CAR Reddit Mentions | ChartExchange

a couple weeks ago I tested the classic "buy Home Depot and Lowe's before hurricane season" trade: event study around June 1 season open, 16 years of data. result: the trade loses, roughly -2 to -3% vs the market, and the drift starts about 8 days before the season even opens. posted it to r/stocks [post](https://www.reddit.com/r/stocks/comments/1uoopxk/everyone_knows_the_hurricane_trade_buy_home_depot/) and the pushback was fair: June 1 is a calendar story, not an event. the real test is actual landfalls, with severity and geography separated. so I built it.
**setup:** 23 US mainland hurricane landfalls 2011 to 2024 (Cat 3+ at landfall, or on NOAA's billion-dollar disaster list). landfall dates verified against HURDAT2, with the 2024 storms checked against NHC tropical cyclone reports. day 0 = the first trading session that could actually react, which matters more than you'd think: 13 of 23 landfalls happened after the close, on weekends, or in Sandy's case while the NYSE itself was shut for two days. anchor those wrong and your event window starts before the event. CAPM market model vs the S&P 500, estimation window well clear of each storm. home improvement (HD, LOW) and insurers (ALL, TRV) run separately this time, per feedback. three windows: pre-landfall \[-15,-1\] for positioning as the forecast track firms up, short \[0,+10\] for the plywood spike, long \[0,+60\] for the rebuild wave.
charts: [https://imgur.com/a/ISBeMhv](https://imgur.com/a/ISBeMhv)
**result 1: the rebuild trade still doesn't exist.** home improvement across all 23 events, long window: -1.9%, p=0.56. null. combined with the season-open study, I've now covered everything from 10 days before season start to 60 days after landfall, and the "buy HD and LOW, storms mean rebuilding" theory never shows up anywhere in that timeline.
**result 2: I got a significant result, then killed it myself.** insurers over the long window: +4.8%, p=0.048. counterintuitive, great headline. insurers RALLY after landfall as uncertainty resolves and rates harden. I nearly posted it.
then I ran the robustness check the data was begging for. 2020 had four Gulf landfalls in two months (Laura, Sally, Delta, Zeta). their 60-day windows overlap almost completely, so they're not four observations, they're roughly one, and that one sits inside the sharpest P&C rate-hardening stretch in years. drop overlapping-window events and rerun on the 13 independent ones: +4.4%, p=0.16. gone. the "finding" was one correlated cluster wearing a trench coat.
the same discipline killed my best single data point: HD and LOW up 28% after Beryl hit Houston in July 2024. looks like the rebuild trade in the flesh, except by the September Fed cut the CAR was already +22%, accumulated through August as rate-cut expectations built. home improvers are rate sensitive, and a market model calibrated before the storm can't subtract a macro tailwind that arrives mid-window.
**the one thing that keeps not dying (but bends): metro hits.** when a storm directly impacts a major metropolitan area (Sandy into NYC, Harvey into Houston, Ida into New Orleans...), home improvement shows an immediate spike: +4.2% in the first two weeks, p=0.044 at N=7, and metro vs non-metro separates over the long window at p=0.016. it survives de-clustering directionally too. but I want to show you exactly how fragile it is. the metro classification of Nicholas (2021) is a judgment call: the NHC report says it "moved into the Houston metropolitan area," same logic as Beryl, so I classified it metro. drop that one storm and the numbers become p=0.072 and p=0.065. one borderline observation is holding my only sub-0.05 result above water. so the honest statement is: metro hits show a consistent, theoretically sensible pattern across every specification I ran, and none of it is proven at N=6-7. if the rebuild trade exists at all, it's not "hurricane season" and it's not "landfalls," it's "major storm hits a major city," and those are rare enough that we may never get a clean answer.
also, per the pre-window suggestion from the last thread: no correlation between pre-landfall positioning and the post-landfall move, in either group. the market doesn't front-run landfalls in any way that predicts what follows.
**what I actually learned:** the difference between a finding and an artifact is usually one robustness check nobody wants to run, because it only ever makes your result worse. small event samples cluster in time, and clustered events inherit whatever macro regime they sit in. and when a result does survive, it's worth finding the single observation it hinges on. mine hinges on whether you count one 2021 storm as a Houston hit. if I'd posted the p=0.048 version you'd have upvoted it, and it would have been wrong.
next up: conditioning the season-open selloff on pre-season ACE forecasts, testing whether the June 1 drop scales with how bad the season was predicted to be. that one's for the person who suggested it in the last thread.
*not financial advice. I test market folklore against data. mostly the folklore loses. this time my own result lost too, which seems fair*

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