After a period of deprivation and frugality, Luise has entered a phase of greater financial freedom. All her funds are in an ETF portfolio that averages a 7% return in the long term. Unfortunately, the 7% return is not constant and fluctuates significantly. Luise plans to withdraw a certain amount every month, either through dividends or by selling shares.

Before I continue with a financial-themed story, I want to clarify that I’m not a financial expert. I’m just an individual who is interested in personal retirement planning and other financial topics, accumulating some solid half-knowledge along the way, and occasionally relying on my more or less sound common sense. From time to time I create or extend a calculator.

This article has been translated in collaboration betwen me and a machine called ChatGPT.

Let’s assume Luise is a 51-year-old data-driven mathematical modeler working in the automation of production processes of small to medium-sized machine manufacturers. She has accumulated an ETF portfolio worth 433,754 euros and wants to withdraw the returns as passive income. Her heirs are spoiled and greedy, so Luise prefers to spend more money herself sustainably and not unnecessarily increase the amount to be inherited. How much can Luise withdraw each month without depleting her portfolio too quickly? As so often, the answer is: “It depends.” We’ll explore two scenarios for this, and more can be simulated using our calculator.

The Early Crash as Worst-Case Scenario

If there is a crash in our ETF portfolio right at the beginning of the withdrawal phase, our savings will be depleted much faster. In the following plot, we have two price trajectories with a very similar annual return of about 7%. The ‘Early Crash’ trajectory crashes right at the beginning and then recovers, while the other, named Wobble doesn’t crash at the beginning but wobbles more later on.

The time axis is an arbitrary choice. Luise can withdraw 1,200 euros every month, and in the worst-case (This is only approximately the worst case, but it looks more realistic than the actual worst case) Early Crash scenario, she would receive almost 420000 euros after 30 years. In the Wobble-scenario, on the other hand, her initial capital has more than quadrupled after 30 years. Wobbling, Luise can even withdraw 2,400 euros per month and still be in the black after 30 years. The exact numbers can be found in the table below.

Withdrawal per Month Scenario Final Value € / 433,754
1,200 Euros Early Crash 419,893 Euros 0.968
1,200 Euros Wobble 1,889,471 Euros 4.356
2,400 Euros Wobble 526,122 Euros 1.213

Both trajectories can be simulated directly in the calculator and used as a basis for calculations.

What advice can we give Luise? Should she be very conservative and withdraw only 3.5%, which equals 1,200 euros, to leave a substantial amount for her ungrateful heirs? Or is there some middle ground?

Adaptive Withdrawals

We consider the following rule. If the portfolio value at month $i$ exceeds the initial value, withdraw 2,400 euros; otherwise, withdraw 1,200 euros. With this strategy, in the Early Crash scenario, Luise would experience minimal loss. However, in the Wobble scenario, she would accumulate only 736,220 euros, leaving significantly less money for her greedy and spoiled heirs compared to a very conservative constant withdrawal of 1,200 euros per month, see calculator.

Calculate Your Own Withdrawal Scenarios

  1. Open https://bertiqwerty.com/balance.
  2. Set up the simulation.
    1. Click on Simulate price development.
    2. Use Advanced -> Add Crash if you want the simulated price to crash at a specific point.
    3. Click Run simulation followed by Add price development for balance computation.
  3. Enter the payments.
    1. The initial capital goes in the Initial capital field.
    2. In ‘Monthly payments,’ you can enter the monthly withdrawal as a negative number. You can also use formulas. Thereby, the variable cb variable represents the current portfolio value in that month and ic the initial capital. For example, the formula 1200 if cb < ic else 2400 corresponds to Luise’s rule in the previous section, since we support Python-style if-else-statements.

Happy simulations!