Sensitivity Analysis 101

How sensitive is sensitivity analysis?

October 2025. Reading Time: 10 Minutes. Author: Nicolas Rabener.

SUMMARY

  • Sensitivity analysis can highlight portfolio risks
  • However, it is sensitive to data availability and assumptions
  • Focusing on tail betas is sensible

INTRODUCTION

The U.S. stock market is currently being driven by a small group of stocks, creating a concentration risk not seen in decades. While comparisons to the 2000 tech bubble are common, a key difference is that today’s leading companies, such as Microsoft and Apple, are highly profitable businesses.

Still, the Shiller CAPE ratio recently surpassed 40 – a level last reached in 2000 – indicating that valuations are very expensive. A common way to assess portfolio risk is through sensitivity analysis, asking questions like: how much would my portfolio fall if the Nasdaq dropped by 50%?

Sensitivity analysis is typically conducted using regression techniques, which we will explore in this research article.

SINGLE VS MULTIPLE REGRESSION ANALYSIS

We will analyze a value-focused U.S. stock portfolio, represented by the iShares Russell 1000 Value ETF (IWD), and assess the impact of a 30% decline in emerging market stocks, proxied by the MSCI Emerging Markets Index. A conventional approach would be to calculate IWD’s beta relative to the EM Index, but this has two limitations: U.S. value stock returns are poorly explained by emerging market returns, and global stock markets are highly correlated. Therefore, a more realistic scenario is to consider a 30% drop in EM stocks alongside a 10% decline in the S&P 500.

A single-variable regression of IWD on EM stocks produces a beta of 0.55, but the R2 is only 0.47, indicating limited explanatory power. When we expand to a multiple regression including the S&P 500, the beta relative to EM stocks falls to 0.07, while the R² rises to 0.73, reflecting a stronger overall fit.