It is common knowledge that roles in Quantitative Finance require expertise in several quantitative domains: mathematics, one of several programming languages (e.g. R or Python), statistics, and finance. As such, the question often arises in the minds of aspiring quantitative analysts: as a beginner, how can I learn about quantitative finance? Such a multi-faceted discipline will require piecing together learning from the several aforementioned domains. As a beginner this can be overwhelming as such a broad array of disciplines is not readily found in a silver bullet course teaching all the essentials in an easily accessible manner.

When beginning the journey of learning about quantitative finance it is important to use the internet as it will be full of invaluable resources that can be leveraged. When looking up quantitative finance online, a logical starting point is gaining a strong grasp of mathematics to give a student a firm grounding in using quantitative methods and tools. This will form the foundation for the rest of the learning journey. In particular basic mathematics such as calculus, differential equations, linear algebra, and probability theory, will need to be grasped at a high level. This is then supplanted by more intermediate and expert level content such as stochastic calculus. Most high level universities are able to explore some, if not all, of these topics at an undergraduate level. It is important to note that such an emphasis is put on quantitative competency as the nature of quantitative finance is concerned with the application of mathematical models to guide/predict investment decisions as opposed to utilising financial and economic theory.

After which, there are multiple paths in which a beginner quant finance learning journey could take. There are several skillsets and domains of knowledge that need to be acquired such as: programming, statistics (i.e. stochastic analysis, time-series analysis, probability theory etc), and acquiring a deep knowledge of finance to guide the application of the quantitative elements. Such exposure takes time to build up and students often pursue a masters to help in this process or in some cases a doctorate to get more hands on exposure in the research design process end-to-end and then testing the hypothesis.

However, it is also common for beginners in the quant finance field to already possess an undergraduate and postgraduate in a technical field (e.g. engineering, computer science, mathematics). As such, in conjunction with their already technical field it is also common to undertake one of several external qualifications to help learn quantitative finance given the academic position they are starting from i.e. strong technical foundations that need to be built upon. In this regard there are several options depending on where a student is at and how intense they want the process to be (a key consideration when balancing other commitments).

In short, there are multiple ways a beginner can learn quantitative finance given how several technical disciplines are intertwined in their application to finance. The only qualifier to that statement is there needs to be a foundational level of mathematics that can be built on.