In our most recent guest blog for the Quant Conference, we discussed ‘The Pursuit of Edge’ and how the quest for alpha for today’s quants is constantly evolving. As investment professionals have discovered from the Covid-19 fallout, an edge that can be successfully executed during a financial crisis can not only be desirable, but also an essential investment strategy.
Andrew Perrins, CEO and Founder of Savvy Investor, outlines how the study of historical financial crises, their progenitors, alleged reflexive feedback loops and ‘anti-diversification’ philosophies can serve as useful starting points for quants wishing to ‘forward model’ the future
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“When things get volatile, they get complicated”.
Crisis Alpha
Having witnessed a decline in volatility over the last decade, global financial markets are now experiencing a measurably higher volatility regime. For those caught in the mêlée of ‘limit ups’ and ‘limits downs’, the feeling may be one of entrapment in a Wild West gun fight of statistically aberrant price swings. For the experienced quant however, these machinations might be viewed as lessons in edge where signals may be parsed through the noise.
When the dust settles after a crisis, stock market legends are born. Soros, Druckenmiller, Eisman, Burry and more recently, Ackman, are names that are synonymous with deriving remarkable success from financial calamity. So, in a world of full of bright financial minds, why does it appear that only a few live long in infamy?
Part of this answer may be due to one aspect of ‘crisis alpha’ espoused by the term’s coiner, Kathryn Kaminski, who famously said: “When things get volatile, they get complicated”.
Despite financial crises being subject to complex forces, our crisis alpha progenitors proved their ability to cut through the chaos and harvest gains at a rate many times their initial risk. Indeed, it may be argued their respective alphas could be achieved through the combination of two key skills:
1. Foresee the crisis
2. Structure any pre-crisis trade(s) as efficiently as possible
Reflexivity
Although those skills may be prerequisites for profiting in times of market stress, there are other phenomena that quants may wish to consider when designing a crisis alpha toolkit.
Today, the phenomenon of reflexivity, where market forces exert strong influences that lead to significant price feedback loops, is an area of study much vaunted by gurus such as Soros and Shiller.
For quantitative modellers wishing to sift through reams of time and sales data, this reflexivity phenomenon may be evident from Softbank’s alleged call option buying spree in US technology stocks during the summer of 2020.
Although an in-depth study of the ‘Nasdaq Whale’ event has yet to be published, some quant commentators have attempted to shed light on the supposed reinforcing feedback loop of a bid for tech stocks, fed by demand for tech call options, fed by option market makers wishing to hedge their books. Only time will tell whether reflexivity, perceived or actual, was the singular cause.
For quants with a science penchant, reflexivity and resonant frequency are discussed further in this rather engaging Ted Talk.
Anti-diversification
In times of market stress, seemingly disparate markets can move in tandem for no apparent reason. Fortunately, Robert Prechter’s ‘All the same market’ theory goes some way to explaining this phenomenon of an aggregate ‘short liquidity’ and ‘short the economic cycle’ thesis when a crisis manifests.
With equities, private equity, real estate, bonds, and commodities all exhibiting similar correlations during these periods, quants may ask wonder if traditional portfolio diversification principles should be applied.
Going against the classicists, Stanley Druckenmiller, a Soros protégé, has long advocated a maxim of ‘anti-diversification’. By concentrating his winners in a select number of trades, Druckenmiller’s unorthodox approach is congruent with impressive long-term performance, which the broader fund management industry has begun to adopt via Focused Funds.
Summary
As quant strategies evolve and machine learning attempts to ‘forward model’ future asset prices, the phenomena of crisis alpha, reflexivity and anti-diversification may serve as useful inputs in new quant research.
For those with foresight of the next financial calamity, it may be useful to keep in mind some of the key philosophies from the progenitors’ playbooks: When faced with a high probability of asymmetric pay-off, model it, structure it and lean in.
“When faced with a high probability of asymmetric pay-off, model it, structure it and lean in.”
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