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Why Trading Begets Trading
From medieval trade fairs to the closing auction, liquidity creates more liquidity
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One of the nice things about electronic trading is that you don't need someone to be willing to pick up the phone if you want to make a trade. You can submit orders hours before or after the market's official trading hours, or, more recently, even overnight, and, as long as you're offering the right price, someone will trade with you. And yet, the vast majority of volume happens during trading hours, and within that, volume is increasingly clustered around the open and the close.
There's always been a case for getting more commerce if you concentrate it at one date and time. In the middle ages, long-distance trade often took place through scheduled trade fairs, which would sometimes rotate around the same region. One continuous fair was a worse prospect, because it meant that there wasn't time to restock inventory and that the odds of the right counterparty showing up at the right time were slim.
Another reading on this is that low-volume trade leads to adverse selection: if someone wants to do business with you, as a buyer or a seller, it's always helpful to have a sense of why. For a medieval merchant, there was always a risk of getting robbed or defrauded, and that risk was higher if someone randomly showed up and coincidentally expressed an interest in their exact wares, especially when relatively few others are doing the same.
Adverse selection takes a different form in a world with functioning institutions, rule of law, etc., but it still drives behaviors: all else being equal, if you're trying to make money from passively transacting with someone else, it makes a lot of sense to do this in a context where they're more likely to be trading for a reason that's completely irrelevant to you. And the best time to do this is a time when everyone's trades have been artificially delayed, even if it's because of the mild inconvenience of clicking the "fill outside regular trading hours" button on their brokerage app interface.
But this extends much, much further than just what time people trade. It also extends to what they choose to trade. Many products seem like they'd be interesting to make a market in, but don't have active trading, and for the ones that do, they're often a sort of platonic reference point for a broader category. A futures contract on a 2-year treasury bond is not necessarily a reference to a specific bond, but a reference to a sort of statistical average bond (someone who's trading these actively would pay attention to which bond is, for the purpose of the contract, cheapest-to-deliver, and would also potentially have a model for how that status might change). When that contract is used to price real-world transactions, it's often used as a reference price, LIBOR (and more recently SOFR) being other common examples of benchmark/reference rates that traders and market participants peg more bespoke contracts to. Rates function the same way: you can trade "what is the price of dollars six months from now" separately from "what is the right interest rate to charge this specific counterparty to borrow dollars for six months," and the market for the former is vastly more liquid because there are so many reasons to trade it.
Extending this even further, it's easier to take a position in broad equity indices than in specific assets—someone trading Coca-Cola might know something specific, either about the company's fundamentals or just about their own trading plans, but it's unlikely that someone trading the S&P 500 would have as definitive or informed a view.
The most interesting part of all of this is that these easy-to-trade and hard-to-trade situations are complementary. The existence of broad market indices to which investors and speculators allocate fairly uninformed capital ends up creating low-signal demand for the constituents of that index. The ability to identify correlations between assets also means that there's more uninformed flow: sometimes, the trader selling that Taiwan-listed stock has a view on it, and sometimes, that trade is offsetting general Taiwan exposure and has nothing to do with the specifics of the company.
The paradox of markets is that all of these traders tend to cluster together: liquidity providers want to be where the uninformed traders are, and informed traders want to be where the liquidity is. And, in the end, they all benefit from this: liquidity is sold at a price, and it's the cost of trading with a fundamental view, which is ultimately what makes the market efficient enough that index funds are a broadly good bet, both for savers and for gamblers.
We’ve covered the clustering of liquidity from a few different angles in The Diff:
We’ve looked at what the business model for new exchanges really is ($).
Businesses like MarketAxess ($) try to centralize some of the trading that otherwise happens peer-to-peer.
The need for uninformed flow makes prediction markets a hard business.
There are many different liquidity clusters, like the one in small companies that don’t want to report as much to their investors ($).
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