Indexing for Dummies: The Evolution of Indexes

Learn how weighting methodology can make a big difference to stock market indexes

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May 07, 2019
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To understand and make the most of index investing, we need knowledge of how the indexes began and evolved over the past 100 years.

That’s the task Russell Wild set for himself in chapter two of “Index Investing for Dummies,” the book he wrote and subsequently published in 2009.

The story begins, of course, with Charles Dow in 1896. He and his partner, Edward Jones, set up a Wall Street news bureau and began publishing the Customer’s Afternoon Letter each day after the market closed. The dozen stocks they covered each day turned into the Dow Jones Industrial Average and their little newsletter turned into The Wall Street Journal.

The Dow was based on the daily valuation of a dozen stocks, all calculated by hand. On May 26, 1896, the average was published for the first time and the sum of one share of each stock divided by 12 was 40.94. That was the first closing average.

What’s important for today’s investor is that this was, and is, a price-weighted index. Wild called the price-weighted approach “archaic” and pointed out a serious flaw. He asked us to imagine an index made up of just two stocks, BAG and BOX. The former has a share price of $10 while BOX has a share price of $50.

This price-weighted index would be 30 (($10 + $50)/2)), where $10 is the price of BAG, $50 is the price of BOX and 2 is the number of stocks in the index. If either BAG or BOX increases by $1 (from $10 to $11 or $50 to $51), the index would rise to 30.5.

That leaves investors in the dark. Is the increase from 30 to 30.5 the result of BAG going up 10% (from $10 to $11) or the result of BOX going up 2% (from $50 to $51)? A price-weighted index doesn’t provide much useful information about where the market is going.

Because of that weighting and the small number of stocks included (the number has since risen to 30), as well as the desire to know more and more about the broad market and its many niches, new indexes emerged. Wild wrote, “the Mother of All Indexes has given way to a number of 'children,' many of which are superior in a number of ways.”

Best known among them is the S&P 500, “The Dow’s Undisputed Number-One Son.” It arrived in 1957 and, as the name suggests, is made up of 500 stocks. These are all large-cap stocks, meaning their capitalization is at least $5 billion.

But they are not simply the largest. The Standard & Poor’s organization reported these were big companies that were also “leaders in important industries within the U.S. economy.”

Part of the reason for the popularity of this index is the weighting methodology. It is a market value-weighted index, where “each stock’s weight in the index is proportionate to its market value.” This meant bigger and more valuable companies such as Exxon Mobil (XOM, Financial) and General Electric (GE, Financial) had a larger representation than smaller companies like American Express (AXP, Financial) and Disney (DIS, Financial) in 2009.

The weighting methodology got a modest revamp in 2005, when it became a float-weighted index. As a result, each company’s representation was based on the float (shares that are available for public sale) rather than the total share count. For example, much of Berkshire Hathaway’s (BRK.A, Financial)(BRK.B, Financial) stock is in private hands.

Because of the popularity of the S&P 500, its weightings have become the industry “normal” and it and indexes like it are generally known as traditional indexes.

An explosion of interest in indexing, along with fund and exchange-traded fund companies looking for new products, has produced a profusion of them, covering almost every imaginable grouping of equities and bonds. With them have come other weighting methodologies:

  • Equal-weighted indexes, in which every stock has the same representation, regardless of market cap or other criterion.
  • Fundamental-weighted indexes, where the representation of individual stocks is based on a financial (fundamental analysis) metric such as its growth rate or dividend yield.
  • Actively-managed indexes; Wild wrote, “Talk about an oxymoron!”

In a useful diversion from the main topic, the author also explained the difference between linear charts and logarithmic charts, something that is helpful when viewing charts of indexes.

This is a linear chart of the S&P 500:

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This is a logarithmic chart of the same index over the same period:

133137072.jpg

The linear chart shows absolute value, the change in actual dollar value over time. The logarithmic chart shows the percentage change over time.

Regarding the linear chart, stock prices were lower on average during the early years than they were near the end of the chart. Suppose a stock is worth $10 in 1960; in that case, a 10% increase in one year would be $1. Fifty years later, in 2010 (or 2009 in keeping with the publication date of the book) that same stock might be worth $180 dollars, meaning a 10% increase would be worth $18. A 10% increase in 1960, then, will look much smaller than a 10% increase in 2010.

On the other hand, a logarithmic chart uses relative values and an increase of 10% will look the same wherever it occurs on a chart that covers a lengthy period. Wild made a couple of useful points about the two types:

“Linear charts, in my mind, are fine for making short-term comparisons. Logarithmic charts, I believe, allow for a more accurate view when measuring performance over decades.

Of course, the two kinds of charts are often used and misused, depending on how the creator of the charts hopes to impress you. If I wanted you to invest in my product, for example, I would likely show you a linear chart when talking about return. I would prefer that you see a logarithmic chart when talking about volatility. It all stems from the very same data, but presentation is everything!”

In summary, different indexes use different types of weightings and investors should search out the type that best suits their goals. They should also know how linear and logarithmic charts can unintentionally shape perceptions of performance and volatility.

Disclosure: I do not own shares in any company listed, and do not expect to buy any in the next 72 hours.

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