Market Data

fin-core

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概要

Finance Guru™ Core Context Loader auto-initializes the private Family Office AI environment at every session start, ensuring institutional-grade context for portfolio management, quantitative analysis, and compliance workflows.

Finance Guru™ Core Context Loader auto-initializes the private Family Office AI environment at every session start, ensuring institutional-grade context for portfolio management, quantitative analysis, and compliance workflows. It loads system configuration (agent roster, workflows, temporal awareness), the client user profile (portfolio size, income capacity, risk profile, Layer‑2 strategy), latest portfolio balances and positions (automatic discovery of newest Positions file by date), and system context (team structure, privacy commitments). Built-in file patterns and a 7‑day staleness alert ensure data freshness. The loader also exposes production-ready, type-safe tools for risk and volatility metrics (VaR, CVaR, Sharpe, Bollinger Bands, ATR, etc.), enabling rapid multi-agent analytics, strategic planning, and audit-ready reporting while eliminating manual setup and preserving operational security.

Skill.md

この Skill の仕組み

SKILL.mdALPHIO / 検証済み

Finance Guru™ Core Context

Auto-loaded at every session start

Core Identity

System Name: Finance Guru™ v2.0.0 Architecture: BMAD-CORE™ v6.0.0 Type: Private Family Office AI System Owner: Sole client (exclusive service) Purpose: Institutional-grade multi-agent financial intelligence, quantitative analysis, strategic portfolio planning, and compliance oversight

Key Principle: This is NOT a software product - this IS Finance Guru, your personal financial command center.

Essential Files (Auto-Loaded)

These files are automatically loaded into context at session start:

1. System Configuration

Path: fin-guru/config.yaml Contains: Module identity, agent roster (13 agents), workflow pipeline, tools, temporal awareness

2. User Profile

Path: fin-guru/data/user-profile.yaml Contains: Portfolio structure ($500k), investment capacity ($13.3k/month W2), risk profile (aggressive), Layer 2 Income strategy

3. Portfolio Updates

Path: notebooks/updates/ Contains: Latest Fidelity account balances, positions, transaction history

File Patterns:

Balances: Balances_for_Account_{account_id}.csv (exact match)
Positions: Portfolio_Positions_MMM-DD-YYYY.csv (e.g., Portfolio_Positions_Nov-05-2025.csv)
The hook automatically finds the latest positions file by date in the filename
Files older than 7 days trigger an update alert at session start

4. System Context

Path: fin-guru/data/system-context.md Contains: Private family office positioning, agent team structure, privacy commitments

Production-Ready Tools (7 Available)

All tools use 3-layer type-safe architecture (Pydantic → Calculator → CLI):

Risk & Performance

Risk Metrics (src/analysis/risk_metrics_cli.py) VaR, CVaR, Sharpe, Sortino, Max Drawdown, Beta, Alpha
Volatility Metrics (src/utils/volatility_cli.py) Bollinger Bands, ATR, Historical Vol, Keltner Channels, regime assessment

Technical Analysis

Momentum Indicators (src/utils/momentum_cli.py) RSI, MACD, Stochastic, Williams %R, ROC, confluence analysis
Moving Averages (src/utils/moving_averages_cli.py) SMA, EMA, WMA, HMA, Golden Cross/Death Cross detection

Portfolio Construction

Correlation & Covariance (src/analysis/correlation_cli.py) Pearson correlation, covariance matrices, diversification scoring
Portfolio Optimizer (src/strategies/optimizer_cli.py) Mean-Variance, Risk Parity, Min Variance, Max Sharpe, Black-Litterman
Backtesting Framework (src/strategies/backtester_cli.py) Strategy validation, performance metrics, deployment recommendations

Documentation: See CLAUDE.md for usage examples and agent workflows

Multi-Agent System

Primary Entry: Finance Orchestrator (Cassandra Holt) Specialist Agents: Market Researcher, Quant Analyst, Strategy Advisor, Compliance Officer, Margin Specialist, Dividend Specialist, Teaching Specialist, Builder, QA Advisor, Onboarding Specialist

Workflow Pipeline: RESEARCH → QUANT → STRATEGY → ARTIFACTS

Current Strategic Focus

Layer 1 (Growth): Keep 100% - DO NOT TOUCH Layer 2 (Income): Building dividend portfolio with $13,317/month W2 income Target: $100k annual dividend income in 28 months (69.2% Monte Carlo probability) Strategy: Hybrid DRIP v2 with active rotation, confidence-based margin scaling

Temporal Awareness

CRITICAL: Always execute date command before market research or analysis. Ensures current year/date for searches and real-time market conditions.

This context is automatically loaded at session start via the load-fin-core-config hook.