Final Projects: Quantitative Finance with Python
Class of 2019
Below are the projects submitted typically by groups of four students from the MBA or MSF programs at Simon.
The objective was:
Suppose you are opening a fintech shop that will get retail investors exposure to investment factors such as value, momentum, and so on. I want you to research the ETF options available to trade, download their returns, and conduct a careful analysis of how much exposure to the different factors these ETFs give investors, analyze the costs involved in each ETF (such as expense ratios, tracking error, alphas, and illiquidity) , and come up with a set of ETFs that would get your clients the cheapest way to get exposure to some set of factors.
You would them come up with a process to discuss how you would combine these different factors. I want you to contrast how the optimal portfolio that you would choose if could invest directly on the factors are different from what you invest if you could only invest using the ETFs that you are recommending.
I selected below what I believe are the very best projects, but there were lots of other projects that were really good too.
Below you can browse their video presentation. Have fun! And cheers to the class of 2019!