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Every June the same idea comes back around: hurricane season is starting, storms mean damage, damage means rebuilding, rebuilding means Home Depot and Lowe's print money. buy before the season, ride the demand. it sounds so obviously right that people repeat it every year without checking.
so I checked.
**method:** event study around June 1 (Atlantic season open) every year 2010–2025. CAPM market model, abnormal returns vs the S&P 500, \[-10, +10\] trading day window, one-sample t-test on the CARs. standard academic methodology, nothing exotic.
**result:** the trade loses. Home Depot -1.7%, Lowe's -3.1% vs the market on average, positive in only 4 of 16 years. statistically significant at p=0.034. worst years 2021 (-9.8%) and 2025 (-7.2%).
plotting it day-by-day made it worse for the theory: the underperformance starts \~8 days *before* June 1. the market isn't slow to price hurricane season, it's early.
**why the obvious trade fails (my read):**
the rebuilding demand is real, but it's localised and it happens *after* a specific storm hits a specific region. at season open, nothing's been damaged. what the whole market sees on June 1 is five months of catastrophe risk starting, and it's been seeing the exact same "seasonal demand" story every year for decades. it's priced. you're not early to anything, you're the exit liquidity for people who were.
(I also ran insurers: Allstate, Travelers for the same window. also negative, which surprises nobody. the home improvement leg is the one people actually trade on, so that's the headline.)
**the general lesson** that keeps showing up when I test these: sound business logic ≠ tradeable stock pattern. "more storms = more plywood sales" can be completely true and the stock still loses, because the question is never whether the story is right, it's whether you know something the price doesn't.
next up I'm testing whether the rebuild bump shows up if you measure after actual major landfalls instead of season open, my guess is that's where the folk theory really lives, but guessing is the whole problem, so.
happy to share methodology details in comments if anyone wants to poke at it.
*not financial advice, past performance ≠ future results, I just like checking whether market folklore survives contact with data*