Weather and investing: how sunshine skews stock returns
- Robin Powell
- 4 minutes ago
- 6 min read
The poor returns of speculative 'lottery-like' stocks are concentrated in the months after sunny weather in the cities where those firms are based, according to new research. The link between weather and investing, it seems, runs deeper than the mood-lifting cliché.
Whatever investors disagree about, most take one thing for granted: prices are moved by information. Earnings, interest rates, takeover rumours, central bank announcements — the raw material of every valuation model and every market report is news about companies and the economy. On that view, weather and investing should have nothing to do with each other.
A peer-reviewed study of 37 years of Nasdaq data complicates that assumption. Reza Bradrania and Ya Gao of the University of South Australia have found a well-documented return pattern that switches on and off with something no valuation model contains: the cloud cover above company headquarters. Their paper, published in the Journal of Behavioral and Experimental Finance in 2024, reports that the poor performance of speculative stocks 'mainly exists following sunny weather'. After cloudy spells, it largely disappears.
What lottery stocks are — and why they disappoint
The finding rests on two pieces of background. The first is the idea of a lottery-like stock: a share offering a small chance of a very large gain. Investors — and even some professional fund managers — are drawn to these stocks for the same reason people buy lottery tickets, and they tend to overpay for them.
The second is how researchers measure that appeal. In 2011, Turan Bali, Nusret Cakici and Robert Whitelaw proposed a simple proxy they called MAX: a stock's single best daily return over the previous month. Stocks with the biggest recent one-day spikes, they showed, go on to underperform. The pattern has become known as the MAX effect.
It holds in Bradrania and Gao's sample too. The stocks with the highest MAX scores underperformed those with the lowest by an average of 1.06 per cent per month on a value-weighted basis, and the gap widens once risk is taken into account.
These are not household names. The median stock in the study's highest-MAX group traded at $3.22 with a market value of around $61 million, against $15.14 and $334 million in the lowest group. Small, cheap and illiquid, they are the natural habitat of the hopeful punt.
What the new research found
Bradrania and Gao's contribution was to ask when the MAX effect does its damage. They assembled every Nasdaq common stock from January 1983 to December 2019 whose company was headquartered in one of the ten US metropolitan areas with the most Nasdaq listings — an average of 4,609 firms at any one time. Nasdaq was a deliberate choice: earlier research by Tim Loughran and Paul Schultz had found that trading in Nasdaq stocks is unusually localised, so the weather where a firm is based plausibly reaches the people trading its shares.
The weather itself came from hourly cloud-cover readings taken at each city's main airport, recorded by the US National Oceanic and Atmospheric Administration between 6am and 4pm, averaged over each month and adjusted for seasonal patterns. A month with unusually low cloud cover counts as sunny; one with unusually high cover counts as cloudy.
The split in the results is the heart of the paper. Following sunny months, the high-MAX portfolio underperformed the low-MAX portfolio by 1.83 per cent per month — a gap that is both large and statistically significant. Following cloudy months, the difference was 0.04 per cent, indistinguishable from zero. On a risk-adjusted basis the contrast is much the same: an underperformance of 1.98 per cent per month after sunshine, against 0.19 per cent after cloud.
The pattern survives across every alternative threshold the authors used to define sunny and cloudy months, though the gap narrows at looser definitions. In their combined tests, which use the full sample rather than splitting it, the conclusion is summarised in a single sentence: 'the MAX effect is doubled following sunny weather'.
The evidence on weather and investing
This is not the first time researchers have connected weather and investing. In 1993, Edward Saunders reported a link between New York cloud cover and Wall Street returns. A decade later, David Hirshleifer and Tyler Shumway found sunshine positively correlated with daily returns across 26 stock exchanges between 1982 and 1997.
The proposed mechanism runs through mood. Sunshine lifts it; people in better moods judge prospects more optimistically and take more risk; and that extra appetite flows towards the most speculative corner of the market, pushing prices of lottery-like stocks up and their subsequent returns down.
That story also explains a curious asymmetry in the results: the effect concentrates after good weather rather than bad. Bradrania and Gao point to psychological research suggesting that optimistic moods distort judgement more powerfully than pessimistic ones — people feeling good rely more on gut feel, while people feeling flat scrutinise.
The finding does not depend on cloud cover alone. The pattern repeats when pleasant weather is measured as less rain or less wind, and — more weakly, at borderline significance — as higher temperature.
Where the evidence has limits
The study has boundaries worth respecting. The design leans on the assumption that the people trading a firm's shares live near its headquarters. The localised-trading evidence dates from 2004, and the sample ends in December 2019 — before commission-free trading apps completed the nationalisation of American retail investing. Whether the pattern survives the post-2020 era is untested. And Loughran and Schultz, whose work underpins the design, themselves found little evidence that cloudy weather affects returns — a point Bradrania and Gao acknowledge.
Second, the paper shows an association, not a mechanism. The authors could not observe individual buying and selling, and say plainly that the risk-taking channel is a conjecture left for future research to test.
Third, the premise itself is now debated. In a January 2026 working paper titled 'MAX on steroids', Turan Bali — a co-author of the original MAX paper — together with Baris Ince and Han Ozsoylev argues that the plain MAX anomaly largely reflects mispricing tied to equity issuance rather than lottery demand, and that MAX is contaminated by market beta (a stock's sensitivity to moves in the wider market). Their cleaned-up measure still finds a lottery effect, strongest in stocks dominated by retail investors — so the lottery preference survives, but plain MAX may not be a clean measure of it. The two papers are not flatly contradictory: the newer study finds mispricing intensifies when sentiment runs high, which rhymes with a mood story. But a reader should know the lottery interpretation of MAX is contested, partly by the anomaly's own originator.
A pattern you cannot trade
None of this amounts to a strategy. Even far bigger anomalies have proved very hard to trade profitably, and this one carries every classic obstacle. The return gap lives in small, cheap, illiquid stocks; the paper does not test whether it would survive trading costs; and its authors present the result as an explanation of mispricing, not an invitation to check the forecast before placing an order.
What the study does offer is evidence that risk appetite moves with influences investors neither choose nor notice. Nobody decides to pay more for a speculative stock because the week has been bright. It appears to happen anyway. That is an argument for investment processes that do not depend on how anyone feels on the day — rules set in advance about what to buy, how much and when.
The case for rules-based investing has never rested on the weather. It turns out even the weather makes it.
Resources
Bali, T. G., Cakici, N., & Whitelaw, R. F. (2011). Maxing out: Stocks as lotteries and the cross-section of expected returns. Journal of Financial Economics, 99(2), 427–446.
Bali, T. G., Ince, B., & Ozsoylev, H. N. (2026). MAX on steroids: A new measure of investor attraction to lottery stocks. SSRN Working Paper No. 6065166.
Bradrania, R., & Gao, Y. (2024). Lottery demand, weather and the cross-section of stock returns. Journal of Behavioral and Experimental Finance, 42, 100910.
Hirshleifer, D., & Shumway, T. (2003). Good day sunshine: Stock returns and the weather. The Journal of Finance, 58(3), 1009–1032.
Loughran, T., & Schultz, P. (2004). Weather, stock returns, and the impact of localized trading behavior. Journal of Financial and Quantitative Analysis, 39(2), 343–364.
Saunders, E. M. (1993). Stock prices and Wall Street weather. American Economic Review, 83(5), 1337–1345.
Investing whatever the weather
If this article has a practical message, it is that good investing runs on rules rather than moods. How to Fund the Life You Want, by TEBI editor Robin Powell and Jonathan Hollow, shows UK readers how to build exactly that kind of plan: rules-based, low-cost and designed to hold up on the days when feelings argue otherwise. Bloomsbury published the second edition; it is available on Amazon.
For readers who would rather have a professional keep the rules for them, TEBI's Find an Adviser directory lists advisers who have publicly committed to evidence-based investing.