No matter how carefully you plan, there's no blueprint for your client's financial future.

It is impossible for your clients to plan for retirement using the approach that most educational and professional organizations in the financial industry teach. There are four reasons why your clients can’t use classical financial planning strategies to retire:

  1. You can’t predict future inflation.
  2. You can’t predict future equity returns.
  3. You can’t predict future tax rates.
  4. You can’t predict how long you’ll live.

… and neither can your clients.

To understand this more clearly, let’s look at each of these elements individually.

1. Inflation

Price inflation (the cost of goods and services) varies from year to year, and monetary inflation (the undue expansion of the money supply) is determined entirely by central banking policy and may influence price inflation significantly. You won’t know what either inflation rate will be 20 years from now, or how it will affect you or your clients. You won’t know the future cost of goods and services, and you won’t know how much your clients need to save for their retirement at age 65, 67, 70, or any other arbitrary retirement age.

While many financial advisors expect inflation to be between 2 and 4 percent over the long-term, this is a wide fluctuation in and of itself and can make a dramatic impact on how much your clients’ money is worth. If inflation is 0 percent, for example, then $1 would be worth $1 30 years from now. If it runs 3 percent, then that same dollar is only worth $0.40. What if inflation is higher than 3 percent? Lower than 3 percent? All of that impacts how much your clients need to accumulate for their future.

2. Investment returns

The traditional approach to retirement planning recommends that at least some of our clients’ money should be invested in equities. This naturally requires you (or your client) to be able to predict future investment returns so that the client knows how much to save, and you know what investments to recommend.

The problem with predicting stock market returns over the short-term is that the market moves unpredictably and is, for practical purposes, totally random. Long-term predictions are also impossible, and this is best understood through a “Monte Carlo analysis.” If you haven’t played with any of the planning software available these days, these simulators all use a “Monte Carlo” type of analysis that is supposed to randomize investment returns for your client. 

However, Monte Carlo simulators, and every other mathematical model that is predictive, have the same problem that no one likes to talk about. The software, and the very method itself, is entirely deductive. What does that mean? Well, you’ve probably heard of deductive reasoning before, right? A well-known deductive argument goes something like this:

All men are mortal;

Socrates is a man;

Therefore, Socrates is mortal.

All deductive arguments have two premises and a conclusion that is deduced from the first two premises. This is important in understanding the flaw in Monte Carlo simulators. On the surface, all deductive arguments make sense, but what you have to ask yourself is: how do I know the premises on which the deduction is based are true?

In other words, how do you know that “all men are mortal” and that “Socrates is a man?” If the only thing you’re relying on is the deductive argument presented, you don’t know. More importantly, you can’t know. The deductive argument doesn’t prove that “all men are mortal” and that “Socrates is a man.” All it really tells you is that if all men are mortal, and if Socrates is a man, then “Socrates is mortal.” So, how does all of this relate to Monte Carlo simulators?

Well, the simulator’s math is perfect, but it relies on inputs that you give it. You, as the advisor, must specify an assumed rate of inflation, an average rate of return, your client’s life expectancy, and a few other assumptions. How do you know any of the assumptions are valid? You don’t. You can’t. Like the deductive argument above, the only thing the simulator will tell you is that if inflation is a certain percent, and if you receive certain investment returns, and if you live to a certain age, then your client’s retirement savings have a certain percent chance of supporting him in his old age.

Here is a simplified version of what Monte Carlo would do for you and your clients. Let’s say your client invests $100,000 and earns an average of 12 percent annually. An average of 12 percent could look like this:

Yr 1 = 20% = $120,000

Yr 2 = 4% = $124,800

Yr 3 = -10% = $112,320

yr 4 = 24% = $139,276

yr 5 = 22% = $169,916

Now, let’s repeat this example but use a straight 12% rate of return:

Yr 1 = 12% = $112,000

Yr 2 = 12% = $125,440

Yr 3 = 12% = $140,492

Yr 4 = 12% = $157,351

Yr 5 = 12% = $176,234

Now, let’s compare that with another scenario involving one down year in which your client lost a catastrophic 40% (similar to what many people went through in 2008):

Yr 1 = 25% = $125,000

Yr 2 = 30% = $162,500

Yr 3 = 20% = $195,000

Yr 4 = 25% = $243,750

Yr 5 = -40% = $146,250

Now, stretch this out over 20 or 30 years. All of these scenarios average 12%, but give your client an actual compounded return that is all over the place. What if your client’s average return is lower than 12 percent? How could you know that in advance? Even if you rely on past performance of the market, and guess 7 percent annually, that still doesn’t solve the issue of when those returns are earned during your client’s investment time horizon. The when is almost more important that knowing what the rate of return is because your clients need to buy low and sell high. They need to know when they can cash in their investments.

Monte Carlo simulators are not advertised as predictive of future investment performance, but they almost have to be (at least implicitly). How else would it calculate your client’s probability of success or failure? It would have to rely on its ability to predict investment returns in order to generate its probabilistic scenarios. At the end of the day, these programs “look cool” but don’t tell you (or your client) anything useful or practical.

3. Taxes

This is fairly easy to understand. Taxes, of course, are determined by politicians and none of us knows who will be elected 20 or 30 years from now, much less in the next election. You won’t know what tax policy will be, and you don’t know what to tell your clients to minimize the impact of taxes 20 years from now.

4. Death

This one is pretty obvious, and it makes it impossible to predict how long your clients will need their savings to last. Even if they use annuities to guarantee an income, there is the problem of not knowing how much total savings is needed to produce the income necessary for your client to survive.

Next week, I’ll discuss why, while it’s impossible to succeed at traditional retirement planning, it’s not impossible to make a financial plan.