Risk Parity Explained: Equal Money Does Not Mean Equal Portfolio Risk

Risk Parity Explained: Equal Money Does Not Mean Equal Portfolio Risk

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Learning objective

Learn why equal capital allocations can create unequal risk, how volatility and correlation determine each asset's marginal risk contribution, and how a simple risk-parity allocation is constructed.

Traditional allocation asks how much money sits in each asset. Risk parity asks how much each asset contributes to total portfolio volatility. A portfolio can hold 50% in each of two assets while the more volatile asset dominates the risk.

Risk parity is a risk-allocation method, not a return forecast. It does not guarantee diversification, and estimates can fail when volatility or correlation changes.

Step 1: distinguish weight from risk contribution

Portfolio variance depends on:

• each asset's weight;
• each asset's volatility;
• correlations between assets.

An asset's risk contribution is its weight multiplied by its marginal contribution to portfolio volatility. Contributions add up to total portfolio risk. An equal-risk portfolio adjusts weights until chosen assets or groups contribute similar amounts.

Worked example

Consider two hypothetical assets:

• Asset A annualised volatility: 10%;
• Asset B annualised volatility: 20%;
• correlation: 0.50;
• starting allocation: 50% / 50%.

The covariance between them is 10% × 20% × 0.50 = 0.01. Using the two-asset covariance matrix, the equal-capital portfolio's variance contributions are approximately:

• Asset A: 28.6% of total variance;
• Asset B: 71.4% of total variance.

Half the money is in each asset, but Asset B supplies most of the risk.

For this two-asset example, inverse-volatility weights are:

• Asset A: 66.7%;
• Asset B: 33.3%.

With the stated correlation, those weights produce approximately equal variance contributions. The lower-volatility asset receives more capital so the risk—not the cash—is balanced.

This result is specific to the assumptions. Add more assets or changing correlations and the solution requires an optimiser or iterative calculation.

Step 2: estimate inputs without false precision

Choose a documented lookback, return frequency and treatment of missing data. Test several reasonable windows. Short windows adapt quickly but are noisy; long windows are stable but slow.

Use consistent currencies and total-return series. Futures, leveraged ETFs and options require exposure measures that reflect contract sensitivity, not simply cash paid.

Step 3: add practical constraints

Pure equal-risk weights can create unwanted concentration. Apply limits for:

• maximum asset and sector weight;
• leverage and margin;
• liquidity and turnover;
• short selling;
• minimum cash buffer;
• transaction costs;
• rebalance frequency.

If low-volatility assets receive leverage, a calm historical series can create a large position just before volatility rises. Stress the leverage and financing separately.

Step 4: monitor risk drift

Weights can remain unchanged while risk contributions move because volatility and correlations change. Recalculate on a schedule and when a defined volatility shock occurs.

Avoid constant tiny rebalances. Use calendar or threshold rules and include trading costs. A model that equalises risk before costs can lose its advantage through turnover.

Step 5: stress correlation

Diversification often weakens during market stress. Test:

• correlations rising towards 1;
• the high-volatility asset becoming more volatile;
• both changes occurring together;
• gaps beyond normal daily volatility;
• financing costs rising.

The portfolio should be judged by stressed drawdown, liquidity and margin as well as normal volatility.

Common mistakes

• Calling equal capital equal risk.
• Using volatility while ignoring correlation.
• Treating historical covariance as stable.
• Leveraging low-volatility assets without a gap test.
• Rebalancing too often and ignoring costs.
• Mixing spot, futures and options exposures on a cash-value basis.
• Assuming equal risk contributions imply equal expected returns.

Practical checklist

• Define return series, currency, lookback and frequency.
• Estimate volatility and the full correlation matrix.
• Calculate current marginal and total risk contributions.
• Add concentration, leverage and liquidity constraints.
• Stress volatility, correlation, gaps and financing.
• Rebalance with a tested calendar or threshold.
• Compare realised risk contributions with model estimates.

This tutorial was prepared with AI-assisted research and writing under The Money Man editorial workflow. It is educational information, not personalised investment advice. All figures are hypothetical, estimates can change abruptly and risk parity does not guarantee against loss.