Finance Guru™

Stop juggling 10 browser tabs for financial analysis.
One command activates 8 AI specialists who work together as your private family office.

Architecture

The Problem I Solved

I was drowning in complexity. Every investment decision meant:

Opening Yahoo Finance for prices
Switching to a spreadsheet for calculations
Googling "how to calculate Sharpe ratio" (again)
Copy-pasting data between 5 different tools
Second-guessing myself because I couldn't see the full picture

The real cost wasn't time—it was confidence. I never felt certain my analysis was complete.

The Insight

What if instead of me becoming an expert in everything, I could have a team of experts who already knew my portfolio, my risk tolerance, and my goals?

Not a chatbot. Not an app. A personal family office that treats me like a wealth management client—but built on AI agents that can actually run calculations.

What I Built

Finance Guru™ is my private AI-powered family office. It's not software you install—it's a system where Claude transforms into specialized financial agents who work exclusively for me.

One command:

/finance-orchestrator

Eight specialists activate:

Agent	Expertise	What They Do
Cassandra Holt	Orchestrator	Coordinates the team, routes my requests
Market Researcher	Intelligence	Scans markets, identifies opportunities
Quant Analyst	Data Science	Runs calculations, builds models
Strategy Advisor	Portfolio	Optimizes allocations, validates strategies
Compliance Officer	Risk	Checks position limits, flags concerns
Margin Specialist	Leverage	Analyzes margin strategies safely
Dividend Specialist	Income	Optimizes yield, tracks distributions
Tax Optimizer	Efficiency	Structures holdings for tax advantage

See It In Action

Me: "Should I add more TSLA to my portfolio?"

What happens behind the scenes:

# Market Researcher checks momentum
uv run python src/utils/momentum_cli.py TSLA --days 90

# Quant Analyst calculates risk metrics
uv run python src/analysis/risk_metrics_cli.py TSLA --days 90 --benchmark SPY

# Quant Analyst checks market-implied risk
uv run python src/analysis/itc_risk_cli.py TSLA --universe tradfi

# Strategy Advisor checks correlation with existing holdings
uv run python src/analysis/correlation_cli.py TSLA PLTR NVDA --days 90

# Compliance Officer validates position size
# → Checks if addition exceeds concentration limits

What I get: A coordinated answer that considers momentum, risk, correlation, and compliance—not just a single data point.

The Technical Foundation

11 Production-Ready Analysis Tools

Every tool follows the same bulletproof pattern:

Pydantic Models → Calculator Classes → CLI Interfaces
     ↓                    ↓                  ↓
 Type Safety         Business Logic      Agent Access

Category	Tools	Key Metrics
Risk	Risk Metrics, ITC Risk	VaR, CVaR, Sharpe, Sortino, Max Drawdown, Beta, Alpha
Technical	Momentum, Moving Averages, Volatility	RSI, MACD, Golden Cross, Bollinger Bands, ATR
Portfolio	Correlation, Optimizer, Backtester	Diversification score, Max Sharpe, Risk Parity
Options	Options Pricer	Black-Scholes, Greeks, Implied Volatility

External Risk Intelligence

ITC Risk Models API integration provides market-implied risk scores:

Real-time risk assessment for TSLA, AAPL, MSTR, NFLX, SP500, commodities
Risk bands help agents validate entry/exit

...

aojdevstudio/finance-guru

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