Opening Cross: Murphy’s Law of ‘Technical’ Analysis

When you consider how technically advanced the financial markets have become since the heydays of exchange pits and curb markets, it’s hardly surprising that every so often, things go wrong. And, as Murphy’s Law dictates, they will probably go wrong at the same time.

And even achieving lofty goals can still fall short of perfection. After all, 99 percent uptime—that would be a record to be proud of, right?—means that over the course of a year, you could expect outages totaling 3.65 days. Even 99.9 percent uptime equates to the best part of four hours offline. And throwing a spanner into the works—or, in the case of an exchange updating its core technology platform, an entire toolbox—increases the chances of serious gear-grinding.

Hence, datafeed-related outages at the London Stock Exchange and its Borsa Italiana division last week must have only added insult to injury for data vendors, consumers and LSE staff alike—already arguing over who’s to blame for data quality issues arising from the migration of some LSE markets to the group’s new Millennium Exchange matching and data engine from subsidiary MillenniumIT.

But it’s not just the way markets operate that has become more technical: It also extends to the way firms identify and place trades, and to the data vendors charged with disseminating content and providing value-add services to clients. For example, Thomson Reuters last week unveiled its Enterprise Platform for Velocity Analytics, which integrates all the vendor’s content along with third-party applications for price discovery, strategy back-testing and execution for quantitative, high-frequency traders, and can be deployed at clients’ sites or as a managed service on its Elektron infrastructure to reach new markets. Speed, complex analysis and location-independence—the three key features of a modern trading strategy.

Also last week, San Francisco-based trading and analytics vendor 4th Story rolled out a series of new features—collectively known as its 4S.White Sands module—for automating and pre-configuring analytics, alerts and trading signals, aimed at traders and strategists that want to monitor vast quantities and combinations of data and circumstances for rare events.

Meanwhile, Titan Trading Analytics, a provider of behavioral trading strategies, has incorporated 12 years of historical data from behavioral finance specialists MarketPsych, which monitors “buzz” from social media and other sources to detect sentiment on specific US stocks as a means of predicting price movements.

In short, the decision-making processes behind placing a trade is an immensely more sophisticated endeavor than it used to be, with data display and analytics tools becoming ever-more complex. And this is also extending to the world of active and retail traders.

Just as TraderMade is expanding the technical charting and analysis tools it built for foreign exchange markets into other asset classes, starting with commodities, online brokers are taking tools developed with high-level traders in mind and rolling them out to retail markets—just like the baby on the E-Trade commercials says. Charles Schwab’s new StreetSmart Edge trading platform—ostensibly aimed at retail investors—highlights the levels of sophistication that the firm now expects from “retail” clients, incorporating Level 2 data, technical and fundamental analysis and automated trading features that not so long ago was the reserve of professional traders.

This nonstop drive toward the more technical—in terms of technical analysis and technology-dependent market infrastructures—offers enormous benefits for institutional and retail investors alike. But until our technical skills attain true perfection—and Murphy’s Law is laid to rest—we’ll have to put up with the poltergeist-like antics of the ghost (or perhaps, the human) in the machine.