About Those Monte Carlo Analyses
If, when I say "Monte Carlo," you think of gambling in Monaco, or a certain model of Chevrolet, then you probably haven't talked with a professional financial advisor about managing your retirement finances. And in some ways, maybe that's just as well.
Most of the large investment firms are using a statistical technique called a "Monte Carlo model," or some similar method, to estimate people's chances of running out of money in retirement. These models typically take into account your age, the amount of money you have, whether your investment style is more conservative or more aggressive, and how much you'd like to withdraw from your savings every month to help pay for your living expenses.
The only thing wrong with this kind of analysis is: everything. The statistical analysis, while impressive, is unreliable. And even if it were reliable, it's not a very helpful way to attack the problem. The problem itself is grossly misstated, and since it's asking the wrong question, it almost inevitably provides unhelpful (or positively damaging) answers. And the investment strategy is usually out of place.
I'll explain those comments in a moment, but perhaps you are wondering how so many smart people at so many big companies could really be wrong. There are three reasons for it.
First, the whole idea of serving the special requirements of people in or near retirement is relatively new. Until about ten years ago, there were no major financial institutions who were even trying to serve this population in a focused way. So there are no time-tested methods of doing it.
Second, in the absence of such knowledge, financial companies naturally started with what they already knew best, and adapted it. What they knew best was investment management, which made some sense because, of course, it's a significant issue for retirees who have built up savings over the years. But unfortunately, it's not the central, most important financial issue for most retirees, and so building analytical tools and retirement services upon this foundation set these companies down a path that was not really appropriate.
Third, these inclinations were exacerbated by the natural tendency to emphasize issues and strategies that make money for the sponsoring company. And when the first investment companies and big-name consulting firms started doing it this way, it became harder and harder for anyone else to strike off upon a completely different path.
So, no, it is not surprising that even very big and sometimes very smart companies have adopted approaches that are not really right for you. So let's get back to why, specifically, these Monte Carlo models are indeed the wrong medicine:
- The statistical analysis is unreliable. The essence of the Monte Carlo technique is that, instead of assuming you will earn a pre-defined return on your investments, or that your money has to last a fixed number of years, these models define a range of potential ups and downs for your investments and a range of potential lifespans for you. Then they do the calculations hundreds or thousands of times, plugging in alternative values that are more or less randomly assigned (hence the gambling metaphor). Finally, they evaluate the results: in how many cases did your money last as long as you did? This technique might work, if they really had accurate statistics about your future risks, but they don't. And while they evaluate certain risks in a faulty way, they ignore other risks completely. These analytical models simply cannot do the one thing they advertise: to tell you your actual risk of running out of money.
- It's not a helpful way to attack the problem. Instead of creating a model that estimates your likelihood of running out of money under a collection of random scenarios, wouldn't it be better to examine a smaller set of realistic scenarios, so that you could see the effect of various actual choices and contingencies you face? What if you live to 100, or you work an extra three years, or the inflation rate increases significantly, or you have extra large medical expenses? The Monte Carlo models don't really show you specifically where such circumstances would help or hurt your finances.
- It answers the wrong question. Most Monte Carlo models ask: what are your odds of getting by financially for the rest of your life if you withdraw a fixed amount (or a gradually increasing amount) from your funds every month/year? If you are in your fifties or sixties now, the odds that you are going to even want to withdraw the same amount for the rest of your life are close to zero. Things change, including some things you probably already know about (like: you will stop working some year, or your mortgage will be paid off, or your Social Security or pension will change when either you or your spouse dies, etc., etc., etc.) So why analyze what your situation would be like if none of this ever occurred, and thereby get an OK on spending your funds in a way that is almost surely wrong? And why go for advice to someone who actually thinks that's the main question that needs to be answered?
- The assumed investment strategy is usually out of place. Since most of these models are used by professionals who have an interest in keeping you active in the investment markets, they usually assume relatively risky investment strategies. Even their "conservative" options are usually pretty risky for people who are retired, or expect to be retired for most of the remainder of their lives. (Enough said about this here. I addressed it in more detail in another column available on this site.)
So if you avoid these models, what do you do instead? You actually have to look pretty hard to find something right now that is significantly better. (My company offers such an alternative, in case you are looking, but it might or might not be right for you.) The main thing is to avoid taking this sort of model very seriously. If you have access to one, go ahead and play with it. But don't think of it as giving you the right answer. Think of it only as telling you very very broadly whether you are in a pretty strong or a pretty weak financial position - in case you don't know that already.
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