Financial crises, machine learning and text data
Text data and machine learning have been increasingly popular in different fields of science, especially in economics. However, the use of text data has been somewhat absent in economic research related to financial crises. This project aims to fill this gap in the literature and answer important questions related to understanding and predicting financial crises by utilizing these novel data sources and methods.
News
People
Phd (Economics) Kim Ristolainen is the principal investigator of the This time is different-syndrome, excess risk-taking and financial crises: emprical approach utilizing machine learning and text data – project funded by Emil Aaltonen Foundation. He has previosly worked as a project reseacher in the research unit of the Bank of Finland and as an Yrjö Jahnsson Fellow in the Department of Economics at MIT. His research has been published for example in The Scandinavian Journal of Economics and in Journal of Financial Stability.
Tomi is finishing his phd dissertation on issues related to economic responses to different news information. He is teaching intermediate econometrics at the University of Turku. He is also a visiting researcher at the Finnish Institute for Health and Welfare. Tomi has published his reasearch for example in Journal of Gambling Studies.
Eetu is a research assistant in the project and he is also working on his Economics master thesis that studies the prediction of asset prices with novel machine learning methods. In addition to Economics, his studies have also focused on computer science.