By Jack Forehand (@practicalquant) —
Investment professionals like to use a myriad of fancy terms to measure risk. The problem with almost all of them is that they are in no way understandable for the average investor. Words like standard deviation, max drawdown, tracking error and Sharpe ratio are often thrown around to judge how risky a portfolio is. Those concepts are not only very difficult for investors to understand, but they also aren’t all that useful in the real world. The reason is that they aren’t aligned with the risks that ultimately lead to investing success.
At it core, risk is very simple. Anyone who invests does so with a particular goal in mind. The simplest definition of risk then is just the chance that goal will not be achieved. For example, if you are saving for college and require a specific amount of money on a specific date, your risk is that you won’t have that money on that date. Measures of risk that aren’t aligned with an investor’s goals can often cloud that simple truth and lead to suboptimal investing decisions.
When you look at risk as the chance you won’t achieve your investing goals, there are 3 main things that can derail you.
- Your goals are not realistic;
- The investment vehicles you are invested in don’t achieve their expected returns;
- Your investments do achieve their expected returns, but your own behavior gets in the way.
The first risk can be painful to accept, but it is also very easy to deal with. If your goals are not realistic given your risk tolerance and the expected returns of the investment vehicles you have available to you, then you need to adjust them to reflect reality. This often requires accepting that the future spending and lifestyle you want may not be possible and that adjustments are needed. It is not an ideal situation, but it is much better to deal with issues like that up front than to take excessive risk in pursuit of an unrealistic goal.
The second one is perhaps the most challenging. If you do everything right and have the right expectations going in, but you happen to invest during a long period of well below average returns, bad luck can sometimes get the best of you. Planning for a low return environment from the outset, even if you don’t think it is likely, can help to deal with this, but ultimately this risk requires the same solution as the first; accepting that future spending will have to fall.
The third risk is the one I want to focus on in this article because I think those of us in the investment business do a bad job of measuring it and communicating it to clients. Investment professionals typically focus a lot on things when we talk to clients about maximizing future returns. For example, keeping fees low is usually a major focus. And that is justified since fees have been shown to be a strong predictor of long-term returns. But the difference between active and passive fees is only 0.6% on average. Studies have shown that the impact of investor behavior on returns is at least double that, and likely much more.
When advisors setup investment strategies and measure their risk, however, many don’t look at metrics that help avoid putting investors in situations where their behavior can get the best of them. Looking at the standard deviation of a portfolio (a fancy term that measures how volatile it is) or its maximum drawdown (the largest loss it has ever sustained), can certainly provide some useful information, but they only paint a small part of a much bigger picture. Focusing on the things that lead to bad behavior can lead to better results.
Jim O’Shaughnessy often talks about how passive investors face a single point of failure and active investors face two. The first point of failure faced by all investors is that they will panic and sell when the market is down. The second faced by active investors is that they will panic and abandon their investing strategy when it underperforms.
So how can these risks be quantified? There is no exact answer, but we have a few questions that we think get to the heart of this issue for investors. When we look at a strategy, we ask the following:
1 – How Often Does the Strategy Lose Money and How Much Does It Lose?
We all know that losses cause more pain for investors that gains cause pleasure. Understanding up front how often a strategy loses money is crucial to matching it with an investor it is appropriate for. The simple way to do this is to look at its full history in individual calendar years. But calendar years are random. If you look at a portfolio’s returns from every day in its history back one year, you get 250 or so one-year periods to look at for each calendar year instead of one, which allows for more meaningful results. If you are looking at the chance a portfolio will lose money, using this approach allows you to look at thousands of one-year periods historically and easily see the percentage of time it has done that historically. You can do the same thing for the number of periods it has lost 10% or 20% and so on.
The result is a simple display of the risk of the portfolio that includes the percentage of time it has lost each given percentage. For an investor who may panic at a certain level of loss (despite what they say every investor has a percentage where they will panic), this allows them to see how often that loss has occurred in the past. If that percentage is too high, the risk can be adjusted to a level that better fits the investor’s risk tolerance.
Here is an example for a portfolio invested in the S&P 500 from the date we launched our model portfolios until today. Over that period, an investor who looked at their one-year performance on a random day would have an 18% chance of seeing a loss and a 10% chance of seeing a loss of more than 10%. The chances of larger losses fall as the loss increases as you would expect. This period has been mostly an up period for the market (other than 2008) so the long-term averages are higher than this. Losses are what typically lead investors to panic and make mistakes, so looking at risk in this way can be helpful.
2 – How Often Does the Strategy Underperform its Benchmark? How Much Does It Underperform By? How Long Does It Underperform?
The same is true for the risk of underperformance. It is often said that pain is the price you pay for outperformance in active management. Measuring risk relative to this pain allows an investor to see just how bad the pain might be. Some of the best performing factor-based strategies we have seen only outperform in 60% of one-year periods. That means that an investor who follows them will have a 40% chance on any given day of looking at their portfolio and seeing that they are trailing the market for the past year. That is too much for most people and will lead to poor decisions. On the other hand, other quantitative strategies we follow don’t outperform by as big of a margin long-term but can outperform in 80% of one-year periods. Those are more appropriate for many investors because they are more likely to be able to stick with them over time. Ultimately, just following the index means that you underperform in 0% of one-year periods and eliminate the risk all together, which is why most investors should index. The tradeoff to that approach is you only get the benchmark return and not the possibility of outperformance.
A second factor to consider is the magnitude and duration of underperformance. The more active a strategy is, the more it will deviate from its benchmark. Very active strategies typically can produce the best long-term returns, but they also can have periods of significant underperformance that can last for a very long time.
The chart below shows our 20-stock model portfolio we follow based on Benjamin Graham’s Defensive Investor value strategy from book The Intelligent Investor. This is an extreme example since this is a very focused deep value portfolio, both of which lead to high levels of risk, but it illustrates a practical way to look at risk for an active strategy.
This strategy has underperformed the market 37% of the time over one-year periods since 2004 with the longest period of underperformance being around 2.5 years. It also underperformed the S&P 500 by over twenty percent in 13% of one-year periods and had a period of almost a year and a half where its trailing twelve-month return was more than 20% behind the S&P 500. This example illustrates just how hard active deep value strategies can be to follow, but it also shows how that risk can be quantified in a way that is understandable for an average investor. This strategy has produced significant outperformance over the market over time, but the price to pay for it has been extreme pain along the way. Those that can’t endure a high level of pain (which is the vast majority of people) shouldn’t use a focused active approach like this.
Our approach is only one of many others that can work, though. The overreaching point is that when you are measuring risk in investing, you should measure it using metrics that are most aligned with the goals you are trying to achieve and the things that are most likely to prevent you from achieving them. The risks of abandoning an investment strategy when it is losing money or underperforming are probably the two biggest risks that will prevent your goals from being met. Your measures of risk should be aligned with that. Investing in a lower return portfolio you can stick with is almost always better than investing in a higher risk one you can’t. Looking at risk properly will allow you to better setup a portfolio that fits you personally. That is the key to long-term investing success.
Jack Forehand is Co-Founder and President at Validea Capital. He is also a partner at Validea.com and co-authored “The Guru Investor: How to Beat the Market Using History’s Best Investment Strategies”. Jack holds the Chartered Financial Analyst designation from the CFA Institute. Follow him on Twitter at @practicalquant.