Work / Aurelius
Case study 05
Aurelius
Portfolio risk analytics and strategy backtesting, open and inspectable.
The problem
Institutional risk tooling lives behind expensive closed platforms, so most private investors size positions on instinct and find out what their drawdown was afterwards.
The system
A FastAPI backend and a Next.js frontend over a documented risk engine. Value at Risk by historical and parametric methods, conditional VaR as expected shortfall, Sharpe, Sortino and Calmar ratios, maximum drawdown with duration, rolling and annualised volatility, downside deviation, beta and alpha under CAPM, a correlation matrix with eigenvalue decomposition, and portfolio concentration by HHI, effective positions and top-N.
- Risk
- VaR, CVaR, Sharpe, Sortino, Calmar, drawdown, beta, alpha
- Structure
- Correlation matrix with eigenvalue decomposition, HHI concentration
- Backtester
- Event driven, models commission and slippage
- Output
- Equity curve, trade ledger with execution detail
- Data
- Works on synthetic sample data, no paid API required
The result
The documentation is explicit that Aurelius is a research and analytics tool. It does not predict markets, guarantee returns or give financial advice. That statement is part of the product, not a footnote added later.
Let's build something useful.
Send the problem, not a spec. I reply with an approach and a scope I can hold to.