How to become an algo trader
Are you a crack programmer without any financial services experience who wants to become an algorithmic trader? While making that career transition may seem daunting, it actually might not be as difficult as you think.
Sell-side and buy-side firms, as well as algorithmic trading fintech companies, are typically willing to train talented coders on the ins and outs of the financial markets, according to Deepak Begari, who got his start as a programmer at an HR software firm before getting his break into the financial services industry at the two big Swiss banks on Wall Street. He recently became the chief technology officer of Quantitative Brokers, an algorithmic trading and data analytics fintech firm.
“Some firms are not willing to hire developers from non-financial backgrounds, but Quantitative Brokers keeps an open mind in hiring people, not just developers who have a financial background, but also those from the telecom industry or any vertical that is focused heavily on programming,” Begari says. “We need solid programmers, and we can teach and train them on the domain-specific knowledge they need.
“It’s not easy to get good programmers, so if your basics are really solid after working for a few years in a non-financial space but you are doing serious programming, then it is easy for you to transfer into the financial space,” he says. “For those interested in trading, focus on mastering the programming skill set first.
“There are firms who do entertain hiring programmers from non-financial backgrounds.”
Getting your foot in the door as an algorithmic trader
As Begari worked to get his Master's in computer science at Texas Tech, his focus was on the .NET Framework, specifically programming using C and C++.
After graduation, he started out his professional career as a programmer at a non-financial software company before breaking into the financial services industry as a programmer analyst/consultant at UBS, where he worked on the IT infrastructure for the wealth management division, then Credit Suisse, where he specialized in the server-side programming for the prime brokerage.
His next stop was a front-office algo trading role at ITG, where he started as a principal software engineer building single stock-trading algorithms. He then started managing a team of developers to implement the portfolio trading algorithm, and in the following years, became the global head of development for algorithmic trading. Having acquired knowledge of algorithmic trading both from technology and business perspectives, Begari was promoted to director of product management at ITG.
From there, Begari worked at REDI Global Technologies and Pragma Trading, eventually becoming a quantitative product manager specializing in algorithmic trading and analytics at Bloomberg Tradebook.
Begari mainly focused on equities, options and FX trading algorithms at Tradebook, whereas now he oversees teams that create trading algorithms in the futures and U.S. cash Treasury markets at Quantitative Brokers.
The latter primarily uses C++ to code its trading algorithms, as did Tradebook, but he’s also used C# and Java at previous employers to build trading engines and algorithms. He also uses Python and R for statistics and data analytics and has used Thomson Reuters' Vhayu and the OneTick Database to access real-time market data. Many other firms value candidates who have used the kdb+ database for similar use-cases.
Those are primarily the skills and experience that you'll need to become an algorithmic trader.
“Knowing the data structures, algorithms and C++ or another programming language inside and out is critical,” Begari says. “That attribute is not easily available, and people really value that.
“Most [financial services and fintech] firms will hire a great programmer without trading experience over a mediocre programmer who knows trading.
Becoming a CFA will pay dividends, even for quants and algo traders
For programmers who want to transition into finance, a great way to get hired as an algorithmic trader is to pick up a certification like the CFA, Begari says.
“That gives you clear exposure to the domain and helps people to recognize that industry exposure,” he says. “I have CFA Level I and II, and while I still have to do Level III, that gave me a lot of exposure – I learned about the mechanics of how asset management works and how that translates into trading and execution costs.
“For any non-financial programmer to sign up for the exam and get the certificate, it takes a lot of hard work, and [hiring managers] will recognize the effort required to get the certification.”
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