Investments
Cutting through the fog - written by Ryan Sobel
Why should you care about how to invest? How it works. Many just want to turn the key and fire up the engine of wealth. After all, there are already thousands out there for hire who say they already know. Every day we are bombarded with conflicting messages about investing from TV commercials, magazines, Facebook, financial professionals, and even from our friends and family about how to invest, which stocks to buy, where the market is going, or if it’s a good time to be in or out. The wide array of financial messages creates an investing fog that surrounds most investors and clouds their decision-making, causing anxiety, fear, and endless investing mistakes.
So what does it take to break free from the fog, unwrap the mystery of investing and make investing decisions with clarity and confidence?
The first thing it takes is an extraordinary commitment to truth and integrity. In fact it was this commitment that allowed me to break free of the fog for myself, and lead the way for my clients to achieve financial freedom and peace of mind.
Most of the investing fog we encounter revolves around the hysteria of attempting to predict the future price of stocks, bonds, metals, cryptocurrencies, and other investments. This hysteria leads investors to ask certain questions like “Which stocks should I buy?”, “Which ones should I avoid?”, and “What’s the market going to do next?” These questions are never truly answered and often cause many investors to become addicted to the financial news of major media networks. These questions also cause investors to experience a virtually endless stream of negative emotions including fear, regret, guilt, shame, envy, and pride. But what if these are actually the wrong questions? What if instead investors chose to ask the one question that would change their investing path forever?
What if instead investors asked “Is it even possible to accurately predict the future price of stocks?” What if the answer to this question was no? What would that mean? How would this change how we invest? Would we still watch Crammer’s Mad Money show? Would we still read stock tips from the Motley Fool? Would we still look at stock charts and use technical analysis? Would we still invest large portions of our wealth in individual stocks? Would we still hire an active stock picker to manage our money? The answer to this question could truly change everything, yet it’s the one question that most investors fail to ask. Given the enormity of the impact of the answer to this question, perhaps this question deserves some more of our attention.
Is it possible to accurately predict the future price of stocks?
As we explore this question, let’s imagine what the world would look like if the answer was yes and prices were predictable. Well if this was the case, there would probably be a well-documented method of figuring out which stocks are going to be winners and which ones are going to be losers. Consequently, investors would know of this and then everyone would only invest in the winners and no one would invest in the losers. Everyone would achieve above average rates of return. No one would ever lose money. If a market crash was coming, all investors would sell before the crash hit and then buy back in at the bottom and ride the wave up. Curiously, this doesn’t seem to be the world we’re living in. Instead, investors and money managers seem to lose money routinely. How could this still be happening after nearly a century of stock trading? Perhaps the opposite is true and it is not possible to predict a stock’s future price. But then why do so many people purport to being able to do this? How would we know for sure? Has anyone accurately studied this?
Efficient Market Hypothesis
Fortunately, the predictability of future stock prices has been studied by the academic community at great length and substantial quantities of research papers have been written about the topic. As a fiduciary and as someone who deeply cares about the lives of my clients, I felt professionally and morally obligated to review the existing literature on this topic in great depth. Some of the reviewed scientific studies are below:
Can Mutual Fund "Stars" Really Pick Stocks? New Evidence from a Bootstrap Analysis Robert Kosowski, Allan Timmermann, Russ Wermers, and Hal White* September 2005
https://rady.ucsd.edu/faculty/directory/timmermann/pub/docs/bootstrap.pdf
Persistence In Mutual Fund Performance Carhart 1997
https://onlinelibrary.wiley.com/doi/full/10.1111/j.1540-6261.1997.tb03808.x
Scale effects in mutual fund performance: The role of trading costs Edelen, Evans, Kadlec 2007
http://www.frontieradvisorsllc.com/files/1267653327_The%20Role%20of%20Trading%20Costs%20in%20MFs.pdf
Efficient Capital Markets: A Review of Theory and Empirical Work Eugene Fama 1969
http://efinance.org.cn/cn/fm/Efficient%20Capital%20Markets%20A%20Review%20of%20Theory%20and%20Empirical%20Work.pdf
False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas Barras, Scaillet, and Wermers 2010
https://www.semanticscholar.org/paper/False-Discoveries-in-Mutual-Fund-Performance%3A-Luck-Barras-Scaillet/d0520f11b55392c010fa048e3186b7512ef9e9e9
Head and Shoulders above the Rest? The Performance of Institutional Portfolio Managers who Use Technical Analysis David Smith Christophe Faugère and Ying Wang 2013
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2202060
The Cross-Section of Expected Stock Returns Fama and French 1992
https://www.ivey.uwo.ca/cmsmedia/3775518/the_cross-section_of_expected_stock_returns.pdf
A Five-Factor Asset Pricing Model Eugene F. Fama and Kenneth R. French 2013
https://www8.gsb.columbia.edu/programs/sites/programs/files/finance/Finance%20Seminar/spring%202014/ken%20french.pdf
After spending nearly 8 months reviewing the above literature it became overwhelmingly clear that it is virtually impossible to predict future stock prices. This is because all knowable and predictable information is already factored into the price of the stock and only unknowable and unpredictable information changes the price. For example, if a company is expected to have high growth and high profits, that information is already well known and the stock price will already be higher to reflect that. If a company is expected to have low growth and low profits, the price of that company’s stock is already lower to take that into account. When new information or news comes out, it affects the price so quickly that it is almost instantaneous and virtually impossible for investors to take advantage of. Because of this, even the best of the best on Wall Street cannot consistently add value to portfolios though individual stock selection or market timing.
A fresh perspective
Once this realization sets in and it becomes clear that no one can predict future stock prices, it completely changes the way the investing world looks. Because all financial news that we might read has already been factored into the price of the stocks, the news now becomes worthless. Reading financial news is now a waste of time. People or media outlets that claim to have a read on the next new hot stock can be completely ignored. Political and economic fear mongers can be ignored as well. As this realization sets, in the fog begins to lift and the host of confusing and conflicting financial messages begin to fade away into the background.
With the fog lifted, and dissipated, the challenge of how to invest can now be approached with significantly more clarity. In summary, the academic research suggests a few things:
1) There is no way to know the difference between a good stock and bad stock.
2) It is impossible to predict which direction market as a whole will move in the short term.
3) A diversified investor is going to get a random and unpredictable sequence of market returns.
4) Some types of stocks are more risky and as a result have had historically higher returns than others.
5) Different types of stocks move differently in comparison to others.
6) The historical returns of the market have been overwhelmingly positive.
These tenants can now serve as the foundation for both optimal portfolio construction as well as proper integration of an investment strategy within an overall financial plan.
The science of portfolio construction
The optimal portfolio is the one that provides investors with the highest possible return for a given amount of risk. To create this, it is important to examine the different risk and return characteristics of different types of stocks. As evidenced in A Five-Factor Asset Pricing Model Eugene F. Fama and Kenneth R. French 2013, certain types of stocks tend to have higher rates of return than others and also have more risk. For example, small companies tend to have higher rates of return than large companies but they also have more risk. Additionally, value companies also tend to have higher rates of return and carry more risk. Value companies are companies who’s stock price is relatively low compared to the amount of assets the company owns. A low stock price compared to the company’s assets often times indicates that the company’s financial future is less certain and has a higher chance of being rocky which increases the risk. This increase in risk also increases the expected return an investor should expect to receive by incurring that risk. Similarly, companies with a low stock price compared to their profits also tend to have more risk and higher rates of return.
With these three risk and return factors (small vs large, value vs growth, and low price to profit vs high price to profit) companies can then be divided into several different categories. For example, a company could be Large and Value while another could be Small and Growth. If the goal was to design a portfolio with the highest expected return without regard for risk it would include only Small, Value, and Low price to profit companies. Doing this however, would result in such a high amount of risk that very few investors could truly bear it. As a result, stock categories with lower expected risk and returns are also added to the portfolio. Significant amounts of math and statistical work is required to determine exactly which amounts of each category should be added to the portfolio to most positively impact the risk and return of the overall portfolio.
Why mid cap companies are inefficient in a portfolio
In the research paper “What’s Happened to the Barbell Effect?” Statistician Lyman Ott reaffirmed that it is generally not efficient to have mid cap or middle sized companies in an optimal portfolio. The reason for this has to do with an investing phenomenon known as the barbell effect. Historically, large companies have had the lowest returns, small companies have had the highest, and mid cap companies have had returns that have landed in the middle. Large and small companies have historically also had dissimilar price movements, meaning that they tend to have very different rates of return in a given year or years. This means that when large does the best, small often does the worst and vice versa. Mixing very large with very small companies creates significant diversification benefit because of their dissimilar price movements. Mid cap companies, by comparison, create less diversification when added to large company portfolios and have lower expected returns than small companies. In other words, if we compare a portfolio that’s one part large, one part mid, and one part small, we would find it to have a lower expected return with about the same amount of risk as a portfolio that had one part large and two parts small. As a result, optimal portfolios are designed this way and have for the most part excluded mid cap companies.
International diversification
One way to maintain high expected rates of return while reducing risk is through international diversification. As we mentioned before, the highest returning stock categories historically have been small, value, and low price to profit. Owning these high returning types of stocks in different countries allows the portfolio to have exposure to these categories much more safely. Stocks from different countries tend to move in different directions more often than stocks from within the same country. It is therefore mathematically advantageous to own high returning stocks from a wide variety of different countries. As of 2018 our client portfolios contain roughly 12,000 stocks in about 45 different countries.
Gold, Silver, and other commodities
Our portfolios do not contain any of the above assets for a variety of reasons. As an overarching philosophy, we do not include any asset in the portfolio that does not have robust scientific evidence that it either reduces risk or increases rates of return. Gold, Silver and all other commodities have historically had extremely high levels of volatility without a high enough rate of return to make up for the risk. Intuitively, this should not be surprising. When we own a stock we own a percentage of a company that is presumably doing everything it can to add value to society and we would expect to receive financial returns for the value that company is adding to the world. On the other hand a gold bar that we purchased that is sitting in a safe for speculation is adding little to no value to the world and we would not expect it to deliver stock market rates of return.
Real Estate
Real estate is not included in our portfolio for slightly different reasons. Before diving into this topic further, it is important to mention that real estate investing in this context is quite different from the type of real estate investing that occurs when an individual purchases a property they own personally. The type of real estate investing that is being discussed here is the type of real estate investment that is available to individual investors when they purchase shares of publicly traded real estate investment trusts also referred to as REITs. Publicly traded REITs function much like individual stocks. They are companies that trade on a stock exchange and are in the business of buying, selling, and managing real estate properties. Like stocks, these companies are available to just about any individual investor regardless of their income, assets, or credit score. REITs have a significant amount of annual return data that scientists and mathematicians can draw from and use to construct portfolios. Historically, while these types of real estate investments have had positive returns, their returns have been lower than that of ordinary stocks and the returns have also been highly correlated with ordinary stock returns. As a result, adding this type of investment to an ordinary stock portfolio would reduce the portfolios rate of return while doing very little to reduce risk. Real Estate Investment Trusts are also very inefficient from a tax standpoint as a large part of their returns are in the form of rental income. This results in investors having to pay ordinary income tax rates on the gains rather than the reduced tax rates of long term capital gains and qualified dividend income that stocks benefit from. Lastly, many of our clients are already invested in real estate in the form of their personal residence or possibly investment properties and including real estate in their investment portfolio would further expose them to the real estate investment risks they’re already taking in their own life.
Cryptocurrencies
Cryptocurrencies are also not included in our client’s investment portfolios. Among other reasons, insufficient return data exists to ensure that the addition of this asset category would in fact add value to the portfolio. From an intuitive perspective, it would also seem reasonable to infer that this asset category might behave similarly to commodities which have historically high risk and low long term rates of return.
Index Funds
Index funds are generally not used in our clients portfolios as they are often a very inefficient method of capturing market returns. One reason for this is that index funds suffer from losses due to a financial phenomenon known as the index reconstitution effect. Because an index is simply a measurement, no one can invest in an index directly and as a result, index funds were created. An index fund is a fund people can invest in that intentionally buys the same stocks that are contained in the index it is trying to track. Unfortunately, mirroring or tracking an index like this often results in reduced performance due to this index reconstitution effect. This effect arises when an index has to add or remove stocks from its list. If a stock becomes either too big or too small, the index at some point has to remove the stock. Each index manages this issue differently. Many of them choose to add and remove stocks annually as is the case with the Russell 2000. The Russell 2000 in an index that tracks US small stocks. Over the course of the year, some stocks in the Russell 2000 become too big for the index. Even though these stocks are now too big, the index allows these stocks to remain in their index until the annual index reconstitution date which is when the index changes its list of stocks. On this day, the index removes the stocks that became too big and replaces them with smaller ones that fit the index’s profile. When this happens all of the index funds that track this index place sell orders and sell all of the stocks that are no longer going to be included in that index. Because the large number of sell orders that index funds place on the same stocks at the same time, the price of the those stocks falls before the sell orders can be completed causing the index funds to take losses before these stocks are removed from the fund.
Another drawback to index funds is that they are chartered to follow an index rather than to capture the returns of a specific asset category. For example, the Russell 2000 index is traditionally thought to be representative of US small companies. The name Russell 2000 comes from the fact that this index measures the performance of the 2,000 smallest companies in the Russell 3000 index. Given that there are over 4,000 publicly traded companies in the US, this index does not measure the performance of any of the US Micro Cap Stocks.
Lastly, index funds also do not usually screen for the firm profitability premium as it is almost impossible to find any index that targets companies with low price to profit ratios. As a result index fund typically miss out on returns from these companies in almost every stock category.