More specifically,
“Monte Carlo Simulation”. This is a technique used by mathematicians and
engineers to find probable answers to highly complex and unpredictable
equations—like the stock market. It can be used to determine how much you can realistically
withdraw during retirement, and thus determine how much you need to have on
hand. But I am getting ahead of myself….
If you know the stock
market (S&P 500) has averaged, say, 12% annual return for the past 70
years, then any inexpensive calculator or financial website can theoretically
tell you how much money you need to have in order to retire with a certain
annual withdrawal amount. Such a nice, neat answer is appealing; but it can be
disastrously wrong!
For
instance, consider a doctor who retired in 1969. Based on average stock market
(S&P 500) returns of 12.3% for the 40 years prior to his retirement, he
thought he would be conservative using a 9.3% return. His calculator said he
could withdraw $70,000 of his $1,000,000 nest egg per year for 30 years,
including increases for inflation. However, as shown below, he would have run
out of money in 12 years – not 30! In reality, he should have only spent about
$41,000 per year. What happened?
He made the typical
mistake of focusing only on the “average” annual return of the stock market
without considering when those returns occurred. In fact, over his
30-year time frame, the market would actually return an average of 13.9%–better
than he had predicted! However, 1969 was a particularly bad time to retire
because the stock market dropped and had miserable returns for a number of
years after that, and high inflation kicked in. (Likewise, can you imagine
someone retiring in 2000, just before the dot-com bubble burst!?!)
Although 12% is indeed
a correct “average” annual return for the past 70 years, that does not address
the pattern of returns for your specific 30-year plan. Using average
returns ignores timing risk. The ending value of the plan’s projections
is based on achieving the average return each and every year. It
ignores market ups and downs along the way.
Most sophisticated
planners these days avoid giving you an absolute withdrawal rate or dollar
amount for retirement. Instead, they would say something like “Based on your
desired withdrawal rate and your portfolio mix, your plan of withdrawing, say,
5% plus an inflationary raise for the next 30 years has a 95% chance of
success. If you withdraw 6%, the chances of your money lasting 30 years drops
to 47%”. In other words, it is important to know the probability that
your plan will work. Enter Monte Carlo Simulation (“MCS”) analysis.
MCS is not perfect, but
it introduces the concepts of volatility and timing risk.
Rather than use a
simplistic “average return” approach for projecting the future, why not admit
that we don’t know the future. However based on the past we do have a
good idea of what the annual range of returns might be each year
for the next 30 years. Why not randomly pick a different—but feasible—return
for each year for 30 years and see how that scenario pans out. One such
scenario is indeed pretty arbitrary, but what if we did that, say 10,000
times! We would get a pretty wide variety of results, but we would begin to
see a trend forming. If 95% of our 10,000 scenarios accomplished our 30-year
goal, then we might feel pretty confident. If only 50% of those scenarios worked
out, then we should be alarmed and revisit our plan.
The figure below shows
what a few of the 10,000 “trials” might look like. The dark line indicates
which plan of withdrawals and portfolio mix would give you a 95% chance of
success, i.e., prevent your going negative before the end of 30 years. Based on
your risk tolerance, you could adopt a more aggressive plan, but at least you
made an “informed decision”.
