Synchronization and Banking
The Problem of Synchronization argued that:
The synchronization of buying and selling is a basic function of markets.
Recent events call for an explanation of how synchronization works in banking. In the space of less than three days from March 8 to March 10, Silicon Valley Bank went from a market cap of over $10 billion dollars with hundreds of billions in deposits to a market cap of zero and receivership by the Federal Deposit Insurance Corporation. What happened? A bank run. Silicon Valley Bank's biggest depositors were venture capitalists and startups funded by those venture capitalists. After a group of influential venture capitalists pulled their deposits and instructed the startups they had funded to do the same, pretty much every other venture capitalist and startup who had an account with Silicon Valley Bank heard about it immediately and followed suit. Chaos was unleashed.
So wasn't synchronization a bad thing here? Yes. Isn't a bank run an example of spontaneously synchronized human behavior? Yes. Then isn't a bank run the kind of market synchronization that you love? No. In fact, as I will explain, a bank run is more like Decoupling in the Nickel Market.
Synchronization Redux
The key distinction is between cycles of "production" and "consumption." Here is a longer excerpt from The Problem of Synchronization quoted at the beginning of this article:
The synchronization of buying and selling is a basic function of markets. More specifically, the synchronization of bids with asks into completed transactions is an important part of market price discovery mechanisms.
Examples of the "bids" and "asks" referenced are the offers to buy and sell apples by people who wanted to consume apples and people who grow apples. The Problem of Synchronization gave an extended explanation of how the cycles of consuming and producing apples are different in frequency and relative timing, and of how market price signals help to synchronize those cycles in such a way that consumption follows production, matching the flow of apple production to the flow of apple consumption.
Doesn't this mean that producers will act in unison with other producers? No. Market prices signal an individual producer how well their cycle of production — relative to the cohort of producers also capable of transacting — matches the cycles of consumption within a given window of time. Market price signals push individual producers to differentiate from other producers in terms of frequency and relative timing of cycles — you can charge more if you're the only producer who is capable of transacting within a given window of time.
The same goes for consumers. Consumers are not more likely to act in unison as a result of market price signals. Again, they're more likely to differentiate their cycles of consumption from other consumers in response to market price signals. You pay less if you're the only one who wants to consume from a fixed quantity of goods available for purchase within a given window of time.
What the market price signals synchronize are transactions from producers to consumers. Without the market price signals — for example, in a centrally planned, fixed price economy — cycles of production and consumption are chronically mismatched, and surpluses or shortages abound.
Synchronized Banking
How does this work for banks? Banks are more complex to analyze than producers of tangible goods because what a bank produces are loans, and loans are themselves cyclical. Ray Dalio does a great job of explaining this:
A producer of tangible goods extracts profits from the higher value that a consumer places on the tangible goods. If apples cost less to grow than buyers will pay to eat them, then there is a business in growing apples.
A bank extracts profits by selling shorter term loans and buying longer term loans. If the bank pays less in interest on its short-term loans than it receives in interest on its long-term loans, then there is a business in banking.
For example, if the bank advertises accounts that pay 1% interest and receives $100 million in deposits, and long term loans are available that pay 4% interest, then the bank could earn the 3% spread in interest on whatever deposits it doesn't need to keep on hand to meet the cash flow requirements of its depositors. The bank can't make $3 million because that would mean tying up all $100 million of its deposits for the duration of the long term loans. But if it invested only $33 1/3 million and kept the other $66 2/3 million liquid, it could still earn $1 million in profit.
The only cycles that matter for tangible goods are the cycles of production and consumption. Apples do have a shelf-life, but their fluctuation in value during that shelf-life is small relative to the price at which they are sold.
In contrast, banks have to worry about both the cycles of production and consumption for deposits (the short term loans) and the cycles of production and consumption for long term loans. And the market price of both kinds of loans can fluctuate dramatically, especially in response to interest rates set by the Federal Reserve.
This is what happened to Silicon Valley Bank. Market prices for its long term loans dropped faster than it was capable of rebalancing its portfolio of long term loans because it got a bunch of short term deposits in 2021, at the peak of a frothy market for venture capital and startups when interest rates were low. Could Silicon Valley Bank have avoided this? Sure. It wasn't impossible to guess that interest rates might go up, and to "ladder in" to longer term loans in such a way that the value of the long term loans wasn't as vulnerable to decline as the Federal Reserve raised interest rates.
But if Silicon Valley Bank had been able to hold onto its long term loans to maturity, it wouldn't have had to worry about their market value declining. And why wasn't it able to do that? Because of bad synchronization — a feedback loop of fear that swept through its depositors in a matter of hours. The situation is not dissimilar from the situation of Tsingshan, the nickel producer that found itself owing $1 billions in a margin call on a short position it had taken to hedge against a decline in the value of nickel. In that case, a feedback loop of short selling triggered by financial buyers had forced Tsingshan into a position where its short term financial obligations — i.e., the margin calls it owed — might have forced it into insolvency despite its long term capability of delivering more than enough nickel to cover the contracts.
In that case, the London Metals Exchange stopped trading, busted some of the trades, and demonstrated in practice that it cared more about the health of (at least one of) the tangible producers of metal than it did about financial buyers and sellers that provide liquidity to buyers and sellers of actual nickel.
In the case of Silicon Valley Bank, something like the opposite occurred. The bank that "produced" the short term loans for venture capitalists and startups got wiped out. The government stepped in to guarantee uninsured depositors, but how much did those depositors really benefit from that in the end? They would have gotten their money bank if they'd never left Silicon Valley Bank (the long term loans would have covered their deposits if held to maturity), and now they have to deal with another bank that's not going to be as friendly to venture capitalists and startups, especially now that they've demonstrated how little trust they have in banks!
The problem is that the depositors pulled their deposits not in response to an immediate need for cash, but in response to a fear that they would lose their cash forever. Is this another example of how frequency capping might make sense?
1907: John Pierpont Morgan slows down a bank run by ordering the tellers to count all the withdrawals twice, by hand.
— Benedict Evans (@benedictevans) March 11, 2023
2023: $42bn withdrawn from SVB in one day.
[Editor Note: The original image was of a Tweet by Benedict Evans who has since quit Twitter.]
Underneath every voluntary transaction that takes place in a market are underlying cycles of production and consumption. Banking transactions are no different. Any sensible regulation of markets, including banks, ought to take the relative frequency and phase of these underlying cycles of production and consumption into consideration. Complex looking market failures, including the London Metal Exchange's busting of nickel trades and the Silicon Valley Bank failure, often boil down to a mismatch between the frequency of production and the frequency of consumption that is too big or too quick to reflect the actual cycles of production and consumption of tangible goods and services that it is the ultimate purpose of markets to serve.