Measuring Macro Sensitivity

Putting macro variables under the microscope

August 2025. Reading Time: 10 Minutes. Author: Abhik Roy, CFA.

SUMMARY

  • Macro variables affect portfolios differently
  • Betas and R2 vary significantly with lookback and frequency
  • GDP growth and inflation require unrealistic long track records to be useful

INTRODUCTION

On 2nd April 2025, a date that Mr. Trump dubbed the “Liberation Day”, a sweeping new tariff regime was introduced creating a swift reaction in the markets in the days that followed with the S&P 500 falling by nearly 12%. This led to a tit-for-tat escalation by many of the major trading partners of the U.S. such as China and Canada. Even after four months of multiple negotiations and pauses, the tariff saga still remains a dynamic and expanding issue.

Economists across the world started commenting on these events and probable outcomes for the U.S. and the world. A common sentiment that echoed throughout was rising inflation and an imminent recession. Given this consensus, investors might want to start positioning their portfolios for these changes, but then the question arises, “How much is my portfolio actually affected?”

In this article, we will examine how to measure the relationship between macro variables and portfolios, and compare the different options available.

R-SQUARED VS SENSITIVITY

While sensitivity, or beta, is a common starting point for measuring these relationships, its dependency on the volatility ratio of the variables can result in figures that are artificially high or low. Furthermore, beta offers little insight into the reliability of the relationship, so we will primarily focus on the R2 where a higher value denotes more explainability.

To measure the beta and R2, we must first determine the appropriate lookback period and data frequency. While a longer lookback and lower frequency gives more long-term stable estimates, investors often do not have the luxury of extensive historical data and must rely on shorter timeframes. Does this render the resulting estimates unreliable?

To test this, we will create four portfolios in the U.S. – a 100% equity, 100% bond, 100% commodities and a traditional 60/40 equity/bond mix. Then we measure the R2 of each portfolio by regressing them against a set of macroeconomic variables across variou