ISM PMI and Stock Returns

Some experts cite Institute for Supply Management (ISM) data as an indicator of future stock market performance. Does the ISM data predict stock market returns? According to ISM, their Manufacturing Report On Business, published since 1931, “is considered by many economists to be the most reliable near-term economic barometer available.” The summary component of this report is the Purchasing Managers’ Index (PMI), aggregating monthly inputs from purchasing and supply executives across the U.S. regarding new orders, production, employment, deliveries and inventories. ISM releases the PMI for a month at the beginning of the following month. Presumably, a strong/increasing PMI corresponds to strong stock returns. Using monthly PMI data and the monthly closes of the S&P 500 Index from January 1950 through January 2012 (745 months), we find that:

The following chart shows the monthly behavior of PMI and same-month closing levels of the S&P 500 Index on a logarithmic scale over the entire sample period. The average level of PMI is 53.0. While the relationship appears to be positive much of the time, visual inspection is not helpful in discovering any ability of PMI to predict stock market behavior.

For another perspective, we relate S&P 500 Index monthly return to PMI.

The following scatter plot relates next-month S&P 500 Index return to the monthly PMI over the entire sample period. The Pearson correlation for the two series is -0.07, and the R-squared statistic is 0.00. While there is a very slight negative relationship, the level of PMI explains practically none of next-month stock return. (For same-month data, the Pearson correlation for the two series is -0.03, and the R-squared statistic is 0.00.)

For greater sensitivity, we relate next-month S&P 500 Index return to the monthly change in PMI.

The next scatter plot relates next-month S&P 500 Index returns to monthly changes in PMI over the entire sample period. The Pearson correlation for these two series is 0.00, and the R-squared statistic is 0.00. Monthly changes in PMI therefore offer no information about next-month stock returns. (For same-month data, the Pearson correlation for the two series is 0.12, and the R-squared statistic is 0.01.)

To check for meaningful non-linearity, we rank and segment monthly changes in PMI.

The next chart shows the average next-month S&P 500 Index return by quintile of ranked changes in PMI since 1950 (149 observations per quintile) and since 1990 (53 observations per quintile). The lack of systematic progressions and inconsistencies across the two sample periods undermine belief in any relationship.

Might PMI or change in PMI systematically lead or lag stock returns at intervals longer than one month?

The final chart relates monthly PMI and changes in PMI to stock returns for various lead-lag relationships, ranging from stocks lead PMI/change in PMI by 12 months (-12) to PMI/change in PMI leads stocks by 12 months (12). Results suggest that:

• Stock returns lead PMI with a cumulative positive relationship (higher stock returns indicate higher future PMI) over the intermediate and long terms.
• PMI leads stocks with a weak cumulative negative relationship (rising PMI indicates lower future stock market returns) over the intermediate and long terms.
• Stock returns lead changes in PMI with a positive relationship by about one to three months.
• Changes in PMI have practically no bearing on future stock market returns.

A recent subsample since 1990 generally confirms the persistence of the relationship between stock market returns and changes in PMI.

In summary, evidence from simple tests mostly does not support a belief that ISM’s PMI (measuring U.S. manufacturing activity) is useful for predicting U.S. stock market returns.

Cautions regarding findings include:

• Retroactive adjustments to PMI data may confound measurement of its predictive power for stocks.
• This analysis does not rule out the possibility that surprises in PMI, relative to some measurable expectation, more usefully forecast stock market returns.
• The subsample since 1990 is small in terms of number of economic cycles.

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