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Quantitative Research (Quant)

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A Quantitative Researcher (aka a Quant) uses mathematics and/or computer science skills to solve finance/investment related problems.

 

As financial companies look for different ways to make money and have an edge over their competitors, there has been a rapid shift towards the use of quantitative strategies. Some examples of firms that often have quants are:

Keep on reading below to understand Quant Research within minutes.

 

What does a Quant actually do?

A quant spends their time researching ways to help the firm succeed. Often times this research involves creating (or improving preexisting) mathematical/computer science models.

 

What do we mean when we say a “model”? A model is just a system that is created to help replicate a real life scenario (like a miniature model of a house!). Additionally, mathematical models usually have inputs (sometimes called “signals”) and provide the user of the model with an output/answer. Furthermore, over time, when trying to improve a certain model, quants will research new signals to help make the model more accurate.

 

 

Below is a typical, simplified example of a model quants design at a financial investment firm:

 

Investment Firm (like an investment manager, hedge fund or trading firm) Quant Model: 

  • Quants at these firms sometimes build models to determine the price of a stock. 
  • For example, their input to the model might be the name of a stock, and the output would be the “fair price” for this stock. 
  • If the current price on the stock market is lower than the “fair price” the model outputs, it is viewed as “cheap” and the firm buys that stock. 
  • Ultimately, this model tells the firm how it should invest aka buy or sell stock. 

While the type of research quants do varies depending on the company, generally speaking, the goal at an investment fund is to discover money-making opportunities, and quants help provide their firms with the tools to do just that. 

 

Why do quants build models? Simple, real life analogy:

Let’s further explain what a model is and why it is useful for a firm through the use of an analogy. The analogy we will use is a basic calculator.

 

Example: 

  • Let’s break down how a basic calculator works and how that is similar to what a “model” is.
  • The inputs for making a calculator do what you want are the numbers and the mathematical operation.
  • For example. If you want to know what 2+2 is, you input a “2”, then a “+”, then a “2”, then a “=”. And the output is your answer, “4”.
  • Here we can view the calculator as a model. It is designed a certain way to make the user’s life easier (can do math operations quickly and easily).
Just like someone designed and built the calculator to take inputs and spit out an answer, quant builds a model that is designed to give the user answers simply. Building these models (and making sure they work as intended) can take a lot of time, research, and hard work. Furthermore, these complex models can guide firms to make the best decisions possible and help them be successful.
 

Junior Quant Research Project Example:

There are many different types of research a quant does. Some examples are: finding new signals, improving old signals, improving how signals are implemented (or combinations of those). To clarify, an investment or trading “signal” is usually an input to a model that indicates whether to buy or sell something.

 

Below is how a quant research project on a new signal often looks at a hedge fund:

  • Signal generation projects usually originate from senior members of the team.
  • Senior members give junior quants a write up on some ideas they have and the direction they see the project going.
  • Also, they provide a lot of relevant academic papers to help start the research process.
  • The junior quant spends a lot of time researching and asking any questions to senior members of the team along the way.
  • Every week or a couple of weeks the junior quant presents in informal settings to their boss summarizing their findings. Additionally, they ask questions about the next steps and get feedback.
  • After the research process is complete, the junior quant comes up with a proposal (aka a thesis) supported by the research.
  • A Powerpoint presentation summarizing their findings and why it leads them to the specific proposal is given to the entire team plus some senior people at the firm.
  • After this, feedback and follow-ups are given to the junior quant before approving the proposal.
  • Finally, the proposal is implemented and the firm uses the research to help them make investment decisions.

Responsibilities of a junior quant researcher:

  • 70% of the time, a quant is working on longer-term research projects. These projects usually require heavy mathematics, computer science, data analytics, etc. and take at least a few months.
  • 20% of the time, a quant will be communicating with their team/other teams and answer any questions others might have on how the model works (since they designed it and are the experts).
  • 10% of the time is spent monitoring past projects, seeing how they perform, and trying to identify areas of improvement.

Some general examples of tools a quant uses:

  • Mathematics – the specific subject matter depends on the company, but the most common are probability, statistics, and calculus.
  • Programming Skills – this is usually very important for data analytics and being able to test their strategies.
  • Excel – to help manage data.
  • Powerpoint – for making presentations on research.
  • Academic Research Papers – to help generate ideas for strategies.

What types of skills are necessary to be a successful Quant?

  • Strong mathematics background – many firms require a graduate degree in a technical subject.
  • Programming background – being a strong programmer allows you to get the information you need quickly and efficiently. Furthermore, it allows you to do powerful big data research projects.
  • Creative – a lot of the time, the solution to the problem you are trying to solve has never been found before. You need to be creative in how you approach this process and try to find a solution.
  • Organized – you spend a lot of time researching, so knowing what you’ve done and what you need to do will help make your research more efficient. Furthermore, you need to present your research to your team when a project is complete and having organized research helps make this more clear for everybody involved.

What are some challenges of being a quant?

  • It can be hard to find new and successful strategies all the time.
  • Research requires creativity and you are often on your own. While this freedom is often a positive it can be stressful to take on this responsibility.
  • Investment strategies constantly need to be improved (a single strategy does not last forever).
  • If a project has a deadline, hours can become much longer than normal shortly before the deadline.

What are some benefits of being in quant?

  • Get to work with some of the brightest minds in the world (many have advanced degrees).
  • Very well-compensated – quants (at investment and trading firms) tend to be some of the best-paid employees on Wall Street.
  • A lot of freedom to be creative and solve exciting problems.
  • Learn a lot – you do not need to be the best at every skill right away (as a junior level quant). You often need to be very good at one or two skills and will learn whatever you are missing very quickly. This is made easier (and more exciting) because you learn by doing and working with brilliant people.

Typical Salary?

The average entry-level quant total compensation is anywhere between $90k-$300k. Some companies pay even more than this, but the grand majority fall in this range. The total compensation after entry-level varies a lot depending on performance, experience, and where you work. But, in general, top-performing quants (aka those that help build the most profitable models) are very valuable to financial firms. As a result, these top performers get paid some of the largest salaries and bonuses on Wall Street.

 

According to ZipRecuiter, the average Quant Researcher makes around $162k per year.

 

Should I go into Quantitative Research?

If you have a strength and/or passion for problem-solving, mathematics, data analytics, programming, investing, etc. you should consider looking further into quant research. You can learn a tremendous amount and work with some incredibly smart individuals (with very impressive backgrounds) as a quant. Furthermore, the compensation is very strong, so you can be intellectually challenged and paid a lot.

 

Some typical career paths for a quant include: working your way up the quant ladder (and becoming a manager), switching to a quant role at another company, or any other technical role (like software engineering, data analytics, trading, academia, etc).

 

If you are interested, we suggest you read a bit about one of the earliest (and most successful) “quantitative hedge funds”: Renaissance Technologies. They are the golden standard for quantitative investment strategies because they are consistently very profitable, and those who build their models are rewarded very generously.

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