── ── Industry
RIA — Position Sizing & Concentration Discipline
The parent expected-value-and-kelly sizes repeated positive-edge bets to maximize long-run growth without ruin. For an RIA, the discipline is inverted toward survival: fractional-Kelly thinking caps concentration so no single position can impair the client's plan.
Run RIA — Position Sizing & Concentration Discipline on a real problem
Bring something you're actually deciding — free, in the browser.
How it works
- Establish the edge is real and repeatable before sizing anything. - Use fractional Kelly (e.g. ¼–½) — full Kelly is too volatile for client capital. - Bound by IPS max-position and drawdown tolerance; the smaller of Kelly-implied and IPS cap wins. - Treat concentrated legacy stock as an over-sized position to unwind on a tax-aware schedule.
When to use it
- sizing a single-name or thematic position
- a client with concentrated stock
- setting max-position/rebalancing bands
- 'how much of the portfolio should this be?'
When not to use it
broad index allocation already governed by the IPS.
Worked example
RIA — Position Sizing & Concentration Discipline
The parent expected-value-and-kelly sizes repeated positive-edge bets to maximize long-run growth without ruin. For an RIA, the discipline is inverted toward survival: fractional-Kelly thinking caps concentration so no single position can impair the client's plan.
Install this skill (free, MIT)
npx skills add deciqAI/knowledge-skillsUseful? Star the repo — stars help other builders find it.
Related mental models
The parent second-order-thinking traces "and then what?" across time and parties.
The parent checklist turns fuzzy "did we cover everything" into a verifiable gate.
The parent premortem runs the clock forward to a failure and works backward.
The parent theory-of-constraints finds the one step that caps total output and subordinates everything to it.