Hi, developer of the tool here. Have been dabbling in trading for about two years and have plenty of data science experience. Trying to merge the two by working on a lot of tools right now. This one was inspired from a few lectures at the MIT's 18.S096 (Topics in Mathematics with Applications in Finance) course that I am taking right now on the OCW.
If you have any questions or comments, happy to discuss.
I’ll give it my second biggest big compliment: I’ve wanted to do something like this for years. (My biggest compliment is: why didn’t I think of that?)
Anyway, do you have a robust methodology for testing this? I’ve seen people make simple mistakes like summing volatilities or using the European options model for US options and dozens of other small issues. It would almost be as large a contribution to come up with a testing suite.
I am at lecture 11 right now (volatility modeling). I guess the best thing I learned was value at risk models and how companies like Morgan Stanley use historical returns, covariance matrices, and monte carlo to estimate their maximum risk. That was fascinating.
Other than that, I dived here and there and found the portfolio optimization lectures to be good. To be honest, all lecture taught by people from the industry are damn good.
As for the strategies, eigen portfolio would be one. I started reading about it and digressed to another blog (https://srome.github.io) that had some excellent resources. From there, I had to read a few more papers to get to MSR. That makes three strategies -> Eigen portfolios, Minimum Variance, and Maximum Sharpe.
The last strategy is using a genetic algo to maximize sharpe ratio. That is a custom implementation as I've quite some experience with GAs.
Happy to talk more about the course and the strategies.
If you have any questions or comments, happy to discuss.