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Asset Class Performance and Timing the Market

Back when I worked as a financial advisor, I always loved sharing charts like this one with clients/potential clients. (Go ahead and take a look at it. I’ll wait.)

The first thing that seems to jump out (at least to me and to many people to whom I showed the chart) was that if a particular asset class is at the top one year, it’s likely to be at the bottom the next year (and vice versa). Wow, a pattern! At first glance, it looks like we could perhaps beat the market by buying whichever asset class had just been at the bottom.

It’s obvious from looking at the chart that–after a while–an underperforming asset class will typically bounce back and have a period of outperformance. Unfortunately, it appears rather difficult to guess how long “a while” is going to be.

In 2 of the 8 years shown in the chart, the worst-performing asset class for the year went on to have the best performance in the following year. However, in 4 of the 8 years, the worst-performing asset class went on to perform either worst or second-to-worst in the following year. Hmm…perhaps buying assets immediately after they’ve had poor years isn’t such a great plan after all.

It’s clear that assets swing back and forth from excellent performance to poor performance. Everybody knows that. What makes timing the market so difficult is that you have to know how long the periods of good (or bad) performance are going to last. Good luck. ūüôā

Investment Volatility vs. Portfolio Volatility

Yesterday I wrote about the advantages of dollar-cost-averaging into a volatile investment as opposed to DCA’ing into a non-volatile investment. (Short version: When DCA’ing into an investment, greater volatility allows for greater returns because, when you’re DCA’ing, you’re automatically taking advantage of market low points by buying more shares. The lower those low points are, the better.)

What I didn’t really stress yesterday is that the necessary volatility is investment-level volatility, not portfolio-level volatility. What’s that mean?

It means that, theoretically, you could create a portfolio of investments that are each volatile, but with opposite timing as to their respective ups and downs. By doing so, you would be taking advantage of the added returns from DCA’ing into volatile investments, while at the same time smoothing out the fluctuations of your entire portfolio’s value. Pretty neat, huh?

How easy is it to do?

Unfortunately, not very. In previous decades, such a result could be achieved by investing part of your portfolio in U.S. equities, and part of it in international equities. However, over the last 20 years or so, as our respective countries’ economies have become increasingly indistinguishable from each other, so have the returns of our countries’ stocks. (Evidence: The precipitous decline of our stock market over the last few months has been closely mirrored by declines of equity markets across the developed world.)

An alternative option that some (too many?) people suggest is to use fixed income investments along with equity investments in order to smooth overall portfolio return. The problem here, however, is that fixed income investments–while they do often move opposite to equity investments–actually provide a lower return over extended periods of time. In my opinion, when you’re still in your investing years, it’s just not worth it to sacrifice returns in order to reduce the volatility of your portfolio.

Worth the effort?

The way I see it, looking for investments whose volatility is oppositely-correlated in order to smooth out portfolio volatility is a nice idea, but unlikely to be worth the effort. And chasing after a goal like low portfolio volatility can lead you to make decisions that don’t make sense in terms of overall portfolio return (overinvesting in bonds, for instance). Besides, if you’re still in your accumulating-investments years, portfolio volatility isn’t really a problem, is it?

Greater Volatility = Greater Returns

Imagine that you’re given the choice between:

  • Investing $1,000 in an investment with a fixed 8% annual return, or
  • Investing $1,000 in an investment that has averaged an 8% annual return over its life, but has historically been rather volatile, earning a positive return in some years and negative return in others.

Which would you choose? I’d imagine that most people would choose the one with a fixed return. In fact, that’s likely the one I’d choose as well.

Now imagine this slightly different scenario: You recently came upon a new income stream of $1,000 per year. You don’t need the money, so you plan to invest it. Your two options are:

  • Investing $1,000 per year in an investment with a fixed 8% annual return, or
  • Investing $1,000 per year in an investment that has averaged an 8% annual return over its life, but has historically been rather volatile, earning a positive return in some years and negative return in others.

In this scenario, which option would you choose? The fixed rate still feels rather attractive. Dealing with uncertainty is difficult, so it’s nice to know exactly what you’re going to get.

On the other hand, if the volatile investment continues to¬†earn an 8% annual return on average–even though it’s year-by-year returns fluctuate a great deal–it’s going to earn you more money.

Why is this?

When dollar-cost-averaging, greater volatility means greater returns. It doesn’t necessarily seem intuitive, but let’s look at the math. [Please note that the following analysis applies only when dollar-cost-averaging into an investment.]

Scenario 1

The following spreadsheet snippet shows our zero-volatility example. (You’re investing $1,000 per year, and the investment earns exactly 8% each year.) As you can see, at the end of the period, you would have invested $3,000, and it would have turned into $3,506.

  • Average return earned by the investment: 8%
  • Volatility: None
  • Amount of money at the end: $3,506.11
  • Return earned on your investment: 8%.

Scenario 2

This next spreadsheet shows a scenario in which the investment still averaged the same exact 8% annual return. (That is, it still started at a $100 share price and three years later had a share price of $125.97.) However, in this scenario–in Years 2 and 3–the investment fluctuated in price from our base-line, 8%-every-year scenario. This time, instead of the share price in Year 2 being $108, it was $128 (or $20 higher). And in Year 3, instead of $116.64 it was $96.64 ($20 lower).

  • Average return earned by the investment: 8%
  • Volatility: $20 upward, followed by $20 downward
  • Amount of money at the end: $3,547.34
  • Return earned on your investment: 8.62%.

As you can see, adding some volatility into the scenario did, in fact, increase your return. In short, this is because Dollar-Cost-Averaging into a volatile investment sets you up to automatically take advantage of price swings by buying more shares when the price is low.

OK, so volatility helps your return in that scenario. But what about in other situations? For example, what happens when the price swings happen in the other order (downward first, followed by upward)?

Scenario 3

This scenario is exactly the same as Scenario 2, but with downward volatility first, followed by upward volatility. So the share price in Year 2 is $88 ($20 lower than the original $108), and in Year 3 the share price is $136.64 ($20 higher than the original $116.64).

  • Average return earned by the investment: 8%
  • Volatility: $20 downward, followed by $20 upward
  • Amount of money at the end: $3,613.09
  • Return earned on your investment: 9.59%.

As you can see, the results are even better than in Scenario 2.

So far, we can conclude that some volatility is better than no volatility and that it’s beneficial regardless of the order in which it occurs. So what happens when we increase the volatility further?

Scenario 4

Scenario 4 is the same as Scenario 2, except the volatility is in the degree of $50 rather than $20.

  • Average return earned by the investment: 8%
  • Volatility: $50 upward, followed by $50 downward
  • Amount of money at the end: $3,947.28
  • Return earned on your investment: 14.36%.

Wow. Look at that return! Earning a 14% return on your money while investing in something that only earned an 8% return over the period is pretty impressive.

Why does volatility increase returns?

  • When you’re DCA’ing into an investment, you’re automatically buying more shares when the market is low, and fewer when the market is high. (“Buy low. Sell high.”)
  • Increased volatility simply creates a situation in which the market lows are lower, thereby making your DCA’ing more effective.

Overall Lesson

If you’re dollar-cost-averaging into an investment, greater volatility means greater returns. In other words, the volatility of the stock market isn’t just something you have to put up with in order to earn superior returns. It’s actually an essential factor that directly improves your return.

The Growth Trap

A recent rereading of Jeremy Siegel’s The Future for Investors (a favorite of mine)¬†reminded me of a lesson from the book that I found particularly valuable.

Siegel uses the term “The Growth Trap” to refer to the common investment mistake of assuming that a company (or an industry, or a country) is a good investment simply because there’s reason to believe that it will grow over the next several years.

For example, it would be easy for anybody to see that Google’s revenues and profits are likely to grow over the next decade. As such, many investors would be inclined to believe that this¬†would make Google¬†a great investment. The problem with this line of reasoning is that a certain level of growth is already built into the price. In other words, the current market price of Google stock (whatever it may be) is already based upon a certain level of assumed growth.

In order for an investment to earn above-average returns, the underlying company doesn’t just have to grow. It¬†has to grow at a faster rate than everybody else has estimated. (Please note: “Everybody else” is–primarily–a group of full-time experts. So in order to be successful in such a wager, you need to have some information that they¬†don’t¬†have.)

If the company ends up growing at a rate that is equal to the projected rate of growth, its stock will earn a return that is roughly equal to the average return of the market. Similarly, if the company grows at a slower rate than has been projected, the company’s stock will actually underperform the market. (Yes, this means that a company can be growing–perhaps even very quickly–while its stock is earning below-average returns.)

The Shrinkage Trap?

Siegel never gives it a name, but the opposite mistake is just as easy to make: Many people assume that just because a company (or industry, or country) is declining, it must make a poor investment. That’s simply not true. If it’s obvious that a company is in decline, then–you guessed it–there’s a certain amount of decline in net income that has already been built into the share price.

How well the investment performs is entirely a function of how quickly the company declines in comparison to how quickly the market has projected it to decline. (And yes, this means that a company’s stock can be earning above-average returns even while the company’s net income is declining–just so long as the company’s rate of decline is less than the rate of decline that had been projected.) ūüôā

In Summary

In short, what ends up being relevant isn’t whether a company is growing or shrinking. The only thing that matters is how quickly the company¬†grows (or shinks)¬†in comparison to how quickly the market (made up of countless experts) thought it would grow (or shrink).

My takeaway: In order to successfully beat the market by picking stocks, it’s not sufficient to know that a company’s profits¬†will grow over [whatever time frame you’re considering]. You have to have reason to suspect that the company’s profits will grow at a rate faster than the rate that has been projected by all the analysts. It seems to me that that is a difficult prediction to make successfully.

The Problem with Picking Stocks? Your Data Stinks.

David Ning recently wrote an excellent post explaining Earnings Per Share (EPS), which is one of the most important pieces of data when analyzing a company to determine whether or not you want to invest in it.

David mentioned one thing though that really reminded me as to why I never try to pick stocks: Different people calculate EPS in different ways. For example, some base the calculation on earnings in the previous period, while some use projected earnings over the next period.

David wisely suggests that you do your own calculation of EPS¬†by using¬†data from¬†the company’s financial statements. This way, you can be sure that when you’re comparing two companies’ data, the calculations were at least made using the same formulas.


EPS is just the tip of the proverbial iceberg.

From what I’ve seen working in the field of accounting, most accountants tend to be reluctant to try to pick stocks. My (completely untested) hypothesis is that it’s a result of our awareness of the imprecise nature of the information that goes into a company’s financial statements. (A company’s financial statements are a primary source of information for investors when considering whether or not to purchase a stock.)

For example, even if you know that the EPS calculation was done using the same formula for each company, it still¬†might be completely meaningless. Why? Because¬†calculating a company’s EPS requires knowing the company’s net income. And the calculation of net income includes¬†(literally) thousands of different assumptions and estimates, which can be different from company to company.

Take depreciation for example.  (Depreciation is the process by which the cost of an asset is spread out over its useful life.) Any time a piece of equipment (or furniture, or a building) is purchased, three questions have to be answered in order to determine how much depreciation expense to recognize each year:

  • How long do we expect to use the asset?
  • Do we think that the asset will be worth anything by the end of that time period?
  • What method of depreciation do we want to use? (There are several. Some of them result in more expense in the earlier years. Some of them spread the cost out more evenly from year to year, etc.)

So, if two companies purchased the exact same¬†asset,¬†but answer the above questions differently, they will report differing amounts of depreciation expense–and thus, differing amounts of net income–each year.

Now to get a sense of how this plays out in real life, multiply that uncertainty by a few thousand assets.

And that’s just depreciation expense. The same types of assumptions and estimates¬†are made when calculating amortization expense, cost of goods sold, revenue from construction (or other long-term) contracts, expenses resulting from fires/flooding/hurricanes/lawsuits, and so on.

In fact, in accounting, we often say that numbers can only be trusted to their first significant digit. In other words, an expense of $2.4 billion could very easily be reported as $2 billion by another company if different assumptions had been made.

Let’s look at an investing-related example.

Imagine you’re making a comparison between two companies’ “current ratios.” (Current ratio is the ratio of a company’s current assets to current liabilities. It’s often used to determine a company’s ability to meet its short-term financial obligations.)

Imagine that Company A has a current ratio of 1.45, and Company B has a current ratio of 1.02. It might be tempting to say that Company A is a better investment, because it has a current ratio that’s almost 50% higher than that of Company B. In reality though, that level of difference could easily be attributed to the use of different accounting methods, assumptions, and estimates.

To say that Company A’s current ratio is significantly higher than Company B’s is to delude yourself. The data simply isn’t good enough to make that statement with any meaningful certainty.

And before you get any ideas about trying to come up with ways to adjust for the different assumptions and estimates, allow me to save you the time. It’s impossible. You don’t have the necessary information to do so. (You’d need information as to the purchase price for all of a company’s assets, how long they expect them to last, and so on. And no matter how nicely you ask, they’re unlikely to give you this data.)

If you want to try and pick stocks, be my guest. Just be aware that the data you’re using isn’t nearly as precise as it appears.

Think You Can Beat the Market? Know Your Competition.

Many investors are tempted to try various strategies to beat the market. (That is, to outperform the major stock market indices.) Some people like to pick stocks. Others attempt to pick winning mutual funds. Others have determined that it can be done using regular index funds and timing their investments so as to avoid downward movements in the market.

As far as I can tell, this desire is simply the result of people’s tendency to estimate their own skills as above average. Apparently, nearly all of us engage in this logical fallacy in a number of ways. Investing seems to be one of them.

As a Whole, It’s Impossible for Us to Outperform

When considered as a single group, it’s impossible for investors to outperform the market. Simple math tells us that–as¬†a group–we must earn exactly the market’s returns. (Actually, we earn the market’s returns, minus the sum of our total investment costs, but that’s a post for another day.)

It would seem logical to conclude, then, that for each person who outperforms the market, there must be somebody who is underperforming the market. The more precise conclusion, however, is that for each investment dollar that is outperforming, there must be another dollar that is underperforming.

Simplified Example: If the market had only ten investors, and¬†one of them had as much¬†money as the other nine combined,¬†it’s possible that all nine of the poorer investors could be underperforming the market, while the one wealthy investor is outperforming the market.

Thus, in order for our investment dollars to outperform the market, somebody’s investment dollars must be underperforming by an equal amount. In order to accurately gauge our likelihood of success in such an endeavor, it¬†would seem wise¬†to consider who, precisely, our competition is.

It’s Not Just Your Day-Trader Neighbor

If all we had to do to outperform the market was be smarter/more clever than the average individual investor, it might not be so difficult. After all, there are plenty of people out there who don’t really know what they’re doing.

Unfortunately–at least for the probability of our¬†being able to beat the market–the majority of the investment dollars we’d be competing with are not controlled by your Average Joe. In fact, only 34% of U.S. stocks are owned in individual accounts by individual investors. That means that two-thirds of our competition is made up of mutual fund managers, pension funds, insurance companies, trusts/foundations, and banks.

So if you decide to try and beat the market, what you’re really betting on is your ability to outperform teams of full-time professionals. Teams with well-funded, well-staffed¬†research departments.

If you’re confident that you can beat them, then (you’re probably deluding yourself, but) go ahead and try. It just seems prudent to know who you’re up against.

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