This is the first in an exciting series of posts written by Frank Smietana, a new expert guest contributor to QuantStart. In this insightful new article Frank looks at the different career roles that are available in the systematic trading space.
A casual reader of trading blogs and news sites might draw the conclusion that our industry is manic depressive, swinging between the sad reality of well paid jobs disappearing overnight, and the panacea of AI-based alpha discovery turning every Python-competent quant into a billionaire.
The reality is far more nuanced than sensational headlines are capable of articulating. Capital markets still employ thousands of capable and talented humans globally, in mostly engaging and well compensated jobs. Key to understanding the nuance is a flexible view of where the intersection of human and artificial intelligence is headed.
While algos and electronic trading have eliminated thousands of jobs, a significant number of new positions have been created for system developers, risk analysts, quants and compliance specialists. Parallels abound in many industries. Unskilled factory jobs aren't coming back, but CNC operators, robot repair technicians and supply chain analysts are well paid and in high demand.
Before delving into specific job roles, it's helpful to define buy- and sell-side. These terms are misleading to novices, as both sides engage in buying and selling securities. A more accurate, though academic definition of buy-side would be "liquidity seeker", while sell-side would be "liquidity provider".
More practically, buy-side firms seek to acquire assets on behalf of retail, institutional or house accounts, hold them for some time period ranging from milliseconds to years, and then liquidate those assets, hopefully at a profit, while remaining within prescribed risk parameters throughout the holding period.
The sell-side is a service provider, arranging the sale or purchase of securities to their buy-side clients, either by acting as an intermediary or by buying/selling securities held by the firm. Buy-side firms earn money by charging management fees and making smart investments, while sell-side firms profit from trading commissions and pocketing the difference between the bid and ask on every trade they facilitate.
Buy-side firms run the spectrum from large institutional fund managers (BlackRock), insurers (Prudential) and pensions (CalPERS), to a multitude of hedge funds (Bridgewater being the world's largest) all the way to a startup fund with a few million in assets under management. Each of these buy-side segments operate under differing investment objectives, time horizons, and regulatory mandates. However, we can generalize job roles and career paths across these segments.
Staffing at large institutional buy-side firms can be thought of as a pyramid, built on a large base of financial and quantitative analysts. The next layer consists of traders, with each trade desk led by a head trader. The portfolio manager sits at the very top of the pyramid. This also describes the typical buy-side career path. Years of hard work and long hours at the lower levels, plenty of networking, great people skills, political savvy, and a fair amount of luck may eventually lead to a portfolio manager position. Scan portfolio manager profiles on LinkedIn and nearly all have MBA, CFA and even Ph.D. credentials. The recent news that BlackRock was firing 5 of the 53 fundamental portfolio managers in its active-equities group is enlightening. Not only is the portfolio manager position difficult to attain, it appears to be increasingly endangered.
Although the staffing structure at hedge funds is largely identical, and no less difficult to rise to the portfolio manager position, there exist far more small hedge funds than USD100B+ AUM institutional asset managers. So if you are set on a buy-side career path culminating in a head trader or portfolio manager position, pursuing this path via a hedge fund places the odds in your favor.
The definition of sell-side trader is a bit more ambiguous than their buy-side counterparts. Sell-side traders have traditionally spanned two disparate roles: proprietary trading and acting as market makers for both existing instruments and initial public offerings (IPOs).
Aside from bringing IPOs to market, both roles are dying a slow and painful death, thanks to automation and regulation. The sell-side prop trader was an early incarnation of today's HFT shops, though on a much longer timeframe. The motivation was to hold positions for short time periods while providing liquidity to market participants. Sell-side prop traders have largely disappeared thanks to the Volker Rule, a component of the Dodd Frank Act which seeks to minimize risk taking by large banks.
Before consigning sell-side prop trading to the dustbin of capital markets history, it's worth noting that regulatory regimes share common attributes with market regimes. They are largely unpredictable, and subject to huge and sometimes sudden swings in sentiment. While nearly everyone has written off sell-side prop trading, the promised gutting of Dodd-Frank by the Trump administration could well bring them back.
Until very recently, "system developer" was synonymous with "software developer". Although that has changed with the growing number of tools that don't require programming per-se, a strong background in computer programming and maths is still required to be successful in this role. On the buy-side, a system developer works closely with traders, quants and portfolio managers to formulate potentially profitable trading ideas, codify the "idea" into a testable system, either by writing software or specifying the underlying logic on a system development platform, and then rigorously testing the system to determine its risk/reward profile, behavior under various market regimes, and correlation with other systems. One "soft" skill required in this role is a fairly high frustration tolerance. Few ideas actually turn into production systems, and of those that do, a surprising number have a short shelf life, before their advantage is either arbitraged away or changes to market structure lessen their profitability.
On the sell-side, a system developer works in a similar capacity, but the objective is to develop algorithms (algos) that improve execution efficiency and minimize slippage when liquidating or acquiring positions in various asset classes. The origins of sell-side algos started in equity trading, but is now seeing uptake in FX, and the more liquid, electronically traded fixed income markets such as US Treasury futures.
One particularly important skill for system developers to master is efficiently managing large volumes of data. Although traditional data sources such as reference and pricing data may already exist in SQL databases, unstructured data such as Tweets, satellite imagery, and news reports are far more challenging to transform into usable content.
The "quant" title serves as a catchall for a number of different roles, mostly within buy-side firms. Quants work primarily on alpha generation, formulating new ideas for system developers to codify and evaluate.
Secondly, quants develop asset valuation models for spotting arbitrage opportunities when instruments diverge from their "fair value". Firms with the quantitative horsepower to spot grossly mispriced assets, and the patience and capital to hold those investments until market consensus aligns, are often spectacularly rewarded. This works best when applied to illiquid instruments and distressed or emerging markets.
Thirdly, quants play a key role in designing new investment products. For institutional investment managers these might include new ETFs, smart beta and factor-based products. Closely related to product development is the notion of modeling product capacity constraints. Many promising products, funds and strategies enjoyed a honeymoon period of stellar performance, marked by glowing press coverage and massive investor inflows; until illiquidity, collateral requirements, and regulatory caps rendered the strategy unworkable.
While a quantitative analyst works on generating alpha, a risk analyst is concerned with the arguably less exciting goal of capital preservation. While risk analysis demands the most mathematically advanced skill set in any buy-side firm, conceptually this field can be divided into three easily understood frameworks.
Ex-post risk is backward looking, involving the measurement and analysis of past market volatility and the factors that contributed to that risk, with the goal of determining whether trading and portfolio management decisions were adequately rewarded given the amount of risk incurred. Risk analysts also use ex-post risk techniques to understand how market and portfolio risk changes over time and how asset class correlations behave under normal and volatile market conditions.
Ex-ante risk is forward looking, and attempts to forecast future market volatility. Given that the future is unknowable, this side of the risk framework is far more difficult, but also one of the most exciting areas of research and potentially disruptive insights. Getting a risk forecast right, even occasionally, can reap big benefits for firms by alerting the portfolio manager to liquidate positions or establish hedges ahead of market volatility.
Scenario analysis (SA) is a third framework used by risk analysts that bridges the gap between ex-ante risk forecasts and ex-post risk measurement. By subjecting a portfolio to stress events like currency devaluations, interest rate hikes, or credit rating downgrades, SA helps risk analysts identify vulnerabilities in the portfolio. Risk analysts can either create hypothetical scenarios or use ex-post stress events such as the 2015 yuan devaluation, the 2013 "taper tantrum" or the 2008 Lehman bankruptcy as the basis of a scenario.
Although the career paths in systematic trading seem different enough, a few core skills apply to all roles. Math and programming skills are mandatory, along with an understanding of market structure, and a familiarity with asset classes and their tradeable instruments.
Soft skills are equally important. The ability to collaborate across teams, confidently present ideas in a coherent and articulate manner, ask relevant questions of co-workers, and defend ideas with solid data are all important career skills worth cultivating.
Algos and AI will certainly continue to displace jobs, but will also create new opportunities. Maintaining a flexible view of where technology is headed, and adapting your skill set accordingly will be key differentiators for both employees and entrepreneurs in the years ahead.
In future posts, we'll explore the most prominent systematic trading strategies currently deployed, and different structures for establishing a trading firm.comments powered by Disqus
You'll get instant access to a free 10-part email course packed with hints and tips to help you get started in quantitative trading!
Every week I'll send you a wrap of all activity on QuantStart so you'll never miss a post again.
Real, actionable quant trading tips with no nonsense.