High Risk Investments Can Make Your Investment Portfolio Safer
Understanding the risk-return tradeoff in a portfolio setting
Registered Investment Advisors, financial advisors and wealth managers, in general, have two essential functions (1) assisting their clients through a rigorous due diligence process, to select investments or portfolio assets that they believe will have a high expected return within the client’s risk tolerance and (2) manage the allocation of these assets within the context of the client’s portfolio to maximize the risk-return parameters of the portfolio. The goal should be the lowest risk portfolio for the client’s target return. But because so many clients are extremely risk averse, many wealth managers do not consider higher risk investments for their clients thereby missing the important advantages these investments can provide when constructing an optimal portfolio asset mix.
The mathematics behind the asset allocation model were first introduced in 1952 in the 14 page paper entitled “Portfolio Selection” authored by Harry Markowitz. (https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1540-6261.1952.tb01525.x) Markowitz proved mathematically that if you can lower the volatility of a portfolio (reduce risk) without lowering expected return (maintaining average return) you will maximize the actual returns of the portfolio. The mathematics behind this counter-intuitive principle, that taking less risk can actually make you more money, earned him the Noble Prize in 1990.
A simple of example of this concept is, take two $100 portfolios. The first portfolio goes up 30% in year one to $130 and it goes down 10% in year two to a total of $117. Portfolio two goes up 10% in year one to $110 and up 10% in year 2 to a total of $121. Both portfolios have a 10% average yearly return but the lower volatility of portfolio two increased the actual cash at the end of the two-year period.
The best way to reduce volatility without lowering expected return is to identify good investments that have a low correlation to one another. In other words, when one investment is going up there are other investments in the portfolio going down or sideways. In this way you get from point A to point B on a less volatile path. The class of investments that have the lowest correlation to traditional investments are “alternative investments”. This includes a myriad of non-traditional investments such as, venture capital, private equity, real estate, gas and oil, timber and hedge funds to name of few. Peng Chen, Gary T. Baierl and Paul D. Kaplan stated in their paper, “Venture Capital and its Role in Strategic Asset Allocation”, published in the Journal of Portfolio Management, that over the forty year period they looked at, “the correlation coefficient between venture capital and public stocks was estimated to be 0.04%. Because of its relatively low correlation with stocks, an allocation to venture capital of 2% to 9% is warranted for an aggressive portfolio.“
Alternative investments, if managed correctly, should decrease the volatility or risk of the overall portfolio and increase it expected return. But how does a wealth manager explain to their clients that what appears on the surface to be a very risky stand-alone investment actually improves the safety and return of their client’s total portfolio. I was faced with this daunting task.
In 1988 I began working with two professors of finance to create an algorithm, using Markowitz’s mathematics, to create enhanced stock portfolios that would outperform target benchmarks. The algorithm was difficult to solve. In 1990 Markowitz agreed to consult with us as we tested multiple variables and inputs to identify optimal outcomes . Eventually Markowitz went on the work at Daiwa and our group went on to create the Weiss, Peck & Greer Quantitative Equity Division where we managed over $2B in pension fund assets utilizing the Markowitz model. I spent a lot of my time going to client meetings, including many union funds, trying to explain to their investment committees how the model worked. Relating it to the game of baseball proved to be the winning formula.
The average amount of runs scored by a baseball team in a year is 800 which is 30 runs per week (expected return). Let’s take two baseball managers. Each will select 9 players for their team (portfolio assets). The goal is to win the most games. Most managers try to find 9 Mike Trouts or Derek Jeters. Manager 1 chooses 9 star players that he believes will perform so well that they will score more than the 800 runs and therefore win more games. These players stats tend to be highly correlated to one another. Manager 2 knows from experience that it is very difficult to score more than 800 runs a year. So he decides that he will select his players to reduce the volatility of his 30 run production per week by selecting players that play well under varying circumstances or players with low correlated stats.
As you can see, Team 2 has almost no volatility in its run production. Team 2 maintained expected return, 30 runs per week, but lowered the volatility of this run production and ended up winning more games. This is the principle that drives the asset allocation model and supports the investment into low correlated assets.
There is a continual struggle in the financial management industry to balance the seemingly unreconcilable dual goals of preservation of capital and taking the risks involved with increasing the value of the client’s portfolio. And although most advisors and their clients are very risk averse and their instincts are to shy away from high risk ventures, what Markowitz made clear is that higher risk investments in the right proportion sitting alongside more traditional assets actually will make a clients investment portfolio safer and increases its expected return.
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