Results May Vary

I’ve written previously about some of what I consider the shortcomings of orthodox financial economics. In general, it appears to me that economic theory is largely detached from reality in much the same way astronomy was before Copernicus and Galileo.

One instance of this detachment from reality is the “random walk” theory of financial markets. This model of market behavior was developed in the 1960s and still holds sway in the retail research departments of most U.S. brokerage firms. It’s based mainly on this:

What the chart shows is the Dow Jones Industrial Average from its creation in 1896 to the present (monthly closing prices; my apologies for the unreadability). The greenish line is a “linear regression,” that is, the straight line that is the best fit to the actual data points. Linear regression was a cutting-edge tool back in the ’60s, when computing power was rather limited. But there’s an unargued underlying assumption in applying it to a market, which makes the “random walk” theory an exercise in circular logic.

The assumption is that the graph of a stock index like the Dow in a way “wants” to be a straight line but can’t manage it. What economists actually say is that the market “seeks equilibrium,” by which they mean that it wants to go up continuously and at a consistent rate. But instead, there are “perturbations” that cause “fluctuations” above or below the idealized rate of gain. Those fluctuations are by nature random (hence “random walk”) and therefore are unpredictable.

Thus, investors shouldn’t try to guess when the market is going to have one of those “perturbations” – in other words, they shouldn’t try to practice “market timing” – but instead should simply buy stocks and hold them for the long term, because the underlying trend always goes higher. And here the logical circle is closed.

Since the 1980s, the random walk theory has come under increasing criticism, and many economists outside the Wall Street houses acknowledge that it’s not a realistic model. Many still want to cling to some variation of randomness, however, and have developed hybrid models that include some degree of self-recursiveness along with the randomness, giving us things like the exotically named GARCH model: “generalized auto-regression with conditional heteroskedacity.” However, scientific studies have shown that these models have zero value in predicting market movements.

Another argument in favor of “buy and hold” investing is the claim that the stock market consistently over the years has provided an average annual percentage return that is higher than other kinds of investments. But this depends very much on how you calculate the annual return. The usual figure is 8 percent, compared with half that return or less from interest-bearing investments such as bonds.

It’s true that if you take the closing price of an index like the Dow on a given day and calculate the percent change from the same day the year before, and you average that calculation over the past 100 years, you’ll get a figure something like that 8 percent number. But the calculation doesn’t bear any resemblance to how people actually invest: You can’t “buy the Dow” every day and sell it a year later.

I’ve constructed a model that I think represents more accurately how people really invest. I had to make some simplifying assumptions, but I believe the result is still more indicative of the kind of average returns investors can expect.

Here’s the idea: Let’s suppose that a worker sets up a program in which he or she invests a set percentage of his or her income each month. This program continues for 30 years, at which point the worker retires and cashes out. I’ve also assumed that the worker gets a cost-of-living raise at the beginning of each year, based on the nominal inflation rate (based on the Consumer Price Index) for the previous year. (That’s something few workers are actually seeing today, so the model may actually overstate the investor’s returns somewhat.)

The following chart shows the average annual return a worker would have received by following this investment strategy:

The time scale (if you can read it; right-click to open it bigger in a new window) indicates the date upon which the worker began the monthly investment program, and the vertical scale shows the percentage return at the end of 30 years for a worker who started investing on the date shown. For example, a worker who started an investment program in the very first month that Charles Dow calculated his industrial average in 1896 (i.e., the very beginning of the blue line) would have earned an average annual return of 2.86 percent over the next 30 years.

The very highest average return, 18.11 percent, would have been earned by a worker who began a monthly investment program in December 1969 and cashed out in December 1999. Obviously, the average annual return for someone who started 10 years later and cashed out last year would have been quite a bit less, just 3.92 percent at the low point in February 2009.

Worse yet, people who started investing in late 1901 to mid-1903 would have lost money, as would almost everyone who started in 1912. Perhaps most surprisingly, anyone who embarked on this kind of program in the late 1940s to mid-1950s -- which we're used to thinking of as boom times -- would have earned a fairly paltry annual return of about 2 percent or less when they cashed out in the late 1970s-early 1980s -- which were not so booming.

Overall according to this scenario, investors who have cashed out to date have earned an average annual return of 5.05 percent or a median annual return of 4.44 percent. Those figures aren’t all that much above the long-term average or median returns on interest-bearing investments. As I said earlier, the results may overstate the average returns because of my assumption about annual salary increases. In addition, the numbers don’t include any taxes or transaction costs such as brokerage commissions.

However, the real lesson of this exercise isn’t about long-term average returns, it’s about the wide variability of the real-time returns. What it boils down to is that even for a long-term investor, your results still depend entirely on when you start investing and when you cash out. If we relate that to our entry into the career world, it shows how much the decision is out of our hands: We can’t choose what year we’re born. Whether we like it or not, we’re all market-timers.

Off Balance

The economic news the past few days has been pretty thoroughly awful: a bigger decline in third-quarter gross domestic product than previously estimated, declines in consumer spending, sales of new houses, industrial production, consumer confidence, etc. etc. Yet the stock market has been rising.

Some of the financial media are attributing the gains to “bargain-hunting,” or speculative buying of beaten-down shares in the belief that the selloff of the past several weeks was overdone. But that strategy would have to be based on an additional belief that the economy won’t continue to deteriorate, and I don’t see much indication that any such belief is widely held (whether true or not).

Another possible cause of the rebound: Maybe investors have decided that the steps being taken by Washington to stem the economic washout will actually work, finally – at least as far as Wall Street’s needs are concerned.

For example, this week Treasury Secretary and former Goldman Sachs CEO Henry Paulson announced that we (you and me, taxpayers) are going to give the nation’s fourth-largest banking company, Citigroup, an additional $300 billion in loan guarantees and a $45 billion cash infusion, on top of the $25 billion we already handed them in the first round of “TARP” investments, which of course did us no discernible good.

Citigroup, as of Sept. 30, reported total assets of $2.05 trillion. You would think that might be enough to enable them to cover their own bad bets. And indeed, the company reported total liabilities of just $1.92 trillion, leaving them with $126.1 billion in stockholder equity.

However, like many other large financial companies, Citigroup has what it refers to (in its latest financial filing with the Securities and Exchange Commission) as “off-balance-sheet arrangements.” As the name implies, these “arrangements” enable companies to take liabilities off their balance sheets by setting up a separate business entity, called a “special-purpose entity,” or SPE. The liabilities are, as Citigroup explains, “recorded on the balance sheet of the SPE and not reflected on the transferring company's balance sheet, assuming applicable accounting requirements are satisfied.” Although SPEs were used by the notorious Enron Corp. to deceive investors and regulators, they’re perfectly legal when used appropriately.

So how much has Citigroup taken “off-balance-sheet” by this method? Again, according to its latest filing with the SEC, the company’s “total involvement” in off-balance-sheet arrangements was $1.29 trillion at the end of September.

Now, it’s very unclear how much of that “involvement” might end up back on Citigroup’s balance sheets if it were required to “consolidate” it, as the Financial Accounting Standards Board has suggested it might decide to decree. But just for the sake of argument, if we suppose that the company were forced to put the whole amount back on its statement of liabilities, the effect would be to drop its stockholder equity from a positive $126.1 billion to a negative $1.16 trillion.

Based on its officially reported positive equity, Citigroup currently has stockholder equity per share, or “book value”, of $23.13. In normal times, stocks of major companies customarily sell for a multiple of book value, but Citigroup’s shares currently are trading below book value. Today’s close, $7.05, was just 30 percent of reported book value; at the low on Friday, before the latest handout was announced, the stock closed at just 16 percent of book value.

On the other hand, if my hypothetical numbers above were used, Citigroup would have a book value of minus $212.87 per share.

So maybe the reason Citigroup’s shares are selling below reported book value is that investors are worried that Citigroup may, indeed, have to “consolidate” some significant portion of its off-balance-sheet liabilities, which would mean its current reported book value is a wee bit unrealistically high. And maybe that has something to do with why our Secretary of Wall Street is so anxious to hand the company big piles of our money.