Chain Reactions (May & Jun '24)
Chain Reactions (May & Jun '24)
Market commentary for May & June 2024
Spice, Blockspace & Compute
Several major events have occurred in the last 50 years that shaped the extraction and transfer of the Earth’s natural resources across nations. In the 1970s, Iran rattled oil markets as one of the world’s largest producers when it underwent dramatic revolution. In the 1990s, Iraq’s invasion of Kuwait sparked the Gulf War and yet another shakeup of the global oil market. Shortly thereafter, the Soviet Union collapsed marking the start of the largest privatization of natural resources ever seen.
Two more recent events that we think are of tantamount importance with regards to the geolocation of strategic natural resources: In 2008, the Bitcoin whitepaper was released, outlining the mathematical schematics for a fault-tolerant system of digital money driven by compute. And now in the 2020s, we see compute being commoditized by the growth of AI (seen via Nvidia’s stock price).
Moving natural resources is a tricky business. We wrote a whole shtick about how this works, but Matt Levine explained it much more nicely in his newsletter today, explaining how the commodity trading firm Trafigura operates: “it is essentially in the business of noticing that oil is cheap in one part of the world, and expensive in another part of the world, buying the oil where it is cheap, loading it on ships, and moving it to where it is expensive.”
Oil must be extracted, refined, and shipped before it can be sold on the market. All of these things incur a cost that somebody is willing to incur in the hopes of securing a profit at some point in the process.
Blockspace can be thought of similarly. Accessing my digital money on the blockchain requires me to pay a fee to someone (a block producer) to get them to put my transaction on the chain. That is the cost for me to leverage decentralized banking. The block producer also incurs a cost to generate enough compute to be able to post a block. It has become very computationally intensive and thus very expensive to mine bitcoin. But the block producers will continue to do this because the cost they incur to produce a bitcoin is covered by their profits from selling to the market.
Seizing the means of production
The above is a crude explanation for how a blockchain works. But the point is to underscore the cost incurred for the producer, and how that relates to any other natural resource produced on Earth. A legitimate Bitcoin mining operation in, say, Texas or Georgia, might consume some 200-500 megawatts, enough to power thousands of homes at a time. Much like how an oil refinery or metals smelter requires a ton of expensive inputs to produce their refined products.
You can think of a mining operation as a large number of computer chips, like GPUs, all operating concurrently to loop through a cryptographic math problem. The more chips you have operating together, the more power you have to solve the cryptographic equation. And solving it rewards you with bitcoin, thus providing an approximate fair market price for such a commodity. The price of a bitcoin is roughly the cost of compute required to mine it (and therefore the cost of the GPUs plus the power consumption required for those GPUs).
Now, consider compute for an alternative use case: generative intelligence. The driving force behind Nvidia’s stock price explosion are FAANG corporations buying more GPUs in order to train larger and larger models. For this industry you would equate compute the same way you would blockspace on a blockchain. A large language model trained on billions of parameters will have some upfront cost for GPU consumption (these days on the order of billions), which drives the AI companies to spend more and more on Nvidia’s GPUs. Thus the cost of compute here is the cost to build the latest model, equal to some large number of GPUs plus the power required for those GPUs to run the training algorithm.
Some might argue here that GPUs are the actual commodity; this is erroneous, because the digital real estate of value that is produced are things like intelligence or decentralized money. The extraction of materials for silicon and the fabrication of graphics chips that we have in our computers includes many commodity funnels indeed. But we posit that there is much greater value, like petrol at the gas station, in the products these manufacturing lines produce.
On Economic Experiments
A grand economic experiment would be one where we took all of the paper receipts for asset ownership (like the deed to your house or your mortgage) and replaced them with some immutable digital offering. It seems logical: why do we need a physical copy of such important documents? What type of forgery concerns could we mitigate; or better, what type of processes could we improve by digitizing assets for transfer?
Some examples: clearinghouses and brokers are replaced with decentralized liquidity pools; stock brokers like Robinhood or ETrade are replaced by an open-source exchange for real-world assets that require no broker; enabling verifiable and indisputable ownership rights over your digital property, like your song, movie, or screenplay.
If you could boil crypto down to one idea, you might just call it a digital experiment to replace existing economic actors that extract too much rent. Spend some time here though and you might just get tired of all the “experiments” that seem to be running away with your money.
Such is Sophie's Choice of crypto. Embrace the digital economy and you are more than likely to encounter a scam, a rug, or some phishy link that drains your digital wallet. Turn your back to the grand experiment, and you’ll likely start to see more clearly the ways the system has extorted you for centuries. Payment for order flow, suspicious loans, backdoor dealmaking… the list of ways the modern financial system can screw you goes on.
Crypto is far from perfect. The tools are far from perfect. The people, most definitely, are far from perfect. Yet the relentlessness of the herd to push toward decentralized services and fairness in the ecosystem nevertheless remains. Economic primitives that could one day benefit all consumers are being tested out in the open, a stark contrast from our banking system today. And while the products borne from these primitives still have a long way to go, the boats beat on, ceaselessly pushing toward Pareto optimality.
Economic experiments should be played out this way, backed by open-source research on a transparent ledger. While the SEC’s position on this differs, the spirit and ethos of crypto is very obviously beginning to chip away at that institution’s willingness (and ability) to remain shrouded operationally. When Gensler loses, the people win.
The Bank of Japan
Governments experimenting with banking is somewhat rare. The Bank of Japan, since 2016, has been engaging in an economic experiment of quantitative easing so juicy that citizens are paid to borrow. Interest rates went so low as to be negative, meaning it's cheap as shit to borrow. Basic economics tells us this should stimulate the economy: if I wanted to start a business in the US, I could maybe finance it through a bank offering a 20% down payment on an SBA loan with a fixed interest rate. But let’s say I was a Japanese citizen with the same loan opportunity; rather than pay a fixed monthly interest payment, the government would pay me a fixed monthly interest payment.
This sounds like a good experiment to stimulate the economy, since you are boosting the demand to borrow and thus encouraging more spending. The catch is inflation. In order to pay for something like this, you’d likely have to print money at an unprecedented rate. This is happening in Japan, and it is the reason why US citizens can get more bang for their buck in Japan right now. The Japanese Yen has weakened relative to the dollar due to this policy of fiscal easing, which is not good for the Japanese consumer.
If the goal is to lift the economy up to benefit all consumers, then this should deem the experiment a failure. But what about the markets? Below is the 5 year chart comparing the FTSE Japan Index (blue) with the S&P 500 (overlaid in yellow). In the last 5 years, Japanese equities have exploded, outpacing one of the S&P 500’s greatest bull runs by a factor of 2.
This makes sense, since cheaper borrowing should help businesses grow while hopefully offsetting the negative impacts of currency devaluation. Presumably, many Japanese citizens have their 401Ks tied up in mutual funds and ETFs that are exposed to Japanese equities, meaning their total wealth has increased. But what about an individual’s purchasing power?
There is likely an irrevocable breaking point of such a policy. At some point, the value of your currency might plummet, which in turn could harm your market’s equities and thus hurt the overall economy. But there is something unique about Japan: their biggest companies (think: Toyota, Sony, Mitsubishi) all do a significant portion of their business in foreign markets (like the US). This means that these companies are actually benefiting from foreign exchange, since they can rake in dollars and euros overseas and swap it for more yen. And so the balancing act of lifting your economy while maintaining your currency’s relative strength is clearly delicate.
Open-source experiments
What lessons can we learn from the Bank of Japan’s great experiments? A ton when it comes to MakerDAO’s SPARK protocol and their mechanisms for DAI, the ETH-collateralized stablecoin.
MakerDAO is essentially running an open, transparent economic experiment with their DAI stablecoin. The goal is to create a decentralized, collateralized stablecoin that maintains its peg without relying on opaque banking machinations or fractional reserve practices.
It works by requiring users to lock up collateral (usually ETH) in order to mint DAI. If your collateralization ratio falls below a certain threshold, the position is liquidated to ensure DAI remains backed, which is a lot like a margin call, except rather than telling you to top up your collateral to protect your position, they just liquidate you immediately to protect themselves. Which sounds like a much safer banking practice if we want to transfer risk from the system to the user.
The result of MakerDAO’s collateral system is a neat dance of incentives and game theory playing out in real-time. The protocol introduces a bottom-up, market-driven approach to maintaining the stablecoin’s peg and stability. In order to keep the system in equilibrium, the protocol can automatically or democratically adjust fees, savings rates, and liquidation ratios. These are useful levers; but they are not as powerful as printing money.
In contrast, the Bank of Japan issues a top-down approach: we can stimulate the economy by printing money, and pay people to borrow to encourage them to further spend more. This can help boost the economy (which it has), but it also introduces major currency devaluation risk.
Both experiments here carry risks. The kicker is that one stakeholder maintains autocratic rule over the experiment, whereas the other can only make minor adjustments and just hope that the system works. MakerDAO lacks the ability to print money out of thin air, but the system has nevertheless survived several major bull market implosions. Maker’s viability is tested each time, and so far it remains alive despite all of the obstacles. Whereas the backdrop for Japan is different. Global GDP has seen positive growth every year since 2010 (except for 2020). How might Japan’s experiment be tested when the global economy faces larger headwinds?
Disclaimer: Unit Zero Labs may own assets mentioned in our articles and research. This is not financial advice.
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