Strats refer to mathematicians, statisticians, computer scientists, and engineers who work in the financial services industry. In particular, strats are used to describe the mathematicians, statisticians, software developers, and engineers who work at investment banks in a front office role. The first strats team was set up within the strategies team at Goldman Sachs by its chief investment officer, Armen Avanessians, in the early 1990s.
History of Strats in Investment Banks
Historically, STEM (Sciences, Technology, Engineering, and Mathematics) graduates who wanted to work in financial services did so in various back-office roles. It was especially true for large investment banks, and it was rare to find a professional with a STEM background to be working in the front office of a major investment bank. In 1985, Goldman Sachs hired Armen Avanessians from Bell Laboratories.
Avanessians was an electronic engineer and programmer who realized the growing importance of using mathematical algorithms to make decisions within financial markets. The strats team was born out of Avanessians’ desire for closer collaboration between quants (i.e., specialists in mathematical finance and statistics) and engineers (i.e., computer scientists and programmers).
What Do Strats Do?
1. Develop software
Software development involves creating (either writing or conceptualizing) computer programs that use mathematical and statistical techniques to generate revenue for the bank.
2. Bridge the gap between the front office and back office
In the past, traders and market makers used strats to communicate with the back office staff. Strats knew enough about the workings of the trading floor to understand the traders’ concerns, and they also understood enough about technology and process engineering to convey the concerns to the relevant back office staff.
3. Perform risk modeling
Strats use mathematical and statistical tools to quantify the various kinds of risks faced by the bank. The different departments at an investment bank face different kinds of risks. For example, quants attached to the fixed income trading desk and quants attached to the equities trading desk may work with very different mathematical and statistical models, because the risks faced by the two groups are vastly different.
4. Price exotic derivatives
The first generation of strats evolved from quantitative specialists within the exotic derivative pricing group at Goldman Sachs. The quants used advanced abstract mathematical concepts such as partial differential equations to accurately price exotic derivatives that did not have well-defined markets.
Strats – Key Skills
1. Programming skills
Strats need to be comfortable with at least one commonly used programming language. Most strats at major investment banks tend to be proficient in programming in at least two widely used programming languages. Examples of popular programming languages include Java, C++, R, and Python.
2. Understanding of stochastic processes
Strats must have an excellent understanding of stochastic calculus (also known as Ito calculus). Stochastic calculus uses analytical tools from classical Newtonian calculus to study stochastic processes.
3. Ability to synthesize programming skills with financial modeling
Strats are neither pure programmers nor pure financial modelers. Strats need to achieve a deep understanding of both fields without specializing in either. Therefore, strats need to possess an incredible breadth of knowledge and be able to synthesize information well.
The past decade has seen a major technological shift within the financial services industry. The exponential increase in the ease of collecting and harnessing data has allowed technology companies such as Alphabet and Facebook to create smarter algorithms.
In an effort to take advantage of the free availability of data, banks have started hiring an ever-increasing number of data scientists and statisticians. This new generation of strats specializes in analytical data management and work on machine learning, artificial intelligence, and digital product design in addition to programming and financial mathematics.