How Lucky Do You Feel?

How Lucky Do You Feel?

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Nine years ago, I wrote about the so-called “Fed Model.” The insights there are still true, though the model has yielded no useful signals over that time. It would have told you to remain in stocks, which given the way many panic,, would not have been a bad decision.

I’m here to write about a related issue this evening.  To a first approximation, most investment judgments are a comparison between two figures, whether most people want to admit it or not.  Take the “Fed Model” as an example.  You decide to invest in stocks or not based on the difference between Treasury yields and the earnings yield of stocks as a whole.

Now with interest rates so low, belief in the Fed Model is tantamount to saying “there is no alternative to stocks.” [TINA]  That should make everyone take a step back and say, “Wait.  You mean that stocks can’t do badly when Treasury yields are low, even if it is due to deflationary conditions?”  Well, if there were only two assets to choose from, a S&P 500 index fund and 10-year Treasuries, and that might be the case, especially if the government were borrowing on behalf of the corporations.

Here’s why: in my prior piece on the Fed Model, I showed how the Fed Model was basically an implication of the Dividend Discount Model.  With a few simplifying assumptions, the model collapses to the differences between the earnings yield of the corporation/index and its cost of capital.

Now that’s a basic idea that makes sense, particularly when consider how corporations work.  If a corporation can issue cheap debt capital to retire stock with a higher yield on earnings, in the short-run it is a plus for the stock.  After all, if the markets have priced the debt so richly, the trade of expensive debt for cheap equity makes sense in foresight, even if a bad scenario comes along afterwards.  If true for corporations, it should be true for the market as a whole.

The means the “Fed Model” is a good concept, but not as commonly practiced, using Treasuries — rather, the firm’s cost of capital is the tradeoff.  My proxy for the cost of capital for the market as a whole is the long-term Moody’s Baa bond index, for which we have about 100 years of yield data.  It’s not perfect, but here are some reasons why it is a reasonable proxy:

  • Like equity, which is a long duration asset, these bonds in the index are noncallable with 25-30 years of maturity.
  • The Baa bonds are on the cusp of investment grade.  The equity of the S&P 500 is not investment grade in the same sense as a bond, but its cash flows are very reliable on average.  You could tranche off a pseudo-debt interest in a way akin to the old Americus Trusts, and the cash flows would price out much like corporate debt or a preferred stock interest.
  • The debt ratings of most of the S&P 500 would be strong investment grade.  Mixing in equity and extending to a bond of 25-30 years throws on enough yield that it is going to be comparable to the cost of capital, with perhaps a spread to compensate for the difference.

As such, I think a better comparison is the earnings yield on the S&P 500 vs the yield on the Moody’s BAA index if you’re going to do something like the Fed Model.  That’s a better pair to compare against one another.

A new take on the Equity Premium

A new take on the Equity Premium!

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That brings up another bad binary comparison that is common — the equity premium.  What do stock returns have to with the returns on T-bills?  Directly, they have nothing to do with one another.  Indirectly, as in the above slide from a recent presentation that I gave, the spread between the two of them can be broken into the sum of three spreads that are more commonly analyzed — those of maturity risk, credit risk and business risk.  (And the last of those should be split into a economic earnings  factor and a valuation change factor.)

This is why I’m not a fan of the concept of the equity premium.  The concept relies on the idea that equities and T-bills are a binary choice within the beta calculation, as if only the risky returns trade against one another.  The returns of equities can be explained in a simpler non-binary way, one that a businessman or bond manager could appreciate.  At certain points lending long is attractive, or taking credit risk, or raising capital to start a business.  Together these form an explanation for equity returns more robust than the non-informative academic view of the equity premium, which mysteriously appears out of nowhere.

Summary

When looking at investment analyses, ask “What’s the comparison here?”  By doing that, you will make more intelligent investment decisions.  Even a simple purchase or sale of stock makes a statement about the relative desirability of cash versus the stock.  (That’s why I prefer swap transactions.)  People aren’t always good at knowing what they are comparing, so pay attention, and you may find that the comparison doesn’t make much sense, leading you to ask different questions as a result.

 

Photo Credit: GotCredit

Photo Credit: GotCredit

This is another piece in the irregular Simple Stuff series, which is an attempt to make complex topics simple.  Today’s topic is:

What is risk?

Here is my simple definition of risk:

Risk is the probability that an entity will not meet its goals, and the degree of pain it will go through depending on how much it missed the goals.

There are several good things about this definition:

  • Note that the word “money” is not mentioned.  As such, it can cover a wide number of situations.
  • It is individual.  The same size of a miss of a goal for one person may cause him to go broke, while another just has to miss a vacation.  The same event may happen for two people — it may be a miss for one, and not for the other one.
  • It catches both aspects of risk — likelihood of a bad event, and degree of harm from how badly the goal was missed.
  • It takes into account the possibility that there are many goals that must be met.
  • It covers both composite entities like corporations, families, nations and cultures, as well as individuals.
  • It doesn’t make life easy for academic economists who want to have a uniform definition of risk so that they can publish economics and finance papers that are bogus.  Erudite, but bogus.
  • It doesn’t specify that there has to be a single time horizon, or any time horizon.
  • It doesn’t specify a method for analysis.  That should vary by the situation being analyzed.

But this is a blog on finance and investing risk, so now I will focus on that large class of situations.

What is Financial Risk?

Here are some things that financial risk can be:

  • You don’t get to retire when you want to, or, your retirement is not as nice as you might like
  • One or more of your children can’t go to college, or, can’t go to the college that the would like to attend
  • You can’t buy the home/auto/etc. of your choice.
  • A financial security plan, like a defined benefit plan, or Social Security has to cut back benefit payments.
  • The firm you work for goes broke, or gets competed into an also-ran.
  • You lose your job, can’t find another job as good, and you default on important regular bills as a result.  The same applies to people who run their own business.
  • Levered financial businesses, like banks and shadow banks, make too many loans to marginal borrowers, and find at some point that their borrowers can’t pay them back, and at the same time, no one wants to lend to them.  This can be harmful not just to the banks and shadow banks, but to the economy as a whole.

Let’s use retirement as an example of how to analyze financial risk.  I have a series of articles that I have written on the topic based on the idea of the personal required investment earnings rate [PRIER].  PRIER is not a unique concept of mine, but is attempt to apply the ideas of professionals trying to manage the assets and liabilities of an endowment, defined benefit plan, or life insurance company to the needs of an individual or a family.

The main idea is to try to calculate the rate of return you will need over time to meet your eventual goals.  From my prior “PRIER” article, which was written back in January 2008, prior to the financial crisis:

To the extent that one can estimate what one can reasonably save (hard, but worth doing), and what the needs of the future will cost, and when they will come due (harder, but worth doing), one can estimate personal contribution and required investment earnings rates.  Set up a spreadsheet with current assets and the likely savings as positive figures, and the future needs as negative figures, with the likely dates next to them.  Then use the XIRR function in Excel to estimate the personal required investment earnings rate [PRIER].

I’m treating financial planning in the same way that a Defined Benefit pension plan analyzes its risks.  There’s a reason for this, and I’ll get to that later.  Just as we know that a high assumed investment earnings rate at a defined benefit pension plan is a red flag, it is the same to an individual with a high PRIER.

Now, suppose at the end of the exercise one finds that the PRIER is greater than the yield on 10-year BBB bonds by more than 3%.  (Today that would be higher than 9%.)  That means you are not likely to make your goals.   You can either:

  • Save more, or,
  • Reduce future expectations,whether that comes from doing the same things cheaper, or deferring when you do them.

Those are hard choices, but most people don’t make those choices because they never sit down and run the numbers.  Now, I left out a common choice that is more commonly chosen: invest more aggressively.  This is more commonly done because it is “free.”  In order to get more return, one must take more risk, so take more risk and you will get more return, right?  Right?!

Sadly, no.  Go back to Defined Benefit programs for a moment.  Think of the last eight years, where the average DB plan has been chasing a 8-9%/yr required yield.  What have they earned?  On a 60/40 equity/debt mandate, using the S&P 500 and the Lehman Aggregate as proxies, the return would be 3.5%/year, with the lion’s share coming from the less risky investment grade bonds.  The overshoot of the ’90s has been replaced by the undershoot of the 2000s.  Now, missing your funding target for eight years at 5%/yr or so is serious stuff, and this is a problem being faced by DB pension plans and individuals today.

The article goes on, and there are several others that flesh out the ideas further:

Simple Summary

Though there are complexities in trying to manage financial risk, the main ideas for dealing with financial risk are these:

  1. Spend time estimating your future needs and what resources you can put toward them.
  2. Be conservative in what you think you assets can earn.
  3. Be flexible in your goals if you find that you cannot reasonably achieve your dreams.
  4. Consider what can go wrong, get proper insurance where needed, and be judicious on taking on large fixed commitments to spend money in the future.

PS — Two final notes:

On the topic of “what can go wrong in personal finance, I did a series on that here.

Investment risk is sometimes confused with volatility.  Here’s a discussion of when that makes sense, and when it doesn”t.

I’m thinking of starting a limited series called “dirty secrets” of finance and investing.  If anyone wants to toss me some ideas you can contact me here.  I know that since starting this blog, I have used the phrase “dirty secret” at least ten times.

Tonight’s dirty secret is a simple one, and it derives mostly from investor behavior.  You don’t always get more return on average if you take more risk.  The amount of added return declines with each unit of additional risk, and eventually turns negative at high levels of risk.  The graph above is a vague approximate representation of how this process works.

Why is this so?  Two related reasons:

  1. People are not very good at estimating the probability of success for ventures, and it gets worse as the probability of success gets lower.  People overpay for chancy lottery ticket-like investments, because they would like to strike it rich.  This malady affect men more than women, on average.
  2. People get to investment ideas late.  They buy closer to tops than bottoms, and they sell closer to bottoms than tops.  As a result, the more volatile the investment, the more money they lose in their buying and selling.  This malady also affects men more than women, on average.

Put another way, this is choosing your investments based on your circle of competence, such that your probability of choosing a good investment goes up, and second, having the fortitude to hold a good investment through good and bad times.  From my series on dollar-weighted returns you know that the more volatile the investment is, the more average people lose in their buying and selling of the investment, versus being a buy-and-hold investor.

Since stocks are a long duration investment, don’t buy them unless you are going to hold them long enough for your thesis to work out.  Things don’t always go right in the short run, even with good ideas.  (And occasionally, things go right in the short run with bad ideas.)

For more on this topic, you can look at my creative piece, Volatility Analogy.  It explains the intuition behind how volatility affects the results that investors receive as they get greedy, panic, and hold on for dear life.

In closing, the dirty secret is this: size your risk level to what you can live with without getting greedy or panicking.  You will do better than other investors who get tempted to make rash moves, and act on that temptation.  On average, the world belongs to moderate risk-takers.

Photo Credit: Kathryn

Photo Credit: Kathryn || Truly, I sympathize.  I try to be strong for others when internally I am broken.

Entire societies and nations have been wiped out in the past.  Sometimes this has been in spite of the best efforts of leading citizens to avoid it, and sometimes it has been because of their efforts.  In human terms, this is as bad as it gets on Earth.  In virtually all of these cases, the optimal strategy was to run, and hope that wherever you ended up would be kind to foreigners.  Also, most common methods of preserving value don’t work in the worst situations… flight capital stashed early in the place of refuge and gold might work, if you can get there.

There.  That’s the worst survivable scenario I can think of.  What does it take to get there?

  • Total government and market breakdown, or
  • A lost war on your home soil, with the victors considerably less kind than the USA and its allies

The odds of these are very low in most of the developed world.  In the developing world, most of the wealthy have “flight capital” stashed away in the USA or someplace equally reliable.

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Most nations, societies and economies are more durable than most people would expect.  There is a cynical reason for this: the wealthy and the powerful have a distinct interest in not letting things break.  As Solomon observed a little less than 3000 years ago:

If you see the oppression of the poor, and the violent perversion of justice and righteousness in a province, do not marvel at the matter; for high official watches over high official, and higher officials are over them. Moreover the profit of the land is for all; even the king is served from the field. — Ecclesiastes 5:8-9 [NKJV]

In general, I think there is no value in preparing for the “total disaster” scenario if you live in the developed world.  No one wants to poison their own prosperity, and so the rich and powerful hold back from being too rapacious.

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If you don’t have a copy, it would be a good idea to get a copy of Triumph of the Optimists.  [TOTO]  As I commented in my review of TOTO:

TOTO points out a number of things that should bias investors toward risk-bearing in the equity markets:

  1. Over the period 1900-2000, equities beat bonds, which beat cash in returns. (Note: time weighted returns. If the study had been done with dollar-weighted returns, the order would be the same, but the differences would not be so big.)

  2. This was true regardless of what presently developed nation you looked at. (Note: survivor bias… what of all the developing markets that looked bigger in 1900, like Russia and India, that amounted to little?)

  3. Relative importance of industries shifts, but the aggregate market tended to do well regardless. (Note: some industries are manias when they are new)

  4. Returns were higher globally in the last quarter of the 20th century.

  5. Downdrafts can be severe. Consider the US 1929-1932, UK 1973-74, Germany 1945-48, or Japan 1944-47. Amazing what losing a war on your home soil can do, or, even a severe recession.

  6. Real cash returns tend to be positive but small.

  7. Long bonds returned more than short bonds, but with a lot more risk. High grade corporate bonds returned more on average, but again, with some severe downdrafts.

  8. Purchasing power parity seems to work for currencies in the long run. (Note: estimates of forward interest rates work in the short run, but they are noisy.)

  9. International diversification may give risk reduction. During times of global stress, such as wartime, it may not diversify much. Global markets are more correlated now than before, reducing diversification benefits.

  10. Small caps may or may not outperform large caps on average.

  11. Value tends to beat growth over the long run.

  12. Higher dividends tend to beat lower dividends.

  13. Forward-looking equity risk premia are lower than most estimates stemming from historical results. (Note: I agree, and the low returns of the 2000s so far in the US are a partial demonstration of that. My estimates are a little lower, even…)

  14. Stocks will beat bonds over the long run, but in the short run, having some bonds makes sense.

  15. Returns in the latter part of the 20th century were artificially high.

Capitalist republics/democracies tend to be very resilient.  This should make us willing to be long term bullish.

Now, many people look at their societies and shake their heads, wondering if things won’t keep getting worse.  This typically falls into three non-exclusive buckets:

  • The rich are getting richer, and the middle class is getting destroyed  (toss in comments about robotics, immigrants, unfair trade, education problems with children, etc.  Most such comments are bogus.)
  • The dependency class is getting larger and larger versus the productive elements of society.  (Add in comments related to demographics… those comments are not bogus, but there is a deal that could be driven here.  A painful deal…)
  • Looking at moral decay, and wondering at it.

You can add to the list.  I don’t discount that there are challenges/troubles.  Even modestly healthy society can deal with these without falling apart.

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If you give into fears like these, you can become prey to a variety of investment “experts” who counsel radical strategies that will only succeed with very low probability.  Examples:

  • Strategies that neglect investing in risk assets at all, or pursue shorting them.  (Even with hedge funds you have to be careful, we passed the limits to arbitrage back in the late ’90s, and since then aggregate returns have been poor.  A few niche hedge funds make sense, but they limit their size.)
  • Gold, odd commodities — trend following CTAs can sometimes make sense as a diversifier, but finding one with skill is tough.
  • Anything that smacks of being part of a “secret club.”  There are no secrets in investing.  THERE ARE NO SECRETS IN INVESTING!!!  If you think that con men in investing is not a problem, read On Avoiding Con Men.  I spend lots of time trying to take apart investment pitches that are bogus, and yet I feel that I am barely scraping the surface.

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Things are rarely as bad as they seem.  Be willing to be a modest bull most of the time.  I’m not saying don’t be cautious — of course be cautious!  Just don’t let that keep you from taking some risk.  Size your risks to your time horizon for needing cash back, and your ability to sleep at night.  The biggest risk may not be taking no risk, but that might be the most common risk economically for those who have some assets.

To close, here is a personal comment that might help: I am natively a pessimist, and would easily give into disaster scenarios.  I had to train myself to realize that even in the worst situations there was some reason for optimism.  That served me well as I invested spare assets at the bottoms in 2002-3 and 2008-9.  The sun will rise tomorrow, Lord helping us… so diversify and take moderate risks most of time.

This is the fourth article in this series, and is here because the S&P 500 is now in its second-longest bull market since 1928, having just passed the bull market that ended in 1956.    Yeah, who’da thunk it?

This post is a little different from the first three articles, because I got the data to extend the beginning of my study from 1950 to 1928, and I standardized my turning points using the standard bull and bear market definitions of a 20% rise or fall from the last turning point.  You can see my basic data to the left of this paragraph.

Before I go on, I want to show you two graphs dealing with bear markets:

As you can see from the first graph, small bear markets are much more common than large ones.  Really brutal bear markets like the biggest one in the Great Depression were so brutal that there is nothing to compare it to — financial leverage collapsed that had been encouraged by government policy, the Fed, and a speculative mania among greedy people.

The second graph tells the same story in a different way.  Bear markets are often short and sharp.  They don’t last long, but the intensity in term of the speed of declines is a little more than twice as fast as the rises of bull markets.  If it weren’t for the fact that bull markets last more than three times as long on average, the sharp drops in bear markets would be enough to keep everyone out of the stock market.

Instead, it just keeps many people out of the market, some entirely, but most to some degree that would benefit them.

Oh well, on to the gains:

Like bear markets, most bull markets are small.  The likelihood of a big bull market declines with size.  The current bull market is the fourth largest, and the one that it passed in duration was the second largest.  As an aside, each of the four largest bull markets came after a surprise:

  1. (1987-2000) 1987: We knew the prior bull market was bogus.  When will inflation return?  It has to, right?
  2. (1949-56) 1949: Hey, we’re not getting the inflation we expected, and virtually everyone is finding work post-WWII
  3. (1982-7) 1982: The economy is in horrible shape, and interest rates are way too high.  We will never recover.
  4. (2009-Present) 2009: The financial sector is in a shambles, government debt is out of control, and the central bank is panicking!  Everything is falling apart.
Sometimes you win, sometimes you lose...

Sometimes you win, sometimes you lose…

Note the two dots stuck on each other around 2800 days.  The arrow points to the lower current bull market, versus the higher-returning bull market 1949-1956.

Like bear markets, bull markets also can be short and sharp, but they can also be long and after the early sharp phase, meander upwards.  If you look through the earlier articles in this series, you would see that this bull market started as an incredibly sharp phenomenon, and has become rather average in its intensity of monthly returns.

Conclusion

It may be difficult to swallow, but this bull market that is one of the longest since 1928 is pretty average in terms of its monthly average returns for a long bull market.  It would be difficult for the cost of capital to go much lower from here.  It would be a little easier for corporate profits to rise from here, but that also doesn’t seem too likely.

Does that mean the bull is doomed?  Well, yes, eventually… but stranger things have happened, it could persist for some time longer if the right conditions come along.

But that’s not the way I would bet.  Be careful, and take opportunities to lower your risk level in stocks somewhat.

PS — one difference with the Bloomberg article linked to in the first paragraph, the longest bull market did not begin in 1990 but in 1987.  There was a correction in 1990 that fell just short of the -20% hurdle at -19.92%, as mentioned in this Barron’s article.  The money shot:

The historical analogue that matches well with these conditions is 1990. There was a 19.9% drop in the S&P 500, lasting a bit under three months. But the damage to foreign stocks, small-caps, cyclicals, and value stocks in that cycle was considerably more. Both the Russell and the Nasdaq were down 32% to 33%. You might remember United Airlines’ failed buyout bid; the transports were down 46%. Foreign stocks were down about 30%.

And then Saddam Hussein invaded Kuwait.

That might have been the final trigger. The broad market top was in the fall of 1989, and most stocks didn’t bottom until Oct. 11, 1990. In the record books, it was a shallow bear market that didn’t even officially meet the 20% definition. But it was a damaging one that created a lot of opportunity for the rest of the 1990s.

FWIW, I remember the fear that existed among many banks and insurance companies that had overlent on commercial properties in that era.  The fears led Alan Greenspan to encourage the FOMC to lower rates to… (drumroll) 3%!!!  And, that experiment together with the one in 2003, which went down to 1.25%, practically led to the idea that the FOMC could lower rates to get out of any ditch… which is now being proven wrong.

Every now and then, you will run across a mathematical analysis where if you use a certain screening, trading, or other investment method, it produces a high return in hindsight.

And now, you know about it, because it was just published.

But wait.  Just published?

Think about what doesn’t get published: financial research that fails, whether for reasons of error or luck.

Now, luck can simply be a question of timing… think of my recent post: Think Half of a Cycle Ahead.  What would happen to value investing if you tested it only over the last ten years?

It would be in the dustbin of failed research.

Just published… well… odds are, particularly if the data only goes back a short distance in time, it means that there was likely a favorable macro backdrop giving the idea a tailwind.

There is a different aspect to luck though.  Perhaps a few souls were experimenting with something like the theory before it was discovered.  They had excellent returns, and there was a little spread of the theory via word of mouth and unsavory means like social media and blogs.

Regardless, one of the main reasons the theory worked was that the asset being bought by those using the theory were underpriced.  Lack of knowledge by institutions and most of the general public was a barrier to entry allowing for superior returns.

When the idea became known by institutions after the initial paper was published, a small flood of money came through the narrow doors, bidding up the asset prices to the point where the theory would not only no longer work, but the opposite of the theory would work for a time, as the overpriced assets had subpar prospective returns.

Remember how dot-com stocks were inevitable in March of 2000?  Now those doors weren’t narrow, but they were more narrow than the money that pursued them.  Such is the end of any cycle, and the reason why average investors get skinned chasing performance.

Now occasionally the doors of a new theory are so narrow that institutions don’t pursue the strategy.  Or, the strategy is so involved, that even average quants can tell that the data has been tortured to confess that it was born in a place where the universe randomly served up a royal straight flush, but that five-leaf clover got picked and served up as if it were growing everywhere.

Sigh.

My advice to you tonight is simple.  Be skeptical of complex approaches that worked well in the past and are portrayed as new ideas for making money in the markets.  These ideas quickly outgrow the carrying capacity of the markets, and choke on their own success.

The easiest way to kill a good strategy is to oversaturate it too much money.

As such, I have respect for those with proprietary knowledge that limit their fund size, and don’t try to make lots of money in the short run by hauling in assets just to drive fees.  They create their own barriers to entry with their knowledge and self-restraint, and size their ambitions to the size of the narrow doors that they walk through.

To those that use institutional investors, do ask where they will cut off the fund size, and not create any other funds like it that buy the same assets.  If they won’t give a firm answer, avoid them, or at minimum, keep your eye on the assets under management, and be willing to sell out when they get reeeally popular.

If it were easy, the returns wouldn’t be that great.  Be willing to take the hard actions such that your managers do something different, and finds above average returns, but limits the size of what they do to serve current clients well.

Then pray that they never decide to hand your money back to you, and manage only for themselves.  At that point, the narrow door excludes all but geniuses inside.

Photo Credit: Istvan || Note OPEC HQ in Vienna

Photo Credit: Istvan || Note OPEC HQ in Vienna

Most games in life are cooperative.  Many are competitive.  A few are perverse.

That’s what the crude oil market is like today.  It reminds me of the prisoner’s dilemma.  In the prisoner’s dilemma, two parties that would benefit from cooperating together tend not to do so because of other incentives that if both follow, they will both end up in a worse place.

This stems from three problems facing OPEC [Organization of the Petroleum Exporting Countries].

  1. The Saudis and the Iranians don’t want to take any action that would benefit the other, even if it would help themselves.
  2. It’s virtually impossible to keep member nations in OPEC from cheating, and producing more than their quota.
  3. Thanks to hydraulic fracturing (at least for now) there is enough supply outside of OPEC at inexpensive prices, that if OPEC cut production as a group, it might not gain as much of the benefit as they did in the ’70s and early ’80s.

Factors 1 and 2 interact, because even if there was a credible deal to cut production on the table, the Saudis likely think that the Iranians might cheat and produce more… leaving the Iranians much better off and the Saudis not that much better off.

We have to remember that the neoclassical model of man as a maximizer of utility or profits is often wrong.  People and nations are envious, and will make do with less if it means those that they dislike are even worse off.  The Saudis may be burning through their financial reserves quickly, but virtually everyone else in OPEC is worse off.  The Saudis might think that they can drive a better deal inside OPEC when almost everyone else is desperate.

What this argues for is crude oil prices staying lower for a longer period of time — my guess is between $30 and $50 per barrel of Brent-type crude.  What could change this?

  • Faster economic growth
  • Turmoil in oil producing regions that reduces supply
  • Depletion of short-life low-cost sources of crude (as is common with hydraulic fracturing)
  • Some clever third parties in OPEC find a way to get the Saudis and Iranians to cooperate while saving face, and no one cheats.

On the other side there is:

  • More cheating within OPEC
  • Weaker growth
  • Higher energy taxes
  • Further technological refinements that lower crude oil production costs further
  • Continued improvements in solar, wind, and energy storage (primarily battery) technology.

At present, my guess is that the marginal barrels of crude oil are being extracted in North America, and probably will be out to 2020 or so.  As such, I would encourage energy investors to stick with strong companies with a mix of low debt and cheap production costs.  Also, look for companies that are misunderstood, that have other businesses away from energy but have been tarred with the low energy price story.

In summary, play it safe while the members of OPEC flounder in a game that they designed for themselves.

Idea Credit: Philosophical Economics Blog

Idea Credit: Philosophical Economics Blog

My most recent post, Estimating Future Stock Returns was well-received.  I expected as much.  I presented it as part of a larger presentation to a session at the Society of Actuaries 2015 Investment Symposium, and a recent meeting of the Baltimore Chapter of the AAII.  Both groups found it to be one of the interesting aspects of my presentation.

This post is meant to answer three reasonable questions that got posed:

  1. How do you estimate the model?
  2. How do we understand what it is forecasting given multiple forecast horizons seemingly implied by the model?
  3. Why didn’t the model how badly the market would do in 2001 and 2008?  And I will add 1973-4 for good measure.

Ready?  Let’s go!

How to Estimate

In his original piece, @Jesse_Livermore freely gave the data and equation out that he used.  I will do that as well.  About a year before I wrote this, I corresponded with him by email, asking if he had noticed that the Fed changed some of the data in the series that his variable used retroactively.  That was interesting, and a harbinger for what would follow.  (Strange things happen when you rely on government data.  They don’t care what others use it for.)

In 2015, the Fed discontinued one of the series that was used in the original calculation.  I noticed that when the latest Z.1 report came out, and I tried to estimate it the old way.  That threw me for a loop, and so I tried to re-estimate the relationship using what data was there.  That led me to do the following:

I tried to get all of them from one source, and could not figure out how to do it.  The Z.1 report has all four variables in it, but somehow, the Fed’s Data Download Program, which one of my friends at a small hedge fund charitably referred to as “finicky” did not have that series, and somehow FRED did.  (I don’t get that, but then there are a lot of things that I don’t get.  This is not one of those times when I say, “Actually, I do get it; I just don’t like it.”  That said, like that great moral philosopher Lucy van Pelt, I haven’t ruled out stupidity yet.  To which I add, including my stupidity.)

The variable is calculated like this:

(A + D)/(A + B + C + D)

Not too hard, huh?  The R-squared is just a touch lower from estimating it the old way… but the difference is not statistically significant.  The estimation is just a simple ordinary least squares regression using that single variable as the independent variable, and the dependent variable being the total return on the S&P 500.

As an aside, I tested the variable over other forecast horizons, and it worked best over 10-11 years.  On individual years, the model is most powerful at predicting the next year (surprise!), and gets progressively weaker with each successive individual year.

To make it concrete: you can use this model to forecast the expected returns for 2016, 2017, 2018, etc.  It won’t be very accurate, but you can do it.  The model gets more accurate forecasting over a longer period of time, because the vagaries of individual years average out.  After 10-11 years, the variable is useless, so if I were put in charge of setting stock market earnings assumptions for a pension plan, I would do it as a step function, 6% for the next 10 years, and 9.5% per year thereafter… or in place of 9.5% whatever your estimate is for what the market should return normally.

On Multiple Forecast Horizons

One reader commented:

I would like to make a small observation if I may. If the 16% per annum from Mar 2009 is correct we still have a 40%+ move to make over the next three years. 670 (SPX March 09) growing at 16% per year yields 2900 +/- in 2019. With the SPX at 2050 we have a way to go. If the 2019 prediction is correct, then the returns after 2019 are going to be abysmal.

The first answer would be that you have to net dividends out.  In March of 2009, the S&P 500 had a dividend yield of around 4%, which quickly fell as the market rose and dividends fell for about one year.  Taking the dividends into account, we only need to get to 2270 or so by the March of 2019, works out to 3.1% per year.  Then add back a dividend yield of about 2.2%, and you are at a more reasonable 5.3%/year.

That said, I would encourage you to keep your eye on the bouncing ball (and sing along with Mitch… does that date me…?).  Always look at the new forecast.  Old forecasts aren’t magic — they’re just the best estimate a single point in time.  That estimate becomes obsolete as conditions change, and people adjust their portfolio holdings to hold proportionately more or less stocks.  The seven year old forecast may get to its spot in three years, or it may not — no model is perfect, but this one does pretty well.

What of 2001 and 2008?  (And 1973-4?)

Another reader wrote:

Interesting post and impressive fit for the 10 year expected returns.  What I noticed in the last graph (total return) is, that the drawdowns from 2001 and 2008 were not forecasted at all. They look quite small on the log-scale and in the long run but cause lot of pain in the short run.

Markets have noise, particularly during bear markets.  The market goes up like an escalator, and goes down like an elevator.  What happens in the last year of a ten-year forecast is a more severe version of what the prior questioner asked about the 2009 forecast of 2019.

As such, you can’t expect miracles.  The thing that is notable is how well this model did versus alternatives, and you need to look at the graph in this article to see it (which was at the top of the last piece).  (The logarithmic graph is meant for a different purpose.)

Looking at 1973-4, 2001-2 and 2008-9, the model missed by 3-5%/year each time at the lows for the bear market.  That is a big miss, but it’s a lot smaller than other models missed by, if starting 10 years earlier.  That said, this model would have told you prior to each bear market that future rewards seemed low — at 5%, -2%, and 5% respectively for the  next ten years.

Conclusion

No model is perfect.  All models have limitations.  That said, this one is pretty useful if you know what it is good for, and its limitations.

Idea Credit: Philosophical Economics Blog

Idea Credit: Philosophical Economics, but I estimated and designed the graphs

There are many alternative models for attempting to estimate how undervalued or overvalued the stock market is.  Among them are:

  • Price/Book
  • P/Retained Earnings
  • Q-ratio (Market Capitalization of the entire market / replacement cost)
  • Market Capitalization of the entire market / GDP
  • Shiller’s CAPE10 (and all modified versions)

Typically these explain 60-70% of the variation in stock returns.  Today I can tell you there is a better model, which is not mine, I found it at the blog Philosophical Economics.  The basic idea of the model is this: look at the proportion of US wealth held by private investors in stocks using the Fed’s Z.1 report. The higher the proportion, the lower future returns will be.

There are two aspects of the intuition here, as I see it: the simple one is that when ordinary people are scared and have run from stocks, future returns tend to be higher (buy panic).  When ordinary people are buying stocks with both hands, it is time to sell stocks to them, or even do IPOs to feed them catchy new overpriced stocks (sell greed).

The second intuitive way to view it is that it is analogous to Modiglani and Miller’s capital structure theory, where assets return the same regardless of how they are financed with equity and debt.  When equity is a small component as a percentage of market value, equities will return better than when it is a big component.

What it Means Now

Now, if you look at the graph at the top of my blog, which was estimated back in mid-March off of year-end data, you can notice a few things:

  • The formula explains more than 90% of the variation in return over a ten-year period.
  • Back in March of 2009, it estimated returns of 16%/year over the next ten years.
  • Back in March of 1999, it estimated returns of -2%/year over the next ten years.
  • At present, it forecasts returns of 6%/year, bouncing back from an estimate of around 4.7% one year ago.

I have two more graphs to show on this.  The first one below is showing the curve as I tried to fit it to the level of the S&P 500.  You will note that it fits better at the end.  The reason for that it is not a total return index and so the difference going backward in time are the accumulated dividends.  That said, I can make the statement that the S&P 500 should be near 3000 at the end of 2025, give or take several hundred points.  You might say, “Wait, the graph looks higher than that.”  You’re right, but I had to take out the anticipated dividends.

The next graph shows the fit using a homemade total return index.  Note the close fit.

Implications

If total returns from stocks are only likely to be 6.1%/year (w/ dividends @ 2.2%) for the next 10 years, what does that do to:

  • Pension funding / Retirement
  • Variable annuities
  • Convertible bonds
  • Employee Stock Options
  • Anything that relies on the returns from stocks?

Defined benefit pension funds are expecting a lot higher returns out of stocks than 6%.  Expect funding gaps to widen further unless contributions increase.  Defined contributions face the same problem, at the time that the tail end of the Baby Boom needs returns.  (Sorry, they *don’t* come when you need them.)

Variable annuities and high-load mutual funds take a big bite out of scant future returns — people will be disappointed with the returns.  With convertible bonds, many will not go “into the money.”  They will remain bonds, and not stock substitutes.  Many employee stock options and stock ownership plan will deliver meager value unless the company is hot stuff.

The entire capital structure is consistent with low-ish corporate bond yields, and low-ish volatility.  It’s a low-yielding environment for capital almost everywhere.  This is partially due to the machinations of the world’s central banks, which have tried to stimulate the economy by lowering rates, rather than letting recessions clear away low-yielding projects that are unworthy of the capital that they employ.

Reset Your Expectations and Save More

If you want more at retirement, you will have to set more aside.  You could take a chance, and wait to see if the market will sell off, but valuations today are near the 70th percentile.  That’s high, but not nosebleed high.  If this measure got to levels 3%/year returns, I would hedge my positions, but that would imply the S&P 500 at around 2500.  As for now, I continue my ordinary investing posture.  If you want, you can do the same.

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PS — for those that like to hear about little things going on around the Aleph Blog, I would point you to this fine website that has started to publish some of my articles in Chinese.  This article is particularly amusing to me with my cartoon character illustrating points.  This is the English article that was translated.  Fun!

Photo Credit: Robert Tuck || Of course, in half a cycle here, the moon will look the same

Photo Credit: Robert Tuck || Of course, in half a cycle here, the moon will look the same

 

Financial markets are trendy and noisy in the short-run, sensible in the long-run, and perverse in the intermediate-term.

What do I mean?

Something like this: short-run movements are news-driven, and driven by people trying to catch up with the latest data.  Many people imitate the behavior of others, and over the intermediate-term, some stock prices get out of whack.  Some subset of industries, factors, and/or companies gets out of alignment, and are mispriced.  In the long run, those pricing errors get corrected, but it takes years to get there.

Here’s an example. to make this tangible and understandable.  As a factor, value has been bad for eight years or so, and as evidence I quote Rob Arnott, from his article entitled, ‘How Can “Smart Beta” Go Horribly Wrong?

The value effect was first identified in the late 1970s, notably by Basu (1977), in the aftermath of the Nifty Fifty bubble, a period when value stocks were becoming increasingly expensive, priced at an ever-skinnier discount relative to growth stocks. More recently, for the past eight years, value investing has been a disaster with the Russell 1000 Value Index underperforming the S&P 500 by 1.6% a year, and the Fama–French value factor in large-cap stocks returning −4.8% annually over the same period. But, the value effect is far from dead! In fact, it’s in its cheapest decile in history.

And then later he says:

How many practitioners who rely on the value factor take the time to gauge whether the factor is expensive or cheap relative to historical norms? If they took the time to do so today, they would find value is currently cheaper than at any time other than the height of the Nifty Fifty (1972–73), the tech bubble (1998–2003), and the global financial crisis (2008–09).

The underlining is mine, to give emphasis. Now I would like to quote from a very old article of mine, The Fundamentals of Market Tops that was originally published at RealMoney.com back in 2004:

You’ll know a market top is probably coming when:

a) The shorts already have been killed. You don’t hear about them anymore. There is general embarrassment over investments in short-only funds.

b) Long-only managers are getting butchered for conservatism. In early 2000, we saw many eminent value investors give up around the same time. Julian Robertson, George Vanderheiden, Robert Sanborn, Gary Brinson and Stanley Druckenmiller all stepped down shortly before the market top.

Point (b) is what I want to highlight… not that we have had many value managers forced into retirement recently, but value funds of all kinds have been losing clients. It’s like being fired fractionally, a sliver at a time, but it adds up to a lot.

Combine that with Arnott’s insight that the valuations of value stocks are at exceptionally low levels – this gives me some hope that we are in the seventh inning or later in this market cycle regarding value investing.

Going Back a Step

Value isn’t the only cheap area presently — European stocks and emerging market stocks look cheap as well.  When areas of the market with bad relative performance have a lot of people giving up on them to pursue recently successful strategies, that helps to put in the bottom on the underperformers, and the top on the outperformers.

You can’t tell exactly when the process will end, but those jumping from one strategy to another, chasing performance, will just add a new set of losses to the old ones.  The trick is to try to anticipate when the cycle will turn for a given market strategy, factor or industry.  No one can do it perfectly, but it makes sense to act when relative valuations are in your favor.

Minimally, those that stick with a valid strategy through thick and thin can benefit from the strategy over the long-term… and that takes some courage, because there are times when your strategy will be out of favor.  That’s what I do with value investing.

Maximally, you would sell a strategy that you were invested in that was topping out in relative terms to buy a strategy that has been trashed for a while, and might be ready to outperform.  That’s even more difficult than sticking with one strategy through thick and thin.  Everyone wants to buy a past winner, and nobody wants to buy a past loser. but that is what would offer large returns if the timing could be right.  Another way of phrasing it, is to always look half a cycle ahead, to where a strategy will be when the excesses correct, or as is more likely, overcorrect, and take the appropriate action now.

Doing that is beyond me.  I’m just grateful that the period of relative underperformance of value may be nearing its end.