers, a technique that proves particularly valuable during market stress when traditional standard deviation measures become unreliable. These normalized components aggregate using a weighting scheme informed by historical predictive power and correlation characteristics.
The indicator produces values on a scale from zero to one hundred, where higher readings indicate calm market conditions and lower readings signal elevated stress. Readings above seventy suggest complacent environments where equity markets typically perform well. The zone between forty and seventy represents mixed conditions without strong directional bias. Readings below forty indicate meaningful stress, with values below twenty signaling crisis-level conditions.
Internal quality mechanisms enhance signal reliability by requiring confirmation across multiple underlying factors before generating actionable signals. This reduces the probability of acting on isolated or unreliable readings and improves overall signal consistency.
Professional application and portfolio integration
Professional portfolio managers recognize the value of volatility regime indicators for risk management and tactical allocation. The fundamental insight is empirically robust: periods of low and stable volatility create supportive environments for equities, while regime transitions and elevated uncertainty warrant caution. Bollerslev, Tauchen and Zhou (2009) found that variance risk premium significantly predicts equity market returns, with volatility conditions leading price performance.
For institutional investors, the index serves as one input in risk management frameworks. Asset managers might use deteriorating readings to trigger portfolio review processes, stress testing exercises, or tactical allocation adjustments. The indicator proves valuable when it diverges from consensus narratives, as volatility markets often recognize fundamental shifts before they appear in prices. Systematic investors can incorporate the index as a conditioning variable for position sizing.
This integration finds support in the concept that derivatives markets often lead equity markets. Options market participants including market makers and institutional hedgers frequently possess informational advantages regarding expected market movements and tail risk.
Practical implementation for individual investors
When the index rises into the favorable zone above seventy with confirmed signal quality, volatility conditions support equity exposure. When the index falls below forty, reducing allocations, increasing cash reserves, or implementing protective strategies becomes appropriate. The zone between these thresholds suggests mixed conditions where other analytical frameworks should take precedence.
Individual investors can treat readings as alerts warranting portfolio examination. A favorable reading might prompt consideration of whether current equity exposure aligns with targets. A stress reading could trigger review of risk reduction measures. The indicator should inform rather than dictate decisions, serving as one perspective within a broader analytical framework.
Fundamental investors can use volatility readings to assess whether the risk environment supports their positioning. Technical analysts may find that volatility conditions help contextualize price patterns. Quantitative investors might incorporate volatility factors into multi-factor models.
Trading behavior and strategy characteristics
The index employs a regime-based methodology identifying periods when market conditions favor risk exposure versus caution. The trading logic accumulates positions when volatility conditions indicate calm environments and reduces exposure when conditions deteriorate. This approach positions with prevailing volatility market signals, recognizing that volatility regimes exhibit meaningful persistence.
The indicator may signal favorable conditions while price fluctuations continue. This reflects underlying volatility metrics remaining supportive despite surface-level movements. The strategy maintains exposure during favorable volatility conditions even when prices experience temporary weakness, and advocates caution during volatility deterioration even when prices appear stable. Success requires trust in the underlying signals and acceptance that price action and volatility conditions may temporarily diverge.
Suitability and implementation requirements
The index aligns with investors possessing specific characteristics. A medium to long term horizon proves essential as volatility regimes operate over weeks to months. A risk management orientation that prioritizes avoiding large drawdowns suits the defensive nature during stress periods. Comfort with systematic decision making helps maintain discipline when signals conflict with market consensus.
The indicator proves less suitable for day traders, investors requiring constant market exposure, and those unable to tolerate periods when the indicator conflicts with price trends. Institutional investors with strict benchmark tracking requirements may find the strategy incompatible with their mandates.
For appropriate investors, the index offers a systematic framework for monitoring market conditions. By providing an objective assessment of volatility regime health, it helps recognize environment shifts and consider positioning adjustments. The strategy demands patience and discipline but rewards those characteristics with potential for improved risk-adjusted returns through drawdown reduction during stress periods.
References
Ang, A. and Chen, J. (2002) Asymmetric correlations of equity portfolios. Journal of Financial Economics, 63(3).
Black, F. (1976) Studies of stock price volatility changes. Proceedings of the 1976 Meetings of the American Statistical Association, Business and Economics Statistics Section.
Bollerslev, T., Tauchen, G. and Zhou, H. (2009) Expected stock returns and variance risk premia. The Review of Financial Studies, 22(11).
Engle, R. (2004) Risk and volatility: Econometric models and financial practice. American Economic Review, 94(3).
Whaley, R.E. (2000) The investor fear gauge. The Journal of Portfolio Management, 26(3).
สคริปต์แบบชำระเงิน
Ichimoku Multi-BG System by Pranojit Dey (Exact Alignment)It shows trend of different levels with the help of Ichimoku, VWAP, SMA and Pivot. Use it as a strong confluence for any entry. Lets trade guys...
Futures Sizing Calculator (Greg.Trading)📐 Futures Sizing Calculator
by Greg.Trading
🔍 Overview
The Futures Sizing Calculator is a visual risk-management tool built for futures traders who demand precision.
It allows you to define your entry, stop-loss, and maximum dollar risk, then instantly calculates optimal contract sizing—directly on the chart.
No spreadsheets. No mental math. Just clear, actionable risk data.
🎯 What This Indicator Does
This indicator combines trade visualization with dynamic position sizing:
✔ Draws Entry and Stop-Loss levels on the chart
✔ Highlights the risk area between entry and stop
✔ Automatically detects LONG or SHORT direction
✔ Calculates stop distance in points
✔ Determines contract size for multiple futures
✔ Displays exact dollar risk per contract size
✔ Updates instantly as prices change
📊 Supported Contracts
The calculator currently supports the most commonly traded CME micro futures:
MNQ – Micro Nasdaq
MES – Micro S&P 500
MGC – Micro Gold
Each contract is calculated using its true point value for accurate risk sizing.
🧮 How the Calculations Work (Conceptually)
The script uses a fixed-risk position sizing model, commonly used by professional traders:
1️⃣ You define a maximum dollar risk per trade
2️⃣ The script measures the distance between Entry and Stop
3️⃣ That distance is multiplied by each contract’s point value
4️⃣ Contract size is calculated to stay within your risk limit
You are shown two sizing options:
Conservative → rounded down (risk stays below limit)
Aggressive → rounded up (risk slightly exceeds limit)
This lets you choose the exposure that best fits your trading plan.
🧭 Visual Trade Mapping
To improve clarity and execution speed, the indicator provides:
🟩 Green / Red dotted lines for Entry and Stop
📦 A transparent risk box between those levels
🔁 A centered LONG or SHORT label inside the risk area
📌 A floating panel displaying all sizing calculations
Everything is placed where your eyes already are—on the chart.
⚙️ How to Use
Add the indicator to any futures chart
Set your Account Size and Risk Amount
Enter your Entry price
Enter your Stop-Loss price
Review:
Trade direction
Risk box
Contract sizing panel
Adjust entry or stop at any time and the calculations update instantly.
⭐ Why This Indicator Is Different
Unlike basic sizing calculators or static tools, this indicator:
✅ Is fully chart-based
✅ Shows real dollar risk, not estimates
✅ Supports multiple contracts at once
✅ Combines numbers with visual confirmation
✅ Is built for live execution and planning
It’s designed to be used during real trades, not just before them.
⚠️ Important Notes
• This is a risk-management tool, not a trading strategy
• It does not generate buy or sell signals
• Always confirm calculations align with your broker’s specifications
Momentum Grid v2.1 + Top StocksThis script is a multi-confirmation momentum and trend assessment tool designed to evaluate market direction using a structured scoring approach rather than single-indicator signals.
Instead of relying on one condition, the indicator combines trend, momentum, and oscillator inputs into a unified framework. Each component contributes one confirmation point, allowing users to assess bullish and bearish strength based on alignment rather than prediction.
Core logic
The script evaluates eight independent conditions:
• Price position relative to multiple exponential moving averages
• EMA trend structure and alignment
• RSI directional bias
• Stochastic momentum direction
• MACD histogram polarity
• Parabolic SAR trend confirmation
• Squeeze momentum state
• Linear regression–based momentum bias
Bullish and bearish scores are calculated separately. Signals are triggered only when a configurable minimum number of confirmations is reached, helping reduce noise during weak or mixed conditions.
CE / PE signal concept
CE and PE labels are generated when bullish or bearish confirmation scores cross the selected threshold. These signals indicate momentum alignment, not guaranteed outcomes, and are evaluated on confirmed bar data only.
Top stocks dashboard
For index context, the script optionally analyzes a small group of heavily weighted stocks associated with the selected index. Each stock is evaluated using its own trend and momentum conditions, providing a quick overview of internal market alignment rather than individual stock recommendations.
This section is intended for situational awareness and index behavior analysis, not for stock-specific trading decisions.
Dashboards and scenario guide
Visual dashboards summarize:
• Trend state across indicators
• Bullish and bearish confirmation scores
• Momentum and volatility context
The scenario guide provides reference levels derived from price and volatility calculations to assist with planning and risk awareness. These values are informational and not trade instructions.
How to use
This indicator is intended as a decision-support and context tool. It works best when combined with price structure, market conditions, and proper risk management. It does not function as a standalone trading system and does not forecast future price movement.
Invite-only note
This script is published as invite-only to maintain controlled access and consistent usage during ongoing refinement. No performance, accuracy, or profitability claims are made. Market behavior varies, and past observations do not guarantee future results.
Pattern Pro [Josh]1. Overview
Pattern Pro is a hybrid technical analysis suite designed to bridge the gap between Classic Chart Patterns and Smart Money Concepts (SMC). Reimagined with a high-contrast "Alien HUD" visual style, this script helps traders identify structural breaks, reversal patterns, and institutional zones with clarity.
2. How it Works (Methodology & Calculations)
The core engine of this script relies on identifying significant market swings using ta.pivothigh and ta.pivotlow functions. These pivot points are stored in dynamic arrays to perform geometric calculations:
Geometric Pattern Recognition:
The script calculates the slope between historical pivots using linear regression logic.
Double Tops/Bottoms: Detects equal highs/lows within a user-defined tolerance (default 0.25%) and validates them with RSI Divergence logic.
Head & Shoulders: Validates the structural hierarchy (Left Shoulder < Head > Right Shoulder) relative to the neckline.
Wedges & Flags: Analyzes trendlines connecting multiple pivots. Converging slopes indicate Wedges, while parallel slopes indicate Flags.
Smart Money Concepts (SMC):
BOS (Break of Structure): Automatically draws lines where price closes beyond a key pivot, signaling trend continuation.
FVG (Fair Value Gaps): Scans for 3-candle price imbalances and projects the 50% equilibrium level.
Supply & Demand Zones: Highlights order blocks derived from the specific candles that formed a confirmed pivot.
Confidence Score: An internal algorithm assigns a percentage score based on pattern clarity and momentum divergence (RSI).
3. Visual Features (Alien HUD)
Neon & Glow Effects: Lines are rendered with multi-layered transparency to create a "glowing" effect, ensuring visibility on dark themes.
Fog/Smoke FX: Adds depth to critical levels without cluttering the chart.
Customization: Users can toggle specific patterns, adjust pivot sensitivity (Lookback), and customize colors.
Disclaimer: This indicator is developed strictly for educational purposes regarding chart behavior and algorithmic pattern recognition.
The signals and patterns generated do not guarantee profitability or future accuracy.
Past performance is not indicative of future results.
Trading involves significant risk. Users should always practice proper risk management and use their own judgment.
ICT Liquidity Purge + SMTSimple indicator.
Instructions
Speed Improvements:
Pivot Length: 5→3 - Detects liquidity levels faster (less bars needed to confirm a pivot)
SMT Pivot Length: 5→3 - Faster SMT divergence detection
Purge Buffer: 0.1%→0.05% - Triggers purges sooner when price touches the level
Removed debug markers - No more blue triangular dots
To make it even faster, you can:
Set Pivot Length to 2 (very aggressive, more noise)
Set Purge Buffer to 0.01% (triggers almost immediately)
Adjust these in the settings based on your timeframe:
Lower timeframes (1m, 3m): Use 2-3 pivot length
Higher timeframes (15m, 1h): Use 4-5 pivot length.
Gold Pin Bar Pivot Alerts - FixedThis script is designed for the high volatility of Gold (XAU/USD). It identifies Pin Bars with body less than 30% of the candle's total range, and the candle occuring at a structural Pivot High or Pivot Low
EMA 6/50 Cross + ADX 20 + AlertsThis indicator is designd to filter noise off the EMA cross with the ADX greater than 20 condition.
MACD Oscillator PanelThis script is a MACD-based oscillator panel designed to help evaluate momentum quality and signal strength rather than producing raw crossover signals alone.
The indicator builds on the classic MACD calculation but extends it through structured filtering and visual context. Instead of treating every MACD crossover equally, this panel categorizes momentum conditions using multiple confirmation layers.
How it works
The base logic uses the standard MACD line, signal line, and histogram derived from exponential moving averages. On top of this foundation, the script evaluates momentum and trend quality using:
• Histogram direction and momentum change
• Relative volume comparison against average volume
• RSI positioning to avoid extreme conditions
• ADX-based trend strength assessment
• Higher timeframe MACD alignment for directional context
Signals are internally classified as strong, medium, or weak based on how many of these conditions align at the time of a MACD crossover.
Visual design
The oscillator panel focuses on clarity and consistency:
• Scaled MACD values maintain proportional visibility across symbols
• Histogram colors reflect momentum direction and strength
• Line fills and gradient zones provide immediate trend bias context
• Optional information table summarizes current state and momentum
No future projections are made. All values are derived from confirmed historical and real-time price data.
How to use
This panel is best used as a confirmation tool, not as a standalone trading system.
Typical usage includes:
• Validating MACD crossover signals from a price-chart indicator
• Filtering low-quality signals during weak or ranging conditions
• Aligning lower-timeframe entries with higher-timeframe momentum
Trading decisions should always be made with proper risk management and broader market context.
Invite-only note
This script is published as invite-only to maintain controlled access and consistent usage during ongoing refinement. It is intended for users who already understand MACD behavior and momentum-based analysis.
No performance, accuracy, or profitability claims are made. Market conditions vary, and past behavior does not guarantee future results.
QFX (Quantum foreign Exchange) PublicI actually use this trading signal tool myself before sharing it. It gives clear long and short signals by analyzing EMAs, mathematical calculations, and market patterns, so whether you’re just starting out or have been trading for years, it helps you spot setups and make smarter, more confident decisions.
AlphaScalp SNIPER FREEAlphaScalp SNIPER FREE is a precision scalping indicator designed to deliver clear, fast, and reliable entry signals with minimal noise.
This FREE version uses a core sniper logic to capture strong momentum moves, making it ideal for traders who want a simple, effective, and easy-to-use scalping tool.
Perfect for testing performance before upgrading to the Premium version.
✅ Key Features (FREE)
Clear BUY & SELL signals directly on the chart
1 Take Profit (TP1) and Stop Loss (SL) automatically plotted
Trend filter to reduce false signals
Non-repaint (based on candle close)
Lightweight & fast on all pairs and timeframes
⚠️ FREE Version Limitations
❌ No TP2 & TP3
❌ No advanced sniper filters
❌ Standard win rate (safe, but not aggressive)
❌ No professional trading modes
⭐ Best For
Learning sniper-style scalping
Manual scalping entries
Backtesting & replay testing
Trying before upgrading to Premium
🚀 Upgrade to SNIPER PREMIUM
The SNIPER PREMIUM version unlocks:
Higher win rate with advanced filtering
TP1 / TP2 / TP3 for scaling profits
Stronger sniper confirmation logic
Designed for serious and consistent traders
FREE to learn. PREMIUM to trade with confidence.
STRAT Candles + HTF Bias Strat Numbers including Timeframe Continuity . TheStrat is a multi-timeframe price action trading strategy developed by Rob Smith, focusing on analyzing candlestick patterns (Inside Bars, Directional Bars, Outside Bars) across different timeframes to find high-probability entry and exit points, emphasizing "Timeframe Continuity" for strength and using tight stops for small losses, ideal for identifying reversals and continuations in various markets
Pre-Market Levels Monitor - CandleClub (20 Stocks)Monitor 20 stocks simultaneously with automatic breakout/breakdown alerts based on pre-market and previous day levels.
What It Does
This indicator tracks four critical price levels for up to 20 stocks in a single dashboard:
- PMH (Pre-Market High) - Highest price from 4:00 AM - 9:30 AM ET
- PML (Pre-Market Low) - Lowest price from 4:00 AM - 9:30 AM ET
- PDH (Previous Day High) - Previous trading day's high
- PDL (Previous Day Low) - Previous trading day's low
Key Features
✅ Real-time Dashboard - All 20 stocks displayed in a color-coded table
- Green cells = Price above level (bullish)
- Red cells = Price below level (bearish)
- Gray cells = Level not yet broken
✅ Smart Alerts - Automatic notifications when stocks break key levels
- Bullish Breakout: Price breaks BOTH PMH and PDH
- Bearish Breakdown: Price breaks BOTH PML and PDL
- Maximum 2 alerts per direction per stock per day (prevents spam)
✅ Zero Manual Work - Set it and forget it
- Levels auto-update daily at 4:00 AM ET
- Works during pre-market, regular hours, and displays data on weekends
- Edge detection ensures alerts fire only once per break
✅ Fully Customizable
- Choose any 20 US stocks
- Adjustable table position and size
- Sort by total alerts, bullish alerts, or bearish alerts
- Customize session times if needed
How To Use
1. IMPORTANT: Use on a 1-minute chart (required for data batching)
2. Enable "Extended Hours" in chart settings to see pre-market data
3. Configure your 20 ticker symbols in indicator settings
4. Set up TradingView alerts for notifications
Perfect For
- Pre-market traders monitoring multiple stocks
- Day traders tracking breakout opportunities
- Swing traders watching key support/resistance levels
- Anyone who wants automated multi-stock level monitoring
Technical Details
- Pine Script v6 - Latest version for optimal performance
- Optimized batching - Stays under TradingView's API call limits
- 20-stock maximum - Due to request.security() call restrictions (20 stocks × 2 calls = 40 limit)
- TradingView Standard plan or higher required
Alert Examples
"Alert: AAPL Bullish Breakout - Break #1
PMH: $183.25 (broken)
PDH: $181.50 (broken)
Current: $183.75
Time: 10:23:15"
Default Stocks Included
Technology: AAPL, MSFT, GOOGL, AMZN, META, NVDA, TSLA, NFLX, AMD, INTC
Finance: JPM, BAC, WFC, GS, MS, C
Healthcare: JNJ, UNH, PFE, ABBV, MRK, TMO
Consumer: WMT, HD, MCD
(All symbols are fully customizable)
Settings Overview
- Symbols (1-20): Configure your watchlist
- Session Times: Adjust pre-market/RTH times (Eastern Time)
- Display Options: Table position, cell size, text size, sorting
- Time Zone: All times in Eastern Time (auto-converts to your local time)
Notes
- Alerts limited to 2 per direction per stock to prevent notification spam
- Use 1-minute chart required (batching system needs consecutive bars)
- Enable Extended Hours to capture pre-market data
- Maximum 80 alerts per day possible (20 stocks × 4 alerts max)
Version
1.0 - Initial Release (January 2026)
---
Created by Gautham Kanaparthy
This indicator is for educational purposes only and does not constitute financial advice. Trading involves risk.
BTC - Satoshis Altcoin Graveyard OVERVIEW
The Satoshi's Altcoin Graveyard (SAG) is a macro-statistical engine designed to solve the problem of Survivorship Bias . It is a well-known phenomenon in the crypto markets that the "Top 10" list is in a constant state of flux. If you look at historical data from CoinMarketCap (CMC) year by year, you will see a revolving door of projects that once seemed "too big to fail" disappearing into obscurity. Meanwhile, Bitcoin has remained the undisputed #1 since inception.
While most traders have a "gut feeling" that Altcoins eventually depreciate against Bitcoin, I believe in measuring it and drawing it on a chart for better visibility. By locking in specific "Cohorts" of market leaders from the past, we can track their inevitable decay through the Satoshi Sieve .
THE 13-COIN STATISTICAL BUCKET
To ensure an objective, non-biased audit, each cohort (we look at 2018, 2020 and 2022) is constructed using a fixed market-cap methodology from the snapshot date (excluding stablecoins):
• The Core: The Top 10 non-stablecoin assets at that time by Marketcap.
• The Risk Alpha: Representative samples from the Top #25, #50, and #100 ranks. (By including lower-ranked "riskier" alts, we capture the full statistical decay of the market, not just the "Blue Chips.")
TECHNICAL ARCHITECTURE
This script is engineered to push the boundaries of the Pine Script engine. TradingView enforces a hard limit of 40 unique data requests . By tracking 3 cohorts of 13 assets plus the Bitcoin base, this indicator utilizes exactly 40/40 requests , providing the maximum possible data density in a single chart window.
THE SPS CONCEPT (Survival Probability Score)
The SPS measures the Breadth of Survival . It answers: "How many coins from this year (the year of the snapshot) are actually outperforming BTC?"
We use a binary logic system to determine if a coin is "Winning" or "Losing" against the only benchmark that matters: Bitcoin.
• The Status Formula: Status = Current_Alt_BTC_Ratio >= Entry_Alt_BTC_Ratio ? 1 : 0 . This means: Every single day, at the Daily Close , the script compares the current Alt/BTC ratio to the fixed ratio from the snapshot date. If the coin is worth more in Bitcoin today than it was back then, it is assigned a "1" (a Win). If it has lost value against Bitcoin, it gets a "0" (a Loss).
• The SPS Line: SPS Line = (Sum of 'Wins' / 13) * 100 This means: We add up all the "Winners" for that specific day and turn it into a percentage. For example, if the Aqua line is at 7.69% on your chart, it confirms that on that day , exactly 1 out of the 13 coins was successfully beating Bitcoin, while the other 12 were underperforming.
THE PERFORMANCE MATRIX
In the top-right corner, we provide a Weighted Portfolio Simulation . This answers the financial question: "If I swapped 1 BTC into an equal-weight basket of these 13 coins on the snapshot day, what is my BTC value today?".
• Value < 1.0 BTC: You lost purchasing power compared to holding Bitcoin.
• Value > 1.0 BTC: You successfully achieved "Alpha" over the benchmark.
HOW TO READ THE CHART
• The Waterfall: Lines generally trend downward as the "Satoshi Sieve" filters out assets that cannot maintain their BTC-relative value.
• Dynamic Winners: We dynamically print the names of the current survivors at the tip of each line. If a cohort shows "None," the graveyard is full.
HOW TO READ THE MATRIX
• The BTC Target: Any portfolio value in the matrix below 1.0 BTC represents a failed altcoin rotation.
• Class of 2018: A portfolio value near 0.15 BTC at the current date, means a 85% loss rate.
• Class of 2020: A portfolio value near 0.77 BTC at the current date, means an approx 20 % loss rate.
• Class of 2022: A portfolio value near 0.31 BTC at the current date, means an approx 70% loss rate.
DIFFERENCE FROM AN ALTCOIN INDEX
Standard Altcoin Indexes (like my ALSI Index ) "rebalance" by removing losers and adding new winners. This is deceptive. The Altcoin Graveyard never rebalances . It forces you to watch the "losers" decay, providing a realistic look at the long-term opportunity cost of "Buy and Hold" for anything other than Bitcoin.
CONCLUSION
The data revealed by the Satoshi Sieve leads to a singular, sobering "Lesson Learned": Picking the right coin to outperform Bitcoin is not just difficult—it is statistically improbable over a long-term horizon.
While the "Risk-Reward" of altcoins is often marketed as having higher upside, the Altcoin Graveyard proves that for the vast majority of assets, the reward does not justify the risk of total portfolio erosion in BTC terms.
• The Mathematical Odds: If you picked a Top 10 coin in 2018, your chance of outperforming BTC today is effectively 0%.
• The Rotation Trap: Most investors "HODL" these assets into the graveyard, hoping for a return to previous ATHs that never comes because the liquidity has already moved on to the next "Class" of winners.
The final conclusion is clear: Diversification into altcoins is often just a slow-motion transfer of wealth back to Bitcoin. If you cannot identify the 1-out-of-13 that survives the Sieve, your best risk-adjusted move has historically been to simply hold the benchmark.
DISCLAIMER
This script is for educational purposes only. It does not constitute financial advice. It is a mathematical study of historical opportunity cost and survivorship bias.
Tags
bitcoin, btc, satoshis graveyard, altseason, dominance, total3, rotation, cycle, index, alsi, Rob Maths, robmaths
ABCD Strategy (v6 Ready)//@version=6
indicator("ABCD Strategy v7 – MTF S/R Filter", overlay=true, max_lines_count=300, max_labels_count=300)
//━━━━━━━━━━━━━━━━━━━━━
// INPUTS
//━━━━━━━━━━━━━━━━━━━━━
pivotLen = input.int(5, "Swing Strength", minval=2)
bcMin = input.float(0.618, "BC Min Fib")
bcMax = input.float(0.786, "BC Max Fib")
cdMin = input.float(1.272, "CD Min Extension")
cdMax = input.float(1.618, "CD Max Extension")
htfTF = input.timeframe("240", "Higher Timeframe (S/R)")
srLookback = input.int(200, "HTF S/R Lookback")
srTolerance = input.float(0.002, "S/R Zone Tolerance (0.2%)")
showSR = input.bool(true, "Show HTF S/R Zones")
showTargets = input.bool(true, "Show Targets")
//━━━━━━━━━━━━━━━━━━━━━
// HIGHER TF SUPPORT / RESISTANCE
//━━━━━━━━━━━━━━━━━━━━━
htfHigh = request.security(syminfo.tickerid, htfTF, ta.highest(high, srLookback))
htfLow = request.security(syminfo.tickerid, htfTF, ta.lowest(low, srLookback))
srHighZoneTop = htfHigh * (1 + srTolerance)
srHighZoneBottom = htfHigh * (1 - srTolerance)
srLowZoneTop = htfLow * (1 + srTolerance)
srLowZoneBottom = htfLow * (1 - srTolerance)
//━━━━━━━━━━━━━━━━━━━━━
// DRAW HTF ZONES
//━━━━━━━━━━━━━━━━━━━━━
if showSR
box.new(bar_index - 5, srHighZoneTop, bar_index + 5, srHighZoneBottom,
bgcolor=color.new(color.red, 85), border_color=color.red)
box.new(bar_index - 5, srLowZoneTop, bar_index + 5, srLowZoneBottom,
bgcolor=color.new(color.green, 85), border_color=color.green)
//━━━━━━━━━━━━━━━━━━━━━
// SWING DETECTION
//━━━━━━━━━━━━━━━━━━━━━
ph = ta.pivothigh(high, pivotLen, pivotLen)
pl = ta.pivotlow(low, pivotLen, pivotLen)
var float A = na
var float B = na
var float C = na
var float D = na
var int Ab = na
var int Bb = na
var int Cb = na
var int Db = na
if not na(pl)
A := B
Ab := Bb
B := C
Bb := Cb
C := low
Cb := bar_index
if not na(ph)
A := B
Ab := Bb
B := C
Bb := Cb
C := high
Cb := bar_index
//━━━━━━━━━━━━━━━━━━━━━
// ABCD LOGIC
//━━━━━━━━━━━━━━━━━━━━━
ab = math.abs(B - A)
bc = math.abs(C - B)
bcFib = bc / ab
validBC = bcFib >= bcMin and bcFib <= bcMax
bull = C > B
cdMinPrice = bull ? C - bc * cdMin : C + bc * cdMin
cdMaxPrice = bull ? C - bc * cdMax : C + bc * cdMax
inDzone = low <= cdMaxPrice and high >= cdMinPrice
//━━━━━━━━━━━━━━━━━━━━━
// MTF STRUCTURE FILTER
//━━━━━━━━━━━━━━━━━━━━━
nearResistance = close <= srHighZoneTop and close >= srHighZoneBottom
nearSupport = close <= srLowZoneTop and close >= srLowZoneBottom
structureOK =
(bull and nearSupport) or
(not bull and nearResistance)
//━━━━━━━━━━━━━━━━━━━━━
// FINAL D CONFIRMATION
//━━━━━━━━━━━━━━━━━━━━━
if validBC and inDzone and structureOK
D := close
Db := bar_index
//━━━━━━━━━━━━━━━━━━━━━
// TARGETS
//━━━━━━━━━━━━━━━━━━━━━
tp1 = bull ? D + math.abs(D - C) * 0.382 : D - math.abs(D - C) * 0.382
tp2 = bull ? D + math.abs(D - C) * 0.618 : D - math.abs(D - C) * 0.618
//━━━━━━━━━━━━━━━━━━━━━
// DRAW PATTERN
//━━━━━━━━━━━━━━━━━━━━━
if not na(D)
line.new(Ab, A, Bb, B, width=2, color=color.blue)
line.new(Bb, B, Cb, C, width=2, color=color.orange)
line.new(Cb, C, Db, D, width=2, color=color.green)
label.new(Db, D, "D (HTF CONFIRMED)", style=label.style_label_down, color=color.yellow)
if showTargets
line.new(Db, tp1, Db + 12, tp1, color=color.green)
line.new(Db, tp2, Db + 12, tp2, color=color.teal)
alertcondition(validBC and inDzone and structureOK,
"ABCD v7 Confirmed",
"ABCD Pattern confirmed at Higher-Timeframe Support/Resistance — wait for price action.")
ABCD Strategy (v7 Ready)//@version=6
indicator("ABCD Strategy v7 – MTF S/R Filter", overlay=true, max_lines_count=300, max_labels_count=300)
//━━━━━━━━━━━━━━━━━━━━━
// INPUTS
//━━━━━━━━━━━━━━━━━━━━━
pivotLen = input.int(5, "Swing Strength", minval=2)
bcMin = input.float(0.618, "BC Min Fib")
bcMax = input.float(0.786, "BC Max Fib")
cdMin = input.float(1.272, "CD Min Extension")
cdMax = input.float(1.618, "CD Max Extension")
htfTF = input.timeframe("240", "Higher Timeframe (S/R)")
srLookback = input.int(200, "HTF S/R Lookback")
srTolerance = input.float(0.002, "S/R Zone Tolerance (0.2%)")
showSR = input.bool(true, "Show HTF S/R Zones")
showTargets = input.bool(true, "Show Targets")
//━━━━━━━━━━━━━━━━━━━━━
// HIGHER TF SUPPORT / RESISTANCE
//━━━━━━━━━━━━━━━━━━━━━
htfHigh = request.security(syminfo.tickerid, htfTF, ta.highest(high, srLookback))
htfLow = request.security(syminfo.tickerid, htfTF, ta.lowest(low, srLookback))
srHighZoneTop = htfHigh * (1 + srTolerance)
srHighZoneBottom = htfHigh * (1 - srTolerance)
srLowZoneTop = htfLow * (1 + srTolerance)
srLowZoneBottom = htfLow * (1 - srTolerance)
//━━━━━━━━━━━━━━━━━━━━━
// DRAW HTF ZONES
//━━━━━━━━━━━━━━━━━━━━━
if showSR
box.new(bar_index - 5, srHighZoneTop, bar_index + 5, srHighZoneBottom,
bgcolor=color.new(color.red, 85), border_color=color.red)
box.new(bar_index - 5, srLowZoneTop, bar_index + 5, srLowZoneBottom,
bgcolor=color.new(color.green, 85), border_color=color.green)
//━━━━━━━━━━━━━━━━━━━━━
// SWING DETECTION
//━━━━━━━━━━━━━━━━━━━━━
ph = ta.pivothigh(high, pivotLen, pivotLen)
pl = ta.pivotlow(low, pivotLen, pivotLen)
var float A = na
var float B = na
var float C = na
var float D = na
var int Ab = na
var int Bb = na
var int Cb = na
var int Db = na
if not na(pl)
A := B
Ab := Bb
B := C
Bb := Cb
C := low
Cb := bar_index
if not na(ph)
A := B
Ab := Bb
B := C
Bb := Cb
C := high
Cb := bar_index
//━━━━━━━━━━━━━━━━━━━━━
// ABCD LOGIC
//━━━━━━━━━━━━━━━━━━━━━
ab = math.abs(B - A)
bc = math.abs(C - B)
bcFib = bc / ab
validBC = bcFib >= bcMin and bcFib <= bcMax
bull = C > B
cdMinPrice = bull ? C - bc * cdMin : C + bc * cdMin
cdMaxPrice = bull ? C - bc * cdMax : C + bc * cdMax
inDzone = low <= cdMaxPrice and high >= cdMinPrice
//━━━━━━━━━━━━━━━━━━━━━
// MTF STRUCTURE FILTER
//━━━━━━━━━━━━━━━━━━━━━
nearResistance = close <= srHighZoneTop and close >= srHighZoneBottom
nearSupport = close <= srLowZoneTop and close >= srLowZoneBottom
structureOK =
(bull and nearSupport) or
(not bull and nearResistance)
//━━━━━━━━━━━━━━━━━━━━━
// FINAL D CONFIRMATION
//━━━━━━━━━━━━━━━━━━━━━
if validBC and inDzone and structureOK
D := close
Db := bar_index
//━━━━━━━━━━━━━━━━━━━━━
// TARGETS
//━━━━━━━━━━━━━━━━━━━━━
tp1 = bull ? D + math.abs(D - C) * 0.382 : D - math.abs(D - C) * 0.382
tp2 = bull ? D + math.abs(D - C) * 0.618 : D - math.abs(D - C) * 0.618
//━━━━━━━━━━━━━━━━━━━━━
// DRAW PATTERN
//━━━━━━━━━━━━━━━━━━━━━
if not na(D)
line.new(Ab, A, Bb, B, width=2, color=color.blue)
line.new(Bb, B, Cb, C, width=2, color=color.orange)
line.new(Cb, C, Db, D, width=2, color=color.green)
label.new(Db, D, "D (HTF CONFIRMED)", style=label.style_label_down, color=color.yellow)
if showTargets
line.new(Db, tp1, Db + 12, tp1, color=color.green)
line.new(Db, tp2, Db + 12, tp2, color=color.teal)
alertcondition(validBC and inDzone and structureOK,
"ABCD v7 Confirmed",
"ABCD Pattern confirmed at Higher-Timeframe Support/Resistance — wait for price action.")
Malaysian SnR StoryLinesA Malaysian SnR StoryLines is an HTF-based (Higher Timeframe) level-drawing indicator that automatically identifies and displays key levels derived from market structure:
🔹 Support
🔹 Resistance
🔹 OCL
As well as their state transitions:
🔹 RBS
🔹 SBR
🔹 QM+ (bullish)
🔹 QM- (bearish)
The goal of this indicator is to visually track the life cycle of levels:
➡️ created → broken → role reversal → invalidated
This helps speed up structure reading and level-based decision-making.
🧩 How does it work?
✅ Levels are always generated from the candle structure of the selected HTF timeframe (e.g., D, W).
✅ When a new HTF candle begins, the indicator creates levels based on patterns found in the closed HTF candles .
Levels are drawn horizontally on the chart, and the labels are aligned to the end of each line (transparent background, shifted).
⚠️ Known limitation:
🔹 If you select a chart timeframe that is too low compared to the HTF, some levels may disappear due to Pine Script/TradingwingView drawing limits.
Feedback and feature ideas are welcome. If you spot an issue, please include the symbol and the timeframes used (chart TF + HTF) so it’s easier to reproduce.
