What do Quantitative Analysts (Quants) Do?
Quantitative Analysts, popularly called “quants” are a small group of professionals in the financial industry who are experts in Quantitative Finance.
Quants combine the knowledge of finance, maths and computer programming, and use this knowledge to develop complex financial models that are used by their employers to price and trade in financial instruments such as derivatives. Most models that you come across underlying complex derivatives are the job of a quant.
Who employs Quants and what do they do?
Quants are mostly employed by sell-side firms such as investment banks, and buy-side firms such as hedge funds. Apart from this, they are also sometimes employed by insurance firms, commercial firms, and financial software developers, among others.
On the sell side (e.g., investment banking), quants are primarily involved with derivative pricing and risk management. They are also called derivative quants.
On the buy side (e.g., hedge funds), quants develop quantitative models of asset behavior that are used to forecast prices, or create trading strategies.
How Much Do Quants Earn?
Given their specialized skill sets, Quants are among the highest paid people in the financial industry. It is common to see salaries of ~$250,000 and bonuses of $500,000 for experienced quants. The compensation also partly depends on the profits of the firm.
An entry-level position in quants can earn you a starting salary of $125,000 to $150,000.
Knowledge and Education
As we mentioned earlier, quants combine the knowledge of finance, mathematics, and computer programming to do their job.
In finance, they have strong understanding of finance theory, financial markets, derivatives, risks, and risk mitigation tools.
In math, quants require a strong hold on probability, statistics, linear algebra, differential, and integral calculus.
Quants need to have strong familiarity with programming tools to execute their job. For example, most high-frequency trading apps are developed using C++ or Java, while statistical analysis is conducted using tools such as Matlab, SAS, S-PLUS, etc. Excel is also extensively used.
Quants need to be able to apply their knowledge to develop complex models. For example, they may want to run Monte Carlo simulation to price a structured product. First they will develop the model, and then implement it using C++ or any other tool.
In the past few years, the demand for quants has risen with the growth in hedge funds and the increasing need for extensive pricing and risk management.
Becoming a quant is a challenging task, and your success in this position is highly dependent on your knowledge, programming skills, intellectual ability, and analytical skills. The job may not be as glamorous at it seems from outside. A quant spends most of his time with computer programs and in front of computer screens filled with numbers.
Most firms looking for quants expect you to have atleast a Master’s degree or PhD in Quantitative Finance, on subjects such as maths, economics, finance, or statistics. You may also pursue a Master’s degree in Financial Engineering or Computational Finance.
One of the popular certifications to become a quant is the Certificate of Quantitative Finance (CQF), which is a six-month intensive program that can be attended part-time in New York or London, or via distance learning from anywhere.
Data Science in Finance: 9-Book Bundle
Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.
What's Included:
- Getting Started with R
- R Programming for Data Science
- Data Visualization with R
- Financial Time Series Analysis with R
- Quantitative Trading Strategies with R
- Derivatives with R
- Credit Risk Modelling With R
- Python for Data Science
- Machine Learning in Finance using Python
Each book includes PDFs, explanations, instructions, data files, and R code for all examples.
Get the Bundle for $39 (Regular $57)Free Guides - Getting Started with R and Python
Enter your name and email address below and we will email you the guides for R programming and Python.