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Most equity risk models answer a single question: how much of a portfolio's variance comes from known factor exposures? It's a useful question, but an incomplete one. On any given day, macro forces can drive 60, 70 or even 80 percent of S&P 500 risk. When a model treats that component as noise, it isn't measuring risk — it's missing it. The result is alpha leakage: returns attributed to security selection that are, in fact, a reward for macro exposure never consciously taken.

Dual risk premia is the framework that closes that gap. Equity investors have access to two distinct return sources. Macro premia come from deliberate exposure to macroeconomic factors — rates, inflation, credit spreads, growth expectations. Idiosyncratic premia come from genuine stock-specific characteristics: an earnings surprise, a management change, a mispriced competitive moat. Both are real and both are earnable, but most portfolios blend them without knowing the proportions. When the regime shifts, the blended book takes damage that looks like stock-picking failure but is actually macro mismanagement.

Quant Insight's Macro Factor Equity Risk Model (MFERM) was built to separate the two. Validated on 11 years of daily data (January 2015 – December 2025) across the S&P 500 and Qi's regional universes, MFERM measures how macroeconomic forces drive returns at the individual-security level. Its core output is the Macro Share of Risk (MSR) — macro factor risk divided by total forecast risk — updated daily rather than monthly or quarterly. Read at the market level, MSR tells you whether the environment is macro-dominant or idiosyncratic; read at the stock level, it tells you which positions are earning genuine alpha and which are riding a macro tailwind.

That measurement makes regime-aware construction possible. When the Macro Share of Risk is elevated, idiosyncratic signals carry more noise, long/short pairs that look uncorrelated on fundamentals may be tightly correlated on macro exposure, and stress testing should focus on macro scenarios. When it's low, stock-specific catalysts have more independent impact and idiosyncratic positions can be isolated cleanly. Qi's Dual Risk Premia strategy formalises the tilt between the two: over an 11-year backtest it delivered excess returns of +2.95% per annum versus the S&P 500, at a tracking error of 3.0% and an information ratio of 0.98. Past performance is not a reliable indicator of future results.

MFERM completes, rather than competes with, Barra, Axioma and Northfield. Those models handle factor risk attribution, construction constraints and enterprise workflow; MFERM adds the daily macro-versus-idiosyncratic decomposition they don't provide as a primary output — the layer that answers, honestly, how much of today's return was macro beta and how much was skill. It is distributed through Goldman Sachs Marquee and FactSet to institutional clients managing a combined $5 trillion or more.

For long/short equity PMs, CROs and multi-asset risk teams, that distinction is where alpha leakage is either stopped or quietly compounds.

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