Indices

Have you heard the story of the Baltimore Stockbroker?

It goes… one day, you receive a letter in the mail from a stockbroker, personally addressed to you, predicting that next month a certain stock will go down. You keep an eye on that stock, and it does indeed go down. You receive another personal letter from the stockbroker, predicting that another stock will go up next month. Curious now, you watch that stock over the next month and lo and behold, it does indeed go up! And month after month for ten months, this same stockbroker sends you letters accurately predicting the ups and downs of stocks. At the end, he asks you to invest a big amount.

It seems like a pretty safe bet, doesn’t it? You have personally seen how good this stockbroker is at predicting the market. But what you don’t know is that the Baltimore Stockbroker has a tricky scheme. At the beginning, when you received that first letter, it was one of 10,240 personal letters, half of which predicted that that certain stock would go up, and the other half predicted it would go down. The half that the stockbroker mailed saying (incorrectly) that the stock would go up never heard from him again. With the remaining 5,120 correspondents, the stockbroker contacted them again and told 2,560 that the next stock would go up and the other half that it would go down. And so-on and so-on until you had just so happened to be one of ten people for whom the stockbroker guessed correctly ten out of ten months. The Baltimore Stockbroker is an old market truism about how easy it is to lie by telling the truth.

I was working with a potential client this week who brought a 27-page financial statement to our meeting. It was divided into more than a dozen different investment areas and each investment category had been compared an index that had been developed to evaluate that particular category. It got me thinking that there are a lot of indices out there. You’re probably familiar with a number of popular examples, such as the S&P 500, the Russell 2000, the DOW, or the Wilshire 5000, but the total number of indices will shock you: 3,730,000[1]. In 2018 alone, 438,000 indices were created. In fact, an entire market has popped up just to make indices. Indices are important for comparing your returns (as we’ve discussed in the past, returns are the most important part of a portfolio) to the market, but many money managers underperform. According to studies for which Eugene Fama² shared the Nobel Prize in 2013, more than 93% of financial advisers underperform the market over the longer-term. It seems to me that they invent a new index to disguise that fact. Thus there are 3.73 million indexes.

Most Financial Advisers are taught to use Modern Portfolio Theory to put together financial plans for their clients. Modern Portfolio Theory is based on Harry Markowitz’s 1963 postulation that stocks move based on two factors: the market (which he called Beta) and the company (which he called Alpha). He developed a formula:
Price Change = Alpha + Beta x a Factor

Modern Portfolio Theory was an attempt at a scientific theory (like Newton’s Laws of Motion) for economics. It concluded, based on Markowitz’s research, that if you want higher returns, you must take greater risk (which I disagree with). Then, in 1986, Brinson, Hood, and Beebower studied asset allocation in 91 large pension plans and found that 85-90% of the risk was due to Beta Factor – the market. That implied that only 10-15% of a stock’s movement could be attributed to the qualities of the company.[2] An idea developed that a portfolio should be created from the top-down; there is, this theory suggests, no need to look at individual companies, and investors ought to look at the stock market itself. Modern Portfolio Theory has since been widely disseminated and taught to many university students who go on to act as financial advisers.

There is another approach to stock picking: the bottoms-up approach, which I subscribe to. In 1997, William Jahnke questioned Brinson, Hood, and Beebower’s study, and carried out his own study using the same data and a different approach. Jahnke found that the Beta Factor (the market) was only 15% of the risk, while the dominate factor was the qualities of the company itself. From a practical standpoint, my bottoms-up approach to stock picking involves looking at 30-40 stocks a month, digging down into the financials of eight or nine, and on one or two I get as far as the 10-Ks and 10-Qs. I am looking at how the company is structured, at the risk in the industry, at their innovations and competition, and I ultimately only make one or two trades each year. I am looking for companies that have a stock price which is lower than its worth. That’s the process and means of investing I refer to when I say I take a bottoms-up approach.

To relate this all back to indices, why do money managers use all these different indices? Even if they are investing in obscure areas like small Chinese companies or African debt derivatives, why shouldn’t they compare to one index like the S&P 500 TR? Isn’t the idea to keep score? In a football game it is the score at the end of the game that counts. Yes, getting more first downs than the other team will usually mean a win, but it is the score that decides the outcome. When I see all those different areas of investment it feels like an equivalent of first downs, passes completed, and other game statistics. But it is the final result that should count.

I was shocked to see there were 3.73 million indices. I use the S&P 500TR to compare each and every one of my client stock accounts. The goal is to deliver returns in excess of the S&P 500 TR over the longer-term. Shouldn’t that be the goal of each manager? It seems to me that using all those esoteric indices is like the Baltimore stock broker. It is factual, but it obscures the how well the manager or financial advisor is really doing.

1 Authers, John. “Number of stock indices at 3m dwarfs tally of quoted companies.” The Financial Times, January 22, 2018. https://www.ft.com/content/9ad80998-fed5-11e7-9650-9c0ad2d7c5b5. Accessed August 30, 2019.

2 Fama, Eugene and Kenneth French. “Luck versus Skill in the Cross-Section of Mutual Fund Returns.” Journal of Finance, October 2010.

3 Jahnke, William W. “The Asset Allocation Hoax.” Semanticscholar.org, February 1997. https://pdfs.semanticscholar.org/b1ee/b50fb691270bee6c823fc24360080eefe045.pdf Accessed August 30, 2019.