Volatility in equities, bonds, and other asset classes remained at very low levels compared to historical norms in 2017, as measured by the standard deviation of daily market price movements. Yet, at the same time, uncertainty was exceptionally high concerning a wide-ranging array of potentially market-moving events which were often in the daily news and getting considerable attention. The co-existence of relatively low volatility and high uncertainty presented an interesting conundrum.
The list of potential volatility-inducing questions was quite long during the year 2017. Would the future course of fiscal policy in the US involve a big corporate tax cut or not? How would trade relationships around the world change as the US pulled back from its former world leadership role? Would the Brexit negotiations hang over the UK economy like Damocles’ sword for years to come? The financial path of Saudi Arabia, the largest oil producer in the Middle East, depended in no small way on how the initial public offering for Aramco goes in 2018, which in turn depended on the price of oil. How would Saudi oil production strategy change before and after the pending IPO? The Federal Reserve embarked on incremental plans to shrink its balance sheet with the European Central Bank followed with adjustments to its asset buying programs. How will asset classes that positively benefited from QE respond to the unwinding? Diplomatic tensions with potential military implications abounded.
Essentially, 2016 and 2017 highlighted that the world faces serious economic and political challenges with the likelihood of binary outcomes. That is, not only is the environment experiencing rising uncertainty, the probability distributions of potential market outcomes are decidedly not normal, often highly skewed, and sometimes even bi-modal, whichmeans that generating returns has gotten markedly more difficult for investors.
And, it is not just about the short-term questions that worry markets. Context matters and demands attention paid to major long-term drivers such as the trend of anti-globalization, demographic changes, migration and societal transformation. The net is that global markets in the “binary age” are impacted by greater exposure to social and political risks than in the 1950-2010 post WWII environment. Particularly, the rise of social populism has caused uncertainty across the markets. In 2016, we witnessed Brexit adding tremendous volatility across the markets and the US election with a boom in banking and energy sector equities and added volatility for the Mexican peso. Meanwhile, the government debt levels reached a historical high with $200 trillion global debt across the world.
One might think all of these uncertainties would have been associated with increased market volatility, especially in equity and bond prices, but it did not happen in 2016 or 2017. To appreciate what events might trigger volatility, we need to examine the complex relationship between uncertainty and volatility.
The long-term drivers of uncertainties
While we typically cite current events and various policy issues that are in the news as sources of uncertainties, our perspective is that it is even more important to look deeper into the often overlooked, long-term drivers of the uncertainties. We need to appreciate that a trend that takes decades to develop may manifest itself quite suddenly and in very powerful ways. What happens is that perceptions of reality tend to be inertia driven, even though virtually everyone is aware that long-term changes are afoot. Then, a catalyst suddenly changes the consensus view of reality. Let’s take a few examples – from bond markets, technology, social perceptions, and corporate change – to illustrate the analytical challenge.
Tailwinds from falling bond yields may be reversing
For over 30 years from 1982 into 2016, investors benefited from falling interest rates. From 2018 forward, that time may be over. As 2017 closed, industrial commodities appeared to have exited their bear market – a necessary condition for inflation pressures to re-emerge.
In a very low rate world, the Fed and other central banks have less room to stimulate than in any period going back to 1934. Therefore, there is less of a cushion for future shocks. The experiment with pushing rates below zero did not work well, and past cycles of quantitative easing may have raised asset prices but did little to encourage economic growth or push inflation higher, which was their objective. For 2018, we have questions surrounding whether the removal of quantitative easing in the US will destabilize markets, if not the economy.
Technological innovation has disrupted employment patterns
Innovation provides kinetic energy that makes disruption possible in all industries. It is no secret that most workers in manual, routine jobs have a high probability of seeing their jobs automated during the 2020s and 2030s. Indeed, in the US, jobs termed as non-routine cognitive (i.e., problem solving jobs) have grown rapidly while manual routine jobs were relatively stagnant.
Technological innovation has also dramatically changed the world of oil production
From the demand-side in the last decade, the emergence of hydraulic fracturing methods of production dramatically altered production patterns. With the changing role of US shale oil production, it is unlikely that OPEC will have the same ability as in the 1970-2010 period to independently manipulate oil prices.
In the 2020s, the disruptive change may appear from the demand side of the equation. Oil is about three-quarters used in its refined state as a transportation fuel. Technological change may dampen demand for oil as transportation fuel efficiency makes great leaps forward. And, further technological innovations in alternative energy sources are likely to put continuous pressure on global oil prices and make traditional oil valuation models unreliable. It is obvious that underlying fundamentals have changed. It is not so obvious when and how risk management approaches will adjust.
The developed world is a major contributor to global instability
In the mature, industrial economies, the widening income gap creates large social impacts, resulting in the potential for resource misallocation. In the long term, a substantial segment of the population will lose confidence in government, eroding social cohesion. With positive growth and low unemployment rate statistics, analysts will often neglect the depths of the divisions that occur underneath the average numbers. Wealth and income gaps are widening at an accelerating pace, which can become substantial fuel for social volatility.1 Unfortunately, there is little monetary policy can do to narrow the wealth and opportunity gap.
Additionally, ageing populations are a source of social change in the developed world. For example, the population in the US is ageing rapidly with over 75 million Americans, or approximately 25% of the US population, will turn 62 or older by 2020 (www.census.gov). An ageing population entering retirement in the US, Europe, and Japan desires predictable income from their nest egg. Growth is still a must for underfunded pension funds and retirees who have not saved enough.
Finally, we note that the number of displaced persons around the world is at record high levels. The refugee crisis from Syria, the rest of the Middle East and Africa adds a new variable and increased level of tension – economically and culturally. Germany’s Chancellor Merkel’s belief that the refugees will provide a much-needed source of low cost labour when the European population is declining and aging at the same time, is unlikely to pan out in the short run. Instead, Germany is bursting at the seams trying to effectively integrate the more than a million refugees who crossed into Europe since 2014; making the recent migration the largest global refugee crisis since WWII.
The speed of corporate destruction has added to the sense of uncertainty, if not equity volatility
The average public company lifespan has declined sharply from the 1950s when the lifetime of an S&P500® company was about 60 years, before it was acquired, failed, or otherwise dropped from the horizon. In the 2010s, corporate lifespans in the US had declined to about 20 years, reflecting the powerful forces of economic disruption.2 And, Sante Fe Institute faculty member, Geofrey West, in a book entitled Scale, takes a look at the maximize size and length of life of companies and cities from the perspective of a natural scientist, adding extra depth to the changes impacting the economic behavior of corporations.
Why rising uncertainties co-exist with low volatility
When you place the current long list of market worries into the context of the long-term drivers of uncertainty, one may be confused as to why rising uncertainties are able to co-exist with low volatility. Essentially, we need both to appreciate the drivers of uncertainty as well as to examine the behavioral patterns related to reacting to uncertainty. The science of fear often sees patterns of behavior that bear a strong resemblance to chaos theory [Chaos: Making a New Science, 1987, by James Gleick], and these observations may help explain the conundrum of high levels of uncertainty co-existing with low levels of market volatility.
Pretend you find yourself walking down a deserted road late at night, and you are more than a little concerned about your safety. You hear footsteps behind you. You keep on walking. The footsteps are getting closer. Your fear level is rising, and yet you keep on walking. As the footsteps get ever-nearer, perhaps you hear a sound or some catalyst, your fear reaches a point where you face a decision to turn and confront the challenge (if there is one) or run away. Once you choose, there will be no going back.
These are among the types of decisions analyzed by chaos theory. Rising fears, or uncertainties, do not trigger a change in behavior. A reaction to the rising fears takes a catalyst; fear or uncertainty alone is not a cause of volatility. In our example, the footsteps get so close as to force a decision about what action to take. And, once the decision is made, you are committed to the new path. By way of another illustration, the same thing happens on a ski slope. You are at the mountain top and resting on your skis peering down the steep expert slope. You could take the bunny slope down or you could push off on a wild ride. Once the decision is made to tackle the steep slope, there will be no turning back.
What we observe is that the uncertainties are well appreciated, from technology, demographics, social change, as well as from the current policy issues such as taxes, trade, and monetary policy. The catalyst only arrives when something actually happens that changes the consensus view from worrying about uncertainties to taking actions to manage the risks associated with the potential market-moving events.
In 2017, despite the uncertainties, the global economy moved forward. The US remained on a path of 2% real GDP growth. Europe and Japan gained a little economic momentum. The real improvement in the global economy came from the developing world. China may have added to its massive debt loads; however, the economy kept on growing. Inflation in the major countries remained subdued. Brazil exited a deep recession. Higher oil prices helped the Russian economy. With economic activity moving forward and without a catalyst, market participants ignored the uncertainties, kept on walking, and volatility was relatively low.
Risk management implications
Low volatility by historical standards, relatively benign markets, and our general inability to estimate the timing, magnitude or even the nature of a coming catalytic event, however, does not mean that risk management should be passive. There was considerable evidence that risk managers were actively involved in addressing the challenges they faced. Indeed, in 2017, open interest in a number of CME Group products, from Treasury bonds to oil to copper to cattle, shot to record highs. The Commodity Futures Trading Commission’s (CFTC’s) commitment of traders’ reports showed heightened short open interest activity from commercials and producers as they hedge risks in commodity production. Cash levels at many major corporations were extremely high, suggesting a cautious approach to new ventures. Investors for some time had moved in the direction of passive, index-based securities, rather than taking aggressive stock-picking risks. Volatility may have been low in 2017, but market participants were on the alert.
Here is our summary of potential risk management solutions for managing heightened uncertainty while volatility remains low.
More sophisticated use of options can help mitigate event risks
On a basic level, options strategies are especially well-suited for managing the risks of uncertainty even when volatility is low. As uncertainty rises, so does the risk, even if the probability is low, of a large, quick change in market prices. This price gap risk (up or down) is not the same as volatility. Traditional, simple options pricing models, such as the original Black-Scholes options pricing model, assume price gap risk does not exist – allowing for a clean interpretation of implied volatility. This approach does not work well in rising uncertainty conditions when event risk generates more highly skewed and sometimes bi-modal probability distributions.
Traditional models do not adequately account for uncertainty because markets exhibit exogenous characteristics
Take investment analysis as an example, the traditional model focuses on the valuation and the growth analysis of companies and industries. But other social political factors, such as financial regulations, and military conflict, could be the main drivers for certain periods, and cause extreme and frequent tail risks. Uncertainty in the global environment makes traditional valuation models unreliable.
Dangers of ignoring context in a world of rising uncertainty should not be ignored
The underlying causes of structural change may take a long time for markets to accept the new reality. Asset managers cannot afford to ignore exogenous risks, because the game-changing catalyst could appear at any time. Flush global liquidity suppressed market volatility, even with global uncertainty at heightened levels. This is a prescription for rising probabilities related to event risk.
Static correlations do not provide diversification
When “black swan” types of events occur, intra-asset class correlations spike, which illustrates the interconnectedness of securities with similar risk characteristics even if their cash flow sources are strikingly different. A recent example form 2016 is Brexit. The pound crashed leading to an emerging market FX sell-off. Meanwhile, the dollar rally impacted the ability of emerging markets to pay off US dollar-denominated debt. In this case, for a short period of time, uncertainty led to risk aversion, with a larger proportion of investors seeking a flight to safety.
There is a strong case for thematic portfolio construction and risk management
All of these challenges and ideas coming from the co-existence of rising uncertainty and low volatility point to the need for thematic-based financial engineering. The long-term drivers of uncertainty provide the context. These themes generate the economic and political conflicts that create short-term, event risk probability distributions that may be highly skewed or even bi-modal and may dramatically shift correlation structures under certain scenarios. Working with themes instead of assets is not a new idea; it is just more important than ever because of the risks of price gaps, shifting correlations, and binary outcomes.