Results for “python”

Synthesize market breadth, regime, and flow signals into a unified capital commitment recommendation with exposure ceiling, bias, and action guidance.

Screen US stocks using William O'Neil's CANSLIM growth stock methodology with composite scoring and weighted components.

Calculate risk-based position sizes for long stock trades using fixed fractional, ATR-based, or Kelly Criterion methods with portfolio constraints.

Detects and ranks trending market themes by analyzing cross-sector momentum, volume, and breadth signals with lifecycle maturity assessment.

Provides expert guidance for systematic backtesting of trading strategies, covering methodology, stress testing, bias prevention, and result interpretation.

Converts abstract edge concepts into concrete strategy draft variants with configurable risk profiles and optional exportable ticket YAMLs for downstream validation.

Reviews trading strategy drafts for edge plausibility, overfitting risk, sample size adequacy, and execution realism, outputting PASS/REVISE/REJECT verdicts with confidence scores.

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

Aggregate and rank signals from multiple edge-finding skills into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.

Evaluates account-level drawdown and losing-streak rules from local thesis files to decide whether new trade risk is allowed, without external APIs.

Convert daily market observations and news reactions into structured edge hints, with optional LLM augmentation, outputting a canonical hints.yaml for downstream concept synthesis.

Builds systematic factor-based investment strategies following AQR Capital Management's methodology, covering factor construction, portfolio optimization, and risk management.

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

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.

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.

Screen US stocks for high-quality dividend opportunities combining value characteristics, attractive yields, and consistent growth using a two-stage screening approach with FINVIZ Elite and FMP APIs.

Evaluates a local pre-trade checklist before manual order entry, blocking planless, oversized, revenge-risk, market-regime-blocked, or circuit-breaker-blocked entries while journaling the decision for later review.

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).

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.

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).

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.

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.

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.