What if some mathematical calculations in the market are just there to get a reaction?
Traders have not to my knowledge named them “Charlie Sheen.” But alert reader Walt Schuplak at the Market Intelligence Group in New York sent an item about rogue algorithms. Our friend Joe Saluzzi at Themis Trading wrote on it yesterday.
Joe explains that certain trading practices create arbitrage opportunity. Profiting from divergence isn’t bad of itself, Joe notes. But if the chance to profit is fostered where divergence could not or would not occur on its own, it raises fundamental questions.
Bloomberg writer Nina Mehta wrote today about the Australian government’s initial rejection of the Singapore Exchange’s effort to buy the Oz stock market. Singapore is a shareholder-owned exchange. The Deutsche Bourse is public. Same with the InterContinental Exchange, throwing in with the Nasdaq on a bid for the NYSE, both of which are public too. The London and Toronto markets are run by public companies. BATS may IPO.
The shares of all these firms in theory compete for investment with your shares. For exchanges, the profit and growth drivers are data and transactions. In US markets, revenue from tape data is divided up according to “quote share,” or how often an exchange is quoting at or near the best bid or offer for a security. Revenues also come from market-access fees, data products, and trades. Growth comes from propagating these drivers through more asset classes. Listing is a small piece.
Stay with me here. This is a crucial concept to grasp in the IR chair. These are your marketplaces. How much money do exchanges make if your stock trades 500 shares daily? Exchanges don’t earn commissions; they generate fractions of pennies per share.
Exchanges need companies with billions of shares outstanding. They need options and swaptions, fixed income and wholesale counterparty clearing, commodities, carbon credits, contracts for difference, futures, swaps and complex derivatives – trading at high speed ideally, with vast webs of manufactured arbitrage, all producing data and transactions.
And there’s more. The exchanges write the rules filed with the SEC that determine what transactions will take place, in what fashion, and at what cost. Do you get to script the terms for how your customers buy or sell your products and have those rules turned into regulatory mandates? Do pharmaceutical companies pen the regs governing generic drugs or the approval process?
I am not criticizing the exchanges. They are dealing with the reality handed to them.
But I hope you grasp the monument to cognitive dissonance that has been erected in the securities-exchange business today. Exchanges are counting on machines to create arbitrage opportunities that shouldn’t exist, because that’s the core growth driver. And the fees for adding and removing shares at the exchanges – the very driver behind arbitrage – are approved by regulators.
In essence, the exchanges can only thrive if everything that you hate and which scares you increases. Clearly, companies need better trading data at minimum. And an alternative exchange model.
If every public company decided that the Berkshire Hathaway model was best – a million shares outstanding, priced at $100,000 – the entire global exchange system, and all that HFT and a great portion of the webbing of derivatives totaling $500 trillion or more would be superfluous.
And…wait for it…which model typifies the Federal Reserve? Is the dollar in finite supply of great value or in a vast and churning sea of HFT?
