Risk Parity
Risk Parity allocates weights so each asset contributes equally to total portfolio risk. Uses inverse volatility as a simple approximation, with optional covariance adjustment.
At a glance
What the backtest shows
- Beat buy-and-hold on 0 of 1 markets by annual return over 5 years.
- Had a smaller maximum drawdown than buy-and-hold on 1 of 1 markets.
- Best market by Sharpe ratio: RISK-PARITY (Sharpe 1.04, CAGR 8.2%).
Equity curve
Score and risk profile
Each bar is a percentile against every strategy on the same market and window (100 = best).
How it held up in sell-offs (RISK-PARITY)
| Period | Strategy | Buy & hold |
|---|---|---|
| Q4 2018 sell-off | -8.2% | -15.9% |
| COVID crash (Feb–Mar 2020) | -13.9% | -26.0% |
| 2022 bear market | -11.3% | -4.4% |
| Market above its 200-day average (annualized) · 69% | +4.0% | +6.9% |
| Market below its 200-day average (annualized) · 31% | +4.0% | +1.7% |
Sell-off dates follow the US stock market. Above/below the 200-day average uses the previous day's position, so there is no look-ahead.
Out-of-sample check (RISK-PARITY)
| Check | Value |
|---|---|
| Chosen parameters on their 3-year training windows (average Sharpe) | 0.44 |
| Same parameters in the following 6 months, when traded (Sharpe) | 0.52 |
| Default parameters over the same months (Sharpe) | 0.52 |
| Parameter re-selections / changes | 28 / 4 |
| Parameter settings with a positive Sharpe (full history) | 3 of 3 |
| Sharpe across settings: worst / median / best | 0.52 / 0.52 / 0.53 |
Out-of-sample periods start on 2013-01-04. Training-window figures are flattered by picking the best of 3 settings; the out-of-sample figure is what the strategy actually earned. A large drop, or a result that depends on one setting, points to overfitting. How walk-forward testing works.
Results by market (5 years)
| Market | CAGR | Buy & hold CAGR | Sharpe | Max drawdown | Buy & hold max DD | Volatility | Arena Score |
|---|---|---|---|---|---|---|---|
| RISK-PARITYRisk Parity | 8.2% | 13.8% | 1.04 | -15.5% | -16.5% | 7.9% | 55 |
Strategy metrics use daily returns without trading costs. Buy-and-hold figures are for the same market and window. Rows are sorted by Sharpe ratio.
RISK-PARITY across time windows
Rules
Entry
Weight proportional to 1/volatility Normalize to sum to 1
Exit
Monthly rebalance
Indicators
Rolling volatility Correlation matrix
Inputs
Lookback = 60 Rebalance = Monthly
Risk
Equal risk contribution target
Strategy evidence
- RISK-PARITY · Inspect evidence 2026-11-10
Only available, validated bundles appear below. Missing evidence is not a passing validation result.
Evidence coverage
1 / 1 declared strategy–market pairs validated
Notes
- Classic risk parity uses inverse volatility
- More sophisticated versions use covariance matrix
- Popularized by Bridgewater's All Weather
Related strategies
Embed this score
Add the live badge to a blog post, README or forum signature. It updates with the daily data.
<a href="https://quantarenas.com/strategy/port-01-risk-parity/"><img src="https://quantarenas.com/badge/port-01-risk-parity.svg" alt="Risk Parity Arena Score on Quant Arena" height="20"></a>
[](https://quantarenas.com/strategy/port-01-risk-parity/)
Backtests are historical simulations on daily data and do not include commissions or slippage. They do not guarantee future results and are not investment advice. See the methodology for how every strategy is tested.