"100 minus your age in stocks" is terrible advice. Here's why—and what actually works.
A glide path is how your asset allocation changes over time. Instead of a static 60/40 portfolio forever, you adjust the mix as you approach and move through retirement.
Target date funds use glide paths. So do smart retirees.
Example glide path:
| Age | Stocks | Bonds |
|---|---|---|
| 30 | 90% | 10% |
| 40 | 80% | 20% |
| 50 | 70% | 30% |
| 60 | 60% | 40% |
| 70 | 50% | 50% |
| 80 | 40% | 60% |
The logic: reduce risk as you have less time to recover from crashes.
But this conventional wisdom has a problem.
The standard declining glide path (more conservative as you age) actually increases your chance of running out of money.
Why? Sequence of returns risk cuts both ways.
A crash early in retirement is devastating. But so is being too conservative when you're 80 and might live another 20 years.
Research by Wade Pfau and Michael Kitces found that a rising equity glide path—starting conservative and becoming more aggressive—actually improved success rates in many scenarios.
Why rising works:
If you retire with 40% stocks and the market crashes in year 1, you lose less. Then you gradually increase stocks when your portfolio has survived the danger zone.
If the market does well early, you miss some upside—but you were never at risk of the worst-case scenario.
The "best" glide path depends on:
Monte Carlo simulation can test different glide paths and show which one maximizes your success probability.
Example comparison:
| Glide Path | 30-Year Success Rate |
|---|---|
| Static 60/40 | 82% |
| Declining 80 to 40 | 79% |
| Rising 40 to 70 | 87% |
In this scenario, the rising glide path wins—but your numbers might be different depending on assumptions.
Vanguard, Fidelity, and Schwab offer target date funds with built-in glide paths. Easy but inflexible—you get their glide path, not one optimized for your situation.
Set calendar reminders to adjust allocation annually. Check your target, rebalance, done.
Use a calculator that can test multiple glide paths against Monte Carlo simulation. Find the one that maximizes success for your numbers.
Don't just pick a number. Test it.
QuantCalc's glide path optimizer tests allocation strategies and finds the one that maximizes your success probability.
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