building a new company HQ–a sign of trouble ahead?

This is a long-standing Wall Street belief.  The basic idea is that as companies expand and mature, their leadership gradually turns from entrepreneurs into bureaucrats.  The ultimate warning bell that rough waters are ahead for corporate profits is the announcement that a firm will spend huge amounts of money on a grandiose new corporate headquarters.

An odd article in the Wall Street Journal reminded me of this a couple of days ago.  The company coming into question in it is Amazon, which has just initiated a search for the site of a second corporate HQ.

What’s odd:

–why no comment on Apple’s new over-the-top $5 billion HQ building?

–the headquarters idea was followed by a discussion of research results from a finance professor from Dartmouth, Kenneth French, which show that publicly traded firms with the highest levels of capital spending tend to have underperforming stocks.

I’ve looked on the internet for Prof. French’s work, much of which has been done in collaboration with Eugene Fama.  I couldn’t find the paper in question, although I did come across an interesting, and humorous, one that argues the lack of predictive value of the capital asset pricing model (CAPM)–despite it’s being the staple of the finance theory taught to MBAs.  (The business school idea is apparently that reality is too complicated for non-PhD students to understand so let’s teach them something that’s simple, even though it’s wrong.)

my thoughts

–money for creating/customizing computer software, which is one of the largest uses of corporate funds in the US, is typically written off as an expense.  From a financial accounting point of view, it doesn’t show up as capital spending.

–same thing with brand creation through advertising and public relations.  I’m not sure how Prof. French deals with this issue.

Over the past quarter-century, there’s been a tendency for companies to decrease their capital intensity.  In the semiconductor industry, this was the child of necessity, since each generation of fabs seems to be hugely more expensive than its predecessor.  Hence the rise of third-party fabs like TSMC.

For hotel companies, it has been a deliberate choice to divest their physical locations, while taking back management contracts.  For light manufacturing, it has been outsourcing to the developing world, but retaining marketing and distribution.

 

What’s left as capital-intensive, then?  Mining, oil and gas, ship transport, autos, steel, cement, public utilities…  Not exactly the cream of the capital appreciation crop.

 

At the very beginning of my investment career, the common belief was that high minimum effective plant size and correspondingly large spending requirements formed an anti-competitive “moat” for the industries in question.  But technological change, from the 1970s steel mini-mill that cost a tenth the price of a blast furnace onward, has shown capital spending to be more Maginot Line than effective defense.

So it may well be that the underperformance pointed to by Prof. French has less to do with profligate management, as the WSJ suggests, than simply the nature of today’s capital-intensive businesses–namely, the ones that have no other option.

 

 

 

 

 

 

volatility, non-correlation …and beta

risk as volatility

Today is about volatility as a measure of risk.

It’s the standard academic method of assessment.  It has a certain initial intuitive plausibility.  After all, if your portfolio values is going all over the map, that sounds bad compared with one that just stays in one place.  Of course, the latter strategy is less damaging when there’s no inflation.  And there’s embedded just below the surface the efficient markets assumption that the highest possible return one can achieve is the market return.  The extra movement created by active management is not only occasionally scary, it just subtracts from your wealth.

you can’t spend risk-adjusted dollars

One of my old bosses used to say that you can’t spend risk-adjusted dollars.  What he meant is that higher volatility may be the price of achieving higher returns.  It doesn’t follow from this, other than in the ivory tower, that lower volatility/lower return investing is just as good.

Take the following two portfolios:

–one is trending upward at the rate of 15% annually, but at the end of any given month, can be as much as either 10% above or 10% below that trend

–the other is trending upward at the rate of 10% annually, but at the end of any given month can be as much as either 3% above or 3% below the trend.

At the end of ten years, the first portfolio is up by 300%, +/- 10%.

The second is up by 160%, +/- 3%.

Try explaining to the second client that he’s just as well off as the first.

why use volatility

Why use volatility as a measure, then?

The main reason, I think, is that data are easily available for computers, so volatility has the feel of being objective.  Another is the semi-religious belief that outperformance is impossible, in which case having extra volatility is an undiluted negative.  (By the way, having a portfolio that outperforms the market day after day, month after month, in an up market is, by definition, more volatile than an index fund.)

caveats

For someone who needs the money tomorrow, or next week or next month, a long-term investment with short-term volatility is the last place we want money to be.

Older investors, who are using savings to live on, have got to have a substantial cash reserve to avoid having to sell potentially volatile holdings during a -10% phase.

And a portfolio that consistently produces low returns coupled with high volatility has trouble written all over it.

daily volatility, non-correlation …and beta

My wife and I are in the process of hiring a financial planner.  While I think this is important to do, our search has brought me back into vivid contact with some of what I consider the nonsensical jargon of academic finance.  I want to write about the general idea of “non-correlated assets,” but I’m going to start by writing about beta.

beta…

In the early days of computer-driven finance, just after WWII, economist Harry Moskowitz proposed beginning to assess the risk of a portfolio by analyzing the interrelationships among individual stocks in it.  That task proved too daunting for the computers of the day for anything but small numbers of stocks.  Others suggested correlating everything to one standard, an index like the S&P 500, for instance, instead.

The regression that would do this has the form of y = α + β(S&P).  This is how beta, the correlation between a given stock’s price movement and that of the market, was born.

So far, so good.

…and gold stocks

One day, people discovered that there was a class of stocks–gold stocks, in particular– that had a beta of 0.  This spawned the idea, encouraged by the gold-bug prejudices of the day, that one could lower the beta of a portfolio just by adding gold stocks.  One could add, say, technology stocks with a beta =2 and offset the risk by adding gold stocks in the same amount.  Simple math said the combination had a beta = 1, or risk exactly equal to that of the market.

Some institutional investors actually bought the theoretical argument about the “magic” property of gold and altered their portfolios in the way I just described.

By doing so, they exposed themselves to the 20-year bear market in the yellow metal that lasted from 1950 to 1970.  They lost their shirts.

They realized only afterward that a beta of zero did not mean that the asset in question had no risk.  It meant instead only that the zero-beta asset did not rise and fall in price in line with the stock market.  In this case, the “uncorrelated” price went straight down during a period when the S&P gained 500%+.  So much for non-correlation.

More tomorrow.

 

 

 

why cash dividends?

In its most common form, a dividend is a distribution of a portion of a corporation’s profits to shareholders in cash.

Yesterday, the Financial Times published an article titled “Alarm grows as investors get bulk of listed groups’ profits:  Unusual situation that tends to occur only in periods of widespread economic weakness.”

The thrust of the article is that companies in the large-cap MSCI Global index are now paying out 51% of their profits in dividends.  That’s up from 43% two years ago (when presumably income for everyone not in natural resources was lower).  It’s also higher than the long-run median of 46%.

Suggested but not stated is the idea that these companies are mortgaging their long-term future by skimping on capital investment to satisfy myopic income-oriented investors. The subtitle of the article suggests the high payout ratio may be a harbinger of recession.

Personally, I’m not alarmed.  And I’m not sure the current situation is that unusual.  In fact, my experience is that corporate attitudes toward, and investor preferences about, dividends vary widely over different time periods and in different parts of the world.

That’s what I’ll be writing about over the next few days.

Some preliminaries today:

–dividends are supposed to be paid out of earnings.  If a company has no current or past profits, it can still make a distribution (why it would is a different question–although some fixed income funds do do this). That kind of distribution is called a return of capital.  The main practical difference is that a return of capital isn’t subject to income tax.

–sometimes a stock split is structured as a dividend.  In the US, this typically happens when the split is very small, like 21 for 20, which would be a 5% stock dividend. In most countries, managements doing so as a substitute for a cash dividend and appear to be hoping that shareholders accept this number shuffling instead of money it (a) wants to retain   …or (b) doesn’t have.

–spinoffs of assets are sometimes structured as dividends, as well.

–managements of dividend-paying companies tend to want to at least maintain the current level of recurring dividend payments.  If a company is feeling especially flush in a given year, it may decide to declare an extra one-time dividend payment.  It will label the payment as “special” or “extraordinary,” to make sure shareholders understand this is not a recurring event.

–unlike the case with preferred shares or coupon-bearing debt, management makes no promises to maintain the current level of dividend payments, or even to pay a dividend at all.   Around the world, however, a dividend cut, meaning reduction or elimination of the dividend payout, is regarded as a very bad thing.  It usually provokes a sharp negative reaction in the stock price   …more so outside the US than inside.  That’s because it signals either very poor management planning or a sharp deterioration in a company’s business.  Investors also tend to have very long memories when it comes to dividend reductions.

–in my experience, the best indicator of a possible future dividend cut is that the company has cut the dividend in the past.  The next best is a close analysis of the sources and uses of funds section of the financial statements.

 

More tomorrow.

 

 

more on risk as volatility

volatility as risk

I was listening to Bloomberg radio the other day when a talking head who usually has interesting things to say (an increasing rarity on Bloomberg) began to “explain” how 2015 was a very risky year for stocks.  This, even though the S&P 500 was ending December in basically in the same place it started out in January.

Measures of interday change in individual stock prices were also relatively benign   …but, he said, intraday price movements in stocks were unusually high.  Therefore, stocks were riskier than usual.

Yes, in a very tortured sense…or for a day trader who’s consumed by hour-to-hour price movements…that might be so.  For you and me, though, that’s crazy.

 

Last September 14th I wrote another post about the academic notion that investment risk can be defined as day-to-day volatility, i.e., the daily change in the price of a given security.

The main pluses for this idea are that it’s simple, the data are readily available and you don’t have to know anything about the security in question or the goals of the holder.

In my earlier post, I pointed out that this notion led to catastrophic results in the late 1980s-early 1990s for institutional holders of commercial real estate and junk bonds.  Neither traded very often, so the daily price–as determined by the last actual transaction–rarely changed. Volatility was negligible.  What a surprise when lots of people wanted to sell at the some time, only to find that low volatility didn’t represent safety.  It signaled illiquidity–there were no buyers at anywhere near the last trade.

not a 100% useless concept

There is a sense in which volatility may be important, though.  Over several year periods, stocks tend to follow an up and down pattern that mirrors the business cycle, with stocks leading the economy by about six months.  Over longer periods, stocks tend to advance on trend around the rate of growth in reported profits, which has historically been about +8% per year in the US.

 

If you’re in your thirties or forties and saving for your retirement or to pay for your young children’s college tuition, then daily or even business cycle fluctuations in stock prices are irrelevant now.  Investing in stocks that have low volatility–which usually also comes with low appreciation potential–makes no sense at all, despite the notion’s academic pedigree.

On the other hand, if you’re saving, say, for a wedding or to buy a house and will need the funds in six months or a year, then having it in stocks is probably a bad idea.  That’s because prices could easily be 10% below today’s level when you need the money.  Just look at a chart of the S&P 500 in 2015–which chronicles a mid-summer S&P swoon– to see what I mean.  In this case, keeping your money in (low-volatility) cash is the better course of action.

 

 

 

 

risk and volatility

risk

I think that defining what risk is is the most difficult topic in finance/investing.

I’m not sure there’s one answer that fits everyone and everything.

We do know that individuals’ perception of what risk entails changes as they age or as their wealth increases; they become more conservative.  We also know that appearances can be deceiving.  A model with a perfectly proportioned body may be clumsy or a terrible athlete.  Experience counts for something, as well.  Situations that appear risky when a neophyte is in control, like in doing brain surgery, may in fact be relatively safe in the hands of an expert.  Information is important, too, like having enough data or experience to know who is the beginner and who is the well-trained seasoned pro.

risk as volatility

Academic finance, and following its lead, pension consultants and their pension fund clients, have all chosen to reduce this complexity to a single concept, risk = volatility.  In other words, the magnitude of day to day price changes in securities. This can be expressed either in absolute form or relative to some benchmark, and may be measured over differing time periods.

Defining risk as volatility has three big advantages:

–easy data availability

–quantitative form

–simplicity.

In a world where no one runs with scissors or texts while driving, or where there’s never a flood, a tornado or huge food items falling from the sky (like in Chewandswallow), that would be enough.

In practice, however, volatility isn’t such a hot measure.

On a very abstract level, there’s no recognition of the issue that philosophers have been pondering for the past two centuries or so–that groups may not be connected by every member having a single thing in common.  One alternative is the possibility of “family resemblances” popularized by Ludwig Wittgenstein over a half-century ago.  So maybe there isn’t one common factor that constitutes risk.

On a more practical level, in the real world not everyone has the same information.  History also shows that markets periodically become highly emotional, either wildly optimistic or deeply pessimistic.  My conclusion, based on decades of experience, is that the results of daily trading don’t constitute infallible indicators.  Quite the opposite–most often one should take the evidence of daily trading with a grain of salt.

…but does it trade?

To my mind, though, the most striking failure of volatility as a risk measure is that it doesn’t take liquidity into account.

An example of what I mean:

In the mid 1980s, I came across for the first time academic articles that touted real estate as the most attractive of major asset classes.

How so?

The argument was that since the end of WWII real estate had not only a higher annual rate of return than stocks or bonds, but it also had the lowest average price volatility of the three.  Not only did real estate deliver the highest absolute gains, but adjusting for its low “risk” property ownership looked even better.  This was an odd result, because one typically thinks that reward and risk are directly correlated, not inversely.  But no one questioned it.

real estate

Anyone who has owned a home over an extended period of time, to say nothing of owners of commercial or office real estate, knows this is loony.  In bad times, bank finance disappears and, along with this, so too transactions.  During 1981-83 in the US, when I experienced this phenomenon first-hand, houses could only be sold at extremely steep discounts to pre-recession prices–or to owners’ notions of fair value based on rental equivalents.  Potential buyers made very low-ball offers, prospective sellers took their homes off the market, and no transactions happened.  In the very narrow sense, therefore, volatility was low.  But that was because there were no sales to demonstrate how the market had deteriorated, prices were stable.  You just couldn’t sell.

junk bonds

The collapse of the junk bond market in the late 1980s demonstrated the same idea.  Junk bonds had been touted as having “all the rewards of stocks with all of the safety of bonds.”  The safety part proved an illusion.  The apparent stability of the net asset values of junk bond funds ended up resting in large part on the fact that the bonds they held seldom traded.  So every day the funds priced themselves using more or less the last trade, which might have been weeks ago–and which might not reflect current circumstances.  This idyll lasted until funds began to have net redemptions, forcing them to sell bonds at real market prices, which were often way below their carrying value on  fund books.