One of my favorite topics to write about is portfolio management.  That’s because I love my methods for managing equities and bonds.  The methods work, but they aren’t a lot of work.  So, I enjoyed writing my piece last night, Earnings Estimates as a Control Mechanism, Flawed as they are.  And I got two good comments that I would like to develop here.  Here’s the first comment:

Actually, David, I think you have left out the more pressing issue with earnings estimates.

The system, such as it is, has evolved as a collaboration between the companies and analysts to promulgate estimates that are deliberately LOWER than is realistic. Both parties know that stock prices do well when they beat estimates, and it is a lot easier to set the bar really low than to actually outperform realistic expectations. I think many small investors don’t realize how the analysts are linked at the hip to the companies they supposedly cover objectively—when the stocks do well, the analysts do well!

This of course is the data shows that 60-70% of companies beat estimates every quarter, even in lousy years, and why you see stocks almost always beat the bottom line estimates even when they fall short of revenue estimates.

Just another way in which the integrity of the markets is in an utter shambles.

I appreciate what you have to say, but it is not something that I did not consider.  I omitted it for reasons of brevity, and I will explain why here.  If management team lowballs earnings estimates, they raise their forward P/E, which is a drag on their stock price.  There is no free lunch here; stock prices converge on the market’s view of future earnings power.  A management team can set their estimate of future earnings wherever they like.  A high estimate may goose stock prices in the short run, and low estimates may cause stock prices to fall in the short run.  But in the intermediate term, actual earnings will mean more to stock prices than any games played with earnings estimates.  Managements that cheat eventually get punished.

Here is the second comment:

A comment that reinforces the caveats on forward earnings: Lombard Odier has shown that there is NO correlation between forward P/E and actual returns over the following 12 months (

And a question. All measures like the growth in tangible book value per share become considerably more complicated to evaluate when a company grows via a series of mergers. In theory one can do the analysis on each tributary. In practice, getting to know the peculiarities of the accounting in each company involved becomes very time consuming. I wonder how you approach such a case?

On the forward earnings piece, that may apply to the market as a whole but that may not work with individual stocks.

On your question: yes, when we are dealing with M&A the calculations become more complex.  Using the measure of tangible book value per share penalizes acquisitive companies, unless they can buy companies for less than their tangible book value per share.  There are other issues, in that one must give companies credit for spinoffs and such.  I covered that my piece Cram and Jam.  The main question that investors should be asking is: are management teams growing net worth per share for investors on a fair market value basis?

Many do not do that.  Instead, they choose a shortcut.  The most common shortcut is maximizing operating earnings per share.  That measure does not take to account the losses that occur from one-time events and chicanery that comes from buying back stock at prices that are too high.

One more note: I usually avoid companies that do a lot of acquisitions relative to their size, because they tend to underperform.

Final comment

I appreciate all the blogs that quoted my piece yesterday, or linked to it.  But there is a misunderstanding.  Though I am not crazy about sell side earnings estimates, I still see them as necessary.  Why?  We need them to allow us to evaluate progress of the company quarter by quarter.  To use a gambling term, earnings estimates are “the line.”

We could argue that we don’t need to evaluate companies quarter to quarter, and I’m fine with that.  Let’s be like Buffett and say that we would be happy if the stock market were closed most of the time.  I could live with that, but most players the stock market could not.  So, if we’re going to allow the market to be open every day, then we need a control function to allow us to estimate the change in value of a corporation when its earnings are released.

Earnings estimates are a necessary evil.  Please remember that as the earnings season begins.

Why does the stock market pay so much attention to earnings estimates?  Don’t earnings estimates embody the worst type of analysis of stocks on Wall Street?

There is some truth to the thought above.  After all, earnings estimates eliminate all one-time charges.  Now, that makes sense in the short run, but not in the long run.  In the short run we want to estimate the growth in value of the business on a continuing basis.  Thus, we eliminate one-time events.  In the long run we must see how a management team has grown the total value of the Corporation.  To do that, we must factor in all of the one-time events as well as the regular earnings in order to see how they have managed Corporation over time.  Would that one-time events were really one-time events.  And, would that one-time events averaged out to zero.  But truth, one-time events are on average highly negative.  And so, companies with a lot of one-time events typically have lousy earnings quality, and deserve a lower price earnings multiple as a result.

So if there is that much trouble with how we measure earnings as far as earnings estimates go, why do we use earnings estimates?  Most of the value of a Corporation on a going concern basis stems from the future earnings of the company.  Investors want to have an estimate of forward earnings so that they can gauge whether the company is growing at an appropriate rate.

Now, it wouldn’t matter if the system were set up by third-party sell side analysts, by buyside analysts, by companies themselves, or by a combination thereof.  The thing is investors are forward-looking, and they want a forward-looking estimate to allow them to estimate whether the companies are doing well with their current earnings or not.

So long as the earnings estimates are relied on a fair measure of likely future earnings of the company, they become an influence on the current price stock.  For example:

  • If earnings estimates rise rapidly, so will stock prices.
  • If actual earnings comes in above estimates the stock price will have one-time rise.
  • And vice versa for when estimates fall , and when actual earnings are less than the estimate.

Now if earnings estimates were done right, together with growth estimates, by angels did not men, they would serve as cornerstones for estimating the value of corporations.  But our ability to see the future even collectively is poor.  Many things happen that we do not expect, whether from the government or the central bank or wars, you name it.

But even with all those flaws, earnings estimates provided useful function in being a feedback mechanism so that the market knows how to react in general, when earnings are released.

New Problem

But when beating earnings estimates become the be all and end all of the corporate management, we run into trouble.  Knowing that the estimate drives the stock price, makes some corporations fuddle the accounting.  They adjust revenue recognition, they differ recognition of expenses, enter into useless mergers and acquisitions, etc. Most accounting chicanery problems would not exist if beating the earnings estimates was not so important.

So what do we as investors do?  We look at the release of actual earnings with skepticism.  We carefully consider the adjustment of net earnings to operating earnings and asked whether the adjustments are truly reasonable or not.  We also don’t give full credibility to earnings estimates as if they were a sure thing.  Further, we review revenue recognition policies, and all other means to easily adjust operating earnings so we are not deceived by corporate managements.

And, if I can be so radical, we begin ignoring earnings and focus on growth tangible book value per share.  We look at growth cash flow per share net of maintenance capital expenditure.  We do all we can estimate free cash flow, and yet, take a step back and ask how the free cash flow is being used.

Free cash flow is not valuable if it’s being used to buy back stock at a high multiple.  It’s not valuable if it’s being used to do a scale acquisition.  Both of these are forms of dilution to common shareholders.

The key question is this: is the management building the net worth per share of the company?  That’s a lot harder question asking if the current earnings beat the estimate, but if this were easy, they would’ve brought someone else in to do it, not you or me.

PS – I leave aside the issue of intangibles here.  Usually intangibles are worthless.  But some are quite valuable, like the name Coca-Cola, or distribution network that is not easily replicated, or research and development is unique to the Corporation has not yet developed into a product.  All that said, for an intangible to have value, it must produce additional cash flow in the cash flow statement under operations, that do not reflect in the earnings statement.

Dragon NaturallySpeaking, Version 11

I’ve played around with voice-recognition software over the years.  Seven years ago, I tried hard to make Dragon NaturallySpeaking work for me.  Despite extensive training, I could not get it to work for me.

After reading a review which I have since lost track of, I decided to buy a copy of Dragon NaturallySpeaking version 11.  I figured, why not take a chance on it being an effective bit of software, given that the review said the software was vastly improved over version 10.  Plus, I found a copy at my local Walmart for 50 bucks; the deal that I do not think you’ll be able to get easily, because after looking on Walmart website, they certainly do not offer that version of the software, and certainly not for 50 bucks.

It’s been interesting to experiment with this software.  I’m only moderate as typing speed goes.  The software seems to have an accuracy level for me after two weeks of roughly 98%.  The initial training session lasted about 10 minutes.  Since that time, I have trained specific phrases that are unique to me about five times.  Each time I did the training why would utter the phrase after the training, it worked.  I was able to dictate an essay for publication on my blog on the evening that I installed the software.  The training worked that well.

When I speak to the computer, I utter phrases not words.  I can talk, and my speech is not stilted.  The software does better when it hears phrases.

During the installation of the software, it asked to look through the files on my PC, and scanned them to see how I write.  I suspect that allows the software to make educated guesses as to what I really want to see on page.  All I can say is that it certainly seems to do a good job.

In making corrections, a menu pops up with the most likely corrections.  Typically I have found that the correct option for correction is on that list, 90% of the time, and you simply utter the command “choose three.”  It also allows you the option to train new phrases, and spell words out, in order to get new vocabulary into the database of the software.

I have kept my hands in my pockets for the creation of this piece.  If there are any errors here is because I did not see the error and issue a voice command to correct it.  With that, I will close by saying that I really like this software, and intend to use it intensively for writing my essays.  I think it cuts the amount of time that it takes to write my essays by about 30 to 40%.

PS – one more note, this version of Dragon NaturallySpeaking contains a quality headset with a microphone.


It’s not perfect.  Sometimes making corrections purely by voice can take minutes and the aggravating.  I find that using a combination of voice hand control is optimal.

Who would benefit from this software:

I think almost anyone can benefit from the software, unless they are a really fast typist.  Beyond that, anyone who has physical handicaps could benefit dramatically from this software.  If you can speak, and master a few voice commands, you can use this software and type.  It can be used for issuing commands in other software, but I have not done that because I can do that more quickly using my hands.

If you want to, you can buy it here: Dragon NaturallySpeaking Home, Version 11.

Full disclosure: I bought a copy of the software with my own money.

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.

One side benefit of deciding to start up Aleph Investments, LLC, is that it is forcing me to write out articles on my rules.  When I was writing for, I wrote a number of articles about my eight rules, but I only wrote about four out of the eight rules.

Before I write about rule number three this evening, I would like to bring you up to date on what I am doing with Aleph Investments, LLC.  This past week I incorporated the business, and in this coming week.  I will be registering as an investment advisor.  I will be managing equity money, on both a long only and hedged basis.  I have yet to choose a custodian and clearing broker, but I am working on this.  Given the state that I am domiciled in, Maryland, there may be delays but I suspect I’ll be up and running by late November or early December.


Let me give you a little history of how the eight rules came to be.  In 2000, I had an e-mail discussion with Kenneth Fisher.  I explained to him what I had been doing with small-cap value, and how I had done well with it in the 90s.  He told me to forget everything that I’ve learned, especially the CFA syllabus, and look for the things that I can do better than anyone else.  We exchanged about five or so e-mails; I appreciate the time he spent on me.

So I sat back and thought about what investments had worked best for me in the past.  I noticed that when I got the call right on cyclical industries, the results were spectacular.  I also noticed that I lost most when investing in companies that didn’t have good balance sheets, no matter how “cheap” they were in terms of valuation.

I came to the conclusion that size and value/growth were not the major determinants of my investing success.  Instead, industry selection played a large role in what went right and wrong with my investment decisions.  So, I decided to formalize that.  I would rotate industries with a value bias.  But that would have other impacts on how I invested.  One of those impacts is rule number three.

I formalized the first seven of the rules in 2002, when the strategy was two years old and seemingly performing quite well.  I began doing what rule number eight states sometime in 2004, and reluctantly added it to the seven rules sometime in 2006.

With that, on to rule number three:

Stick with higher quality companies for a given industry.

There are three simple reasons for why rule number three works:

  • First, companies with lower debt levels within a given industry tend to be more profitable than companies with higher debt levels that industry, contrary to what the Modigliani-Miller theorems state.
  • Second, many investors, both retail and professional, have a bias toward what we might call “lottery ticket stocks.”  Many people swing for the fences in the stocks that they buy and accept high risks in order to achieve a high return.  On average, this strategy does not work.  In general, buying high beta, high volatility stocks is a recipe for disaster and buying low beta, low volatility stocks tends to earn money better than the market averages.
  • Third, if you are rotating industries, there are two ways to do it.  These two ways are not mutually exclusive, you can have part of your portfolio in one strategy and part of your portfolio in the other.  Method one is to look for trends that are clearly going on, but that the market has not fully discounted.  In this case, one can buy companies with excellent or good balance sheets because the trend will carry you along.  Method two is to look for industries that are sick but not dead.  In that case, you only select companies with excellent balance sheets.  This is how it works: if the industry remains sick, weaker competitors will be destroyed, capacity will exit, and pricing power will return to the survivors.  If the industry’s pricing power suddenly improves, then all of the companies industry will do well.  The one with the excellent balance sheet will outperform the market as a whole.  That the ones with poor balance sheets do even better is not a concern.  The idea is to avoid losing money; don’t take the risk by buying the “lottery ticket stock.”

For what it is worth, this same idea not only works with stocks but it works with bonds as well.  If you read the book Finding Alpha, the author has an extensive discussion on why high quality bonds outperform low-quality bonds over the long haul.  In general, corporate bond investors underestimate the costs of default risk.  BBB bonds do best, followed by AAA bonds, and then other investment grade bonds.  After that, the lower the rating of the bond the worse they do.

The same is true of stocks, which is why it pays to look at where the market is in its liquidity cycle.  In November of 2008 through March of 2009, it made a lot of sense to buy junk bonds, and I did so for my church building fund.  Though I didn’t say it at the time and did not act on it, it was also in hindsight the right time to buy junk stocks.  Oh well, that’s water under the bridge.  I tend not to take the risk of buying junk stocks because I don’t want to lose money.  I did well enough by adding to more cyclical names that had strong balance sheets.

Two notes before I close: first, industries tend to have preferred habitats.  In other words, typically the difference between the company with the best balance sheet the industry and the company with the worst balance sheet industry is not all that great.  Why is that?  If you’re in the same industry, typically you have similar levels of fixed costs versus variable costs, and you face the same levels of variability in sales.  These two factors together will lead an industry to a preferred level of financial leverage.  But even though the difference might not be that much between the company with the best balance sheet and the worst balance sheet within the industry, when pricing power is weak that small difference is significant.

Second, I am a proponent of “good enough” investing.  What I am saying here is that it is very difficult to achieve optimal results, and that if you try too hard to achieve optimal results, it is likely that you will do worse than good enough results.  The demands of perfection kill.  Size your goals to what is humanly possible.  My methods allow me to sleep at night.  My methods allow me to step away from my computer, and spend time analyzing what really might matter.  I can go visit clients and not worry that something is going to blow up on me.

This is not laziness on my part.  It is my view that most investors can do well enough in investing at low to moderate levels of risk.  But at high levels of risk, you have to get too many things right too much of the time in order to succeed.

That’s all for now.  Back next week when I write about rule number four.

Sometimes, I’m behind the curve.  I told myself that I had to get the essay to the Society of Actuaries by today, but now it’s evening time and I still haven’t done it.  So, with your permission, I’m going to write it now.  They asked for the following:

The U.S. Congress recently passed the most sweeping financial reform measure since the Great Depression. The purpose of this legislation is to prevent the risky behavior and decision-making that led to the financial crisis, and to prevent future crises.

  • Does this legislation solve the problems of the past?
  • Are there other significant issues not addressed?
  • Does this legislation cause other concerns?
  • In reflecting on the events of the last two years, is it possible to effectively develop early warning indicators that trigger intervention in advance of a complete collapse of an entire financial system or market?
  • Does it make sense to have a chief risk officer of, say, the United States of America, whose role it would be to manage/mitigate this risk?

Given these five questions as a charge, here is my essay:


At the very heart of financial regulatory reform, an error was made at the very beginning.  As is common in American culture, the assumption was made that our laws and regulations were inadequate, rather than existing laws and regulations were inadequately enforced.  As such, the law that was eventually passed largely strengthened the strictures against the crimes that happened.

But, the same regulators were left in place.  Almost no one was fired for the incompetence demonstrated in not using the regulations that already existed for preventing shoddy loan underwriting.  The SEC had the right to set capital ratios at 12 to 1, but waived that right and allowed the investment banks to be unlimited in their leverage.  The GSEs took far too much credit risk, but who, if anyone, was fired for allowing them to do so?  Or, who was fired for doing so?

The trouble is this: during boom times, it is virtually impossible to get regulators to oppose politicians who are being lobbied by financial services organizations when they are making gobs of money, and it all seems riskless, as the bubble expands.  This is endemic to human nature; it is politically impossible to oppose booms.  I for one wrote extensively about the coming housing bust, but all I received was derision.  I wrote about the blowup coming in subprime residential mortgage bonds, but all I got was a yawn.

So, unless we get a new set of regulators that are willing to be junkyard dogs, I don’t care what laws we put in place.  Laws are only as good as those that are willing to enforce them.

Problems with the Financial Regulatory Reform Bill

Aside from a lack of change in the regulatory apparatus and personnel, my biggest difficulty with financial regulatory reform bill was a lack of change dealing with risk-based liquidity.  We don’t get runs on banks because of the insurance from the FDIC.  But banks often find themselves facing a run if they use a lot of repo funding.  Funding long-term assets short term is a recipe for disaster.  The bill made no effective change with respect to this.

And though there will be higher levels of capital required of banks, which is good, there was not enough thought given toward the riskiness of assets and how much capital they require.  Basel III basically kept the same structure as Basel II, but did not make significant corrections to the differences in risk regarding assets.  Further, they still allow companies to evaluate their own risks, rather than having a conservative and standardized approach for evaluating risk.

And to the degree that Americans believe that the financial regulatory reform bill will it prove the situation, it has given them a false sense of security.  And that could be the worst problem of all.

Creating an Early Warning System

There is great demand for an early warning system that could highlight whether systemic risk is getting too high for the financial economy overall, or whether risk is getting too high for any given subclass of financial risks in the economy.  I am happy to say that creating an early warning system would be easy.  Consider the differences between fresh produce and financial assets:

  • Time horizon — fresh produce is perishable, whereas most risky assets are long-dated, or in the case of equities, have indefinite lives.
  • Ease of creation — New securities can be created easily, but farming takes time and effort.
  • Excess Supply vs. Excess Demand — With a bumper crop, there is excess supply, and the supply is typically high quality.  Now to induce buyers to buy more than they usually do, the price must be low.  With financial assets, demand drives the process.  Collateralized Debt Obligations were profitable to create, and that led to a bid for risky debt instruments.  The same was true for many structured products.  The demand for yield, disregarding safety, created a lot of risky debt and derivatives.
  • Low Supply vs. Low Demand — With a bad crop, there is inadequate supply, and the supply is typically low quality.  Prices are high because of scarcity.  With financial assets, low demand makes the process freeze.  What few deals are getting done are probably good ones.  Same for commercial and residential mortgage lending.  Only the best deals are getting done.

Fresh produce is what it is, a perishable commodity, where quantity and quality are positively correlated, and pricing is negatively correlated.  Financial assets don’t perish rapidly, quantity and quality are negatively correlated, and pricing is often positively correlated to the quantity of assets issued, since the demand for assets varies more than the supply.  Whereas, with fresh produce, the supply varies more than the demand.

When I was a corporate bond manager, one of the first things that I learned was that when issuance is heavy, typically future performance will be bad.  Whenever there is high growth in debt in any sector of the economy, it is usually a sign that a mania is going on.  But it is very hard for a corporate bond manager who is benchmarked to an index to underweight the hot sector.

It is also very hard for a loan underwriter at a bank to stay conservative when he is being pushed for volume growth from his superiors, and most of his competitors are being liberal as anything.  It is hard for anyone in the financial services arena to not follow the prevailing tendency to lower credit standards during a boom.

So if I were to give advice to the new office studying systemic risk, I would give this one very simple bit of advice: look for the sector where debt is growing faster than what is ordinary.  It’s that simple.

If they want to get a little more complex, I would tell them this: when a boom begins, typically the assets in question are fairly valued, and are reasonably financed.  There is also positive cash flow from buying the asset and financing it ordinarily.  But as the boom progresses, it becomes harder to get positive cash flow from buying the asset and financing it, because the asset price has risen.  At this point, a compromise is made.  The buyer of the asset will use more debt and less equity, and/or, he will shorten the terms of the lending, buying a long-term asset, but financing it short-term.

Near the end of the boom, there is no positive short-term cash flow to be found, and the continuing rise in asset prices has momentum.  Some economic players become willing to buy the asset in question at prices so high that they suffer negative cash flow.  They must feed the asset in order to hold it.

It is at that point that bubbles typically pop, because the resources necessary to finance the bubble exceed the cash flows that the assets can generate.  And so I would say to the new office studying systemic risk that they should look for situations where people are relying on capital gains in order to make money.  Anytime an arbitrage goes negative, it is a red flag.

The new financial regulatory reform bill did create an office for analyzing systemic risk, and created a council that supposedly will manage it.  Would it be smart to concentrate the efforts into one leader who will both analyze and control systemic risk?

For better or worse, Americans tend to look for one strong leader who will lead them out of their problems.  Anyone who might be chief risk officer of the United States, would have to have control over the Federal Reserve, which creates most of the systemic risk that we have through its monetary policy, and its lack of leadership in overseeing the banks.  I don’t think it’s politically possible to put a risk manager in charge of the Fed, it might be desirable to do so.  The Federal Reserve always gets what it wants.


I don’t have a lot of hope that the current financial regulatory reform bill will improve matters much.  The same regulators are in place, who did not use the laws that they had available to them to prevent the last crisis.

Systemic risk can be prevented if regulators focus on areas where debt is growing dramatically, and where cash flow from buying and borrowing is diminishing dramatically.  But it is intensely difficult to stand in the way of a boom, and tell everyone “Stop!”  The politics just don’t favor it.

Finally, it would be difficult to create a chief risk officer the United States.  The current politics do not favor creating such a strong office, because it would have to control the Federal Reserve.

Quant Investor's Almanac 2011

This is an odd book.  It runs through the year highlighting the US economy data releases week-by-week in 2011.  It describes ways in which the data releases affect the behavior of markets on average.

There are many interesting articles in the book, but there is little in the way of an overarching theme, or anything that might say, “And here is how it could work for you,” even though quants typically only trot out only their formulas that have weakened, while keeping their potent ideas private.

I found it disappointing.  Hey, but maybe someone else will love it.


This book is useless to the average investor, who does not trade futures.  Personally, I have experienced that trading around data releases is usually a zero-sum game.  Part of that is due to the inaccuracy in the data.

Who would benefit from this book:

If you run a quantitative hedge fund, and aren’t aware of the government data news flow each week, or how it can be used for profit, then this is the book for you.

If you want to learn about some obscure quantitative strategies just for fun, this could be a good book for you.

If you want to, you can buy it here: The Quant Investor’s Almanac 2011: A Roadmap to Investing.

Full disclosure: I was mailed a copy of the book without asking for 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.