Dynamic Financial Risk Assessment & Blockchain Technology

Assessing global financial risk is a practice in patient observation. However, current operational challenges in data sourcing and live ownership tracking can lead leverage to run wild in obscure parts of the market. Anonymous, accessible blockchain-enabled asset ownership systems can lighten this load by allowing for easier tracking of leverage spikes. 

Let’s start with the why behind the need for market participants to maintain a deep understanding of leverage levels in a system. For starters, greater leverage (defined by the ratio of market exposure to assets) increases the likelihood of accidents (as defined by the uncontrolled depreciation of assets in a way that is seemingly stupid). If a hedge fund is levered at a ratio of 10:1, they can bet on $10 million of assets with just $1 million. If the prices go up a lot, the fund manager can make a lot. If the prices recede, they can lose more than they otherwise would have.

The reason this leads to issues in the market is because leverage is a complicated, mathematical function made even more complicated when existing derivatives all price in their own statistical assumptions in a multi-tranched, instrumental fashion.

Under the Investment Act of 1940, strict financial regulatory language puts forward rules on how mutual funds may invest in other mutual funds. Unless granted an explicit mandate to invest as a fund-of-fund (FoF), a mutual fund manager cannot simply purchase other funds instead of directly purchasing securities. There are several reasons for this. One is to ensure that the consuming investor purchasing into the higher-level mutual fund has an accurate understanding of the fund’s exposure (this is closely linked to the 80% provision stipulated under the Names Rule.) The second reason the SEC cares about unregistered FoFs is that it becomes impossible for consuming investors to discern the actual fee structures underlying the mass of funds they are purchasing into. The sword becomes unwieldly.

This is also true with levered products and sectors of the market, though unfortunately without helpful governmental regulation (in most cases). Risk and exposure build in unforeseen ways that become extremely complicated to dissect. To put a hammer to a nail, the below equation defines leverage as a function of several dissecting risk measures as understood by an idempotent matrix:

 This equation takes a lot to unpack, and when the small n grows massively, while participants don’t know how many institutions are all betting on different outcomes, it grows to a nearly impossible problem. An easy way to think about this problem is within the context of stacking Jenga tiles. One, two, three, or maybe four levels are fine. But when leverage pushes that number to ten, then one hundred then more the entire structure becomes deeply unstable to the point where a single breath of air could send everything tumbling down. That could be due to a war in eastern Europe, a new “mini” budget in a particular parliamentary nation, or an infamous little virus. Crash!

This is bad not just for our hedge fund manager, but also for your 401k plan or your local firefighter’s pension plan. Everybody is hurt.

Never fear though, leverage is controllable. Regulation passed since the Great Financial Crisis has done a phenomenal job of decreasing leverage in the banking system (where issues originated). Just look at the below graph:

Not too bad. Also, leverage is a beast that feeds on the unknown. Remember all those financial instruments that crashed markets in 2008? Here is their use now:

Again, much better. The key point here is that defining risk is mitigated by knowledge. This is true in life, love, and finance. So, what can we do about that? Well, perhaps the greatest challenge to global risk analysts is that they don’t actually know how much leverage is riding on any particular financial product. For example, in the UK every fund analyst knew that many pension managers were using a complex derivative product to hedge interest rate risk in Gilts. But nobody knew by how much. The guesses, it turns out, were very, very off. Leading to this nice little chart:

The United Kingdom looked like an emerging market economy. Fortunately, blockchain technology offers us something special. The ability to view on-chain settlement quantities. Of course, doing this in a transparent fashion would never be accepted by fund managers or regulators. Nor should it, breaches in selective disclosure would be a mess to work through while the technology was introduced. However, anonymous records of ownership transfers for shares and contracts represented by NFTs would allow for dynamic, measured assessment of risk pileups. It would be possible to know exactly how many institutions were betting the same way. This would lead to a more accurate picture of where risk existed in the broader system, in turn, lowering expected returns and the number of investors who would look to continue to pile up in the same products.

Of course, this system wouldn’t be a cure-all, and sometimes even professionals get carried away by a range of incentives from compensation to career risk. But it would absolutely provide another tool for players and regulators to do their jobs. Metcy APIs would be at the heart of this system, providing rapid on-chain analysis where even a little change can make a sizeable impact.