Courses - COMPAMA - COMPutational economics and optimization- Agents, Machines and Artificial intelligence
Courses | 2021-2024
The COMPAMA courses are available for internal and external students who meet the requirements. Each course is worth 2.5 credits and the teaching is concentrated in one week. For more details visit the corresponding webpages.
Students outside of NTNU should apply for admission through NTNU’s Søknadsweb. More information regarding the application process can be found at NTNU's research and PhD courses. For submitting applications after the formal deadline have passed contact directly Rodrigo Graça.
| Course | When | Guest lecturer |
|---|---|---|
| IØ8812 - Introduction to machine learning and AI methods with economic applications* |
Fall 2021
December 6th to December 10th 2021 (week 49)
Online |
The guest lecturer is Doron Avramov. He is a Professor of Finance at IDC Herzliya, Israel, and holds a Ph.D. in Finance from The Wharton School of the University of Pennsylvania. His research interests include the application of machine learning in financial economics.
In this course, he will mostly focus on Machine Learning Methods in Asset Pricing. |
| Spring 2024
April 22nd to April 26th 2024 (week 17)
NTNU (Trondheim) |
The guest lecturer is Rickard Sandberg. He is an Associate Professor of Mathematical Statistics at the Stockholm School of Economics (Sweden) where he also heads the Center for Data Analytics. His research interests include the applications of predictive analytics and machine learning in various fields of finance, economics, and retailing.
*NB! In this course, he will mostly focus on Machine Learning methods for customer and marketing segmentation, credit risk assessment, forecasting and fraud detection. |
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IØ8813 - Advanced course in economic applications of machine learning and AI
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Spring 2022
June 6th to June 10th (week 23) |
The lecturer is Sebastian Jaimungal. He is a Professor at the University of Toronto, a fellow of the Fields Institute for Mathematical Sciences and the Oxford-Man Institute. He acts on several editorial boards including Quantitative Finance and the SIAM Journal on Financial Mathematics. His research interests lie in mathematical finance and range over a variety of topics including machine learning, reinforcement learning, mean field games, stochastic control, and algorithmic trading.
In this course, he will mostly focus on reinforcement learning. |
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Spring 2024
April 29th to April 30th (week 18) & May 2nd to May 3rd (week 18)
NTNU (Trondheim) |
The lecturer is again Sebastian Jaimungal, and he will mostly focus on reinforcement learning. | |
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IØ8814 - Agent-based modelling in the interface between economics and behavioral psychology
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Fall 2022
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The lecturer is Wander Jager. He is an Associate Professor and Managing Director of the Groningen Center for Social Complexity Studies. His research focuses on how interactions between people give rise to the emergence of collective behavior. In particular, he is interested in the spreading of new technologies, opinion dynamics & polarization, and the societal transition towards sustainability.
In this course, agent-based modeling will be explored, including different applications and inherent challenges. The challenges of implementing behavioral theory in a valid manner in agent-based models will be addressed. |
|
Fall 2024
October 7th to October 11th (week 41)
NTNU (Trondheim) |
The lecturer is Gary Polhill. He is a Senior Research Scientist at The James Hutton Institute. He has more than 25 years of experience working on agent-based modelling in land use change, biodiversity incentivization, energy demand, everyday pro-environmental behaviour, commuting, district regeneration and agri-food value chains. He is interested in coupled social-technical-environmental systems and their complex co-evolutionary dynamics, and the computing infrastructure needed to support this.
This course will introduce agent-based modelling, explain why it is so well-suited to exploring the dynamics of complex social-ecological systems, and provide plenty of opportunities for hands-on experience with agent-based modelling. |
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| IØ8815 - Business economics in the era of artificial intelligence* |
Spring 2023
May 22th to May 24th (week 21) & May 30th to May 31st (Week 22) |
The lecturer is Selva Nadarajah. He is an Associate Professor of Information and Decision Sciences at the University of Illinois at Chicago. Selva's research addresses problems at the interface of operations and finance using reinforcement learning, machine learning, and optimization. His recent application areas of interest include the operations of commodity and energy conversion assets (e.g., production, storage, and transport), the corporate clean energy transition, and the social impact of this transition. Selva’s research has received awards from the operations (INFORMS), finance (Commodity and Energy Markets Association), and machine learning (NeurIPS) communities.
*NB! In this course, he will focus on reinforcement learning for a structured class of problems that includes multi-armed bandits and general resource allocation, that have garnered substantial attention in practice. |
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Fall 2024
September 16th to 20th |
The guest lecturer is Rickard Sandberg. He is an Associate Professor of Mathematical Statistics at the Stockholm School of Economics (Sweden) where he also heads the Center for Data Analytics. His research interests include the applications of predictive analytics and machine learning in various fields of finance, economics, and retailing. This course provides an intensive exploration of econometrics and artificial intelligence (AI) methodologies as applied to financial data analysis using Python. Participants will delve into theoretical foundations, engage in practical applications, and case studies. An extensive set of financial data, ranging from small to big data, will be analyzed. |
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| IØ8816 - Machine learning and numerical techniques in financial econometrics |
Fall 2023
November 6th to November 10th, 2023 (Week 45)
Norges Bank (Oslo) |
The lecturer is Eric Ghysels, a Bernstein Distinguished Professor of Economics at the University of North Carolina – Chapel Hill, Professor of Finance at the Kenan-Flagler Business School and Faculty Research Director of the Rethinc.Labs at the Kenan Institute. His main research interests are time series econometrics, finance, machine learning, artificial intelligence, blockchain and Fintech in general. His most recent research focuses on MIDAS regression models and related econometric methods. This course is designed to teach students how to conduct empirical research in asset pricing. More information on the program can be found here. |