Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for January 2021 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for January 2021 (Final)
1st ETF 2nd ETF 3rd ETF

CPI and Stocks Over the Short and Intermediate Terms

| | Posted in: Economic Indicators

Do investors reliably react over short and intermediate terms to changes in the U.S. Consumer Price Index (CPI), a logical measure of the wealth discount rate? Using monthly total and core (excluding food and energy) CPI releases (for all items, not seasonally adjusted) from the Bureau of Labor Statistics (BLS) and contemporaneous S&P 500 Index opens and closes during mid-January 1994 (earliest available CPI release dates) through mid-September 2020 (321 releases), we find that:

The following chart plots total CPI and the S&P 500 Index based on monthly data (the open on CPI release days for the stock index) over the full sample period. While stocks and CPI sometimes move in opposite directions and both series drop noticeably during Fall 2008, visual inspection reveals no systematic relationship. For a closer look, we relate change in CPI to stock market return over short and intermediate intervals.

The following two scatter plots relate S&P 500 Index release-day return (open to close, upper chart) and 5-day future return (open on release day to close four trading days later, lower chart) to monthly change in total CPI over the full sample period.

  • For release-day return (upper chart), the Pearson correlation is 0.018 and the R-squared statistic is 0.000, indicating no relationship.
  • For 5-day future returns (lower chart), the Pearson correlation is 0.024 and the R-squared statistic is 0.001, indicating practically no relationship.

Statistics for changes in core CPI are slightly stronger, with Pearson correlation -0.040 (R-squared 0.002) for same-day return and Pearson correlation 0.041 (R-squared 0.002) for 5-day return. However, these relationships are still very weak.

Results offer practically no support for belief that investors react to CPI releases in a systematic way over the short term.

In case there is an interesting non-linearity, we look at average 5-day stock market returns by range of changes in CPI.

The next chart summarizes average S&P 500 Index 5-day future returns by ranked fifth (quintile) of changes in total and core CPI over the full sample period. Each quintile consists of 64-65 observations. While there is some indication that the stock market likes big increases in CPI, differences in results between total and core CPI and lack of systematic progressions across quintiles undermine belief in reliable relationships.

What about monthly stock market reactions to CPI releases?

The next scatter plot relates next-month S&P 500 Index return (from open to open on successive CPI release days) to monthly change in CPI over the full sample period. The Pearson correlation is 0.03 and the R-squared statistic is 0.001, indicating practically no relationship.

In case there is interesting non-linearity, we look at next-month average stock market returns by range of changes in CPI.

The next chart summarizes average S&P 500 Index next-month return by quintile of monthly changes in total CPI over the sample period, with one standard deviation variability ranges. Each quintile consists of 63-64 observations. Rather than a progression of returns by quintile, results indicate that investors prefer moderate changes in CPI to extreme changes. Results also indicate that variability in investor response is high for extreme changes in CPI.

Is there any other notable lead-lag relationship between monthly change in CPI and monthly stock behavior?

The next chart plots Pearson correlations for various lead-lag relationships between monthly change in CPI and monthly S&P 500 Index return (between CPI release dates) over the full sample period, ranging from stock market return leads change in CPI by 12 months (-12) to change in CPI leads stock market return by 12 months (12). Results weakly suggest that relatively strong (weak) stock returns lead relatively relatively high (low) CPI growth a few months later.

There is some persistence in monthly lead-lag correlations. What if the relationship is cumulative, significant not for monthly changes but for quarterly changes?

The next scatter plot relates next-quarter S&P 500 Index return (from open to open on quarterly CPI release days) to  quarterly change in CPI over the full sample period. Sample size is 106 quarters. The Pearson correlation is -0.06 and the R-squared statistic is 0.003, indicating no material relationship.

In case there is an interesting non-linearity, we look at next-quarter average stock market return by range of changes in CPI.

The next chart summarizes average S&P 500 Index next-quarter return by tercile (ranked thirds) of quarterly changes in total CPI over the full sample period, with one standard deviation variability ranges. Each tercile consists of only 35 observations. There is no consistent indication of investor preference for growth in CPI, though investor responses are relatively variable for the smallest changes in CPI.

Is there any notable lead-lag relationship between quarterly changes in CPI and quarterly stock market behavior?

The final chart plots Pearson correlations for various lead-lag relationships between quarterly change in CPI and quarterly S&P 500 Index return (between CPI release dates) over the full sample period, ranging from stock market return leads change in CPI by six quarters (-6) to change in CPI leads stock market return by six quarters (6). Results suggest that:

  • Relatively strong (weak) stock returns lead to relatively high (low) growth in CPI the next quarter.
  • Relatively high (low) CPI growth represents a slight headwind (tailwind) for the stock market during the next year.

In summary, evidence from a variety of simple tests offers very little support for belief that U.S. CPI data alone is useful for short-term or intermediate-term timing of the broad U.S. stock market.

Cautions regarding findings include:

  • Tests are in-sample. An investor operating in real time may draw different conclusions. In-sample test results are too weak to motivate out-of-sample testing.
  • Subsample sizes for non-linearity tests are modest.
  • The above analysis may contain some revision bias due to occasional BLS adjustments of old data.
  • Analyses do not rule out the possibility that surprises in CPI changes, relative to some measurable expectation, usefully forecast stock market returns.

See also “PPI and the Stock Market” and “CPI-to-PPI Ratio and the Stock Market”.

Login
Daily Email Updates
Filter Research
  • Research Categories (select one or more)