18 So when measured in clock time, prices changes will have thinner middles and fatter tails, just like a cauliflower, a coastline, or a cosmos. 19 Subsequent studies have shown that this clock time / volume time distinction helps explain equity price dynamics, especially at times of market stress. For example, Easley et al (2011) show that the distribution of price changes during the Flash Crash was highly non-normal in clock time, with fat tails and persistence. But in volume time, normal service – indeed, nearnormality – resumed. This fractal lens can be used to explain why market liquidity can evaporate in situations of market stress, amplifying small events across time, assets and markets. Fractal geometry tells us that what might start off as a snowflake has the potential to snowball. (a)  Behaviour of high frequency traders  HFT has had three key effects on markets. First, it has meant ever-larger volumes of trading have been compressed into ever-smaller chunks of time. Second, it has meant strategic behaviour among traders is occurring at ever-higher frequencies. Third, it is not just that the speed of strategic interaction has changed but also its nature. Yesterday, interaction was human-to-human. Today, it is machine-to-machine, algorithm-to-algorithm. For algorithms with the lifespan of a ladybird, this makes for rapid evolutionary adaptation. Cramming ever-larger volumes of strategic, adaptive trading into ever-smaller time intervals would, following Mandelbrot, tend to increase abnormalities in prices when measured in clock time. It will make for fatter, more persistent tails at ever-higher frequencies.
The scenarios the NGFS have produced pull together, for the first time, both transition risks and physical risks, and their economic and financial consequences, in a coherent way. As a result, they are decision-useful, reflecting the totality of risks we will face. A guiding principle has been to try to shine a light on some of the uncertainties that exist. We have focused on multiple scenarios and multiple models to highlight the range of potential outcomes. Since modelling these impacts is subject to significant uncertainty and extensive academic debate, our work is open source and we seek your expertise and challenge. 4  The NGFS was founded by 8 central banks and supervisors including the Bank of England in 2017. Members are committed to sharing best practices, contributing to the development of climate and environment-related risk management in the financial sector and mobilising mainstream finance to support the transition towards a sustainable economy. It is currently comprised of 90 members and 14 observers. The first iteration of these scenarios, published in June 2020, drew from the existing work on mitigation pathways, climate change and adaptation that supported the Intergovernmental Panel on Climate Chance (IPCC) Special Report on Global Warming of 1.5°C.5 The NGFS will next month release an update, which will include bespoke scenarios, detailed macroeconomic modelling and a new online portal that can be used to explore physical risks. Insights from the design of the NGFS climate scenarios I would like to share some of the insights I’ve gleaned from this work.