Machine Learning/Finance

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Machine Learning

The importance of machine learning in finance continues to grow.

Goldman Sachs hunts AI experts for all-important quant team

Paul Clarke, Financial News, Friday November 23, 2018 4:29 am, https://www.fnlondon.com/articles/goldman-sachs-hunts-ai-experts-for-all-important-quant-team-20180130

Abstract: "US bank is building its vast strats department by hiring a new generation of machine learning and artificial intelligence specialists."

Goldman Sachs is pitting itself against tech giants like Google and Facebook to attract scarce artificial intelligence talent as it places a renewed emphasis on ensuring its sales and trading staff are given cutting-edge IT.

The US investment bank, which has been described by CEO Lloyd Blankfein as a "technology company", is building its strats department, a huge division comprised of quant and technology professionals and which serves its trading businesses among other functions.

Thalia Chryssikou, co-head of global sales strats and structuring across fixed income currencies and commodities and equities, said the bank has shifted its focus towards recruiting a "new generation" of strats.

"The strats we hired 10 to 15 years ago typically specialized in modeling risk and pricing analytics," she said during an interview in an email newsletter from the bank. "Today, we're focused on hiring a new generation of strats who specialize in data management and analytics, including machine learning (ML), artificial intelligence (AI), program management and digital product design, in addition to quantitative sciences."

Goldman's strats division is made up of quantitative finance, engineering and technology professionals spanning various departments across the bank's trading functions, as well as back office and compliance. It has been growing since then-chief information officer Marty Chavez was handed control of both technology and strats in 2014.

Strats now comprise 27% of total headcount within Goldman Sachs's securities business, according to Chryssikou, up from 18% five years ago. Strats made up 27% of experienced hires within Goldman's FICC division last year, according to a September presentation by chief operating officer Harvey Schwartz. The team has also doubled within its investment bank since 2014.

Strats have become increasingly important to a range of functions at Goldman Sachs as it looks to automate more processes and equip its markets business with cutting-edge technology. Last year, for example, a team of 75 programmers at the bank introduced software to reduce some of the grunt work of junior investment bankers.

More broadly, however, Goldman's strats and technology teams have been creating systems to help their sales and trading staff make more informed decisions for their clients. In its fourth quarter results presentation, Chavez said the real growth in headcount last year was within "engineering" as the bank is "digitising our plarform generally".

Goldman recently hired Jeff Wecker as chief data officer and Matthew Rothman as head of data and client service. Rothman is currently hiring quantitative researchers within the securities division at Goldman.

"Almost nothing we do to service our clients—from trade execution, regulatory compliance and the advanced quantitative analysis we touched on earlier—could be possible without investments in technology and engineering," said Chryssikou. "It is essential and our hiring in the business reflects that."

Growth in fixed income futures algorithmic trading at JP Morgan has accelerated rapidly in 2020 as buy-side traders globally turned to the investment bank's machine learning-equipped algos to grapple with intense market volatility.

Speaking to The TRADE, Peter Ward, global head of futures and options electronic execution at JP Morgan, explains that while the volatility contributed to recent growth, adoption of futures algo trading has picked up pace with clients significantly in the last few years.

Since 2016, futures volumes traded via algos at JP Morgan has increased 40% year-on-year. In fact, algos now comprise almost 20% of the bank's total futures trading flow, up significantly from roughly 4-5% in 2016 and 2017, figures seen by The TRADE have revealed.

The period of intense volatility in 2020 due to the global pandemic played a key role in the cumulative buy-side adoption of futures algos as traders became more accustomed to on-screen execution and liquidity.

Reinforcement Learning

Quantum Computing