Awesome Open Source
Awesome Open Source


Presentations

Slide show presentations regarding data driven investing.

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.

Does Meta Labeling Add to Signal Efficacy?

Successful and long-lasting quantitative research programs require a solid foundation that includes procurement and curation of data, creation of building blocks for feature engineering, state of the art methodologies, and backtesting.

In this project we create a open-source python package (mlfinlab) that is based on the work of Dr. Marcos Lopez de Prado in his book Advances in Financial Machine Learning. Dr. de Prado's book provides a guideline for creating a successful platform. We also implement a Trend Following and Mean-reverting based trading strategies. Our results confirm the fact that a combination of event-based sampling, triple-barrier method, and meta-labeling improves the performance of the strategies.

The presentation of this slide is also in this repo titled: Improved Signals.

This document is more of a project report, our goal in Capstone 2 is to write an academic paper. (I would have liked more time to fix the formatting and flow of this document)

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.

Hackathon Portfolio Optimization

Linear financial modeling is prime for disruption. In this presentation we show how de Prado’s Hierarchical Risk Parity portfolio optimization outperforms mean variance and other techniques (out-of-sample). This slide show was developed for the Capitec Bank hackathon where we won a small prize for best “Spirit”.

Improved Signals

Does Meta-Labeling Add to Signal Efficacy? A slide show presentation illustrating how meta-labeling results in improved performance metrics for investment strategies (out-of-sample). It is a technique that every discretionary and systematic fund should employ and will aid fundamental firms transition to quantamental.

Quantcon 2018

A quick review of our experience at Quantcon. This is where Ashutosh and Jacques met for the first time in person and got signed copies of Marcos Lopez de Prado's latest book Advances in Financial Machine Learning. The presentation is based on the keynote lecture by de Prado: The 7 Reasons Most Machine Learning Funds Fail.


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