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.


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.


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: Baynham Goredema || When things are crowded, how much freedom to move do you have?

Photo Credit: Baynham Goredema || When things are crowded, how much freedom to move do you have?

Stock diversification is overrated.

Alternatives are more overrated.

High quality bonds are underrated.

This post was triggered by a guy from the UK who sent me an infographic on reducing risk that I thought was mediocre at best.  First, I don’t like infographics or video.  I want to learn things quickly.  Give me well-written text to read.  A picture is worth maybe fifty words, not a thousand, when it comes to business writing, perhaps excluding some well-designed graphs.

Here’s the problem.  Do you want to reduce the volatility of your asset portfolio?  I have the solution for you.  Buy bonds and hold some cash.

And some say to me, “Wait, I want my money to work hard.  Can’t you find investments that offer a higher return that diversify my portfolio of stocks and other risky assets?”  In a word the answer is “no,” though some will tell you otherwise.

Now once upon a time, in ancient times, prior to the Nixon Era, no one hedged, and no one looked for alternative investments.  Those buying stocks stuck to well-financed “blue chip” companies.

Some clever people realized that they could take risk in other areas, and so they broadened their stock exposure to include:

  • Growth stocks
  • Midcap stocks (value & growth)
  • Small cap stocks (value & growth)
  • REITs and other income passthrough vehicles (BDCs, Royalty Trusts, MLPs, etc.)
  • Developed International stocks (of all kinds)
  • Emerging Market stocks
  • Frontier Market stocks
  • And more…

And initially, it worked.  There was significant diversification until… the new asset subclasses were crowded with institutional money seeking the same things as the original diversifiers.

Now, was there no diversification left?  Not much.  The diversification from investor behavior is largely gone (the liability side of correlation).  Different sectors of the global economy don’t move in perfect lockstep, so natively the return drivers of the assets are 60-90% correlated (the asset side of correlation, think of how the cost of capital moves in a correlated way across companies).  Yes, there are a few nooks and crannies that are neglected, like Russia and Brazil, industries that are deeply out of favor like gold, oil E&P, coal, mining, etc., but you have to hold your nose and take reputational risk to buy them.  How many institutional investors want to take a 25% chance of losing a lot of clients by failing unconventionally?

Why do I hear crickets?  Hmm…

Well, the game wasn’t up yet, and those that pursued diversification pursued alternatives, and they bought:

  • Timberland
  • Real Estate
  • Private Equity
  • Collateralized debt obligations of many flavors
  • Junk bonds
  • Distressed Debt
  • Merger Arbitrage
  • Convertible Arbitrage
  • Other types of arbitrage
  • Commodities
  • Off-the-beaten track bonds and derivatives, both long and short
  • And more… one that stunned me during the last bubble was leverage nonprime commercial paper.

Well guess what?  Much the same thing happened here as happened with non-“blue chip” stocks.  Initially, it worked.  There was significant diversification until… the new asset subclasses were crowded with institutional money seeking the same things as the original diversifiers.

Now, was there no diversification left?  Some, but less.  Not everyone was willing to do all of these.  The diversification from investor behavior was reduced (the liability side of correlation).  These don’t move in perfect lockstep, so natively the return drivers of the risky components of the assets are 60-90% correlated over the long run (the asset side of correlation, think of how the cost of capital moves in a correlated way across companies).  Yes, there are some that are neglected, but you have to hold your nose and take reputational risk to buy them, or sell them short.  Many of those blew up last time.  How many institutional investors want to take a 25% chance of losing a lot of clients by failing unconventionally?

Why do I hear crickets again?  Hmm…

That’s why I don’t think there is a lot to do anymore in diversifying risky assets beyond a certain point.  Spread your exposures, and do it intelligently, such that the eggs are in baskets are different as they can be, without neglecting the effort to buy attractive assets.

But beyond that, hold dry powder.  Think of cash, which doesn’t earn much or lose much.  Think of some longer high quality bonds that do well when things are bad, like long treasuries.

Remember, the reward for taking business risk in general varies over time.  Rewards are relatively thin now, valuations are somewhere in the 9th decile (80-90%).  This isn’t a call to go nuts and sell all of your risky asset positions.  That requires more knowledge than I will ever have.  But it does mean having some dry powder.  The amount is up to you as you evaluate your time horizon and your opportunities.  Choose wisely.  As for me, about 20-30% of my total assets are safe, but I have been a risk-taker most of my life.  Again, choose wisely.

PS — if the low volatility anomaly weren’t overfished, along with other aspects of factor investing (Smart Beta!) those might also offer some diversification.  You will have to wait for those ideas to be forgotten.  Wait to see a few fund closures, and a severe reduction in AUM for the leaders…

Photo Credit: Tony & Wayne || Do we PEG the growth of pretty flowers?

Photo Credit: Tony & Wayne || Do we PEG the growth of pretty flowers?

I was looking through an article to see if it had any decent stock ideas, and noted that most of the companies featured were growth stocks.  As such, my first pass for analysis is the PEG ratio, which is the ratio of the Price-Earnings ratio divided by the growth rate expressed as a percentage (e.g. 8% => 8 for this calculation.).

I’ve written about the PEG ratio a long time ago, and it is a classic article of mine.  The PEG ratio is a valid concept for “growth at a reasonable” price investors.  It does not work well for value investors or aggressive growth investors.  My rule for implementation comes to this: if the current P/E ratio is 12 or higher and the PEG ratio is lower than 1.5, that stock might be worth a look.  Better to find the PEG ratio below one, though.

I went through the article and concluded that maybe Becton Dickinson and Hanesbrands might be worth a look.  But then I thought, “What if I applied the formula to propose overvalued stocks?”

I set my screener for a 2016 PE higher than 12 and a PEG higher than 2.0x, with failing momentum, where the stock was down more than 20% in the nine months prior to the current month.  Here were the 50 stocks that resulted:

What I find fascinating here is the mix of hot companies, basic materials and energy names, and limited partnerships.

This is only a start for analysis, so don’t run out and short these.  Not that I am big on shorting, but high earnings valuations, and failing price momentum could be a good place to start.  I have no positions in any of these companies, and I rarely if ever short.  I just thought this would be an interesting exercise.


I’m still working through the SEC’s proposal on Mutual Fund Liquidity, which I mentioned at the end of this article:

Q: <snip> Are you going to write anything regarding the SEC’s proposal on open end mutual funds and ETFs regarding liquidity?

A: <snip> …my main question to myself is whether I have enough time to do it justice.  There’s their white paper on liquidity and mutual funds.  The proposed rule is a monster at 415 pages, and I may have better things to do.   If I do anything with it, you’ll see it here first.

These are just notes on the proposal so far.  Here goes:

1) It’s a solution in search of a problem.

After the financial crisis, regulators got one message strongly — focus on liquidity.  Good point with respect to banks and other depositary financials, useless with respect to everything else.  Insurers and asset managers pose no systemic risk, unless like AIG they have a derivatives counterparty.  Even money market funds weren’t that big of a problem — halt withdrawals for a short amount of time, and hand out losses to withdrawing unitholders.

The problem the SEC is trying to deal with seems to be that in a crisis, mutual fund holders who do not sell lose value from those who are selling because the Net Asset Value at the end of the day does not go low enough.  In the short run, mutual fund managers tend to sell liquid assets when redemptions are spiking; the prices of illiquid assets don’t move as much as they should, and so the NAV is artificially high post-redemptions, until the prices of illiquid assets adjust.

The proposal allows for “swing pricing.”  From the SEC release:

The Commission will consider proposed amendments to Investment Company Act rule 22c-1 that would permit, but not require, open-end funds (except money market funds or ETFs) to use “swing pricing.” 

Swing pricing is the process of reflecting in a fund’s NAV the costs associated with shareholders’ trading activity in order to pass those costs on to the purchasing and redeeming shareholders.  It is designed to protect existing shareholders from dilution associated with shareholder purchases and redemptions and would be another tool to help funds manage liquidity risks.  Pooled investment vehicles in certain foreign jurisdictions currently use forms of swing pricing.

A fund that chooses to use swing pricing would reflect in its NAV a specified amount, the swing factor, once the level of net purchases into or net redemptions from the fund exceeds a specified percentage of the fund’s NAV known as the swing threshold.  The proposed amendments include factors that funds would be required to consider to determine the swing threshold and swing factor, and to annually review the swing threshold.  The fund’s board, including the independent directors, would be required to approve the fund’s swing pricing policies and procedures.

But there are simpler ways to do this.  In the wake of the mutual fund timing scandal, mutual funds were allowed to estimate the NAV to reflect the underlying value of assets that don’t adjust rapidly.  This just needs to be followed more aggressively in a crisis, and peg the NAV lower than they otherwise would, for the sake of those that hold on.

Perhaps better still would be provisions where exit loads are paid back to the funds, not the fund companies.  Those are frequently used for funds where the underlying assets are less liquid.  Those would more than compensate for any losses.

2) This disproportionately affects fixed income funds.  One size does not fit all here.  Fixed income funds already use matrix pricing extensively — the NAV is always an estimate because not only do the grand majority of fixed income instruments not trade each day, most of them do not have anyone publicly posting a bid or ask.

In order to get a decent yield, you have to accept some amount of lesser liquidity.  Do you want to force bond managers to start buying instruments that are nominally more liquid, but carry more risk of loss?  Dividend-paying common stocks are more liquid than bonds, but it is far easier to lose money in stocks than in bonds.

Liquidity risk in bonds is important, but it is not the only risk that managers face.  it should not be made a high priority relative to credit or interest rate risks.

3) One could argue that every order affects market pricing — nothing is truly liquid.  The calculations behind the analyses will be fraught with unprovable assumptions, and merely replace a known risk with an unknown risk.

4) Liquidity is not as constant as you might imagine.  Raising your bid to buy, or lowering your ask to sell are normal activities.  Particularly with illiquid stocks and bonds, volume only picks up when someone arrives wanting to buy or sell, and then the rest of the holders and potential holders react to what he wants to do.  It is very easy to underestimate the amount of potential liquidity in a given asset.  As with any asset, it comes at a cost.

I spent a lot of time trading illiquid bonds.  If I liked the creditworthiness, during times of market stress, I would buy bonds that others wanted to get rid of.  What surprised me was how easy it was to source the bonds and sell the bonds if you weren’t in a hurry.  Just be diffident, say you want to pick up or pose one or two million of par value in the right context, say it to the right broker who knows the bond, and you can begin the negotiation.  I actually found it to be a lot of fun, and it made good money for my insurance client.

5) It affects good things about mutual funds.  Really, this regulation should have to go through a benefit-cost analysis to show that it does more good than harm.  Illiquid assets, properly chosen, can add significant value.  As Jason Zweig of the Wall Street Journal said:

The bad news is that the new regulations might well make most fund managers even more chicken-hearted than they already are — and a rare few into bigger risk-takers than ever.

You want to kill off active managers, or make them even more index-like?  This proposal will help do that.

6) Do you want funds to limit their size to comply with the rules, while the fund firm rolls out “clone” fund 2, 3, 4, 5, etc?


You will never fully get rid of pricing issues with mutual funds, but the problems are largely self-correcting, and they are not systemic.  It would be better if the SEC just withdrew these proposed rules.  My guess is that the costs outweigh the benefits, and by a wide margin.



Liquidity is ephemeral, and difficult to define.  The first real article at my blog was about liquidity, and the three things that liquidity can mean, notably: the ability to:

  • Enter into large or exit from commitments to risk assets cheaply (cost)
  • Borrow at tight credit spreads compared to the safest borrowers
  • Make large adjustments to their asset allocations rapidly (speed)

Most of these phenomena can be observed without complex models.  Ask yourself:

  • Is credit growing rapidly?
  • Are the exchanges moving turning over stocks more rapidly?
  • Are credit spreads tight?
  • Have credit terms and conditions deteriorated?
  • Do lenders care more about volume of lending than quality of lending?

My bias is that I think most of the academic mathematical models of liquidity risk are overly technical, and tend to obscure liquidity conditions rather than reveal what is going on.  You may disagree with that view.

But unless you disagree with that view and you like math, this book will not be worth a lot to you.  Yes, there are qualitative sections, and they are good.  For example, the beginning of chapter 2 is very good at illustrating the paradoxical nature of liquidity.  Chapters 1-3 would have made a very good qualitative monograph on liquidity — but it would be so small that you couldn’t charge $80+ for it.

Chapters 4-6 will only be useful to the mathematically inclined.  I’m dubious that they even be useful then, because much of it is calculus, which does not do well with discontinuous events such as market panics.  (You would have thought that the quants on Wall Street would have learned by now, but no…)  Even if the models did work, there are simpler ways to see the same things, as I pointed out above.

As such, I really can’t recommend the book, and at $80+ the price is a lot more expensive than the free Monograph from the CFA Institute “The New Economics of Liquidity and Financial Frictions.” [PDF]  Read that, not this, and save liquidity.


The book could have used a better editor.  Too many typos in the introductory chapters.

Summary / Who Would Benefit from this Book

If you are a math nerd, and want to pay a lot of money to buy a book that I think will at least partially mislead you on liquidity risk, then this is the book for you.  If you want to buy it, you can buy it here: Market Liquidity Risk.

Full disclosure: I received a copy from a friendly PR flack.

If you enter Amazon through my site, and you buy anything, I get a small commission.  This is my main source of blog revenue.  I prefer this to a “tip jar” because I want you to get something you want, rather than merely giving me a tip.  Book reviews take time, particularly with the reading, which most book reviewers don’t do in full, and I typically do. (When I don’t, I mention that I scanned the book.  Also, I never use the data that the PR flacks send out.)

Most people buying at Amazon do not enter via a referring website.  Thus Amazon builds an extra 1-3% into the prices to all buyers to compensate for the commissions given to the minority that come through referring sites.  Whether you buy at Amazon directly or enter via my site, your prices don’t change.

Photo Credit: Kevin Dooley || At the Ice Museum, ALL of the assets are frozen!

Photo Credit: Kevin Dooley || At the Ice Museum, ALL of the assets are frozen!

This article is another experiment. Please bear with me.

Q: What is an asset worth?

A: An asset is worth whatever the highest bidder will pay for it at the time you offer it for sale.

Q: Come on, the value of an asset must be more enduring than that.  You look at the balance sheets of corporations, and they don’t list their assets at sales prices.

A: That’s for a different purpose.  We can’t get the prices of all assets to trade frequently.  The economic world isn’t only about trading, it is about building objects, offering services… and really, it is about making people happier through service.  Because the assets don’t trade regularly, they are entered onto the balance sheet at:

  • Cost, which is sometimes adjusted for cost and other things that are time-related, and subject to writedowns.
  • The value of the asset at its most recent sale date before the date of the statement
  • An estimated value calculated from sales of assets like it, meant to reflect the likely markets at the time of the statement — what might the price be in a deal between and un-coerced buyer and seller?

Anyway, values in financial statements are only indicative of aspects of value.  Few investors use them in detail.  Even value investors who use the detailed balance sheet values in their investment decisions make extensive adjustments to them to try to make them more realistic.  Other value investors look at where the prices of similar companies that went private to try to estimate the value of public equities.

Certainly the same thing goes on with real estate.  Realtors and appraisers come up with values of comparable properties, and make adjustments to try to estimate the value of the property in question.  Much as realtors don’t like Zillow, it does the same thing just with a huge econometric model that factors in as much information as they have regarding the likely prices of residential real estate given the prices of the sparse number of sales that they have to work from.

Financial institutions regularly have to estimate values for variety of illiquid assets in a similar way.  I’ve even been known to help with those efforts on occasion, though management teams have not always been grateful for that.

Q: What if it’s a bad day when I offer my asset for sale?  Is my asset worth less simply because of transitory conditions?

A: Do you have to sell your asset that day or not?

Q: Why does that matter?

A: If you don’t need the money immediately, you could wait.  You also don’t have to auction the asset if you think that hiring an expert come in and talk with a variety of motivated buyers could result in a better price after commissions.  There are no guarantees of a better result there though.

The same problem exists on the stock market.  If you want the the money now, issue a market order to sell the security, and you will get something close to the best price at that moment.  That said, I never use market orders.

Q: Why don’t you use market orders?

A: I don’t want to be left at the mercy of those trading rapidly in the markets.  I would rather set out a price that I think someone will transact at, and adjust it if need be.  Nothing is guaranteed — a trade might not get done.  But I won’t get caught in a “flash crash” type of scenario, or most other types of minor market manipulation.

Patience is a virtue in buying and selling, as is the option of walking away.  If you seem to be a forced seller, buyers will lower their bids if you seem to be desperate.  You may not notice this in liquid stocks, but in illiquid stocks and other illiquid assets, this is definitely a factor.


That’s all for now.  If anyone has any ideas on if, where, or how I should continue this piece, let me know in the comments, or send me an e-mail.  Thanks for reading.


Imagine that you are in the position of a high cost crude oil producer that has a lot of debt to service.  The price that you can sell your oil for is high enough that you make some cash over your variable cost.  The price is low enough that you are not recouping the cost of what you paid to buy the right to develop the oil, the development cost, and cost of equity capital employed.

In this awkward situation you continue to produce oil, because it may keep you from defaulting on your debts, even though you are not earning what is needed to justify the GAAP book value of your firm.  You’re destroying value by producing, but because of the debt, you don’t have the option of waiting because not surviving loses more money than pumping oil and seeing if you can survive.

Where there is life, there is hope.  Who knows, one of three things could “go right:”

  1. Enough competitors could fail such that global industry capacity reduces and prices rise.
  2. Demand for oil could rise because it is cheap, leading prices to rise.
  3. You could get bought out by a more solvent competitor with a longer time horizon, who sees the assets as eventually valuable.

Trouble is with #1, you could fail first.  With #2, the process is slow, and who knows how much the Saudis will pump.  With #3, the price that an acquirer could pay might not be enough for shareholders, or worse, they could buy out your competitors and not you, leaving you in a worse competitive position.

One more thought: think of the Saudis, the Venezuelans, etc… all of the national oil companies.  They’re not in all that different a spot than you are.  They need cash to fund government programs or they may face unrest.  For some like the Saudis, who assets in reserve, the odds are lower.  For the Venezuelans, who have had their economy destroyed by the politics of Chavez, the odds are a lot higher.

There will be failures among energy producers, and that could include nations.  Failures with each will be temporary as debts get worked through/compromised and new management takes over, and high cost supply gets shut down.  The question is: who will fail and who won’t.  The job of the hypothetical firm that I posited at the beginning of this article is to survive until prices rise.  What will a survivor look like?

  • Relatively high contribution margins (Price – variable cost per barrel)
  • Relatively little debt
  • Debt has long maturities and/or low coupons.

Now, I’m going to give you 40% of the answer here… I’m still working on the contribution margin question, but I can give you a useful measure regarding debt.  My summary measure is total debt as a ratio of market capitalization.  It’s crude, but I think it is a good first pass on debt stress, because the market capitalization figures carry an implicit estimate of the probability of bankruptcy.

Anyway here’s a list of all of the oil companies in the database that have debt greater than their market cap:

CompanyCountrytickerMkt capDebt / Market Cap
Energy XXI LtdBermudaEXXI17126.93
SandRidge Energy Inc.United StatesSD26416.63
Comstock Resources IncUnited StatesCRK1469.45
Linn Energy LLCUnited StatesLINE1,1728.81
EXCO Resources IncUnited StatesXCO2137.2
Cosan Limited(USA)BrazilCZZ1,0156.34
W&T Offshore, Inc.United StatesWTI2456
Halcon Resources CorpUnited StatesHK6205.89
BreitBurn Energy Partners L.P.United StatesBBEP6145.05
Magnum Hunter Resources CorpUnited StatesMHR1885.05
California Resources CorpUnited StatesCRC1,3254.92
Sanchez Energy CorpUnited StatesSN3684.74
Crestwood Equity Partners LPUnited StatesCEQP5434.64
Rex Energy CorporationUnited StatesREXX1714.51
Penn West Petroleum Ltd (USA)CanadaPWE4034.19
Atlas Resource Partners, L.P.United StatesARP3654.09
Gastar Exploration IncUnited StatesGST1083.8
Petroleo Brasileiro PetrobrasBrazilPBR35,7483.71
Stone Energy CorporationUnited StatesSGY2923.59
Bill Barrett CorporationUnited StatesBBG2523.19
EP Energy CorpUnited StatesEPE1,5523.15
Memorial Production Partners LUnited StatesMEMP5993.05
Premier Oil PLC (ADR)United KingdomPMOIY8282.95
Triangle Petroleum CorporationUnited StatesTPLM2862.88
Ultra Petroleum Corp.United StatesUPL1,2812.68
Bonanza Creek Energy IncUnited StatesBCEI3332.55
Northern Oil & Gas, Inc.United StatesNOG3592.47
Denbury Resources Inc.United StatesDNR1,4792.37
Jones Energy IncUnited StatesJONE3542.36
Chesapeake Energy CorporationUnited StatesCHK4,9172.35
Vanguard Natural Resources, LLUnited StatesVNR8332.27
LRR Energy LPUnited StatesLRE1282.23
Pengrowth Energy Corp (USA)CanadaPGH7052.21
Legacy Reserves LPUnited StatesLGCY4612.1
Aegean Marine Petroleum NetworGreeceANW3911.85
GeoPark LtdChileGPRK2021.8
Mitsui & Co Ltd (ADR)JapanMITSY23,7271.74
Oasis Petroleum Inc.United StatesOAS1,3901.69
Santos Ltd (ADR)AustraliaSSLTY3,8131.59
Whiting Petroleum CorpUnited StatesWLL3,5931.46
Midcoast Energy Partners LPUnited StatesMEP5581.45
Paramount Resources Ltd (USA)CanadaPRMRF1,0061.35
Encana Corporation (USA)CanadaECA5,9441.33
Clayton Williams Energy, Inc.United StatesCWEI5971.25
Clean Energy Fuels CorpUnited StatesCLNE4681.23
EV Energy Partners, L.P.United StatesEVEP4051.23
WPX Energy IncUnited StatesWPX1,6601.2
Baytex Energy Corp (USA)CanadaBTE1,0681.19
ONEOK, Inc.United StatesOKE7,4531.18
SunCoke Energy Partners LPUnited StatesSXCP5051.18
TransAtlantic Petroleum LtdUnited StatesTAT1261.13
Global Partners LPUnited StatesGLP1,0711.12
NGL Energy Partners LPUnited StatesNGL2,6591.12
Sprague Resources LPUnited StatesSRLP4951.11
Amyris IncUnited StatesAMRS2661.07
Sunoco LPUnited StatesSUN1,6051.06
SM Energy CoUnited StatesSM2,3601.05
Solazyme IncUnited StatesSZYM2021


This isn’t a complete analysis by any means. Personally, I would be skeptical of holding any company twice as much debt as market cap without a significant analysis.  Have at it your own way, but be careful, there will be a lot of stress on oil companies with high debt.

Photo Credit: Dr. Wendy Longo || This horizon is distant...

Photo Credit: Dr. Wendy Longo || This horizon is distant…

I ran across two interesting articles today:

Both articles are exercises in understanding the time horizon over which you invest.  If you are older, you may not have the time to recover from market shortfalls, so advice to buy dips may sound hollow when you are nearer to drawing on your assets.

Thus the idea that volatility, presumably negative, doesn’t hurt unless you sell.  Some people don’t have much choice in the matter.  They have retired, and they have a lump sum of money that they are managing for long-term income.  No more money is going in, money is only going out.  What can you do?

You have to plan before volatility strikes.  My equity only clients had 14% cash before the recent volatility hit.  Over the past week I opportunistically brought that down to 10% in names that I would like to own even if the “crisis” deepened.  That flexibility was built into my management.  (If the market recovers enough, I will rebuild the buffer.  Around 1300 on the S&P, I would put all cash to work, and move to the alternative portfolio management strategy where I sell the most marginal ideas one at a time to raise cash and reinvest into the best ideas.)

If an older investor would be hurt by a drawdown in the stock market, he needs to invest less in stocks now, even if that means having a lower income on average over the longer-term.  With a higher level of bonds in the portfolio, he could more than proportionately draw down on bonds during a crisis, which would rebalance his portfolio.  If and when the stock market recovered, for a time, he could draw on has stock positions more than proportionately then.  That also would rebalance the portfolio.

Again, plans like that need to be made in advance.  If you have no plans for defense, you will lose most wars.

One more note: often when we talk about time horizon, it sounds like we are talking about a single future point in time.  When the time for converting assets to cash is far distant, using a single point may be a decent approximation.  When the time for converting assets to cash is near, it must be viewed as a stream of payments, and whatever scenario testing, (quasi) Monte Carlo simulations, and sensitivity analyses are done must reflect that.

Many different scenarios may have the same average rate of return, but the ones with early losses and late gains are pure poison to the person trying to manage a lump sum in retirement.  The same would apply to an early spike in inflation rates followed by deflation.

The time to plan is now for all contingencies, and please realize that this is an art and not a science, so if someone comes to you with glitzy simulation analyses, ask them to run the following scenarios: run every 30-year period back as far as the data goes.  If it doesn’t include the Great Depression, it is not realistic enough.  Run them forwards, backwards, upside-down forwards, and upside-down backwards.  (For the upside-down scenarios normalize the return levels to the right side up levels.)  The idea here is to use real volatility levels in the analyses, because reality is almost always more volatile than models using normal distributions.  History is meaner, much meaner than models, and will likely be meaner in the future… we just don’t know how it will be meaner.

You will then be surprised at how much caution the models will indicate, and hopefully those who can will save more, run safer asset allocations, and plan to withdraw less over time.  Reality is a lot more stingy than the models of most financial Dr. Feelgoods out there.

One more note: and I know how to model this, but most won’t — in the Great Depression, the returns after 1931 weren’t bad.  Trouble is, few were able to take advantage of them because they had already drawn down on their investments.  The many bankruptcies meant there was a smaller market available to invest in, so the dollar-weighted returns in the Great Depression were lower than the buy-and-hold returns.  They had to be lower, because many people could not hold their investments for the eventual recovery.  Part of that was margin loans, part of it was liquidating assets to help tide over unemployment.

It would be wonky, but simulation models would have to have an uptick in need for withdrawals at the very time that markets are low.  That’s not all that much different than some had to do in the recent financial crisis.  Now, who is willing to throw *that* into financial planning models?

The simple answer is to be more conservative.  Expect less from your investments, and maybe you will get positive surprises.  Better that than being negatively surprised when older, when flexibility is limited.

Too often in debates regarding the recent financial crisis, the event was regarded as a surprise that no one could have anticipated, conveniently forgetting those who pointed out sloppy banking, lending and borrowing practices in advance of the crisis.  There is a need for a well-developed model of how a financial crisis works, so that the wrong cures are not applied to the financial system.

All that said, any correct cure will bring about a predictable response from the banks and other lending institutions.  They will argue that borrower choice is reduced, and that the flow of credit and liquidity to the financial system is also reduced.  That is not a big problem in the boom phase of the financial cycle, because those same measures help to avoid a loss of liquidity and credit availability in the bust phase of the cycle.  Too much liquidity and credit is what fuels eventual financial crises.

To get to a place where we could have a decent model of the state of overall financial credit, we would have to have models that work like this:

  1. The models would have to have both a cash flow and a balance sheet component to them — it’s not enough to look at present measures of creditworthiness only, particularly if loans do not fully amortize debts at the current interest rate.  Regulatory solvency tests should not automatically assume that borrowers will always be able to refinance.
  2. The models should try to go loan-by-loan, and forecast the ability of each loan to service debts.  Where updated financial data is available on borrowers, that should be included.
  3. The models should try to forecast the fair market prices of assets/collateral, off of estimated future lending conditions, so that at the end of the loan, estimates can be made as to whether loans would be refinanced, extended, or default.
  4. As asset prices rise, there has to be a feedback effect into lowered ability to finance new loans, unless purchasing power is increasing as much or more than asset prices.  It should be assumed that if loans are made at lower underwriting standards than a given threshold, there will be increasing levels of default.
  5. A close eye would have to look for situations where if the property were rented out, it would not earn enough to pay for normalized interest, taxes and maintenance.  When asset prices are that high, the system is out of whack, and invites future defaults.  The margin of implied rents over normalized interest, taxes and maintenance would be the key measure, and the regulators would have to have a function that attributes future losses off of the margin of that calculation.
  6. The cash flows from the loans/mortgages would have to feed through the securitization vehicles, if any, and then to the regulated financial institutions, after which, how they would fund their future liabilities would have to be estimated.
  7. The models would have to include the repo markets, because when the prices of collateral get too high, runs on the repo market can happen.  The same applies to portfolio margining agreements for derivatives, futures, and other types of wholesale lending.
  8. There should be scenarios for ordinary recessions.  There should also be some way of increasing the Ds at that time: death, disability, divorce, disaster, dis-employment, etc.  They mysteriously tend to increase in bad economic times.

What a monster.  I’ve worked with stripped-down versions of this that analyze the Commercial Mortgage Backed Securities [CMBS] market, but the demands of a model like this would be considerable, and probably impossible.  Getting the data, scrubbing it, running the cash flows, calculating the asset price functions, implied margin on borrowing, etc., would be pretty tough for angels to do, much less mere men.

Thus if I were watching over the banks, I would probably rely on analyzing:

  • what areas of credit have grown the quickest.
  • where have collateral prices risen the fastest.
  • where are underwriting standards declining.
  • what assets are being financed that do not fully amortize, including all repo markets, margin agreements, etc.

The one semi-practical thing i would strip out of this model would be for regulators to score loans using a model like point 5 suggests.  Even that would be tough, but even getting that approximately right could highlight lending institutions that are taking undue chances with underwriting.

On a slightly different note, I would be skeptical of models that don’t try to at least mimic the approach of a cash flow based model with some adjustments for market-like pricing of collateral and loans.  The degree of financing long assets with short liabilities is the key aspect of how financial crises develop.  If models don’t reflect that, they aren’t realistic, and somehow, I expect that non-realistic models of lending risk will eventually be the rule, because it helps financial institutions make loans in the short run.  After all, it is virtually impossible to fight loosening financial standards piece-by-piece, because the changes seem immaterial, and everyone favors a boom in the short-run.  So it goes.