Home Affordability SimulatorBuy the house without giving up early retirement

Sequence-of-returns risk is a home-buying problem

Sequence-of-returns risk is usually explained as a retirement problem: two retirees earn the same average return over thirty years, but the one who hits a bear market in the first few years — while withdrawing — runs out of money, and the one who hits it late doesn't. The order of returns matters whenever money is moving in or out of the portfolio. Which is why it's also, under-appreciatedly, a home-buying problem: a down payment is the single largest withdrawal most people ever make.

The withdrawal you don't call a withdrawal

Buying a $650,000 home with 20% down means pulling roughly $150,000–$170,000 out of your taxable account in one day — down payment, closing costs, and the capital-gains tax bill that selling appreciated shares to fund them triggers. From your portfolio's perspective this is exactly a retiree's worst-case: a massive withdrawal at a fixed date you don't get to choose based on market conditions.

Now run the two orderings. If markets deliver their bad years after your portfolio has recovered and compounded, you're fine. If the crash lands the year after closing — when your buffer is at its lifetime minimum and your fixed costs just jumped — the same average return produces a completely different life. You may be forced to sell more shares, at the bottom, to cover a payment that no longer fits a reduced income. In the worst futures, you sell the house itself into a depressed market and pay 6% in selling costs for the privilege.

Correlation makes it worse than the retirement version

The retiree's sequence risk is about one asset. The buyer's involves three correlated ones: equities, home prices, and their own paycheck. 2008–2012 is the canonical example — stocks and home values fell together, and layoffs spiked at the same time. The model behind this site encodes all three linkages: home prices are drawn correlated with market returns, and the job-loss hazard multiplies (3× by default) in any year the market falls more than 15%. When you simulate futures with those correlations on, the dangerous scenarios stop being independent bad-luck lotteries and start clustering — which is exactly what makes a purchase price that looks fine on average unsafe in the tail.

What actually protects you

Price, not prediction. You can't time the crash, but you can choose a price whose bad futures are survivable. Every dollar of price is leverage: a smaller purchase means a smaller withdrawal at the worst possible moment, a bigger surviving buffer, and a payment a reduced income can still carry.

A buffer that survives closing. The most fragile position isn't a high payment — it's an empty taxable account the morning after you get the keys. If funding the closing table takes your liquid savings to zero, the simulation will show you exactly which futures punish that.

Testing the plan against the cluster, not the average. A spreadsheet with a steady 7% return literally cannot represent this risk — sequence risk vanishes when every year is identical. It only appears when futures are drawn path by path. That's what the simulator does: thousands of orderings of returns, home prices, and layoffs, with the failures counted honestly. The output worth staring at is the failure panel — how plans break at a given price tells you more than any average outcome.

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