Photo Credit: Jimmie

Photo Credit: Jimmie

Every now and then, a piece of good news gets announced, and then something puzzling happens.  Example: the GDP report comes out stronger than expected, and the stock market falls.  People scratch their heads and say, “Huh?”

A friend of mine who I haven’t heard from in a while, Howard Simons, astutely would comment something to the effect of: “The stock market is not a futures contract on GDP.”  This much is true, but why is it true?  How can the market go down on good economic news?

Some of us as investors use a concept called a discounted cash flow model.  The price of a given asset is equal to the expected cash flows it will generate in the future, with each future cash flow discounted to reflect to reflect the time value of money and the riskiness of that cash flow.

Think of it this way: if the GDP report comes out strong, we can likely expect corporate profits to be better, so the expected cash flows from equities in the future should be better.  But if the stock market prices fall, it means the discount rates have risen more than the expected cash flows have risen.

Here’s a conceptual problem, then: We have estimates of the expected cash flows, at least going a few years out but no one anywhere publishes the discount rates for the cash flows — how can this be a useful concept?

Refer back to a piece I wrote earlier this week.  Discount rates reflecting the cost of capital reflect the alternative sources and uses for free cash.  When the GDP report came out, not only did come get optimistic about corporate profits, but perhaps realized:

  • More firms are going to want to raise capital to invest for growth, or
  • The Fed is going to have to tighten policy sooner than we thought.  Look at bond prices falling and yields rising.

Even if things are looking better for profits for existing firms, opportunities away from existing firms may improve even more, and attract capital away from existing firms.  Remember how stock prices slumped for bricks-and-mortar companies during the tech bubble?  Don’t worry, most people don’t.  But as those prices slumped, value was building in those companies.  No one saw it then, because they were dazzled by the short-term performance of the tech and dot-com stocks.

The cost of capital was exceptionally low for the dot-com stocks 1998-early 2000, and relatively high for the fuddy-duddy companies.  The economy was doing well.  Why no lift for all stocks?  Because incremental dollars available for finance were flowing to the dot-com companies until it became obvious that little to no cash would ever flow back from them to investors.

Afterward, even as the market fell hard, many fuddy-duddy stocks didn’t do so badly.  2000-2002 was a good period for value investing as people recognized how well the companies generated profits and cash flow.  The cost of capital normalized, and many dot-coms could no longer get financing at any price.

Another Example

Sometimes people get puzzled or annoyed when in the midst of a recession, the stock market rises.  They might think: “Why should the stock market rise?  Doesn’t everyone know that business conditions are lousy?”

Well, yes, conditions may be lousy, but what’s the alternative for investors for stocks?  Bond yields may be falling, and inflation nonexistent, making money market fund yields microscopic… the relative advantage from a financing standpoint has swung to stocks, and the prices rise.

I can give more examples, and maybe this should be a series:

  • The Fed tightens policy and bonds rally. (Rare, but sometimes…)
  • The Fed loosens policy, and bonds fall. (also…)
  • The rating agencies downgrade the bonds, and they rally.
  • The earnings report comes out lower than last year, and the stock rallies.
  • Etc.

But perhaps the first important practical takeaway is this: there will always be seemingly anomalous behavior in the markets.  Why?  Markets are composed of people, that’s why.  We’re not always predictable, and we don’t predict better when you examine us as groups.

That doesn’t mean there is no reason for anomalies, but sometimes we have to take a step back and say something as simple as “good economic news means lower stock prices at present.”  Behind that is the implied increase in the cost of capital, but since there is nothing to signal that, you’re not going to hear it on the news that evening:

“In today’s financial news, stock prices fell when the GDP report came out stronger than expected, leading investors to pursue investments in newly-issued bonds, stocks, and private equity.”

So be aware of the tone of the market.  Today, bad news still seems to be good, because it means the Fed leaves interest rates low for high-quality short-term debt for a longer period than previously expected.  Good news may imply that there are other places to attract money away from stocks.

Ideas for this topic are welcome.  Please leave them in the comments.

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Photo Credit: Sepehr Ehsani — Which project is better, project A or project B?

I can’t remember where I ran into it, but I found this article on a blog that I had not run into before on Calculating [the] Cost of Equity for Value Investors.  I think it gets close to the right answer, and I would like to sharpen it here.

My answer to a lot of economic questions is: what’s the alternative?  Many people look at the shiny formulas in investing but don’t ask what they really mean.  (More people just don’t look at the formulas… which has its pluses and minuses.  The math reveals, but it also conceals hidden assumptions.)

After wisely dismissing how to calculate the cost of equity from Modern Portfolio Theory [beta] and the Gordon model, he considers cost of equity based off of return on equity, and begins to get tied up in problems.  Let me try.

The cost of equity is important for a number of reasons:

  • It helps answer the question, “When should a company issue or buy back stock?”
  • It provides a measure for the alternative use of equity capital on competing unlevered projects/investments of equivalent riskiness.

Note the each of the reasons is structured as a series of comparisons.  I’ll use a discounted cash flow [DCF] analysis as an example.  Imagine a simple project requiring an investment of equity capital.  There is a certain cost, and the risk is enough that you can’t borrow money for financing — it must be funded by equity.  There are expected after-tax cash flows from the project that you think are a best estimate of returns.  When would you invest in the project?

I would compare investments versus other similar investments, and look at as many similar projects from a riskiness perspective, and see which investment yielded the best return.  The second place project as returns go is the alternative project for investment by which the winning project is judged, and surprise, the winning project has a positive net present value evaluated at the rate of the alternative project.

(An aside: it just hit me that I am recreating part of the learning process that I went through back when I was a TA at UC-Davis 31 years ago, helping teach Corporate Financial Management [CFM], while taking quadratic programming [QP] course at the same time — I ended up doing my QP paper on using QP to choose investments to maximize returns without explicitly calculating internal rates of return, thus quietly solving a problem that the undergrad CFM textbook said could not be done.  FWIW, which isn’t much.)

Now, I’m waving my hands at what I mean by risk, but to me it is the best estimate of the probability distribution of outcomes, thus giving you estimates of what the likelihood and severity of adverse outcomes could be.  The thing is, in real life we know these figures poorly at best, but the framework is still useful because the investor making the decision needs to choose the project of a class of projects with roughly the same risk profile.  Though my initial example included only equity-financed projects, this could be expanded to consider all projects, where the amount of debt on projects affects their risk, and the tax-affected debt cash flows are a deduction from returns.

The process would remain the same: look at as many similar projects from a riskiness perspective, and see which investment yielded the best return on the equity.  The second place project as returns on the equity go is the alternative project for investment by which the winning project is judged.

Back to Stocks

Where does that leave us as stock investors?  I subscribe to the “pecking order” theory of the cost of capital, which says that firms use the cheapest form(s) of capital to fund their incremental financing needs, which means they should rarely issue equity. The exception would be if they are undertaking a project so large that it would make the company significantly more risky if they were to issue only debt for financing.

We do see companies engaging in buyback activity when they can’t find better uses for slack capital.  In many cases, there are few large projects begging for the attention of management.  Buying back stock earns the earnings yield for the firm.  Managements buying back stock make the statement that there are no more incremental projects of equivalent risk that would have an unlevered return on equity greater than the earnings yield for the firm.

Now maybe shareholders may have a bigger set of investment choices than the firm does, so perhaps dividends could be a better choice for shareholders, but it will have to be a lot better, because dividends are taxable.

In general, we want to see management teams be careful users of equity capital, taking note of its cost for the benefit of shareholders.  Every good management team should have their schedule of possible projects for investment, but always recognize there is the alternative of buying back stock as a last resort.  In that limited sense, the earnings yield is the cost of equity for the firm, unless big profitable projects beckon.

There’s more to say here, but maybe this is a good start.  Thoughts?

Photo Credit: Penn State

Photo Credit: Penn State

There have been a few parties worrying about crises stemming from ETFs, because they make it too easy for people to sell a lot of assets in a crisis.

I think that fear is overblown, but I don’t think it is non-existent, and I would like to use a bond ETF as an example of what could be possible.

Most bonds don’t trade every day.  Only the most liquid bond issues trade every day, and they form the backbone for pricing the bonds that don’t trade.

But how do you price a bond when it doesn’t trade?  It’s complicated, but let me try to explain…

When a less liquid bond actually has a trade, the bond pricing services take note of it.  They calculate the yield spread of the less liquid bond versus similar bonds (similar in industry, rating, maturity, currency, domicile, other features) that are liquid, and compare it to:

  • where that yield spread was in the past
  • where the yield spread is relative to other similar less liquid bonds that have recently traded
  • where models might imply the yield spread should be, given other securities related to it (stock, preferred stock, junior debt, other bonds in the same securitization, etc.)
  • where investment banks that make a market in the bonds are indicating they would buy or sell.

Now consider that the bond pricing services are doing this for all the bonds they cover every day, and in real time when the NAVs are made available for ETFs.  The bond pricing services attempt to create a set of prices for all securities that they cover that is consistent with the market activity in aggregate, adjusting at a reasonable speed to changing market conditions.  It’s complex, but it allows investors to have a reasonable estimate of the value of their bonds.

(Note: the same thing is done with illiquid stocks as a result of the late trading scandal in mutual funds back in the early 2000s for setting the NAV of mutual funds —  less liquid stocks have the same problem in a lesser way than bonds.)

The technical name for this is matrix pricing, which is a bit of a misnomer — multifactor pricing would have been a better name.  It works pretty well, but it’s not perfect by any means — as an example, you can’t take the calculated price and trade at that level — it is only indicative of where an uncoerced buyer and seller might trade on a normal day.  It may be a useful guide, though your broker making a market may disagree, which is part of the art of understanding value in the bond markets.

The Possible Problem

Now imagine an ETF with a relatively large amount of less liquid bonds in it, and a market environment where yield spreads are relatively tight, as it is now.  In such an environment, even the less liquid bonds may have their yield spreads relatively tight versus their more liquid cousins.  Now imagine that a relatively violent selloff starts in the bond market over credit issues.

If you were a bond manager at such a time, surprised at the move, but thought it would go further, and you wanted to lighten up on some of your positions, would you try to sell your liquid or less liquid bonds first?  Most of the time, you would sell the liquid ones, because it is relatively easy to get the trades done.  If the selloff is bad enough, it will be impossible to sell the less liquid bonds — practically, that market shuts down for a time.

But if there are very few trades of the less liquid bonds, what does the pricing service do?  Initially, it might rely on the old spread relationships, leaving the less liquid bonds with higher prices than they should have.  But with enough time, a few trades will transpire, and then the multifactor models will catch up “all at once” with where the pricing should have been.

For a time, the NAVs would be high relative to where the bonds actually should trade.  The unit creation/liquidiation process might not catch up with it, because the less liquid bonds are difficult to source, and there is often a cash payment in lieu of the less liquid bonds.  That cash payment figure could be too high in my scenario, leading to a rush to liquidate by clever investors sensing an arbitrage opportunity.

Now, would this be a catastrophe for the markets as a whole?  I don’t think so, but some investors could find the NAVs of their bond ETFs move harder than they would expect in a bear market.  That might cause some to sell more aggressively, but remember, for every seller, there is a buyer.  Someone outside the ETF processes with a strong balance sheet will be willing to buy when the price is right, because they typically aren’t forced sellers, even in a crisis.

Practical Advice

If you own bond ETFs, know what you own, and how much of the portfolio is less liquid.  Have a passing familiarity with how the NAV is calculated, and how units get created and liquidated.  Try to have a sense as to how “jumpy” investors are in the asset sub-class you are investing in, to know whether your fellow investors are likely to chase market momentum.  They may cause prices of the ETFs to vary considerably versus NAVs if a large number of them take the same action at the same time.

Know yourself and your limits, and be willing to hold or add when others are panicking, and hold or sell when others are too optimistic.  If you can’t do that, maybe hand it over to a financial advisor who stays calm when markets are not calm.

Till next time…

 

This is the third time I have written this article during this bull market.  Here are the other two times, with dates:

The first time, we had doubled since the bottom.  Second time, up 2.5x.  Now it is a triple since the bottom.  That doesn’t happen often, and this rally is getting increasingly unusual by historic standards.  That said, remember that every time a record gets broken, it shows that the prior maximum was not a limit.  If you think about that, after a bit you know that idea is obvious, but that isn’t the way that many people practically think about extreme statistics.

Let’s look at my table, which is the same as the last two times I published, except for the last line:

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Since the second piece, the gains have come slowly and steadily, though faster than between the first and second pieces.  As I said last time,

In long recoveries, gains first come quickly, then slowly, then near the end they often come quickly again.  Things are coming quickly again now, but who can tell how long it might persist.”

Indeed, and after the first piece, the market did nothing for about 16 months, after which the market started climbing again at a rate of about 1.5% per month for the last 27 months.  Though not as intense as the rally in the mid-’80s, this is now the third longest rally since 1950, and the third largest.  It is also the third most intense for rallies lasting 1000 calendar days or more.  This is a special rally.

 

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And now look at the cumulative gain:

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Does this special rally give us any clues to the future?  Sadly, no.  Or maybe, too much.  Let me spill my thoughts, and you can take them for what they are worth, because I encouraged caution the last two times, and that hasn’t been the winning idea so far.

  1. To top the rally of the ’90s for total size, we would have to see 2700 on the S&P 500.
  2. It is highly unlikely that this rally will top the intensity of that of the ’50s or ’80s.  Gains from here, if any, are likely to be below the 1.7%/month average so far.
  3. For this rally to set a length record, it would have to last until 12/14/16 (what a date).
  4. Record high profit margins should constrain further growth in the S&P 500, but that hasn’t worked so far.  As it is, there are very good reasons for profit margins to be high, because unskilled and semi-skilled labor in the capitalist world is not scarce.
  5. Rallies tend to persist longer when they go at gradual clips of between 1-2%/month.  Still, all of them eventually die.
  6. At present the market is priced to give 5.5%/year returns over the next 10 years.  That figure is roughly the 85th percentile of valuations.  Things are high now, but they have been higher, as in the dot-com bubble.  We are presently higher than the peak in 2007.
  7. On the negative side, it doesn’t look like the market is pricing in any war risk.
  8. On the positive side, I’m having a hard time finding too many industries that have over-borrowed.  Governments and US students show moderate credit risk, as do some industries in the finance and energy sectors.
  9. Finally, the most unusual aspect of this era is how little competition bonds are giving to stocks.  In my opinion, that idea is getting relied on too heavily for a relative value trade.  Instead, what we may find is that if bond yields rise, stocks, particularly dividend paying stocks, will get hit.  By relying on a relative yield judgment for stocks, it places them both subject to the same risks.

I still think that we are on borrowed time, but maybe you need to regard me as a stopped digital clock with a date field, which isn’t even right twice per day.  Historically, if the rally persists, stock prices should only appreciate at a 8-9% annual rate with the bull this old.

That’s all for now.  I’m not hedging my equity portfolio yet, but maybe my mind changes near 2300 on the S&P 500, should we get there.

PS — the title comes from the fact that markets move down twice as fast as they go up, so be ready for when the cycle turns.  The first article in the series focused on that.

Sometime in the next few weeks, I am going to dig into my pre-2003 [pre-RealMoney] files and see if there is anything there to share with readers.  Most of my best stories I have already told in my various series.  The one I will tell tonight I don’t think I have told.

In 1994, we had a problem at Provident Mutual’s Pension Division.  Our main external equity manager was having a very lousy year as value managers that focused on absolute yield were getting taken to the cleaners.  This was after a few years of poor performance — the joke was, given the great performance of the past, “Hey, can you develop the 19-year track record?”  (The last 5 years as a group were horrid, but the previous 14 were great.)

Aside: there aren’t many absolute yield managers in equities today.  Back when dividend yields were higher, and corporate bond yields were higher, both absolute and relative yield managers flourished as interest rates and dividend yields crested in the early 1980s, and the stocks paying high dividends got bid up as interest rates fell, much as the same thing happened to zero coupon and other noncallable long duration bonds.

The process started with a call from a manager of managers who proposed that we start up “multiple manger funds,” where we would be the manager of managers.

This offered several advantages:

  • It offered us an easy out with our long-held failing manager, because we are not firing them, just making them a portion of the assets in the value fund.
  • It would make eliminating them easier in a second step, with less PR damage.
  • It would make us look like we were taking action and control in a new way for our clients. (They loved it.)
  • As it was, we did a good job selecting managers, and the funds performed well.
  • We could negotiate lower fees with the managers,
  • It gave us a great marketing story.
  • Our margins and growth improved.

I was critical to the process, being the only member of the team with investment expertise.  Everyone else was a marketer or the divisional head.  (I take that back, one member of the marketing area was genuinely sharp with investments.)  After we chose the managers, I set the allocations.

Now onto tonight’s topic (what a long intro): At the beginning of our relationship with the manager of managers, they did a traditional holdings-based analysis of how a manager managed assets.  About one year into the process, they introduced returns-based style analysis.

Though the Wikipedia article just cited has a bevy of errors, it will still give you a flavor for what it is.  Let me give my own explanation:

It takes a lot of effort and wisdom to look at quarterly portfolio snapshots and analyze what a manager is doing.  You almost have to be as wise as the manager himself to analyze it, but many fund analysts developed the skill.

But returns-based style analysis offered the holy grail: we can understand what the manager is doing simply by comparing the returns of the manager versus returns on  variety of asset indexes, using constrained multiple regression.

The idea was this: the returns of a manager are equal to his alpha versus a composite index that best fits his performance.  Since we were dealing with long-only managers, the weights on the index components could not be negative.

The practical upshot to the manager of mangers was: “Whoopee!  We can analyze every manager under the sun just by looking at their return patterns.  No more time-consuming work.”

After the first meeting with the manager of managers, I expressed my doubts, and asked for a special meeting with their quants.  A week later, I had a meeting with a few members of their staff, of which one was the quant, a nice lady 10 years my junior, who I felt sorry for.  She started her presentation at a very basic level, and asked “Do you have any questions?”  I asked, “Isn’t this just an quadratic optimization problem where you are choosing weights on the convex hull?”  She paused, and said, “Oh, so you *do* understand this.”  The meeting ended son after that — we agreed on the math, and in math, there is no magic.

But that placed me on the warpath; I genuinely felt the advice we were getting had declined in value.  I wrote a 16-page report to our manager explaining why returns-based style analysis was inferior.

  • There is no way to correctly estimate error bounds, because of nonlinear constraints.  (Note: two years later, I guy came up with an approximate way to do it in an article in the Financial Analysts Journal.  I called him, and we had a great talk.  That said, approximate is approximate, and I haven’t seen any adopt it.)
  • Because many of the indexes are highly correlated with each other, small differences in manager returns make a huge difference in the weight calculated for each index.
  • If a manager is changing investments because he senses a factor like market cap size or valuation is cheap, it will get interpreted as a change in his index, and will not come out as alpha, but as beta.
  • If I don’t believe that the CAPM and MPT are valid, why should I believe this monstrosity?
  • And more… I hope I find my 16-page paper in my files.

After six more months we terminated the manager of managers, and hired a better one.

  • Lower fees
  • Lower fees from managers (they had greater bargaining power)
  • We reduced our fees to clients
  • Better marketing name
  • Holdings based manager analysis

After that, things were much better, and we continued to grow.

My years at Provident Mutual were exceedingly fruitful — this was just one of many areas where my efforts paid off well.

All that said, there is no way to fix returns-based style analysis.  It is a bogus concept and needs to be abandoned.  Those who use it do not grasp the limits of econometrics, and are Sorcerer’s apprentices.

PS — Need I mention that the originator of the idea, Bill Sharpe, is not all that sharp with econometrics?  He’s a bright guy, but it is not his strong suit.

PPS — there are not many actuaries with a background in econometrics.  That is why I have written this.

There are several reasons to avoid illiquidity in investing, and some reasons to embrace it.   Let me go through both:

Embrace Illiquidity

  • You are offered a lot of extra yield for taking on a bond that you can’t easily sell, and where you are convinced that the creditor is impeccable, and there are no sneaky options that you have implicitly sold embedded in the bond to take value away from you.
  • An unusual opportunity arises to invest in a private company that looks a lot better than equivalent public companies and is trading at a bargain valuation with a sound management team.
  • You want income that will last for your lifetime, and so you take some of the money you would otherwise allocate to bonds, and buy a life annuity, giving you some protection against longevity.  (Warning: inflation and credit risks.)
  • In the past, you bought a Variable Annuity with some good-looking guarantees.  The company approaches you to buy out your annuity at a 10-20% premium, or a 20-30% premium if you roll the money into a new variable annuity with guarantees that don’t seem to offer much.  Either way, turn the insurance company down, and hold onto the existing variable annuity.
  • In all of these situations, you have to treat the money as money lost to present uses.  If there is any significant probability that you might need the money over the term of the asset, don’t buy the illiquid asset.

Avoid Illiquidity

  • Often the premium yield on an illiquid bond is too low, or the provisions take value away with some level of probability that is easy to underestimate.  Wall Street does this with structured notes.
  • Why am I the lucky one?  If you are invited to invest in a private company, be skeptical.  Do extra due diligence, because unless you bring something more than money to the table (skills, contacts), the odds increase that they are after you for your money.
  • Often the illiquid asset is more risky than one would suppose.   I am reminded of the times I was approached to buy illiquid assets as the lead researcher for a broker-dealer that I served.
  • Then again, those that owned that broker-dealer put all their assets on the line, and ended up losing it all.  They weren’t young guys with a lot of time to bounce back from the loss.  They saw the opportunity of a lifetime, and rolled the bones.  They lost.
  • We tend to underestimate how much we might need liquidity in the future.  In the mid-2000s people encumbered their future liquidity by buying houses at inflated prices, and using a lot of debt.  When everything has to go right, the odds rise that everything will not go right.
  • And yet, there are two more more reason to avoid illiquidity — commissions, and inability to know what is going on.

Commissions

Illiquid assets offer the purveyor of the assets the ability to pay a significant commission to their salesmen in order to move the product.   And by “illiquid” here, I include all financial instruments that carry a surrender charge.  Do you want to know how much the agent made selling you an insurance product?  On single-premium products, it is usually very close to the difference between the premium you paid, and the cash surrender value the next day.

Financial companies build their margins into their products, and shave off a portion of them to pay salesmen.  This not only applies to insurance products, but also mutual funds with loads, private REITs, etc.  There are many brokers masquerading as financial advisers, who do not have to act strictly in the best interests of the client.  The ability to receive a commission makes them less than neutral in advising, because they can make a lot of money selling commissioned products.  In general, it is good to avoid buying from commissioned salesmen.  Rather, do the research, and if you need such a product, try to buy it directly.

Not Knowing What Is Going On

There are some that try to turn a bug into a feature — in this case, some argue that the illiquid asset has no volatility, while its liquid equivalents are more volatile.  Private REITs are an example here: the asset gets reported at the same price period after period, giving an illusion of stability.  Public REITs bounce around, but they can be tapped for liquidity easily… brokerage commissions are low.  Some private REITs take losses and they come as a negative surprise as you find  large part of your capital missing, and your income reduced.

What I Prefer

In general, I favor liquid investments unless there is a compelling reason to go illiquid.  I have two private equity investments, both of which are doing very well, but most of my net worth is tied up in my equity investing, which has done well.  I like the ability to make changes as time goes along; there is value to being able to look forward, and adjust.

No one knows the future, but having some slack capital available to invest, like Buffett with his “elephant gun,” allows for intelligent investing when liquidity is scarce, and yet you have some.  Many wealthy people run a liquidity “barbell.”  They have a concentrated interest in one company, and balance that out by holding very safe cash equivalents.

So, in closing, avoid illiquidity, unless you don’t need the money, and the reward is very, very high for making that fixed commitment.

FinEconMost of my readers are not going to want to buy this book, because they are not inclined toward math.  But for those that are math-inclined, I would encourage you not to buy the book.  Why?

Well, there are much better books on Econometrics out there, that could teach the subject better.  I can safely say that no Econometrics class would use this book as a text.

Beyond that, the book does not come up with a lot of areas where “this is where you have to be careful in using regression on econometric data.”

I did learn a few things from the chapter on factor analysis, but that is not typically classified as econometrics.

As such, I don’t see any class of people that would benefit from this book.

Quibbles

Already mentioned.

Summary

There is no good audience for this book.  If you still want the book, you can buy it here: The Basics of Financial Econometrics: Tools, Concepts, and Asset Management Applications (Frank J. Fabozzi Series).

Full disclosure: The publisher asked me if I would like a copy and I said yes.

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.

71zM0CNU4QL This is an ambitious book.  It tries to draw together financial statement analysis, value investing, short-selling, technical analysis, market timing, and portfolio management into one slim book of 254 pages.

It spends the most time on financial statement analysis, going over revenue recognition, inventories, and all of the squishier areas of accounting that most industrial companies face.  It will not help you much with financial companies, they are far more complex, and deserve a book all their own.

I was surprised that the book did not suggest common summary measures of accounting quality, such as Normalized Operating Accruals.  It did feature Cash Flow from Operations less Net Income, which is almost as good.

The book focuses on the short side — how do you make money from failure?  The long side suggests maxing out on small cap value stocks, and idea which  I like, but can get overfished at times.

Think of it this way: do you want to run a portfolio that is systematically short company size, long value, short liquidity, long quality, etc?  I helped do that for 4.5 years at a hedge fund, and boy that ride was bumpy.  The market can remain insane longer than you can remain solvent.

But, to the book’s credit, it understands position sizing for short positions, which is momentum following.  Short more of things that fall.  Do not add to shorts when the prices rise.  This is a key insight of the book, and it is a reason why value managers often don’t do well in a long-short context.

My last complaint is that the book does not explain even in broad terms how they balance the various portfolio management ideas.  If you buy this book, you are on your own.  You do not  have a full roadmap to guide you.  If you were going to use this as a main strategy, you would have to fill in a lot of holes.

Now, I’m often critical of turn-the-crank books — follow my rules, and you will make money.  But I am more critical of almost turn-the-crank books — follow my rules, and you still won’t know exactly what to do.

Is this a good book?  Yes.  Read it and you will learn a lot.  Will it help you analyze stocks?  Also yes.  You can make a lot more money by avoiding stocks with a high probability of losing money.  Will it tell you exactly what to do?  No.  That is a strength and a weakness — I’m not sure any book on investing that offers a formula can be exact, and be good.  Investing is an art, not a science.  Then again, science is an art, not a science, but that’s another topic — all the great discoveries come from not following the scientific method.

So if you want to learn, this is a good book.  If you want a foolproof way to make money, sorry, this won’t do it for you, and the same for almost every other investment book.

Quibbles

There are far better books on all of the topics that they cover, and most of them have been reviewed at my blog.  Far better to read books that specialize on a single topic, than one that is a hodgepodge.

Summary

This is a good book, but average investors should not buy it as a formula, because they can’t implement it.  Average investors could benefit from the book, because it gives them a taste of a wide number of investing topics.  Just be aware that you aren’t getting a full dose of anything.  If you still want that, you can buy it here: What’s Behind the Numbers?: A Guide to Exposing Financial Chicanery and Avoiding Huge Losses in Your Portfolio.

Full disclosure: I borrowed this book via Interlibrary Loan.  It is going back tomorrow, and I will not buy a copy to replace it.

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.

Industry Ranks 6_1521_image002

My main industry model is illustrated in the graphic. Green industries are cold. Red industries are hot. If you like to play momentum, look at the red zone, and ask the question, “Where are trends under-discounted?” Price momentum tends to persist, but look for areas where it might be even better in the near term.

If you are a value player, look at the green zone, and ask where trends are over-discounted. Yes, things are bad, but are they all that bad? Perhaps the is room for mean reversion.

My candidates from both categories are in the column labeled “Dig through.”

You might notice that I have no industries from the red zone. That is because the market is so high. I only want to play in cold industries. They won’t get so badly hit in a decline, and they might have some positive surprises.

If you use any of this, choose what you use off of your own trading style. If you trade frequently, stay in the red zone. Trading infrequently, play in the green zone — don’t look for momentum, look for mean reversion. I generally play in the green zone because I hold stocks for 3 years on average.

Whatever you do, be consistent in your methods regarding momentum/mean-reversion, and only change methods if your current method is working well.

Huh? Why change if things are working well? I’m not saying to change if things are working well. I’m saying don’t change if things are working badly. Price momentum and mean-reversion are cyclical, and we tend to make changes at the worst possible moments, just before the pattern changes. Maximum pain drives changes for most people, which is why average investors don’t make much money.

Maximum pleasure when things are going right leaves investors fat, dumb, and happy — no one thinks of changing then. This is why a disciplined approach that forces changes on a portfolio is useful, as I do 3-4 times a year. It forces me to be bloodless and sell stocks with less potential for those with more potential over the next 1-5 years.

I like some technology stocks here, some industrials, some retail stocks, particularly those that are strongly capitalized.

I’m looking for undervalued industries. I’m not saying that there is always a bull market out there, and I will find it for you. But there are places that are relatively better, and I have done relatively well in finding them.

At present, I am trying to be defensive. I don’t have a lot of faith in the market as a whole, so I am biased toward the green zone, looking for mean-reversion, rather than momentum persisting. The red zone is pretty cyclical at present. I will be very happy hanging out in dull stocks for a while.

That said, some dull companies are fetching some pricey valuations these days, particularly those with above average dividends. This is an overbought area of the market, and it is just a matter of time before the flight to relative safety reverses.

The Red Zone has a Lot of Financials; be wary of those. I have been paring back my reinsurers, but I have been adding to P&C insurers. What I find fascinating about the red momentum zone now, is that it is loaded with cyclical companies.

In the green zone, I picked almost all of the industries. If the companies are sufficiently well-capitalized, and the valuation is low, it can still be an rewarding place to do due diligence.

Will cyclical companies continue to do well? Will the economy continue to limp along, or might it be better or worse?

But what would the model suggest?

Ah, there I have something for you, and so long as Value Line does not object, I will provide that for you. I looked for companies in the industries listed, but in the top 5 of 9 balance sheet safety categories, and with returns estimated over 12%/year over the next 3-5 years. The latter category does the value/growth tradeoff automatically. I don’t care if returns come from mean reversion or growth.

But anyway, as a bonus here are the names that are candidates for purchase given this screen. Remember, this is a launching pad for due diligence, not hot names to buy.

I’ve tightened my criteria a little because the number of stocks passing last quarter’s screen was much higher, which was likely an artifact of earnings expectations rolling forward another year.

Anyway, enjoy the list of purchase candidates — I know that I will:

Industry Ranks 6_19997_image002

Full Disclosure: long SYMC

52wk I usually don’t like reviewing books that say, “Follow this formula, and you will make lotsa money.  Thus it was with some hesitance that I requested this book.  I did it partly off of Tweedy, Browne’s study, which is aptly titled, “What Has Worked in Investing.”  For those reading at Amazon, Google “Tweedy Browne What has Worked” for the link.  Stocks that hit new 52-week lows on average are ready to rebound.  So why don’t people buy them?

Are you kidding?  Look at that chart!  Do you really want to catch a falling knife?!  You want to throw good money after bad!?  Why do you want to buy that dog, anyway…

Shhh.  The competition is gone.  There are no friends of failure.  But made some companies get unfairly tarred as losers, when it is simply a good company that made a few mistakes.

That is the idea behind this book.  Analyze companies from which most market players  have fled.  Look for those with  the following characteristics:

  1. They must have a durable competitive advantage.
  2. They must must a strong free cash flow yield.
  3. They must have a return on invested capital that exceeds the cost of that capital.
  4. They must not have too much debt relative to free cash flow.

I Had Troubles Getting to Solla Sollew

But here’s the big problem, and advantage, of the book.  He does not give you the “secret sauce.”  He gives you the principles.  Indeed he can’t give a formula, because many of his criteria don’t admit an easy formula.  You can’t calculate free cash flow from looking at GAAP accounting — you would need to know what portion of capital expenditure is to maintain existing assets, and that is nowhere disclosed.  Typically, when you see free cash flow in screening software, all capital expenditure is deducted from cash flow from operations, producing too conservative of a figure.

Thus we can’t replicate points 2 & 4.  What about 1 & 3?  Companies do not comes with tags saying “Durable Competitive Advantage” and “No Durable Competitive Advantage.”  That is a judgment call.  You could use Morningstar’s Moat Ratings, or Gross Margins as a fraction of assets.  The author does not give explicit guidance.  As to point 3, the main problem is that we don’t know what a company’s cost of capital is.  There are a lot of assumptions lying behind that, and they matter a great deal.

The easiest of his five criteria to calculate is the price vs the 52-week low.  Still, he doesn’t give us a threshold.

So What Good is This Book?!

Unless you are an expert, not much good, unless you simply want to play the 52-week low anomaly.  That said, actionable strategy would be to review the 52-week lows, and analyze companies with low debt and high past profitability that seem to have a franchise that is not easily attacked.  I think the theory is solid.  That said, it does no give a lot of the details, not that most readers would understand it if they did.

This book is good, in that it is realistic.  Though not explicit, it informs you that it is very difficult to choose superior stocks, and it it does not give you a cut-and-dried method.

So If You Can’t Do It Yourself, Then What Is This Book?!

Though the disclosure at the end says otherwise, this book is an advertisement for the author’s method of money management.  In none of his five criteria does he get sharp.  The general principles are correct, but you aren’t given the tools to use them.  That means if you want to use them, you must go through the author.

Verification

They have a website — 52weeklow.com, but it is not laden with data as the book intimates, as of the day that I write this.  That would be worth seeing.

Quibbles

On pages 74-75 he gives a strained view of margin of safety, comparing free cash flow yields to the 10-year Treasury yield.  Margin of safety is more of a balance sheet construct, asking how likely is is that a company will get into financial stress.  What he is actually measuring here is valuation.  What he is doing is not wrong, but it is mislabeled.  Also remember, you can estimate free cash flow, but you never know for sure.

Also, as mentioned before, we have no idea of what his thresholds are and how he actually implements the strategy.

Thus after this article are two attempts to work out the strategy.  What should not be surprising is that there are no companies on both lists.

Summary

This is a good book, but average investors should not buy it, because they can’t implement it.  If you still want that, you can buy it here: The 52-Week Low Formula: A Contrarian Strategy that Lowers Risk, Beats the Market, and Overcomes Human Emotion.

Full disclosure: The PR flack asked me if I wanted the book, and I said “yes.”

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.

Application Attempt One

These were the companies selected — Morningstar Wide Moat, 5% Free Cash Flow Yield, Less than 20% above the 52-week low.

one

And here is the second try: Gross margins as a ratio of Assets over 13%, free cash flow yield over 5%, Long-term debt as a ratio of free cash flow greater than five, less than 20% above the 52-week low.

two

Not one alike on the two lists.  Tells you that his book would be very difficult to implement.  *I* don’t know how I would implement it.