Stress Testing Investment Strategies: Combining Historical Data and Projected Assumptions

Why It Matters

Objective, historically grounded stress testing improves portfolio resilience, allowing investors to anticipate and respond to geopolitical, economic, and technological shocks with greater confidence.

Key Takeaways

• Use factor-based models to simplify multi‑asset stress testing.
• Historical events provide realistic shock magnitudes and scenario depth.
• Distinguish geopolitical risk increase from fragmentation for accurate impact.
• Template scenarios in FactSet help clients customize stress tests quickly.
• AI and policy events require thematic scenarios beyond traditional shocks.

Summary

The FactSet Insight podcast with Christina Brattonova focuses on how investors can stress‑test portfolios by blending historical data with forward‑looking assumptions. Brattonova explains that rather than shocking each security individually, a multi‑asset factor‑based framework uses representative indices—market, regional, industry, style, commodity—to capture the drivers of price volatility. By assigning correlated shocks to these factors and layering multiple historical events of varying magnitude, analysts create realistic, objective scenarios that reflect both the depth and breadth of potential market disruptions.

Key insights include the use of historical analogues to calibrate shock size, the grouping of events by severity, and the distinction between short‑term geopolitical risk spikes and longer‑term geopolitical fragmentation. This approach yields three advantages: realistic assumptions grounded in actual market reactions, noise reduction through multiple observations, and coverage of diverse outcome paths. The methodology was illustrated with recent Iran‑related tensions, where a “risk‑increase” scenario predicted modest equity losses (≈1%) and bond resilience, while a “fragmentation” scenario forecasted double‑digit equity declines and broader bond drops—outcomes that closely matched market movements in the weeks that followed.

Clients benefit from FactSet’s ready‑made template scenarios, which can be quickly deployed and further tailored with bespoke shocks—such as commodity spikes or AI‑related regulatory changes. The podcast also highlighted thematic stress tests for economic (inflation, recession), political (elections, tariffs), and technological (cyber‑attacks, AI hype) drivers, demonstrating the platform’s flexibility across a spectrum of uncertainty sources.

The broader implication is that investors gain an objective, data‑driven lens for portfolio resilience, enabling faster decision‑making when shocks materialize. By integrating factor‑based modeling with historically anchored magnitude tiers, firms can move beyond speculative assumptions and align risk management with observable market dynamics.

Original Description

When a dynamic operating environment poses uncertainty across financial markets, scenario analysis and portfolio stress testing can help financial professionals model potential impacts on their investment strategies. In this episode, FactSet Principal Product Manager of Risk Kristina Bratanova-Cvetanova, CFA, discusses how to determine the appropriate shock factors, the use of historical scenarios and data, and incorporation of your own assumptions to assess portfolio risk and potential outcomes.

Recorded March 17, 2026, at 10:00 a.m. ET.

The FactSet Insight podcast is for informational purposes only. The information contained within is not legal, tax, or investment advice. FactSet does not endorse or recommend any investments and assumes no liability for any consequence relating directly or indirectly to any action or inaction taken based on the information contained in this podcast episode. The views shared by third-party contributors do not necessarily reflect the opinion of FactSet.

© FactSet Research Systems Inc. All rights reserved.