BTC D-AccumulatorBTC D-Accumulator — Adaptive Bitcoin Macro Accumulation System
Overview
BTC D-Accumulator is an advanced Bitcoin-focused accumulation detection and signal generation tool designed for daily timeframe traders and long-term investors. Its main purpose is to help users identify potential macro accumulation zones and market cycle resets with high statistical confidence. By combining on-chain metrics (NUPL, CVDD), adaptive EMA-based trend filtering, and a proprietary math-driven crossover logic, it delivers clear accumulation signals classified into four levels of conviction: AI BUY, BUY, Low Accumulation, and Risky Accumulation.
What It Does
BTC D-Accumulator analyzes BTC price action and market health across several complementary dimensions:
1. On-Chain Valuation Metrics - NUPL (Net Unrealized Profit/Loss) is used to gauge sentiment extremes and potential undervaluation. CVDD (Cumulative Value Days Destroyed) defines probabilistic long-term floor values based on historical spending behavior.
2. Macro Crossover Logic - A custom math-based moving average crossover system dynamically adjusts its periods to the timeframe. Detects major market cycle resets or restarts (AI SELL / AI BUY signals).
3. Dynamic EMA Filtering - Evaluates BTC’s position relative to EMA50, EMA100, and EMA200 to confirm broader trend context and filter signals.
4. Momentum and Mean Reversion Conditions - RSI and smoothed RSI values ensure that signals are only triggered when the market is statistically oversold. A custom dual-line momentum engine measures directional bias and deceleration.
5. Visual Labels & Alerts - Each signal is displayed with a label directly on the chart (AI BUY, BUY, or arrows for other accumulation levels). Built-in alerts allow traders to be notified instantly when accumulation signals appear.
How It Works
BTC D-Accumulator uses the combined state of these components to classify price action into four actionable accumulation signals:
1. AI BUY – Strongest macro accumulation signal triggered by a proprietary math crossover and confirmed by other criteria.
2. BUY – High-probability accumulation signal combining on-chain undervaluation and momentum exhaustion.
3. GREEN ARROW – Moderate accumulation signal triggered when BTC is below major EMAs and shows volatility compression.
4. ORANGE ARROW – Early accumulation attempt during oversold conditions but with less confluence; higher risk.
Result: Signals only appear when multiple valuation, momentum, and trend filters align, improving selectivity and reducing noise.
How To Use It
1. Confirm the Context: Always ensure you are viewing BTC pairs (BTCUSD, BTCUSDT, BTCUSDC) on the Daily timeframe. Assess the overall market trend and sentiment before taking action.
2. Act According to the Signal Type:
-- AI BUY: Indicates a major cycle reset or strong accumulation opportunity; suitable for scaling into long-term positions.
-- BUY: Signals a statistically favorable zone for adding exposure with high confidence.
-- Low Accumulation: Moderate conviction entry; consider using partial position size.
-- Risky Accumulation: Early accumulation in potentially unstable market conditions; requires tighter risk control.
3. Manage Exposure: Use stop losses and scale entries progressively rather than committing all capital at once. Combine with your macro thesis and portfolio objectives.
Why It Is Unique
1. Integrates on-chain valuation metrics (NUPL, CVDD) with adaptive EMA filtering and math-based cycle detection.
2. Designed specifically for Bitcoin daily charts, avoiding false signals in other pairs or timeframes.
3. Provides four clearly classified accumulation signals, enabling flexible strategy deployment across different conviction levels.
4. Includes real-time visual labels and alerts for improved situational awareness and automation.
Apply Risk Management
Never rely exclusively on signals without understanding Bitcoin’s broader context. Maintain a clear risk/reward plan, diversify across entries, and size positions responsibly.
Timeframe Selection
Optimized for the Daily timeframe only. Using lower or higher timeframes will disable or distort signals.
Asset Selection
Only applicable to BTCUSD/BTCUSDT/BTCUSDC
Best Suited For
Bitcoin investors, swing traders, and position traders who want a systematic framework to identify macro accumulation opportunities.
Important Notes
The signals generated by BTC D-Accumulator are intended to support informed decisions, not to replace independent analysis. While the indicator incorporates advanced on-chain and price-based metrics, it does not guarantee outcomes. Use all information in combination with your trading plan and risk management practices.
License
This indicator was developed by the ProphetAlgoAI team. Its use is restricted to TradingView under a private, invite-only agreement. Redistribution or usage outside TradingView is strictly prohibited without explicit authorization from the ProphetAlgoAI team.
Analisi fondamentale
ADT MSI TableKey Features:
1. Market Smith Methodology
Composite Rating: Combines price and volume strength
Relative Strength Rating: Measures stock performance vs benchmark
Base Pattern Detection: Identifies consolidation patterns
Breakout Signals: Detects valid breakouts with volume confirmation
2. Indian Market Adaptations
INR Currency Formatting: Displays prices in ₹, Lakhs, and Crores
Indian Benchmarks: NIFTY, SENSEX, NIFTY500 options
Market Cap Display: Formatted in Indian currency standards
Trading Hours Compatibility: Works with NSE/BSE data
3. Comprehensive Data Table
Real-time Metrics: Current price, daily change, volume analysis
Technical Indicators: MA positions, RS rating, composite rating
Performance Tracking: 3M, 6M, 12M returns
Signal Generation: BUY/SELL/HOLD recommendations
4. Visual Elements
Multiple Moving Averages: 10, 20, 50, 200 period MAs
Support/Resistance Levels: Dynamic pivot-based levels
Volume Analysis: Color-coded volume bars with surge detection
Trend Background: Color-coded background based on trend strength
Breakout Markers: Visual signals for valid breakouts
5. Customizable Parameters
Adjustable Periods: All timeframes can be modified
Table Positioning: 9 different table positions
Alert System: Customizable breakout and volume alerts
Display Options: Toggle any component on/off
6. Indian Market Specific
No Errors: Fully compatible with Indian stock data
Proper Formatting: All values in Indian currency format
Market Hours: Optimized for Indian trading sessions
Volume Calculations: Adapted for Indian market volume patterns
Global Risk Matrix [QuantAlgo]🟢 Overview
The Global Risk Matrix is a comprehensive macro risk assessment tool that aggregates multiple global financial indicators into a unified risk sentiment framework. It transforms diverse economic data streams (from currency strength and liquidity measures to volatility indices and commodity prices) into standardized Z-Score readings to identify market regime shifts across risk-on and risk-off conditions.
The indicator displays both a risk oscillator showing weighted average sentiment and a dynamic 2D matrix visualization that plots signal strength against momentum to reveal current market phase and historical evolution. This helps traders and investors understand broad market conditions, identify regime transitions, and align their strategies with prevailing macro risk environments across all asset classes.
🟢 How It Works
The indicator employs Z-Score normalization across various global macro components, each representing distinct aspects of market liquidity, sentiment, and economic health. Raw data from sources like DXY, S&P 500, Fed liquidity, global M2 money supply, VIX, and commodities undergoes statistical standardization. Several components are inverted (USDT.D, DXY, VIX, credit spreads, treasury bonds, gold) to align with risk-on interpretation, where positive values indicate bullish conditions.
This unique system applies configurable weights to each component based on selected asset class presets (Crypto Investor/Trader, Stock Trader, Commodity Trader, Forex Trader, Risk Parity, or Custom), creating a weighted average Z-Score. It then analyzes both signal strength and momentum direction to classify market conditions into four distinct phases: Risk-On (positive signal, rising momentum), Risk-Off (negative signal, falling momentum), Recovery (negative signal, rising momentum), and Weakening (positive signal, falling momentum). The 2D matrix visualization plots these dimensions with historical trail tracking to show regime evolution over time.
🟢 How to Use
1. Risk Oscillator Interpretation and Phase Analysis
Positive Territory (Above Zero) : Indicates risk-on conditions with capital flowing toward growth assets and higher risk tolerance
Negative Territory (Below Zero) : Signals risk-off sentiment with capital seeking safety and defensive positioning
Extreme Levels (±2.0) : Represent statistically significant deviations that often precede regime reversals or trend exhaustion
Zero Line Crosses : Mark critical transitions between risk regimes, providing early signals for portfolio rebalancing
Phase Color Coding : Green (Risk-On), Red (Risk-Off), Blue (Recovery), Yellow (Weakening) for immediate regime identification
2. Risk Matrix Visualization and Trail Analysis
Current Position Marker (⌾) : Shows real-time location in the risk/momentum space for immediate situational awareness
Historical Trail : Connected path showing recent market evolution and regime transition patterns
Quadrant Analysis : Risk-On (upper right), Risk-Off (lower left), Recovery (lower right), Weakening (upper left)
Trail Patterns : Clockwise rotation typically indicates healthy regime cycles, while erratic movement suggests uncertainty
3. Pro Tips for Trading and Investing
→ Portfolio Allocation Filter : Use Risk-On phases to increase exposure to growth assets, small caps, and emerging markets while reducing defensive positions during confirmed green phases
→ Entry Timing Enhancement : Combine Recovery phase signals with your technical analysis for optimal long entry points when macro headwinds are clearing but prices haven't fully recovered
→ Risk Management Overlay : Treat Weakening phase transitions as early warning systems to tighten stop losses, reduce position sizes, or hedge existing positions before full Risk-Off conditions develop
→ Sector Rotation Strategy : During Risk-On periods, favor cyclical sectors (technology, consumer discretionary, financials) while Risk-Off phases favor defensive sectors (utilities, consumer staples, healthcare)
→ Multi-Timeframe Confluence : Use daily matrix readings for strategic positioning while applying your regular technical analysis on lower timeframes for precise entry and exit execution
→ Divergence Detection : Watch for situations where your asset shows bullish technical patterns while the matrix shows Risk-Off conditions—these often provide the highest probability short opportunities and vice versa
[DEM] % Off High % Off High calculates and plots the percentage difference between the current closing price and the all-time high of the given ticker observed since the indicator started calculating. It is displayed as a percentage, formatted with two decimal places.
Key Metrics Dashboard (Float, MCap, ATR) (ValueRay)This dashboard displays critical fundamental and volatility data, saving you from switching screens. It’s perfect for traders who need to quickly assess a stock's character, risk profile, and potential before making a move.
📊 Metrics Included
- Market Cap (MCap): Quickly gauge company size.
- Float: See tradable shares (color-coded for low-float stocks).
- Short %: Measure bearish sentiment and short-squeeze potential (color-coded).
- ATR % & ADR %: Understand true volatility to manage risk.
🚀 Key Features
- Fully Customizable: Toggle any metric on/off to create your ideal view.
- Flexible Layout: Choose your preferred on-chart position, size, and layout (horizontal or vertical).
- Lightweight & Clean: Get essential data without cluttering your chart.
If you find this indicator useful, please give it a Boost (🚀)!
Happy Trading
Fair value - NASDAQ - 1WUS100 true value based on underlying top stocks. It gives you insight into the true trend of the index. Use in combination with other indicators (such as EMA and enter ideally 200-400 ticks below highest imbalance).
Familiarise yourself with it, it's not a magic wand and won't instantly help you unless you know how to use it properly.
TPO[Fixed Range, Anchored, Bars Back]TPO Bars Back, Fixed Range and Anchored
Overview
The TPO Profile (Time Price Opportunity Profile) is a powerful market profile indicator that displays the amount of time price spent at different levels during a specified period. Unlike traditional volume profile indicators that show volume distribution, TPO Profile shows time distribution , providing insights into where price has spent the most time and identifying key support and resistance levels.
Key Advantages Over TradingView's Built-in TPO
Simplified Composite Creation : Automatically creates TPO profiles for any time range without manual split/merge operations
Instant Value Area Calculation : Immediately shows Value Area, POC, VAH, and VAL for your selected period
No Manual Assembly Required : TradingView's native TPO requires you to manually split sessions and merge them to create composites - this indicator does it automatically
Flexible Time Ranges : Create composites for any custom time period (multiple days, weeks, specific events) with a few clicks
Real-time Composite Updates : Anchor mode creates live composites that update as new data arrives
Multiple Composite Analysis : Easily compare different time periods without the tedious manual process
Key Features
Core Functionality
Time-Based Analysis : Shows time spent at each price level rather than volume
Configurable Time Blocks : Use any timeframe for TPO counting (30min, 1H, 4H, etc.)
Multiple Price Levels : Adjustable from 5 to 200 levels for granular analysis
Point of Control (POC) : Automatically identifies the price level with highest time activity
Value Area Calculation : Shows the price range containing 70% (configurable) of time activity
Automatic Composite Generation : Creates multi-session composites without manual intervention
Three Operating Modes
1. Bars Back Mode
Analyzes the last N bars from the current bar
Perfect for recent market activity analysis
Range: 10-500 bars
Use Case : Intraday analysis, recent session review
2. Fixed Range Mode
Analyzes a specific time period between start and end times
Ideal for historical analysis of specific events
Creates perfect composites for multi-day periods
Use Case : Earnings periods, news events, specific trading sessions, weekly/monthly composites
3. Anchor Mode (NEW)
Starts from a specific time and extends to the current bar
Dynamically updates as new bars form
Perfect for building live composites from any starting point
Use Case : Live session monitoring, event-based analysis from a specific point, growing composites
Visual Elements
TPO Bars
Horizontal bars showing time distribution at each price level
Longer bars = more time spent at that level
Color-coded to distinguish Value Area from outlying levels
Point of Control (POC)
Red line marking the price level with highest time activity
Most significant support/resistance level
Configurable line style (Solid/Dashed/Dotted) and width
Value Area High/Low (VAH/VAL)
Green and Orange lines marking the boundaries of the Value Area
Shows the price range containing the specified percentage of time activity
Optional display with customizable line styles
Single Print Detection
Identifies price levels touched by only one time block
Display options: Lines or Boxes
Purple color highlighting these significant levels
Often act as strong support/resistance in future trading
Customization Options
Time Block Configuration
Block Time : Choose timeframe for TPO counting (30min, 1H, 4H, etc.)
Allows analysis at different time granularities
Higher timeframes = broader perspective, Lower timeframes = finer detail
Visual Styling
Line Styles : Solid, Dashed, or Dotted for all line elements
Line Widths : 1-5 pixels for POC, VAH, and VAL lines
Colors : Fully customizable colors for all elements
Transparency : Adjustable transparency for better chart readability
Label Management
Show/Hide Labels : Toggle POC, VAH, VAL labels
Font Sizes : Tiny, Small, Normal, Large, Huge
Label Positioning : 8 different position options relative to lines
Offset Controls : Fine-tune label positioning
Line Extension
Level Offset Right : Controls how far lines extend
Smart extension logic:
Value ≤ 0: Infinite extension (extend.right)
Value ≥ 1: Extends exactly N bars ahead
Trading Applications
Support & Resistance
POC often acts as strong support/resistance
Value Area boundaries provide key levels
Single prints frequently become significant levels
Market Structure Analysis
Identify areas of price acceptance (thick TPO bars)
Spot areas of price rejection (thin TPO bars)
Understand where market participants are comfortable trading
Composite Profile Analysis
Create multi-day, weekly, or monthly composites instantly
Compare different composite periods without manual work
Analyze longer-term price acceptance levels
Build composites around specific events or announcements
Session Analysis
Monitor intraday session development in real-time
Compare different sessions (London, New York, Asia)
Track how profiles change throughout the trading day
Build live composites across multiple sessions
Event Analysis
Use Fixed Range mode for earnings, news events
Use Anchor mode to track price development from specific events
Compare pre/post event price acceptance levels
Create event-based composites automatically
Input Parameters
Mode Selection
Mode : Bars Back | Fixed Range | Anchor
Bars Back : Number of bars to analyze (10-500)
Start Time : Beginning time for Fixed Range and Anchor modes
End Time : Ending time for Fixed Range mode only
Analysis Configuration
Block Time : Timeframe for TPO blocks (e.g., "30" for 30-minute blocks)
TPO Levels : Number of price levels (5-200)
Value Area % : Percentage for Value Area calculation (50-95%)
Display Options
Show POC : Display Point of Control line
Show Value Area : Display Value Area box
Show VAH/VAL Lines : Display Value Area boundary lines
Show Single Prints : Display single print detection
Single Print Style : Lines or Boxes
Styling Controls
Colors : TPO, POC, Value Area, VAH, VAL, Single Print colors
Line Styles : POC, VAH, VAL line styles
Line Widths : POC, VAH, VAL line widths
Labels : Show/hide, font size, position, offset controls
Technical Details
Calculation Method
Divides the price range into equal levels based on TPO Levels setting
For each time block, determines which price levels it crosses
Adds +1 count to each crossed level
Identifies POC as the level with highest count
Calculates Value Area by expanding from POC until target percentage is reached
Performance Considerations
Historical data limited to prevent buffer overflow errors
Smart bounds checking for different timeframes
Optimized cleanup routines to prevent drawing object accumulation
Pine Script Version
Built on Pine Script v6
Uses modern Pine Script best practices
Efficient array handling and drawing object management
Best Practices
Timeframe Selection
Block Time = Chart Timeframe : Traditional TPO approach
Block Time > Chart Timeframe : Smoother, broader perspective
Block Time < Chart Timeframe : More granular, detailed analysis
Level Count Guidelines
Low levels (10-20) : Better for swing trading, major levels
High levels (50-100) : Better for scalping, precise entries
Very high levels (100+) : For very detailed analysis
Mode Selection
Bars Back : Daily analysis, recent activity
Fixed Range : Historical events, specific periods, manual composites
Anchor : Live monitoring, event-based analysis, growing composites
Composite Creation Workflow
Select Fixed Range or Anchor mode
Set your desired start time (and end time for Fixed Range)
Adjust TPO Levels for desired granularity
Enable VAH/VAL lines to see Value Area boundaries
The composite profile generates automatically with all key levels
This indicator eliminates the tedious manual process of creating composite TPO profiles in TradingView. Instead of splitting sessions and manually merging them, you get instant composite analysis with automatic Value Area calculation, POC identification, and single print detection. The combination of time-based analysis, multiple operating modes, and extensive customization options makes it a powerful tool for understanding market structure and price acceptance levels across any time period.
Red Report Filter x 'Bull_Trap_9'Hello Traders!
This one is my favorite.
This is indicator / filter: '2 of 2.'
'1 of 2' is the, 'Closed Market Filter,' I posted before this that you may like.
Again, I prefer 'Filter' over 'Indicator' because this Pine Script code does not interact with the actual price data.
It makes handling high impact reports effortless.
As you all know; if you're on a Prop and breach a 'Red,' you lose your account.
This will filter up to 5 reports. More than enough unless you're on EURUSD!
It offers both 'Red' and 'Orange' report control.
The default window times of 15 / 6 are programmed for red events. You can always alter the base code for your desired, 'Before / After.'
Click the tooltip for more info.
How to use:
You do need to update the inputs daily with the current report times before each open.
I trade YM / US markets. Those reports are very repetitive on their delivery times, so I usually leave a 10:00 setting in slot 1. I then toggle it 'On' or 'Off' per demand.
Just open the dialogue box and it is pretty self explanatory.
I used task scheduler for a lot of years, but that wasn't very reliable, modest work to set up daily and a lot of times I may not hear it or it malfunctions because of a Windows update.
TradingView has the little icon that floats from the bottom right, but who really looks for that.
Any audio alert is subject to fail for a number of reasons.
This filter REDS the screen in your face. Leaves no doubt about what's coming.
I know there may be other apps and options out there, but this filter is integral to the TradingView chart itself embedded through Pine Script. It is right there, a click away, easy to input data, and as long as your chart is active and working, the filter will fire.
I did not build an alert condition into this, but I'm sure that could be an option if you want to program in audio as well.
Please Note: Only when the price candles push into the filter zone, will the filter start to display. Run a test a minute from the current price candle and you can see how it functions.
I appreciate your interest.
Closed Market / Back-Test Filter x 'Bull_Trap_9'Hello TradingView Traders!
This is a very valuable tool that I believe all traders will find useful.
This indicator / filter is '1 of 2'. I prefer it as a filter because it is not meant for live trade analysis. It is designed to make a trader aware of their individual trade sessions and to help aid in static chart candlestick back-testing.
Also, look for my indicator / filter, '2 of 2': 'Red Report Filter'
There are two functions to this filter.
Primary use: It allows a trader to set a session window: Open / Close.
During a trade session, like YM, I only trade 9:30 - 15:00. Without the filter, many times I have traded past my cutoff because I was focused on the chart and not the time.
With this filter on as close nears with an open trade and the filter starts to apply, I know I am at session close with no more trades upon exit. Otherwise, I know the session is done with no further trades.
It is also nice to have the filter on during the session open as a demarcation boundary.
Secondary use: It is used as a chart back-test tool.
When applied to a traders back-test chart, the trader can control their trade session envelopes for easier and more precise evaluation. The filter will allow only the candles per session that the trader wants to focus on and will filter all other non-session candles.
I can easily compare a whole week of 30m session data, concentrating solely on the filtered trade windows.
Please Note: The filter will be active as far back as the historic data prints.
Thanks for viewing!
Pristine Fundamental AnalysisThe Pristine Fundamental Analysis indicator enables users to perform comprehensive fundamental stock analysis in a fraction of the time! 🏆
For swing/position traders, fundamental analysis is essential—it informs stock selection and strengthens conviction, enabling traders to stay in positions long enough to capture larger moves. Since every ticker represents both a business and a tradable asset, fundamental analysis perfectly complements technical analysis.
💠 Fundamental Analysis Insights - Weekly Timeframe
EPS & sales trends, margins & ratios, and valuation metrics are displayed on the weekly timeframe for in-depth analysis outside market hours.
💠 Fundamental Analysis Insights - Daily Timeframe
A slimmed down version of the fundamental analysis table is displayed on the daily timeframe to provide users quick insights into the fundamentals, while allowing them to focus on technical analysis during market hours.
💠 Fundamental Analysis Metrics to Deepen Understanding of Companies!
EARNINGS & SALES TRENDS
Why does it matter? Company stock prices tend to track the growth trajectory of earnings and sales over time. By analyzing fundamentals, users can gain an edge that pure technical traders do not have. This edge is most pronounced during big market dislocations when investors are forced to liquidate their top holdings.
▪ EPS - Measures year-over-year growth, quarter-over-quarter growth, and the surprise between actuals & analyst estimates
▪ Sales Analysis - Measures year-over-year growth, quarter-over-quarter growth, and the surprise between actuals & analyst estimates
MARGIN ANALYSIS
Why does it matter? Revenue is the lifeblood of a company. Margins measure company profits and expenditures as a percentage of revenue
▪ G% - Gross margin measures the percentage of revenue a company retained after subtracting the direct costs of producing the goods or services it sells, known as the cost of goods sold (COGS)
▪ CFO% - Measures the percentage of a company's revenue that was converted to Cash flow from operations (CFO). CFO, also known as operating cash flow (OCF), is the amount of cash a company generated from its core business activities over a specific period. It reflects the actual cash inflows and outflows resulting from the company’s main operations, such as selling products or providing services, and excludes cash flows from investing and financing activities.
▪ Net% - Net margin measures the percentage of revenue that was converted to net profit
▪ ROE% - Return on Equity measures how much net income a company produced for each dollar of equity invested by shareholders
▪ R&D% - R&D margin measures how much the company invested in research & development as a percentage of revenue
▪ D/E - The Debt to Equity ratio measures how much of a company’s financing comes from creditors (debt) versus owners (equity), providing insight into the company’s financial leverage and risk profile. The indicator tracks changes in the ratio over time
VALUATION METRICS
Why does it matter? Valuation metrics provide users an understanding of the potential risk if the fundamental trajectory of the company, or the broad market, changes! The more highly valued a company is, the more downside risk is present if conditions worsen, and vice versa.
▪ PE - The Price-to-Earnings ratio measures a company’s current share price relative to its trailing twelve-month(TTM) earnings per share (EPS). It helps investors assess how much they are paying for each dollar of a company’s earnings and is often used to gauge whether a stock is overvalued, undervalued, or fairly valued compared to its peers or historical averages.
▪ PS - The Price-to-Sales ratio measures a company’s current share price relative to its trailing twelve-month(TTM) sales per share. It helps investors assess how much they are paying for each dollar of a company’s sales and is often used to gauge whether a stock is overvalued, undervalued, or fairly valued compared to its peers or historical averages.
▪ BB% - Buyback yield measures the annual percentage of stock repurchased by the company. Share buybacks reduce total share count, which directly increases earnings per share!
💠 What Makes This Indicator Unique
There are many fundamental dashboards, however, what makes this indicator unique is customized metrics that were used to achieve back-to-back top finishes in the US Investing Championship. The main purpose of the indicator is to highlight companies with a history of EPS and sales acceleration , rather than focusing on the values in isolation, or even the growth of the values. Our goal is further evolution of the metrics and color signals based on continued backtesting and analysis of real-time market data.
▪ Custom Margin Metrics : Several of the margin metrics are unique and offer significant value beyond EPS and sales data alone.
For example, there are plenty of companies that have negative EPS due to non-cash expenses and/or investments they are making into their business, but that does not by itself mean that the companies are not worthy of an investment. Roblox (RBLX) is a great example. The company has consistently negative EPS, but the CFO% margin is positive! That means the core business throws off significant amounts of cash, and a large amount of it is being allocated to aggressive R&D spend, which is captured by the R&D% metric. This could propel the fundamentals of the business well into the future.
▪ Color Signals Based on Thresholds : The background colors of metrics are based on historical analysis and apply relevant thresholds to help users identify companies with strong fundamentals
▪ Comprehensive Inline Documentation : All headers cells offer detailed information about the relevant calculations/metrics as well as in-depth information on color coding and how to interpret each value. This small, yet important detail, allows users to quickly identify accelerating fundamental trends
💠 Practical Use Case Examples
Analyzing fundamentals to trade a Power Earnings Gap setup 👇
In August 2023, APP reported a +467% YoY increase in EPS, 181% higher than Wall Street estimates! This sparked a generational trading opportunity.👇
After the first earnings report with stellar earnings growth, APP rallied > 1000% in 2 years, following the trajectory of sales and EPS.👇
💠 Settings and Preferences
💠 Tips and Tricks
Fundamentals drive price action during periods of fundamental transition
▪ Pre-revenue companies that are anticipated to start earning revenue
▪ Revenue-generating companies that are anticipated to flip from negative to positive EPS
▪ Revenue-generating companies that are anticipated to flip from negative cash flow to positive cash flow
▪ Major accelerations or decelerations in sales or EPS
Visual SL/TP con ATR + Pips/TicksThis indicator automatically displays the current ATR size along with suggested SL (Stop Loss) and TP (Take Profit) values, expressed in key units such as pips and ticks.
✅ Compatible with:
Forex (e.g., EURUSD)
Indices (e.g., NAS100, US30)
Gold (XAUUSD)
Cryptocurrencies (e.g., XRPUSDT)
🎯 Ideal for scalping, intraday, or swing trading.
🧠 Saves calculation time and improves trading speed.
Includes:
Automatic SL/TP calculation based on ATR multiples
Conversion to pips and ticks for quick reading
Dynamic support for different instrument types
📌 Tip: Use this indicator alongside your entry strategy with EMAs or volume for more precise trading.
EPS and Sales Magic Indicator V2EPS and Sales Magic Indicator V2
EPS and Sales Magic Indicator V2
Short Title: EPS V2
Author: Trading_Tomm
Platform: TradingView (Pine Script v6)
License: Free for public use under fair usage guidelines
Overview
The EPS and Sales Magic Indicator V2 is a powerful stock fundamental visualization tool built specifically for TradingView users who wish to incorporate earnings intelligence directly onto their price chart. Designed and developed by Trading_Tomm, this upgraded version of the original 'EPS and Sales Magic Indicator' includes an enriched and more insightful presentation of company performance metrics — now with TTM EPS support, advanced color-coding, label sizing, and refined control options.
This indicator is tailored for retail traders, swing investors, and long-term fundamental analysts who need to view Quarter-over-Quarter (QoQ) earnings and revenue changes directly on the price chart without switching tabs or breaking focus.
What Does It Display?
The EPS and Sales Magic Indicator V2 intelligently detects quarterly financial updates and displays the following data points via labels:
1. EPS (Earnings Per Share) – Current Quarterly Value
This is the most recent Diluted EPS published by the company, fetched using TradingView’s request.financial() function.
Displayed in the format: EPS: ₹20.45
2. EPS QoQ Percentage Change
Shows the percentage change in EPS compared to the previous quarter.
Highlights improvement or decline using arrows (up for improvement, down for decline).
Displayed in the format: EPS: ₹20.45 (up 15.3 percent)
3. Sales (Revenue) – Current Quarterly Value
Fetches and displays Total Revenue of the company in ₹Crores for easier Indian-market readability.
Displayed in the format: Sales: ₹460Cr
4. Sales QoQ Percentage Change
Measures and presents the quarter-over-quarter percentage change in total revenue.
Uses arrows to indicate growth or contraction.
Displayed in the format: Sales: ₹460Cr (down 3.8 percent)
5. EPS TTM (Trailing Twelve Months)
You now get the TTM EPS — the sum of the last four quarterly EPS values.
This value provides a better long-term earnings snapshot compared to a single quarter.
Displayed in the format: TTM EPS: ₹78.12
All of these values are automatically calculated and displayed only on the bars where a new financial report is detected, keeping your chart clean and insightful.
Customization Features
This indicator is built with user control in mind, allowing you to personalize how and what you want to see:
Show EPS in Label: Enable or disable the display of EPS and EPS QoQ values.
Show Sales in Label: Toggle the visibility of revenue and sales change percentage.
Color Options for Label Themes: The label background color is automatically determined based on performance.
Green: Both EPS and Sales increased QoQ.
Red: Both decreased.
Orange: One increased and the other decreased.
Gray: Default color (if values are unavailable or mixed).
Label Text Size: Choose from Tiny, Small (default), or Normal.
Visual Design
Placement: The labels are positioned just below the candlesticks using yloc.belowbar, so they do not obstruct price action or interfere with technical indicators.
Anchor: Aligned precisely with the financial reporting bars to maintain clarity in historical comparisons.
Background Style: Clean, semi-transparent styling with soft text colors for comfortable viewing.
How It Works
The indicator relies on TradingView’s powerful request.financial() function to extract fiscal quarterly financials (FQ). Internally, it uses detection logic to identify fresh data updates by comparing current vs. previous values, arithmetic to compute QoQ percentage changes in EPS and Sales, logic to build formatted labels dynamically based on user selections, and conditional color and sizing logic to enhance interpretability.
Use Cases
For Long-Term Investors: Quickly identify if a company’s profitability and revenue are improving over time.
For Swing Traders: Combine recent earnings trends with price action to evaluate if post-result momentum has real backing.
For Technical and Fundamental Traders: Layer it with moving averages, RSI, or volume to create a hybrid analysis environment.
Limitations and Notes
Financial data is provided by TradingView’s financial API, and occasional missing values may occur for less-covered stocks.
This tool does not repaint but depends on the timing of the official financial updates.
All values are rounded and formatted to prioritize readability.
Works best on Daily or higher timeframes (weekly or monthly also supported).
License and Fair Use
This script is free to use and share under TradingView’s open-use guidelines. You may copy, fork, and build upon this indicator for personal or educational purposes, but commercial usage requires attribution to the author: Trading_Tomm.
Future Enhancements (Planned)
Addition of Net Profit (QoQ and TTM)
Inclusion of Operating Margin, Profit Margin, and Book Value
Option to switch between numeric and graphical display (table mode)
Alerts on extreme earnings deviation or sales slumps
Final Thoughts
The EPS and Sales Magic Indicator V2 represents a clean, visual, and smart way to monitor a company’s core performance from your chart screen. It helps you align fundamental strength with technical strategies and provides instant financial clarity, which is especially vital in today’s fast-moving markets.
Whether you’re preparing for an earnings season or scanning past performance to pick your next investment, this indicator saves time, enhances insights, and sharpens decisions.
Live SPX Buy/Sell Zones (Simulated)This is a indactor that best indicates whats happening with buyers and sellers
Algorithmic ScalperAlgorithmic Scalper — Adaptive Trend-Cycle Trading System
Overview
Algorithmic Scalper is an advanced trend detection and signal generation tool designed for scalpers and intraday traders. Its primary goal is to help traders spot and confirm high-probability trend entries with precision. By combining a multi-layer trend detection engine, an ATR-driven trend structure, and EMA trend clustering, it delivers clear LONG, SHORT, OOT LONG (early countertrend long), and OOT SHORT (early countertrend short) signals that can be acted upon within a structured trading framework.
What It Does
Algorithmic Scalper analyzes price action across four core dimensions:
1. Trend Detection — Identifies the dominant trend using a 4-EMA trend cluster (customizable values: 20, 50, 100, 200), which provides the foundation for trend classification and signal labeling.
2. Cycle Timing — Uses a proprietary trend-cycle engine inspired by the Schaff trend approach. This engine applies smoothing and filtering across four internal phases to adapt to market shifts, making trend-confirmation significantly more robust compared to traditional RSI or Stoch-style indicators.
3. ATR Barrier Framework — Constructs a dynamic ATR-based trend zone, similar to advanced ATR trailing methods. This zone adjusts itself in real-time based on market volatility, allowing precise breakout detection and trend adherence.
4. Momentum Validation — Incorporates a MACD-style momentum measure (differential EMA + signal line) that confirms trend strength and trend changes.
5. Signal Alert - Supports built‑in alerts, allowing traders to be notified instantly when a new signal is triggered, so they can stay engaged with the market even when away from the screen.
How It Works
The indicator uses the interplay between these elements to classify price action into one of four actionable states:
1. LONG: Strong trend-confirmation signal aligning trend, momentum, and ATR structure.
2. SHORT: Strong trend-confirmation signal for downside movement.
3. OOT LONG: Early warning for a countertrend long entry when price is stretched away from the trend zone, ideal for reversal or scalp strategies.
4. OOT SHORT: Early warning for a countertrend short entry when price is extended to the upside.
Result: Each signal is calculated only when trend, trend-cycle, momentum, and ATR align, making the entries highly selective and aligned with market structure.
How To Use It
1. Confirm the Context: Always assess the signal within the current market structure. Use higher timeframes to confirm trend direction and strength.
2. Act According to the Signal Type:
-- LONG / SHORT: Enter trend-following positions when trend and momentum align. These signals are ideal for breakout or trend-confirmation trades.
-- OOT LONG / OOT SHORT: Enter countertrend positions when price is extended from its trend zone and confirmed by trend-cycle shifts. These are higher risk and require tighter risk controls.
Why It Is Unique
1. Integrates trend detection, trend-cycling, ATR trend structure, and MACD-style momentum into a single streamlined tool.
2. Goes beyond simple EMA ribbons by adding adaptive trend-cycle filtering for higher precision trend detection.
3. Provides four clearly classified signal types for both trend and countertrend setups.
4. Enables traders to clearly understand the market state, making it ideal for both breakout/trend and reversal strategies.
Apply Risk Management
Never use signals in isolation. Maintain a pre-defined risk/reward ratio, utilize stop losses, and adapt position sizes according to market volatility and personal risk tolerance.
Timeframe Selection
The indicator is optimized for 5-minute and 15-minute charts, making it ideal for scalping and active intraday strategies.
Best Suited For
Scalpers, intraday traders, and active market participants.
Important Notes
The signals generated by Algorithmic Scalper are meant to support decision-making. They should always be used in conjunction with sound trading knowledge, risk management practices, and personal market analysis.
The indicator does not guarantee outcomes and should not be treated as a standalone buy/sell tool. Its value lies in providing actionable trend context, allowing traders to make confident decisions.
This tool is built to evolve as market dynamics evolve, making it a robust long-term addition to any trading toolkit.
License
This indicator was developed by the ProphetAlgoAI team. Its use is restricted to TradingView under a private, invite-only agreement. Redistribution or use outside TradingView is strictly prohibited unless explicitly authorized by the ProphetAlgoAI team.
Bid/Ask Volume Tension with Rolling Avg📊 Bid/Ask Volume Tension with Rolling Average
This indicator is designed to help traders identify pivotal moments of buildup, exhaustion, or imbalance in the market by calculating the tension between buy and sell volume.
🔍 How It Works:
Buy volume is approximated when the candle closes higher than or equal to its open.
Sell volume is approximated when the candle closes below its open.
Both are smoothed using an EMA (Exponential Moving Average) for noise reduction.
Tension is calculated as the absolute difference between smoothed buy and sell volume.
A rolling average of tension shows the baseline for normal behavior.
When instant tension rises significantly above the rolling average, it often signals:
A build-up before a large move
Aggressive order flow imbalances
Potential reversals or breakouts
🧠 How to Use:
Watch the orange line (instant tension) for spikes above the aqua line (rolling average).
Purple background highlights show when tension exceeds a customizable multiple of the average — a potential setup zone.
Use this indicator alongside:
Price action (candlestick structure)
Support/resistance
Liquidity zones or order blocks
⚙️ Settings:
Smoothing Length: Controls the responsiveness of buy/sell volume smoothing.
Rolling Avg Window: Defines the lookback period for the baseline tension.
Buildup Threshold: Triggers highlight zones when tension exceeds this multiple of the average.
🧪 Best For:
Spotting pre-breakout tension
Detecting volume-based divergences
Confirming order flow imbalances
HTF Box Range Overlay - FIXEDThis script overlays higher timeframe candles (e.g. 4H) onto lower timeframe charts (e.g. 5min), showing both the body and wick ranges of the last N HTF candles.
Features:
✔ Displays both candle body and wick as separate shaded boxes
✔ Fully customizable for bullish/bearish colors and wick appearance
✔ Supports any higher timeframe (15m, 1H, 4H, 1D, etc.)
✔ Clean overlay with no performance lag
✔ Automatically adjusts in real-time as new candles form
Great for traders using HTF zones, supply/demand, or structure-based confluence. Works best when used on intraday charts.
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.
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
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.
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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.