Indrani De, CFA, PRM
Robin Marshall, M.A., M.Phil
Mark Barnes, PhD
Alex Nae, M.Sc
Correlations of asset returns (CAR) clearly play a key role in asset allocation decisions, given the potential benefits from portfolio diversification. But these correlations are not directly observable, and must be estimated from underlying data sets. In addition, probability theory informs us there may be a link between volatility in returns and measured correlation. Specifically, in periods of higher volatility in returns, measured correlation will be higher, even if the underlying drivers of correlation have not changed.
This has led some to conclude “correlation breakdowns may reflect time-varying volatility of financial markets rather than a change in the relationships between asset returns.” But despite these statistical issues, changes in key macro drivers may also explain changes in CAR, and indeed the underlying volatility in returns, which drives the higher correlations.
In this paper, we attempt to identify key drivers of correlations in returns, using FTSE Russell multi-asset index data since 2000.
Key takeaways:
- Higher correlation of US asset returns has persisted since Covid
- The persistence may be due to higher-for-longer rates and inertia in core inflation
- Only US HY credit shows no structural break in correlation
- Inflation may be a strong driver of the higher correlation in returns, even if the relationship is non-linear
- Less stable correlations suggest investors need vigilance in making asset allocation decisions
Points of differentiation:
- Analysis of multi-asset returns using FTSE Russell multi-asset index data
- Linking correlation of returns analysis to asset class characteristics
- Detailed assessment of the role of inflation in driving higher correlation of returns
- A consistent narrative for why, and how, the correlation of returns has changed since 2000
What our research means for investors?
The paper provides investors with a thorough guide to the evolution of the correlation of US asset returns since the 1990s, and why correlations may be less stable since Covid, and what that means for portfolio models built around the notion of low, and stable, correlations of returns.