Quantitative finance is the use of mathematical models and extremely large datasets to analyze financial markets and securities. Common examples include (1) the pricing of derivative securities such as options, and (2) risk management, especially as it relates to portfolio management applications. Professionals who work in this field are often referred to as “Quants.”
Quantitative finance focuses on the mathematical models used to price securities and measure risk. Financial engineering goes one step further to focus on applications and build tools that will implement the results of the models.
Financial engineering combines the mathematical theory of quantitative finance with computational simulations to make price, trade, hedge, and other investment decisions.
A quantitative analyst uses mathematical models and applies them to financial markets in order to support the trading and risk management departments that operate in banks and financial institutions.
A career as a quant requires a strong background in math, with analysts often getting advanced degrees such as a Master’s or Ph.D. in the field. These types of jobs are much less common than traditional financial analysts who work across the finance industry.
Specifically, quantitative finance analysts need to understand:
Most large banks and financial institutions have quantitative finance analysts working in either operations or information technology (IT) departments, which means there are numerous career opportunities available. Smaller, boutique firms typically don’t have such analysts, so you’ll want to focus on the bulge bracket banks and other large institutions in your career search.
Thank you for reading CFI’s guide on Quantitative Finance. These additional CFI resources will be a big help: