Hi All,
As part of my masters project we have put together a lot of documentation and presentations regarding starting a quant hedge fund, which I think could be useful for this community.
We have a couple of slide decks:
Our research is focused on machine learning in finance. Also have a few presentations there plus our open source code that anyone could make use of.
Hope that you find this useful.
Link to project: http://www.quantspor...rce-hedge-fund/
As part of my masters project we have put together a lot of documentation and presentations regarding starting a quant hedge fund, which I think could be useful for this community.
We have a couple of slide decks:
- Data Driven Investments: Highlights the business process that hedge funds need to go through. This includes starting a hedge fund, raising capital, third party services providers, and flow of capital.
- Development Tools: A brief presentation on the tools we are using in the development of mlfinlab. It can also be seen as our way of work. TLDR: Github as a developer platform, Travis-CI for continuous integration (code style checks, 100% code coverage, unit test checks, documentation, push to PyPi Index), Pycharm as a dev-environment, Jupyter Lab as a research environment.
- Quantcon 2018: A quick review of our experience at Quantcon. The presentation is based on the keynote lecture by de Prado: The 7 Reasons Most Machine Learning Funds Fail.
Our research is focused on machine learning in finance. Also have a few presentations there plus our open source code that anyone could make use of.
Hope that you find this useful.
Link to project: http://www.quantspor...rce-hedge-fund/
