Results for “tradermonty”

Monitor dividend portfolios for risk triggers and route anomalies into a human review queue without auto-selling.

Validate financial data quality in market analysis documents before publication, checking price scales, instrument notation, date accuracy, allocation totals, and unit usage.

Reviews closed trades, partial exits, and monthly trade aggregates for process adherence, risk discipline, execution quality, and evidence-based trading behavior patterns.

Screen post-earnings gap-up stocks for Post-Earnings Announcement Drift patterns using weekly candle analysis to detect red candle pullbacks and breakout signals.

Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path.

Analyze investment portfolios by fetching real-time holdings via Alpaca MCP Server, then assess asset allocation, diversification, risk metrics, and generate rebalancing recommendations.

Convert Kanchi-style dividend investing into a repeatable US-stock operating procedure covering screening, deep dive, entry planning, and post-purchase monitoring.

Synthesizes outputs from 8 upstream market analysis skills into a unified conviction score (0-100), pattern classification, and allocation recommendation for Druckenmiller-style portfolio positioning.

Record and analyze post-trade outcomes for trading signals, tracking false positives, missed opportunities, and regime mismatches to generate feedback for signal aggregation and skill improvement.

Screen US equities for parabolic exhaustion patterns, generate conditional pre-market short plans, and monitor intraday trigger signals using 5-min bars.

Scans US equities for daily +20%/-20% movers, classifies catalysts and chart context, updates forward outcomes, and summarizes cohort patterns for research.

Analyze S&P 500 market breadth charts and CSV data to assess market health, identify trading signals, and generate positioning recommendations for different trader types.

Generate falsifiable trade strategy hypotheses from market data, trade logs, and journal snippets, with ranked hypothesis cards, experiment designs, kill criteria, and optional strategy.yaml export.

Tracks institutional investor ownership changes and portfolio flows using 13F filings data to identify stocks with significant smart money accumulation or distribution.

Screens for dividend growth stocks with 12%+ annual dividend growth and 1.5%+ yield that are experiencing temporary pullbacks identified by RSI oversold conditions (RSI ≤40).

Analyzes market breadth using Monty's Uptrend Ratio Dashboard data to diagnose the current market environment. Generates a 0-100 composite score from 5 components (breadth, sector participation, rotation, momentum, historical context).

Quantifies market top probability using O'Neil Distribution Days, Minervini leading stock deterioration, and Monty defensive sector rotation, producing a 0-100 composite score with risk zone classification for tactical 2-8 week timing signals.

Detect IBD-style Distribution Days for QQQ/SPY, track 25-session expiration and 5% invalidation, count d5/d15/d25 clusters, classify market risk, and emit TQQQ/QQQ exposure recommendations.

Collects market data from Yahoo Finance and Exa, calculates technical indicators, scans watchlists, and generates market analysis reports to identify trading opportunities.

Fetch upcoming economic events and data releases using the FMP API, including central bank decisions, employment reports, inflation data, GDP releases, and other market-moving indicators for specified date ranges.

Provides analytics and operations for the Metal Dollar (XMD) stablecoin, covering minting, redemption, supply metrics, collateral reserves, and oracle prices.

Track investment theses across their lifecycle — from screening idea to closed position with postmortem. Register theses from screener outputs, manage state transitions, attach position sizing, review due dates, and generate postmortem reports with P&L and MAE/MFE analysis.

Detects Follow-Through Day (FTD) signals for market bottom confirmation using William O'Neil's methodology, with dual-index tracking and a state machine for rally attempt, FTD qualification, and post-FTD health monitoring.

Retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep API, filtered by market cap over $2B, and organizes them into a markdown table grouped by date and timing.

Screens recent post-earnings stocks using a 5-factor scoring system (Gap Size, Pre-Earnings Trend, Volume Trend, MA200 Position, MA50 Position) and assigns A/B/C/D grades to identify momentum trade candidates.

Analyzes Stockbee-style Day 1 Episodic Pivot candidates by scoring catalyst quality alongside price/volume confirmation, gap/range expansion, volume shock, neglect/revaluation context, liquidity, and risk to the EP-day low.

Screen US stocks for Stockbee-style short-term momentum burst setups using 4% breakout, dollar breakout, range expansion, volume expansion, prior range contraction, close-location, failure filters, and risk-distance scoring.

Screen US stocks for Stockbee-style selling-exhaustion hammer setups using prior momentum, pullback depth, undercut/reclaim, long lower-wick geometry, close-location, volume confirmation, quality/liquidity gates, and risk-distance scoring.

Build and maintain a model book for Stockbee-style Momentum Burst setups by ingesting screener candidates, updating 3-day and 5-day forward outcomes with MFE/MAE and stop-hit status, and summarizing cohort statistics to improve setup recognition.