Traders Who Code, Or Coders Who Trade?

But how extensive will the role of programmers be, and what does their ascent mean for traditional managers and traders with fundamental skillsets?


The Wall Street Journal was the latest to chronicle the industry’s shifting realities in an article this month titled, “Wall Street Erases the Line Between Its Jocks and Nerds.” The piece describes how well-known Wall Street stereotypes barely cease to exist anymore and how the “nerds” are now the ones with the edge.


Today, most firms on The Street place a high value on deep technical know-how. Firms like Goldman Sachs and Citigroup are even offering free computer programming classes for their traders, and even veterans of the trading floor are signing up.


According to one Goldman Sachs executive, “everyone who comes to sales and trading needs to know how to code.”


It wasn’t always this way. Everybody remembers the stereotype of fast-talking, charismatic traders. The type of person that Hollywood loves to portray through Gordon Gekko or the team from JT Marlin, the fictional firm in Boiler Room.


It’s hard to imagine these people parked in front of a computer screen for hours on end, quietly and thoughtfully plugging away on a keyboard. That was always the job of coders – to stick with the Hollywood analogy, the Peter Gibbons type from Office Space who was expected to quietly do their job somewhere in the back office.


But now, as traders are being schooled in computer science, coders are diving into the deep end of finance. They’re becoming the decision makers who execute trades and take positions on behalf of firms and their clients. And in fact, the SEC now requires anyone responsible for designing or overseeing a trading algorithm to become licensed as a “securities trader.”


From one end of the spectrum we’re seeing the emergence of “traders who code.” And from the other end, “coders who trade.” These jobs are merging as one in which computer programming knowledge will be an essential component.


The role of professionals investors with traditional backgrounds is clearly diminishing. But there are signs that firms still value and need a separation of functions at some level. For example, The Journal article had this to offer from UBS:


“There must be a clear delineation of responsibility,” said Mike Dargan, group chief information officer at UBS. On the Swiss bank’s markets desks, “scrum teams” of traders and coders collaborate to quickly roll out new functions, but aren’t encouraged to start to do each other’s jobs.


“We want traders to be educated” about how their software works, Mr. Dargan said. “But we want them trading.”


This outlook provides a hint as to how this massive industry shift will likely play out. Accessing and using data will be essential, but there are many practical reasons why coding skills might not be. For one, computer programming doesn’t come easy to everyone, and some people who aren’t great coders may still have the gut instinct to see a good investment. You don’t want to lose that talent.


This is why there’s a need for people who are experts in software, data and user experience design to come together and create ways for even the traditional traders and managers to use data. And that’s exactly why we created Elsen.


Elsen makes it easy for anyone to work with massive amounts of financial data to solve the most complex problems. This includes traditional financial professionals with no technical knowledge, expert programmers, and everyone in between. Using web-based applications built on Elsen nPlatform, people with no technical background can perform research and develop new strategies in only a few clicks. And, direct API access can give people with technical expertise the control they desire for more advanced functions.


But the important thing is that no technical knowledge is required. After all, you don’t have to be a mechanic to drive a car, so why do you have to be a programmer to make a trade? That’s why we’ve developed technology that can help make anyone successful in the new data-driven realities of finance.

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