Wagner's lessons
Quantifying the unquantifiable: how much did risks change?
Photo: Danielle Tunstall
A fortnight ago, a well-armed private army marched, largely unopposed, on the capital of a nuclear-armed, globally strategic state that is an essential producer of a long list of resources critical to the functioning of the global economy. Yegeny Prigozhin’s challenge to Russian central authority was as short lived as it was bizarre and markets opened the following Monday with an audible yawn: beyond a 6% fall in the Russian rubble, few market prices have moved since in ways that suggest any concern.
Markets have a hard time pricing anything beyond the base case: most trading is a dualistic struggle between the consensus and the anti-consensus. The combination of the unusually benign post-WWII world of Apex neoliberalism and ever-increasing capacity to quantify and compute has accentuated markets’ focus on mean, or average, outcomes. Even derivatives – “what-if” markets – ruthlessly converge to average break-even volatilities. Events that cannot be quantified often are ignored, not because market participants are unaware of the risk – who wasn’t glued to their favorite news source 25-26 June? – but because they can’t conceive of how to incorporate events outside their models’ parameters or frameworks for base and alternative cases.
Yet, Covid, Russia’s invasion of Ukraine, and the recent exponential leap forward in artificial intelligence capabilities all have reminded us that we live in a highly nonlinear world of deep Uncertainty: i.e., non-quantifiable risk. Events like the Wagner rebellion that threaten Complexity cascades – a chain reaction of systemic failures or nonlinear realignments – only heighten Uncertainty, “fattening the tails” of the probability distribution, potentially in inconceivable dimensions by unknown magnitudes: “unknown unknowns” to use Donald Rumsfeld’s memorable phrase.
The Wagner revolt confirmed that Russian state instability, as I warned last year in Clash of the Themes, is one of the scarier unknown unknowns threatening the current economic expansion. Simultaneously it discretely raised the probability of instability. Because the probability remains low and uncertain, the lack of movement in asset prices since or movement in the wrong direction (Figure 1) is unsurprising. But consistent near-median pricing of risks across derivatives markets (Figure 2) makes far less sense and suggests the potential for mispricing.
Not everyone can exploit the mispricings I discuss here: volatility traders, especially those with a cross-asset focus, are best positioned to exploit them. However, asset allocators will derive the most substantive gains from portfolio insurance based on the mispricings. Even non-specialists can benefit from the main message of this note: background risks have shifted discretely higher while markets have failed to price the change; hence some degree of portfolio risk reduction is appropriate if you lack access to cost-effective hedging strategies.