A consolidated audit trail might sound good on paper, but as Max discovers, the SEC’s proposal has failed to impress many in the industry. However, while cost is a major factor, the critics might at least look to invest in some sturdy lightning rods.
How much is avoiding another ‘Flash Crash’ worth? That’s the question US market participants are asking as they respond to the Securities and Exchange Commission’s (SEC) proposed real-time consolidated audit trail of trading activity across equity and options markets to spot anomalies and potential abuse.
“The information in the consolidated audit trail might give earlier indications on the state of the markets, generating warnings of impending problems such as the Flash Crash,” says Stephen Elston, managing director of Quantia Analytics, whose analysis of May 6 shows monitoring market activity in real-time would have generated warnings more than a minute before the worst of the crash in some stocks.
However, the proposal has met with a mixed reception from the markets. For example, Finra (the Financial Industry Regulatory Authority)—which already produces the Oats (Order Audit Trail) and Trace consolidated trade feeds, and would be a key component in any solution—says the SEC “significantly overvalued the regulatory benefits” of real-time reporting, and that real-time data is less reliable than corrected and validated information.
Wells Fargo Advisors echoed this, saying real-time reporting “inhibits” detection of fraudulent or manipulative activity, since “accurate market information often does not happen in real time,” but “only ‘settles down’ in a period after the real-time execution.”
But to be able to monitor for more than just suspicious activity—for example, to detect a systemic problem and take action in real-time—the SEC needs raw, un-corrected data to see exactly what caused actions at a point in time. Once data is validated and corrected after the fact, it can become harder to detect the cause of an incident.
“You don’t just need feeds, a ticker plant and databases… you also need to be able to look at these in real time and spot patterns of behavior that indicate something is going awry—from a trader trying to manipulate the market to an issue with a trading application submitting a lot of orders in a short time, which might indicate an algo trading system going wrong,” says Giles Nelson, deputy chief technology officer at Progress Software.
Wells Fargo was also concerned that the 32-month estimated schedule for implementation would be “woefully short,” and that “rushing through such a dramatic change… poses a great risk of harm,” resulting from a lack of vetting and stress-testing, suggesting a five-year plan would be more realistic.
Among the plan’s supporters, new exchange Direct Edge said it “would significantly enhance the capabilities of regulators to police trading across asset classes… [and] create a more complete timeline of an order’s lifecycle,” while TD Ameritrade called it “the right solution and… overdue,” but estimated its initial spend to support its contributions to a system would be $1.25 million, including $750,000 in development and $500,000 for hardware, and would require three full-time staff.
Many said the industry-wide costs required to implement a consolidated audit trail—estimated by the SEC at around $4 billion, with ongoing annual costs of around $2.1 billion—are too high, though others believe a system can be achieved for much less.
In fact, a consortium calling itself TickLab—comprising data architecture consultancy Noetic Partners, data vendor Activ Financial and high-performance computing technology vendors Cray Research and XtremeData—has proposed that it can build a system that includes full-depth tick data capture and high-performance storage for fast retrieval for less than $100 million, which would cost less than $100 million per year to run.
So, how much is an orderly market worth? Those who believe lightning never strikes the same place twice might say the benefits aren’t worth the cost. But lightning always strikes again somewhere, and—as the saying goes—those who don’t learn from the past are doomed to repeat it.
Waters Wavelength Podcast Episode 75: An Update on the Julia Programming Language; AI & Alternative Data; Digital Currencies
Julia Computing's Viral Shah talks about the programming language he helped create and what's ahead for it. Then James and Anthony talk about the pairing of AI & alternative data, digital currencies, and Game of Thrones.Subscribe to Weekly Wrap emails