Cops and Regulators

It’s a story that is (appropriately) on the back burner in the media, but the slowly unwinding tale of The Greatest Ponzi Scheme Ever continues. In case you have (appropriately) been paying attention to other things, let me offer a quick recap.

Starting as long as twenty years ago, Bernie Madoff, a well known and successful figure on Wall Street, ran a Ponzi scheme. As with all such scams, he pretended to be putting his clients’ money in a make-believe sure-fire investment. Those few who asked to cash out were given money he raised from other investors. By 2008, Madoff’s imaginary investment empire was worth an imaginary $50 billion.

And he never got caught. Like funds of all kinds, last year he was hit by a wave of people wanting to cash out. Unlike other funds, the money he needed for the withdrawals did not exist. So before things got really really ugly, Bernie turned himself in. (Actually that’s not quite right. He confessed to his sons that he had been running a Ponzi scheme and that he planned to turn himself in. They immediately dropped a dime on Ol‘ Dad. Wall Street is a really tough place.)

That’s a pretty good plotline, but it gets better. If you are, like me, an investment professional in Boston, you have probably met a guy named Harry Markopolos. You might also remember that for several years in the middle of this decade Harry tried to make a living as a freelance financial fraud investigator, sort of a bounty hunter for the investment world. Well it turns out that one of his longest running investigations was Madoff’s ponzi scheme. Markopolos figured out it was a scam as soon as he saw the returns Madoff claimed to be getting in 1999. He then spent the following nine years trying to convince the SEC to do something about it.

We do not yet know why the SEC did nothing. Further plot thickeners such as bribery or blackmail are certainly possible, but not likely. The mundane truth is that the SEC is just not that good at what most people think they do for a living. They are regulators and not cops. There is a difference.

To illustrate this, let me change subjects abruptly to an excellent article in the Atlantic last November by Jeffery Goldberg. It is the account of his concerted multi-year effort to get himself placed on the TSA’s notorious No Fly List. He failed, although he did manage to have a nail clipper and a can of shaving cream confiscated. On other occasions he boarded planes with items that ought to have raised some eyebrows, including lengths of rope, dustmasks, full sized Hezbollah flags, and of course, the traditional box-cutter. He also used badly forged boarding passes and at one point ripped up a stack of them in view of a TSA officer. (I thought the article was hysterically funny. Most of my friends swore they’d never fly again. Go figure.)

The TSA didn’t stop Goldberg for the same reason that the SEC didn’t stop Madoff. They are regulators. They employ large numbers of comparatively underpaid and undertalented people to make sure that most folks mostly keep within regulations most of the time. That can be a worthwhile government function (not in the case of the TSA) but it’s completely different from finding the really bad guys and throwing them in jail.

If you point out an obvious wrongdoer to a cop he will arrest him and then, if necessary, work out exactly which crimes have been broken. Point out to a regulator a wrongdoer who is not obviously breaking any regulations, and the outcome will be paralysis. We don’t know for sure yet, but I will bet real money that is what happened at the SEC. They stood around scratching their heads trying to figure out what SEC rules were being broken by Madoff, couldn’t come up with any, added in the fact that there were no complaining victims, and decided to move on to other cases.

If you are confused (or outraged) that the SEC might not see any obvious violations to pursue with Madoff, you are not thinking like a regulator. Regulators work with very detailed and specific rules that they try to jam everybody and everything into. There is no such thing as “the spirit” of a regulation and no general remit for the regulator to fight evil beyond what is very specifically allowed or not. Madoff was not selling securities, as the law defines them. The SEC had a lot of rules about how Madoff could invest his clients’ money in the public markets, but nobody has alleged that he broke any rules there. (Not surprising, given that he apparently didn’t invest his clients’ money at all.) Expecting the SEC to go after Madoff under the general principle that he might have been carrying out the greatest securities related fraud in history is like expecting the airport screener to take a closer look at the unlikely items in the carry-on of the guy in the al-Qaeda tee shirt. (Seriously. Goldberg wore one. Read the article.)

Markopolos had no direct contact with Madoff. (He still mispronounces his name. It’s MADE-off, as in “Bernie made off with a whole lot of money.”) Which raises the question, why didn’t any of the thousands of other people who must have come across the same data in the course of their business come to the same conclusions as Markopolos did and alert the SEC? It’s possible a few did, but it is clear that the vast majority of financial professionals did nothing. Again, because the SEC are regulators, not cops.

Innocent or guilty, dealing with regulators is a painful drag. As a wag once put it “the process is the penalty.” Unless you are absolutely sure something is rotten you just don’t finger your fellow man to a regulator. And even then probably not. You might call the cops if you thought that perhaps your neighbor was beating his wife, but it is almost inconceivable that you would call the IRS because you knew for a fact he was cheating on his taxes.

Obviously, what the Madoff scam needed was cops, not regulators. But there were lots of cops. This was, after all, plain old fraud in fancy packaging. The police in any of the hundreds of jurisdictions where Madoff’s victims lived could have, in principle, investigated him. And of course there was the FBI. But if Markopolos had brought his story to any of these I am sure they would have all sent him back to the SEC. Wall Street fraud is their thing, isn’t it? The final irony is that had Madoff claimed to be investing his clients’ money in something other than regulated securities, Manhattan real estate for example, he almost certainly would have been stopped a long time ago.

Compared to the global economic crisis and our government’s fumbling responses to it, the Madoff story is relatively minor, almost a comic relief. It would be unfortunate, but not all that unexpected, for the two stories to become intertwined in public memory, as popular imagination blames “accounting scandals” like Enron and Worldcom for the tech bubble bursting and blames fraudsters for the great S&L fiasco of the early 1990s. We already hear vague accusations that the root cause of our problems is a failure of regulators to properly regulate. As regards Madoff, the opposite is true. The regulator did everything we could have expected of it. It was our mistake for expecting anything more.

Phil Town’s Rule #1, Part #4

[This is part 4 of a multi-part review of Phil Town's book Rule #1, The Simple Strategy for Successful Investing in Only 15 Minutes a Week! If you haven't already, you might want to read Part 1, Part 2 and/or Part 3 first.]

This is a strained analogy, but I think it works.

You are driving along on a quiet Saturday night. Phil Town pulls up alongside you in a big flashy car. He leans out the window and says “Hey, for $25 ($35 in Canada) I can take you to the coolest party ever.”

“Uh, I dunno…”

“It’s at this really gorgeous mansion on the beach. There’s an open bar, a huge gourmet buffet, and dozens of beautiful scantily-clad young people of both sexes who are tipsy and really open-minded, if you know what I mean. Also, the Rolling Stones said they would drop by later and play a few sets.”

Now you are pretty sure this is too good to be true, but there is that slim chance this smooth guy in the expensive car is telling the truth, and it is only $25. So why not? You hand over the money and Phil, assuring you the party is nearby, tells you to follow him. Which you do, weaving in and out of traffic at increasing speeds, making hairpin turns on mountain roads, running red lights, going the wrong way on one-way streets, and so on. Finally, Phil drives off the end of a pier, whereupon you discover that his car is actually amphibious. You stay on shore, watching him sail off into the sunset, calling back to you that the party is just a little farther.

So if by some miracle you have gotten through the main stock selection bits of Rule #1 with your sanity intact and a stock or two to buy, Town has just a little more work for you. We are almost there, you can hear him say.

On page 196 of Rule #1 Town introduces what he calls “the Tools” and what the rest of us investment types call technical indicators. Technical analysis is probably older than you think, possibly as old as the stock market, but at least as old as the familiar charts that show stock prices over time as squiggly lines. It is the developed pseudo-science of chart reading, based on the idea that stock prices follow a pattern that allows you to predict their near-term future. The name “technical” is old too, dating from a pre-computer era when the field seemed high-tech and nearly mystical.

Town is agonizingly ambiguous about the role that the Tools play in Rule #1 and vague about the specifics of how to use them, or even which exact tools to use. He instructs his readers to treat them as something they should follow without hesitation or reflection but also says “I’m not married to the specific set of Tools that I’m about to introduce to you.” He recounts how they have made him money, but seems to sell them to the reader primarily as confidence building accessories that will help a person pull the trigger and invest.

I am not going to conduct a backtest of the Tools. This because: 1) You are probably sick of backtests by now. 2) Town does not quite say that the Tools make money, in fact he is clear that as a stand-alone they do not, so finding that they do not work would not be a refutation of anything. And 3) Town is so unspecific about which tools to use, and how, that whatever results I got could be brushed aside by a true believer on the grounds that I did not do what Town really meant.

The three tools that Town recommends, but is not wedded to, are called MACD, Stochastics, and moving average. They are all, essentially, complex formulas that take only past prices of a stock as inputs and attempt to produce a “signal” that will predict if the stock is on its way up or down in the near future.

I have a lot of disdain for these sorts of tools. (Could you tell?) It is not that the underlying phenomena that they try to capture do not exist. They do. Stock prices really do exhibit some “momentum,” meaning that a stock that has been going up over the past three to six months is a little more likely to go up in the near future than one that has been flat. And over shorter periods, a few weeks for example, stock prices really do tend to revert, that is, stocks that have gone up or down a lot over a short period tend to give or get back some of the price movement right afterwards. These are small effects, but they are real and with enough data a person can prove it.

But these effects are not just small, they are simple. Calculations like MACD are not any more predictive than much less complex measures of price momentum. They have a lot of moving parts, in my opinion, just for the sake of having a lot of moving parts. It makes them seem so much more sophisticated and meaningful that way. In fact, these tools are no more subtle than looking a stock chart and saying “Golly, this has been going up all year. I think I’ll buy some.” or “Gosh, this has really been beaten up this week. I think I’ll buy some.”

Moreover, and here is where Town’s car is revealed to be a boat, these technical buy and sell indicators are by their nature short term. If you follow them you will inevitably be buying and selling every few weeks. Town gives the happy story of a couple who successfully used his system to make lots of money over two years in the stock of the Cheesecake Factory. They bought and sold the stock eleven times during that time. That is almost a trade in or out every month. Understanding, very late in the book, that this is what Town has in mind is probably a jarring surprise for many readers. In most of the book he stresses that he buys companies, not stocks, and that he would never buy a stock he was not willing to hold for ten years. Warren Buffet, an investor known particularly for his patience and long-term view, is cited as an inspiration throughout the book (he appears in the index 29 times) and the title is taken from something the great man said.

And yet, when you get down to it, Rule #1 is a form of investing that relies on a lot of short term trading. Look at any stock’s price chart and it is easy to imagine how profitable it could potentially be to trade in and out, buying on lows and selling on highs, provided, of course, you knew when those lows and highs were. The point is that that is true about any stock, not just that one in a thousand that passed the growth and value screens.

[Links to parts of this review: Part 1, Part 2, Part 3, Part 4, and Part 5]

Phil Town’s Rule #1, Part #3

[This is part 3 of a multi-part review of Phil Town's book Rule #1, The Simple Strategy for Successful Investing in Only 15 Minutes a Week! If you haven't already, you might want to read Part 1 and/or Part 2 first.]

Last time I walked through the third of Town’s Four Ms. Today it’s the turn of the fourth, Margin of Safety. As a concept and phrase, margin of safety has a long and august history. Benjamin Graham, Warren Buffet’s mentor and the founding father of modern value investing, coined it in the 1930s. The idea is that if you buy a stock at enough of a discount it is hard for things to go wrong. To be specific, if you buy it for less than liquidation value, the value of the company’s tangible assets less its debts, then the worst case scenario is that the company will go out of business, auction off what it owns, and make you whole. That is quite a safety net.

Graham was writing and investing in the Great Depression and its aftermath. Even by today’s measures, the bargains available in the stock market in the 1930s and 1940s were inexplicable. Stocks that sold for less than book value were common. So when Graham talked about margin of safety he was making a pretty convincing “what’s the worst that could happen?” argument. Buy something for half of what it is really worth, and even assuming things go badly, you have a big cushion to fall back on.

Things have changed a lot since the concept of margin of safety was born. Looking for stocks you can buy for less than liquidation value is not a viable strategy. When Town talks about a margin of safety he is not suggesting that there is a liquidation value safety net, he is just making the argument that if a stock is cheap enough the cards are stacked in your favor. That is not a terrible way to invest, but it is not about safety. What he is saying is that you should buy cheap stocks because they tend to go up. Which is true. The trick is deciding which stocks are the really cheap ones.

There are lots of ways to do this, ranging from the exquisitely complex to the brutally simple. Entire books have been written on the topic. Town’s methodology is definitely on the simple side, although still more bother than it is worth.

The most annoying part of his valuation method is that he calls the value that gets calculated for the stock not the “true value” or “fair value” but “sticker price.” What could be more jarringly inappropriate? A sticker price is what a car manufacturer puts on the sheet of paper glued to the window of a new car in the forlorn hope that somebody, somewhere, will pay that much for it. Why not just call it the “unrealistic goal price?”

In a nutshell, Town instructs the reader to value a stock as follows. 1) Project earnings per share ten years from now. 2) Project a price/earnings ratio for ten years from now. 3) Use the future earnings and future price/earnings ratio to back out a price for the stock in ten years. 4) Discount that back into today’s dollars.

I will not repeat Town’s specific instructions for coming up with earnings projections, future P/E ratios, and the like. Suffice it to say that all are somewhat questionable, often obscure, and easily expressed as computer code I can use to test it.

Backtesting this value portion of Rule #1 is actually easier than the growth part. With fewer numbers as inputs, it runs faster and lets more stocks pass. But passing stocks are still pretty rare. Only 45 of the 1000 met the cutoff on December 31, 2007. That’s more than passed the growth test, but it’s still fewer than 1 in 20. (Again, running this without computer automation would be at best torturous.) And how did the passing stocks do? Not so great. The 45 lost an average of 47.19% during 2008, against an average loss of merely 37.01% for the other 955.

For the nine years 2000-2008, Town’s Margin of Safety screen selected an average of 51 stocks at the start of each year and on average they lost 0.27% over the next 12 months. The stocks that did not make the cut rose an average of 3.00%. That’s really pretty dismal. Any worse and I might suggest that shorting these names was a reasonable strategy.

Of course, Margin of Safety is not meant as a stand-alone. Town would have you invest in stocks that pass both the growth (Moat) and value (Margin of Safety) screens. So how many stocks passed both screens as of 12/31/07? Just one: Cognizant Technology. It lost 46.78% last year.

Overall, of the nine years of the sample, four (2000, 2002, 2004, and 2007) had no stocks at all that passed the two screens. The other five years had a grand total of 11 names that qualified. As it happens, some of those picks did pretty well. Others did poorly, but the average annual return was 14.77%, a little more than 10% better than the unselected members of the 1000 did in the same years.

And so what? This is hardly an actionable plan for putting your money to work in the stock market, given that there is nothing at all to buy half the time. And finding these needles in a haystack is not really practical without specialized software. Nor is this, with such a tiny sample, evidence that Rule #1 works after all. And Town is not done yet. There are still more parts to this “simple strategy for successful investing in only 15 minutes a week.” Stay tuned.

[Links to parts of this review: Part 1, Part 2, Part 3, Part 4, and Part 5]

ETFs and Other Mutual Funds

Million Dollar Journey today asks Can You Invest Solely in ETFs? The answer given is, basically, yes. And that is true. You could also live for a week eating only pickles. At least I’m pretty sure.

This is probably as good a time as any to give a quick rundown of the differences between open-end mutual funds and ETFs.

What is usually meant when somebody says “mutual fund” is an open-end mutual fund. Like with all funds, what you own when you own shares in an open-end fund is a proportionate share of a large portfolio of assets run by a management company.

With an open-end fund, you can buy or sell shares only once a day, at a price calculated based on the closing prices of everything in the portfolio. When you buy/sell shares, you are trading with the fund itself. If you buy, your money goes in the fund and new shares are issued to you. If you sell, your shares are cancelled and cash comes out of the fund.

Most open-end funds are “active” meaning that the management company is actively deciding on a day to day basis what to have in the portfolio. A sizable minority are “passive” or “index” funds that simply hold the members of a published index, such as the S&P 500.

ETFs, or Exchange Traded Funds, are similar in that you own shares of a portfolio, but these trade all day long on the stock exchange like a stock. When you buy or sell shares of ETFs, you are trading with another investor who is selling or buying.

For reasons I will spare you, ETFs are always passively managed portfolios.

In both types of fund the management company that runs it gets paid in the form of annual fees, sometimes referred to as “expenses.” (I’m not sure if an “expense” sounds smaller than a “fee”, but it sure does sound more unavoidable.) How much the management company charges varies a lot from fund to fund, but as a general rule, active open-end funds charge the most, followed by ETFs, followed by passive open-ended funds. Additionally, to buy or sell an ETF you would pay a commission to a stock broker.

So if ETFs are, essentially, index funds with higher fees than otherwise identical open-end index funds, why would you invest in them? The short answer is that most people reading this shouldn’t. The long one is that there are a few situations in which it makes sense. Since ETFs trade like stocks you can short them, buy them on margin, and trade them at a moment’s notice. There are also some rather exotic types of assets available as ETFs but not as open-ended funds. But if you are a typical investor looking to hold a vanilla index for more than a week or two, ETFs will only cost you more money.

Phil Town’s Rule #1, Part #2

[This is the second installment of a review of Rule #1, by Phil Town. If you haven't already, you might want to read part 1 first.]

Rule#1 starts with a bang. From page 1:

This book is a simple guide to returns of 15 percent or more in the stock market, with almost no risk. In fact, Rule #1 investing is practically immune to the ups and downs of the stock market – and by the end of the book I’ll have proved it to you.

The First Amendment is a wondrous thing. You can say anything you want in a book (or a blog) and the worst thing that will happen to you is that people will think you are a jerk or an idiot. On the other hand, if Phil Town had started a mutual fund and put this paragraph at the start of his sales brochure, government regulators would have shut him down right away. (Although as a hedge fund he might have gotten away with it for a while. This is almost exactly what Bernie Madoff claimed to be delivering to his clients.)

As I wrote in part #1, there are lots of books that promise a formula for getting rich picking stocks. What makes Rule #1, The Simple Strategy for Successful Investing in Only 15 Minutes a Week! attractive as a victim of my scrutiny is that most of Town’s “simple strategy” is very specific. So specific, in fact, that I can program a computer to carry it out. I can go back in time and work out what stocks his system would have picked and track their performance. This is what is known in the investment biz as a backtest. It’s the first thing that would pop into the head of a pro being pitched on a system for picking stocks. It is pretty clear that Town’s mind is uncluttered by such concepts.

Town summarizes the core of his system, not all that gracefully, as four Ms: Meaning, Management, Moat, and Margin of Safety. Meaning and Management are squishy subjective things. And squishy subjective things annoy me. By Meaning, Town signifies both that you should understand the business of the company involved and that it should resonate with you in a vaguely moral way. And by Management he means that you should make sure that it has good management. I can’t teach my computer to simulate these two, so they get a free pass.

Moat turns out to be a set of ratios Town calls the Big Five. Four are growth rates: growth in sales, earnings, free cash flow, and book value. And the fifth, ROIC, is strongly associated with growth. (ROIC, according to Town, stands for Return On Investment Capital. Actual investment professionals believe it stands for Return On Invested Capital.)

Town says you should calculate each of the numbers three times, for one, five, and ten year time periods. Then, if a stock has a score of at least 10% on each of these fifteen numbers it is attractive enough to be further considered for purchase. I can only assume that his intent is that his reader should do this by hand, one stock at a time, which would eat up the weekly 15 minute time allotment pretty fast. But with access to the right tools, I can do 1000 stocks relatively easily.

Which is exactly what I did. I took the 1000 largest stocks in the US as of December 31, 2007 and found those that pass the Rule #1 Moat test. There are exactly 20 of them. Which means that only 1 in 50 stocks pass this screen, and there are more screens to come. Imagine what it would be like to use this system without automation, testing one stock at a time. And 12/31/07 is pretty typical. I tested the eight previous years and found, on average, 16 stocks that cleared the screen out of possible 1000.

Of course, the point is to find stocks that will go up, and on this score the screen is marginally better than throwing darts. The 20 stocks that cleared the hurdle at the end of 2007 lost an average of 34.67% in 2008. That’s actually not that bad, as the other 980 stocks gave up 37.53% on average. Including the other eight years of this decade the stocks that met the criteria to pass the Moat test returned an average of 4.29%, against 2.82% for the others. That ain’t terrible, but consider:

1) So few stocks clear the screen that one or two lucky picks can make the whole thing look good. In 2000 the screen only picked 5 names, but two of them, Paychex, up 83% for the year, and Concord EFS, up 71%, did very well. Kick out those two and the average return for the screened stocks for the whole nine years drops to 0.14%.

2) 4.29% is nothing like the 15% returns promised.

3) So few stocks clear this screen, and remember this is only part of the Simple Strategy, that a person has to wonder if this is really a practical methodology for an ordinary investor.

Next up, I will continue with Rule #1′s value screen, the Margin of Safety.

[Links to parts of this review: Part 1, Part 2, Part 3, Part 4, and Part 5]