Risk Management: Tools, Strategy, and Policy Governance
In recent years, access to data and sophisticated algorithms have made quantitative risk management tools very powerful. On the other side of that equation, effective risk management often collapses because of behavioral or other soft risk factors at the committee level. The qualitative side introduces a lot of subjectivity, so timeframes, volatility, tracking errors, inflation, liquidity, and even peer comparisons may impact committee decisions.
The way that these risks are subjectively prioritize can lead to vastly different conclusions, decisions, and eventual outcomes. That's why relying upon risk scores from even those sophisticated available tools won't hold up when they still can't always predict behavior.
How Changing Prioritization of Risk Factors Can Influence Portfolio Success
For example, many advisors consider treasuries a natural safe haven during bear markets. Mostly, this conclusion is born by historical examples. It's also a sort of self-fulfilling prophecy because of investor expectations.
- When the stock market declined in the early 2000s because of the Dot-Com Bubble popping, the stock market dropped almost 40 percent, but treasury notes increased in price.
- A similar scenario famously happened again in 2008 and 2009 with the mortgage crisis.
There isn't some physical, negative correlation between rising treasury prices and declining stock market prices. It's just that stock prices don't tend to fall in a total information vacuum, so before and during the events, investors experienced fears about economic problems. A number of investors acted upon these concerns by moving assets from equities to government notes as a safe haven. Those actions helped strengthen government assets and weaken commercial equities at the same time. In the past, this may have helped protect portfolio values, but is this always true?
Truisms Aren't Always True
What if the situation changes? What if something occurs that causes a positive correlation between government investments and stocks? Then the situation that investors rely upon because of historical examples would move from becoming a truism to something that's no longer true at all. It's likely that something else will become a logical safe haven at this time, but it's difficult to predict right now what that would be. As illustrated above, behavior has caused the negative correlation in the past, but behavior could change.
This actually happened. While a diversification into treasuries helped investors overall during the housing crisis, there were acute periods of uncertainty when concerns over deflation drove both treasury and municipal bonds down too. As noted in a Balance Article, this diversification usually helps provide protection; however, there are no guarantees. The outcome depends upon investor perception of the overall economy and of course, upon the way that perception impacts their behavior.
How Unexpected Behavior Can Damage Good Companies
This example isn't directly related to a correlation between government bonds and stocks; however, it does illustrate an important example of problems with assuming future events will mirror historical ones. Morgan Stanley has prided itself on its investment in cybersecurity risk management for many years. This financial giant knew how much they could lose if attackers breached their sensitive information. The problem is that they expected bad behavior to come from outside or even foreign hackers who might use sophisticated tools to compromise their systems.
The company still became a victim of the digital loss of 350,000 customer records. This attack didn't happen because of some determined, sophisticated hacker. An employee of the company simply used their own security credentials for the theft. The company did not anticipate this behavior; investors who analyzed such threats thought Morgan Stanley was well protected.
This data breach generated just as many losses as if it had come from the outside. The company did not expect an inside attack, and this is a good example of unanticipated behavior as well.
Is Historical Data Always a Good Predictor of Future Outcomes?
Anybody who has taken an elementary statistics class or read the fine print in a securities statement knows that past performance doesn't guarantee future outcomes. Even if the coin showed heads three times, there is still the same 50-50 chance of the coin showing tails on the next flip. While positive and negative correlations between certain kinds of investments are more complex than tossing coins, portfolio management still relies upon many qualitative uncertainties.
Even worse, as illustrated in the examples above, expectations of future behavior that are based upon historical data are not 100-percent reliable. In some cases, it is these very expectations that may generate more risks. Saying that something did not happen in the past when it happens the first time might offer an explanation for how risk management was managed; however, it still doesn't offer any solutions or a good defense of poor risk management.
How to Improve Risk Management in the Future
In the future, your risk management tools may incorporate some sophisticated artificial intelligence and unimaginably huge data stores that can somehow account for all possible scenarios. To work perfectly, future tools may have to understand human behavior better than humans do. In that imagined future, maybe investors can rely totally upon risk scores to balance their portfolios.
These days, human beings have to look for examples of acute scenarios that might alter behavior and change risk scenarios. Examples, as illustrated above, could include something like fears of deflation or even insiders behaving badly. The thing is that when analysts look back at these situations, those risks that weren't accounted for seem sort of obvious and predictable -- but only in hindsight. As always, foresight is what's difficult. Mostly, just because something hasn't happened before or happened very often, doesn't mean it won't happen in the future.