Breaking through the Chinese walls to the open-source and data for my research project
Presented by Ilya Zaznov
Open source plays important role in many different fields, especially in research. The research project I’m currently working on is not an exception, its goal is to explore the application of machine and deep learning methods in algorithmic trading with the main focus on the trading strategy. In this process I need at least three core components available in open access:
Prior research papers in this field
Code for the machine learning models described in these papers
Data-sets used for training and testing these models
At the beginning of my project, I expected to easily open source all of these, however, in each of these three dimensions I encountered challenges of two kinds: availability and quality. I would like to share on the upcoming thematic evening what are the particular open sourcing challenges I am experiencing and how I’m overcoming these Chinese walls.
Ilya Zaznov is a PhD student in the department of Computer Science, University of Reading, UK. His PhD research area is an application of machine/deep learning methods to the algorithmic trading. The main topic of the thesis is formulated as “Application of Deep Learning methods to the Limit Order Book and Order Flow Data for Stock Price Prediction”.