Kiplinger’s recommends target date funds

Long-time readers will know that I recommend these funds for people who don’t want to spend too much time on investing. See Kiplinger’s article.

I like Vanguard’s target-date funds because of their low costs. While they tend to be more conservative than other company’s target-date funds, an investor willing to take on more risk could easily do so by investing only in the longest-date fund, no matter when that investor plans to retire, or by supplementing the target-date fund with a pure-stock index fund.

A game of risk or a risky game?

The traditional thinking in the world of finance is that to increase returns you need to increase risk. This view is quite logical. Let’s consider an investor who wants a minimum of risk. She can buy certain blue-chip stocks such as Wal-Mart, Home Depot [[hd]] , and GE [[ge]]. The stocks offer low risk because they are all giant companies with dominant market positions; I think it is a fair bet that all three companies will still be around in one form or another 50 or 100 years from now. For such low risk our investor will get a relatively low return because these companies are so huge and have less ability to grow than they had in the past. Now, with such great blues chip stocks available why would our investor choose to buy shares in a company such as DayStar technology [[DSTI]] or Cheniere Energy [[LNG]]? Neither of these companies currently makes a profit nor has any significant revenue. In owning such companies an investor has significantly more risk of losing her capital. Therefore, no rational investor would buy the stock of such companies without being assured that those investments offer the potential of very great reward.

This thinking underlies the Capital Asset Pricing Model (CAPM). Now, for the most part this works quite well. However, there are some problems with the capital asset pricing model. One huge problem is that in this model risk is defined as the stock’s volatility. Volatility is of course a measure of how much a stock’s price changes each day, week, and year. For those of us who are long-term investors, however, volatility is an inadequate measure of risk. What matters more for us is the stability of the future earnings of a company.

For financial analysts and portfolio managers, volatility is most commonly measured by something they call beta. Simply put, beta is a measure of the correlation of the stock’s price to the broader stock market as a whole. Therefore, an index fund would have a beta of 1.0. Let’s say we have a stock that has a beta of 2.0; this means that in general, when the market goes up 10% the stock will go up 20%, conversely, when the market goes down 10% the stock will go down 20%.

Since we’re already talking about beta and financial analysts, I might as well mention alpha. Alpha is a measure of a portfolio’s performance. An alpha of zero indicates that a portfolio matched the market’s return. An alpha of one would indicate that a portfolio outperformed the market by 1% annually.

The goal of a professional portfolio manager, at least according to the capital asset pricing model, is to construct a portfolio with the desired amount of alpha in order to maximize returns without exceeding a certain level of risk (beta). According to the model, it is impossible to consistently beat the market because the market is efficient. This aspect of the model is known as the efficient market hypothesis and I obviously believe it to be wrong. I will deal with why this is wrong in a later article. For now let’s return to risk.

One finding that has been problematic both for the efficient market hypothesis and for beta is the finding that low P/B stocks outperform high P/B stocks. According to the CAPM, this could not happen without low P/B stocks being more risky than high P/B stocks. However, low P/B stocks do not have higher betas than high P/B stocks. The creator of the efficient market hypothesis himself, Eugene Fama, realized then that beta do not adequately measure risk. He and his collaborator Eric French argued that low P/B stocks are more risky than high P/B stocks. I disagree with this but the important point is that as of their paper in 1992 (unfortunately not available free online), beta was officially dead or at least dying.

So how can we measure risk? There are no easy ways to do so. We must rely on sound fundamental analysis. Risk obviously decreases the more products the company makes and the more customers to which it sells. Thus, GE and Berkshire Hathaway are less risky than almost all other companies because their revenue streams are so diverse. Conversely, ExpressJet [[xjt]] and the other regional airlines are very risky because they all have only one or two customers. Similarly, small defense contractors are risky if they sell only a few major products and to only one major customer: the United States government.

Another risk factor is debt. Companies with more debt are much less likely to be able to survive a recession or industry downturn because they would be unable to meet their debt obligations if their revenues drop more than slightly. For this reason, companies such as Fortune Brands [[fo]], Blockbuster [[bbi]], and Ford [[f]] have elevated risk due to high debt loads.

Another risk factor is obviously competition. Companies and highly competitive industries have greater risk than companies with monopolies or that for other reasons do not have much competition. There are many ways that a company can avoid too much competition, including patents, trade secrets, operating in a niche market, and effective branding. Ceteris paribus, a dollar of earnings that is at lower risk from competition is worth more than a dollar of earnings that comes from a highly competitive industry.

This is not to say that companies in highly competitive industries cannot be great investments. Those companies that are wildly successful in competitive industries usually have some key advantage that gives them an edge in that is not easily copied. This advantage is not always easy to identify. For example, Southwest Airlines [[luv]] had the important advantage over legacy carriers of not having an established business prior to airline deregulation. This meant that Southwest was not burdened with the same costs that hindered the larger airlines. In addition, Southwest’s fares were simple and did not penalize travelers for arbitrary reasons such as not staying over a weekend. Another good example of a successful company in a competitive industry is Wal-Mart [[wmt]]. What did Wal-Mart offer that Kmart [[shld]] and other discounters could not? One thing it offered was everyday low prices. By avoiding sales Wal-Mart gained both the reputation as the low-price leader and it gained more consistent profitability. Wal-Mart has also been known for some time for the effectiveness of its distribution system. In an industry with low profit margins and high inventory requirements, any improvement in logistics drops straight to the bottom line.

The last important risk factor is the elasticity of demand for a company’s products. The business cycle is a fact of life; any company that suffers less during recessions, whether because it sells products that are always in demand or because it sells to people who are not greatly affected by recessions, has lower risk than the average company. Big industrial companies such as auto manufacturers and aircraft manufacturers are usually very cyclical. Cyclicality of earnings is not in and of itself a black mark against a business. However, combined with high debt and stiff competition, a cyclical company in an industry downturn can be a very risky bet. See, for example, General Motors [[gm]] or Northwest Airlines [[nwa]].

While it is not possible to exactly quantify risk, it can still be approximated. Any decision to invest in a company should come only after carefully weighing the possibility for reward against the risk that company presents. In certain circumstances, adequate calculation of risk and reward cannot be made, such as with development stage companies with no revenues. In such cases, the conservative investor would do well to watch from the sidelines unless she is an expert in the field and is sure that she is not paying too much.

On a related note, I urge you to read Richard Russell’s article on the perfect business, which discusses the ideal business from the standpoint of a small-business owner. The points Russell brings up are also important to large publicly traded companies.

Disclosure: I have no position in any stock mentioned above. I have a full disclosure policy.

Why you should not decide which stocks to buy

In my previous article on regression to the mean I touched upon the reason for why we should not simply let our intuition guide us in making investment decisions (or any decision, for that matter). Rather, it is best to have some sort of formal decision-making process.

Why is it so much better to use a formula than to simply think holistically? Is not our thinking better? Can we not adapt our thinking to any extenuating circumstances if we think holistically? Consider a stock with a low P/E ratio but a high short ratio. It might be a good idea to avoid the stock, right? Quite simply, no. The P/E ratio is probably ten times more important than the short ratio in determining whether to buy or sell a stock. Sure, the short ratio is correlated with stock market returns, but a lot less so than is the P/E ratio.

When making intuitive judgments it is easy to be led astray by such salient but marginally important information. It is true that our feelings and intuition can be highly useful, such as in our estimation of the quality of a company’s management. However, a formula can incorporate that subjective, holistic information as well. There is no reason why we cannot use intangible information in a formalized investment decision process. We could have a part of the formula where you enter in a ‘1’ if the management is good, ‘0’ if mediocre, or ‘-1’ if bad. In the case of a company with an ongoing proxy fight, we could run the computation twice, with different inputs depending upon who wins. Comparing the two possible outcomes to other investment opportunities would give us a means of deciding whether the possible benefits outweighed the risks. This can prevent emotions and unimportant information from leading us to the wrong decision.

For a further discussion of the problems we humans face in making decisions when faced with complicated and conflicting information, I suggest reading Psychological Study of Human Judgment: Implications for Investment Decision Making by Paul Slovic (1972). (Unfortunately, no free full-text version of this paper is available online.)

My (Optimistic) Prediction for 2008: It Will “Suck”

In response to a reader comment on my prediction of financial Armageddon for 2008, I have another, more optimistic prediction. As I said before, I am not a fan of predictions per se. It is, however, useful to outline possibilities. This possibility is more likely than financial Armageddon. As you can surmise from my title, I do not believe the economy will be all roses and sunshine this year.

What everyone seems to ignore is that recession is necessary from time to time. Mal-investment must be corrected. Profligate spenders must be chastened. The economy has invested too much capital into housing and it needs to reinvest that capital into other sectors. Unfortunately, that will cause pain. But to try like the Fed to avoid the pain will only delay it and worsen it. That is exactly what happened in 2001 as the Fed cut rates drastically to avoid pain from the stock market crash. The easy money went into housing and caused the current problems.

February: Lenders and counterparties give up on ACA Capital Holdings, the smallest and weakest monoline bond insurer. It declares bankruptcy. The bailout of the other bond insurers succeeds, barely. Ambac [[abk]],  and MBIA [[mbi]] survive in run-off mode. New competitors such as Berkshire Hathaway’s [[brka]] subsidiary take over 100% of the municipal-bond insurance market. Harry Macklowe loses much of his real estate empire when he fails to refinance his short term debt. Rents decrease in Manhattan for the first time in years.

March: The stock market continues to stagnate.

April: Towards the end of the month, the homebuilders report more huge writedowns. Several see their stocks drop another 80%. One or two small public builders declare bankruptcy. The largest all survive. On a personal note, the author of this blog sells his house, which he had owned for almost four years, for a 20% loss.

May: Losses to banks from the failure of ACA alone top $20 billion. Bank stocks continue going down, but losses look like they won’t increase further. House prices in St. Louis are down 25% from their peak. In parts of California, house prices are down over 30%.

June: No bank runs, surprisingly.

July: Numerous small companies declare bankruptcy. The default rate on junk bonds approaches an annualized 7% for the year.
August: By this time house prices have fallen over 40% in California from their peak prices. The worst seems over, although house prices will stagnate for the next four years at least.

September: Mortgage insurers Radian [[rdn]] and PMI Group [[pmi]] are bailed out by banks and vulture investors, and none of the mortgage insurers declare bankruptcy. The carnage in the financial sector appears to be over.

October: Google’s profit increases 80%. Citigroup continues to flounder after losing several more top executives.

November: Barack Obama or John McCain wins the election. His (and Congress’) plans to help the economy do nothing for the economy while wasting taxpayers’ money.

December: The unemployment rate hits 5% in the US and the country enters a recession.

Disclosure: I am long BRK-A. I think Barack Obama is naive at best (and a corrupt scoundrel at worst; see his land dealings in Chicago) and John McCain is a fool who has no regard for free speech (as shown by McCain-Feingold).

My Prediction for 2008: Financial Armageddon

I’m not much for predictions (because they are usually bad), but I thought I’d give it a try. Here is how financial Armageddon could come to pass this year. I do not think it will happen, but it is possible.

February: Lenders and counterparties give up on ACA Capital Holdings, the smallest and weakest monoline bond insurer. It declares bankruptcy. The bailout of the other bond insurers fails. Ambac [[abk]], already in run-off mode, is downgraded to junk. MBIA [[mbi]] survives a bit longer. Harry Macklowe loses much of his real estate empire when he fails to refinance his short term debt. Rents decrease in Manhattan for the first time in years.

March: Ambac becomes insolvent. MBIA is downgraded to junk.

April: MBIA declares bankruptcy. Towards the end of the month, the homebuilders report more huge writedowns. Several banks surprise everyone by calling loans on a teetering Standard Pacific Homebuilders [[spf]]. It declares bankruptcy. Several smaller, private, homebuilders are likewise pushed into bankruptcy by their lenders.

May: Losses to banks from the failure of ACA alone top $20 billion. Analysts estimate that the major banks will have to write down $250 billion as a result of the failure of the other bond insurers. Citigroup’s [[c]] stock is now down over 50% in the last 6 months alone. The Bank of America [[bac]] acquistion of Countrywide Financial [[cfc]] falls through and Countrywide declares bankruptcy. On a personal note, the author of this blog finally sells his house, which he had owned for almost four years, for a 25% loss. House prices in St. Louis are down 30% from their peak. In parts of California, house prices are down over 50%.

June: Several regional banks based in California are paralyzed by bank runs. They declare bankruptcy. The FDIC estimates that the bailout of their depositors will cost $30 billion.

July: Forgotten by almost everyone, pushed to collapse by banks’ unwillingness to refinance its debt, Chrysler declares bankruptcy. Several small companies join it there.

August: By this time house prices have fallen over 60% in California from their peak prices. It is now impossible to obtain a mortgage with a FICO score below 600, a smaller than 20% down payment, or an income at least four times the mortgage payment (including insurance and taxes).

September: A large insurer reveals write downs due to mortgage-backed security losses equal to its book value. Its stock drops 90% in one day, leading the S&P 500 down 8%. Mortgage insurer Radian [[rdn]] declares bankruptcy. It is joined in bankruptcy by competitor PMI Group [[pmi]].

October: Google’s profit increases 70%. Citigroup’s book value is now down 50% over the last two years.

November: Hillary Clinton wins the US election even though 80% of the population hates her. She decides to play the role of Franklin Roosevelt and her policies look to drive the US into a depression.

December: The unemployment rate hits 6% in the US and the country continues a recession that started back in the spring.

Disclosure: I have no position in any stock mentioned above. I hate Hillary Clinton. I am actually not pessimistic enough to believe that much of the above will occur.

Monoline bond insurers need $200 billion to retain AAA credit rating

According to Egan Jones, the 4th largest credit rating agency in the US. Unlike the other rating agencies, Egan Jones is paid by money managers and not by the companies whose bonds it rates. Egan Jones has already downgraded MBIA [[mbi]] 13 notches below AAA.

Independent studies I have seen indicate that Egan Jones is generally faster and more accurate than S&P, Moody’s, and Fitch. If Egan Jones is right in this case, any planned bailout will fail and the monoline bond insurers will be bankrupt in under a year.

Disclosure: I have no relationship with Egan Jones and no position, long or short, in any bond insurer mentioned, although I do own shares of Berkshire Hathaway, which has recently started a competing bond insurer. I have an iron-clad disclosure policy that has a AAAAA rating (or its equivalent) from Fitch, Moody’s, Egan Jones, S&P, A.M. Best, and The Slovenian Institute for Rating Blog Disclosure Policies.

Discounted cash flows for dummies

Performing a DCF analysis is a subject about which I have meant to write for some time. It is the culmination of the search for an objective means of valuing companies based on the total profit they will produce in the future. Various equations exist for calculating a company’s net present value. I will present one of the simpler equations for two reasons: it is easier and it involves fewer assumptions that could be wrong.

For a handy spreadsheet to calculate the present value of future cash flows, given expected growth rates and current cash flows, see this workbook (Excel format).

Performing a DCF analysis is relatively simple. We take the current profit per share (as measured best by free cash flow to equity, FCFE). Free cash flow to equity can be difficult to calculate, so free cash flow (FCF) can be used instead. If you wish to perform a quick and dirty DCF, you can use earnings instead of FCF, but this is generally not a good method.

The standard means for conducting a DCF is to take the present profit per share and then project assumed changes in that profit into the future. We use an interest rate as the discount rate to account for the time value of money (there are many different approaches for selecting the correct discount rate). Therefore, the further in the future a dollar is earned, the less it is worth today. This is because time has value. In the workbook I use 8% as the discount rate. Many people use the rate on the 10-year treasury bond. If you do that, use a long-term average of yields, otherwise your calculations of current value will change drastically over short time periods as the interest rate fluctuates. Also, you should add a risk premium onto the risk-free rate if you use it as the discount rate. A simple and theoretically defensible method would be instead to just use the long-term return on equities as the discount rate, or even the expected return given current valuations (see Rob Arnott’s work on expected returns given valuations). If we can expect the stock market over the next 50 years to appreciate around 8% per year, we would not choose an individual stock over the index unless that stock could be expected to return greater than 8% per year.

A DCF analysis is often conducted out towards infinity. In other words, given our assumptions, we figure the present value of the company infinitely far in the future. If a company were to increase its profit every year at the risk-free rate, than its profit in today’s dollars would remain the same infinitely far in the future. This never happens, so besides a period of relatively quick growth, we introduce a final growth rate for each company that is less than the risk-free rate. For this final growth rate I use the long-run inflation rate. In essence, we assume that after a period of growth the companies do not grow except in nominal returns.

‘Growth’ investors like to say that if you buy a really great, fast growing company, it really does not matter how much you pay for it. They are actually right. As I will discuss later, the faster a stock grows, the more important its growth rate becomes to its investment value. At the extreme, a company that will forever grow earnings at a rate at or above the risk-free rate will be worth an infinite amount of money, and thus its price will always be less than its true value. Conversely, the investment value of a company with zero growth will be determined purely by its current price.

There is much more to DCF analysis than this. We can model changing leverage (debt) rates, changing ROC rates, and just about anything else we want in a DCF analysis. One key, however, is to remember that a DCF analysis is only as good as our assumptions. As I will showed in the article Regression to the Mean, our assumptions are often more inaccurate than we believe.

Disclosure: This article was originally published elsewhere.

My advice to Bill Ackman and anyone else short the bond insurers

I have some advice to any of you who think that now is a good time to short the bond insurers: don’t do it. Don’t mess with the government. By all rights, the bond insurers are already insolvent, dead, and it is only a matter of time before they are gone. However, politicians do not like turmoil and they love bailouts. They also love cheap insurance for government bonds. Therefore, there will be a bailout in some way. It may not save current shareholders, but the bailout has the risk of killing the shorts. For that reason, now is a good time to stay away from MBIA [[mbi]] and Ambac [[abk]].

A theoretical trader who shorted the infamous Semper Augustus tulip bulb at 5000 florins during the Dutch tulip mania would have had a great win snatched by the government’s cancellation of all tulip contracts. This is a similar case where it would be smart to stay out of the government’s way.

For why I think the bond insurers are dead, see Bill Ackman’s letter to the rating agencies about the bond insurers.

Disclosure: I grow no tulips and have no position in any stock mentioned. I have a disclosure policy.