Let’s start with a known fact about the stock market. It is random. Burton Malkiel was one of the first to document this fact in his book, “A Random Walk Down Wall Street.” There is no order or predictability about markets. The stock market processes billions of bits of information every day that result in nearly $500 billion of trades each and every day. This information translates to price. Investors decide whether they believe the price is too low or too high and react accordingly.
There are basically two kinds of investors: those who process the information and regularly make buy-and-sell decisions based on their interpretation of the data (called “speculators”) and those who ignore the daily movement of price and information. These are called “long-term investors.” Sometimes, they are referred to as “buy and hold.”
Which way is the best way to invest in the markets?
Many observers and commentators will make an argument for both strategies. But what does the science show? Is there any evidence to suggest one investment strategy is better than another?
According to Eugene Fama, recipient of the 2013 Nobel Prize in Economic Sciences, the market is both random and efficient. He received his prize for showing that the market processes information so fast, it is impossible for an investor to do anything but anticipate news. The best guesser wins. This is not science. What is science? Science is the systematic analysis of a series of events and/or behavior of both the physical and natural world order through observation and experimentation. The key to science is hypothesis testing and probabilities. Can the observed results be duplicated or predicted with any degree of accuracy? The important conclusion from any scientific analysis is the probability and predictability of the results. What level of confidence can you have in these conclusions? The higher the confidence level, the more certainty can be applied to the observations.
The most important questions a financial advisor can ask are why, what and how? Why are you investing? How much risk are you willing to take, and what is your long-term expected outcome? For most investors, the answer is simple: They want either wealth building or income. They want to accumulate capital during their accumulation years so that they can harvest an acceptable and predictable income in their nonworking years. A common thread among investors is their desire to be economically free from worry and fear of loss. They would rather have a “return of their money than a return on their money.” Another adage is “Never risk a dollar you cannot afford to lose.” Risk is volatility. It refers to the amount of fluctuation you can expect around the average return most of the time.
This brings us to one of the most important questions you can ask a client: “Do you know how much risk you are buying?” Most investors never look at their portfolio from a risk perspective. They establish a risk tolerance and then expect their investment team to set the portfolio allocation based on the amount of risk they are willing to endure. But this is much different than understanding the amount risk you are buying.
Most people don’t even think about whether they are buying risk. But the truth is, there is risk in everything, from putting your money under a mattress to buying speculative, high-tech stocks with no earnings. Risk or volatility is measured by a mathematical function called “standard deviation.” It is derived from the number of events observed. The fewer events, the less reliable the measure. Assume you invested in a particular stock or fund that went up 10 percent and then went down 20 percent over a two-year period. This was a 30 percent swing in two years. It would be logical to conclude that this was a very volatile stock. But if you stepped back and looked at the performance of the stock over 20 years (assuming it had been around that long), saw the range of returns, and measured the amount of ups and downs, you might find that, most of the time, the variation was 10 percent instead of 30 percent. If this were the case, you might draw a different conclusion about its volatility. In other words, if the average return was 10 percent, most of the time stock price varied between +20 percent and -0 percent. The negative 20 percent was an outlier in the data. It did not happen most of the time.
This is why Fama says that you can derive no knowledge from returns over a three- to five-year period. It is all noise. He says you have to have a long-term view and trust your investment process. Warren Buffett, who many consider to be the most successful investor of our age, says you don’t have to have a genius IQ or a deep understanding of business to be a successful investor. You only need two things: first, an intellectual framework for investing based on research, historical data and analysis. The second thing you must have is an emotional guardrail, a way to protect your framework from being corrupted or destroyed when the market gets jumpy and chaotic. Since this happens frequently, being protected from your inner fears is one of the most important things advisors can do for their clients.
The intellectual framework is much easier to attain than establishing emotion guardrails to protect your process. The adrenalin and endorphins in the brain are virtually uncontrollable. The fear of loss has been measured at twice the intensity as the exhilaration of gain. More important, studies have shown that most people have no ability to control their fear when the markets get volatile. So what is the solution? As an advisor, you have to establish a strong trust bond with your clients and help them understand the framework you are using. You have to demonstrate that their faith in you during a down market is justified.
Go back in time to 2008. This was a worldwide crash. There was no part of the market that was safe. U.S. markets, global markets and emerging markets were all in panic mode. Even the fixed markets were in turmoil. Investors lost 40 to 50 percent of their portfolio value in a short period of time. How did investors respond? Some sold and some held on to their portfolio. The ones who sold had to accept their losses, and, in many cases, they never regained the courage to go back into the market. As a result, their loss became real, and they never recovered from the trauma.
Other investors, those with some form of emotion guardrails around their portfolios, hung on and eventually recovered their loss when the market rebounded. For some sooner than others, but eventually the market turned around and began hitting new highs again. This is the history of markets. It is not easy to hold on during a rocky market. But those who do are most often rewarded with new highs once the volatility settles back to the norm. The buy-and-hold investor believes what is observable. Markets go up and markets go down. But, over time, markets have always rebounded and gone up. Will this be true in the future? Who knows? But it is what the evidence has shown over the last 90 years.
We do not have to go back 90 years to find evidence of market randomness. As of 2017, there were 4,760 U.S.-based mutual funds. Of these, 1,523 were fixed income. In addition, there were 1,054 international funds in 2,183 U.S.-based equity funds. For the five years prior to 2017, there were 2,867 equity funds in the U.S. During the five-year period dating back to 2012, 82 percent of these funds still remained, and of this total, 26 percent performed at or above the benchmark for their category.
Looking back 10 years, we find there were 3,229 funds in the U.S. market. Of these, only 58 percent survived the 10-year period, and within this beginning cohort of funds, only 27 percent matched or exceeded their benchmark returns. The data is even worse after 15 years, where 2,828 funds began the period, with only 51 percent surviving and 14 percent matching or beating their benchmark.
What about top funds, the top quartile? Looking at the 10-year period from 2006 to 2017, only 26 percent of this group remained in the top quartile at the end of three years. The question is, Do you want to try to outwit the market? Or is it better to be the market?
Buffett said you need an intellectual framework. How do you build an intellectual framework? There are many theories on investing. It is estimated that there are over 300 observable factors identified and measured by finance scientists, trying to explain market behavior. These researchers are seeking to find consistent, repeatable factors that can predict future market performance. Remember, extensive research shows that markets are random, and the information moves so fast, it is impossible to accurately predict any outcomes.
Before we look at the reclassification of these factors, let’s establish a baseline or benchmark to use to compare outcomes. In the market as a whole, based on the Center for Research in Security Prices (CRSP), $1 grew from 1926 through 2017 to $5,977. This is a 9.9 percent compounded return, also called the “internal rate of return.” For comparison, the S&P 500, the largest 500 stocks in the database, grew to $7,399. This was a 10.4 percent IRR. We could call the S&P 500 a submarket of the total market. The S&P is also thought of as a submarket to the total market.
If this submarket did 50 basis points better over 90 years, then are there other submarkets that have outperformed the total market? Since 1990, there have been five Nobel Prizes awarded in this field of research for work identifying market forces, which might explain, to some degree, the market performance spectrum. Harry Markowitz, Merton Miller and William Sharpe were the first three to be recognized in 1990 for their work in this field. They were followed by Robert Merton (1997) and Eugene Fama (2013). In addition, other researchers have identified factors that they think explain market behavior and provide guidelines to advisors on how to best build an investment portfolio that would be sustainable over long time frames.
In the final analysis, many have concluded that there are only four unique factors that are independent and can explain performance. Research shows these four can be measured scientifically and produce repeatable results with a high degree of certainty. These four factors are based on:
- Size of the company as measured by capitalization
- Book-to-market ratios
- Profitability
- The stock-bond paradigm
Each of these has significant scientific evidence to conclude that these factors contribute significantly to explaining market performance.
The first factor identified dates back to 1950. This factor is often referred to as “modern portfolio theory.” The research identified that stock returns were higher than bond returns over long time periods. The “size effect” was identified in 1981. The research showed small returns over long time periods exceeded large cap. In 1991, research identified what is referred to as the “value effect.” This factor is determined by examining the book-to-market ratio for every corporation in the database. Then, in 2012, enough evidence was presented to show there is a “profitability effect” that can be identified and managed. These four factors comprise the investment categories needed to build a stable, consistent portfolio over long time frames.
What does the evidence show? Let’s first look at size. Using data from CRSP, we can calculate the capitalization for each of the 32,000 stocks. By taking the price of the stock, at any point in time, and multiplying it by the number of outstanding shares of stock, the product is the FMV at that time. These outcomes can be force-ranked from the highest to the lowest. Stocks can be categorized by their fair market value, recognizing that the market value changes day by day. By determining the median, the midpoint of the cohort of stocks, the upper half can be classified as large cap (those above the median) and as small cap for those stocks that are below the median. These two distinct groups can be analyzed over time to see how they perform compared to the market as a whole and each other.
The data shows that small cap outperforms large cap 57 percent of the time, over the last 90 years, when measuring rolling 12-month returns. There are 1,069 rolling 12-month periods during this time frame (90 x 12 = 1,080 less the 11 uncompleted periods). This also means that 43 percent of the time, large cap has outperformed small cap. If we expand the analysis to five-year rolling periods, the percentage of time that small cap beats large cap increases to 64 percent. Over the rolling 10-year period, small beats large 74 percent of the time, and looking at the 15-year rolling periods, the percentage is 82 percent of the time. Clearly, as the period of time extends, there is an observable increase in the consistency of small-cap companies outperforming large-cap companies.
The same thing can be done by determining the book-to-market ratio. This ratio tells us the relationship between the net worth (or liquidation value) of a company compared to its capitalization value. The larger the ratio, the greater the asset value is when compared to the fair market value. Again, by force-ranking this ratio for the large-cap stocks and the small-cap stocks, the data can be reclassified into four subgroups, which include large-cap stocks with a ratio less than the median (called “growth”) and large-cap stocks with a ratio greater than the median (called “value”). The same can be done for small-cap stocks — small growth and small value. The question is, How did these perform compared to each other?
Research shows that there has been a considerable difference between value and growth companies. If we use the same method for determining the gain value produces over growth, we find that 61 percent of the time value beats growth using the one-year rolling average method. When we look at the five-year rolling data, value beats growth 77 percent of the time. Over 10 years, it increases to 88 percent, and over any 15-year rolling period, value beats growth 97 percent of the time. This data shows that value is a major factor when explaining how the market performs. So even though the market is random and totally unpredictable, there is a large amount of certainty in the relationship between value and growth.
The final factor is profitability. Once again, the data is stark. Highly profitable companies have a distinct performance advantage over low-profit companies. Although this makes sense, how do you find these companies and integrate this knowledge into your portfolios? The one-year rolling data shows that highly profitable companies outperform low-profitable companies 71 percent of the time. If we look at the five-year data, this percentage jumps to 92 percent, while the 10-year and 15-year data both show that high-profitable companies will outperform low-profitable companies 100 percent of the time.
How have these different categories performed since 1926? The large-cap growth classification has seen $1 growth to $3,076. The small-cap growth classification, over the same period, grew to $2,257. Compare this to the large-cap value class, which grew to $16,169. This leaves the small-cap value category. A dollar invested in the small-cap value asset class grew to an astounding $84,307. What is important to remember is that each has a unique risk factor. The small-cap market is about 50 percent more volatile than the large market. This may explain why most managers put so little of the portfolio in the small market.
Relying on the research, these four classifications, based on the four factors, provide the basis for building a portfolio. The question becomes, how do you allocate your capital? How do you determine the percentage of the portfolio that should go into each of these classifications?
Harry Markowitz first developed the Efficient Frontier in the 1950s. Conceptually, the Efficient Frontier is the optimum allocation based on volatility and return. Each asset class has a historic risk and return for a specified period of time. Combining these is a complex mathematical iteration. For instance, we can build a model using five different classifications: large-cap growth and value; small-cap growth and value; plus an aggregate class that covers all whole market. Using 5 percent increments in each class, there are 3,125 combinations. But only one is the optimum. Which one? The algorithm creates a dispersion chart that shows the best choice. The advisor can then rebalance the portfolio frequently to make sure the allocation stays on the Efficient Frontier.
The final question is, using the historical database, how would the Efficient Frontier model perform compared to the market? The market has the same characteristics — a historical return and a measurable volatility. If we use the Efficient Frontier to match the volatility, over the same time frame, using the entire market, what is the result? Our research shows that the total market, with no attempt to capture the anomaly premiums, grew to $5,977. With the Efficient Frontier model, using the same assumptions, same stocks, same risk, same time period, $1 grew to $25,123. This increase can only be attributed to the allocation within the classifications, based on the anomaly research.
What is the advisor’s role in the process? Whether you use a Turnkey Asset Management Program (TAMP), or you do it yourself, there are three component parts required to produce a portfolio. You need a chef, who may or may not delegate the actual activity to another third party. You need proper ingredients. And you need a great recipe — the intellectual framework Buffett refers to. If you have these working properly, you can create a great result for your clients.
There is a lot written about the future of money managers as the industry gathers artificial intelligence programs and builds robo-advisors. The one thing AI will never be able to replace is the personal interaction and the need to help calm clients during the inevitable downturns.
If you plan to build a successful money management practice, you need important strategies. First, you need the intellectual framework. I have shown you one today, based on significant research and scientific testing. There are others. You need to find the one that fits your philosophy. The second element is the one that requires significant education and hand-holding. You are the guardrails that keep the clients from destroying their framework. To do this, you need to understand not only how you build your portfolios, but also why. You need to be able to tell a story that will calm their nerves when the market gets whacky. Remember, the single most important thing clients want from their advisors is peace of mind. They don’t want to know, but they want to make sure you know.
Hopefully, this paper will help you find your way in this exciting new frontier.
