DJIA-Gold Ratio as a Stock Market Indicator

May 5, 2014 • Posted in Gold, Technical Trading

A reader requested a test of the following hypothesis [presented by Simon Maierhofer, co-founder of ETFguide] from the article “Gold’s Bluff – Is a 30 Percent Drop Next?”: “Ironically, gold is more than just a hedge against market turmoil. Gold is actually one of the most accurate indicators of the stock market’s long-term direction. The Dow Jones measured in gold is a forward looking indicator.” To test this assertion, we examine relationships between the spot price of gold and the level of the Dow Jones Industrial Average (DJIA). Using monthly data for the spot price of gold in dollars per ounce (London 3:00 PM fix) and DJIA over the period January 1971 through March 2014 (519 months), we find that:

The following chart plots the ratio of the level of DJIA to the price of gold in dollars per ounce (DJIA/gold) over the entire sample period. The ratio ranges from 1.3 at the end of January 1980 to 42.2 at the end of August 1999, with an average value of 12.8 over the entire sample period. Its value at the end of March 2014 is 12.7. Visual inspection suggests that, while the ratio may be very slowly mean reverting, the sample period is too short to determine a reliable mean or periodicity (if any).

To test predictive power, we first relate monthly level of DJIA/gold to next-month change in DJIA.


The following scatter plot relates next-month return on DJIA to monthly value of DJIA/gold over the entire sample period. The Pearson correlation for the two series is -0.05 and the R-squared statistic 0.003, indicating that the monthly level of DJIA/gold explains less than 1% of the variation in DJIA the following month. In other words, the ratio of DJIA level to spot gold price is not a useful indicator at a one-month forecast horizon.

The Pearson correlation between next-monthly change in gold price and monthly value of DJIA/gold is 0.00 and the R-squared statistic 0.000, indicating no relationship.

To test for an exploitable non-linearity, we calculate average future DJIA returns by ranked fifth (quintile) of DJIA/gold.


The next two charts summarize average next-month returns for DJIA (upper chart) and gold (lower chart) by quintile of DJIA/gold over the entire sample period and two equal subperiods (break point at end of July 1992). There are 103-104 observations per quintile for the total sample.

While variation in average future DJIA monthly returns across quintiles is not completely systematic, returns for the highest fifths of DJIA/gold observations are the lowest for the entire sample period and the subperiods. However, subperiod results differ noticeably from each other and from the results for the entire sample period.

The DJIA/gold ratio quintiles show no ability to predict average future monthly returns for gold.

Note that these analyses are in-sample, meaning that an investor would need foresight through the end of the sample period to trade on this information during the sample period. A realistic investment scenario would limit an investor to past data only, and the sample is scant from that out-of-sample perspective. For example, an investor operating in the 1980s would have calculated a much lower mean for DJIA/gold than an investor operating in the 2000s.

Might DJIA/gold work more convincingly at an annual forecast horizon?




The next scatter plot relates next-year DJIA and gold returns to end-of-year DJIA/gold over the entire sample period (42 annual returns).

The Pearson correlation for future DJIA returns is -0.20 and the R-squared statistic 0.04, indicating that end-of-year DJIA/gold explains about 4% of DJIA return the following year. In other words, a low (high) DJIA/gold is a little bit predictive of a strong (weak) stock market at a forecast horizon of one year.

The Pearson correlation for future gold returns is 0.02 and the R-squared statistic 0.00, indicating that end-of-year DJIA/gold explains none of gold return the following year. In other words, stocks and not gold drive any reversion in DJIA/gold at an annual horizon.

The average annual return for DJIA for the 20 years with the lowest (highest) values of DJIA/gold is 9.6% (7.5%). However, excluding either the best (1975) or the worst (2008) year for DJIA during the sample period makes the highest values of DJIA/gold beat the lowest values. In other words, a single extreme year alters the conclusion, demonstrating the fragility of any predictive power.


In summary, evidence from the past 43 years offers little support for belief that the ratio of DJIA to gold price usefully predicts stock market returns and no support for belief that the ratio predicts gold returns.

Use of gold prices before 1971 would have little incremental value since: “On March 17, 1968, …the price of gold on the private market was allowed to fluctuate…[, and] in 1975…the price of gold was left to find its free-market level.”

Cautions regarding findings include:

  • As noted, the available sample of free market gold prices may be too short to expose a reliable DJIA-gold relationship (which, if it exists, may be too long to be useful to most investors). Potential wildness in stock and gold price behaviors exacerbates the scantness of the available data.
  • Also as noted, the above analyses are in-sample. An investor operating in real time during the sample period would have had even less historical data to use for estimating future returns.
  • Because of weak and inconsistent evidence, the above analyses test no trading strategies based on DJIA/gold.
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