Tutorials
I started a YouTube channel to provide tutorials for people interested in coding and financial markets/quant research.
All of the code is published on my GitHub here: https://github.com/joelalcedo/codewithjoel_r
In this video, you'll learn basic implementation of hierarchical clustering of cryptocurrencies and stocks; useful for a wide range of cross-asset research, portfolio construction and optimization problems.
Why does this matter? Stocks, currencies, bonds - basically any asset - can go up/down for the same reasons (eg. same macro factors, policies, a pandemic). An uncorrelated/diversified portfolio is an important tool to improving the likelihood of better risk-adjusted returns.
An analogy...strawberry jam & jelly are different foods made of the same fruit. If you exclusively eat jam and jelly, you'd likely end up with strange health issues. Stomach space is finite - efficiently allocating a broad range of nutrients mitigates the risk of health issues.
In this tutorial, you'll learn some tips and tricks on creating awesome interactive data visualizations in R.
This link will show you all of the different types of data visualizations you will learn how to create in Tutorial #2.
Being able to work with data is one thing - having the tools to communicate the results take time, practice and a bit of art.
In this tutorial, we'll walk through how to calculate a volume weighted average share price in R using data wrangling techniques.
In the data science community, a popular adage states that over 80% of a practitioner's time is spent wrangling and cleaning data.
This rings very true in my experience (in fact, I would say the number is north of 90%!).
Having sharp data wrangling skills is essential.