is mostly a measure of emotions and not necessarily investment risk. This is also true of other measures, such as downside standard deviation, maximum drawdown and downside capture.
Investment risk is the chance of underperformance. Measuring underperformance depends on the time horizon of the investment and the specific goal of the investor. For example, if the goal is to have a fixed amount at a fixed time in the future (e.g. $100,000 in two years), risk is measured as the chance of ending up with less than $100,000 in two years. In this case, short-term volatility is an important contributor to risk.
In cases where there is a specific long-term need (e.g. $1,000,000 in 30 years), risk is measured as the chance of not meeting this goal. In the cases where there is no specific time horizon, however, the appropriate benchmark is the highest expected return investment being considered, since over long time periods the actual return should approximate the expected return due to the law of large numbers. Most long-term investment situations fall into the latter.
Another important consideration is that short-term volatility plays an ever smaller role as the time horizon lengthens. This is because the short-term emotionally and economically-driven price changes tend to offset one another over the long run, to the tune of reducing long-term volatility by a factor of three to four relative to short-term volatility.
Risk and volatility are not synonymous
The widely used mean-variance optimization methodology for constructing portfolios was first introduced in 1952 by 1990 Nobel Prize laureate Harry Markowitz of the Rand Corporation:
“We first consider the rule that the investor does (or should) maximize discounted expected, or anticipated, returns. This rule is rejected both as a hypothesis to explain, and as a maxim to guide investment behavior. We next consider the rule that the investor does (or should) consider expected return a desirable thing and variance of return an undesirable thing. This rule has many sound points, both as a maxim for, and hypothesis about, investment behavior.” [15]
Unfortunately, the industry took this approach and mistakenly began building portfolios by minimizing short-term volatility relative to long-term returns. This places emotion at the very heart of the long horizon portfolio construction process. In the context of BPM, the reason this approach became so popular is that it legitimizes the emotional reaction of investors to short-term volatility. I refer to this as the unholy alliance between mean-variance optimization, on the one hand, and emotional investors on the other. This is a classic case of catering to client emotions.
Currently, risk and volatility are frequently thought of as interchangeable. One of the ironies is that, by focusing on short-term volatility when building long-horizon portfolios, it is almost certain that investment risk increases. Since risk is the chance of underperformance, focusing on short-term volatility will often lead to investing in lower expected return markets (e.g. low expected return bonds versus higher expected return stocks) with little impact on long-term volatility. [16] Lowering expected portfolio return in an effort to reduce short-term volatility actually increases the chance of underperformance, which means increasing risk.
A clear example of this is the comparison of long-term stock and bond returns. Stocks dramatically outperform bonds over the long run, so by investing in bonds rather than stocks, short-term volatility is reduced at the expense of decreasing the long-term return and, in turn, increasing long-term investment risk. Equating short-term volatility with risk leads to inferior long-horizon portfolios.
The cost of equating risk and emotional volatility can be seen in other areas as well. It is known that many investors pull out of the stock market when faced with heightened volatility, but research shows that this is exactly when they should remain in the market and even increase their stock holdings, as subsequent returns are higher on average while volatility declines. [17]
It is also the case that many investors exit after the market declines only to miss the subsequent rebound. This was dramatically the case following the 2008 market crash when investors withdrew billions of dollars from equity mutual funds during a period in which the stock market more than doubled. The end result is that investors frequently suffer the pain of losses without capturing the subsequent gains. [18] Again this is the result of not carefully separating emotions from risk and thus allowing emotions to drive investment decisions.
Assimilating Basic Principle III
Principle III will likely be the most difficult to assimilate. It involves redirecting the powerful emotion of loss aversion, while acting contrary to the hardwired tendencies of thinking short-term and social validation. For a number of investors, this may be too much to ask. But for others, progress may be possible. A first step is calling things as they are. Rather than labelling everything risk, be careful to identify and separate that portion which is really emotion. There are risks that must be taken into account when making investment decisions but don’t muddy the water by carelessly lumping emotions and investment risk together into a single number, as is the case for many popular risk measures.
A flying analogy may help think about the separation process. All of us who fly have experienced turbulence, which can range from being unnerving to downright frightening. When asked about their flight, many travelers will comment on the amount of turbulence they encountered. However, we know from years of FAA (Federal Aviation Administration) research that turbulence rarely causes injury or death. Instead, pilot error (over 50%) and other human error are the leading causes of plane crashes.
What if the FAA had instead listened to passengers to determine the risk of flying? Rather than meticulously studying each accident and uncovering the true cause, the FAA would have spent considerable time trying to reduce turbulence, as requested by passengers, thus missing the critical role of human error in accidents. By focusing on short-term turbulence, they would have actually made flying more dangerous. Luckily they did not and as a result 2012 was the safest year in commercial flight since the dawn of the jet age.
We are not so fortunate in the investment industry. Rather than carefully separating risk from emotions, the industry provides a mixed bag of risk measures that exacerbate the emotional aspects of investing. As I argued earlier, this means many long-horizon portfolios are built to reduce short-term volatility, while at the same time increasing portfolio risk.
So to make the transition, it is necessary to allay the fears of clients while at the same time disregarding many a conventional wisdom. Unlike those who have a fear of flying and only have themselves to change, the investment professional has to confront both clients and the investment establishment. Sadly, the risk measures put forward by the industry are more emotional measures than they are investment risk measures.
Summarizing the three Basic Principles
Behavioral Portfolio Management focuses on the behavioral aspects of financial markets to help make better investment decisions. BPM’s first basic principle is that Emotional Crowds dominate the determination of both stock prices and volatility, with fundamentals playing a small role. This means that more often than not prices reflect emotions rather than underlying value, a consequence of arbitrage failing to keep prices in line with fundamentals. As a result, price distortions are the rule rather than the exception, making it possible for BDIs to build superior portfolios, which is the second basic principle.
Volatility and risk are not synonymous. In the case of meeting short-term financial goals, volatility is an important contributor to investment risk, as measured by the chance of underperformance, and this is the third basic principle. On the other hand, volatility plays a much less important role when building long-horizon portfolios. By focusing on short-term volatility when
