7 articles on monte carlo & projections
Monte Carlo retirement planning: what 1,000 lifetimes show that one projection hides
Monte Carlo retirement planning on 1,000 simulated lifetimes: the median ends at $1.08M after 30 years, but 10.4% run out. What a 7% projection hides.
Why 90% chance of success is the right goal and 100% is a trap
90% chance of success vs 100%: rigid 3.95% hits 90% on 1,000 paths. 2% still only 99.4%. 100% is not on the grid.
Probability of success vs projected balance
Probability of success vs projected balance on 1,000 shared paths: 2% prints 99.4% and $1.89M median; 6% prints 63.0% and $308k.
Monte Carlo vs Historical Backtesting in Retirement Plans
Monte Carlo vs historical backtesting: overlapping 40-year tapes are not a probability. Simulation is assumptive and reproducible. Use both.
Does Monte Carlo Overstate Retirement Success?
Does Monte Carlo overstate retirement success? Independent draws miss clustered crashes. Ignoring fees and floors will print a kind number. What we do instead.
How Many Monte Carlo Simulations Are Enough?
For most retirement plans, 1,000 simulations is enough: an 85% success rate lands within about 2 points, 83% to 87%. At 100 paths it is ±7.
Monte Carlo Simulation in Personal Finance: Why Projections Fall Short
Monte Carlo simulation in personal finance: a $4.3M projection landed at the 71st percentile; the median was $2.9M across 5,000 regime-aware lifetimes.
Other topics
- Retirement withdrawals — Safe withdrawal rates, the 4% rule, and flexible vs rigid spending policies.
- Investing costs — Fee drag, expense ratios, and the lifetime dollar cost of 1%.
- Investing behavior — Time in the market vs timing the market, and the cost of panic selling.
- Strategy comparison — Apples-to-apples benchmarks of allocation and spending rules on identical markets.