Golden Ears Finance was designed with a singular purpose: to automatically discover trending stocks by analyzing global RSS news feeds. The software extracts stock tickers mentioned in financial news across 116 sources from 8 regions worldwide (110 RSS, 5 Atom, 1 API), surfacing opportunities based on real market momentum and media attention.
Adding stocks manually (through share targets, direct input, or other means) will dilute the original intent of Golden Ears Finance. The power of this platform lies in its ability to identify stocks that are organically trending in financial news.
Manually introduced stocks:
Recommendation: Use manual stock additions sparingly and rely primarily on the RSS-driven trending analysis for best results.
The trending ticker bar automatically identifies and highlights Exchange-Traded Funds (ETFs) mentioned in financial news, distinguishing them from individual stocks.
The system recognizes 58 popular ETFs and displays a blue ETF badge next to their ticker symbols in the trending bar.
Click on any ETF ticker to open the modal and see its full name (e.g., "SPDR S&P 500 ETF Trust" for SPY).
ETF badges use a distinctive blue gradient to help you quickly differentiate between ETFs and individual stocks.
ETFs can be analyzed just like stocks - click to view stats, run AI analysis, or add to your watchlists.
Clicking any trending ticker opens a detailed popup with live financial data from Yahoo Finance:
Current trailing EPS showing company profitability per outstanding share.
Analyst-estimated future EPS for the next fiscal year.
The stock's highest and lowest prices over the past year, showing price volatility.
Analyst consensus 1-year price target with upside/downside percentage from current price.
Current and forward P/E ratios for valuation assessment.
Company market capitalization and industry sector classification.
SPY, QQQ, IWM, VTI, VOO, IVV, DIA, VT, VEA, VWO
XLF, XLE, XLK, XLV, XLI, XLP, XLY, XLU, XLB, XLRE, XLC
TLT, BND, HYG, LQD, TIP, SHY, IEF, AGG
GLD, SLV, USO, GDX, GDXJ
TQQQ, SQQQ, SPXU, UPRO, UVXY, SOXL, SOXS, LABU, LABD
ARKK, ARKG, SMH, SOXX, XBI, IBB, VNQ, SCHD, JEPI, JEPQ
Each article in the news feed displays rich metadata extracted from RSS sources to help you quickly assess content relevance and credibility.
When available, the article author's name is displayed in the footer alongside the source and publication date. This helps identify content from trusted analysts or journalists you follow.
Articles may display up to 5 topic tags as small badges above the footer. Tags are extracted directly from RSS feeds and can include categories like sectors, asset classes, or themes (e.g., "Technology", "Earnings", "Fed").
Every article shows its source publication and relative timestamp (e.g., "2 hours ago") so you can prioritize recent news from preferred sources.
The system automatically identifies stock tickers mentioned in article titles and summaries, making it easy to track which companies are in the news.
Not all RSS feeds provide author names or tags. The display adapts automatically—if metadata is unavailable, those fields simply won't appear. Major financial sources like Reuters, Bloomberg, and Seeking Alpha typically include rich metadata.
The narrative engine uses regional weighting to provide more accurate market intelligence by considering the geographic origin of news sources.
| US | United States | Weight: 1.0 | |
| Europe | European Union & UK | Weight: 0.9 | |
| Asia | China, Japan, India, HK | Weight: 0.85 | |
| Global | Multi-regional sources | Weight: 0.8 | |
| MiddleEast | Gulf States, Israel, etc. | Weight: 0.75 | |
| Oceania | Australia, New Zealand | Weight: 0.7 | |
| LatAm | Latin America | Weight: 0.6 | |
| Africa | African continent | Weight: 0.5 |
Each narrative's strength score includes a regional coverage bonus (up to 15 points). Multi-region coverage increases the score.
Visualize which regions are driving specific narratives. Higher weights indicate more market-moving potential.
AI analysis considers regional context when generating narrative summaries and predictions.
Track how narratives spread across regions over time for better trend analysis.
This feature requires an OpenAI and/or Grok API key to generate AI confidence scores and summaries. Configure your API keys in Account > API Keys.
End-of-day AI-generated top stock picks that combine multiple data signals into a composite "Super AI Score". Found under Watchlists > Super AI Picks.
Super AI Picks uses existing data from other modules. No additional API key is needed, though better results come from having AI analysis data from OpenAI/Grok enabled.
The Super AI Score combines 7 weighted components:
Based on news mentions and source diversity from all 116 feeds in the last 24 hours. Higher scores mean more media attention.
Participation in active market narratives. Stocks appearing in multiple strong narratives score higher.
Derivative Impact Score measuring options, dark pool, and institutional activity.
Institutional ETF exposure based on how many ETFs hold the stock and total weight across all ETF holdings.
Consensus from dual AI analysis (OpenAI + Grok valuation opinions).
Economic environment factor from FRED data including GDP, unemployment, inflation, and interest rates.
Extra points for stocks with exposure to TSP funds or Emerging Markets (not part of weight distribution).
| Profile | Weights | Min Score | Best For |
|---|---|---|---|
| Conservative | 32% AI, 20% DIS, 16% Narrative, 12% Macro, 10% Trend, 10% ETF | 75 | Higher confidence, AI-validated picks |
| Aggressive | 25% Trend, 23% AI, 20% Narrative, 12% Macro, 12% DIS, 8% ETF | 65 | Momentum-oriented, higher risk picks |
| Custom | User-defined weights (must total 100%) | User-defined | Personalized strategy based on your investment style |
Create your own scoring formula with the Custom profile:
Quick access to common configurations: AI Heavy (50% AI), Trend Heavy (35% Trend), Balanced (16% each), Macro Focus (32% Macro), DIS Focus (32% DIS), and ETF Focus (28% ETF).
Fine-tune each component weight using sliders. Real-time validation ensures weights total exactly 100%.
Set your own minimum score threshold and bonus cap to control which stocks qualify for your picks.
Your custom weights are saved locally and persist between sessions. Click "Save & Apply" then "Generate Now" to use them.
Super AI Picks are regenerated automatically every 2 hours. You can also click "Generate Now" to trigger an immediate refresh with your current profile settings.
AI-powered market intelligence module that tracks narratives across 15 emerging market regions. Found under Watchlists > EM Spotlight.
This feature requires an OpenAI and/or Grok API key for dual AI analysis. Both keys are recommended for consensus scoring. Configure your API keys in Account > API Keys.
| Brazil | Bovespa, Petrobras, Vale, Real currency | LatAm feeds |
| Argentina | Merval, Buenos Aires, YPF, Peso | LatAm feeds |
| Mexico | Bolsa, IPC Index, Peso, FEMSA | LatAm feeds |
| India | Sensex, Nifty, BSE, NSE, Rupee | Asia feeds |
| South Africa | JSE, Johannesburg, Rand, Naspers | Africa feeds |
| Nigeria | NGX, Lagos, Naira, Dangote | Africa feeds |
| Egypt | EGX, Cairo, Egyptian Pound | Africa/MiddleEast feeds |
| China | Shanghai, Shenzhen, CSI, Hang Seng, Yuan | Asia feeds |
| Indonesia | IDX, Jakarta, Rupiah | Asia feeds |
| Thailand | SET, Bangkok, Baht | Asia feeds |
| Vietnam | Ho Chi Minh, VN-Index, Dong | Asia feeds |
| Turkey | BIST, Istanbul, Lira | Europe/MiddleEast feeds |
| Poland | WSE, Warsaw, Zloty | Europe feeds |
| Middle East | Gulf, Dubai, Saudi, Tadawul, Abu Dhabi | MiddleEast feeds |
| APAC | Asia-Pacific, ASEAN, Pacific Rim | Asia + Oceania feeds |
Both OpenAI and Grok analyze region-specific news and generate consensus narratives with confidence scores.
Each region has specific keywords (indices, currencies, major companies) to identify relevant articles from RSS feeds.
AI generates sentiment (bullish/bearish/neutral), market outlook, and risk level for each region.
Automatically extracts mentioned stock tickers from articles for quick watchlist additions.
Background scans run every 2 hours to keep narratives fresh. Manual scans can be triggered anytime.
These feeds are exclusively used by the EM Spotlight module and are not included in general narrative scanning:
Real-time SEC filing tracking and analysis. Found under Tools > SEC Filings.
AI-generated filing summaries require an OpenAI or Grok API key. Basic filing data is available without API keys. Configure your API keys in Account > API Keys.
Material events requiring immediate disclosure - mergers, acquisitions, leadership changes, material agreements.
Comprehensive annual financial reports with audited statements, business overview, and risk factors.
Quarterly financial statements and management discussion of financial condition.
Insider transactions - purchases, sales, and option exercises by company insiders.
Quarterly reports of institutional investment managers with $100M+ in assets.
Securities registration statements for IPOs and secondary offerings.
Monitor dark pool trading activity and institutional order flow. Found under Tools > Dark Pool.
Off-exchange trading volume as percentage of total volume - high percentages may indicate institutional accumulation.
Large block transactions (10,000+ shares) that bypass public exchanges.
Buy vs sell pressure in dark pools - positive indicates accumulation, negative indicates distribution.
Automated detection of abnormal dark pool activity spikes relative to historical averages.
Dark pool data feeds directly into the Squeeze Score calculation, with high dark pool activity contributing to the overall squeeze potential rating.
Federal Reserve Economic Data (FRED) integration for macro indicators. Found under Tools > Macro/FRED.
AI analysis of macro trends and market implications requires an OpenAI or Grok API key. Chart and data display works without API keys. Configure your API keys in Account > API Keys.
Federal Funds Rate, Treasury yields (2Y, 10Y, 30Y), yield curve analysis.
CPI, PCE, PPI - core and headline inflation tracking with historical trends.
Unemployment rate, nonfarm payrolls, jobless claims, labor force participation.
Real GDP growth, industrial production, consumer spending, housing starts.
Comprehensive earnings calendar with AI-powered impact analysis. Found under Tools > Earnings.
AI-powered impact predictions and earnings analysis require an OpenAI or Grok API key. Calendar and basic earnings data are available without API keys. Configure your API keys in Account > API Keys.
Upcoming earnings dates with expected EPS, revenue estimates, and historical beat/miss records.
Pre-earnings AI analysis predicting potential market reaction (bullish/bearish/neutral).
Track earnings surprises - magnitude of beats/misses and subsequent price movements.
Visual overview of earnings performance by sector and market cap.
AI-powered social sentiment analysis from Reddit financial communities. Integrated throughout the platform.
Sentiment classification (bullish/bearish/neutral) requires an OpenAI or Grok API key. Basic mention counts and velocity are available without API keys. Configure your API keys in Account > API Keys.
Aggregates mentions from r/wallstreetbets, r/stocks, r/investing, r/options, r/SecurityAnalysis, and r/StockMarket.
Tracks how quickly a stock's mentions are increasing - spikes indicate emerging interest.
AI classifies each mention as bullish, bearish, or neutral based on context.
Combined score based on mention volume, velocity, sentiment, and source diversity.
Comprehensive ETF analytics with holdings data and constituent analysis. Found under Watchlists > ETF Intelligence.
Each ETF displays a temperature badge indicating current activity level:
ETF has strong momentum (change > 2%) or good gains combined with high trading volume relative to average.
ETF is positive or has above-average trading activity. Moderate opportunity indicator.
ETF is negative or has below-average volume. Lower activity level.
Complete list of holdings for 35+ tracked ETFs with weight percentages and sector allocation.
Compare any two ETFs to see shared holdings and understand diversification or concentration.
For any stock, see which ETFs hold it and at what weight - useful for understanding institutional ownership.
HHI index and top 10 weight metrics to assess ETF concentration risk.
View the most common stocks held across all tracked ETFs to identify market consensus positions.
Research view organizing 100+ ETFs by their issuing institution. Click "Load Institutions" to see 17 major ETF issuers with AUM and market share data:
BlackRock (iShares), Vanguard, State Street (SPDR), Invesco, Schwab, JPMorgan, ARK Invest, VanEck, and more.
Each issuer shows assets under management and their share of the US ETF market.
Click any issuer card to expand and see all ETFs they manage. Click any ETF to view details.
Only loads on demand - click the button to fetch data without slowing down page navigation.
Real-time expense ratio data for 80+ ETFs showing annual costs. Color-coded tiers help identify low-cost options:
Holdings data syncs daily via background scheduler to ensure current information.
Real-time capital flow detection using 10 ETF pair comparisons to identify market sentiment shifts. Found under Watchlists > ETF Intelligence.
The system compares pairs of ETFs that represent opposing market themes. When one ETF significantly outperforms its pair, it signals capital rotation and changing investor sentiment.
| Risk-On | Green signals | Capital flowing into growth, tech, and aggressive assets |
| Risk-Off | Red signals | Capital flowing into bonds, gold, and defensive assets |
| Neutral | No significant spread | No clear directional bias in the market |
| XLK vs XLF | Tech vs Financials | Growth vs value sector preference |
| XLE vs SPY | Energy Decoupling | Commodity strength vs broad market |
| XLY vs XLP | Consumer Sentiment | Discretionary vs staples = confidence level |
| QQQ vs IWM | Large vs Small Cap | Flight to quality vs economic optimism |
| TLT vs SPY | Bonds vs Stocks | Risk-off safety vs risk-on equities |
| GLD vs SPY | Gold vs Stocks | Safe haven demand vs confidence |
| VWO vs VEA | EM vs Developed | Emerging market momentum vs stability |
| XLV vs XLK | Defensive vs Growth | Healthcare safety vs tech growth appetite |
| SMH vs XLK | Semis vs Tech | Semiconductor strength, AI momentum |
| KRE vs XLF | Regional vs Major Banks | Regional bank health vs flight to quality |
Intelligent tagging system for organizing and filtering your stock watchlists.
Momentum, Value, Growth, Dividend, Swing Trade, Day Trade, Long-term Hold
High Risk, Moderate Risk, Low Risk, Speculative, Blue Chip
AI Discovered, RSS Trending, Squeeze Candidate, SEC Alert, Earnings Play
Create your own tags for personalized organization.
Enhanced short squeeze detection with integrated real-time signals. Found under Tools > Squeeze Scanner.
AI-powered squeeze discovery from RSS feeds requires an OpenAI or Grok API key. Squeeze Score calculations and data display work without API keys. Configure your API keys in Account > API Keys.
Real dark pool data integration - high activity suggests institutional interest.
Percentage of float sold short - higher indicates more squeeze potential.
Cost to borrow shares - elevated fees indicate supply constraint.
Call/put ratio and unusual options activity signaling directional bets.
Integrated Social Interest Score from Reddit feeds.
Rate of price change indicating momentum building.
Runs OpenAI and Grok in parallel simultaneously. Shows side-by-side results and highlights consensus picks where both AIs agree - higher confidence candidates.
Scan RSS feeds using OpenAI GPT-4o for squeeze candidate identification.
Scan RSS feeds using xAI's Grok for alternative AI perspective on squeeze candidates.
Dual scan highlights tickers found by both AIs with averaged confidence scores for higher conviction plays.
Trailing 12-month earnings per share. Positive shown in green, negative in red.
Visual progress bar showing current price position within 52-week low-high range. Hover for exact values.
Analyst consensus target price with upside/downside percentage vs current price.
Measures derivative market pressure (0-100) based on options activity and institutional flows.
AI-generated market intelligence report built from live GEF data. Operates in two modes: Classic (6 narrative sections) and Matrix Intelligence (reliability-scored signal table with dual-AI comparison). Found under Dashboard > Daily Briefing. Requires POWER_USER subscription or higher.
Generation uses OpenAI (gpt-4o-mini), Grok (grok-3), and Gemini (gemini-2.5-flash) in parallel. Both OpenAI and Grok run simultaneously for consensus analysis. Gemini provides a third-tier fallback. Configure API keys in Account > API Keys if needed.
Broad market environment, current session status (pre-market / open / after-hours / closed), and macro backdrop for the day.
Notable price movers and catalyst context outside regular trading hours, sourced from AfterHoursSnapshot data.
Institutional dark pool signals — tickers with volume ratios above 30% over a 90-day lookback window.
Buy/sell pressure inferred from sector themes, narrative strength, and active market signals across all GEF data sources.
High-impact tail risks, black swan signals, and edge-case opportunities from geopolitics clusters and emerging market data.
Actionable bullet-point summary of the most important signals for traders to investigate further — never a trade recommendation.
A seventh panel loaded separately from /api/dis/high-pressure shows stocks with a DIS score ≥ 70, indicating elevated derivative market activity worth monitoring.
Clickable cards showing Trending Tickers, Headline Density, Risk-On/Risk-Off score, and market snapshot metrics. Each card links to the relevant app section.
Full signal reliability table with color-coded reliability bars (0–100%), freshness badges (hours since last update), and coverage metadata per data category.
Side-by-side OpenAI and Grok output with confidence scores. A Consensus block appears when both providers agree. Disagreements are flagged explicitly.
Compact summary cards for News (article counts), Narratives (active themes), ETFs (risk mode, risk score), and FRED economic data (macro event count).
| Headlines | Top 10 articles from 116 RSS sources (last 24 hours) |
| Squeeze Watch | Top 5 squeeze candidates with AI confidence ≥ 0.4 |
| Narratives | Active market narratives with strength score ≥ 30 |
| Emerging Markets | Recent regional highlights from EM Spotlight |
| After-Hours Movers | Latest session price movers from AfterHoursSnapshot |
| Dark Pool Activity | Tickers with >30% dark pool volume (90-day window) |
| Geopolitics | High-impact geopolitical event clusters |
| Market Snapshots | Latest broad market summary data |
Briefings are generated on demand and cached for 4 hours. The status endpoint (/api/daily-briefing/status) shows cache expiry and AI provider availability without triggering a new generation.
The Daily Briefing can be exported as a professionally formatted PDF in 8 languages. Available on Power User and Elite plans.
English, German, Spanish, Thai, Arabic, Farsi (Persian), Hindi, and Bengali. Translation uses formal register — the language of financial journalism and government publications, not casual equivalents.
Rotates between OpenAI and Gemini per call for reliability. If the primary provider fails, the other takes over automatically. Each translation call is independent so a single section failure does not block the rest of the export.
Your language selection is locked for 24 hours per briefing date. This prevents repeated regeneration costs and ensures consistency if you download the same date's PDF more than once.
Rendered as a print-ready document with GEF branding, section headers, and the full Matrix Intelligence content. Downloaded directly — no email delivery required.
A 10-section market intelligence report built automatically every Friday at 06:00 UTC by three AI providers running in parallel. Found under Dashboard > Weekly Report. Requires POWER_USER subscription or higher.
OpenAI, Grok, and Gemini each generate every section in parallel via a ThreadPoolExecutor. Section 8 (AI Consensus) explicitly compares all three provider outputs. A Prompt Moderator system enforces data-grounding rules — no hallucination, no financial advice, data_unavailable sentinel returned when data is missing.
High-level overview of the week's dominant market themes, key movers, and macro backdrop.
Risk-on vs risk-off assessment with ETF sector rotation signals and broad market positioning.
Top tickers from trending analysis, dark pool activity, squeeze candidates, and DIS scores.
FRED economic indicator highlights, macro event impacts, and Fed/policy developments for the week.
Capital flow signals across sector ETF pairs, risk mode scoring, and institutional positioning shifts.
Geopolitical risks, earnings surprises, high-volatility signals, and tail risk events for the coming week.
Which of the 26 tracked market narratives gained momentum, decayed, or reversed during the week.
Side-by-side comparison of OpenAI, Grok, and Gemini outputs. Highlights agreements and flags divergences.
Evidence-grounded observations for further research — clearly labeled as informational, not trading advice.
TikTok hooks, Facebook summaries, X (Twitter) post snippets, and hashtags generated for content distribution (admin users only). Each snippet has a "Post to X" button to share directly to Twitter/X.
An income-focused module for tracking dividend-paying stocks with safety scoring, calendar, screener, and alert functionality. Found under Watchlists > Dividend Tracker. Requires POWER_USER subscription or higher.
Each stock receives a composite safety score built from 5 weighted components. Missing data triggers automatic weight redistribution so the score remains meaningful even with partial information.
| Payout Ratio | How much of earnings is paid as dividends — lower is safer |
| Dividend Growth History | Consecutive years of stable or increasing payments |
| Free Cash Flow Coverage | Whether free cash flow supports the dividend payout |
| Debt-to-Equity | Leverage level — high debt threatens future payments |
| Earnings Stability | Consistency of earnings over multiple periods |
Upcoming ex-dividend dates grouped by week. Shows record date, payment date, yield, and safety score for each symbol.
Filter your watchlist by yield range, payout ratio, and safety score. Identify high-yield or Dividend Aristocrat candidates quickly.
Four alert types: EX_DIV_UPCOMING (days before ex-date), PAY_UPCOMING (days before payment), CUT_RISK_SPIKE (safety score drop), and YIELD_CHANGE (significant yield movement).
Import any dividend stock directly into the Research-First Trading Simulator as a research packet with one click from the company detail modal.
Eight system-default symbols are seeded for all users (no login required to view): JNJ, PG, KO, PEP, XOM, CVX, JPM, SCHD. These represent a cross-section of established dividend payers. Add your own symbols to build a personalized income watchlist.
Dividend Tracker symbols are tagged automatically: dividend_risk for low safety scores, and dividend_aristocrat for stocks with 25+ consecutive years of dividend growth — visible throughout the app wherever StockTags appear.
Golden Ears Finance uses a three-tier access model with centralized entitlement management. Tiers control which features are available, AI usage limits, and advanced functionality.
| Feature | FREE | POWER_USER | ELITE |
|---|---|---|---|
| News Feed, Trending Tickers, Charts | ✓ | ✓ | ✓ |
| Market Narratives & Dashboard | ✓ | ✓ | ✓ |
| Dividend Tracker (default 8 symbols, view only) | ✓ teaser | ✓ full | ✓ full |
| Daily Briefing (Classic + Matrix) | ✗ | ✓ | ✓ |
| Weekly Report Builder | ✗ | ✓ | ✓ |
| Dividend Tracker (full — calendar, screener, alerts, custom watchlist) | ✗ | ✓ | ✓ |
| AI Budget (daily) | Limited | Standard | Elevated |
| Research-First Trading Simulator | ✓ | ✓ | ✓ |
All legacy v1 subscribers retain full access to every feature regardless of tier. No action required — your access is preserved automatically.
Subscriptions are managed through Stripe. Upgrade or manage your plan from the Account > Subscription section. Stripe handles all payment processing — Golden Ears never stores card details.
Golden Ears includes an intelligent AI provider management system that ensures AI-powered features remain available even when primary providers experience issues.
The system automatically tries providers in order: 1) Replit OpenAI integration, 2) Your own API keys, 3) Backup provider pool, 4) Cached responses.
Recent AI responses are cached with feature-specific TTLs: Narratives (2h), Briefings (4h), Squeeze (1h), Breaking News (30min).
If the primary provider fails, the system seamlessly switches to the next available provider without interrupting your experience.
When no live AI providers are available, the system serves cached data and displays a notification banner.
You can check the current AI provider status in Account > API Keys. The status shows:
When you see an orange banner at the top of the app indicating "AI features operating in degraded mode," it means:
For the best experience, you can add your own API keys in Account > API Keys:
Your keys are stored securely in your session and never shared. Having your own keys ensures uninterrupted AI functionality.
Export your watchlists as CSV files compatible with Yahoo Finance portfolio import.
Use Yahoo Finance's portfolio features to track historical performance, compare against benchmarks, and see how your Golden Ears discoveries perform over time.
Your OpenAI and Grok API keys can optionally be included in data exports for backup and transfer purposes.
API keys are now stored encrypted in your user account using Fernet symmetric encryption. This means your keys persist across logins, browsers, and devices automatically. When you import a backup with API keys, they are encrypted and saved to your account for seamless access.
The Derivative Impact Score (DIS) Alerts system notifies you when derivative market pressure on your watched stocks exceeds your specified thresholds.
Click any stock ticker to open its modal, then set a DIS threshold (40-100). You'll be alerted when the score crosses above your threshold.
The system checks DIS scores every 2 hours and 15 minutes. When scores exceed your thresholds, alerts are generated automatically.
To prevent alert fatigue, each ticker has a 12-hour cooldown between alerts. You won't be spammed with repeated notifications.
View all triggered alerts in the DIS Alerts panel. Unread alerts show a badge count. Mark as read or manage your alert rules easily.
| Dark Pool Activity | 25% weight | Institutional trading volumes in dark pools |
| Social Interest Score | 20% weight | Reddit mention frequency and sentiment |
| Macro Event Sensitivity | 15% weight | Exposure to upcoming economic events |
| Earnings Proximity | 15% weight | Days until next earnings report |
| Squeeze Potential | 15% weight | Short interest and options flow signals |
| ETF Concentration | 10% weight | Weight across tracked ETF holdings |
| Trending Tickers Bar | Top of page | Click any ticker to see its DIS score in the modal popup |
| Undervalued Stocks Table | Watchlists > Undervalued | DIS column shows color-coded scores for each stock |
| Overvalued Stocks Table | Watchlists > Overvalued | DIS column shows color-coded scores for each stock |
| Short Interest Scanner | Tools > Short Interest Scanner | DIS column integrated with squeeze candidates, sortable |
| ETF Intelligence | Tools > ETF Intelligence | Average DIS displayed for ETF holdings analysis |
| Daily Briefing | Intelligence > Daily Briefing | "Derivative Pressure Highlights" section features high-DIS stocks |
| High Pressure Dashboard | Dashboard widget | Shows stocks with elevated DIS scores requiring attention |
| Ticker Modal | Click any ticker | Full DIS breakdown with alert configuration controls |
Golden Ears tracks bonds and fixed income markets using 10 dedicated RSS feeds from central banks and financial news sources. This module provides rate monitoring, topic classification, and yield curve analysis.
U.S. Treasury bonds and notes: auctions, yields, duration, and bid-to-cover ratios. Includes all maturity buckets from 3-month to 30-year.
Corporate bond markets: credit spreads, issuance, defaults, investment grade vs high yield, and credit rating changes.
Federal Reserve (Fed), European Central Bank (ECB), and Bank of England (BoE) policy decisions, rate expectations, and forward guidance.
Consumer Price Index (CPI), Personal Consumption Expenditures (PCE), inflation expectations, real yields, and Treasury Inflation-Protected Securities (TIPS).
Curve shape analysis, spread inversion detection, recession indicators, and term premium monitoring.
Optional integration with Federal Reserve Economic Data (FRED) provides real-time Treasury yields and spreads. When FRED is unavailable, the module operates in news-only mode using headline classification.
When the 10Y-2Y or 10Y-3M Treasury spread turns negative (inverted), Golden Ears surfaces this as a warning. Historically, yield curve inversions have preceded recessions, though timing varies significantly.
Remember: This is informational context, not a trading signal. Inversions can persist for extended periods before any economic impact materializes.
Bond news is aggregated from: Federal Reserve releases, U.S. Treasury press, Reuters Bonds, FT Bonds, Bond Buyer, European Central Bank, Bank of England, and Investing.com Fixed Income.
The Geopolitics module scans RSS feeds for global instability signals—military actions, sanctions, civil unrest, and diplomatic developments—that may impact financial markets.
Armed conflicts, military exercises, defense posturing, and territorial disputes that may affect commodity prices, defense stocks, or regional markets.
Economic sanctions, trade restrictions, tariffs, and export controls that may disrupt supply chains or affect specific sectors.
Protests, strikes, political instability, and social movements that may impact regional economies or specific industries.
Treaty negotiations, summit outcomes, alliance changes, and international agreements that may shift market sentiment.
AI analysis attempts to link geopolitical events to potential market implications. These connections are speculative and provided for informational context only—not as trading recommendations.
Geopolitical events are inherently unpredictable in their market effects. A seemingly significant event may have minimal market impact, while a minor development may trigger outsized reactions. Use this module for awareness, not prediction.
An experimental module for tracking high-volatility, early-stage signals. Speculative Lab surfaces stocks showing unusual activity patterns before they reach mainstream coverage.
Speculative Lab candidates carry elevated risk. These are early signals, not recommendations. Many candidates will not develop into significant moves. Use extreme caution and never risk capital you cannot afford to lose.
Speculative Lab uses an event-first scoring approach that prioritizes the type of catalyst over pure velocity metrics. This helps surface meaningful signals earlier, before news velocity spikes.
| Event Impact | 30% weight | Based on event type: halt (95), M&A (90), regulatory (85), earnings (80), guidance (80), offering (70), insider (65), other (40) |
| Volume Confirmation | 20% weight | Unusual volume ratio compared to historical average |
| News Velocity | 15% weight | Deduplicated article count in the last 24 hours |
| Novelty | 15% weight | How new the story is—higher scores for first-mover coverage |
| Source Diversity | 10% weight | Number of independent sources covering the story |
| Recency | 5% weight | Time since most recent article publication |
| Short Interest | 5% weight | Elevated short interest indicating potential squeeze setup |
The system automatically classifies news into 8 event types, each with a baseline impact score:
Exchange-initiated trading halts signal imminent material news.
Merger, acquisition, or buyout announcements.
FDA decisions, SEC actions, or other regulatory catalysts.
Quarterly or annual earnings releases and surprises.
Forward guidance updates from company management.
Secondary offerings, dilution events, or capital raises.
Notable insider buying or selling patterns.
General news without a specific high-impact catalyst.
Speculative Lab includes built-in safeguards against pump-and-dump schemes:
Speculative Lab signals are for research and education only. High scores indicate unusual activity patterns—not quality or certainty. Always conduct your own due diligence and consult a financial advisor before making investment decisions.
These endpoints power the narrative engine and regional analysis features.
| Method | Endpoint | Description |
|---|---|---|
| GET | /api/narratives |
Get all active narratives with regional coverage data |
| GET | /api/narratives/regional-heatmap |
Get regional heatmap data with weighted scores |
| POST | /api/narratives/scan |
Trigger manual narrative scan with regional tracking |
| GET | /api/narratives/{id} |
Get detailed narrative with regional breakdown |
| GET | /api/feed-sources |
Get all RSS feeds with region weights and display names |
| GET | /api/articles/history |
Get historical articles filtered by region |
| GET | /api/watchlist/emerging-markets |
Get all EM Spotlight narratives across 15 regions |
| GET | /api/watchlist/emerging-markets/{region} |
Get detailed narrative for a specific region |
| POST | /api/watchlist/emerging-markets/scan |
Trigger manual EM Spotlight scan for all regions |
The narrative strength score (0-100) is calculated using the following formula:
Golden Ears Finance is designed to sharpen market understanding, not to tell users what to trade. This Education Center explains concepts, methodology, and interpretation—content that remains valid over time.
Signal > Noise | Explanation > Prediction | Restraint > Hype
All AI outputs are governed by the GEF Core Analytical Directive: factual, neutral, professional tone with explicit grounding in provided data. No hype, no predictions, no financial advice.
GEF IS:
GEF IS NOT:
Bottom line: We explain; we don't recommend.
The Intelligence Briefing is a multi-layer summary generated twice daily (7am & 2pm UTC). It aggregates data from multiple independent systems:
How to interpret:
Tip: Start with the Executive Summary, then drill into sectors of interest.
Confidence in GEF measures data quality and agreement, not prediction accuracy. It answers: "How reliable is this analysis based on available evidence?"
Confidence is based on:
Confidence is NOT:
Key insight: High confidence means "well-supported by data," not "guaranteed to happen."
These three systems measure different aspects of market activity:
| System | What It Measures | Time Horizon |
|---|---|---|
| Trending | Media attention—how often a ticker is mentioned across news sources | Hours to days |
| Narratives | Thematic momentum—how stories/themes are developing across markets | Days to weeks |
| DIS | Derivative pressure—options/futures market positioning intensity | Hours to days |
When they align: If a ticker is Trending + connected to a strong Narrative + has high DIS, multiple independent systems are flagging it. This doesn't predict direction—it indicates high market attention.
Key: Each system is independent. Agreement = stronger signal quality, not direction.
Economic and geopolitical events don't move markets directly—they transmit through channels:
Macro Transmission Chain:
Geopolitical Transmission Chain:
Why this matters: Understanding transmission helps you interpret why a narrative is forming, not just that it exists.
GEF deliberately does not provide price predictions or buy/sell recommendations. Here's why:
What we provide instead:
Philosophy: An informed user with good data will make better decisions than one following predictions.
Market narratives follow predictable lifecycle stages. Recognizing where a narrative sits helps calibrate expectations:
| Stage | Characteristics | Signal |
|---|---|---|
| Emergence | Few sources, early mentions, low momentum | Watch—may develop or fade |
| Acceleration | Growing source count, rising momentum, cross-region spread | Active narrative gaining traction |
| Peak | Maximum coverage, high AI confidence, broad awareness | Mature narrative—may be crowded |
| Decay | Declining mentions, fading momentum, new narratives emerging | Story is aging—attention shifting |
Key insight: Peak narratives often correlate with peak crowding. Early narratives carry more uncertainty but less crowding.
GEF surfaces risk indicators without predicting outcomes. Here's how to interpret risk language:
Risk Level Indicators:
What risk levels mean:
Remember: Risk describes the environment, not the outcome.
Not all data sources are equal. GEF enforces a Source Matrix that classifies every data source into trust tiers, preventing low-quality scraped data from dominating rankings or creating false signals.
The Three Trust Tiers:
| Tier | Examples | Max Score | Can Create? |
|---|---|---|---|
| Tier 1 | SEC filings, regulatory disclosures | 100% | Yes |
| Tier 2 | Exchange notices, official feeds | 60% | With Tier 1 corroboration |
| Tier 3 | Scraped calendars, media listings | 10% | Never |
Why this matters:
Key insight: This system ensures that GEF rankings reflect authoritative data, not social media hype or scraped calendar entries.
A framework for filtering financial noise and focusing on what matters: understanding why markets move, not predicting where they will go.
Key: Not a trading system or signal service.
Every piece of market information contains two layers: the raw fact and the interpretation applied to it.
Key: The same fact can support opposite interpretations.
Signal strength is influenced by: source count, source diversity, recency, and AI confidence. Severity: High=confirmed/active, Medium=developing, Low=background.
Key: Triple AI agreement + source quality tiers.
Markets move on narratives—stories connecting data into themes across 26 categories with momentum tracking and cross-correlation detection.
Key: Momentum -100 to +100, source quality tiers.
Markets rarely provide unanimous signals. Embrace contradiction as information about where debate is active.
Key: Low contradiction may indicate crowding.
Information has a half-life. Breaking news decays in hours; macro themes persist for weeks or months.
Key: Structural narratives have multi-month relevance.
Cognitive biases that distort interpretation: confirmation bias, recency bias, and action bias.
Key: Wait for clarity before acting.
Alerts surface important information quickly—but an alert is an invitation to investigate, not a call to trade.
Key: Best response is "investigate further."
Value depends on when information was published and how many independent sources confirm it.
Key: Fresh + diverse = higher confidence.
Early-stage signals carry elevated uncertainty. Event type matters more than volume spikes—a trading halt with low volume is more significant than high volume with no catalyst.
Key: Early ≠ Better. Most speculative signals never materialize.
Understanding how military operations, sanctions, civil unrest, and energy supply disruptions transmit to financial markets. Markets react to geopolitical events through predictable channels.
Key: Identify transmission paths: oil/gas, defense contractors, emerging market currencies, sovereign credit, and commodity supply chains.
The simulator teaches disciplined research before every simulated trade using a 6-step gate workflow. It reinforces the GEF philosophy: understand before acting.
Key: Complete all 6 research gates to unlock trading. The Process Score rewards thoroughness, not speed.
How to read Swing Score (range position, volume, volatility compression, momentum, sector tailwind) and Institutional Conviction Score (source credibility, coverage depth, freshness, AI agreement). What the 7 semantic tiers mean and how cross-channel validation separates genuine setups from noise.
Key: A high Swing Score is a structural condition signal, not a trade trigger. Combine with your own research.
How bull flag patterns form, what the 5 structural scoring factors measure (pole strength, consolidation depth, volume signature, breakout proximity, sector alignment), and how to read the Grok AI narrative without treating it as a trade signal.
Key: Pattern detection is deterministic; AI interpretation is contextual. A high-scoring setup still requires fundamental validation.
The Trading Simulator is an education-focused practice environment that enforces disciplined research before every simulated trade. No real money is involved.
How it works:
Key Metrics:
Modes:
Philosophy: The simulator exists to build the habit of research-first decision making. Speed is not rewarded — discipline is. Access the full guide from the Simulator tab using the "How-To Guide" button.
Swing Intel identifies equities showing structural conditions historically associated with 52-week range expansion. It does not predict breakouts — it surfaces setups worth additional research.
Two independent scores per ticker:
| Swing Score (0–100) | Measures technical setup quality: 52-week range position (high = near highs), volume trend, volatility compression (tighter range = higher score), price momentum, and sector tailwind. A score above 70 indicates strong structural alignment across multiple factors. |
| Institutional Conviction Score (0–100) | Measures information quality: source credibility tier, coverage depth (how many independent sources), freshness (recency decay), and AI provider agreement rate. High conviction means the signal is well-supported by quality data, not just volume of mentions. |
7 Semantic Tiers (from highest to lowest):
How to use it: Sort by Swing Score to find structural setups. Use ICS to filter for well-supported signals. Cross-validate any candidate against the News Feed, Narratives, and DIS before treating it as research-worthy.
What it is not: Swing Intel is not a buy signal list. A tier-1 result means the system has found structural conditions and quality data — it does not mean the stock will move. You still need a thesis, a risk plan, and your own research.
Pattern Intelligence (Bull Candle) detects bull flag chart patterns using deterministic scoring. A bull flag is a consolidation period following a sharp trending move — the "pole" is the initial surge, the "flag" is the pullback or sideways drift before potential continuation.
The 5 structural scoring factors:
| Pole Strength | The magnitude and speed of the initial trending move. A stronger pole with clear institutional volume scores higher than a slow drift upward. |
| Consolidation Depth | How orderly the pullback is. Shallow, tight consolidation (flag stays within 30–40% of the pole's range) scores higher than deep or erratic pullbacks. |
| Volume Signature | Volume should expand on the pole and contract during consolidation. This pattern — high on the thrust, low on the rest — is the textbook bull flag volume structure. |
| Breakout Proximity | How close the price is to the top of the flag channel. Setups near resistance are flagged as "breakout ready"; those in early consolidation are "developing." |
| Sector Alignment | Whether the broader sector is in trend or neutral. A bull flag in an uptrending sector has higher follow-through potential than one in a weak or declining sector. |
AI Narrative (Grok): Each candidate receives a generated setup narrative explaining why the pattern scored as it did and what conditions would confirm or invalidate the setup. Read the narrative as context — not as a recommendation.
Scan schedule: The pattern engine runs every 4 hours during trading hours. Alerts fire for High Conviction setups (score ≥ 80) and appear in the Pattern Alerts bell icon at the top of the section.
Key interpretation rule: A high-scoring bull flag means the price structure is clean and the setup is technically sound at the moment of the scan. It does not mean the breakout will occur. False breakouts are common, especially in low-liquidity stocks. Always validate volume, news catalysts, and macro context before treating any pattern as actionable.
For informational purposes only. Not investment advice. Golden Ears Finance does not provide trading recommendations, price targets, or financial guidance. Always consult a qualified financial advisor before making investment decisions.
Swing Intel identifies equities showing structural conditions associated with 52-week range expansion. It is a dual-scoring intelligence module — not a signal service. Found under Tools > Swing Intel.
Measures technical setup quality across 5 components: 52-week range position, volume trend relative to average, volatility compression (Bollinger Band width), price momentum (RSI-based), and sector tailwind (ETF proxy performance). Each component is independently normalized before combining.
Measures information quality: source credibility tier (Tier 1 = authoritative, Tier 2 = mainstream, Tier 3 = scraped), coverage depth (number of independent sources), freshness (recency-weighted decay), and AI provider agreement rate (OpenAI + Grok + Gemini consensus).
High Conviction → Institutional Accumulation → Emerging Intel → Volatility Expansion → Sector Momentum → Narrative Expansion → Watchlist. Tiers are assigned from the combined score matrix — both axes must be strong for the highest tiers.
Each candidate is cross-validated across discovery channels: RSS feed mentions, DIS scoring, dark pool activity, and narrative strength. The more channels independently agree on a ticker, the more reliable the signal.
Enter any ticker symbol to run an immediate Swing Intel score. Useful for validating a ticker you found through another channel — the system will compute both scores in real time using live market data.
Full candidate list is refreshed on a scheduled basis. The refresh timestamp shown on each result indicates when the data was last computed. Sort by Swing Score, ICS, or tier to prioritize your review queue.
| Step 1 | Sort by Swing Score ≥ 70 to find structurally aligned setups |
| Step 2 | Filter for ICS ≥ 65 to ensure the signal is well-supported by quality sources |
| Step 3 | Check the discovery channels — does the ticker also appear in DIS, Dark Pool, or Narratives? |
| Step 4 | Cross-reference against the News Feed for any recent catalysts or adverse news |
| Step 5 | Use the Research-First Simulator to build a structured thesis before any simulated trade |
Swing Intel is available to Power User and Elite subscribers. Free users can see the module exists but cannot access candidate lists or per-ticker scoring.
Institutional-grade bull flag pattern detection with deterministic scoring and Grok AI narrative interpretation. Found under Tools > Bull Candle. Scans run automatically every 4 hours.
A bull flag is a chart pattern consisting of a sharp upward move (the "pole") followed by a brief consolidation (the "flag") before potential continuation. The consolidation should be orderly: tight range, declining volume, and contained depth relative to the pole.
5 structural factors scored independently: pole strength, consolidation depth, volume signature (high on pole, low on flag), breakout proximity, and sector alignment. Each factor contributes 20 points. Scores ≥ 80 are classified as High Conviction.
Each candidate receives a plain-language setup description from Grok identifying what makes the pattern notable, what the volume structure indicates, and what conditions would confirm or invalidate the setup. This is context — not advice.
The alert bell at the top of the Bull Candle section fires for High Conviction setups detected in the latest scan. Alerts include the ticker, score, and time of detection. Click to review the full candidate card. Dismiss individually or all at once.
The pattern engine scans every 4 hours. Each scan evaluates the current candidate pool against fresh price and volume data. Candidates that no longer meet the structural threshold are removed. New ones are added as conditions evolve.
A "Run Scan" button is visible only to admin users, allowing on-demand scans outside the scheduled 4-hour cycle. Standard users see results from the most recent scheduled scan.
A score of 90/100 means the price structure is technically clean at the time of the scan: the pole was strong, the consolidation is orderly, volume behaved correctly, and the sector is supportive. It does not mean the stock will break out. False breakouts occur frequently, particularly in lower-liquidity names.
Before treating any Pattern Intelligence result as research-worthy, validate: Is there a fundamental catalyst? What does the News Feed show for this ticker? What is the DIS score? Is the broader market in a risk-on or risk-off posture? Pattern structure is one input — not a complete thesis.
Live Treasury Bill rate cards, yield curve visualization, investment return calculator, and upcoming auction calendar. Data sourced from the FRED API (Federal Reserve Economic Data) and the US Treasury FiscalData API. Found under Fixed Income > T-Bills. Available to Power User and Elite subscribers.
Current yields for 5 maturities: 4-Week (DTB4WK), 8-Week, 13-Week (DTB3), 26-Week (DTB6), and 52-Week (DTB1YR). Sourced from FRED and refreshed every 30 minutes. Each card shows the maturity, current yield, and day-over-day change.
Canvas-rendered chart showing the current shape of the short-end T-Bill yield curve across all 5 maturities. A normal (upward-sloping) curve means longer maturities pay more. Inversion — where shorter maturities yield more than longer ones — is a historically significant signal worth monitoring.
90-day rolling trend lines for each maturity, showing how rates have moved over the past 3 months. Useful for understanding whether rates are rising, falling, or stabilizing across the short end of the curve.
Enter a principal amount and select a maturity. The calculator shows the estimated interest earned and total return at maturity, annualized and for the actual term. Useful for comparing T-Bill yields against other short-term alternatives.
Upcoming T-Bill auction dates and recent auction results. Includes settlement dates, announced amounts, and historical stop-out rates from the Treasury FiscalData API. Auctions run weekly for most maturities.
AI-generated commentary on the current T-Bill rate environment: what the yield levels suggest about Federal Reserve expectations, how they compare to historical averages, and what the curve shape implies for near-term monetary policy.
| Discount pricing | T-Bills are sold at a discount to face value and mature at par. The difference is your return. A 5% 13-week bill on $10,000 earns approximately $125 over the 13-week term. |
| Auction process | The Treasury sells T-Bills weekly via competitive and non-competitive bids. Non-competitive bidders accept whatever yield clears the auction — the "stop-out rate." |
| Secondary market | T-Bills trade in the secondary market between auctions. GEF shows primary market (FRED) rates, which reflect auction yields, not secondary market pricing. |
| Risk profile | T-Bills are backed by the full faith and credit of the US government and are considered the closest proxy to a risk-free rate. They carry no default risk but are subject to reinvestment risk when rates fall. |
| Rate cache | FRED data is cached for 30 minutes. Rates shown are current as of the last cache refresh — the timestamp is visible on each rate card. |
Yahoo Finance, CNBC, MarketWatch, Nasdaq, NYSE, Seeking Alpha, Barron's, Benzinga, Reddit subs
ECB, BBC Business, EuroNews, The Guardian, City A.M., STOXX indices
Nikkei Asia, SCMP, China Daily, Economic Times India, HKEX News
Gulf News Business, Al Jazeera Business, Arab News
Australian Financial Review, ABC Australia Business
LatinFinance, Buenos Aires Times, MercoPress
Business Daily Africa, AllAfrica Business, Moneyweb SA
Reuters, Bloomberg, Financial Times (multiple feeds), Capital.com
RSS Ticker Discovery is GEF's mechanism for finding stock tickers that are appearing in financial news but have not yet been added to GEF's tracking whitelist. The 116+ RSS sources ingested daily frequently cover companies before they reach mainstream screeners — this tool surfaces those early signals.
It scans every article title ingested in the last 4 hours, extracts uppercase letter sequences that match the shape of a ticker symbol, filters out noise, and ranks whatever remains by how many distinct RSS feeds mentioned it. Candidates that clear the minimum feed threshold are presented for your review. You decide which ones deserve a permanent place in GEF's tracking pipeline.
| Step 1 — Title sweep | Every article title fetched in the last 4 hours is scanned using a broad pattern that matches 2–5 uppercase letters (the standard shape of a US equity ticker). This deliberately casts a wide net. |
| Step 2 — Noise filtering | A curated exclusion list strips common English words (THE, AND, FOR…), financial acronyms (CEO, ETF, IPO, GDP, USA, FED…), country codes, and other false-positive sources. This list has over 200 entries refined over time. |
| Step 3 — Known-ticker exclusion | Any token already present in GEF's whitelist (339 tracked tickers + all ETFs) is removed. Only genuinely unlisted candidates pass through. |
| Step 4 — Feed diversity threshold | A candidate must appear in titles from at least 3 distinct RSS feed sources to qualify. Single-source noise (a publication's proprietary acronym, a column header, etc.) is filtered out automatically. |
| Step 5 — Scoring & ranking | Score = (distinct feed count × 12) + (article count × 2), capped at 100. A candidate mentioned across 8 feeds in 15 articles scores higher than one in 3 feeds in 3 articles. Sorted by feed count first, then article count. |
| Step 6 — Sample headlines | Up to 3 article titles containing the candidate are shown so you can judge context before deciding whether to add it. |
Click the Scan Now button to trigger a fresh analysis of the most recent article titles. The scan runs entirely from the database — no external HTTP calls — and typically completes in 1–3 seconds.
Each result shows: the ticker token, feed count, article count, a score (0–100), and 1–3 sample headlines. Read the headlines first — they tell you whether this is a genuine company or a false positive (country code, abbreviation, etc.).
Clicking Add runs a yfinance validation check to confirm the ticker is a real, tradeable security. If it passes, the ticker is added to GEF's live tracking. It will begin appearing in the trending bar and all downstream modules immediately. Requires POWER_USER+.
Any ticker you added via Discovery can be removed from the Added Tickers tab. Removal takes effect immediately and the ticker exits GEF's tracking pipeline. Requires POWER_USER+.
Displays all tickers you have contributed to GEF's dynamic additions list. Use this to audit what you have added and remove anything that turned out to be incorrect or irrelevant.
The same detection algorithm runs automatically inside the Trending engine every cycle. Unlisted tickers that clear the feed threshold appear in the trending ticker bar with an amber ⚡ NEW badge. Hover for the feed count. Click over to Ticker Discovery to review and add without running a manual scan.
Tickers added through Discovery are stored in a persistent additions file (ticker_discovery_additions.txt) and loaded at application startup. They are treated as first-class members of the GEF whitelist for all purposes: trending scoring, narrative matching, DIS screening, and all other modules that consume the whitelist. Additions survive application restarts.
On GCP, this file persists for the lifetime of the instance. It does not survive a clean re-deploy unless the file is included in the deployment artifact. For durable production additions, the recommended path is to add tickers directly to services/ticker_lists.py via the COMMON_STOCK_TICKERS set.
The broad regex intentionally catches more than it should — that is what makes it sensitive enough to find genuine early coverage. Common false positives include:
Always read the sample headlines before adding. The yfinance validation step confirms the ticker exists as a security — it does not confirm relevance, liquidity, or fit for your strategy.
An education-focused simulated trading environment with 9 isolated database tables and a mandatory 6-step research gate workflow. No real money is involved. Found under Tools > Trading Simulator.
Navigate to the Simulator tab and click "How-To Guide" for a full walkthrough. Create a simulator account with virtual cash ($1K–$10M) and choose Beginner or Standard mode.
Each trade requires: Narrative (why this stock?), Market Snapshot (auto-captured live data), Source Review (confirm you read the news), Stress Test (DIS/FRED/Bonds review), Invalidation Triggers (what would disprove the thesis?), and Risk Acknowledgement.
Read-only bridge to production squeeze data. Browse live squeeze candidates and import any ticker directly into a new research packet with one click — no manual entry needed.
Close positions with MARKET (instant fill), LIMIT (target price), or TRAILING (dynamic stop that follows price). Partial sells are supported. Trailing orders use a 15-second watcher scheduler.
Open positions refresh every 5 seconds via yfinance. Prices blink green on upward moves and red on downward moves for immediate visual momentum feedback.
Track equity curve chart, cash balance, unrealized P&L, drawdown (worst peak-to-trough decline), and exposure percentage. Full order history with fill prices.
The 6 research gates are designed to pull data from across the GEF platform:
| Narrative gate | Narratives Dashboard — 26 market themes |
| Market Snapshot gate | Auto-captured live market data with timestamp |
| Source Review gate | News Feed — 116+ global sources |
| Stress Test gate | DIS, FRED Macro, Bonds & Fixed Income |
| Invalidation gate | User-defined thesis conditions (2–3 required) |
| Risk gate | Simulation-only confirmation |
Three simulator features are independently controllable via environment flags: SIM_ENABLE_SQUEEZE_TAB (Squeeze Candidates tab), SIM_ENABLE_TRAILING_ORDERS (TRAILING sell order type), and SIM_ENABLE_REALTIME_BLINK (real-time price polling and blink animations).