Practical analysis for investment professionals
25 May 2023

Do Sentiment Metrics Matter to the Markets?

Consumer spending accounts for almost 70% of nominal US GDP. As such, consumer sentiment ought to have some correlation with market performance.

Financial journalists certainly act as though it does. Whenever new sentiment or confidence numbers — consumer or otherwise — are released, pundits spring into action, speculating on what the data’s implications are for the markets and the overall economy. But how much do these measures actually matter to market performance?

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To answer this question, we explored the correlations between consumer and business sentiment metrics and market returns. Specifically, we examined monthly data from the University of Michigan Consumer Sentiment Index, the Conference Board’s US Consumer Confidence Index (CCI), and the Business Confidence Index (BCI) and compared their relationship to the performance of nine different MSCI stock and bond indices going back to the 1970s, focusing on US high-yield bonds, US long-term bonds, US short-term bonds, US aggregate fixed income, US growth equity, US value equity, US small cap, US large cap, and international equity. 

In aggregate, we did not find any significant or sustained correlation between market returns and the three sentiment measures over the entire 50-plus year sample period. The highest correlation, between the University of Michigan Consumer Sentiment Survey and US small-cap stocks, maxed out at a weak 0.21.

Correlations between Changes in Consumer Confidence Indices and Investment Returns, 1970s to 2020s

Michigan Consumer
Sentiment Index
Consumer Confidence
Index (CCI)
Business Confidence
Index (BCI)
US High-Yield Bond0.180.17–0.01
US Long-Term Bond–0.010.04–0.10
US Short-Term Bond–0.010.03–0.11
US Fixed Income–0.010.08–0.13
US Growth0.140.120.07
US Value0.170.150.07
US Small Cap0.210.140.11
US Large Cap0.150.150.06

Yet over time, the correlations exhibit some illuminating trends.

The University of Michigan Consumer Sentiment Index’s correlation with equity returns has diminished. Indeed, since 2010, it has fallen precipitously and been statistically indistinguishable from zero.

University of Michigan Consumer Sentiment Index: Historical Market Correlations

US High-Yield Bond0.24–0.050.340.35–0.090.20
US Long-Term Bond0.24––0.13–0.07
US Short-Term Bond0.23–0.09–0.090.05–0.160.14
US Fixed Income0.22–0.15–0.010.13–0.180.09
US Growth0.–0.04–0.05
US Value0.–0.070.01
US Small Cap0.080.330.180.360.000.04
US Large Cap0.–0.03–0.02

The CCI, however, has displayed the greatest positive correlation to equity returns since the 2000s. And since 2020, equity correlations and bond correlations have averaged a rather significant 0.30.

Consumer Confidence Index (CCI): Historical Market Correlations

US High-Yield Bond0.250.0140.
US Long-Term Bond0.090.01–0.04–0.02–0.090.26
US Short-Term Bond0.04–0.04–0.09–
US Fixed Income0.160.03–0.07–
US Growth0.
US Value0.04–
US Small Cap0.
US Large Cap–

The BCI shows a similar trend. The BCI has charted its highest positive correlations with the equity return measures, with the upswing beginning in the 2010s.

The Business Confidence Index (BCI): Historical Market Correlation

1970s1980s 1990s2000s2010s2020s
US High-Yield Bond–0.29–
US Long-Term Bond–0.35–0.21–0.110.05–0.060.09
US Short-Term Bond–0.12–0.17–
US Fixed Income–0.39–0.18–
US Growth0.14–
US Value0.05–
US Small Cap0.13–
US Large Cap0.06–

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That markets correlate more with the CCI and BCI than the University of Michigan Consumer Sentiment Index has several potential implications. Perhaps the CCI and BCI have grown in prestige over time relative to the Michigan index and now the market pays more attention to them. Or maybe their methodologies better reflect an evolving market and economy.

Of course, whatever the roots of these phenomena, the larger takeaway given the relative weakness of these correlations is that financial journalists and commentators may derive more meaning from these metrics than they warrant.

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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

Image credit: ©Getty Images / Natee Meepian

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About the Author(s)
Derek Horstmeyer

Derek Horstmeyer is a professor at George Mason University School of Business, specializing in exchange-traded fund (ETF) and mutual fund performance. He currently serves as Director of the new Financial Planning and Wealth Management major at George Mason and founded the first student-managed investment fund at GMU.

Yuge Pang

Yuge Pang is a recent graduate of George Mason University School of Business with a concentration in finance. She is interested in valuation and data analysis and plans to study for a master's degree and pursue the CFA charter. She is also a dean's list student and FNAN & FPWN Honors Program member. She served as a Montano Student Investment Fund analyst and participated in the CFA Institute Ethics Challenge in Spring 2022.

Kexin Xu

Kexin Xu is a recent graduate of George Mason University School of Business with a concentration in finance. She is interested in commodities trading in the financial services industry and will be starting a quantitative commodities trading internship at a steel trading company. She plans to pursue the CFA charter in the near future. She served as a member of the Montano Student Investment Fund in an analyst role during her time at George Mason and participated in the CFA Institute Equity Research Challenge in Spring 2023.

2 thoughts on “Do Sentiment Metrics Matter to the Markets?”

  1. Luis G. says:

    Why was a correlation used rather than a regression using different lagged periods? The sentiment index this month and market returns 1 month later, 3 months later and maybe one year later.

  2. Kirk Cornwell says:

    “Sentiment metrics” are examples of information cited by the media that are right (correlate) some of the time so they keep citing them. It’s similar to the suggestion that there are only “sellers” on down days and “buyers” on up days. Your bottom line conclusion is right on.

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