Python for Financial Analysis Series — Introduction (2024)

Highlight:

• A concise introduction on how we can use Python for financial analysis.

Background

Python has become one of the most popular skills needed in the financial industry. Major banks, big asset managers and famous insurance companies are requiring their employees to know Python. If Excel/VBA was (or maybe still is) the number one tool for financial analysts, Python and Jupyter Notebook are taking off within this community.

Why Python?

Good question! Computer engineers may give us a huge list of why Python is good but also evil. We may also hear the data scientists and statisticians arguing about Python vs R. We probably have found articles about Julia (a new start language used by many hedge funds) outperforming Python.

But when we go back to our financial analysts work, do we care which one is in theory better?

No! We care more about if we can get the job done before 6 pm every day.

Python is such a language easy to learn (even simpler than VBA in Excel). Python is such a language coming with many matured toolboxes, which can help us done the job more quickly (maybe elegantly as well). Python is such a language just powerful enough for most of our daily tasks.

Don’t get me wrong. There are very challenging financial tasks needing better technologies even better computer languages to handle with. But let’s face it, the majority of our daily works are not going to be a big deal for Python at all. So just don’t worry about the performance for now.

So now we want to learn Python, but HOW?

I heard from many people the followings:

After finishing the online classes, it is still difficult to apply what have learnt to our daily works.

I found the class is way too long and teaches things that I will not use in the future.