Blog – Page 71 – Focused Compounding

Geoff Gannon February 27, 2007

20 Questions for John Bethel of Controlled Gree

John Bethel bought his first stock in 1986, and became devoted to value investing that same year after reading Warren Buffett’s “Superinvestors of Graham-and-Doddsville.” He became self-employed in 1994, and began investing all his own money at that time.

John writes Controlled Greed, a blog reporting his adventures as a stock picker. He personally owns every stock recommended on the site. Controlled Greed launched in April 2005; John’s reported stock picks have averaged +36.9% for the life of the blog through 2006. His stock picks averaged +27.5% for the year 2006 (both figures include dividends).

Visit Controlled Greed

1. Are you a value investor?

Yes.

2. What is value investing?

Stated simply, it’s buying a stock that’s trading for less than the underlying value of the company it represents. There may be different ways of measuring this, such as discounts to tangible book value or sum-of-the-parts analysis, among others, but that’s basically what it is.

3. What is your approach to investing?

I want to buy a company that’s undervalued, and that I can see a way or several potential ways for the value to be realized over the long term. Sometimes I get lucky and the stock price rises in several months, but my window upon buying is three to five years.

4. How do you evaluate a stock?

The process of finding a stock to invest in can take days or years. I start by reading, reading, and reading some more. I think you need to love reading generally to be a good value investor. My memory is that Warren Buffett told Charlie Rose on Rose’s PBS show that when he comes to the Berkshire Hathaway office every day he starts by reading newspapers, business magazines and annual reports. And that reading is the bulk of his job.

I also follow the holdings of some of my favorite investors. One of the things I like about Christopher Browne’s “The Little Book of Value Investing” is that he writes about this very approvingly. If the guys at Tweedy Browne are looking at what Peter Cundill, Mason Hawkins and Marty Whitman hold, and they’re all looking at each other’s portfolios, then it’s something you and I should be doing too. It’s a great way to build a list of candidates for investment.

That said, you shouldn’t buy a stock just because one of your favorite investors owns it. They may have bought it at a much lower price than what it’s going for once it’s reported, for one thing. And you still need to research it to make sure you understand it. Plus, many of the top-notch investors have portfolios with billions of dollars of assets — meaning they can’t take advantage of some smaller bargains.

Reading all this stuff as the years go by builds up a knowledge base. Sometimes I come across a story that makes sense, I research to confirm it, and make the stock purchase. Other times, it takes longer.

An example is …

Geoff Gannon January 3, 2007

On Old Posts and a New Year

I started this blog on Christmas Eve 2005 with this post. So, the blog is now just over one year old heading into 2007.

In the weeks ahead, I’ll review some of the posts of the past year as well as the performance of the twenty or so stocks discussed on this blog during 2006.

Different people started reading this blog at different times; so, I’ll use the start of 2007 as an opportunity to collect and organize past posts in a way that makes sense to relatively new readers.

Personal Favorites

I guess I should start by presenting my personal favorites from 2006 (in no particular order):

On Confidence

On Inflexible Enterprises

On Maintenance Cap-Ex and “The Pleasant Surprise”

On Formulaic Investing

On Value Investing

On Conviction and the Value Gap

On the Physical Effects Fallacy

On Technical Analysis

On Some Lessons from Buffett’s Annual Letter

On Paying a Fair Price

In Defense of Extraordinary Claims

Normalized P/E Ratios

Recently, I’ve written a lot of posts on normalized P/E ratios as part of a little study on valuations conceived as an attempt to offer some idea of what kind of long-term returns investors can expect from the stock market:

On 15-Year Normalized P/E Ratios for the Dow

On Normalized P/E Ratios and the Election Cycle

On Normalized P/E Ratios and the Election Cycle (Again)

On Normalized P/E Effects Over Time

On Calculating Normalized P/E Ratios

On the Difference Between Actual Earnings and Normalized Earnings

On the Dow’s Normalized Earnings Yields for 1935-2006

In Defense of Extraordinary Claims

On Normalized P/E Ratios Over Six Decades

Company Specific Posts

I spent much of the year writing about individual stocks. These are simply posts in which I discuss a specific company at length. You’ll need to actually read the posts to see what I thought about the stock at that time. Also, remember that some of these stocks are now priced very differently. Please use the date of the post to determine what the price was when the post was written. Here is a collection of my company specific “analysis” type posts (again, in no particular order):

An Analysis of Blyth (BTH)

An Analysis of Energizer Holdings (ENR)

An Analysis of Lexmark International (LXK)

An Analysis of Journal Communications (JRN)

An Analysis of the Journal Register Company (JRC)

An Analysis of Nintendo (NTDOY)

An Analysis of Overstock.com (OSTK)

An Analysis of Pacific Sunwear (PSUN)

An Analysis of Cascade Bancorp (CACB)

An Analysis of Fifth Third Bancorp (FITB)

An Analysis of TCF Financial Corporation (TCB)

An Analysis of Valley National Bancorp (VLY)

An Analysis of Wells Fargo & Company (WFC)

I now have a different view of some of these stocks. For the most part, this is the result of changes in the share price. Obviously, if the share price increased dramatically since I discussed a stock, that stock is less attractive than when I wrote the post. I’ll discuss a few of these situations in the next week or so.…

Geoff Gannon January 1, 2007

On Normalized P/E Ratios Over Six Decades

After my last post, Bill Rempel (among others) inquired about the difference in normalized P/E ratios over different decades. He felt a standard applied across 70+ years might not be particularly useful today, because so much has changed (increased participation in equity markets, different monetary policies, etc.) As a result, it might be that while “relatively cheap” is better than “relatively expensive” within each time period, it is inappropriate to compare years from dissimilar decades as if the same standards applied.

I agree. So, over the next two posts, I’ll try to give you an idea of what the compound point growth in the Dow looked like following the low normalized P/E years and high normalized P/E years within each decade. In other words, I’ll look at low normalized P/E years and high normalized P/E years relative to other years in the same decade.

In this post, I’ll simply show you the results of two different comparisons across decades.

The first comparison consists of a group of the five lowest normalized P/E years from each decade vs. the five highest normalized P/E years from each decade. The second comparison consists of a group of the three lowest normalized P/E years from each decade vs. the three highest normalized P/E years from each decade.

Although this is still a comparison across many decades (for this post, I’m only using 1940-1999, because I want to use only “complete” decades), it should give you some idea of whether the normalized P/E effect is simply a result of a few years in just one or two particular decades, or whether the effect tends to hold up over many different decades.

In my next post, I will go a step further, and actually break down the results decade by decade.

The Least You Need to Know

If you can’t be bothered to read yet another post on normalized P/E ratios (I’ve written quite a few lately), here’s the least you need to know:

1. The five lowest normalized P/E years from each decade from the 1940s through the 1990s saw higher compound point growth in the Dow over the subsequent 1, 3, 5, 10, 15, 20, 25, and 30 years than the group of the five highest normalized P/E years from each decade.

2. The three lowest normalized P/E years from each decade from the 1940s through the 1990s saw higher compound point growth in the Dow over the subsequent 1, 3, 5, 10, 15, 20, 25, and 30 years than the group of the three highest normalized P/E years from each decade.

Obviously, there’s a lot more nuance to the results than is suggested by the above two statements; but, the most important point to take away from this post is simply that the combined low normalized P/E group (drawing equally from all decades from the 1940s through the 1990s) beat its high normalized P/E counterpart over all the holding periods I measured.

Remember, these are the combined groups. This post doesn’t address the …

Geoff Gannon December 29, 2006

In Defense of Extraordinary Claims

About two weeks ago in a post entitled “We Have Some Bearish Bloggers Out There“, Bill Rempel wrote, “Personally, I’m in the ‘extraordinary claims require extraordinary proof’ camp.” I’d like to think I am too, because Bill is right – extraordinary claims do require extraordinary proof.

So, before making any extraordinary claims about future long-term market returns (i.e., predicting future returns that differ substantially from historical returns), I’d like to spend this post laying out the case for why current circumstances are extraordinary. After all, extraordinary times call for extraordinary claims.

Essentially, this is a post about why the present is unlike the past and what that means for the future.

In a previous post, I wrote:

Stocks are not inherently attractive; they have often been attractive, because they have often been cheap.

Unless they internalize this fact, investors risk assuming that historical returns that existed under special circumstances can continue to serve as a useful frame of reference, even when these special circumstances no longer exist.

Later in this post, I will discuss the possibility of a “paradigm shift” (i.e., a change in basic assumptions within the theory of investment) that began in 1995. The only other period in the 20th century which saw similar upheaval in investment thinking was the 1920s.

Common Stocks as Long Term Investments

That theoretical crisis (and the higher valuations that followed it) has often been partly attributed to a thin volume published in 1924 by Edgar Lawrence Smith. The book was called “Common Stocks as Long Term Investments” and it was based on a study of 56 years of market data (1866 – 1922).

Smith found that stocks had consistently outperformed bonds over the long run. Neither the data in support of this conclusion nor the logical explanation for this outperformance (public companies retain earnings and these retained earnings lead to compound growth) was wrong.

However, a few years after Smith’s book was published, the special circumstances of the past disappeared as stocks (which had historically had higher yields than bonds) saw their prices surge and their yields plunge. Soon, stocks had lower yields than bonds – part of the reason for their past outperformance (the initial yield advantage) was gone and the margin of safety which a diversified group of stocks had offered over bonds narrowed considerably.

Simply put, circumstances changed. John Maynard Keynes saw this possibility when he reviewed Smith’s book in 1925:

“It is dangerous…to apply to the future inductive arguments based on past experience, unless one can distinguish the broad reasons why past experience was what it was.”

That has been the objective of this little study from the outset. In this post, I will focus on how the circumstances of the present differ from the circumstances of the past.

I will also endeavor to demonstrate that historical returns were the result of special circumstances, which (logically) need not apply now or in the future. The historical data suggests these circumstances may yet …

Geoff Gannon December 27, 2006

On the Dow’s Normalized Earnings Yields for 1935-2006

Before tackling the subject of what kind of returns investors can expect from the stock market over their lifetime (and what a “fair” value for the Dow might be) we need to put today’s valuations in historical perspective.

To do this, I will first provide a graph of the Dow’s 15-year normalized P/E ratio for each year from 1935-2006. For information on how these “normalized” numbers were calculated, please see my previous post “On Calculating Normalized P/E Ratios.”

I consider this graph to be something of a conceptual crutch. Everyone cites P/E ratios – even I do, because it’s one of the best known measures in investing. Regardless of the audience you’re writing for, you can count on them understanding the P/E ratio.

However, presenting P/E ratios is a bit misleading, because I don’t really think in terms of P/E ratios – I think in terms of earnings yields. You should too.

The earnings yield is a much easier number to work with. It facilitates comparisons with other possible investments, simplifies the process of estimating the expected rate of return over various holding periods, and just generally makes life a whole lot easier.

The earnings yield is simply the inverse (i.e., reciprocal) of the P/E ratio. Simply put, it’s “e” over “p”. For example, a stock with a price-to-earnings ratio of 12.5 has an earnings yield of 8%.

Here is a graph of the Dow’s 15-year normalized earnings yield for each year from 1935-2006:

Finally, to give you an idea of the role interest rates played during this period, here is a graph showing both the Dow’s normalized earnings yield and AAA corporate bonds yields for each year from 1935-2006:

Just look over these graphs for now. I’ll discuss the importance of normalized earnings yields in my next post. Without some historical perspective, you may have trouble following that discussion.

On Normalized P/E Ratios and the Election Cycle

On Normalized P/E Ratios and the Election Cycle (Again)

On Normalized P/E Effects Over Time

On Calculating Normalized P/E Ratios

On the Difference Between Actual Earnings and Normalized Earnings

I’ll have many more posts on this project in the days ahead. If you have any questions (or suggestions) about this project, please feel free to comment to this post – or, simply send me an email.…

Geoff Gannon December 26, 2006

On the Difference Between Actual Earnings and Normalized Earnings

Yesterday, I concluded my post “On Calculating Normalized P/E Ratios” with this graph of the percentage difference between the Dow’s actual earnings and its 15-year normalized earnings for each year from 1935-2005:

I also wrote:

The difference between actual earnings and normalized (or “expected”) earnings is one of the most fascinating statistics in this little study.

To better understand this statistic we need to look at its distribution over the 71 years in this study.

First, let’s look at a graph of the difference between the Dow’s actual earnings and its 15-year normalized earnings for each of the last seventy-one years. But, this time, instead of presenting the data in chronological order, I will simply plot the data in ascending order by difference between actual and normalized earnings:

Based on this graph, you would probably guess that the Dow’s actual earnings have been higher than its normalized earnings about half the time and lower than its normalized earnings about half the time.

That’s quite right. From 1935-2005, the difference between the Dow’s actual earnings and its normalized earnings was positive in 36 years and negative in 35 years.

Distribution of the Data

From 1935-2005, the percentage difference between the Dow’s actual earnings and its 15-year normalized earnings ranged from (62.12%) to 65.14%. The average (mean) difference between actual and normalized earnings was 0.44%. The median difference was 0.09%.

According to the “empirical rule”, in a normal (bell-shaped) distribution, about 68% of the values will be within one standard deviation of the mean, about 95% of the values will be within two standard deviations of the mean, and about 99.7% of the values will be within 3 standard deviations of the mean.

In our little study, 49 of 71 values (69.01%) are within one standard deviation of the mean, 67 of 71 values (94.37%) are within two standard deviations of the mean, and 71 of 71 values (100%) are within three standard deviations of the mean. No value is more than 2.5 standard deviations from the mean. In fact, the greatest distance between a value and the mean is 2.26 standard deviations.

Of the 49 values within one standard deviation, 24 are positive and 25 are negative. Of the 67 values within two standard deviations, 34 are positive and 33 are negative.

Frequency of Various Differences

I can quickly give you some sense of how common large and small differences between the Dow’s actual earnings and its 15-year normalized earnings were from 1935-2005.

Remember, negative numbers mean actual earnings fell below normalized earnings; positive numbers mean actual earnings exceeded normalized earnings.

(71.24%) – (56.90%): 2 of 71 years or 2.82% of the time

(56.90%) – (42.57%): 2 of 71 years or 2.82% of the time

(42.57%) – (28.23%): 6 of 71 years or 8.45% of the time

(28.23%) – (13.90%): 13 of 71 years or 18.31% of the time

(13.90%) – 0.44%: 13 of 71 years or 18.31% of the time

0.44% – 14.78%: 15 of 71 years or …

Geoff Gannon December 25, 2006

On Calculating Normalized P/E Ratios

So far, I’ve referenced normalized P/E ratios in four of my posts: “On 15-Year Normalized P/E Ratios for the Dow“, “On Normalized P/E Ratios and the Election Cycle“, “On Normalized P/E Ratios and the Election Cycle (Again)“, and “On Normalized P/E Effects Over Time“.

However, I’ve yet to explain how I calculated these normalized P/E ratios. Obviously, I took the Dow’s average price for the year and divided by a normalized earnings number. But, how did I come up with a normalized earnings number – in other words, what exactly is the normalization process?

The Normalization Process

The normalization process is actually quite simple and straightforward. First, you need to decide upon a reasonable long-term growth rate; otherwise, you won’t have a “trend” to use for comparisons between actual and “expected” earnings. Essentially, “normalized earnings” are just “expected earnings” based on a long-term trend rather than short-term considerations.

For the Dow, a reasonable long-term growth rate would be about 6%. Many different approaches (logical and empirical) will bring you to a similar conclusion. Of course, we could argue forever about what the “right” long-term growth rate assumption is.

That’s because there is no right long-term growth rate. To the extent that future circumstances differ from past circumstances, there may be deviations from this trend. But, for the most part, it is not unreasonable to use an earnings growth rate of 6% per annum when normalizing the Dow’s earnings.

Once you’ve decided upon an appropriate earnings growth rate, you simply take one plus your assumed growth rate and raise it to a power equal to the distance between the current year and the year you are adjusting. This number is the adjustment factor.

If you were calculating a 15-year normalized P/E ratio, you would use the following fifteen “adjustment factors”: 1.06, 1.12, 1.19, 1.26, 1.34, 1.42, 1.50, 1.59, 1.69, 1.79, 1.90, 2.01, 2.13, 2.26, and 2.40.

You start by multiplying the first adjustment factor (1.06) by the most recent year’s earnings. Then, you multiply the second adjustment factor by the second most recent year’s earnings and so on.

Finally, you add up your adjusted earnings (i.e., the products of the operations you just performed) and you divide by the number of years used in your normalization process. When calculating a 15-year normalized P/E ratio, you would divide the sum of your adjusted earnings by 15. It’s really that simple.

For instance, if you were calculating normalized earnings for 1995, you would multiply 1994’s EPS by 1.06, 1993’s by 1.12, 1992’s by 1.19, 1991’s by 1.26 and so on.

Please note that I am not suggesting you ever use this normalization process on an individual stock. In fact, I think that would be a rather ridiculous approach that would generally prove inferior to a careful consideration of the known facts regarding that particular enterprise and its future prospects.

I am, however, suggesting that when applied to a diversified group of very large American businesses …

Geoff Gannon December 23, 2006

On Some of My Favorite Sites

It’s the end of the year. A lot of bloggers try to do something special at this time – make a prediction, summarize the past year, look back, look ahead, etc. I am planning something special for you this weekend.

But, for now, I don’t have anything of my own to share. Rather, I’d like to share the fruits of other people’s labor.

So, I now present some great sites I don’t mention enough (and you probably don’t read enough):

Bill Rempel, a.ka. No DooDahs

I haven’t done an official count, but I think it’s safe to say the blogger who has given me the most material to work with this year was Bill Rempel. His blog is quite different from my own, but his posts always leave me with something to think about. Most recently, I wrote a post “On Gold and Rome” after reading Bill’s post entitled “Not Bullish On Gold“. Several of my best posts were written after reading something Bill wrote. If you haven’t checked out his blog yet, I encourage you to do so now.

By the way, you can see Bill’s responses to the questions posed by Ticker Sense in their Financial Blogger Outlook. Click the image of a table to see Bill’s views on housing, gold, the dollar, bonds, etc.

Fat Pitch Financials

George of Fat Pitch Financials is a value investor and (in many ways) a disciple of Warren Buffett. He looks for “fat pitches” whether they are spin-offs, arbitrage opportunities, or simply great businesses. He also started Value Investing News, a great place to browse some of the best recent articles and posts in the world of value investing.

Value Blog Review

As you probably know, Steven Rosales contributes to this site (in fact, he writes most of our book reviews). He also has his own site where you can find plenty of material that doesn’t appear here. He reviews books, blogs, and online resources of interest to new investors. He’s also started discussing a few of his early trades. This is a great site for new investors to check out. You’ll feel like a fellow traveler setting off on a journey into the world of investing together.

GuruFocus

This great resource tracks about thirty investing “gurus” – people like Warren Buffett, Bill Miller, Marty Whitman, Seth Klarman, and Bruce Berkowitz. I love how easy this site is to browse. There are other sites that track some of these gurus. But, this one is by far the best. I can’t recommend it highly enough. Don’t wait until the New Year, bookmark this site today.

24/7 Wall St.

This is a site you want to check once a day – everyday. Make it a kind of ritual. There’s often something interesting here and they keep the material coming constantly. You can’t live on posts like mine alone, you need a balanced diet and 24/7 Wall St. is just the kind of blogging buffet (for once …

Geoff Gannon December 21, 2006

On Normalized P/E Effects Over Time

In a previous post, I explained why I chose to present the performance of high and low 15-year normalized P/E years by measuring the compound point growth in the Dow over the subsequent fifteen years:

“I thought if long-term performance was as closely tied to “earnings power” as I thought it ought to be, then fifteen years of past earnings data and fifteen years of future share price growth should be enough to detect this relationship…I gave no thought to the possibility that any normalized P/E effect would be discernible over much shorter time periods.”

Well, I should have given that possibility some serious thought, because the normalized P/E effect is discernible over much shorter periods of time.

In fact, the normalized P/E effect is discernible in a way I did not expect to find – and may even have subconsciously preferred not to find.

I write about long-term investing on this blog, because I think about long-term investing and I want others to think about it too. As a result, I really don’t want to present findings from my little normalized P/E study that suggest there is a short-term P/E effect. More than anything, I really don’t want to present findings that suggest the normalized P/E effect is ever more pronounced over a shorter period of time than a longer period of time.

That last sentence requires some explanation. I will need to (reluctantly) employ a physics analogy. I say “reluctantly”, because I’ve (not so subtly) hinted that economists (and their science) suffer from a certain degree of physics envy, as well as an unhealthy attachment to precisely quantifiable figures. Nevertheless, I think this physics analogy will work, because everyone knows enough physics to know what I’m talking about.

The Weighing Force

Conceptually, I thought of the normalized P/E effect as evidence of a perpetual, pervasive, propensity that I’ll call “the weighing force” (for Ben Graham). Knowing what we know about markets, their participants, and the aims of those participants, we should expect markets to often appear efficient, simply because there is a natural tendency for price and value to converge.

I use the term “natural” quite loosely here, because we’re dealing with a complex, human phenomenon. Still, it seems appropriate to consider this tendency for price and value to converge to be a natural consequence of value-seeking market participants.

This is especially true, because some market participants are capable of extracting value outside the market by purchasing stock to gain influence or complete control of a business and then milking that business for cash, selling corporate assets, or integrating the entire business into their own operations.

For evidence of this “outside” influence on the stock market, consider Marty Whitman’s Third Avenue Value Fund, which makes purchases with the expectation that value will be extracted from many of the fund’s holdings without the fund actually selling shares in the open market.

Simply put, if you create a market for productive assets (like pieces of businesses) the weighing force is …