Video Description
A Talk from Machine Learning in Quant Finance Conference 2024
In this paper, a shorter and more publication focused version of our recent article “A Bottom-Up Approach to the financial Markets” (Mahdavi-Damghani & Roberts, S. 2019 .) is presented. More specifically we propose a new approach to studying the financial markets using the Bottom-Up approach instead of the traditional Top-Down. We achieve this shift in perspective, by re-introducing the High Frequency Trading Ecosystem (HFTE) model Mahdavi-Damghani, B. 2017 . More specifically we specify an approach in which agents in Neural Network format designed to address the complexity demands of most common financial strategies interact through an Order-Book. We introduce in that context concepts such as the Path of Interaction in order to study our Ecosystem of strategies through time. We show how a Particle Filter methodology can then be used in order to track the market ecosystem through time. Finally, we take this opportunity to explore how to build a realistic market simulator which objective would be to test real market impact without incurring any research costs.
Speaker Bio
Dr. Babak Mahdavi-Damghani
Dr. Babak Mahdavi-Damghani (BMD) completed his PhD in Machine Learning for Quantitative Finance at the University of Oxford. He has a broad range of work experiences in the financial industry, notably having worked for Citigroup, Socgen, GAM Systematic, Credit Suisse, LSEG, the Oxford Algorithmic Trading Programme and Andurand Capital Management.
He has experience through all the major asset classes in both the buy and sell sides. He is the founder of EQRC and an alumni of the Oxford Man Institute of Quantitative Finance. He is also the author of numerous publications, including cover stories of Wilmott magazine and mathematical models currently taught at the CQF.