| W1 |
Market data + quant workflow |
Build the first market-data ingestion service for SPY, QQQ, AAPL, MSFT. |
Can run a script that fetches and stores daily OHLCV data for 4 tickers, and compute simple returns. |
| W2 |
Probability, returns, and volatility |
Implement a quant analytics module with returns, variance, volatility, and rolling metrics. |
Analytics module passes tests for daily returns, log returns, and 20-day rolling volatility on real data. |
| W3 |
Covariance, correlation, and risk |
Build covariance/correlation risk toolkit and basic portfolio risk analytics. |
Can compute and visualize a correlation matrix for 4 assets and calculate portfolio volatility for a given weight vector. |
| W4 |
Linear algebra + regression |
Build regression and PCA modules for market data analysis. |
Can run linear regression and PCA on multi-asset returns and explain the output in a notebook. |
| W5 |
Buffer — consolidate weeks 1–4 |
Close all open gaps from weeks 1–4. No new features. |
All prior milestones fully met, tests green, notes cleaned up, no known blockers carried forward. |
| W6 |
Backtesting basics |
Build a simple backtesting engine for moving-average crossover and trend-following strategies. |
Backtester runs a moving-average crossover on SPY and outputs Sharpe, CAGR, and max drawdown. |
| W7 |
Monte Carlo + simulation |
Build Monte Carlo and random-walk simulation tools. |
Can generate 10k simulated price paths for SPY and compare the distribution against historical returns. |
| W8 |
Portfolio polish + demo |
Create a demo-worthy v1 of the quant research platform. |
A single notebook or CLI command demos the full pipeline: data ingestion, analytics, backtest, simulation. |
| W9 |
Options intro preparation |
Prepare the platform for options analytics: payoff diagrams and option contracts model. |
Can plot call/put/covered-call payoff diagrams and have a documented options-engine architecture draft. |