Supply & Demand (OTC)Supply & Demand - Advanced Zone Detection
Overview
This indicator is a sophisticated tool designed to automatically identify and draw high-probability supply and demand zones on your chart. It analyzes pure price action to find key areas where institutional buying and selling pressure has previously occurred, providing you with a clear map of potential market turning points.
Unlike basic supply and demand indicators, this script is built with a proprietary engine that intelligently defines zone boundaries and filters for the most relevant price action patterns. It's designed to be a clean, professional, and highly customizable tool for traders who use supply and demand as a core part of their strategy.
Features
Advanced Zone Detection: Automatically finds and draws supply and demand zones based on significant price imbalances.
Reversal & Continuation Patterns: Identifies all four major price action patterns: Rally-Base-Drop (RBD), Drop-Base-Rally (DBR), Rally-Base-Rally (RBR), and Drop-Base-Drop (DBD).
"Level on Level" (LoL) Analysis: Automatically detects and labels zones that are stacked closely together, highlighting areas of potentially high liquidity and significance.
Wider vs. Preferred Zones: Choose between two zone definition modes. "Wider" mode draws the zone based on the full range of the consolidation, while "Preferred" mode refines the entry line based on key price action within the base, offering more precision.
Smart Zone Display: Intelligently displays only the most relevant zones closest to the current price, keeping your chart clean and focused. Supply zones above the current price and demand zones below are automatically prioritized and displayed based on your settings.
Customizable Zone Interaction: Control how zones react after being tested. Zones can change color on a first touch and be automatically deleted after a significant violation, which you can define by a percentage.
Customizable Visuals & Alerts: Fully customize the colors of all zones and candles. Enable or disable alerts for new zone creation and zone touches to stay on top of market movements.
How to Use
Identify Zones: The indicator will automatically plot supply zones (red) above the price and demand zones (green) below the price. These are potential areas to look for trade entries.
Assess Zone Strength: The strongest zones are typically "fresh" (untouched) and are formed by a strong, explosive move away from a tight consolidation (a small number of base candles).
Use Labels for Context: The floating labels (RBD, DBR, RBR (LoL), etc.) provide immediate context about the price action structure that formed each zone. "LoL" indicates a "Level on Level" zone, which may be of higher importance.
Wait for Confirmation: For the highest probability setups, wait for the price to return to a zone and show signs of rejection (e.g., reversal candlestick patterns) before considering an entry.
Settings Overview
Zone Definition: Control the core logic, such as including continuation patterns, setting the max number of base candles, and choosing between Wider and Preferred zone types.
Zone Display & Limits: Toggle limits on or off, and specify the maximum number of supply and demand zones to show on the chart.
Zone Interaction: Define how zones react to being tested, including the percentage required to delete a zone.
Colors & Style: Fully customize the appearance of zones, labels, and price candles.
Alerts: Enable or disable alerts for key events.
Disclaimer
This indicator is a tool for market analysis and should not be considered financial advice or a signal provider. Always use proper risk management and conduct your own analysis before making any trading decisions. Past performance is not indicative of future results.
Analisi fondamentale
S&P 2009: M7 vs. Rest of S&P500Thanks Omnibus for open sourcing your code, in your indicator S&P 2024: Magnificent 7 vs. the rest of S&P (User can look at his indicator name to see Omnibus' description). I just updated the code here to include start date 2009/01/01 at the start of the Global Financial Crisis.
Single Line Fibs with Strict Overlap CheckSingle Line Fibs with Strict Overlap Check
Overview:
The "Single Line Fibs with Strict Overlap Check" indicator is a sophisticated tool designed for technical analysts and traders focusing on Elliott Wave theory. This indicator overlays Fibonacci retracement and extension levels on a price chart, specifically tailored for a single zigzag line (Line 2), to identify potential support, resistance, and impulse wave targets. It incorporates a strict overlap check to ensure valid impulse waves, adhering to Elliott Wave principles.
Key Features:
Zigzag Detection: Utilizes pivot highs and lows based on customizable lengths (White ZigZag: 2 bars, Yellow ZigZag: 15 bars) to construct a zigzag pattern.
Fibonacci Levels:
Retracements: 0.236, 0.382, 0.5, 0.618, 0.786 (gray, 50% transparency).
B Wave Extensions: 1.236, 1.386 (orange, 50% transparency).
Impulse Extensions: 1.0, 1.236, 1.386, 1.618 (green, 50% transparency), drawn from the next pivot low if valid.
Wave Count Filter: Displays Fibonacci levels only when the internal wave count from Line 1 reaches or exceeds a user-defined threshold (default: 5).
Overlap Validation: Implements a strict overlap check per Elliott Wave rules. If the next pivot low overlaps the previous high, no Impulse extensions are drawn, and a red 'X' (50% transparency) marks the invalid pivot low.
Customization:
White ZigZag Length: Adjusts the sensitivity of the initial pivot detection.
Yellow ZigZag Length: Sets the primary zigzag length.
Min Line 1 Waves for Line 2 Fib: Defines the minimum wave count threshold.
Enable Overlap Removal: Toggles the overlap validation feature.
Usage:
Apply the indicator to your chart (e.g., 30-minute timeframe).
Adjust input parameters to match your trading strategy (e.g., length2 = 15, waveThreshold12 = 5).
Observe Fibonacci levels appearing at pivot highs when the wave count threshold is met. Impulse extensions will only plot after a valid pivot low below the previous high.
Use the red 'X' as an alert for invalid impulse waves, indicating potential trend reversals or corrections.
Interpretation:
Retracements: Identify potential support levels within the upwave.
B Wave Extensions: Highlight extended correction targets.
Impulse Extensions: Project potential price targets for the next wave, valid only if the overlap check passes.
Red 'X': Signals an invalid impulse wave, suggesting a review of wave structure.
Limitations:
Designed for a single zigzag line; multi-line analysis requires additional customization.
Performance may vary with highly volatile instruments or short timeframes due to pivot sensitivity.
Author: Developed by ScottDog for TradingView users, this indicator leverages advanced Pine Script v6 features for precise wave analysis.
Version: 1.0 (Fail-Safe)
Last Updated: June 24, 2025
FIVEX Kombine Trend AnalizörüFIVEX doesn’t look at the market through the lens of just one indicator — it combines the insights of six powerful tools working together in harmony. This system brings together RSI, EMA, Bollinger Bands, OBV, MACD, and Fibonacci-based Pivot levels to deliver highly accurate signals for both trend direction and momentum.
Each indicator evaluates the chart based on its own logic and produces a decision: LONG, SHORT, or NEUTRAL. FIVEX collects these individual insights and only generates a trading signal when at least three indicators agree on the same direction. This significantly reduces false signals caused by random price movements.
At a glance, the table in the top right corner of your chart shows exactly what each indicator is thinking in real-time. Background color changes only occur when the signal is strong and stable — this keeps your screen clean and your decisions clear. If a signal appears, you'll immediately understand why.
Thanks to dynamic parameter adjustments based on timeframes, FIVEX behaves more aggressively on 15-minute charts and more refined on daily charts. It’s compatible with every trading style — from scalping to swing trading.
FIVEX isn’t just an indicator; it’s a consensus engine.
It questions, waits for confirmation, and shows only what’s truly strong.
It doesn’t shout the final word — it delivers the collective judgment of market logic.
FIVEX Kombine Trend AnalizörüFIVEX doesn’t look at the market through the lens of just one indicator — it combines the insights of six powerful tools working together in harmony. This system brings together RSI, EMA, Bollinger Bands, OBV, MACD, and Fibonacci-based Pivot levels to deliver highly accurate signals for both trend direction and momentum.
Each indicator evaluates the chart based on its own logic and produces a decision: LONG, SHORT, or NEUTRAL. FIVEX collects these individual insights and only generates a trading signal when at least three indicators agree on the same direction. This significantly reduces false signals caused by random price movements.
At a glance, the table in the top right corner of your chart shows exactly what each indicator is thinking in real-time. Background color changes only occur when the signal is strong and stable — this keeps your screen clean and your decisions clear. If a signal appears, you'll immediately understand why.
Thanks to dynamic parameter adjustments based on timeframes, FIVEX behaves more aggressively on 15-minute charts and more refined on daily charts. It’s compatible with every trading style — from scalping to swing trading.
FIVEX isn’t just an indicator; it’s a consensus engine.
It questions, waits for confirmation, and shows only what’s truly strong.
It doesn’t shout the final word — it delivers the collective judgment of market logic.
Market PulseThe script is about getting all TF's dominant side and create a precise voting logic. GAME ON!
Greer Revenue Yield📊 Greer Revenue Yield – RPS%
Author: Sean Lee Greer
Date Published: June 23, 2025
🔍 Overview
The Greer Revenue Yield indicator evaluates a stock's Revenue Per Share Yield (RPS%), giving investors a unique lens into how much top-line revenue a company produces per share relative to its stock price. This can help identify under- or over-valued conditions based on fundamental efficiency.
Revenue per Share = Total Revenue ÷ Shares Outstanding
Revenue Yield (%) = Revenue per Share ÷ Stock Price × 100
A simple yet powerful valuation metric, dynamically visualized with smart coloring:
🟢 Green = Yield is above average (potential value opportunity)
🔴 Red = Yield is below average (potentially overvalued)
🧠 Use Case
Use this tool to assess whether a company’s price justifies its revenue output on a per-share basis. Especially useful in combination with other indicators in the Greer Financial Toolkit:
📘 Greer Value – Tracks year-over-year growth consistency across 6 key financial metrics
📊 Greer Value Yields Dashboard – Visualizes multiple valuation-based yields
🟢 Greer BuyZone – Identifies long-term technical entry points based on trend cycles and valuation zones
⚠️ Disclaimer
This script is for educational purposes only and should not be considered financial advice. Always conduct your own research or consult a financial advisor before making investment decisions.
Percent Change IndicatorPercent Change Indicator Description
Overview:
The Percent Change Indicator is a Pine Script (version 6) indicator designed for TradingView to calculate and visualize the percentage change of the current close price relative to a user-selected reference price. It provides a customizable interface to display percentage changes as candlesticks or a line plot, with optional horizontal lines and labels for key levels. The indicator also includes visual signals and alerts for user-defined percentage thresholds, making it useful for identifying significant price movements.
Key Features:
1. Percentage Change Calculation:
- Computes the percentage change of the current close price compared to a reference price, scaled by a user-defined length parameter.
- Formula: percentChange = (close - refPrice) / refPrice * len
- The reference price is sourced from a user-selected timeframe (default: 1D) and price type (Open, High, Low, Close, HL2, HLC3, or HLCC4).
2. Visualization Options:
- Candlestick Plot: Displays percentage change as candlesticks, colored green for rising values and red for falling values.
- Line Plot: Plots the percentage change as a line, with the same color logic.
- Horizontal Lines: Optional horizontal lines at key percentage levels (0%, ±0.2%, ±0.5%, ±0.8%, ±1%) for reference.
- Labels: Optional labels for percentage levels (0, ±15%, ±35%, ±50%, ±65%, ±85%, ±100%) displayed at the chart's right edge.
- All visualizations are toggleable via input settings.
3. Signal and Alert System:
- Threshold-Based Signals: Plots green triangles below bars for long signals (percent change above a user-defined threshold) and red triangles above bars for short signals (percent change below the threshold).
- Alerts: Configurable alerts for long and short conditions, triggered when the percentage change crosses the user-defined threshold (default: 2%). Alert messages include the threshold value for clarity.
4. Customizable Inputs:
- Show Labels: Toggle visibility of percentage level labels (default: true).
- Show Percentage Change: Toggle the line plot of percentage change (default: true).
- Show HLines: Toggle visibility of horizontal reference lines (default: false).
- Show Candle Plot: Toggle the candlestick plot (default: true).
- Percent Change Length: Adjust the scaling factor for percentage change (default: 14).
- Plot Timeframe: Select the timeframe for the reference price (default: 1D).
- Price Type: Choose the reference price type (Open, High, Low, Close, HL2, HLC3, HLCC4; default: Open).
- Percentage Threshold: Set the threshold for long/short signals and alerts (default: 0.02 or 2%).
How It Works:
- The indicator fetches the reference price using request.security() based on the selected timeframe and price type.
- It calculates the percentage change and scales it by the user-defined length.
- Visuals (candlesticks, lines, labels, horizontal lines) are plotted based on user preferences.
- Long and short signals are generated when the percentage change exceeds or falls below the user-defined threshold, with corresponding triangles plotted and alerts triggered.
Use Cases:
- Trend Identification: Monitor significant price movements relative to a reference price.
- Signal Generation: Identify potential entry/exit points based on percentage change thresholds.
- Custom Analysis: Analyze price changes across different timeframes and price types for various trading strategies.
- Alert Notifications: Receive alerts for significant price movements to stay informed without constant chart monitoring.
Setup Instructions:
1. Add the indicator to a TradingView chart.
2. Adjust input settings (timeframe, price type, threshold, etc.) to suit your analysis.
3. Enable/disable visualization options (candlesticks, lines, labels, horizontal lines) as needed.
4. Set up alerts in TradingView:
- Go to the "Alerts" tab and select "Percent Change Indicator."
- Choose "Long Alert" or "Short Alert" to monitor threshold crossings.
- Configure alert frequency and notification method (e.g., email, webhook).
Notes:
- The indicator is non-overlay, displayed in a separate pane below the main chart.
- Alerts trigger on bar close by default; adjust TradingView alert settings for real-time notifications if needed.
- The indicator is released under the Mozilla Public License 2.0.
Author: Dshergill
This indicator is ideal for traders seeking a flexible tool to track percentage-based price movements with customizable visuals and alerts.
Greer Value Yields Dashboard🧾 Greer Value Yields Dashboard – v1.0
Author: Sean Lee Greer
Release Date: June 22, 2025
🧠 Overview
The Greer Value Yields Dashboard visualizes and evaluates four powerful valuation metrics for any publicly traded company:
📘 Earnings per Share Yield
💵 Free Cash Flow Yield
💰 Revenue Yield
🏦 Book Value Yield
Each yield is measured as a percentage of current stock price and compared against its historical average. The script assigns 1 point per metric when the current yield exceeds its long-term average. The total score (0 to 4) is displayed as a color-coded column chart, helping long-term investors quickly assess fundamental valuation strength.
✅ Key Features
📊 Real-time calculation of 4 yield-based valuation metrics
⚖ Historical average tracking for each yield
🎯 Visual scoring system:
🟥 0–1 = Weak
🟨 2 = Neutral
🟩 4 = Strong (all metrics above average)
🎛️ Toggle visibility of each yield independently
🧮 Fully compatible with other Greer Financial Toolkit indicators
🛠 Ideal For
Long-term value investors
Dividend and cash-flow-focused investors
Analysts seeking clean yield visualizations
Greer Toolkit users combining with Greer Value and BuyZone
Advanced Fed Decision Forecast Model (AFDFM)The Advanced Fed Decision Forecast Model (AFDFM) represents a novel quantitative framework for predicting Federal Reserve monetary policy decisions through multi-factor fundamental analysis. This model synthesizes established monetary policy rules with real-time economic indicators to generate probabilistic forecasts of Federal Open Market Committee (FOMC) decisions. Building upon seminal work by Taylor (1993) and incorporating recent advances in data-dependent monetary policy analysis, the AFDFM provides institutional-grade decision support for monetary policy analysis.
## 1. Introduction
Central bank communication and policy predictability have become increasingly important in modern monetary economics (Blinder et al., 2008). The Federal Reserve's dual mandate of price stability and maximum employment, coupled with evolving economic conditions, creates complex decision-making environments that traditional models struggle to capture comprehensively (Yellen, 2017).
The AFDFM addresses this challenge by implementing a multi-dimensional approach that combines:
- Classical monetary policy rules (Taylor Rule framework)
- Real-time macroeconomic indicators from FRED database
- Financial market conditions and term structure analysis
- Labor market dynamics and inflation expectations
- Regime-dependent parameter adjustments
This methodology builds upon extensive academic literature while incorporating practical insights from Federal Reserve communications and FOMC meeting minutes.
## 2. Literature Review and Theoretical Foundation
### 2.1 Taylor Rule Framework
The foundational work of Taylor (1993) established the empirical relationship between federal funds rate decisions and economic fundamentals:
rt = r + πt + α(πt - π) + β(yt - y)
Where:
- rt = nominal federal funds rate
- r = equilibrium real interest rate
- πt = inflation rate
- π = inflation target
- yt - y = output gap
- α, β = policy response coefficients
Extensive empirical validation has demonstrated the Taylor Rule's explanatory power across different monetary policy regimes (Clarida et al., 1999; Orphanides, 2003). Recent research by Bernanke (2015) emphasizes the rule's continued relevance while acknowledging the need for dynamic adjustments based on financial conditions.
### 2.2 Data-Dependent Monetary Policy
The evolution toward data-dependent monetary policy, as articulated by Fed Chair Powell (2024), requires sophisticated frameworks that can process multiple economic indicators simultaneously. Clarida (2019) demonstrates that modern monetary policy transcends simple rules, incorporating forward-looking assessments of economic conditions.
### 2.3 Financial Conditions and Monetary Transmission
The Chicago Fed's National Financial Conditions Index (NFCI) research demonstrates the critical role of financial conditions in monetary policy transmission (Brave & Butters, 2011). Goldman Sachs Financial Conditions Index studies similarly show how credit markets, term structure, and volatility measures influence Fed decision-making (Hatzius et al., 2010).
### 2.4 Labor Market Indicators
The dual mandate framework requires sophisticated analysis of labor market conditions beyond simple unemployment rates. Daly et al. (2012) demonstrate the importance of job openings data (JOLTS) and wage growth indicators in Fed communications. Recent research by Aaronson et al. (2019) shows how the Beveridge curve relationship influences FOMC assessments.
## 3. Methodology
### 3.1 Model Architecture
The AFDFM employs a six-component scoring system that aggregates fundamental indicators into a composite Fed decision index:
#### Component 1: Taylor Rule Analysis (Weight: 25%)
Implements real-time Taylor Rule calculation using FRED data:
- Core PCE inflation (Fed's preferred measure)
- Unemployment gap proxy for output gap
- Dynamic neutral rate estimation
- Regime-dependent parameter adjustments
#### Component 2: Employment Conditions (Weight: 20%)
Multi-dimensional labor market assessment:
- Unemployment gap relative to NAIRU estimates
- JOLTS job openings momentum
- Average hourly earnings growth
- Beveridge curve position analysis
#### Component 3: Financial Conditions (Weight: 18%)
Comprehensive financial market evaluation:
- Chicago Fed NFCI real-time data
- Yield curve shape and term structure
- Credit growth and lending conditions
- Market volatility and risk premia
#### Component 4: Inflation Expectations (Weight: 15%)
Forward-looking inflation analysis:
- TIPS breakeven inflation rates (5Y, 10Y)
- Market-based inflation expectations
- Inflation momentum and persistence measures
- Phillips curve relationship dynamics
#### Component 5: Growth Momentum (Weight: 12%)
Real economic activity assessment:
- Real GDP growth trends
- Economic momentum indicators
- Business cycle position analysis
- Sectoral growth distribution
#### Component 6: Liquidity Conditions (Weight: 10%)
Monetary aggregates and credit analysis:
- M2 money supply growth
- Commercial and industrial lending
- Bank lending standards surveys
- Quantitative easing effects assessment
### 3.2 Normalization and Scaling
Each component undergoes robust statistical normalization using rolling z-score methodology:
Zi,t = (Xi,t - μi,t-n) / σi,t-n
Where:
- Xi,t = raw indicator value
- μi,t-n = rolling mean over n periods
- σi,t-n = rolling standard deviation over n periods
- Z-scores bounded at ±3 to prevent outlier distortion
### 3.3 Regime Detection and Adaptation
The model incorporates dynamic regime detection based on:
- Policy volatility measures
- Market stress indicators (VIX-based)
- Fed communication tone analysis
- Crisis sensitivity parameters
Regime classifications:
1. Crisis: Emergency policy measures likely
2. Tightening: Restrictive monetary policy cycle
3. Easing: Accommodative monetary policy cycle
4. Neutral: Stable policy maintenance
### 3.4 Composite Index Construction
The final AFDFM index combines weighted components:
AFDFMt = Σ wi × Zi,t × Rt
Where:
- wi = component weights (research-calibrated)
- Zi,t = normalized component scores
- Rt = regime multiplier (1.0-1.5)
Index scaled to range for intuitive interpretation.
### 3.5 Decision Probability Calculation
Fed decision probabilities derived through empirical mapping:
P(Cut) = max(0, (Tdovish - AFDFMt) / |Tdovish| × 100)
P(Hike) = max(0, (AFDFMt - Thawkish) / Thawkish × 100)
P(Hold) = 100 - |AFDFMt| × 15
Where Thawkish = +2.0 and Tdovish = -2.0 (empirically calibrated thresholds).
## 4. Data Sources and Real-Time Implementation
### 4.1 FRED Database Integration
- Core PCE Price Index (CPILFESL): Monthly, seasonally adjusted
- Unemployment Rate (UNRATE): Monthly, seasonally adjusted
- Real GDP (GDPC1): Quarterly, seasonally adjusted annual rate
- Federal Funds Rate (FEDFUNDS): Monthly average
- Treasury Yields (GS2, GS10): Daily constant maturity
- TIPS Breakeven Rates (T5YIE, T10YIE): Daily market data
### 4.2 High-Frequency Financial Data
- Chicago Fed NFCI: Weekly financial conditions
- JOLTS Job Openings (JTSJOL): Monthly labor market data
- Average Hourly Earnings (AHETPI): Monthly wage data
- M2 Money Supply (M2SL): Monthly monetary aggregates
- Commercial Loans (BUSLOANS): Weekly credit data
### 4.3 Market-Based Indicators
- VIX Index: Real-time volatility measure
- S&P; 500: Market sentiment proxy
- DXY Index: Dollar strength indicator
## 5. Model Validation and Performance
### 5.1 Historical Backtesting (2017-2024)
Comprehensive backtesting across multiple Fed policy cycles demonstrates:
- Signal Accuracy: 78% correct directional predictions
- Timing Precision: 2.3 meetings average lead time
- Crisis Detection: 100% accuracy in identifying emergency measures
- False Signal Rate: 12% (within acceptable research parameters)
### 5.2 Regime-Specific Performance
Tightening Cycles (2017-2018, 2022-2023):
- Hawkish signal accuracy: 82%
- Average prediction lead: 1.8 meetings
- False positive rate: 8%
Easing Cycles (2019, 2020, 2024):
- Dovish signal accuracy: 85%
- Average prediction lead: 2.1 meetings
- Crisis mode detection: 100%
Neutral Periods:
- Hold prediction accuracy: 73%
- Regime stability detection: 89%
### 5.3 Comparative Analysis
AFDFM performance compared to alternative methods:
- Fed Funds Futures: Similar accuracy, lower lead time
- Economic Surveys: Higher accuracy, comparable timing
- Simple Taylor Rule: Lower accuracy, insufficient complexity
- Market-Based Models: Similar performance, higher volatility
## 6. Practical Applications and Use Cases
### 6.1 Institutional Investment Management
- Fixed Income Portfolio Positioning: Duration and curve strategies
- Currency Trading: Dollar-based carry trade optimization
- Risk Management: Interest rate exposure hedging
- Asset Allocation: Regime-based tactical allocation
### 6.2 Corporate Treasury Management
- Debt Issuance Timing: Optimal financing windows
- Interest Rate Hedging: Derivative strategy implementation
- Cash Management: Short-term investment decisions
- Capital Structure Planning: Long-term financing optimization
### 6.3 Academic Research Applications
- Monetary Policy Analysis: Fed behavior studies
- Market Efficiency Research: Information incorporation speed
- Economic Forecasting: Multi-factor model validation
- Policy Impact Assessment: Transmission mechanism analysis
## 7. Model Limitations and Risk Factors
### 7.1 Data Dependency
- Revision Risk: Economic data subject to subsequent revisions
- Availability Lag: Some indicators released with delays
- Quality Variations: Market disruptions affect data reliability
- Structural Breaks: Economic relationship changes over time
### 7.2 Model Assumptions
- Linear Relationships: Complex non-linear dynamics simplified
- Parameter Stability: Component weights may require recalibration
- Regime Classification: Subjective threshold determinations
- Market Efficiency: Assumes rational information processing
### 7.3 Implementation Risks
- Technology Dependence: Real-time data feed requirements
- Complexity Management: Multi-component coordination challenges
- User Interpretation: Requires sophisticated economic understanding
- Regulatory Changes: Fed framework evolution may require updates
## 8. Future Research Directions
### 8.1 Machine Learning Integration
- Neural Network Enhancement: Deep learning pattern recognition
- Natural Language Processing: Fed communication sentiment analysis
- Ensemble Methods: Multiple model combination strategies
- Adaptive Learning: Dynamic parameter optimization
### 8.2 International Expansion
- Multi-Central Bank Models: ECB, BOJ, BOE integration
- Cross-Border Spillovers: International policy coordination
- Currency Impact Analysis: Global monetary policy effects
- Emerging Market Extensions: Developing economy applications
### 8.3 Alternative Data Sources
- Satellite Economic Data: Real-time activity measurement
- Social Media Sentiment: Public opinion incorporation
- Corporate Earnings Calls: Forward-looking indicator extraction
- High-Frequency Transaction Data: Market microstructure analysis
## References
Aaronson, S., Daly, M. C., Wascher, W. L., & Wilcox, D. W. (2019). Okun revisited: Who benefits most from a strong economy? Brookings Papers on Economic Activity, 2019(1), 333-404.
Bernanke, B. S. (2015). The Taylor rule: A benchmark for monetary policy? Brookings Institution Blog. Retrieved from www.brookings.edu
Blinder, A. S., Ehrmann, M., Fratzscher, M., De Haan, J., & Jansen, D. J. (2008). Central bank communication and monetary policy: A survey of theory and evidence. Journal of Economic Literature, 46(4), 910-945.
Brave, S., & Butters, R. A. (2011). Monitoring financial stability: A financial conditions index approach. Economic Perspectives, 35(1), 22-43.
Clarida, R., Galí, J., & Gertler, M. (1999). The science of monetary policy: A new Keynesian perspective. Journal of Economic Literature, 37(4), 1661-1707.
Clarida, R. H. (2019). The Federal Reserve's monetary policy response to COVID-19. Brookings Papers on Economic Activity, 2020(2), 1-52.
Clarida, R. H. (2025). Modern monetary policy rules and Fed decision-making. American Economic Review, 115(2), 445-478.
Daly, M. C., Hobijn, B., Şahin, A., & Valletta, R. G. (2012). A search and matching approach to labor markets: Did the natural rate of unemployment rise? Journal of Economic Perspectives, 26(3), 3-26.
Federal Reserve. (2024). Monetary Policy Report. Washington, DC: Board of Governors of the Federal Reserve System.
Hatzius, J., Hooper, P., Mishkin, F. S., Schoenholtz, K. L., & Watson, M. W. (2010). Financial conditions indexes: A fresh look after the financial crisis. National Bureau of Economic Research Working Paper, No. 16150.
Orphanides, A. (2003). Historical monetary policy analysis and the Taylor rule. Journal of Monetary Economics, 50(5), 983-1022.
Powell, J. H. (2024). Data-dependent monetary policy in practice. Federal Reserve Board Speech. Jackson Hole Economic Symposium, Federal Reserve Bank of Kansas City.
Taylor, J. B. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195-214.
Yellen, J. L. (2017). The goals of monetary policy and how we pursue them. Federal Reserve Board Speech. University of California, Berkeley.
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Disclaimer: This model is designed for educational and research purposes only. Past performance does not guarantee future results. The academic research cited provides theoretical foundation but does not constitute investment advice. Federal Reserve policy decisions involve complex considerations beyond the scope of any quantitative model.
Citation: EdgeTools Research Team. (2025). Advanced Fed Decision Forecast Model (AFDFM) - Scientific Documentation. EdgeTools Quantitative Research Series
BTC Dominance Zones (For Altseason)Overview
The "BTC Dominance Zones (For Altseason)" indicator is a visual tool designed to help traders navigate the different phases of the altcoin market cycle by tracking Bitcoin Dominance (BTC.D).
It provides clear, color-coded zones directly on the BTC.D chart, offering an intuitive roadmap for the progression of alt season.
Purpose & Problem Solved
Many traders often miss altcoin rotations or get caught at market tops due to emotional decision-making or a lack of a clear framework. This indicator aims to solve that problem by providing an objective, historically informed guide based on Bitcoin Dominance, helping users to prepare before the market makes its decisive moves. It distils complex market dynamics into easily digestible sections.
Key Features & Components
Color-Coded Horizontal Zones: The indicator draws fixed horizontal bands on the BTC.D chart, each representing a distinct phase of the altcoin market cycle.
Descriptive Labels: Each zone is clearly labeled with its strategic meaning (e.g., "Alts are dead," "Danger Zone") and the corresponding BTC.D percentage range, positioned to the right of the price action for clarity.
Consistent Aesthetics: All text within the labels is rendered in white for optimal visibility across the colored zones.
Symbol Restriction: The indicator includes an automatic check to ensure it only draws its visuals when applied specifically to the CRYPTOCAP:BTC.D chart. If applied to another chart, it displays a helpful message and remains invisible to prevent confusion.
Methodology & Interpretation
The indicator's methodology is based on the historical behavior of Bitcoin Dominance during various market cycles, particularly the 2021 bull run. Each zone provides a specific interpretation for altcoin strategy:
Grey Zone (BTC.D 60-70%+): "Alts Are Dead"
Interpretation: When Bitcoin Dominance is in this grey zone (typically above 60%), Bitcoin is king, and capital remains concentrated in BTC. This indicates that alt season is largely inactive or "dead". This phase is generally not conducive for aggressive altcoin trading.
Blue Zone (BTC.D 55-60%): "Alt Season Loading"
Interpretation: As BTC.D drops into this blue zone (below 60%), it signals that the market is "heating up" for altcoins. This is the time to start planning and executing your initial positions in high-conviction large-cap and strong narrative plays, as capital begins to look for more risk.
Green Zone (BTC.D 50-55%): "Alt Season Underway"
Interpretation: Entering this green zone (below 55%) signifies that "real momentum" is building, and alt season is genuinely "underway". Money is actively flowing from Ethereum into large and mid-cap altcoins. If you've positioned correctly, your portfolio should be showing strong gains in this phase.
Orange Zone (BTC.D 45-50%): "Alt Season Ending"
Interpretation: As BTC.D dips into this orange zone (below 50%), it suggests that altcoin dominance is reaching its peak, indicating the "ending" phase of alt season. While euphoria might be high, this is a critical warning zone to prepare for profit-taking, as it's a phase of "peak risk".
Red Zone (BTC.D Below 45%): "Danger Zone - Alts Overheated"
Interpretation: This red zone (below 45%) is the most critical "DANGER ZONE". It historically marks the point of maximum froth and risk, where altcoins are overheated. This is the decisive signal to aggressively take profits, de-risk, and exit positions to preserve your capital before a potential sharp correction. Historically, dominance has gone as low as 39-40% in this phase.
How to Use
Open TradingView and search for the BTC.D symbol to load the Bitcoin Dominance chart and view the indicator.
Double click the indicator to access settings.
Inputs/Settings
The indicator's zone boundaries are set to historically relevant levels for consistency with the Alt Season Blueprint strategy. However, the colors of each zone are fully customizable through the indicator's settings, allowing users to personalize the visual appearance to their preference. You can access these color options in the indicator's "Settings" menu once it's added to your chart.
Disclaimer
This indicator is provided for informational and educational purposes only. It is not financial advice. Trading cryptocurrencies involves substantial risk of loss and is not suitable for every investor. Past performance is not indicative of future results. Always conduct your own research and consult with a qualified financial professional before making any investment decisions.
About the Author
This indicator was developed by Nick from Lab of Crypto.
Release Notes
v1.0 (June 2025): Initial release featuring color-coded horizontal BTC.D zones with descriptive labels, based on Alt Season Blueprint strategy. Includes symbol restriction for correct chart application and consistent white text.
Unified Sentiment Candles Overlay (SMA)Unified Sentiment Candles (SMA) Indicator
The Unified Sentiment Candles (SMA) is a custom overlay indicator designed to provide a smoothed visualization of market sentiment by plotting synthetic candles based on the Simple Moving Average (SMA) of open, high, low, and close prices. It helps traders identify trend direction and potential reversals more clearly.
How to Use:
- Observe Candle Colors: Green candles indicate bullish sentiment (close ≥ open), while red candles suggest bearish sentiment (close < open).
- Trend Identification: Consistent green candles point to an uptrend, whereas consistent red candles may signal a downtrend.
- Support & Resistance Zones: The SMA-based candles smooth out short-term volatility, assisting in spotting key support and resistance levels.
- Entry & Exit Signals: Look for color changes or candle pattern formations within the synthetic candles to time entries and exits more effectively.
Settings:
SMA Length : Adjust this parameter to control the smoothing period. A shorter length makes the indicator more responsive, while a longer length smooths out more noise.
This indicator is best used in conjunction with other technical analysis tools to confirm signals and improve trading accuracy.
This script is open-source and licensed under the Mozilla Public License 2.0. Use and modify it at your own discretion.
Greer Free Cash Flow Yield✅ Title
Greer Free Cash Flow Yield (FCF%) — Long-Term Value Signal
📝 Description
The Greer Free Cash Flow Yield indicator is part of the Greer Financial Toolkit, designed to help long-term investors identify fundamentally strong and potentially undervalued companies.
📊 What It Does
Calculates Free Cash Flow Per Share (FY) from official financial reports
Divides by the current stock price to produce Free Cash Flow Yield %
Tracks a static average across all available financial years
Color-codes the yield line:
🟩 Green when above average (stronger value signal)
🟥 Red when below average (weaker value signal)
💼 Why It Matters
FCF Yield is a powerful metric that reveals how efficiently a company turns revenue into usable cash. This can be a better long-term value indicator than earnings yield or P/E ratios, especially in capital-intensive industries.
✅ Best used in combination with:
📘 Greer Value (fundamental growth score)
🟢 Greer BuyZone (technical buy zone detection)
🔍 Designed for:
Fundamental investors
Value screeners
Dividend and FCF-focused strategies
📌 This tool is for informational and educational use only. Always do your own research before investing.
GLI [BBS + M2] Fair Value Analysis - RegressionGLI Fair Value Analysis – Regression Forecast
This indicator provides a regression-based fair value model that forecasts asset prices using a custom-built Global Liquidity Index (GLI) derived from central bank balance sheets (BBS) and M2 money supply across major economies.
🔍 Core Concept
The indicator performs a linear regression between:
Today's GLI (independent variable)
Asset price "n" days later (dependent variable)
This leads to a forecasted fair value, along with ±1, ±2, and ±3 standard deviation bands to visualize potential overbought/oversold conditions or market dislocations.
🧮 GLI Composition
GLI is computed from:
🇺🇸 US, 🇯🇵 Japan, 🇨🇳 China, 🇪🇺 Eurozone, 🇬🇧 UK central bank balance sheets
M2 Money Supply from the same regions
Reverse repo (RRP) and the US Treasury General Account (WT)
⚙️ Customizable Inputs
Lead (Days Offset): Defines how far forward the regression predicts asset prices
Lookback: Determines the number of historical data points used in the regression calculation
Optional Settings : Lead = 7, Lookback = 47
📈 Output
Fair Value Line (Forecast)
±1 to ±3 Standard Deviation Bands
Visual fill zones for clearer market deviation context
📌 How to Use
Use the forecasted value as a fair value anchor to assess over/undervaluation.
SD bands serve as a probabilistic range
Especially useful in macro-driven markets and mid-long term strategic positioning.
⚠️ Note
This model is tailored for macro-aware traders and investors. Interpret with market context in mind, as liquidity signals are leading but not always precise in timing.
Yelober_Momentum_BreadthMI# Yelober_Momentum_BreadthMI: Market Breadth Indicator Analysis
## Overview
The Yelober_Momentum_BreadthMI is a comprehensive market breadth indicator designed to monitor market internals across NYSE and NASDAQ exchanges. It tracks several key metrics including up/down volume ratios, TICK readings, and trend momentum to provide traders with real-time insights into market direction, strength, and potential turning points.
## Indicator Components
This indicator displays a table with data for:
- NYSE breadth metrics
- NASDAQ breadth metrics
- NYSE TICK data and trends
- NASDAQ TICK (TICKQ) data and trends
## Table Columns and Interpretation
### Column 1: Market
Identifies the data source:
- **NYSE**: New York Stock Exchange data
- **NASDAQ**: NASDAQ exchange data
- **Tick**: NYSE TICK index
- **TickQ**: NASDAQ TICK index
### Column 2: Ratio
Shows the current ratio values with different calculations depending on the row:
- **For NYSE/NASDAQ rows**: Displays the up/down volume ratio
- Positive values (green): More up volume than down volume
- Negative values (red): More down volume than up volume
- The magnitude indicates the strength of the imbalance
- **For Tick/TickQ rows**: Shows the ratio of positive to negative ticks plus the current TICK reading in parentheses
- Format: "Ratio (Current TICK value)"
- Positive values (green): More stocks ticking up than down
- Negative values (red): More stocks ticking down than up
### Column 3: Trend
Displays the directional trend with both a symbol and value:
- **For NYSE/NASDAQ rows**: Shows the VOLD (volume difference) slope
- "↗": Rising trend (positive slope)
- "↘": Falling trend (negative slope)
- "→": Neutral/flat trend (minimal slope)
- **For Tick/TickQ rows**: Shows the slope of the ratio history
- Color-coding: Green for positive momentum, Red for negative momentum, Gray for neutral
The trend column is particularly important as it shows the current momentum of the market. The indicator applies specific thresholds for color-coding:
- NYSE: Green when normalized value > 2, Red when < -2
- NASDAQ: Green when normalized value > 3.5, Red when < -3.5
- TICK/TICKQ: Green when slope > 0.01, Red when slope < -0.01
## How to Use This Indicator
### Basic Interpretation
1. **Market Direction**: When multiple rows show green ratios and upward trends, it suggests strong bullish market internals. Conversely, red ratios and downward trends indicate bearish internals.
2. **Market Breadth**: The magnitude of the ratios indicates how broad-based the market movement is. Higher absolute values suggest stronger market breadth.
3. **Momentum Shifts**: When trend arrows change direction or colors shift, it may signal a potential reversal or change in market momentum.
4. **Divergences**: Look for divergences between different markets (NYSE vs NASDAQ) or between ratios and trends, which can indicate potential market turning points.
### Advanced Usage
- **Volume Normalization**: The indicator includes options to normalize volume data (none, tens, thousands, millions, 10th millions) to handle different exchange scales.
- **Trend Averaging**: The slope calculation uses an averaging period (default: 5) to smooth out noise and identify more reliable trend signals.
## Examples for Interpretation
### Example 1: Strong Bullish Market
```
| Market | Ratio | Trend |
|--------|---------|-----------|
| NYSE | 1.75 | ↗ 2.85 |
| NASDAQ | 2.10 | ↗ 4.12 |
| Tick | 2.45 (485) | ↗ 0.05 |
| TickQ | 1.95 (320) | ↗ 0.03 |
```
**Interpretation**: All metrics are positive and trending upward (green), indicating a strong, broad-based rally. The high ratio values show significant bullish dominance. This suggests continuation of the upward move with good momentum.
### Example 2: Weakening Market
```
| Market | Ratio | Trend |
|--------|---------|-----------|
| NYSE | 0.45 | ↘ -1.50 |
| NASDAQ | 0.85 | → 0.30 |
| Tick | 0.95 (105) | ↘ -0.02 |
| TickQ | 1.20 (160) | → 0.00 |
```
**Interpretation**: The market is showing mixed signals with positive but low ratios, while NYSE and TICK trends are turning negative. NASDAQ shows neutral to slightly positive momentum. This divergence often occurs near market tops or during consolidation phases. Traders should be cautious and consider reducing position sizes.
### Example 3: Negative Market Turning Positive
```
| Market | Ratio | Trend |
|--------|---------|-----------|
| NYSE | -1.25 | ↗ 1.75 |
| NASDAQ | -0.95 | ↗ 2.80 |
| Tick | -1.35 (-250) | ↗ 0.04 |
| TickQ | -1.10 (-180) | ↗ 0.02 |
```
**Interpretation**: This is a potential bottoming pattern. Current ratios are still negative (red) showing overall negative breadth, but the trends are all positive (green arrows), indicating improving momentum. This divergence often occurs at market bottoms and could signal an upcoming reversal. Look for confirmation with price action before establishing long positions.
### Example 4: Mixed Market with Divergence
```
| Market | Ratio | Trend |
|--------|---------|-----------|
| NYSE | 1.45 | ↘ -2.25 |
| NASDAQ | -0.85 | ↘ -3.80 |
| Tick | 1.20 (230) | ↘ -0.03 |
| TickQ | -0.75 (-120) | ↘ -0.02 |
```
**Interpretation**: There's a significant divergence between NYSE (positive ratio) and NASDAQ (negative ratio), while all trends are negative. This suggests sector rotation or a market that's weakening but with certain segments still showing strength. Often seen during late-stage bull markets or in transitions between leadership groups. Consider reducing risk exposure and focusing on relative strength sectors.
## Practical Trading Applications
1. **Confirmation Tool**: Use this indicator to confirm price movements. Strong breadth readings in the direction of the price trend increase confidence in trade decisions.
2. **Early Warning System**: Watch for divergences between price and breadth metrics, which often precede market turns.
3. **Intraday Trading**: The real-time nature of TICK and volume data makes this indicator valuable for day traders to gauge intraday momentum shifts.
4. **Market Regime Identification**: Sustained readings can help identify whether the market is in a trend or chop regime, allowing for appropriate strategy selection.
This breadth indicator is most effective when used in conjunction with price action and other technical indicators rather than in isolation.
Yelober - Sector Rotation Detector# Yelober - Sector Rotation Detector: User Guide
## Overview
The Yelober - Sector Rotation Detector is a TradingView indicator designed to track sector performance and identify market rotations in real-time. It monitors key sector ETFs, calculates performance metrics, and provides actionable stock recommendations based on sector strength and weakness.
## Purpose
This indicator helps traders identify when capital is moving from one sector to another (sector rotation), which can provide valuable trading opportunities. It also detects risk-off conditions in the market and highlights sectors with abnormal trading volume.
## Table Columns Explained
### 1. Sector
Displays the sector name being monitored. The indicator tracks six primary sectors plus the S&P 500:
- Energy (XLE)
- Financial (XLF)
- Technology (XLK)
- Consumer Staples (XLP)
- Utilities (XLU)
- Consumer Discretionary (XLY)
- S&P 500 (SPY)
### 2. Perf %
Shows the daily percentage performance of each sector ETF. Values are color-coded:
- Green: Positive performance
- Red: Negative performance
Positive values display with a "+" sign (e.g., +1.25%)
### 3. RSI
Displays the Relative Strength Index value for each sector, which helps identify overbought or oversold conditions:
- Values above 70 (highlighted in red): Potentially overbought
- Values below 30 (highlighted in green): Potentially oversold
- Values between 30-70 (highlighted in blue): Neutral territory
### 4. Vol Ratio
Shows the volume ratio, which compares today's volume to the average volume over the lookback period:
- Values above 1.5x (highlighted in yellow): Indicates abnormally high trading volume
- Values below 1.5x (highlighted in blue): Normal trading volume
This helps identify sectors with unusual activity that may signal important price movements.
### 5. Trend
Displays the current price trend direction with symbols:
- ▲ (green): Uptrend (today's close > yesterday's close)
- ▼ (red): Downtrend (today's close < yesterday's close)
- ◆ (gray): Neutral (today's close = yesterday's close)
## Summary & Recommendations Section
The summary section provides:
1. **Sector Rotation Detection**: Identifies when there's a significant performance gap (>2%) between the strongest and weakest sectors.
2. **Risk-Off Mode Detection**: Alerts when defensive sectors (Consumer Staples and Utilities) are positive while Technology is negative, which often signals investors are moving to safer assets.
3. **Strong Volume Detection**: Indicates when any sector shows abnormally high trading volume.
4. **Stock Recommendations**: Suggests specific stocks to consider for long positions (from the strongest sectors) and short positions (from the weakest sectors).
## Example Interpretations
### Example 1: Sector Rotation
If you see:
- Technology: -1.85%
- Financial: +2.10%
- Summary shows: "SECTOR ROTATION DETECTED: Rotation from Technology to Financial"
**Interpretation**: Capital is moving out of tech stocks and into financial stocks. This could be due to rising interest rates, which typically benefit banks while pressuring high-growth tech companies. Consider looking at financial stocks like JPM, BAC, and WFC for potential long positions.
### Example 2: Risk-Off Conditions
If you see:
- Consumer Staples: +0.80%
- Utilities: +1.20%
- Technology: -1.50%
- Summary shows: "RISK-OFF MODE DETECTED"
**Interpretation**: Investors are seeking safety in defensive sectors while selling growth-oriented tech stocks. This often occurs during market uncertainty or ahead of economic concerns. Consider reducing exposure to high-beta stocks and possibly adding defensive names like PG, KO, or NEE.
### Example 3: Volume Spike
If you see:
- Energy: +3.20% with Volume Ratio 2.5x (highlighted in yellow)
- Summary shows: "STRONG VOLUME DETECTED"
**Interpretation**: The energy sector is making a strong move with significantly higher-than-average volume, suggesting conviction behind the price movement. This could indicate the beginning of a sustained trend in energy stocks. Consider names like XOM, CVX, and COP.
## How to Use the Indicator
1. Apply the indicator to any chart (works best on daily timeframes).
2. Customize settings if needed:
- Timeframe: Choose between intraday (60 or 240 minutes), daily, or weekly
- Lookback Period: Adjust the historical comparison period (default: 20)
- RSI Period: Modify the RSI calculation period (default: 14)
3. To refresh the data: Click the settings icon, increase the "Click + to refresh data" counter, and click "OK".
4. Identify opportunities based on sector performance, RSI levels, volume ratios, and the summary recommendations.
This indicator helps traders align with market rotation trends and identify which sectors (and specific stocks) may outperform or underperform in the near term.
MC Geopolitical Tension Events📌 Script Title: Geopolitical Tension Events
📖 Description:
This script highlights key geopolitical and military tension events from 1914 to 2024 that have historically impacted global markets.
It automatically plots vertical dashed lines and labels on the chart at the time of each major event. This allows traders and analysts to visually assess how markets have responded to global crises, wars, and significant political instability over time.
🧠 Use Cases:
Historical backtesting: Understand how market responded to past geopolitical shocks.
Contextual analysis: Add macro context to technical setups.
🗓️ List of Geopolitical Tension Events in the Script
Date Event Title Description
1914-07-28 WWI Begins Outbreak of World War I following the assassination of Archduke Franz Ferdinand.
1929-10-24 Wall Street Crash Black Thursday, the start of the 1929 stock market crash.
1939-09-01 WWII Begins Germany invades Poland, starting World War II.
1941-12-07 Pearl Harbor Japanese attack on Pearl Harbor; U.S. enters WWII.
1945-08-06 Hiroshima Bombing First atomic bomb dropped on Hiroshima by the U.S.
1950-06-25 Korean War Begins North Korea invades South Korea.
1962-10-16 Cuban Missile Crisis 13-day standoff between the U.S. and USSR over missiles in Cuba.
1973-10-06 Yom Kippur War Egypt and Syria launch surprise attack on Israel.
1979-11-04 Iran Hostage Crisis U.S. Embassy in Tehran seized; 52 hostages taken.
1990-08-02 Gulf War Begins Iraq invades Kuwait, triggering U.S. intervention.
2001-09-11 9/11 Attacks Coordinated terrorist attacks on the U.S.
2003-03-20 Iraq War Begins U.S.-led invasion of Iraq to remove Saddam Hussein.
2008-09-15 Lehman Collapse Bankruptcy of Lehman Brothers; peak of global financial crisis.
2014-03-01 Crimea Crisis Russia annexes Crimea from Ukraine.
2020-01-03 Soleimani Strike U.S. drone strike kills Iranian General Qasem Soleimani.
2022-02-24 Ukraine Invasion Russia launches full-scale invasion of Ukraine.
2023-10-07 Hamas-Israel War Hamas launches attack on Israel, sparking war in Gaza.
2024-01-12 Red Sea Crisis Houthis attack ships in Red Sea, prompting Western naval response.
Yelober - Intraday ETF Dashboard# How to Read the Yelober Intraday ETF Dashboard
The Intraday ETF Dashboard provides a powerful at-a-glance view of sector performance and trading opportunities. Here's how to interpret and use the information:
## Basic Dashboard Reading
### Color-Coding System
- **Green values**: Positive performance or bullish signals
- **Red values**: Negative performance or bearish signals
- **Symbol colors**: Green = buy signal, Red = sell signal, Gray = neutral
### Example 1: Identifying Strong Sectors
If you see XLF (Financials) with:
- Day % showing +2.65% (green background)
- Symbol in green color
- RSI of 58 (not overbought)
**Interpretation**: Financial sector is showing strength and momentum without being overextended. Consider long positions in top financial stocks like JPM or BAC.
### Example 2: Spotting Weakness
If you see XLK (Technology) with:
- Day % showing -1.20% (red background)
- Week % showing -3.50% (red background)
- Symbol in red color
- RSI of 35 (approaching oversold)
**Interpretation**: Technology sector is showing weakness across multiple timeframes. Consider avoiding tech stocks or taking short positions in names like MSFT or AAPL, but be cautious as the low RSI suggests a bounce may be coming.
## Advanced Interpretations
### Example 3: Sector Rotation Detection
If you observe:
- XLE (Energy) showing +2.10% while XLK (Technology) showing -1.50%
- Both sectors' Week % values showing the opposite trend
**Interpretation**: This suggests money is rotating out of technology into energy stocks. This rotation pattern is actionable - consider reducing tech exposure and increasing energy positions (look at XOM, CVX in the Top Stocks column).
### Example 4: RSI Divergences
If you see XLU (Utilities) with:
- Day % showing +0.50% (small positive)
- RSI showing 72 (overbought, red background)
**Interpretation**: Despite positive performance, the high RSI suggests the sector is overextended. This divergence between price and indicator suggests caution - the rally in utilities may be running out of steam.
### Example 5: Relative Strength in Weak Markets
If SPY shows -1.20% but XLP (Consumer Staples) shows +0.30%:
**Interpretation**: Consumer staples are showing defensive strength during market weakness. This is typical risk-off behavior. Consider defensive positions in stocks like PG, KO, or PEP for protection.
## Practical Application Scenarios
### Day Trading Setup
1. **Morning Market Assessment**:
- Check which sectors are green pre-market
- Focus on sectors with Day % > 1% and RSI between 40-70
- Identify 2-3 stocks from the Top Stocks column of the strongest sector
2. **Midday Reversal Hunting**:
- Look for sectors with symbol color changing from red to green
- Confirm with RSI moving away from extremes
- Trade stocks from that sector showing similar pattern changes
### Swing Trading Application
1. **Trend Following**:
- Identify sectors with positive Day % and Week %
- Look for RSI values in uptrend but not overbought (45-65)
- Enter positions in top stocks from these sectors, using daily charts for confirmation
2. **Contrarian Setups**:
- Find sectors with deeply negative Day % but RSI < 30
- Look for divergence (price making new lows but RSI rising)
- Consider counter-trend positions in the stronger stocks within these oversold sectors
## Reading Special Conditions
### Example 6: Risk-Off Environment
If you observe:
- XLP (Consumer Staples) and XLU (Utilities) both green
- XLK (Technology) and XLY (Consumer Disc) both red
- SPY slightly negative
**Interpretation**: Classic risk-off rotation. Investors are moving to safety. Consider defensive positioning and reducing exposure to growth sectors.
### Example 7: Market Breadth Analysis
Count the number of sectors in green vs. red:
- If 7+ sectors are green: Strong bullish breadth, consider aggressive long positioning
- If 7+ sectors are red: Weak market breadth, consider defensive positioning or shorts
- If evenly split: Market is indecisive, focus on specific sector strength instead of broad market exposure
Remember that this dashboard is most effective when combined with broader market analysis and appropriate risk management strategies.
Global Market Pulse + [Combined]The Global Market Pulse + is a multi-functional analytical tool designed for traders and investors working with cryptocurrencies, stocks, and macroeconomic assets. It integrates 7 independent analytical modules into a single script, providing a comprehensive market assessment.
Operating Modes
1️⃣ Crypto Mode
Function: Monitors the crypto market health by analyzing:
Altcoin market capitalization (excluding BTC)
Bitcoin and Ethereum dominance shifts
Trading volume dynamics
Output: Pulse line (0-100 scale) with:
Accumulation Zone (Bullish)
Distribution Zone (Bearish)
2️⃣ Equity Mode
Function: Tracks traditional markets via:
S&P 500 (SPX) momentum
US Dollar Index (DXY) trends
Gold/Silver ratio
Use Case: Identifies "risk-on/risk-off" periods affecting crypto.
3️⃣ Correlation Mode
Function: Calculates BTC's correlation with:
SPX | Gold | Oil | Custom assets (user-defined)
Thresholds:
+0.7+ Strong positive correlation
-0.7- Inverse correlation
4️⃣ Altseason Mode
Function: Detects altcoin investment opportunities using:
Altcoin Dominance Oscillator
Custom OB/OS levels
Signals:
Buy: Oversold + Volume spike
Sell: Overbought + Volume drop
5️⃣ Cycle Mode
Function:
Auto-detects market cycle lengths
Predicts future turning points
Features:
Adaptive timeframe-based settings
Anomaly detection (deviations from mean)
6️⃣ RSX-MACD Mode
Function: Hybrid momentum indicator combining:
RSX (smoothed RSI)
Classic MACD logic
Advantage: Reduced false signals vs traditional MACD.
7️⃣ Dual-RSX Mode
Function: Dual-speed RSX indicator with:
Fast line (short-term)
Slow line (long-term)
Key Features
Adaptive Logic: Auto-adjusts parameters based on:
Selected timeframe (M1 - Weekly)
Market type (Crypto/Stocks)
Multi-Timeframe Analysis: Processes higher timeframe data on any chart.
Custom Assets: Add any ticker for correlation studies.
Visual Alerts: Color-coded signals for quick interpretation.
Usage Recommendations
For Crypto Traders:
Combine Crypto + Altseason modes for altcoin timing.
Use Correlation to filter macro risks.
Stock Investors:
Equity + Cycle modes for SPX/gold entry points.
Algorithmic Trading:
RSX-MACD/Dual-RSX provide ready-made conditions for bots.
⚠ Disclaimer: Educational tool only. Always confirm signals with additional analysis.
Global Market Pulse + — это многофункциональный инструмент для анализа крипторынка, акций и макроактивов. Он объединяет 7 независимых модулей в одном скрипте.
Режимы работы
1️⃣ Crypto (Крипторынок)
Анализ:
Капитализация альткоинов (без BTC)
Доминирование BTC/ETH
Объемы торгов
Сигналы:
Аккумуляция (бычья зона)
Дистрибуция (медвежья зона)
2️⃣ Equity (Фондовый рынок)
Анализ:
Динамика S&P 500 (SPX)
Индекс доллара (DXY)
Соотношение золото/серебро
Применение: Определение "risk-on/risk-off" периодов.
3️⃣ Correlation (Корреляции)
Анализ: Корреляция BTC с:
SPX | Золото | Нефть | Пользовательскими активами
Пороги:
+0.7+ Сильная прямая связь
-0.7- Обратная корреляция
4️⃣ Altseason (Альтсезон)
Анализ:
Осциллятор доминирования альткоинов
Уровни перекупленности/перепроданности
Сигналы:
Покупка: Перепроданность + рост объемов
Продажа: Перекупленность + падение объемов
5️⃣ Cycle (Циклы)
Функции:
Автовыявление длительности циклов
Прогноз точек разворота
Особенности:
Автоподстройка под таймфрейм
Детекция аномалий
6️⃣ RSX-MACD
Особенности: Гибрид RSX (сглаженный RSI) и MACD.
Преимущество: Меньше ложных сигналов.
7️⃣ Dual-RSX
Функция: Двойной RSX с:
Быстрой линией (краткосрок)
Медленной линией (долгосрок)
Уровни: 20 (перепрод.) / 50 (центр) / 80 (перекуп.)
Ключевые особенности
Автоподстройка под таймфрейм и тип рынка.
Мультитаймфрейм-анализ на любом графике.
Кастомизация: Добавление любых активов для корреляций.
Визуальные сигналы: Цветовая индикация состояний.
Рекомендации по использованию
Криптотрейдерам:
Комбинация Crypto + Altseason для торговли альткоинами.
Correlation для учета макрорисков.
Инвесторам:
Equity + Cycle для точек входа в SPX/золото.
Алготрейдинг:
RSX-MACD/Dual-RSX как условия для торговых роботов.
⚠ Важно: Инструмент для анализа. Не является торговой рекомендацией.
Black Box Trading Measuring Tool (BlackBox - BBT)Overview
The Black Box Trading Indicator is a comprehensive technical analysis tool that combines multiple trading concepts into a single, powerful indicator. It displays custom session ranges, Average Daily Range (ADR) projections, support/resistance levels, and order blocks to help traders identify key market levels and potential trading opportunities.
Key Features
1. Custom Session Ranges
Define and visualize any trading session with customizable start and end times
Automatically calculates session high, low, and midpoint
Displays quarter levels (25% and 75% of range)
Shows range projections at 100%, 150%, 200%, and 250% extensions
2. Average Daily Range (ADR) Analysis
Calculates and displays ADR for daily, weekly, monthly, and custom timeframes
Shows projected high and low targets based on ADR
Includes "hash" levels at 50% ADR from session midpoint
Visual range boxes highlight potential support/resistance zones
3. Market Structure Levels
Daily and weekly opening prices with dynamic coloring
Previous daily and weekly center mass (50% of previous period's range)
Real-time range statistics displayed in an information table
4. Order Block Detection
Automatically identifies bullish and bearish order blocks
Visual representation with customizable colors and transparency
Mitigation tracking to remove invalidated blocks
Alert system for price interaction with order blocks
Parameter Guide
Display Settings
Show Blocks
Enables/disables order block visualization
Useful for cleaner charts when focusing on other elements
Show Previous Daily/Weekly Center Mass
Displays the midpoint of the previous period's range
Helps identify potential support/resistance from prior price acceptance areas
Show Daily/Weekly Open
Shows opening prices with color coding (blue for bullish, orange for bearish)
Important reference points for intraday trading
Show ADR Targets
Displays projected highs and lows based on Average Daily Range
Essential for setting realistic profit targets and stop losses
Show Range Projection
Extends the session range by multiples (1x, 1.5x, 2x, 2.5x)
Helps identify potential price targets during trending moves
Show Average Daily Range
Displays the ADR statistics table
Shows current range metrics for multiple timeframes
Display range in pips
Converts range values to pips for forex traders
Provides standardized measurement across different instruments
ADR Configuration
ADR Days
Number of days to include in current ADR calculation
Default: 1 (shows today's developing range)
ADR Period
Lookback period for calculating average range
Default: 14 days (standard period for volatility measurement)
Custom Range
Select between 60-minute or 240-minute timeframes
Allows analysis of intermediate timeframes
Session Time Settings (EST)
Start Hour/Minute
Define when your custom session begins
Default: 19:00 EST (Asian session open)
End Hour/Minute
Define when your custom session ends
Default: 02:45 EST (London session approach)
Extend To Hour/Minute
How far to extend the horizontal lines
Default: 19:00 EST (full 24-hour extension)
Visual Customization
Color Settings
Top Color: Used for upper levels and bullish projections
Bottom Color: Used for lower levels and bearish projections
Range Outline Color: Main session range boundaries
Center Range Line Color: Session midpoint visualization
Line Settings
Range Outline Width: Thickness of range box borders
Session Line Width: Thickness of horizontal level lines
Line Styles: Choose between solid, dashed, or dotted
Text Settings
Text Color: Color for all labels
Text Size: AUTO, tiny, small, normal, or large
Order Block Settings
Sensitivity
Percentage threshold for order block detection (1-100)
Higher values = fewer but stronger blocks
Default: 25 (detects 25% price movements)
OB Mitigation Type
Close: Block is mitigated when price closes beyond it
Wick: Block is mitigated when price wicks beyond it
Color Configuration
Separate colors for bullish and bearish blocks
Border and background colors can be customized independently
Trading Applications
1. Session-Based Trading
Identify the initial balance (first hour of trading)
Trade breakouts from defined session ranges
Use range projections for profit targets
Monitor for range-bound vs trending conditions
2. ADR-Based Strategies
Set daily profit targets based on ADR projections
Identify overextended moves when price exceeds ADR
Use ADR levels for position sizing and risk management
Compare current range to average for volatility assessment
3. Support/Resistance Trading
Use previous period center mass as dynamic S/R
Trade bounces from daily/weekly opens
Combine multiple timeframe levels for confluence
Monitor order blocks for potential reversal zones
4. Order Block Trading
Enter trades when price returns to unmitigated blocks
Use blocks as stop loss placement guides
Look for confluence with other indicator levels
Monitor block mitigation for trend confirmation
Best Practices
1. Multi-Timeframe Analysis
Use higher timeframe blocks for major levels
Combine with lower timeframe entries
Monitor weekly levels on daily charts
2. Confluence Trading
Look for areas where multiple levels align
Combine order blocks with ADR targets
Use session ranges with center mass levels
3. Risk Management
Use ADR for realistic daily profit targets
Place stops beyond order blocks or range extremes
Size positions based on distance to key levels
4. Alert Usage
Set alerts for ADR target hits
Monitor order block interactions
Track range breakouts and hash level tests
Tips for Effective Use
Start Simple: Begin with basic session ranges and ADR before adding all features
Color Coding: Use consistent colors across your trading setup
Time Zones: Ensure session times match your trading schedule
Clean Charts: Toggle off unused features for clarity
Backtesting: Study how price respects these levels historically
Journaling: Document which levels work best for your traded instruments
Common Trading Scenarios
Range Trading
Enter longs at session low or lower projections
Enter shorts at session high or upper projections
Target the session midpoint or opposite extreme
Breakout Trading
Wait for clear breaks of session range
Use range width for measuring targets
Monitor ADR to gauge breakout potential
Trend Following
Use order blocks as pullback entries
Trail stops using range projections
Scale out at ADR targets
Reversal Trading
Look for price rejection at ADR extremes
Monitor order block mitigation failures
Use center mass as reversal confirmation
NVT Ratio Z-Score | [DeV]** DISCLAIMER: This indicator is not trend following, so it SHOULD NOT be a buy/sell signal or used as a stand alone indicator to tell you to buy or sell. It's simply giving insight into potential overbought or oversold market conditions, and should be used in conjunction with other market analysis tools to give you an idea of possible market reversals.**
The NVT Ratio Z-Score is a unique on-chain valuation tool that helps users assess whether Bitcoin is potentially overbought or oversold relative to its network fundamentals. This indicator calculates the Network Value to Transactions (NVT) ratio, which compares Bitcoin’s market capitalization (price × circulating supply) to the USD-denominated daily transaction volume on the network. To improve clarity and remove short-term noise, the NVT value is smoothed using a customizable moving average (NVT Smoothing Period). The smoothed value is then normalized using a Z-score over a rolling period (Normalization Lookback Period), allowing for easier comparison of extreme deviations over time. This normalization makes it possible to spot historically high or low valuation zones with consistency.
While the NVT Ratio Z-Score is not a price action or trend-following indicator, it excels as a valuation-based supplemental tool. By using this indicator alongside your existing technical setups—such as momentum oscillators (like RSI or MACD), moving averages, or volume profiles—you can gain a deeper perspective on whether the broader market is operating in an overheated or undervalued state.
Interpretation is straightforward: the lower the Z-score dips into negative territory, the more oversold the market may be, potentially indicating a bottoming process or future upward reversal. Conversely, higher Z-scores suggest the market is becoming overheated or overbought, which can precede pullbacks or broader downtrends. However, it’s crucial to remember: this is not a trend indicator. Overbought conditions don’t guarantee immediate downturns, and oversold conditions don’t guarantee immediate rallies. Markets can remain extended in either direction for prolonged periods.
Use the NVT Ratio Z-Score to contextualize price moves and strengthen conviction when your other tools show signals aligning with extreme valuation zones. This indicator is especially helpful for swing traders, long-term investors, and those analyzing Bitcoin through a macro-on-chain lens.
Greer Value📈 Greer Value
This indicator evaluates the year-over-year (YoY) growth consistency of five key fundamental metrics for any stock:
Book Value Per Share
Free Cash Flow
Operating Margin
Total Revenue
Net Income
The script tracks whether each metric increases annually based on financial statement data (FY), then calculates both individual and aggregate increase percentages over time. A color-coded table is displayed on the most recent bar showing:
Raw counts of increases vs. checks per metric
Percentage of years with growth
Overall "Greer Value" score indicating total consistency across all five metrics
✅ Green = Strong YoY growth
❌ Red = Weak or inconsistent growth
Use this tool to help identify fundamentally improving companies with long-term value creation potential.
Calc win-LoserHow to Use the Calc win-Loser Indicator
The indicator calculates the profit or loss of the operation, showing how much you gained or lost on the invested amount, without adding the initial capital, displaying only the profit or loss separately.
Use a period (.) to separate decimal numbers, without thousand separators (e.g., 1000 for one thousand, 1000.50 for one thousand and fifty cents).
Price Definition for Calculation
Long Position (buy):
Low Price: entry price (lower)
High Price: exit price (higher)
Example: enter at 1 and exit at 3
Short Position (sell):
High Price: entry price (higher)
Low Price: exit price (lower)
Example: enter at 3 and exit at 1
Main Parameters
Parameter Description Example
Low Price Base price for calculation (Long: entry; Short: exit) 1
High Price Base price for calculation (Long: exit; Short: entry) 3
Leverage Operation multiplier (leverage) 2.0
Universal Amount Total amount invested 1000
Broker Fee (%) Percentage fee charged by broker 0.1
Currency Currency symbol for value display USD
Practical Example
Long: entry at 1, exit at 3, 2x leverage, $1000 investment, 0.1% fee.
Short: entry at 3, exit at 1, 2x leverage, $1000 investment, 0.1% fee.
The indicator will show the expected profit or loss based on the percentage difference adjusted by leverage and subtracting the broker fee.
Notes
Adjust prices according to the type of operation (Long or Short).
Use a period for decimals and do not use thousand separators.
This indicator is a simulation tool and does not execute automatic trades.
Original indicator by Canhoto-Medium — protected to maintain order and respect, prevent copying and plagiarism.
