In 1952 a guy named Harry Markowitz introduced something known as Modern Portfolio Theory (MPT). Harry won a Nobel prize for his work which mathematically showed how and why risk and return for an individual asset should not be viewed on its own, but on how that asset impacts the overall risk and return of a portfolio of assets. My prior blog post on asset allocation explains the basic mechanics of how different asset classes can impact the risk and return of a portfolio. In this post we will dive a little deeper to show how the efficient frontier is constructed.
Fortune Telling/History, Theory and Reality
Steve and I are not in the business of fortune telling. I can’t speak for Steve but it is my belief that it is impossible for someone or some fund company to predict what will happen with different asset classes in the future. My reasoning is simple, if even one person knew what was going to happen the system would not work, in engineering terms it would go unstable. I use Back to the Future II as my example. Remember when Biff gets his hands on that sports almanac and everything went to hell? That is what I think would happen if even one person in the world knew exactly what was going to happen with stocks, bonds etc. My advice is that if someone says or acts like they know what is going to happen in the financial markets you should steer clear of them.
What I do believe, which is useful for you helping you grow your wealth, is that asset classes tend to behave differently. We don’t know exactly how the asset classes will behave relative to each other in the future, but history at least gives us a pretty good jumping point to engineer a portfolio. Also, by testing portfolios against as many time periods in history as possible we can find portfolios with a high probability of solid performance in the future.
This post is to give you a high level understanding of portfolio construction and why it works. This post covers the THEORY of it all. Steve has some great posts using real historic data putting the theory to the test, showing the REALITY.
Portfolio Construction – Feasible Portfolios
There are literally an infinite number of ways to construct a portfolio. Image you had only two asset classes in your portfolio, US large cap stocks and a US total bond fund. Even with that simple of a portfolio there is still an infinite number of portfolios, you could have 99.999% in the stocks and 0.001% in bonds as an example. When you start adding in numerous asset classes you can see how the choice of portfolio construction can get a little daunting. In the parlance of modern portfolio theory all of these different options would be considered feasible portfolio’s. The interesting thing is that some feasible portfolios are better than others. Some portfolios maximize their return given their level of risk or minimize their risk given their level of return. These portfolios are known as efficient portfolios.
So how does that work, how are some portfolios better than others? It all comes back to the fact that uncorrelated asset classes don’t “move” the same, they vary (I’m using this last word for a reason!). And what Mr. Markowitz figured out is how to mathematically derive these optimal portfolios. Long story short if you know the historical return of the different asset classes in your portfolio you can define what is called the variance-covariance matrix. In more laymans terms you known how all of the different asset classes varied over the years, how correlated or uncorrelated they were. If you also know the average historical returns (or project the future average returns….a bit trickier of a task!) of the different asset classes you can generate all portfolios which live on what is called the efficient frontier. The efficient frontier shows the maximum amount of return you can achieve for a given level of risk OR the minimum risk you can achieve for a given level of risk.
To show this graphically, the plot below was created from asset class data from 1972 through 2015. To start, a simple portfolio of only US stocks and bonds is looked at (Steve’s engineered bond portfolio actually). The curve represents all possible portfolios of these two asset classes where the portfolio is efficient. Let’s start at the top right of the curve, here you are able to achieve the most return but also have the most risk, in this situation this is most likely a portfolio of 100% stock and 0% bonds. Risk is defined as standard deviation, or how volatile the portfolio will be (lower is less volatile). As you move to the left on the curve your risk and return is reduced as you add bonds to the portfolio. At some point you get to what is known as the “minimum variance portfolio”, this is the point on the curve where the risk is minimized. This is a very simple example but a good place to start.
Expanding the Efficient Frontier
So what does all of this matter to you? Well, the theory shows us that as we add asset classes to our portfolio like emerging markets or real estate investment trusts (REITs) the efficient frontier actually moves or “expands”. Why is this good? Because it means that for a given level of risk you can actually improve your return or for a given level of return you can reduce your risk. Or you can split the difference and get a little bit of both…..more return AND less risk!
Three efficient frontiers are plotted below, the first is our original stock/bond portfolio, the second has added REITs and emerging markets (EM) and the last has also added large and small cap international stocks. Take a hard look at the plot and notice how the curves shift to the left as you add asset classes. Also notice how the slope of the lines increase as you add asset classes. Both of these changes are GOOD NEWS, they give you more return for the level of risk you are taking in the market.
Harry Markowitz did us all a pretty big solid with his work on Modern Portfolio Theory. The big take away is that adding more asset classes to a portfolio can help improve risk adjusted returns. Long story short we can grow our wealth faster. Steve and his sweet MATLAB magic will put that theory to the test with real portfolios to provide actionable information to create your own efficient portfolio. Stay tuned!