Our project consists of 3 components (Rank, Filter, and Allocate). The Ranking algorithm assigns ranks to 8000+ listed companies based on its score on 78, time-sensitive metrics. The Filter algorithm will execute buy order for the highest ranked which meet Filter requirements. The Allocate will determine the amount to trade. It is a low-frequency, long-short, market neutral strategy. We obtain our data from Factset, and use Portfolio123 for our backtesting. We currently have a ranking algorithm, but we hope to reiterate it to make it more resilient towards systematic risks, and we also want to find a more optimal & efficient way to run tests. Please let us know if you are interested. We can discuss the details and the hours subsequently.
Years: Any
Location: Anywhere
Requested on: 2020-08-12
Tensorflow, Python, Machine learning, Data Analytics