Key Developments So Far
As buy-side institutions, and the industry at large, continue to become more quantitative, Investment Banks have been increasingly investing in quantitative support within existing business lines which may or may not have had a direct quant team in the past. Specifically, this was seen across a number of European Investment Banks who invested in building out the robustness of their existing Repo and Equity Finance/Prime Brokerage business lines by creating direct quant support. Due to the greenfield nature of these initiatives, leadership opportunities building out these new desks were extremely attractive to the senior quant candidates, especially to those supporting legacy platforms within domestic banks.
Firmwide library technology migration and greenfield projects continue to be a priority for a number of European, US and Canadian investment banks. As new versions of modern programming languages are introduced (such as C++ 14, C++17), Banks recognize that they have to stay ahead of the curve and use the latest object-oriented languages in order to be up to par with their competitors. Many Tier 1 Investment Banks and vendors have been tasked with simply maintaining and calibrating their existing libraries whereas a few smaller Tier 2 and Tier 3 Investment Banks undertook a complete library rewrite. One of the most notable developments was at a Tier 3 Investment Bank that recently began rewriting their entire quantitative library from scratch – one which had not been touched for over two decades – in order to make their business more efficient and cohesive.
On another note, banks have been most notably building out their Equity Quant divisions. We’ve seen many sell-side institutions add additional headcount in their Equity Quant teams across internal and institutional trade execution. The ability to understand market microstructure, lower transition costs, and work on smart order execution strategies have been highly rewarding for internal trading teams as well as institutional clients.
Overall, there has been a strong emphasis on building out teams focused on Electronic Trading. The idea behind this is that if they can analyze the market microstructure, liquidity, and trading of other players in the market, they can execute and trade at a more optimal price point themselves. So much so that Electronic Trading teams within Investment Banks have felt as though the Buy-side traders are trading ‘smarter’ as time goes on, thereby incentivizing Investment Banks to come up with new and innovative product offerings.
Investment performance for 2018 was lackluster in the first half of the year but picked up in the second. According to HFR (Hedge Fund Research, Inc.), hedge funds gained just .81% in the first half of 2018 vs. the S&P 500’s 1.67%. Quant funds in particular have struggled the most and been the worst-performing category of funds in the first half of this year - down 4% as a category. This is clearly evidenced by major and well-known hedge funds such as Mana Partners, SPM, and Hutchin Hill shutting down. Common sentiment places the blame for this poor performance on market volatility in February, impacted by trade policies and rising interest rates.
Even with a sluggish year, investors do not seem to have any plans to slow down allocation to quant funds. Only 4.3% of clients polled by JPMorgan at an investment conference in March said they had no plans to use Artificial Intelligence and “Big Data” in their investment process. And the prevailing sentiment is that quant funds will be well-equipped to handle a bearish turn in the market that some economists feel looms on the horizon. For example, we’ve seen Exodus Point launch with a record $8 billion in AUM – making a big splash in the industry – and WorldQuant quickly raised $2 billion for its first fund open to outside investors.
From a recruitment standpoint these industry factors have led to many individuals feeling that 2018 was a good year to explore the market in search of a better deal or even opportunities to start funds of their own. With capital-raising seeming to not be the uphill battle that it was only a couple years ago, we expect this trend to continue in 2019 and have built a great network of Portfolio Managers who are opportunistically looking for better deals.
Recruitment Growth Areas
The Repo market has become a hot topic this year for some banks. Since the financial crisis, banks have become heavily regulated and as a result, they have been forced to change the way they do business. Historically the repo desk for most financial institutions has been the most profitable area and the primary source of most of the funding for the banks’ trading activities. Given the importance of this desk, banks are increasingly putting more emphasis on stacking their repo desk with premiere Quant Strats with cross-product knowledge to be the driving force behind revenue generation across the bank.
The demand for traditional quants to have strong technology skills raising a recruitment dilemma to most firms. In an effort to find this talent, investment banks are looking to non-traditional places like Amazon, Google, Facebook, etc to find the next generation of quantitative talent who are also machine learning and technology specialists. This type of talent is different from your traditional desk quant whom focus primarily on derivatives pricing. The machine learning technology professionals are seen as a versatile addition to a strat team that can help to support multiple lines of trading businesses, using a blend of mathematics and computer science to add value across a business that must move forward with technological developments in the market.
Electronic trading, particularly within equities, has seen an increase in headcount across major tier one US and European investment banks and smaller Canadian banks towards the tail end of this year and going in to 2019. The equity electronic trading across the biggest players on the street are seeing strong financial performances and as a result are investing heavily into research and development around new electronic offerings. Most investment banks now have teams that are solely focused on statistical modelling and development where they utilize different variations of machine learning and statistical analysis to build the best liquidity seeking algorithms on the market. The competitive landscape to have the best algo offerings continues to be at the forefront of investment banks challenges as they try to understand their client base and tailor their research and development needs according to what will get the most market share.
We’ve also seen an increase in demand from buy-side institutions to systematize their strategies which in turn forces them to reach out to prime brokerages in order to understand their trading strategies in more detail and run the most efficient trading that they can.
High Frequency Trading (HFT) in general has been stagnant due to the declining appeal over the last few years. That said, the need for talent still exists. The staple HFT players have been hiring on a case by case basis, and there are smaller (but no less competitive) prop-trading firms that are actively recruiting across quant research, trading, and technology. Candidates with HFT experience have also been targeted by internal execution groups at hedge funds, many of which have made concerted efforts to hire former HFT researchers for in-house algorithmic trading. These candidates have the skill-set needed to conduct market microstructure research to build optimal execution algorithms. As the traditional alpha signals have been mediocre over the past year, firms have placed a great emphasis on cutting costs.
While the buzz around cryptocurrency trading has quietened quite a bit since the first half of the year, it remains a point of interest and a desirable market for many. We’ve seen a tremendous uptick in Quants and Quant Traders being hired within the space as a number of prop-trading firms, hedge funds and family offices have been diversifying their portfolios to include cryptocurrency trading. Given how premature the market is from a systematic perspective, having the right mind-set and the ability to automate and generate alpha within crypto is highly desired. Cryptocurrency trading firms allow traditional Quants and data scientists the ability to work closer to the market and trading, while offering a bonus potential that rivals top-paying hedge funds and Investment Banks. There have been a number of candidates throughout the year that have left stable positions at investment banks and even hedge funds to start a crypto shop of their own, in some cases because they were making more on their personal trading account part-time than they were making full-time.
Salary & Compensation Trends
For senior-level talent, we have seen banks stray away from the traditional comp bands that they have typically been restricted to over the years. In order to attract top talent, banks have recognized that they must provide more-than-competitive offers in this candidate-driven market, and many have increased their average pay for Associate to Director-level hires.
Hedge funds are actively recruiting in the market this year as we’ve seen volatility pick back up. In order to entice high level talent throughout the year, hedge funds have been dangling the prospect of large guaranteed bonus figures, especially as most candidates that are already on the buy-side are more interested in this form of increased earning potential than a marginal base increase. Cryptocurrency firms in particular have leaned heavily towards offering unlimited upside of the strategies’ performance and stock options; however these firms tend to offer a much lower base given their start-up nature.
All in all, hedge funds continue to offer the best pay packages in the industry for both junior and senior level talent, so much so that we’ve seen PhD graduates receive packages that exceed some candidates with 3-5 years of experience. We believe this is due to the incredibly competitive market for junior level talent (largely in part due to the interest in being able to train them from scratch within the context of the firm’s culture), and as a result we have been advising our clients that in certain situations it might make more sense to buck this particular trend and hire someone with experience rather than a fresh graduate to avoid paying more for someone that has yet to prove themselves within the field.
And as a reminder, since October 2017, employers are no longer allowed to ask a prospective employee their compensation history due to the new law enacted to combat discrimination.
There has been a divergence between big, medium, and small sized community growth and this continues to expand. 53 of the largest metropolitan cities have accounted for 93.3% of the nation’s population growth since the last financial crisis. In addition, these metropolitan cities generated two-thirds of output growth and 73% of employment growth between 2010 and 2016. One contributing factor is the continuing growth of tech-related industries - as the need for Quants and data scientists continues to grow, job opportunities in major metropolitan areas will be on the rise.
New York has remained the premiere and most desired financial hub despite speculation around major world events such as Brexit. When the United Kingdom (UK) announced their intent to exit the EU in 2016, there was a lot of uncertainty from an economical/financial standpoint on how they would be able to thrive on their own. Many global firms pre-empted this potential risk by moving some UK-based teams (a large majority being in London) to other European cities. It remains to be seen what the next few years will bring and how this decision may ultimately affect the overall economy.
Apart from New York and London, cities that are fighting to get on the radar include Toronto, Luxembourg, Sao Paulo (currently leading in Latin America), Zurich, Singapore, Hong Kong, Tokyo, and Johannesburg. Of these, the APAC cities have been the most active, and many global investment banks have been actively looking to grow their presence in the region to stay abreast of competition.
Within firms, the largest shift in relocation we have seen this year has been among the Back Office & Risk functions. Many Risk teams have been cutting costs and moving their teams either outside the New York metropolitan area to cities like Charlotte/Raleigh, or even outside the country to cities with a much lower cost of living. An extreme example of this move is Credit Suisse, currently in the process of moving a large portion of their risk team to either Wroclaw (Poland) or Raleigh. Since real estate prices in New York continue to rise and revenue-generating functions of the business benefit from being in close physical proximity to Manhattan given the stock exchanges, banks are trying to optimize costs around these other functions in this way.
Advice For Candidates
It is especially important for mid-senior level Quants to remain current and hands-on with the latest technology. With the infrastructure around the Quant space continuing to develop, it is vital for candidates at all levels to remain up to speed from a programming perspective and to have a strong understanding of what technology groups at other banks are doing in order to drive innovation and stay competitive. It has become rarer to find senior candidates that have remained hands-on throughout their career, which has led to stronger financial packages being offered to the few that fit the bill.
Discussing the benefits of networking may seem like beating a dead horse, but given the size of Quantitative Finance, this is especially important. Just about all of our clients will conduct an informal or formal reference check at some point in the interview process.
It is also important to enter an interview with an idea of the sort of compensation packages that you would be happy with. With new salary laws in place, it’s important to be upfront with a prospective employer on what your expectations are for salary and total compensation. Avoid selling yourself short, but keep in mind that having too high of an expectation may disqualify you from being selected to interview or move forward in an interview process. We would be happy to discuss compensation trends for your specific role, seniority, and location relative to peers in the industry.
Technical Skills In Demand
In the Front Office Quant market, C++ and Python remain the most vital languages to know in order to break into/remain in the Front Office. Hiring managers have become more lenient on asset class knowledge as this is something that can be taught, whereas coding experience requires hands-on previous experience either in academia or in previous roles. An increasing number of junior candidates have enrolled in coding bootcamps that are offered through various schools and academies since they recognize that this will make them that much more marketable and desirable to a potential hiring manager. Oft-mentioned languages/technologies include Matlab, SQL, Java, Hadoop, Q, KDB+, C#, C++, HTML5, Python, and R.
Machine Learning techniques and data processing continue to be the most in-demand skills. Market microstructure and algo execution model development and research are also in high demand by both banks and hedge funds. Many hedge funds and buy-side shops are getting “better” at trading by working with smarter execution systems, and therefore demand the best talent to keep the innovation moving forward.
What Hiring Managers Are Looking For
A PhD in a quantitative field is a must-have for the buy side and one should also develop a strong programming skillset. For data and research, Python has become the main programming language of choice. For implementation, trading, and automation, C++ and Java remain the language of choice. A strong understanding of finance even for purely quantitative roles is also something that can set one apart from other candidates.
And as always, having strong communication skills is a given. This is more prevalent across Portfolio Management teams and Front Office teams where there is ample interaction with Traders, Salespersons, and Portfolio Managers. The ability to discuss and explain research findings, new applications, and general data-use to the end user is very important and something our clients are vetting candidates for by testing communication skills and the ability to work well in a team setting.
We’re excited to see how the Quantitative Finance space continues to develop in 2019, both in terms of the technologies being developed and implemented, as well as organizational changes in response to the shifting landscape (cryptocurrency markets, regulatory reform etc.). In particular, we anticipate that most buy-side firms will continue to invest heavily across machine learning technologies sources, and most sell-side firms will continue upgrading their quantitative frameworks and electronic trading offerings. As a recruitment firm embedded in heart of the financial services industry, we are excited to continue our partnerships across FinTech, Investment Management, and Investment Banking, and to remain at the forefront of market developments.