FactSet

Stress Testing Investment Strategies: Combining Historical Data and Projected Assumptions

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.