Help · Knowledge base · Concept
Geometric compounding & volatility drag
Geometric compounding & volatility drag
Definition
A portfolio lives one path, not an average of paths —
and over that path, wealth compounds GEOMETRICALLY:
what matters is the product of return relatives, not
their sum. The consequences are arithmetic, not
opinion: a −50% year requires +100% to recover;
volatility itself taxes growth (geometric mean ≈
arithmetic mean − σ²/2, the VOLATILITY DRAG); and the
sizing that maximizes long-run growth (the Kelly
fraction — risk-kelly-criterion) is finite, above
which MORE risk produces LESS terminal wealth. This
entry is the philosophy underneath every sizing rule in
pillar 7 — the reason position sizing is not a detail.
How it works / structure
- The core identities: terminal wealth =
Π(1+rᵢ) — order-independent but ruin-sensitive (one
−100% zeroes the product forever, the formal ground
of every never-risk-ruin rule); the drag
approximation g ≈ μ − σ²/2 (two assets with equal
average returns and different volatility compound
differently — the quiet one wins; documented in the
leveraged-ETF reset record,
instrument-leveraged-inverse-etf, where the drag is the product’s documented decay). - The Kelly consequence (MacLean-Thorp-Ziemba): growth as a function of sizing is a hill — maximum at the Kelly fraction, ZERO again at roughly twice it; oversizing is not aggressive, it is mathematically self-defeating; estimation error makes practical sizing fractional-Kelly (the documented industry convention, and pillar 7’s justification for conservative defaults).
- The rebalancing/diversification connection:
combining imperfectly correlated assets lowers σ² at
similar μ — diversification is a GROWTH strategy, not
just comfort (
port-diversification-math’s deepest argument); volatility-managed exposure (risk-volatility-targeting) is drag management restated. - The time-horizon honesty (Markowitz’s analysis):
the geometric-mean criterion dominates for long
horizons but is not a universal utility — short
horizons and consumption needs change the objective;
the KB uses growth-optimality as the long-run frame,
with drawdown budgets (
risk-max-drawdown-budget) as the binding short-run constraint.
When it applies
Every sizing decision (the philosophy IS pillar 7’s foundation); leverage evaluation (drag grows with the square of exposure — the arithmetic that retires most leverage proposals); strategy comparison (Sharpe-equal strategies with different vol compound differently); multi-year simulation design (the engine simulates paths, not averages, for exactly this reason).
Risk profile & failure modes
- Arithmetic-mean seduction (the signature error): evaluating strategies by average return ignores the σ²/2 toll — high-vol strategies look better in expectation tables than in compounded ledgers; the platform reports geometric outcomes.
- Oversizing via optimism: Kelly computed on
estimated (optimistic) edges lands past the peak —
the documented LTCM-family failure
(
episode-ltcm-1998); fractional sizing prices the estimation error. - Ruin-blindness in fat tails: drag formulas assume
no absorbing barrier — gap risk and leverage create
one; the geometric frame makes ruin infinitely
costly, which is the formal case for scenario floors
(
risk-scenario-analysis). - Misapplied universality: short-horizon, liability-driven, or option-shaped objectives are not growth-optimal problems — the frame is stated per mandate.
Evidence & limits
The identities are mathematics; MacLean-Thorp-Ziemba compiles the growth-criterion literature including its critiques (Samuelson’s utility objections — labeled); Markowitz (1976) carries the long-run case. Nothing here is empirical claim — it is the arithmetic frame the platform’s risk entries instantiate.
Falsifiable-thesis examples
Illustrations only, not signals:
- “Across the strategy library, realized geometric return tracks μ − σ²/2 within measurement error (drag-identity audit)” — falsified by the ledger regression.
- “Half-Kelly sizing outperforms full-Kelly on terminal wealth in replays where edges are estimated with realistic error (estimation-robustness check)” — falsified by the paired simulation.
Cross-references
- The sizing machinery it grounds:
risk-kelly-criterion,risk-fixed-fractional,risk-volatility-targeting - The constraint partner:
risk-max-drawdown-budget - The growth case for diversification:
port-diversification-math - The cautionary record:
episode-ltcm-1998,instrument-leveraged-inverse-etf
Sources
- MacLean, L., Thorp, E. and Ziemba, W. (2011), The Kelly Capital Growth Investment Criterion: Theory and Practice — World Scientific — the growth-optimal framework and its cautions
- Markowitz, H. (1976), Investment for the Long Run: New Evidence for an Old Rule — Journal of Finance 31(5), 1273-1286 — geometric-mean criterion analysis
The agent cites this page.
Inside the platform, this entry is live context. A signed-in citation opens the in-app view of the same id.