Risk Update – November 2021

Most will by now be aware that both the Federal Reserve Chair, Jerome Powell, as well as the US Treasury Secretary (a former Federal Reserve Chair), Janet Yellen, have officially announced the retirement of the word “transitory” in terms of how they describe the, now deemed to be “persistent”, rises in their various price measures, eg PCE and CPI. We have been mocking their ongoing use of the word “transitory”, in their justification of maintaining all-time extreme levels of accommodation, going back to early this year.

In our April 2021 Update https://convex-strategies.com/2021/05/21/risk-update-april-2021/ we said “ The Fed and their mouthpieces continue to swear it is all transitory and due to base-effects.” Then further, “The current bout of measured inflation, along with the far more severe actual inflation of things like lumber and copper and gasoline and corn and houses and cars and cryptos and equities, may or may not be transitory. Regardless, it would seem, at the very least, to raise questions as to whether we should be on the most extreme accommodative monetary policy setting, along with most aggressive fiscal policy support, in known history. Might some sort of hypothetical “neutral” setting make some sense?”

We expanded on this in our May 2021 Update https://convex-strategies.com/2021/06/17/risk-update-may-2021/, noting how previous similar spikes in their price index measures (aka “inflation”) had indeed been transitory, but had clearly aligned to policy tightening by the Fed followed by sharp declines in equity markets. In a very out-of-character twist, we opined that maybe “this time is different”. Maybe the Fed (et al) would continue to ignore their own price stability targets, justified with their weak “transitory” New Speak, and we would not get the mean reversion of pricing indices that had historically been the case when these sorts of spikes were met with a traditional tightening response, as opposed to the current spike being met with unprecedented levels of continued accommodation.

Not surprisingly, we were right! It turned out that all-time low policy rates, paired with all-time extreme asset purchases by central banks, along with all-time large fiscal stimulus programs, did not result in a mean reversion of price indices. Quite the opposite, in fact. So now, after running what was admittedly as large a policy mismatch as possibly imaginable, the Fed has conceded and intends to start reducing the pace at which they add assets to their balance sheet, aka “tapering”. The other similar example, the ECB, intends to do nothing different, sticking with their current level of all-time most extreme monetary accommodation. Surely that won’t have any unpleasant outcomes……

Figure 1: PPI y-o-y% Eurozone (blue), Germany (white), Italy (purple), France (orange)

Source: Bloomberg

Chair Powell, in comments to the Senate Finance Committee, justified their failed projections around the presumed “transitory” nature of “inflation” thusly:

I think what we missed about inflation, was we didn’t predict the supply-side problems, and those are highly unusual and very difficult, very non-linear, and it’s really hard to predict those things, but that’s really what we missed, and that’s why all of the professional forecasters had much lower inflation projections.Jerome Powell to the US Senate. 30 November 2021.

We might, again, challenge the sincerity of this statement. We noted as far back as our June 2020 Update https://convex-strategies.com/2020/07/17/risk-update-june-2020/ the unprecedented acceleration of M2 Money Supply in the US, what we consider a fair proxy for actual inflation, ie. the growth of money and credit. One need not go too far back in time to find examples of central bankers arguing that their extreme policies were indeed intended to ignite rises in their price stability measures, and presumably one such feedback loop might be expected to be via acceleration in actual inflation.

Below is a simple view where we have lagged the y-o-y% of the PPI and CPI indices by 10 months and showed them along with the y-o-y% change of M2 Money Supply. We have thrown in, as well, the y-o-y% change of the Shiller Home Price Index. Does anyone seriously believe they were “surprised” by the non-transitory nature of this year’s increases in their price indices? Do we really believe it was all just unpredictable supply-side problems?

Figure 2: US y-o-y% M2 (white), PPI 10mth lag (orange), CPI 10mth lag (blue), House Price (purple)

Source: Bloomberg

Likewise, the ECB lays out within their “inflation” forecasts on their website the idiosyncratic causes of the, still assumed to be transitory, overshoots in their price stability measure:

“Inflation is expected to average 2.2% in 2021, driven by temporary upward factors. These include: a rebound in energy inflation amid strong base effects; strong increases in input costs related to supply disruptions; one-off increases in services prices as COVID-19-related restrictions ease; and the reversal of the German VAT rate cut. As these factors fade from the beginning of 2022 and temporary imbalances between supply and demand ease, HICP inflation is expected to decline to rates of 1.7% and 1.5% in 2022 and 2023, respectively.”

https://www.ecb.europa.eu/pub/projections/html/ecb.projections202109_ecbstaff~1f59a501e2.en.html#toc6

Again, they want us all to believe that it was unforeseeable. Below, we again show the y-o-y% change of Eurozone M2 Money Supply, as a proxy for true inflation, and the y-o-y% change of their HICP Price Index, this time with a 9mth lag on the HICP number. Turns out, M2 might have been a good predictor of what was to come.

Figure 3: Eurozone y-o-y% M2 (white), CPI 9mth lag (blue), House Price (purple)

Source: Bloomberg

At the same website link above, the ECB has this picture with their forward-looking forecasts for y-o-y% changes of HICP.

Figure 4: Eurozone HICP y-o-y% and ECB Forecast

Source: European Central Bank

We can look at the up-to-date numbers and replicate the forecast portion as below. Not looking great on those forecasts.

Figure 5: Updated Eurozone HICP y-o-y% (white) and ECB Forecast (red)

Source: Bloomberg

Yet, as we noted in last month’s Update https://convexstrategies.com/2021/11/19/risk-update-october-2021/, they “assure us that their precision handling of all the knobs and dials will smoothly guide this incredibly complex system to the desired future outcomes, and yet claim no impact of their past actions on the current circumstances. To them, the past evolves with a total randomness, a series of unforeseeable exogeneous shocks. The future, however, is perfectly within their control.”

The current overshoot in their pricing stability measure has nothing to do with their past, and still current, policies of extreme monetary accommodation and the subsequent historically large acceleration in money growth. It is merely the result of unforeseeable supply constraints and other factors related to the Covid pandemic. Yet going forward, and with no adjustment to their policies, they expect to guide inflation quickly back down below their randomly chosen target level.

Our comments on this subject from last month seemed somehow familiar and we did manage to track down where we had seen them before.

We are ready to accept almost any explanation of the present crisis of our civilization except one: that the present state of the world may be the result of genuine error on our own part and that the pursuit of some of our most cherished ideals has apparently produced results utterly different from those which we expected.Friedrich A. von Hayek, The Road to Serfdom

As you would expect from a Nobel Prize winner, Mr. Hayek says it much better than we ever could. The above quote is one of many examples that you could find from Mr. Hayek that you would swear were being spoken live today from a wise analyst of the current nature of things. If you haven’t done it, you really should make the time to read The Road to Serfdom. Not the lightest read you will ever pick up, but uncanny in its perpetual relevance. If you are like us, you will find yourself flipping back and rereading paragraphs and pages stunned that it was written 75 years ago. It is a bit of a mind-bender.

It is no great trick to find other examples where accelerated growth in money supply could have been treated as an indicator for future rises in pricing indices. Australia and South Korea give their own versions of the same impression.

Figure 6: Australia yoy% M2 (white) PPI 10mth lag (orange) CPI 10mth lag (blue) House Price (purple)

Source: Bloomberg

Figure 7: Korea y-o-y% M2 (white), PPI (orange), CPI (blue), House Price (purple)

Source: Bloomberg

Going back to the core of the fiat reactor, we can see over time how “actual inflation” (as a proxy, the compounding line of the M2 Money Supply Index) has fed through into prices and how the acceleration since the “Black Swan” response to the Covid pandemic are universal across various price measures, eg. equities, houses, consumer prices. Over this 20yr time horizon, you will notice the S&P has a “beta” of pretty close to 1.0 with money supply.

Figure 8: US M2 (white), S&P 500 (yellow), Home Price (purple), CPI (blue). 2001-2021. Normalized

Source: Bloomberg

In case you think we are “gaming” our chosen time horizon, below we expand it to 60 years. Still the same game. We leave readers to consider for themselves whether they feel that the near perfect passthrough of actual inflation to financial asset inflation is incidental or intentional. Either way, it is hard to argue that it is anything other than the most explicit driver of wealth disparity in society, though those driving it certainly do try to argue otherwise.

Figure 9: US M2 (white), SPX (yellow), CPI (blue). 1961-2021. Normalized.

Source: Bloomberg

As our regular readers know, we very much see the world through the lens of Self-Organized Criticality (if you don’t know, please read our August 2021 Update https://convex-strategies.com/2021/09/22/risk-update-august-2021/). Complex systems organize themselves into unstable states of disequilibrium and inevitably reach a critical state from which they rather harshly readjust back to a moment of equilibrium, aka Sandpile Theory. It is, as Per Bak named the book, how nature works.

In our view of the world, imbalances build up over time, with frequent intermediate avalanches here and there that, as Bak says, “don’t add up to much”, until fragility and connectivity reach a critical state and eventually an avalanche triggers that interconnectivity and the sandpile rather catastrophically returns to its equilibrium state. This is the normal function of things. What is abnormal are outside agents trying to prop up and sustain unstable sandpiles that are in their critical states. In the current world of financial market and economic imbalances, it is probably safe to assume that the various manipulations that have accumulated – zero interest rates, unprecedented asset purchases by central banks, all-time extremes of government debt after endless rounds of bail-out and stimulus packages – are making every effort to keep the increasingly fragile sandpile from finding its natural equilibrium state.

What market participants tend to consider Black Swans are merely the inevitable rebalancing of fragile systems. They are only considered Black Swans due to the flawed measurements of the Normal/Gaussian thin-tailed distribution world of simplified financial mathematics. It is what allows for the trusty old friend of the fiduciary: “nobody could have seen that coming”. For those cognitive of the power law nature of complex systems, the out-sized impacts of infrequent interconnected avalanches are better termed as Grey Swans and would become increasingly relevant as the fragility of the system grows. This goes back to our forest fire analogy; the potential scale and likelihood of a catastrophic fire expands as the amount of combustible material on the ground grows. Common sense, really.

All of the Black Swan/Grey Swan rhetoric is inherent in what we refer to as the “Challenge of Measurement”. Even though the financial world knows it is wrong, they continue to use the simplified tools they have developed. As we have previously discussed, it is the “Streetlight Effect”, we look for our keys under the streetlight, not where we dropped them. Few have said it more clearly than Friedrich von Hayek in his Nobel Prize acceptance speech. If you are truly interested in issues of complex systems, you must read this speech. It is Bak, Mandelbrot and Taleb all wrapped up in a mere 10 pages.

And while in the physical sciences the investigator will be able to measure what, on the basis of a prima facie theory, he thinks important, in the social sciences often that is treated as important which happens to be accessible to measurement. This is sometimes carried to the point where it is demanded that our theories must be formulated in such terms that they refer only to measurable magnitudes.”

https://www.nobelprize.org/prizes/economic-sciences/1974/hayek/lecture/

Given our view that the current sandpile is highly imbalanced and naturally biased towards reversion to a steadier equilibrium state, all else equal, the expected near-term outcome would be a correlated unwind of unstable, undercapitalized risks in the system. We have seen over the past dozen or so years how relatively ordinary, if infrequent, events, eg. a failing investment bank or a spreading novel respiratory virus, can provide sufficient ex-post justification for the critical state tipping point of reversion to equilibrium. Of course, those ex-post assignations of blame are mere justification for the cognitive dissonance of having not recognized the ex-ante fragility that was already in place.

As Nassim Taleb so brilliantly puts it, “Black Swans are observer-dependent: a Black Swan for the turkey is a White Swan for the butcher”. The butcher knows the inevitable end-state of a plumped up sandpile. What we don’t know is what lengths outside agents will go to maintain ever greater levels of disequilibrium. From the perspective of the butcher, the Grey Swan events (we assume all butchers are aware of the appropriate use of power-law distributions) and their potentially outsized scale impacts are the actions of the outside agents and the subsequent results. Below we break out a little visualization, using the y-o-y% change of the NASDAQ 100 Index, of some past Grey Swan Events, focusing on the Federal Reserve for this example as the principle outside agent.

Figure 10: NASDAQ 100 Stock Index y-o-y% and Grey Swan Policy Events

Source: Bloomberg

Market participants have time and again under-participated in the potential outsized compounding impact of these events as they have generally been unprepared for, or overly cautious of, the inevitable connective series of avalanches that occur as unstable sandpiles revert towards equilibrium. The standard market solution isn’t risk management, but rather risk reduction (aka “balanced portfolio”): foregoing upside to reduce downside. In our race car analogy, they are driving at 60% capacity on an assumption, based upon a flawed Gaussian extrapolation of recent historical frequencies, that there won’t be any corners sufficiently sharp that they will crash. As noted above, they are unprepared for a corner sharper than the 95%tile of recent occurrences, so get wiped out before the Grey Swan event of another never-before-seen central bank intervention; and/or they are overly cautious, not having sufficient power allocated to the engine to fully participate in the outsized scale of the aftermath of that intervention should they survive the short and tight corner. Risk management, on the other hand, is the premise of having truly efficient brakes, allowing you to navigate the sharpest of unexpected corners, while being willing and able to ‘red line’ the engine when the track straightens back out.

From the perspective of the butcher, what could be the next Grey Swan event? In our above chart we have proposed the next phase of QE, what we have labelled “QE Tech ETFs”. In the most recent Grey Swan event, what we have labelled QE Everything (it should really be QE Everything Fixed Income, but we were tight for space), our chosen index of upside participation risk, NDX 100, rallied circa 100% over the next year. Racers with good braking ability will have handled the inevitable connected avalanching of the sandpile (blamed on the Covid pandemic and often wrongly described as a Black or Grey Swan itself) and come out the other side with engines roaring post the unprecedented leap into Crazytown of QE Everything. (We won’t bother to create a Normal Distribution and show the percentile of where the March 2020, and onwards, actions rank in terms of Federal Reserve interventions, but trust us it is 99.9%tile). https://www.federalreserve.gov/newsevents/pressreleases/monetary20200323b.htm

Now that they have seemingly lost control of the topside of their chosen measures of price stability, with QE Everything spiking real yields to all-time lows, they are talking about backing away from the current slate of sandpile supporting policies. Should the sandpile do what they inevitably do, ie seek a stable equilibrium, while price stability issues are still a societal (and political) concern, what can the Fed do? Well, the uber-duration assets that likely get hit the hardest, and potentially represents one of most critical fingers of fragility in the sandpile and risks triggering a chain reaction of connectivity, are the heretofore high-flying tech stocks. It isn’t hard to imagine a Federal Reserve, that has shown the willingness time and again to do whatever-it-takes to preserve and grow the disequilibrium of the sandpile, but who is reluctant to continue to manipulate interest rates lower, who dials up a whole new level of QE and, like they did across a range of debt products in 2020, fires up the printing presses to provide direct support to Tech ETFs. Sound crazy? Sounds like a Grey Swan.

Of course, we of all people know that you cannot predict or model Black or Grey Swans. That is the whole point. What you can do is observe the convexity of your investment strategy to “Participate and Protect”. Have good brakes so that you can, safely, drive faster. As ever, we can visualize it with simple examples in Scattergram or Compounding forms where what we are looking for, in our ultimate objective of terminal performance (ie. compounded capital), is acceleration in the good bits and deceleration in the tricky bits. For the Risk Reducing strategy we will use a Balanced Racer of 57% S&P500/43% US Treasury Bond Index. For the Risk Managed Strategy will use a Barbell Racer of our good old Always Good Weather Portfolio of 45% Nasdaq/40% S&P500/40% CBOE Eurekahedge Long Volatility Index. We have adjusted these weightings to equalize the downside deviation risk of the two portfolios, per the work that we showed in our September 2021 Update (https://convex-strategies.com/2021/10/19/risk-update-september-2021/). To equalize the risk, you need to de-risk the traditional 60/40 portfolio down to 57/43 while adding additional topside exposure to our usual 40/40/40 Always Good Weather to nudge it up to 45/40/40. Those adjustments alone should tell you something about the opportunity cost of using the poor risk mitigating efficacy of the fixed income component. How has that race gone over the last couple of years of an attempted return to equilibrium of the sandpile met with the Grey Swan of QE Everything? As you would expect, the racer with the better brakes, Barbell Racer, has fared significantly better. The Barbell Racer was better prepared for the inevitable connective series of avalanches (unexpected sharp corner) allowing far more speed/participation after the Grey Swan interventions of the Federal Reserve.

Figure 11: Barbell (blue) vs Balanced Racer (red). Jan2020-Nov2021. Scattergram and Return Dist.

Source: Convex Strategies, Bloomberg

Figure 12: Barbell Racer (blue) vs Balanced Racer (red). Jan2020-Nov2021. Compounded Line

Source: Convex Strategies, Bloomberg

Figure 13: Barbell (blue) vs Balanced Racer (red). Jan2005-Nov2021. Scattergram and Return Dist.

Source: Convex Strategies, Bloomberg

Figure 14: Barbell Racer (blue) vs Balanced Racer (red). Jan2005-Nov2021. Compounded Line

Source: Convex Strategies, Bloomberg

We think markets and economies follow the dynamics of Complex Adaptive Systems/Self-Organized Criticality. We think sandpiles that have evolved into states of disequilibrium will inevitably tend towards catastrophic avalanches. We think policy makers will continue to go to extremes to try to prevent the sandpile from returning to a natural state of equilibrium. We think it is fun to imagine how, when and what these events may transpire. Fortunately, we know convexity is the answer to well managed investment portfolios and investors shouldn’t be relying on anybody’s imaginations.

For a complex natural shape, dimension is relative. It varies with the observer. The same object can have more than one dimension, depending on how you measure it and what you want to do with it… Think of dimension, not as an inherent property, but as a tool of measurement.

Benoit Mandelbrot, “The (Mis)Behavior of Markets”.

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