What a difference a quarter makes!  As I said one quarter ago:

Are you ready to earn 6%/year until 9/30/2026?  The data from the Federal Reserve comes out with some delay.  If I had it instantly at the close of the third quarter, I would have said 6.37% — but with the run-up in prices since then, the returns decline to 6.01%/year.

So now I say:

Are you ready to earn 5%/year until 12/31/2026?  The data from the Federal Reserve comes out with some delay.  If I had it instantly at the close of the fourth quarter, I would have said 5.57% — but with the run-up in prices since then, the returns decline to 5.02%/year.

A one percent drop is pretty significant.  It stems from one main factor, though — investors are allocating a larger percentage of their total net worth to stocks.  The amount in stocks moved from 38.00% to 38.75%, and is probably higher now.  Remember that these figures come out with a 10-week delay.

Remember that the measure in question covers both public and private equities, and is market value to the extent that it can be, and “fair value” where it can’t.  Bonds and most other assets tend to be a little easier to estimate.

So what does it mean for the ratio to move up from 38.00% to 38.75%?  Well, it can mean that equities have appreciated, which they have.  But corporations buy back stock, pay dividends, get acquired for cash which reduces the amount of stock outstanding, and places more cash in the hands of investors.  More cash in the hands of investors means more buying power, and that gets used by many long-term institutional investors who have fixed mandates to follow.  Gotta buy more if you hit the low end of your equity allocation.

And the opposite is true if new money gets put into businesses, whether through private equity, Public IPOs, etc.  One of the reasons this ratio went so high in 1998-2001 was the high rate of business formation.  People placed more money at risk as they thought they could strike it rich in the Dot-Com bubble.  The same was true of the Go-Go era in the late 1960s.

Remember here, that average returns are around 9.5%/year historically.  To be at 5.02% places us in the 88th percentile of valuations.  Also note that I will hedge what I can if expected 10-year returns get down to 3%/year, which corresponds to a ratio of 42.4% in stocks, and the 95th percentile of valuations.  (Note, all figures in this piece are nominal, not inflation-adjusted.)  At that level, past 10-year returns in the equity markets have been less than 1%, and in the short-to-intermediate run, quite poor.)

You can also note that short-term and 10-year Treasury yields have risen, lowering the valuation advantage versus cash and bonds.

I have a few more small things to add.  Here’s an article from the Wall Street Journal: Individual Investors Wade In as Stocks Soar.  The money shot:

The investors’ positioning suggests burgeoning optimism, with TD Ameritrade clients increasing their net exposure to stocks in February, buying bank shares and popular stocks such as Amazon.com Inc. and sending the retail brokerage’s Investor Movement Index to a fresh high in data going back to 2010. The index tracks investors’ exposure to stocks and bonds to gauge their sentiment.

“People went toe in the water, knee in the water and now many are probably above the waist for the first time,” said JJ Kinahan, chief market strategist at TD Ameritrade.

This is sad to say, but it is rare for a rally to end before the “dumb money” shows up in size.  Running a small asset management shop like I do, at times like this I suggest to clients that they might want more bonds (with me that’s short and high quality now), but few do that.  Asset allocation is the choice of my clients, not me.  That said, most of my clients are long-term investors like me, for which I give them kudos.

Then there is this piece over at Bloomberg.com called: Wall Street’s Buzz Over ‘Great Leader’ Trump Gives Shiller Dot-Com Deja Vu.  I want to see the next data point in this analysis, which won’t be available by mid-June, but I do think a lot of the rally can be chalked up to willingness to take more risk.

I do think that most people and corporations think that they will have a more profitable time under Trump rather than Obama.  That said, a lot of the advantage gets erased by a higher cost of debt capital, which is partly driven by the Fed, and partly by a potentially humongous deficit.  As I have said before though, politicians are typically limited in what they can do.  (And the few unlimited ones are typically destructive.)

Shiller’s position is driven at least partly by the weak CAPE model, and the rest by his interpretation of current events.  I don’t make much out of policy uncertainty indices, which are too new.  The VIX is low, but hey, it usually is when the market is near new highs.  Bull markets run on complacency.  Bear markets plunge on revealed credit risk threatening economic weakness.

One place I will agree with Shiller:

What Shiller will say now is that he’s refrained from adding to his own U.S. stock positions, emphasizing overseas markets instead.

That is what I am doing.  Where I part ways with Shiller for now is that I am not pressing the panic button.  Valuations are high, but not so high that I want to hedge or sell.

That’s all for now.  This series of posts generates more questions than most, so feel free to ask away in the comments section, or send me an email.  I will try to answer the best questions.

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Late edit: changed bolded statement above from third to fourth quarter.

This post may fall into the “Dog bites Man” bucket, but I will see if I can’t shed a little more light on the phenomenon.  Here’s the question: “When do we see new highs in the stock market most often?”  The punchline: “After a recent new high.”

The red squares above show the probability of hitting a new high so many days after a new high.  The black line near it is a best fit power curve.  The blue diamonds above show the probability of hitting a new high so many days after not hitting a new high.  The green triangles above show the ratio of those two probabilities, matching up against the right vertical axis. The black line near it is a best fit power curve.

As time goes to infinity, both probabilities converge to the same number, which is presently estimated to be 6.8%, the odds that we would hit a new high on any day between 1951 and 2015.  Here’s the table that corresponds to the above graph:

Probability of a new high afterDays after no new highDays after new highProbability Ratio
1st day3.1%57.3%18.29
2nd day4.2%43.3%10.39
3rd day4.6%36.7%7.90
4th day4.8%33.8%6.99
5th day5.1%30.0%5.87
6th day5.2%28.2%5.37
7th day5.5%24.2%4.36
8th day5.7%22.5%3.97
9th day5.6%23.4%4.18
10th day5.6%22.6%4.00
11-155.9%19.0%3.22
16-206.0%17.2%2.86
21-306.1%16.4%2.71
31-406.2%14.5%2.35
41-506.2%15.2%2.47
51-606.3%14.2%2.28
61-756.3%13.9%2.21
76-906.3%13.6%2.16
91-1056.3%12.8%2.02
106-1206.4%12.5%1.96
121-1406.4%12.0%1.87
141-1606.5%11.3%1.75
161-1806.4%11.5%1.79
181-200 days6.4%11.8%1.84

 

E.g., as you go down the table the probability 43.3% represents the probability that you get a new high on the second day after a new high.

Here’s an intuitive way to think about it: if you are not at a new high, you are further away from a new high than if you were at a new high recently.  Thus with time the daily probability of hitting a new high gets higher.  If you were at a new high recently, you daily odds of hitting a new high are quite high, but fall over time, because the odds of drifting lower at some point increase.  Valuation is a weak daily force, but a strong ultimate force.

That said, the odds of hitting new highs a long time away from a new high are significantly higher than the odds of hitting a new high where there has been no new high for the same amount of time.

Closing Thoughts

I could segment the data another way, and this could be clearer: If you are x% away from a new high, what is the odds you will hit a new high n days from now?  As x gets bigger, so will the numbers for n.  Be that as it may, when you have had new highs recently, you tend to have more of them.  New highs clump together.

The same is true of periods with no new highs — they tend to clump together and persist even more.

Valuation and momentum are hidden variables here — momentum aids persistence, and valuation is gravity, eventually causing markets that don’t fairly price likely future cash flows to revert to pricing that is more normal.  Valuation is powerful, but takes a long while to act, often waiting for a credit cycle to do its work.  Momentum works in the short-run, propelling markets to heights and depths that we can only reach from human mimickry.

That’s all.

I was reading through The Wall Street Journal’s Daily Shot column, done by the estimable @SoberLook, and saw the following graph and text:

The S&P 500 move this year is completely outside the historical seasonal trends.

Graph Credit: Deutsche Bank via @SoberLook at The Wall Street Journal

Averages reveal, but they also conceal.  When I look at a graph like this, I know that any given year is highly likely to look different than an average of years.  So, no surprise that the returns on the S&P 500 are different than the averages of the prior 11 or 19 years.

But how has the S&P 500 fared versus the last 68 years?  At present this year is 20th out of 68, which is good, but not great or average.  But look at the graph at the top of this article: up until the close of the 25th trading day of the year (February 7th) the market had performance very much like a median year.  All of the higher performance has come out of the last nine days.  (For fun, it is the ninth best out of 68 for that time of year; even that is not top decile.)

I can tell you something easy: you can have a lot of different occurrences over nine days in the market.  The distribution of returns would be quite wide.  Therefore, don’t get too excited about the returns so far this year — they aren’t that abnormal.  You can be concerned as you like about valuation levels — they are high.  But 2017 at present is a “high side of normal” year compared to past price performance.

And, if you want to be concerned about a melt-up, it is this kind of low positive momentum that tends to persist, at least for a while.  Trading behavior isn’t nuts, even if valuations are somewhat steamy.

I’m around 83% invested in equity accounts, so I am conservative, but I’m not thinking of hedging yet.  Let the rally run.

Doctored Photo Credit: Marvin Isidore Macatol || And I say this is heresy!

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My last post produced the following question:

What if your time horizon was 60 years? Would a 5% real return be achievable?

I am answering this as part of an irregular “think deeper” series on the problems of modeling investment over the very long term… the last entry was roughly six years ago.  It’s a good series of five articles, and this is number six.

On to the question.  The model forecasts over a ten-year period, and after that returns return to the long run average — about 9.5%/year nominal.  The naive answer would then be something like this: the model says over a 60-year period you should earn about 8.85%/year, considering that the first ten years, you should earn around 5.63%/year.  (Nominally, your initial investment will grow to be 161x+ as large.)   If you think this, you can earn a 5% real return if inflation over the 60 years averages 3.85%/year or less.  (Multiplying your capital in real terms by 18x+.)

Simple, right?

Now for the problems with this.  Let’s start with the limits of math.  No, I’m not going to teach you precalculus, though I have done that for a number of my kids.  What I am saying is that math reveals, but it also conceals.  In this case the math assumes that there is only one variable that affects returns for ten years — the proportion of investor asset held in stocks.  The result basically says that over a ten-year period, mean reversion will happen.  The proportion of investor asset held in stocks will return to an average level, and returns similar to the historical average will come thereafter.

Implicitly, this assumes that the return series underlying the regression is the perfectly normal return series, and the future will be just like it, only more so.  Let me tell you about some special things involved in the history of the last 71 years:

  • We have not lost a war on our home soil.
  • We have not had socialism to the destructive levels experienced by China under Mao, the USSR. North Korea, Cuba, etc.  (Ordinary socialism isn’t so damaging, though there are ethical reasons for not going that way.  People deserve freedom, not guarantees.  Note that stock returns in moderate socialist countries have been roughly as high as those in the US.  See the book Triumph of the Optimists.)
  • We have continued to have enough children, and they have become moderately productive workers.  Also, we have welcomed a lot of hard working and creative people to the US.
  • Technology has continued to improve, and along with it, labor productivity.
  • Adequate energy to multiply force and distribute knowledge is inexpensively available.
  • We have not experienced hyperinflation.

There are probably a few things that I have missed.  This is what I mean when I say the math conceals.  Every mathematical calculation abstracts quantity away from every other attribute, and considers it to be the only one worth analyzing.  Qualitative analysis is tougher and more necessary than quantitative analysis — we need it to give meaning to mathematical analyses.  (What are the limits?  What is it good for?  How can I use it?  How can I use it ethically?)

If you’ve read me long enough, you know that I view economies and financial markets as ecosystems.  Ecosystems are stable within limits.  Ecosystems also can only develop so quickly; there may be no limits to growth, but there are limits to the speed of growth in mature economies and financial systems.

Thus the question: will these excellent conditions continue?  My belief is that mankind never truly changes, and that history teaches us that all governments and most cultures eventually die.  When they do, most or all economic arrangements tend to break, especially complex ones like financial markets.

But here are three more limits, and they are more local:

  • Can you really hold for 60 years, reinvesting and never taking a material amount out?
  • Will the number investing in the equity markets remain small?
  • Will stock be offered and retired at ordinary prices?

 

Most people can’t lock money away for that long without touching it to some degree.  Some of the assets may get liquidated because of panic, personal emergency needs, etc.  Besides, why be a miser?  Warren Buffett, one of the greatest compounders of all time, might have ended up happier if he had spent less time compounding, and more time on his family.  It would have been better to take a small part of it, and use it to make others happy then, and not wait to be the one of the most famous philanthropists of the 21st century before touching it.

Second, returns may be smaller in the future because more pursue them.  One reason the rewards for being a capitalist are large on average is that there are relatively few of them.  Also, I have sometimes wondered if stock returns will fall when the whole world is employed, and there is no more cheap labor to be had.  Should that bold scenario ever come to pass, labor would have more bargaining power in aggregate, and profits would likely fall.

Finally, you have to recognize that the equity return statistics are somewhat overstated.  I’m not sure how much, but I think it is enough to reduce returns by 1%+.  Equity tends to be offered for initial purchase expensively, and tends to get retired inexpensively.  Businessmen are rational and tend to go public when stock valuations are high, pay employees in stock when valuations are high, and do stock deals when valuations are high.  They tend to go private when stock valuations are low, pay employees cash in ordinary times, and do cash deals when valuations are low.

As a result, though someone that buys and holds the stock index does best, less money is in the index when stocks are low, and a lot more when stocks are high.

Inflation Over 60 Years?

I mentioned the risk of hyperinflation above, but who can tell what inflation will do over 60 years?  If the market survives, I feel confident that stocks would outperform inflation — but how much is the open question.  We haven’t paid the price for loose monetary policy yet.  A 1% rise in inflation tends to cut stock returns by 2% for a year in real terms, but then businesses adjust and pass through higher prices.  Vice-versa when inflation falls.

Right now the 30-year forecast for inflation is around 2.1%/year, but that has bounced around considerably even within a calm environment.  My estimate of inflation over a 60-year period would be the weakest element of this analysis; you can’t tell what the politicians and central bankers will do, and they aren’t sure themselves.

Summary

Yes, you could earn 5% real returns on your money over a 60-year period… potentially.  It would take hard work, discipline, cleverness, frugality, and a cast iron stomach for risk.  You would need to be one of the few doing it.  It would also require the continued prosperity of the US and global economies.  We don’t prosper in a vacuum.

Thus in closing I will tell you that yes, you could do it, but there is a large probability of failure.  Don’t count on buying that grand villa on the Adriatic Sea in your eighties, should you have the strength to enjoy it.

Photo Credit: Mike Morbeck || On Wisconsin! On Wisconsin!

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It was shortly after the election when I last moved my trading band.  Well, time to move it again, this time up 4%, with a small twist.  I’m at my cash limit of 20%, with a few more stocks knocking on the door of a rebalancing sale, and none near a rebalancing buy.  (To decode this, you can read my article on portfolio rule seven.)  Here is portfolio rule seven:

Rebalance the portfolio whenever a stock gets more than 20% away from its target weight. Run a largely equal-weighted portfolio because it is genuinely difficult to tell what idea is the best. Keep about 30-40 names for diversification purposes.

This is my interim trading rule, which helps me make a little additional money for clients by buying relatively low and selling relatively high.  It also reduces risk, because higher prices are riskier than lower prices, all other things equal.

There are two companies that are double-weights in my portfolio, one half-weight, and 32 single-weights.  The half-weight is a micro-cap that is difficult to buy or sell. (Patience, patience…)  With cash near 20%, a single-weight currently runs around 2.2% of assets, with buying happening near 1.75%, and selling near 2.63%.

But, I said there was a small twist.  I’m going to add another single-weight position.  I don’t know what yet.  Also, I’m leaving enough in reserve to turn one of the single-weights into a double-weight.  That company is a well-run Mexican firm that has  had a falling stock price even though it is still performing well.  If it falls another 10%, I will do more than rebalance.  I will rebalance and double it.

Part of the reason for the move in both number of positions and position size at the same time is that both the half-weight and one single-weight that is at the top of its band are being acquired for cash, and so they (3.5% of assets) behave more like cash than stocks.

Thus, amid a portfolio that has been performing well, I am adjusting my positioning so that if the market continues to do well, the portfolio doesn’t lag much, or even continues to outperform.  I’m not out to make big macro bets; I will make a small bet that the market is high, and carry above average cash, but it will all get deployed if the market falls 25%+ from here.

I keep the excess cash around for the same reason Buffett does.  It gives you more easy options in a bad market environment.  Until that environment comes, you’ll never know how valuable is is to keep some extra cash around.  Better safe, than sorry.

Photo Credit: eflon || The title of the article comes from a comment Greenberg supposedly made to Buffett when AIG was much bigger than Berkshire Hathaway — times change…

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The title of the article comes from a comment Greenberg supposedly made to Buffett when AIG was much bigger than Berkshire Hathaway [BRK] — times change…

It’s come to this: AIG has sought out reinsurance from BRK to cap the amount of losses they will pay for prior business written.  It’s quite a statement when you are willing to pay $10 billion in order to have BRK pay 80% of claims over $25 billion, up to $20 billion in total.  At $50 Billion in claims AIG is on its own again.

So what business was covered?  A lot.  This is the one of the biggest deals of its type, ever:

The agreement covers 80% of substantially all of AIG’s U.S. Commercial long-tail exposures for accident years 2015 and prior, which includes the largest part of AIG’s U.S. casualty exposures during that period. AIG will retain sole authority to handle and resolve claims, and NICO has various access, association and consultation rights.

Or as was said in the Wall Street Journal article:

The pact covers such product lines as workers’ compensation, directors’ and officers’ liability, professional indemnity, medical malpractice, commercial automobile and some other liability policies.

Now, AIG is not among the better P&C insurance companies for reserving out there.  2.5 years ago, they made the Aleph Blog Hall of Shame for P&C reserving.  Now if you would have looked on the last 10-K on page 296 for item 8, note 12, you would note that AIG’s reserving remained weak for 2014 and 2015 as losses and loss adjustment expenses incurred for the business of prior years continued positive.

For AIG, this puts a lot of its troubles behind it, after the upcoming writeoff (from the WSJ article):

AIG, one of the biggest sellers of insurance by volume to businesses around the globe, also said it expects a material fourth-quarter charge to boost its claims reserves. AIG declined to comment on the possible size. Its fourth-quarter earnings will be released next month.

For BRK, this is an opportunity to make money investing the $10 billion as claims on the long-tail business get paid out slowly.  It’s called float, which isn’t magic, but Buffett has done better than most at investing the float, and choosing insurance business to write and reinsure that doesn’t result in large losses for BRK.

I expect BRK to make an underwriting profit on this, but let’s assume the worst, that BRK pays out the full $20 billion.  Say the claims come at a rate of $5 billion/year.  The average payout period would be 7.5 years, and BRK would have to earn 9.2% on the float to break even.  At $3.75B/yr, the figures would be 10 years and 6.9%.  At $2.5B/yr, 15 years and 4.6%.

This doesn’t seem so bad to me — now I don’t know how bad reserve development will be for AIG, but BRK is usually pretty careful about underwriting this sort of thing. That said BRK has a lot of excess cash sitting around already, and desirable targets for large investments are few.  This had better make an underwriting profit, or a small loss, or maybe Buffett is ready for the market to fall apart, and thus the rate he can earn goes up.

All that said, it is an interesting chapter in the relationship between the two companies.  If BRK wasn’t the dominant insurance company of the US after the 2008 financial crisis, it definitely is now.

Full disclosure: long BRK/B for myself and clients

Idea Credit: Philosophical Economics Blog || I get implementation credit, which is less…

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My last post on this generated some good questions.  I’m going to answer them here, because this model deserves a better explanation.  Before I start, I should say that in order to understand the model, you need to read the first two articles in the series, which are here:

If you are curious about the model, the information is there.  It includes links to the main article at Economic Philosopher’s blog ( @jesselivermore on Twitter).

On to the questions:

Is this nominal or real return? Where can I find your original blog post explaining how you calculate future returns? Similar charts using Shiller PE, total market cap to gdp, q-ratio etc. all seem to imply much lower future returns.

This is a nominal return.  In my opinion, returns and inflation should be forecast separately, because they have little to do with each other.  Real interest rates have a large impact on equity prices, inflation has a small impact that varies by sector.

This model also forecasts returns for the next ten years.  If I had it do forecasts over shorter horizons, the forecasts would be lower, and less precise.  The lower precision comes from the greater ease of forecasting an average than a single year.  It would be lower because the model has successively less power in forecasting each successive year — and that should make sense, as the further you get away from the current data, the less impact the data have.  Once you get past year ten, other factors dominate that this model does not account for — factors reflecting the long-term productivity of capital.

I can’t fully explain why this model is giving higher return levels, but I can tell you how the models are different:

  • This model focuses in investor behavior — how much are investors investing in stocks versus everything else.  It doesn’t explicitly consider valuation.
  • The Shiller PE isn’t a well-thought-out model for many reasons.  16 years ago I wrote an email to Ken Fisher where I listed a dozen flaws, some small and some large.  That e-mail is lost, sadly.  That said, let me be as fair as I can be — it attempts to compare the S&P 500 to trailing 10-year average earnings.  SInce using a single year would be unsteady, the averaging is a way to compare a outdated smoothed income statement figure to the value of the index.  Think of it as price-to-smoothed-earnings.
  • Market Cap to GDP does a sort of mismatch, and makes the assumption that public firms are representative of all firms.  It also assumes that total payments to all factors are what matter for equities, rather than profits only.  Think of it as a mismatched price-to-sales ratio.
  • Q-ratio compares the market value of equities and debt to the book value of the same.  The original idea was to compare to replacement value, but book value is what is available.  The question is whether it would be cheaper to buy or build the corporations.  If it is cheaper to build, stocks are overvalued.  Vice-versa if they are cheaper to buy.  The grand challenge here is that book value may not represent replacement cost, and increasingly so because intellectual capital is an increasing part of the value of firms, and that is mostly not on the balance sheet.  Think of a glorified Economic Value to Book Capital ratio.

What are the return drivers for your model? Do you assume mean reversion in (a) multiples and (b) margins?

Again, this model does not explicitly consider valuations or profitability.  It is based off of the subjective judgments of people allocating their portfolios to equities or anything else.  Of course, when the underlying ratio is high, it implies that people are attributing high valuations to equities relative to other assets, and vice-versa.  But the estimate is implicit.

So…I’m wondering what the difference is between your algorithm for future returns and John Hussman’s algorithm for future returns. For history, up to the 10 year ago point, the two graphs look quite similar. However, for recent years within the 10-year span, the diverge quite substantially in absolute terms (although the shape of the “curves” look quite similar). It appears that John’s algorithm takes into account the rise in the market during the 2005-2008 timeframe, and yours does not (as you stated, all else remaining the same, the higher the market is at any given point, the lower the expected future returns that can be for an economy). That results in shifting your expected future returns up by around 5% per year compared to his! That leads to remarkably different conclusions for the future.

Perhaps you have another blog post explaining your prediction algorithm that I have not seen. John has explained (and defended) his algorithm extensively. In absence of some explanation of the differences, I think that John’s is more credible at this point. See virtually any of his weekly posts for his chart, but the most recent should be at http://www.hussmanfunds.com/wmc/wmc161212e.png (DJM: the article in question is here.)

I’d love to meet and talk with John Hussman.  I have met some members of his small staff, and he lives about six miles from my house.  (PS — Even more, I would like to meet @jesselivermore).  The Baltimore CFA Society asked him to come speak to us a number of times, but we have been turned down.

Now, I’m not fully cognizant of everything he has written on the topic, but the particular method he is using now was first published on 5/18/2015.  There is an article critiquing aspects of Dr. Hussman’s methods from Economic Philosopher.  You can read EP for yourself, but I gain one significant thing from reading this — this isn’t Hussman’s first model on the topic.  This means the current model has benefit of hindsight bias as he acted to modify the model to correct inadequacies.  We sometimes call it a specification search.  Try out a number of models and adjust until you get one that fits well.  This doesn’t mean his model is wrong, but that the odds of it forecasting well in the future are lower because each model adjustment effectively relies on less data as the model gets “tuned” to eliminate past inaccuracies.  Dr. Hussman has good reasons to adjust his models, because they have generally been too bearish, at least recently.

I don’t have much problem with his underlying theory, which looks like a modified version of Price-to-sales.  It should be more comparable to the market cap to GDP model.

This model, to the best of my knowledge, has not been tweaked.  It is still running on its first pass through the data.  As such, I would give it more credibility.

There is another reason I would give it more credibility.  You don’t have the same sort of tomfoolery going on now as was present during the dot-com bubble.  There are some speculative enterprises today, yes, but they don’t make up as much of the total market capitalization.

All that said, this model does not tell you that the market can’t fall in 2017.  It certainly could.  But what it does tell you versus valuations in 1999-2000 is that if we do get a bear market, it likely wouldn’t be as severe, and would likely come back faster.  This is not unique to this model, though.  This is true for all of the models mentioned in this article.

Stock returns are probabilistic and mean-reverting (in a healthy economy with no war on your home soil, etc.).  The returns for any given year are difficult to predict, and not tightly related to valuation, but the returns over a long period of time are easier to predict, and are affected by valuation more strongly.  Why?  The correction has to happen sometime, and the most likely year is next year when valuations are high, but the probability of it happening in the 2017 are maybe 30-40%, not 80-100%.

If you’ve read me for a long time, you will know I almost always lean bearish.  The objective is to become intelligent in the estimation of likely returns and odds.  This model is just one of ones that I use, but I think it is the best one that I have.  As such, if you look the model now, we should be Teddy Bears, not full-fledged Grizzlies.

That is my defense of the model for now.  I am open to new data and interpretations, so once again feel free to leave comments.

As such, if you look the model now, we should be Teddy Bears, not full-fledged Grizzly Bears. Click To Tweet

Idea Credit: Philosophical Economics Blog || I get implementation credit, which is less… 😉

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Are you ready to earn 6%/year until 9/30/2026?  The data from the Federal Reserve comes out with some delay.  If I had it instantly at the close of the third quarter, I would have said 6.37% — but with the run-up in prices since then, the returns decline to 6.01%/year.

That puts us in the 82nd percentile of valuations, which isn’t low, but isn’t the nosebleed levels last seen in the dot-com era.  There are many talking about how high valuations are, but investors have not responded in frenzy mode yet, where they overallocate stocks relative to bonds and other investments.

Think of it this way: as more people invest in equities, returns go up to those who owned previously, but go down for the new buyers.  The businesses themselves throw off a certain rate of return evaluated at replacement cost, but when the price paid is far above replacement cost the return drops considerably even as the cash flows from the businesses do not change at all.

For me to get to a level where I would hedge my returns, we would be talking about considerably higher levels where the market is discounting future returns of 3%/year — we don’t have that type of investor behavior yet.

One final note: sometimes I like to pick on the concept of Dow 36,000 because the authors didn’t get the concept of risk premia, or, margin of safety.  They assumed the market could be priced to no margin of safety, and with high growth.  That said, the model does offer a speculative prediction of Dow 36,000.  It just happens to come around the year 2030.

Until next time, when we will actually have some estimates of post-election behavior… happy investing and remember margin of safety.

Are you ready to earn 6%/year until 9/30/2026? Click To Tweet

Photo Credit: ajehals || Pensions are promises. Sadly, promises are often broken. Choose your promiser with care…

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If you want a full view of what I am writing about today, look at this article from The Post and Courier, “South Carolina’s looming pension crisis.”  I want to give you some perspective on this, so that you can understand better what went wrong, and what is likely to go wrong in the future.

Before I start, remember that the rich get richer, and the poor poorer even among states.  Unlike what many will tell you though, it is not any conspiracy.  It happens for very natural reasons that are endemic in human behavior.  The so-called experts in this story are not truly experts, but sourcerer’s apprentices who know a few tricks, but don’t truly understand pensions and investing.  And from what little I can tell from here, they still haven’t learned.  I would fire them all, and replace all of the boards in question, and turn the politicians who are responsible out of office.  Let the people of South Carolina figure out what they must do here — I’m a foreigner to them, but they might want to hear my opinion.

Let’s start here with:

Central Error 1: Chasing the Markets

Credit: The Courier and Post

Much as inexperienced individuals did, the South Carolina Retirement System Investment Commission [SCRSIC] chased the markets in an effort to earn returns when they seemed easy to get in hindsight.  As the article said:

It used to be different, before the high-octane investment strategies began. South Carolina’s pension plans were considered 99 percent funded in 1999, and on track to pay all promised benefits for decades to come.

That was the year the pension funds started investing in stocks, in hopes of pulling in even more income. A change to the state constitution and action by the General Assembly allowed those investments. In the previous five years, U.S. stock prices had nearly tripled.

Prior to that time, the pension funds were largely invested in bonds and cash, which actually yielded something back then.  If the pension funds were invested in bonds that were long, the returns might not have been so bad versus stocks.  But in the late ’90s the market went up aggressively, and the money looked easy, and it was easy, partly due to loose monetary policy, and a mania in technology and internet stocks.

Here’s the real problem.  It’s okay to invest in only bonds. It’s okay to invest in bonds and stocks in a fixed proportion.  It’s okay even to invest only in stocks.  Whatever you do, keep the same policy over the long haul, and don’t adjust it.  Also, the more nonguaranteed your investments become (anything but high quality bonds), the larger your provision against bear markets must become.

And, when you start a new policy, do what is not greedy.  1999-2000 was the right time to buy long bonds and sell stocks, and I did that for a small trust that I managed at the time.  It looked dumb on current performance, but if you look at investing as a business asking what level of surplus cash flows the underlying investments will throw off, it was an easy choice, because bonds were offering a much higher future yield than stocks.  But the natural tendency is to chase returns, because most people don’t think, they imitate.  And that was true for the SCRSIC, bigtime.

Central Error 2: Bad Data

The above quote said that “South Carolina’s pension plans were considered 99 percent funded in 1999.”  That was during an era when government accounting standards were weak.  The standards are still weak, but they are stronger than they were.  South Carolina was NOT 99% funded in 1999 — I don’t know what the right answer would have been, but it would have been considerably lower, like 80% or so.

Central Error 3: Unintelligent Diversification into “Alternatives”

In 2009, I had the fun of writing a small report for CALPERS.  One of my main points was that they allocated money to alternative investments too late.  With all new classes of investments the best deals get done early, and as more money flows into the new class returns surge because the flood of buyers drives prices up.  Pricing is relatively undifferentiated, because experience is early, and there have been few failures.  After significant failures happen, differentiation occurs, and players realize that there are sponsors with genuine skill, and “also rans.”  Those with genuine skill also limit the amount of money they manage, because they know that good-returning ideas are hard to come by.

The second aspect of this foolishness comes from the consultants who use historical statistics and put them into brain-dead mean-variance models which spit out an asset allocation.  Good asset allocation work comes from analyzing what economic return the underlying business activities will throw off, and adjusting for risk qualitatively.  Then allocate funds assuming they will never be able to trade something once bought.  Maybe you will be able to trade, but never assume there will be future liquidity.

The article kvetches about the expenses, which are bad, but the strategy is worse.  The returns from all of the non-standard investments were poor, and so was their timing — why invest in something not geared much to stock returns when the market is at low valuations?  This is the same as the timing problem in point one.

Alternatives might make sense at market peaks, or providing liquidity in distressed situations, but for the most part they are as saturated now as public market investments, but with more expenses and less liquidity.

Central Error 4: Caring about 7.5% rather than doing your best

Part of the justification for buying the alternatives rather than stocks and bonds is that you have more of a chance of beating the target return of the plan, which in this case was 7.5%/yr.  Far better to go for the best risk-adjusted return, and tell the State of South Carolina to pony up to meet the promises that their forbears made.  That brings us to:

Central Error 5: Foolish politicians who would not allocate more money to pensions, and who gave pension increases rather than wage hikes

The biggest error belongs to the politicians and bureaucrats who voted for and negotiated higher pension promises instead of higher wages.  The cowards wanted to hand over an economic benefit without raising taxes, because the rise in pension benefits does not have any immediate cash outlay if one can bend the will of the actuary to assume that there will be even higher investment earnings in the future to make up the additional benefits.

[Which brings me to a related pet peeve.  The original framers of the pension accounting rules assumed that everyone would be angels, and so they left a lot of flexibility in the accounting rules to encourage the creation of defined benefit plans, expecting that men of good will would go out of their way to fund them fully and soon.

The last 30 years have taught us that plan sponsors are nothing like angels, playing for their own advantage, with the IRS doing its bit to keep corporate plans from being fully funded so that taxes will be higher.  It would have been far better to not let defined benefit plans assume any rate of return greater than the rate on Treasuries that would mimic their liability profile, and require immediate relatively quick funding of deficits.  Then if plans outperform Treasuries, they can reduce their contributions by that much.]

Error 5 is likely the biggest error, and will lead to most of the tax increases of the future in many states and municipalities.

Central Error 6: Insufficient Investment Expertise

Those in charge of making the investment decisions proved themselves to be as bad as amateurs, and worse.  As one of my brighter friends at RealMoney, Howard Simons, used to say (something like), “On Wall Street, to those that are expert, we give them super-advanced tools that they can use to destroy themselves.”   The trustees of SCRSIC received those tools and allowed themselves to be swayed by those who said these magic strategies will work, possibly without doing any analysis to challenge the strategies that would enrich many third parties.  Always distrust those receiving commissions.

Central Error 7: Intergenerational Equity of Employee Contributions

The last problem is that the wrong people will bear the brunt of the problems created.  Those that received the benefit of services from those expecting pensions will not be the prime taxpayers to pay those pensions.  Rather, it will be their children paying for the sins of the parents who voted foolish people into office who voted for the good of current taxpayers, and against the good of future taxpayers.  Thank you, Silent Generation and Baby Boomers, you really sank things for Generation X, the Millennials, and those who will follow.

Conclusion

Could this have been done worse?  Well, there is Illinois and Kentucky.  Puerto Rico also.  Many cities are in similar straits — Chicago, Detroit, Dallas, and more.

Take note of the situation in your state and city, and if the problem is big enough, you might consider moving sooner rather than later.  Those that move soonest will do best selling at higher real estate prices, and not suffer the soaring taxes and likely diminution of city services.  Don’t kid yourself by thinking that everyone will stay there, that there will be a bailout, etc.  Maybe clever ways will be found to default on pensions (often constitutionally guaranteed, but politicians don’t always honor Constitutions) and municipal obligations.

Forewarned is forearmed.  South Carolina is a harbinger of future problems, in their case made worse by opportunists who sold the idea of high-yielding investments to trustees that proved to be a bunch of rubes.  But the high returns were only needed because of the overly high promises made to state employees, and the unwillingness to levy taxes sufficient to fund them.

Seven central errors committed by the South Carolina Retirement System and politicians Click To Tweet

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Most days, I don’t trade.  I study.  I model.  I muse.  I plan.

There are some clever traders out there.  I am not one of them.  What little trading I do is done efficiently and effectively to get the best prices for assets that I want to buy and sell, but that’s not where most of the money is made in investing.

I can be like a chef who goes out to the market in the morning and buys the best ingredients available that day at great prices, except that my period of analysis is years, not a day.  The point is that I consider the deals that the market is offering, and choose attractive ones that will benefit my clients and me for years to come.  (I am still the largest investor that I manage money for — I eat the exact same meal that I serve to clients.)

What trading I do divides into two categories, which are designed for two different time horizons.  The first time horizon is long — 3-10 years in length.  Can I find companies with good or better business prospects trading at prices more attractive than the businesses that I currently own?

This is mostly a patient thing, unless I conclude that I got something materially wrong, in which case I try to be quick to sell.  Patience is needed, because investing is like farming.  It doesn’t grow overnight.  It will take time for value to be built, and time for people to recognize that the company is better than they thought it was.  It won’t be a linear process, either, unless something unusually good happens.  There are setbacks with almost every winning investment.  Keep your eyes on the main drivers of growth in value, and whether management is using excess cash to the best ends, which will vary by company.

At least half of my winners spent time as an unrealized capital loss at some point.  My timing is sometimes nonideal, but ideal timing is not required for great results if the time horizon is years.  So I watch and monitor, and occasionally trade away the position when I find something with materially better prospects.

As an aside, not all RIA clients would like this, because it looks like I’m not doing that much.  I sometimes wonder how much better money management would be if clients were happy with portfolios that don’t change much and don’t have many of the current hottest and most recognizable companies in them.  Portfolios filled with unknown companies in boring but profitable industries… difficult to talk about at parties, but often more profitable.

What I have mentioned above is 85% of what I do.  The shorter-run movements of the market provide the other 15% as ideas and companies go in and out of favor in the short run.  I mentioned that my timing is often not the best.  This gives me an opportunity to do a little better.

I’ve mentioned that I use a 20% band around my position weights for the companies that I own.  As prices fall and hit the bottom of the band, I buy enough to come back up to the target weight.  Vice-versa for when the price hits the upper band.

20% is a significant move — it’s enough to justify the trading costs.  If the company is still a good one, the fall in price gives me the opportunity to lower my average cost modestly.  Note that this is a modest change — I’m not trying to be a hero or a home-run hitter.  I learned better when I was younger that making timing decisions on that level is too undisciplined.  It is far better to edge in and edge out around a core position — with a good company, a lower price means lower risk, and a higher price means higher risk, so this method is always taking and shedding risk at appropriate levels.

Edge in, edge out — trades like this happen a few times a month — more frequently when the market is lively, less often when it is sleepy.  Hey, don’t force things.  This is gradual reallocation of money from less to more attractive homes for capital.  The time horizon here is 3-12 months, and offers the ability to make a little more off of core positions.

Over 5 years, companies that I own might have a grand total of 5-10 trades from edging in and out.  It will always be a mix of both buys and sells — few companies don’t have moves of 20%+ down amid growth.  (As some will note, if markets are efficient, why is there such a large gap between 52-week highs and lows for individual stocks?  Really, markets aren’t efficient — they are just very hard to beat.)

Now, others will come up with different ways of managing multiple time horizons in investing, but this method offers a decent balance between the short- and long-terms, and does so in a businesslike, disciplined way.  And so I edge in and edge out.

This balances the short- and long-terms, and does so in a businesslike, disciplined way. Click To Tweet