Investment Return Comparison

Software engineer in Munich · Peak earning years

This page compares financial outcomes for a Software engineer living in Munich, Germany, following the Peak earning years life scenario.

A high-income trajectory with strong saving capacity and rapid wealth accumulation. Compounding works faster here, but results remain exposed to market cycles and timing.

Munich offers very strong income potential in high-skill sectors, along with some of the highest living costs in Germany.

The comparison focuses on how changing the Investment return (expected) influences long-term results, while all other assumptions remain constant.

Simulation Overview

Base scenario assumptions

  • The simulation starts at age 30 and runs until age 65.
  • The initial annual labor income is €33,040.
  • Labor income grows annually at an average rate of 4%.
  • A labor income tax rate of 35% is applied to gross earnings.
  • The saving rate is set to 30%.
  • Minimum annual living expenses are €19,500.
  • Savings are invested with stochastic annual returns.
  • The average annual return is 6%, with year-to-year variability.
  • All values are expressed in real terms, assuming average annual inflation of 2%.
  • The simulation includes stochastic life events such as unemployment, and health issue.
  • These events may temporarily affect income, expenses, or net worth.
  • Financial independence is defined as having net worth equal to 25 times annual expenses.
  • Bankruptcy is triggered if net worth remains below €0 for 2 consecutive years.
🔁
Varied parameter
Investment return (expected) 3% → 7%

Scenario Comparison

Results are shown as a realistic range. P10 represents a pessimistic outcome, while P90 represents an optimistic outcome. Most simulations fall between these two values.

ScenarioMedian Net WorthP10 Net WorthP90 Net WorthFI ProbabilityFI Median Age
3% 624,964 423,128 934,773 83% 60
5% 856,779 566,285 1,317,875 97% 57
7% 1,203,227 783,850 1,874,910 100% 54

How Your Financial Life Evolves

These charts show how each scenario affects long-term outcomes, including expected wealth, downside risk, and the likelihood of achieving financial independence.

Net Worth Median

net_worth_median for Software engineer in Munich

Net Worth Range

net_worth_range for Software engineer in Munich

Fi Probability

fi_probability for Software engineer in Munich

Fi Median Age

fi_median_age for Software engineer in Munich

What would you like to explore next?