Commentary: Know what you hold

Updated: Oct 13

The idea of "knowing what you own" seems like it ought to be a basic threshold for an investor to know about their portfolio. However, we'll explore how not all investments are necessarily what they may appear, and how Basepoint swims against many industry trends when it comes to portfolio management.

4 dogs playing poker with 3 of them showing their cards to the table
“If you don’t study any companies, you have the same success buying stocks as you do in a poker game if you bet without looking at your cards.” -Peter Lynch

Dear Family, Friends, and Clients,

Knowing what you hold seems like a minimum threshold for success in any endeavor. The example of making bets in poker without looking at your cards seems like hyperbole; but a careful look at the average portfolio will show exactly this tendency. In fact, academic research is touting this methodology as the only way to guarantee success. “Why look at individual companies, when you can buy a portfolio of great American businesses with very low cost?”, they rhetorically retort, “You are guaranteed average results without doing any work”. This discussion will attempt to explain in detail why Basepoint swims against the indexing tide, when just buying a portfolio of index funds would be cheaper and easier.

In physics, scale is an important factor in determining whether a system is deterministic (Newton) or probabilistic (Einstein). In determinism, the outcome is known with certainty, in advance; the path of a planet is not capricious. In probabilistic systems, the outcome is stochastic, and a certain level of randomness is present. The combined mass of an object or system determines whether the physics of Newton dominate, or the physics of Einstein. Newton even famously quipped that he could “calculate the motion of heavenly bodies, but not the madness of people.” Our own sun contains 10^57 hydrogen atoms; this is an unfathomable number of individual observations. With this many individual particles clinging together, the results are all but certain, and Newton’s First Law confirms this. It is statistically impossible for a star to simply disappear because all 10^57 atoms would have to conspire simultaneously.

In contrast to large, deterministic systems, Don Lincoln at Fermilab Today wrote: “At the quantum scale, space is a writhing, frantic, ever-changing foam, with particles popping into existence and disappearing in the wink of an eye. This is not just a theoretical idea—it's confirmed.” At the very small scale, nothing is certain. Particles can simply vanish without notice or apparent cause, and atoms can be entangled and send signals to each other faster than the speed of light. It is a terrifying world that lacks certainty, and although there is probably a perfectly reasonable explanation for this behavior, we do not yet understand the underlying mechanism.

So where does that leave those of us clinging to a giant, wet rock hurtling through space around a massive nuclear furnace? Somewhere in the middle. Our scale is not quite large enough to be completely deterministic, and not small enough to be completely random. We have many observations to utilize in decision making, but not quite enough to guarantee certainty. The problem lies in trying to tie the physics of Newton to the actions of people; even Newton lamented the impossibility. Using statistical techniques designed to give reliable results in a system of billions of observations falls short when applied to thousands of data points- especially when friction, in the form of exogenous surprises, is also present. At the human scale neither certainty nor chaos prevail. We must integrate the disciplines of both scales to get reliable results over many decisions.

When a subatomic particle snaps out of existence, it seems completely random to us. There is possibly some sort of unobservable factor missing from our perspective to help us predict when a particle will just cease to exist. It is not quite that random at the level of a company. Usually there are assets, liabilities, revenue, and expenses to help guide us in deciding the probable trajectory of the future. That is not to say that seemingly random events do not occur. If Amazon decides to enter your business, your stock price may plummet and your sales may dry up, but this type of occurrence is uncommon enough that diversification can help to mitigate the impact of this type of random tribulation. It is also possible for us to miss certain fundamental signals that were clear to others. Diversification is insurance against ignorance and bad luck.

So why not just buy every company and transition to the physics of Newton? The simple matter of fact is that determinism does not guarantee success, and inertia does not apply at our scale, especially not in investing. A body in motion does not necessarily stay in motion in the presence of randomness. Over-diversification simply reduces the exposure to risk of returns that deviate from average. There is no law that states that average results will not be significantly negative, especially when the average price of a security is high in relation to the income it produces. If you buy 505 individual companies at 42 times their annual earnings, it will be difficult to achieve higher than a 2.38% annual return without significant economic expansion since you own exposure to the entire economy. Your results are tied to economic growth, interest rates, and investor psychology.

A further danger inherent in modern day indexing stems from the way indexes are weighted. Every index must have a scheme to allocate capital among the various components. The three most common weighting methodologies are: capitalization-weighted, price-weighted, and equal-weighted.

The composition of capitalization-weighted indexes is based on the total size of each company. Share price is multiplied by total shares outstanding, which equals market capitalization, and this determines each company’s proportional weight in the index. They are structured this way to make it more realistic for all investors to be able to purchase the entire index. Sometimes capitalization-weighted indexes are also float-adjusted, which means that only the shares available to the general public are included in the weighting. For instance, Warren Buffett owns a large percentage of Berkshire Hathaway, so his shares are removed when calculating Berkshire’s proportion of the index.

Price-weighted indexes are composed based on the share price of each holding. The Dow Jones Industrial Average is a well-known price-weighted index. This type of index is much easier to calculate, and before computers it was less labor intensive to just take the average of all the prices (with adjustment factors). The main problem with a price-weighted index is that it punishes stocks that split, and rewards stocks that do not. If a $300 stock splits 3 for 1, the price-weighting of the index will decrease by 2/3. In addition, a price-weighted index pays no attention to the size of a company, so in theory, a company with 1 share at $100,000,000 would become a very large percentage of the index and be inaccessible to investors looking to replicate the index.

An equal-weighted index simply allocates a consistent dollar amount to each stock. An equal-weighted index with 10 holdings at a tracking value of $1,000 each would be a level of $10,000. This type of index over-weights small companies in relation to capitalization-weighted indexes, and it has higher trading costs due to equalizing the positions on a frequent basis. In addition, it is not always possible to buy fractional shares, so replicating the index at smaller levels is very difficult.

Intuition would lead one to believe that the Standard and Poor’s 500 is comprised of 500 stocks in equal weights. This is not the case. The S&P 500 is float-adjusted, and capitalization-weighted, and is comprised of 505 stocks. This means that larger companies are a larger percentage of the index, and that as companies grow larger, they become an ever-larger percentage of the index. This is a built-in momentum mechanism that places higher emphasis on companies as they grow. An unfortunate side effect of this is that during a market mania the most overvalued companies become a larger and larger percentage of your portfolio. This is greatly rewarding as the market screams higher, but equally punishing when these trends reverse. Currently, Apple is the largest component in the S&P 500 at 5.99% of the index. Conversely, News Corp is the smallest position at .008523%. As Apple increases in value it becomes a bigger percentage of the index. Currently, the top 10 positions out of 505 are 27% of the index, and the top 20 positions in the index are 37% of the exposure.

S&P 500 - Top 20 market cap holdings as of 5/4/2021
S&P 500 - Top 20 market cap holdings as of 5/4/2021

When we evaluate a portfolio of securities, we think in terms of how much value we are getting for each dollar invested, and how much each dollar invested earns. We consider a portfolio a collection of cash flows that can be translated into an asset price, and appreciation comes from the annual earnings the firms produce. We believe it is a mistake to purchase streams of cash flow with the intention of hoping someone else will pay us more for them next week. Furthermore, we try to purchase them at a discount to what they are worth, and only when we are receiving an adequate return. We evaluate how much of the earnings are being paid out in dividends because the retention of earnings is what causes our companies to grow over time. A savings account paying 5% will compound at this rate indefinitely. As our companies retain earnings, they reinvest them in the business, and hopefully produce at least a dollar of asset value for every dollar they retain. While this is not always the case, it is why having “able and competent management” is so important, and why having a business with a “durable competitive advantage” is so important, these factors protect the integrity of our retained earnings.

If we look at the top 20 holdings of the S&P 500 in proportion to their weighting in the index, and assume we had a million-dollar portfolio holding these positions, which is 37% of the portfolio of an index investor, we find the following data:

$1million portfolio with S&P 500 weighting
* Fair value calculated by Morningstar

Discount of S&P 500 top 20 holdings 5/4/21