Peer review for "Stock Prediction Using Foundamentals"

[dongtinm]

Their project is about quantitative finance. It is to find potential methods to improve the practice of interpreting operating performance of a public company. They want to explore how the operation of a public company affect its stock returns so that they can gain fresh insights from financial market. The dataset they are using is NYSE SP500company fundamental Kaggle dataset which contains the stock prices, the fundamental financial metrics, and the descriptions of each security from 2010 to 2016.
Here are three things that I like about this proposal:

1. This proposal clearly states their objective, and what dataset they will use.
2. Although many groups have used the same data they are using, they discovered their drawbacks. They are going to use a different method.
3. The idea of try to correlate the stock returns to macroeconomic data is interesting.
   Three things that need improvement:
4. To deal with the noise, they are going to simply remove all non-finance company. The result hence will lose generality.
5. I think it will be better if they can talk more about what value this project can bring. What organizations will be benefited from reading this project.
6. If this proposal is presented to an outsider, he/she may not understand the financial jargon they are using such as fundamental metrics.