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Speaker "Victor Martinez" Details Back

 

Topic

Multivariate Time Series and Deep Learning

Abstract

Given the recent successes of AI/ML techniques to identify complex patterns in multivariate data sets, we will explore some of the analytical properties of such techniques and study the potential in financial time series analysis. As pattern recognition methodologies, ML has been very effective in combining complex structures to identify stationary relations that emanate from various combination of high dimensional data sets. In the case for non-stationary systems, ML has been only modestly successful. Its impact to detect patterns in multivariate financial time series has been limited. Deep Neural Networks can be modified to detect patterns in time for time varying relations that are persistent by conservation principles
Who is this presentation for?
Finance analytical experts and AI practitioners
Prerequisite knowledge:
General finance and deep learning
What you'll learn?
Application of ML in finance time series

Profile

Victor H. Martinez, PhD, is a Managing Director and Lead Data Scientist at State Street Corp. Recent work at State Street consist of applying AI methodologies for portfolio management, multi asset pricing focusing on liquidity, analysis of flow, and correlation risk. He also worked as a Quantitative Director Analyst focusing in mathematical finance methods for asset pricing and application to illiquid asset valuations, derivatives, risk management, business valuation, and study of fund dynamics. Prior to State Street, Mr. Martinez served as professor of Finance for the Zicklin School of Business at Baruch College of the City University of New York where his research included Option Theory, Asset Pricing, News Analysis, M&A, and Mathematical Finance. He also worked for various hedge funds including Citadel LLC, Archelon LLC, and Tradelink focusing in quantitative trading strategies and risk management. He holds a PhD in Theoretical Physics from the Massachusetts Institute of Technology and a BS in Physics and Mathematics from Stony Brook University at State University of New York