Home / Ideas / Inverse-Volatility Naive Risk Parity

Risk-managed & volatility-targeted allocation · 2026-08-18

Inverse-Volatility Naive Risk Parity

weight a multi-asset ETF sleeve by 1/realized-vol so each sleeve contributes equal risk

expected Sharpe 0.5–1.0confidence: highfree daily data

The most robust, estimation-light risk-based allocator: it needs only each asset's realized vol (no covariance inversion), and independent backtests place its Sharpe well above equal-weight and 60/40. QuantPedia reports 0.98 vs 0.67 for equal-weight on the same SPY/EFA/GLD/IEF sleeve; ReSolve finds naive risk parity competitive with fully optimized methods.

Universe

Liquid cross-asset ETF sleeve — e.g. SPY (US equity), EFA (developed ex-US), IEF/TLT (Treasuries), GLD (gold), DBC (commodities); 5–8 sleeves.

How it works

Each rebalance, compute 60–126-day realized vol per ETF, set weight proportional to 1/vol (normalized to 1), hold long-only, rebalance monthly with a one-day execution lag.

Expected performance

Research-derived Sharpe estimate: 0.5–1.0.

Backtest this idea with SignalChain

This is a research lead — not a finished backtest. SignalChain takes an idea like this and runs the whole pipeline inside Claude Code: it researches the concept against academic and practitioner sources, sets benchmarks, writes and lints a VectorBT backtest, runs it, and grades the result PASS/FAIL. One command:

/signalchain inverse-volatility risk parity: weight SPY EFA IEF TLT GLD DBC by 1/60d-realized-vol, long-only, monthly rebalance, one-day lag Get SignalChain — $49 →

Research & sources

Not financial advice. This page describes a research idea, not a recommendation. Any performance figures are hypothetical, research-derived estimates and are not indicative of future results. SignalChain is a research and educational tool; you are solely responsible for any decisions you make.