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Markets and Black Swans

April 11, 2020

Markets and Black Swans

Markets and Black Swans

I began studying complexity theory as a consequence of my involvement with Long-Term Capital Management, LTCM, the hedge fund that collapsed in 1998 after derivatives trading strategies went catastrophically wrong.

After the collapse and subsequent rescue, I chatted with one of the LTCM partners who ran the firm about what went wrong. I was familiar with markets and trading strategies, but I was not expert in the highly technical applied mathematics that the management committee used to devise its strategies.

The partner I was chatting with was a true quant with advanced degrees in mathematics. I asked him how all of our trading strategies could have lost money at the same time, despite the fact that they had been uncorrelated in the past.

He shook his head and said, “What happened was just incredible. It was a seven-standard deviation event.”

In statistics, a standard deviation is symbolized by the Greek letter sigma. Even non-statisticians would understand that a seven-sigma event sounds rare. But, I wanted to know how rare. I consulted some technical sources and discovered that for a daily occurrence, a seven-sigma event would happen less than once every billion years, or less than five times in the history of the planet Earth!

I knew that my quant partner had the math right. But it was obvious to me his model must be wrong. Extreme events had occurred in markets in 1987, 1994 and then 1998. They happened every four years or so.

Any model that tried to explain an event, as something that happened every billion years could not possibly be the right model for understanding the dynamics of something that occurred every four years.

…click on the above link to read the rest of the article…

“The Market Is On The Edge Of Chaos, A Zone Where Rare Events Become Typical”

February 3, 2018

“The Market Is On The Edge Of Chaos, A Zone Where Rare Events Become Typical” 

According to Fasanara Capital, which has long argued  that the market’s systemic fragility is approaching its breaking point, markets stand at a critical juncture, ready to snap, as the following note from Fasanara’s Francesco Filia lays out.

* * *

The Market System Is Tight In All Directions

The Four Pillars Holding Markets Up Are Strained, All At The Same Time

Viewed as a combination of intertwined components, each component is showing growing signs of pressure and seem to be running out of road for further advancing. The synchronicity of them, more than any single component taken independently, is what should draw attention, as it compounds systemic risk.

Here are the four components, characterizing the basin of chaotic attraction for markets nowadays:

What happens when the system is tight in its key possible directions of expansion? That it expands no more. Stochastically, on one of the components a tipping point is reached, which jumpstarts the autolytic effect, spreading back through the vectors of the complex system, and snapping the unstable equilibrium into an alternative stable state. That is our thesis.

In this recent interview, we discuss the impending tipping points for markets due to a synchronicity of excess valuations, excess indebtedness, excessively low cash balances and a drawback in excessive public flows.

Let’s give a cursory look across the four components. Again, the list is by no means exhaustive, but rather a work-in-progress (seemingly endless) collecting of data points, following on to our previous work of ‘a long list of anomalies’ here and here.

…click on the above link to read the rest of the article…

Panarchy: Implications for Economic & Social PolicyHumanity’s Test

December 3, 2014

Panarchy: Implications for Economic & Social PolicyHumanity’s Test.

Background 

Panarchy is a model that seeks to explain the evolution of complex systems, developed firstly by Buzz Holling through his observation of the adaptive cycle of forests[1]. The forest cycle follows a process of growth/exploitation, conservation, release and reorganization/renewal. At first, there is rapid growth as new species establish themselves in a recently disturbed environment. As the vegetation becomes denser, and the linkages within the system proliferate, the forest moves into a slower-growing state of conservation. It becomes increasingly stable within, and highly adapted to, a limited number of conditions. Efficiency, through the reuse of existing structures and increased connectivity, is traded for lower resilience. A disturbance that exceeds the reduced bounds of resilience then causes the forest to “crash” to a simpler state that releases the material and energy accumulated in the earlier adaptive phases. A highly uncertain phase of renewal can then start, during which novel combinations of species may establish themselves. These can then rapidly develop during a new growth phase. This adaptive cycle has been found to operate across many different natural systems.

Panarchy model

figure 1: Panarchy Model from The Sustainable Scale Project. Accessed at http://www.sustainablescale.org/ConceptualFramework/UnderstandingScale/MeasuringScale/Panarchy.aspx

The Panarchy model accepts the fundamentally dynamic nature of ecosystems, and moves away from the previous assumptions of linear and predictable natural systems that could be managed through actions targeted at one variable, such as the maximum sustainable fishing catch. Instead a panarchy approach accepts that components of complex systems may actively adapt to changes within their environments, creating surprising outcomes. Ecological systems are non-linear, and capable of moving from one stable state to another, very different, one. Within an overall system there are nested sets of adaptive cycles, with the larger cycles operating more slowly than the smaller ones. The different cycles can interact, with the larger ones tending to play a stabilizing role. At a critical point though, changes at different scales may interact and reinforce each other leading to systemic collapse.

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Olduvai IV: Courage
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Olduvai II: Exodus
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