Even the most rigorous bottom-up investment process is influenced—sometimes significantly—by the macroeconomic backdrop. Valuation multiples expand or contract as interest rates and growth expectations shift. Earnings quality, growth sustainability, and competitive dynamics are all affected by macro tailwinds or headwinds. Most portfolios—whether concentrated or diversified—contain unintentional macro exposures, such as sensitivity to the yield curve, inflation expectations, or commodity prices. Qi’s analysis of hundreds of fundamental equity portfolios has shown that 50–80% of quarterly returns can be explained by macro factors. Understanding and managing these exposures does not diminish a manager’s fundamental edge; instead, it sharpens it by isolating genuine alpha from macro-driven noise and allowing managers to make more deliberate risk-reward decisions.

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Qi complements traditional style factor models. While Axioma decomposes risk into style factors, Qi decomposes risk into macro factors. One can connect style and macro by using Qi to reveal the macro forces driving style and other thematic factors. Qi can also be used“side by side” with traditional equity fundamental factor models. It provides a macro lens to view your overall portfolio exposure and risk. Most clients use both. This dual approach provides deeper insights into portfolio behavior, especially during regime shifts.

They complement each other within your risk process.

Use both for comprehensive risk intelligence. Style models identify your exposures to factors like value and momentum; Qi explains your portfolio in terms of macro factors. Qi can also show the macro drivers of style factors. For example, knowing your portfolio has high momentum exposure is valuable—understanding what macro conditions drive momentum's performance is transformative.

Most clients integrate Qi through:

• A dedicated "Macro Risk" section showing factor sensitivities and contributions
• Enhanced attribution that includes macro alongside traditional breakdowns
• Scenario analysis showing potential impacts from specific macro shifts
• Risk alerts when factor relationships deviate from historical patterns

We provide templates aligned with standard risk frameworks, ensuring
seamless integration without disrupting existing workflows.

Our data, insights and analysis translate directly into portfolio actions in variety of ways.
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Managers can:
- Adjust tactical allocations based on changing macro sensitivities
- Hedge specific macro risks rather than broadly de-risking
- Time entries and exits based on regime awareness
- Build balanced portfolios that avoid concentrated macro bets
- Allocate risk budgets to high-conviction themes while controlling unintended exposures

Example:
before the 2022 slowdown, a client identified heightened growth sensitivity and implemented targeted sector rotations and overlay hedges. This reduced drawdowns by 40% relative to their benchmark while preserving alpha opportunities.

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We use daily real GDP “Nowcasts” to give us a point-in-time real GDP estimate every day. These Nowcasts are econometric models that take in all the economic data releases and update the most likely real GDP for the current quarter. There are Nowcasts for all major economies.

MFERM enables long/short managers toexplicitly monitor and control macro risk within their portfolios. By quantifying sensitivities to key macro factors, managers can set explicit macro risk limits, ensure that idiosyncratic alpha is not eroded by unintended macro bets, and time adjustments to gross and net exposures based on changes in the macro risk environment. This is particularly valuable in avoiding drawdowns during adverse macro shocks without unnecessarily cutting positions that still have strong fundamental merit.

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Our selection process balances rigor with relevance:

• Economic significance (clear financial theory connection)
• Statistical validation (persistent explanatory power)
• Independence (minimal overlap between factors)
• Cross-asset relevance (explanatory power across markets)
• Stability analysis (predictive value across regimes)

Qi treats macro variables as exogenous toindividual securities—meaning macroeconomic trends exist independently of the company’s internal fundamentals but still exert significant influence over asset prices. While equities possess fundamental drivers such as earnings growth, margins,and competitive positioning, they do not inherently have macro traits.

To capture the impact of macro forces, Qi employs a robust Partial Least Squares Regression (PLSR) algorithm, which is specifically designed to address the high multicollinearity often found among macroeconomic variables. This statistical approach ensures stable and intuitive estimates of portfolio sensitivities,even when factors are highly correlated. Factor selection is guided by a seasoned team of macro strategists, portfolio managers, and data scientists, ensuring the inclusion of both economically meaningful and empirically robust variables.

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