We have good news and bad news.
The good news is that investors have put more funds to work in equities during January. We track behaviors – investment, speculation, the crowd following trends and managing risk. We’ve seen increased investment behavior in the past twenty trading days for clients. That’s good, even if your stock or sector wasn’t on the receiving end. It means more competition for shares, and that generally is a boon to stock prices.
What’s the bad news? We see wide disparity between prices investors think are correct for shares, and the prices the market sets. We’ve developed measures for looking at how trades execute in context of others to separate what we might call intermediation from where the orders that attracted intermediaries were priced when they entered the market.
Aren’t these prices one and the same, what with the efficient market and all? Au Contraire. That would be too simple.
The market is a lot like the economy. You might think we’re stating the obvious, but we don’t mean what you think. In the economy, people are buying and selling things on the economic principles of scarcity and choice. If something is scarce, like returns in the stock market, people choose other things, such as returns in savings accounts.
Unfortunately, if you save during tough times, which is logical, then the gross domestic product languishes and congresspersons lose their jobs. So the government intervenes to cause you to make choices you would not otherwise make, such as investing in stocks when economies aren’t really growing. That’s because you have no other choice, since the Fed has set interest rates on savings near zero.
What does this have to do with IR? US equity markets are built on this same brilliant platform. Markets depend on the “liquidity provider,” or maker-taker, model, where brokers and exchanges alike are smoothing out scarcities by furnishing liquidity. It makes liquid markets. But it distorts prices, producing continual tendencies toward bubbles and swoons like we saw in housing. Induced behavior isn’t natural and can change abruptly.
Then, induced behavior ripples through all the other behaviors. An order over here to acquire shares in a technology fund after an analyst ups the sector outlook ahead of earnings can alter the behavior over there of an algorithm behind a statistical arbitrage scheme. These trades have different valuation models but each can set the price of the next trade, and in that fashion re-price the entire volume food chain, or what we might call the economy of your trading market.
Suppose a bookie in Las Vegas used phantom liquidity to smooth imbalances on either side of a book. An “odds liquidity provider,” let’s call it. How would you know the real odds on whether Pittsburgh or Green Bay will win the Super Bowl? How would you assess your risk as a bookie that you might be massively exposed? How could you rely as a bettor on the posted odds or “over-under” if something besides bets on the book determined the spread?
We’ll wrap with good news. Public companies can band together and ask rule makers (there’s never been higher receptivity, we believe) to offer the breathtakingly simple solution: End intervention, so “natural” liquidity and the eye of the beholder set price. Imagine the odds of that.
