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Foundations: Theses, Signals, & Timelines
Define a trade thesis and the signals that actually trigger actions.
Outline: hypothesis → variables → decision rules
Education • No investment advice
Build Your Stock Skills the Quant Way
A practical, no-hype starter kit to make more deliberate, risk-aware decisions. Inspired by principles used in quantitative investing.
📈 Position sizing & risk checklists
🧪 Simple backtest & journaling templates
🧠 Behavior & discipline prompts
⚙️ Execution routines you can repeat
Mentor Inspiration: David E. Shaw
David E. Shaw is widely regarded as a pioneer of quantitative investing and the founder of D. E. Shaw & Co., a global investment and technology firm known for research-driven, algorithmic strategies. The curriculum is inspired by widely adopted principles of systematic investing—translate hypotheses into rules, test those rules, and manage risk first.
Founder
D. E. Shaw & Co.
Quant Pioneer
algorithmic & systematic
Skills & capabilities to emulate
Quant research
Signal design
Backtesting
Risk budgeting
Position sizing
Execution & slippage
Data hygiene
Journaling & review
System thinking
Cross-disciplinary teamwork
What you’ll practice under this framework
- Turn ideas into explicit entry/exit/risk rules and define when rules may change.
- Run lightweight sanity checks/backtests to avoid cherry-picking and overfitting.
- Allocate risk via position sizing, stops, and portfolio-level drawdown limits.
- Design an execution routine that limits slippage and emotional overrides.
- Journal decisions (not only outcomes) to spot process leaks quickly.
- Iterate a repeatable loop: hypothesis → rules → check → execute → review.
