MACRO ECONOMIC OUTLOOK
The Ukraine war, fallout from sanctions, hawkish sentiment among global central banks and gyrations in commodity markets add layers of uncertainty to what was already an uncertain environment for financial markets.
In this setting, forecasts are, at best, conditional and rest on a foundation of radical uncertainty (see article “Stuff Happens”). While we can quantify risk (i.e., options price implied volatility) and then assign probabilities (i.e., trading ranges) using statistical analysis, uncertainty, defined as ‘unknowable unknowns’, cannot be measured. That fact severely limits our confidence in evaluating potential outcomes and appropriate investment strategies.
Despite these shortcomings, we will discuss some of the risks that, we believe, will have the biggest impact on our client’s portfolios over the next six to twelve months.
Our view on growth and inflation is compromised by pandemic dislocations. The post-pandemic recovery is still in its early stages. Global economies are dealing with new variants, zero-covid policies serially disrupt supply chains and the Russian invasion has slowed the regional and global recovery. Ukraine is not only a large producer of grain but also an important supplier of parts for Europe’s auto industry.
Globalization has left us with complex interconnected logistics, in which even minor disruptions in raw materials and components have an outsized impact on output and prices.
Working from home has altered the real estate landscape. Preference for more space at a reasonable price has set off a migration away from city centers and office space in downtown cores has been slow to recover. How all this shakes out will be determined both by longer-term employee preferences and by corporate decisions on return to work.
We anticipate more significant expectation gaps within the industrialized world. Consumer prices in many countries were already above trends before the Ukraine war. The invasion exacerbated the situation causing further disruptions in inflation expectations. If these temporary and regional gaps become entrenched, we could see a de-coupling of longer-term inflation expectations resulting in a 1970s style wage-price spiral.
Given the tight U.S. labor market, it is not surprising that such a potential wage-price spiral weighs heavily on Fed policy. The degree to how far this spiral escalates will hinge on how long consumers are both willing and able to absorb higher prices.
We are already seeing some reduction in demand (note recent reductions in growth expectations) but longer-term inflation expectations and the impact that it will have on wage demands will rest on whether the thesis that these inflationary effects are transitory has legs.
One factor that bears watching is the sharp selloff in the Dow Jones Transportation Index (DJTI), down more than 13% since the beginning of April. The index gauges the performance of twenty U.S. trucking, railroad and airline stocks.
This selloff reflects an unusually soft truckload freight market during March that caught analysts by surprise. March is typically a robust period as shippers stock shelves in preparation for summer.
More disturbing is that a weak transportation sector is considered an early warning sign for an economic slowdown. Historically accurate… but in this case, extenuating circumstances may alter the relationship. Last year, companies loaded up on inventory fearing shortages and supply chain friction. Many of these same companies are still carrying excess inventory.
Softer load volumes could also mean consumers are pulling back amid high inflation. That may be true in some sectors, but the effect is not widespread based on data from the airline industry. Travel demand is rebounding strongly, and airlines have been able to pass on price increases to offset higher costs for jet fuel.
Subduing inflation at the expense of employment and GDP growth is currently the primary objective for global central banks. That’s significant, because in normal times central banks would look through the inflationary consequences of a supply-side shock. What makes this different is current inflation shockwaves were already percolating from a surge in post-pandemic demand.
For that reason, monetary policy is focused on preventing the second-tier effects of higher headline CPI, which could power already elevated inflation expectations. The downside of this strategy is the risk of a hard landing that could lead to a recession later this year or in 2023. While this is not our base case, given the demand side of the equation it is a risk we are monitoring.
Recession risk is particularly high across the European Union and Japan. Both regions are saddled with weak inflation dynamics and are more dependent on Russian energy. Despite these concerns, the European Central Bank (ECB) demonstrated at its March meeting that it remains hawkish and appears intent on removing accommodation.
The U.S. Federal Reserve (Fed) at its March meeting started a new tightening cycle by lifting the Fed Funds rate. At the same time, the Governors signaled a series of rate hikes through the remainder of this year, coupled with a plan to reduce the balance sheet by U.S. $95 billion per month.
The Bank of Canada has indicated they will follow the Fed’s hawkish stance. In March, the Bank of England raised rates for the third time in three months. Other central banks in both developed and emerging markets are on a tightening path given rampant inflation pressures.
The exception is China. Below-target inflation, a strong currency, and concerns about COVID-lockdown-disrupted growth have tempered monetary policy and make any tightening moves this year less likely.
Supported by central banks, governments globally provided sizeable backstops for business and consumers in the early days of the pandemic. As a result, deficits and national debts ballooned. Higher rates will increase the cost of financing that debt and limit any future fiscal measures to offset the pain on individual consumers and taxpayers.
On the other hand, Europe must navigate a much finer line. We expect further European stimulus will likely be in the form of increased defense spending. Significantly, Germany has recently agreed to increase their defense spending within NATO to 2% of GDP.
Unfortunately, defense spending takes time to become effective and will not offset the inflationary burden of higher short-term energy costs. Most likely, Europe will address this time lag through transfers and tax subsidies, although these will only partially offset the impact of higher energy costs on disposable income. The greater concern is the long-term impact of higher EU debt levels, which will limit future responses should a recession take hold.
We doubt the U.S. will deliver any major fiscal stimulus given the current political gridlock. The November mid-terms may well result in a Republican majority in the House and possibly in the Senate, resulting in further gridlock, which would limit fiscal easing for years to come.
While none of these scenarios benefit cyclical growth, they should help moderate inflation pressures. The inflation we are now experiencing is largely the inevitable result of dovish monetary policy and fiscal largesse from early in the pandemic. Simply stated… it takes two to tango.
Despite this array of uncertainties, our investment thesis remains relatively intact. In previous reports we focused on what we knew so far: higher short-term inflation and rising interest rates. We were looking for three to four rate hikes in 2022 and, perhaps, four additional hikes in 2023. We now believe that more rate hikes will occur in 2022 with fewer in 2023, with rates in line with our previous outlook at the end of this cycle. What’s changed is that we will likely get there quicker.
The takeaway is that higher rates depress bond prices, thereby impairing the risk mitigation benefits traditionally associated with fixed income assets. From a portfolio management perspective, it comes down to a question of duration.
Investopedia defines duration as a measure of the sensitivity of the price of a bond or other debt instrument to a change in interest rates. A bond’s duration is easily confused with its term or time to maturity because certain types of duration measurements are also calculated in years.
However, duration is a tool that fixed income analysts use to calculate how much the price of a bond with a set maturity date will move given a change in interest rates. For example, the price of a bond with a duration of fifteen years (that’s the typical duration for a bond with a thirty-year term to maturity) would be expected to decline by fifteen percentage points given a one percent rise in thirty-year rates. Similarly, a bond that matures in five years would typically have a duration of three years implying a three percent move in the bonds’ price given a one percent rise in five-year rates.
Risk reduction rests on the proposition that assembling a collection of different assets (i.e., bonds, stocks, and cash) with historically low correlations in returns can reduce variability within a portfolio. In a rising rate environment, equity and fixed income assets become highly correlated. Although bonds will move less because they are generally 30% less volatile than blue-chip equities, they will trend in the same (downward) direction.
We are not dismissing the diversification benefits of bonds, we are simply saying that in a rising rate environment, there may be better solutions – for example, reducing equity risk by employing option writing strategies.
Like bonds, the strategy of selling call options against a long stock position is statistically about 70% as risky as an outright long stock position. However, within the covered call strategy we can also select stocks like banks and insurance companies that may benefit from rising rates.
To provide some context, let’s consider an example. Suppose we own shares of Microsoft at say USD $295 per share. If we sold a July $305 call option, we would receive approximately USD $13.00 per share in premium. That USD $13.00 per share is taxed as a capital gain and obligates us to sell shares to the call buyer at the call option’s strike price (i.e., USD $305 per share). To summarize:
What we know with certainty is that one of three things will occur between now and the option’s expiration in July. Microsoft will rise, fall, or stay the same. The following table examines the results of all three outcomes.
To paraphrase an old Meat Loaf song: Two Out of Three Ain’t Bad; two of the three outcomes provide better returns than owning the shares outright. The only time you are better off owning the shares without selling a call option occurs if the stock rises substantially above the USD $305 per share strike price. In that situation we still earn the maximum profit from the strategy and in terms of a risk mitigation, we think this strategy is more effective in the current environment.
Value versus Growth
The other strategy that can mitigate risk in a rising rate environment is to shift emphasis from growth stocks to value stocks. Typically, we utilize a ‘barbell’ strategy that incorporates both value and growth plays through the business cycle. We overweight one end or the other depending on where we are today and where we think we will be at a future point.
At this stage, we believe that 2022 will be a second half story. The objective is to get through the first half with as little damage as possible and then build on that foundation in the second half of the year. The success of this approach will depend on the trajectory of inflation.
If inflation is, in large part, transitory as central banks are suggesting, then we will enjoy the benefits of the risk mitigation strategies during the first half and, ideally, benefit from the second half rebound.
In time, as we work our way through this rate cycle, bonds will become more attractive and play a more important role in your portfolios. At some point in 2023, we will likely re-set our asset allocation to shift our equity exposure back from value to growth while transitioning some of our equity exposure back into fixed income.
That time will come… just not yet!
Lord Mervyn King, a former governor of the Bank of England, is best known for reinvigorating the concept of “radical uncertainty,” which he set out in his book The End of Alchemy. Radical uncertainty refers to an exhaustive range of outcomes so profound that it is impossible to assign reasonable probabilities within any economic model. It is chaos theory on steroids. More generically, it can be explained using a censored version of a famous T-shirt… to wit: “Stuff Happens!”
To quote from King’s book (p. 304):
“In a world of radical uncertainty there is no way of identifying the probabilities of future events and no set of equations that describes people’s attempt to cope with, rather than optimize against, that uncertainty. … In the latter world, the economic relationships between money, income, saving, and interest rates are unpredictable, although they are the outcome of attempts by rational people to cope with an uncertain world.”
What makes King’s assertions so poignant is that they are coming from the mind of a mainstream economist – an ex-central banker who relied on data to optimize conditions that support economic growth by forecasting inflation, managing interest rates, and improving labor markets.
The original theory of radical uncertainty was espoused by University of Chicago professor Frank H. Knight in his 1921 book Risk, Uncertainty and Profit. The so-called “Knightian Uncertainty” set out to debunk the position that “risk,” could be quantified by attaching probabilities based on experience and/or statistical analysis. Knight argued that true “uncertainty” is unmeasurable because it represents the ‘unknowable unknowns’.
Unfortunately, Knight’s work was largely forgotten as subsequent generations of modern-day economists developed models built on Keynesian economic theory set out by John Maynard Keynes in his seminal book The General Theory of Employment, Interest and Money. Economists became focused on developing seemingly precise models that would attach probabilities to future outcomes based on past observations.
It took the failure to predict the 2008 financial crisis and the subsequent fallout to bring the theory of radical uncertainty back into focus. In short… stuff happens (Lehman, Brexit, Greece, climate change, Trump, Putin, and war). Such ‘unknowable unknowns’ led to regime shifts, rendering seemingly reliable empirical relationships obsolete and limiting the ability of any model to predict future events based on historical observations.
We are not suggesting that radical uncertainty is so pervasive that forecasting is futile. Particularly over short periods, where historical data can provide insight into future trends. But, and this is a big ‘but’, one must recognize that in an unstable environment, five-standard-deviation (i.e., highly unlikely) ‘black swan’ (completely unpredictable) events occur more frequently than statistical analysis would suggest.
The presence of radical uncertainty means that we must alter the normal probability distribution by increasing the potential for statistical “fat tail” outcomes. Think about a fat tail this way. When events with low probability occur, people tend to overestimate the chance that they will occur again. For example, insurance companies typically raise your rate immediately after you had an accident. However, statistically most people are less likely to have another accident having just experienced the trauma. Most of us change our driving habits, becoming more cautious.
Graphically, the fat tail distribution is the subjective dotted line on the accompanying chart. The dotted line attempts to measure radical uncertainty by altering the normal probability curve after an unusual event. Eventually, over time the dotted subjective probability line should recede to follow the normal distribution curve.
The fat tail was first envisioned as an economic theory by Robert Barro. He argued that investors will buy government bonds as protection against black swan events. This transition is meant to offset stock market chaos believing that government stability would be sufficient to at least pay the interest and eventually the principal obligation.
However, this is a theory that has never been tested because we have never experienced a generational (i.e., greater than 20 years) doomsday scenario.
Incorporating radical uncertainty within economic scenarios assumes that fat tail distributions are the norm and not the exception. It is not to dismiss the view that economic and market forecasts based on statistical/econometric models don’t make sense… they do. It is simply a recognition that economic models are based on structural stability which, in a post-pandemic world, doesn’t exist. To compensate, one must apply unthinkable “what if” scenarios in recognition that statistical analysis using past data is of little use deciphering scenarios in which there is no precedent.
This approach draws into question the value of the U.S. Federal Reserve’s forward guidance. If the future is radically uncertain, then the modern central bank practice of giving markets forward guidance may well be misguided. It would be wise to take as gospel the notion that any forward guidance is “data dependent” and as such, the FED’s policy for interest rates and balance sheet reduction, is no more than a conditional forecast. It begs the question: if central bank forecasts turn out to be wrong most of the time because “stuff happens,” is there a value in providing forward guidance in the first place?
When central bankers fail to acknowledge the existence of radical uncertainty beyond the “data dependent” nomenclature, it creates the illusion that the future is highly predictable. Doing away with the forward guidance might free up more opportunity for analysts to think… about the unthinkable.
Finally, there is a view that politics (i.e., populism), rather than the invisible hand of capitalism, is managing economies. Unfortunately, political action lacks the objectivity of business decisions, which is why radical uncertainty has become more acute than it has been for decades. Moreover, political variables are not incorporated into forecasting models, which means little credence is given to extreme outliers even though most outsized surprises are the result of short-sighted political whims.
Despite global economies being subjected to shocks resembling a game of whack-a-mole (Ukraine war, pandemic restrictions, inflation, supply chain friction) financial markets remain within an expanded trading range that implies a “steady but vulnerable” macro-economic tilt. Lurking in the background of elevated asset prices is mounting government debt, outsized consumer demand, limited returns from monetary policy and the rise of populism. These are the risks that we know, and they do not account for the radical uncertainty of the ‘unknowable unknowns.’ Hence our current investment strategy remains capital preservation and risk mitigation option strategies.
DERIVATIVES – The Good, The Bad and The Ugly
Let’s be honest… derivatives have a bad name. No wonder – derivatives have been blamed for most every financial collapse: programmed trading was responsible for exacerbating the 1987 stock market crash; unauthorized trading in Nikkei 225 index futures contracts brought 200-year-old UK based Barings Bank to its knees over a span of one month in 1995; currency futures led to the 1998 collapse of the Long-Term Capital hedge fund; and interest rate swaps were held responsible for the downfall of the mortgage market and subsequent 2007-2009 financial meltdown.
We think it appropriate to put (pun intended) derivatives into perspective since they are important tools in how we manage money. Derivatives, when used properly in the management of your portfolio, can both enhance returns and reduce risk.
First some background. Derivatives are secondary securities whose value is based (derived) on the value of the primary security, typically referred to as the underlying security.
According to Investopedia, there are two broad categories of derivative products: “lock” and “option.” Lock products (e.g., swaps, futures, or forwards) bind the respective parties from the outset to the agreed-upon terms over the life of the contract. On the other hand, option products (e.g., stock, index, interest rate, currency, commodity options) offer the holder the right, but not the obligation, to buy or sell the underlying asset or security at a specific price on or before the option’s expiration date.
Derivative contracts are ‘levered’ (i.e., a few dollars control many dollars) which is what appeals to speculative traders. And there lies the rub! Ex-post examination of financial meltdowns typically show they were caused by excess leverage not by the underlying instrument. Which means how one employs leverage determines whether a strategy is aggressive or conservative.
To employ a main street analogy, let’s assume you are purchasing a new home. When you agree on a price, you sign a purchase and sale agreement that includes a possession timeline. You put down a “good faith” deposit that is a down payment of sorts committing you to take delivery at an agreed upon date. In essence the purchase and sale agreement is a bonafide futures contract. Namely, a contract to take delivery of a product (i.e., the house) at an agreed upon price on a specified future date.
Now let’s look at this example in terms of strategy. Say the purchase price was $1,000,000 and your deposit was $50,000 (5% of the purchase price). If your intent was to sell (i.e., flip) the house before taking possession, the 5% deposit provides leverage that allows you to control a much larger asset for a short period of time (speculation). If you can flip the house for, say $1,050,000, you double your initial investment. If the house declines to say, $950,000, you lose your deposit and then some if it costs you extra to back out of the contract.
Of course, most home buyers intend to take possession of the house at the agreed upon date. The buyers finance the remainder of the purchase price on the closing date and live happily ever after. In this scenario, the purchase and sale contract is a conservative risk management tool because the buyers are locking in a price that they are happy with and will take delivery on the closing date.
When Barings Bank faced bankruptcy, it was because a rogue trader – Nicholas W. Leeson – leveraged a position with Nikkei 225 index futures. He was betting the index would rise when it continued to fall (see accompanying chart). Going back to our house example, Mr. Leeson was buying the equivalent of purchase and sales contracts on thousands of homes at the same time. The end began when the Nikkei plunged after the Kobe earthquake on 17 January 1995.
Leeson, who had speculated heavily on the Nikkei for the previous two and a half years, had exposed Barings to unlimited potential losses. By March 2nd, 1995, Barings had lost over U.S. $1 billion, which caused UK’s second oldest bank at the time to collapse under the weight of its short-term obligations. It was the same story with margin calls on Long-Term Capital in 1998 and, on a much larger scale, with the financial collapse in 2007 through March 2009.
The programmed trading fiasco on Black Monday in 1987 was not caused by leverage as much as a computer-driven hedge strategy using S&P 500 index futures. Computer-driven sell programs and a ticker tape that was running an hour late, exacerbated the decline that today remains the biggest one day drop in stock market history.
So, what have we learned from these examples? In all cases, it was not the derivatives that caused the problem, it was how aggressive traders employed derivatives as a speculative investment strategy or, in the 1987 meltdown, how managers replaced human engagement with algorithms designed to hedge downside risk.
Neither condition exists in our derivative strategies. In all cases we employ derivatives as risk management tools. Where we have employed derivative strategies that require us to take possession of a specific asset at a future date, we set aside sufficient funds to meet that obligation.
We sell unlevered call options against certain securities to earn additional income and when we do that, we own the underlying securities or have assumed a limited risk obligation (i.e., we have cash set aside to honor any purchase obligation) to own the underlying securities.
In general, we do not employ any leverage and, when we do, it is limited to 20% of the value of the pools we are managing. Which is to say, at the height of any strategy we never leverage our pools beyond 120% of their value.
Richard N Croft
 Chaos Theory is the branch of mathematics that deals with complex systems whose behavior is highly sensitive to slight changes in conditions, so that small alterations can give rise to strikingly divergent consequences.