Market Returns

Financial simulators–broadly grouped into a) historical return calculators and b) Monte Carlo simulators–are popular tools for financial planning. But it’s important to recognize their limitations.

Historical Return Calculators

Historical return simulators (e.g. FireCalc) allow you to test a given strategy against historical returns to see how often it would have worked. For example, you can check how often a 4% starting withdrawal rate would have been successful over a 30-year retirement given various stock/bond allocations.

Such calculators are useful for showing what has not worked in the past. Showing that a strategy has worked only occasionally tells us that we should have little confidence that it will work in the future. That’s why, for example, we know that it’s unwise to plan to withdraw 7% of your portfolio every year during retirement.

Monte Carlo Simulations

Monte Carlo simulators (this one, for example) allow you to perform similar tests. But instead of testing a proposed strategy using actual historical sequences of returns, they ask you to provide statistical descriptors of investment returns (average return, standard deviation of returns, correlation to other investments, etc.), then they test the proposed strategy against numerous return sequences generated using those descriptors.

Monte Carlo simulations are especially useful for testing how much a plan’s probability of success will change as a result of changing assumptions. (For example, if stocks end up being 10% more volatile over annual periods than they’ve been historically, will that be a major problem?)

Are Historical Returns Meaningful?

Consider this analogy: You’re trying to determine the average height of a group of people (as well as other facts such as the standard deviation of heights among the group). With every additional person from the group that you measure, your data set grows and you can be more confident in your conclusions.

We try to do the same thing with historical returns–collect an ever-growing pile of data and use it to determine things like average annual stock market return.

But there’s a problem here: As our sample size grows, our population could be changing. For example, I’d assert that the financial markets and world economies are meaningfully different from, say, 50 years ago in several ways (examples: instantaneous information on stock, bond, and commodity prices; automated trading in very large amounts by institutional investors).

What effect will those changes have on investment returns in the future? I don’t know. But I don’t think we can simply assume that such changes will have no effect.

As such, any data older than 50 years is of limited value. As we continue to collect more data, we have to keep throwing our old data out as it becomes less and less relevant. Even today’s data may not be particularly relevant if you’re concerned with returns several decades into the future.

Conclusion: The predictive value of any simulations based purely on historical data must be taken with a healthy dose of skepticism.

February 16, 2011 10 comments

Russell Kinnel, director of mutual fund research at Morningstar, recently compared investor returns at Vanguard to investor returns at Fidelity. His study is interesting because it looks at investor returns (aka “dollar-weighted returns“) rather than investment returns (aka “time-weighted returns”).

A brief example of dollar-weighted returns

If Mutual Fund ABC earned a 25% return in Year 1, then lost 20% in Year 2, its effective annual return over the two years would have been 0% (because it would be back exactly where it started).

If, however, the fund had doubled in size at the end of Year 1–due to investors chasing performance and buying the fund after a great year–its dollar-weighted return would be significantly below 0%, because the performance in Year 2 would be weighted twice as heavily in the calculation. In short, dollar-weighted returns measure how the investors performed rather than how the investments performed.

What did Morningstar’s research show?

The study showed that Vanguard investors earned greater returns than Fidelity investors over the last 10 years. But that doesn’t really mean a great deal to me. It could simply be the result of Vanguard’s larger funds being in more successful asset classes than Fidelity’s.

What does interest me, however, are the two following facts:

  • As usual, mutual fund investors underperformed their own investments across the board.
  • Vanguard’s investors underperformed their investments by a smaller margin than Fidelity’s investors.

Why do we underperform?

We underperform because we try to time the market, and we (usually) fail. We chase performance–both in terms of hot asset classes and in terms of hot funds–and it destroys our returns.

Why do Vanguard investors perform better?

My hypothesis is that it has to do with the core philosophies of the two companies. As a company whose success has been based on index funds, Vanguard’s core tenets are minimizing costs, diversifying, and buying and holding.

In contrast, Fidelity, at its core, is about active investment. Many of their own fund managers turn over their portfolios more than once per year. It wouldn’t be terribly surprising to learn that their investors do something similar.

Kinnel has a similar opinion:

“It’s possible that the performance gap also has something to do with each firm’s message to investors. Vanguard preaches long-term investing and goes so far as to warn investors away from hot-performing funds…Fidelity also preaches long-term investing, but it sometimes nudges people to invest based on short-term results.”

What can we learn here?

Surely, some people will look at this study and see it as evidence of an opportunity to outperform the market. They’ll draw the conclusion that we must learn to “be fearful when others are greedy and greedy when others are fearful,” as Warren Buffett would say.

To me, the lesson is slightly different. I see it as another piece of evidence that our predictive abilities are decidedly lacking. After all, nearly every single one of those people who underperformed sincerely believed that he was going to outperform.

“I am above average!” is the battle cry of underperformance.

October 27, 2009 2 comments

A bit of a different post today: I wanted to share a spreadsheet that I maintain, which includes a good deal of data regarding historical stock and bond returns (in the U.S.).

Click here to download the spreadsheet.

Historical Return Data Included:

If, for example, you wanted to know any of the following, you could find it in the spreadsheet:

  1. The return of the U.S. stock market for each calendar year from 1928-2008.
  2. The nominal return for stocks or 10-year T-Bonds for any 3-year, 5-year, 10-year, 25-year, or 30-year period between 1928 and 2008.
  3. The inflation-adjusted version of #2 above.
  4. How you would have fared if you’d been dollar-cost-averaging into the market across any 10-year period from 1928-2008.
  5. The standard deviation of stock or bond market returns over 1-year, 3-year, 5-year, 10-year, 20-year, and 30-year periods from 1928-2008.
  6. Changes in gold prices each year from 1900-2008.

Credits

My thanks go to the following people/organizations for the underlying data:

Other Notes

I’m not perfect, and the data might not be either. If, after downloading the spreadsheet, you have any questions or see any errors in any of my calculations, please let me know.

Lastly, please remember that past performance is exactly that: past performance, not to be confused with future performance.

Enjoy. :)

September 29, 2009 4 comments

For whatever reason, anytime somebody brings up index funds one of the bigger personal finance blogs (like The Simple Dollar or Get Rich Slowly), there tends to be somebody in the comments who says something to the effect of “Index funds failed investors over the last decade.”

I can’t tell you how much this frustrates me given that:

For those who are not aware: “Index Fund” is not synonymous with “S&P 500 Index Fund.” There are index funds that track a whole host of other things, including bonds, commodities, and REITs.

How did a (re)balanced portfolio perform?

Just to set the record straight, I thought I’d take a minute to share the results internationally diversified portfolios, constructed from real index funds over the last decade.

The following portfolios are assumed to have been rebalanced annually on January 1 of each year. The stock portion is assumed to be 30% international (Vanguard’s Total International Stock Index Fund) and 70% U.S. (Vanguard’s Total Stock Market Index Fund). The bond portion is assumed to be Vanguard’s Total Bond Market Index Fund.

From 1999-2008, the following are the annualized rates of return for various asset allocations:

  • 70% bonds, 30% stocks: 4.44%
  • 60% bonds, 40% stocks: 4.02%
  • 50% bonds, 50% stocks: 3.54%
  • 40% bonds, 60% stocks: 3.00%
  • 30% bonds, 70% stocks: 2.39%

[You can see a screen shot of the spreadsheet with all the results here.]

Now, I’ll be the first to admit, those returns are hardly spectacular, and they were almost certainly below investor expectations. But they’re hardly the catastrophic declines in value that some people seem to think occurred.

August 26, 2009 13 comments

photo courtesy of Alex E. Proimos on flickrAs they say, you can drown in a river that has an average depth of 6 inches (should you attempt to cross and find that, at this particular point, the river is 8 feet deep).

Similarly, investors must be cautious about data regarding average returns offered by investments.

For example, if an investor were to look look at calendar years from 1928-2008, he would see that the stock market has earned an (arithmetic) average after-inflation return of 7.9%. Not bad! But to count on earning an 8% real return is to set oneself up for failure. For example:

  • In 28 of those 81 years, the stock market actually lost money.
  • In 8 different years, the market lost more than 20% of its value.
  • In 4 different years, the market lost more than 1/3 of its value (with the worst year being 2008, with a loss of 36.6%).*

And, as investors were reminded in the last year, even lengthier periods can be subject to wildly variable rates of return. Again, looking at calendar years from 1928-2008, we can see that:

  • In 10 of the 72 ten-year periods, the market lost money.
  • Over the 10-year period ending in 1974, a stock market investor would have lost more than 37% of his money, with a compounded real rate of return of -4.6%.

Takeaway Lesson: When making an investment plan, be sure to take into account not only average returns, but the variability of returns as well.

*I only noticed while writing this that on an after-inflation basis, 2008 (real return of -36.6%) was in fact worse than 1931 (real return of -33.8% due to annual deflation of approximately 10%).

August 17, 2009 13 comments

Black DiceThe concept of expected return is one that plays a vital role in just about every topic within the field of investing. Yet my (entirely anecdotal) experience suggests that many investors are unclear on what, exactly, “expected return” means.

Expected return is simply the sum of each of the possible outcomes, multiplied by its probability.

For example, when rolling a six-sided die, the expected return of a roll is a value of 3.5, calculated as follows:
(1/6 x 1) + (1/6 x 2) + (1/6 x 3) + (1/6 x 4) + (1/6 x 5) + (1/6 x 6) = 3.5.

Expected Return in Investing

The expected return for an investment is calculated in precisely the same way: by summing {each outcome (i.e., possible return) multiplied by its probability}.

The trick, of course, is that we don’t know the probabilities of each outcome the way that we do when rolling a die. Therefore, in investing, the best we can do is estimate an expected return.

Often, past performance data is used as a stand-in for probabilities. In most cases this is better than nothing, but it still leaves a lot to be desired. For example, just because we have data that says that stocks have outperformed bonds in 77% of 5-year periods from 1928-2008, it’s inaccurate to say that there is a 77% probability that stocks will outperform bonds over any given 5-year period in the future.

Don’t Expect the Expected Return

It’s important to remember that the expected return of an investment is simply one point (out of an infinite number of points) on the spectrum of possible returns. And, interestingly enough, with high-risk investments over short periods, we don’t actually expect to earn the expected return–or even anything particularly close to it.

Or, as Carl Richards puts it, “average is not normal.”

Risk and Expected Return

The concept that risk and return are positively correlated is one of the most fundamental tenets of finance. What many people miss, however, is that it’s expected return that’s correlated with risk.

In other words, there’s no knowing that a high-risk investment is going to earn a greater return than a low-risk investment over a given period. All we can do is expect that it will. (There is, after all, a reason that it’s called “risk.”)

The Role of Time

The longer the period we look at, the more likely it is that we’ll see a value close to the expected return.

That’s why, over short periods of time, stock returns are wildly unpredictable, yet over extended periods of time, inflation-adjusted stock returns tend to close in around a small range of values.

That’s also why, as we look at longer and longer periods, higher risk investments (i.e., stocks) become more and more likely to outperform lower risk investments (i.e., bonds).

In Summary

Expected return frequently trips people up in two ways:

  1. It may have been estimated poorly in the first place (using poor estimates of the probability for each outcome), and
  2. Even if it was calculated correctly, outcomes that are dramatically different from the expected return can still occur.

The most important things to remember are that the “expected” outcome becomes more and more likely over longer periods, and that–no matter how fancy our calculations–there’s no way to truly calculate the probability of any given outcome.

August 12, 2009 1 comment

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