hudson-and-thames / research
- понедельник, 8 июня 2020 г. в 00:20:53
Jupyter Notebook
Notebooks based on financial machine learning.
Contains all the Jupyter Notebooks used in our research.
All of the research we do in these notebooks is on the full tick history dataset from Tick Data LLC, but not provided because of royalty fees. The data can be purchased for about $750 US Dollars for the full history of a single ticker.
We do provide a 2 year sample on tick, volume, and dollar bars to help the community get started.
Our hope is that the sample data and notebooks will enable the community to build on the research and contribute to the open source community.
A good place to start for new users is to use the data provided to answer the questions at the back of the chapters in Advances in Financial Machine Learning.
Please review the Guidelines for research
The following folder contains 2 years sample data on S&P500 Emini Futures, for the period 2015-01-01 to 2017-01-01.
Specifically the following data structures:
Recommended versions:
conda create -n <env name> python=3.6 anaconda
accept all the requests to install.source activate <env name>
.pip install -r requirements.txt
conda activate <env name>
pip install -r requirements.txt
We will create a symlink inside each of the Chapters for ease of dataset changes. You may change the symlink of official_data
to your own dataset rather than using the 2 year sample; the format follows Tick Data LLC.
Create a symbolic link inside the Chapter folder to where you saved the official data:
cd Chapter3; ln -s ../Sample-Data official_data
BlackArbsCEO has a great repo based on de Prado's research. It covers many of the questions at the back of every chapter and was the first source on Github to do so. It has also been a good source of inspiration for our research.