Part 1 (40-45 min talk)

Title: Artificial Intelligence-Driven Financial Risk Analytics and Portfolio Optimization

Abstract. Simulation and optimization algorithms are used in quantitative finance and risk management to model, evaluate, hedge and optimally re-balance portfolios of financial assets. The primary goal of simulation is to model uncertainty in asset values over time. Optimization techniques help to minimize risk and maximize performance of financial portfolios. As performance, numerical stability and practical applicability of simulation and optimization algorithms still remain a challenge in financial modeling, we look at machine learning practice to improve the accuracy of financial modeling. Moreover, we investigate how we can enhance formulating financial modeling and optimization problems with Artificial Intelligence algorithms such as Natural Language Processing and Neural Nets. Natural language understanding algorithms for portfolio stress-testing and for financial optimization problems such as sentiment analysis and chat-bots will be discussed and demonstrated.

This is joint work with Helmut Mausser, Curt Burmeister, Rob Seidman, Alina Sienkiewicz, Jerry Feng.

Part 2 (30 min talk)

Title: Machine Learning-Driven Course Curriculum Design

Abstract: Nowadays, we typically have gaps between job market demands and competencies that students acquire during their university studies. Course curricula in many cases lack practical content that is relevant for employers. Using automatic data collection from online resources such as online job postings and surveys, we utilize data analytics and natural language processing algorithms to extract useful information about relevant skills and qualifications from data. We use these data-driven research results to identify management competencies and technical skills for students to be included in courses curriculum. The aim of this project is to help universities to create or adapt master programs, especially in data analytics, in a way that graduating students would possess necessary skills that are needed at the job market. We would demonstrate how we re-designed sequence of courses and course curricula for Master of Business and Management in Artificial Intelligence Program at Kyiv School of Economics based on our research results.

This is joint work with Olena Skaliansa.

About the speaker: Oleksandr Romanko, Ph.D.

Senior Research Analyst, Watson Financial Services, IBM Canada

Adjunct Professor, University of Toronto

Honorary Director, Master of Business and Management in Artificial Intelligence Program, Kyiv School of Economics