the future of crypto regulation

The “Wild West of crypto” in the US seems to have arisen from the inability of the SEC, CFTC, IRS, and the Federal Reserve to coordinate on how to approach crypto. The FTX situation is somewhat akin to earlier losses associated with “over the counter” swaps. Initially, swaps were explicitly exempted from most regulation by prior Federal laws, so regulators could claim their hands were tied. Rules for reporting and clearing swaps were enacted after the Global Financial Crisis, but some aspects of individual swap transactions (e.g. margin requirements) are still generally treated as private business contracts. In the US, the CFTC has primary regulatory power on swaps, but the SEC can get involved in cases where swap transactions are based on securities that the SEC would normally regulate.

A clear regulatory picture in the US would improve the ability of the G20 countries to collaborate on sensible guidelines, leaving unregulated crypto activities to operate only in small countries with economic incentives for liberal engagement with cryptocurrencies (e.g. El Salvador).

References

1 // Code of Federal Regulations.

https://www.govinfo.gov/content/pkg/CFR-2021-title17-vol1/xml/CFR-2021-title17-vol1-sec1-17.xml

2 // Blackburn, T., DiBartolomeo, D., Zieff, W. Global Commodities Applied Research Digest. Published September 1, 2022: https://www.jpmcc-gcard.com/gcard-article/assessment-of-cryptocurrency-risk-for-institutional-investors/ peer-reviewed by

Carl Densem

Author

Dan diBartolomeo

Dan diBartolomeo is founder and president of Northfield Information Services, Inc. He serves as PRMIA Regional Director for Boston, as well as on boards for several financial industry associations including IAQF, QWAFAFEW, BEC and CQA. Dan spent eight years as a Visiting Professor in the risk research center at Brunel University in London. In 2010, he was awarded the Tech 40 award by Institutional Investor magazine for his analysis that contributed to the discovery of the Madoff hedge fund fraud. He is currently the co-editor of the Journal of Asset Management and has authored nearly fifty research studies in peer review publications.

The Turing Test can be used to tell apart two important types of challenge facing Risk Managers today: complex and complicated issues. While complicated issues can be dealt with by algorithmic, rulesbased systems and likely better run by computers, complex issues exhibit qualities that befuddle such programmatic thinking and can only be handled by human ingenuity.

does your risk management pass a turing test?

by Rick Nason, PhD, CFA

The English mathematician Alan Turing, who was portrayed in the movie “The Imitation Game,” is widely considered to be the grandfather of the computer. As part of his theorizing about computers, Turing devised a thought experiment which is now called the Turing Test. In one version of a Turing Test, you are to imagine two curtains. Behind one curtain is a human, and behind the other curtain is a computer. The Turing Test is to have an observer ask questions or pose problems to each of the “curtains” and by the responses decide as to whether the responses are coming from a computer or a human. If a computer is indistinguishable from a human, then it is said to have “passed” the Turing Test.

You might be asking, “what does this have to do with risk management?” and the response is everything. In essence, the Turing Test answers the question of whether or not your risk management is robotic in nature or human in nature. More importantly, it answers the question of whether your risk management can deal with adaptive complexity (for which you need human responses), or solely complicated risk issues (for which a computer solution will suffice).

Complicated

In Systems Thinking there are two main types of systems: complicated and complex. Complicated systems work based on defined rules or laws whose trajectories can be calculated and thus predicted. This makes managing complicated issues relatively straightforward. Checklists, procedures, and automation are effective at managing complicated risks.

Gravity is one such example of a complicated system: if you hold your coffee mug up in the air and let go of it, then it will fall to the ground.

Complexity

By contrast, complex systems are those which are unpredictable, and furthermore are not reproducible. Financial market bubbles and crashes are examples of complex issues. Perhaps a more quirky example is the unprecedented demand for toilet paper at the beginning of the COVID crisis. Who could have predicted that toilet paper would be the item in greatest demand? Furthermore, it is likely that a totally different “fad issue” other than toilet paper will arise with the next crisis.

Complexity arises when three conditions are present:

1. There are agents (think individuals, groups of individuals, companies, economies etc.),

2. Who can interact (through discussions, media reports, social media, business competition) and

3. Who can adapt (change their minds, opinions, strategies, or their desires).

Complex situations exhibit a host of properties that create special challenges for risk management. One specific property of complex systems is that of emergence. A particular example of emergence is that of a murmuration of starlings, for which videos are easily found on social media. In a murmuration, a flock of birds collectively create beautiful patterns of flight, but the patterns are constantly changing and never repeating. Furthermore, the patterns of the flock are completely unpredictable. Charts of the stock market are another example of emergence where there are obvious patterns in the movement of the market averages, but unpredictable breaks and departures as new patterns form.

how are complex and complicated risks managed?

Complexity imposes special demands on the risk manager, and they need to be managed very differently than traditional complicated issues. To begin, a risk manager must first determine whether the risk is complicated or complex. Secondly, a complex situation cannot be solved – it can only be managed. Thirdly, a “try, learn, adapt” approach is needed to deal with the ever changing, and non-reproducible aspect of complexity. Each complex situation must be treated as unique; what was best practice and worked last time, will not necessarily work the next time the risk arises.

Complexity requires flexibility and adaptability. Rigid rules and processes designed for complicated situations will be ineffective against complex ones, and indeed will often be more harmful than helpful. This is why the Turing Test for your risk management system becomes relevant.