Market Structure in 3D

Show me examples.

When I was a fresh-faced goofy college kid, my Logic professor, who was Greek and credible with his Hellenic accent, would say that a thing was theory only until you provided examples in the real world.

We hear that notion regularly. “So what exactly do you see with market structure? Give us some examples.” You asked. We’re doing it. We’ll aim to give you them regularly. Each will be an actual, real-world example, though the confidential nature of the data we track may preclude names.

As background, we’re clustering trading volumes behaviorally. It’s not quantitative analysis, which follows price and volume. It’s sorting out volumes with different time horizons and purposes to see which kind is prevailing. Often, price and volume change little, while behind the scenes tumult ensues among parties trading for different time horizons and purposes.

Here’s an example: Two large technology companies engaged in a bidding war for a third company. One of the two bidders was our client. There are three basic dimensions to market structure: trade executions driven by rational investment theses; trades for risk-management purposes based on changing market information, economic data or portfolio risk; and speculation in which traders take the other sides of trades, or sit between buyers and sellers to capitalize on short-term price movement or liquidity fluctuation.

Speculators are the truth-tellers about rumors and deals. If outcomes are uncertain, the parties most likely to know are the ones whose whole business it is to figure such things out. They’re not always right, but their batting average in our experience is over 80%. We pay attention.

In this instance, we saw 100% uniformity in speculators’ conclusions about the deal. How? They all did exactly the same thing. Literally no arbitrager questioned the prevailing sentiment.

For the IRO, that’s powerful data to present to boards and management teams. “Market structure indicates that the market universally expects us to prevail.” That says two things: Either your business and resources are more potent than your competitor’s, or you had better prevail or be prepared to suffer a high price. As a kicker, the IR team also could tell the Board and management that stock price was unlikely to change much at conclusion of the deal. Such was the outcome.

These are the things we see every day with market structure analytics.