The following is excerpted from a blog post by Michael Kitces. To read the entire post, click here.
The inspiration for today's blog post comes from some research I am working on for the February issue of The Kitces Report, looking at how we as planners use Monte Carlo analysis to evaluate the risks to a retirement plan and the implications of bad markets. In discussing some of this work with a colleague, I realized how much of a misconception has embedded in the mind of financial planners about what really does, and does not, cause a retirement plan to run out of money.
For instance, assume the client has a balanced portfolio, with a long-term expected return of 8%, and a standard deviation of 15%. Accordingly, we look at three potential "problem" scenarios:
1. In a market crash, the portfolio drops 22% in a single year, and then experiences a sharp recovery and rallies almost 50% the following year (albeit from a lower base) to get back to the original growth rate.
2. In an extended
bear market, the portfolio declines by 5.4% per year for 5 years. At the end of the decline, the portfolio rallies a whopping 23.3%/year for the next 5 years to get back to the original growth trend.
3. In a protracted difficult market environment, the portfolio declines by only 1.5% per year but the declines last 10 years. As the markets eventually hit a valuation bottom, the market rallies forth at 18.4%/year for the next 10 years, finally recovering back to the original growth pace after 20 years.
All three of these results represent -2 standard deviation events over a 1-, 5-, and 10-year time horizon, respectively. Thus, these would actually be results that are uncommon but entirely probable in a typical Monte Carlo analysis, although notably clients tend to focus much more on the first scenario (the sharp market decline) than the third scenario (the protracted slightly-declining market).
If we look at how these portfolios grow over time, we would get Chart 1, which shows the results of the 1-year, 5-year, and 10-year dips. Ultimately, the recovery rallies get all of the portfolios back on the same track, whether it's a fast decline with a fast recovery or a slower decline with a slower recovery.
But these results simply assume that the client stays invested, with no cash flows in and out of the portfolio. Of course, if the client has no need to take any distributions from the portfolio, there is time to wait. But what happens if these various bear markets strike while the client is taking ongoing withdrawals from the portfolio? How do the results change?
Chart 2 shows the same portfolios modeled above, except this time there is an annual withdrawal at the end of the year of $50,000, which is increased annually assuming 3% inflation. With the client taking ongoing withdrawals, the results are substantially altered. The sharp decline followed by a sharp recovery trails only slightly in the long run, compared to the steady return portfolio. On the other hand, the portfolio that loses 5%/year for 5 years and then recovers ends out dipping far lower, and even after the recovery, finishes with less than 2/3rds the 1-year dip scenario. Conversely, the the catastrophe, as the portfolio draws down so low with ongoing withdrawals, that by the time the good returns arrive, the portfolio can't recover. It actually runs out of money completely in the final year.
(Advisers: Which asset class do you think will produce the best returns over the next ten years? Answer here).
Michael Kitces, MSFS, MTAX, CFP, CLU, ChFC, is the director of research for Pinnacle Advisory Group, a private wealth management firm located in Columbia, Maryland that oversees approximately $1 billion of client assets. He is the publisher of the e-newsletter The Kitces Report and the blog Nerd's Eye View through his website www.Kitces.com. Kitces is also one of the 2010 recipients of the Financial Planning Association's “Heart of Financial Planning” awards for his dedication to advancing the financial planning profession. Follow Kitces on Twitter at @MichaelKitces.
