There have been many proposed market indicators that seem crazy or at least simplistic “cool stories”, including:

• Whether an NFC team or AFC team won the Superbowl
• The length of cigarette butts
• How full parking lots have been
• Length of skirts

Some such indicators can be dismissed. The sample size might be too small. Or the measurement might be too subjective. But then it gets tricky. What if the statistics are inarguable but the effect still seems weird and implausible?

Which leads us to consider moon phases as an indicator. This was studied by Ilia Dichev and Troy Janes in the paper “Lunar Cycle Effects in Stock Returns.”

They found that stock returns around new moons are significantly higher than those surrounding full moons by examining stock market data from the Dow Jones Industrial Average (DJIA), the S&P 500, NASDAQ, and NYSE-AMEX. Their results showed a clear and consistent pattern: stock returns during the days surrounding a new moon were higher compared to those around a full moon.

For instance, between 1896 and 1999, the mean daily return for the DJIA during the seven days around the new moon was 0.035%, compared to 0.017% during the seven days around the full moon. Although the difference was economically significant, the large standard deviation of daily returns (approximately 1.1%) led to a t-statistic of 0.96, indicating that these results weren’t statistically significant.

However, the results for the S&P 500 were more striking. The study showed that over the period from 1928 to 2000, the mean daily return for the S&P 500 during the new moon was 0.046%, compared to 0.024% during the full moon. While this difference in returns was also marked by a t-statistic of 0.96, the economic implications were notable. For a longer 15-day window, the S&P 500 displayed a difference of 0.017% between new moon and full moon returns, resulting in an annualized difference of around 5%, a figure comparable to the average market risk premium.

This isn’t just a US effect. They also examined 24 other countries and markets.

International markets, in fact, exhibited even stronger lunar cycle effects. For example, in many countries, the mean daily returns around the new moon were more than double those around the full moon. For pooled data across all 24 countries, the new moon return was 0.055% compared to 0.023% around the full moon, with a t-statistic of 3.43, which represents a statistically significant difference at high confidence levels. When looking at this global data, the annualized difference in returns during the new moon versus the full moon ranged from 7% to 10%, numbers that are difficult to ignore.

Studies that use long term data sets and data from different countries are always more compelling than those that don’t. No matter what the statistics tell us, an effect that has persisted for 100 years in dozens of markets deserves some consideration. But it is also nice to know why an effect exists. That way, we can stop trading the effect when the reason goes away.

One theory is that the full moon may induce feelings of pessimism or risk aversion, possibly rooted in superstitions. Conversely, the new moon may be linked to optimism and more aggressive risk-taking. Maybe traders sleep better because their dog isn’t howling at the moon?

But, unless you believe in lycanthropy, no reason seem very convincing. And they are all post-hoc justifications. You wouldn’t start with those ideas as a hypothesis and find the effect from there.

On a scale of one to ten, how much do I believe in this effect? If ten is “stock markets go up” and one is “the winner of the Superbowl matters”, I’d rate this a four.

If you wanted to trade something as a standalone signal, that would be a problem. You would need to scale according to some sort of confidence score. And you would never know when to give up. But in a multi-variate kitchen sink model, this is much less of a problem. Any one signal is of minor importance and as it comes and goes, the model will weight the signal accordingly as part of the adaptive process.

While the lunar cycle’s impact on stock returns might seem more aligned with ancient myths than modern finance, the research by Dichev and Janes demonstrates that the effect is real and economically significant. Stock returns around new moons consistently outperform those around full moons, and this pattern holds across markets worldwide. It is weird, but it seems to have some predictive power.

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