In the movie A Beautiful Mind, there is a scene where the brilliant mathematician John Nash, played by Russell Crowe, sits with a colleague in a bar and talks about the nature of competition, while they enjoy a wholesome college meal of pizza and beer. Is it true that there must always be one winner and one loser in any game? Can it be possible to have an ‘equilibrium’ where different players achieve the best possible outcome by cooperating? Nash’s formulations on this concept, in which he proposed the aptly named concept of a “Nash Equilibrium”, ultimately won him the Nobel Prize.
Today, we’d like to take that same approach to investing, and set up a portfolio that allows diverse asset classes to work together. Indeed, there is a certain beauty when we allow the volatility and turbulence, or the ‘Beta’, of different assets to achieve harmony together.
Dar Sandler Davide De Micco
In our last article we talked about the two fundamental drivers of asset class returns: Growth and Inflation. We demonstrated how the market’s expectations for these variables are what ultimately determine their long-term returns. More specifically, we focused on how these variables can change over time contrary to market expectations. Based on those observations, we can divide the world into four conceptual buckets, where each bucket represents what happens when Growth or Inflation comes in above or below those expectations. Different asset classes will perform better than others in each bucket.
In our first article we also reviewed how the industry standard 60/40 model (60% equities, 40% bonds) is a poor path to diversification. That is why it is preferable to target risk, which is measured in volatility of returns. By targeting risk and allocating investments proportionally, we achieve the best possible diversification in which no asset will dominate another.
But enough with the talk – how do we take these concepts and use them to construct a portfolio that truly thrives through rain and shine?
We can take each driver, growth and inflation, and derive two different categories of outcomes: one when that driver is above market expectations, and one when it is below. We can then think of each of those categories as a ‘bucket’ in which we can place different kinds of asset classes. Another way to think of this would be to imagine our entire portfolio as a track team, in which we want to assign team members based on their strengths and weaknesses. We’ll put our fastest runners on the short distance sprints, and the brawny members on the shot put or hammer throw.
Similarly, for our portfolio design we will select asset classes that will best perform in each bucket. For our “Growth above expectations” team we might pick assets like Equities, Emerging Market Credit, and Real Estate, as these are asset classes that will excel when economic growth comes above expectations, leading to higher demand.
We now face a new question: how much of each one do we assign? While a track team might be aiming to win medals in each individual competition, our goal for the portfolio is to deliver the best possible overall return for the amount of risk that we are willing to accept. We can then target a pre-defined amount of risk in each bucket. In other words, each of our buckets will contribute an equal amount of risk to the overall portfolio, 25%. In this way, our risk is equally balanced for each bucket.
We have now achieved the “Beautiful Beta” portfolio.
At the end of the day, no matter what you might have heard from Jim Cramer on CNBC, you don’t know what will happen tomorrow. No matter how many books and blogs you read, the act of timing the market, or achieving ‘Alpha’, will always be hard to impossible. This is not our game, nor should it be yours.
Through this approach, you can opt-out of timing the market. In fact, we invite you to be completely indifferent to what the market does in the short term. If somebody wants to try and calculate the best time to buy and sell stock based on Fibonacci ratios, then more power to him! But if it’s possible to collect risk-premiums in a way that won’t give you heart palpitations after each Federal Reserve announcement, why not take the easier path?
The picture below shows an example of the portfolio that we are proposing.
Your reaction might now be: Great! – I like this, but this portfolio clearly has a specific expected return and risk. In other words, we can say that there is a set ‘Sharpe ratio’ that defines the ratio of return to risk for this portfolio. Let’s say I like the overall approach, but would like to target a different level of risk? What do I do if the risk-profile is too low, and I’d like to make life a little more exciting? Or I’m counting the days to retirement and prefer to sail on smoother waters?
Should I just follow the advice of Modern Portfolio Theory, which recommends the 60/40 model, and just buy more of the riskier assets and less of the less risky ones, if my end goal is to achieve higher volatility? And if so, how do I do that if I have already taken the time to elegantly set up my buckets and risk targeting? Won’t these adjustments just deteriorate the quality of my approach?
We have a different answer: there is a tool that allows you to adjust risk in a beautiful way. In addition, we can achieve that without disrupting the Sharpe ratio and harming the benefits of diversification, which happens when we modify allocations under the 60/40 model.
What is this tool? It is called “leverage”. Now hold on a moment, don’t run away just yet. We aren’t talking about the kind of leverage that caused the meltdown in 2008. Quite to the contrary, this is a carefully controlled approach that allows us to tweak exactly what we get out of each asset class, in a way that is simply impossible if all we do is buy and sell the asset class itself. Do you want to learn how to use leverage to adjust the portfolio risk without disrupting the risk/return ratio? In other words, would you like to see an approach in portfolio construction that allows you to have your cake and eat it too? Stay tuned for our next article!
Edited by: Simon Cartoon