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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
Pine Script® göstergesi
QuantAlgo tarafından
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
Pine Script® göstergesi
derMatzeImNetz tarafından
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.
Pine Script® göstergesi
mindyourbuisness tarafından
16
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.
Pine Script® göstergesi
Bull_Trap_9 tarafından
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!
Pine Script® göstergesi
Bull_Trap_9 tarafından
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
Pine Script® göstergesi
pristinecap tarafından
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.
Pine Script® göstergesi
Trading_Tomm tarafından
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
Pine Script® göstergesi
JasonHyde tarafından
1
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.
Pine Script® göstergesi
bayfxakif tarafından
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.
Pine Script® göstergesi
Almureqeeb tarafından
61
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
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1
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.
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controllinghand tarafından
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.
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Dshergill tarafından
2
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
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controllinghand tarafından
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. --- 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
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EdgeTools tarafından
4
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.
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LabOfCrypto tarafından
1
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.
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The_Forex_Steward tarafından
1
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.
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controllinghand tarafından
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.
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lemniscuss tarafından
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.
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yelober tarafından
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.
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yelober tarafından
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