Welcome!

I am the Director of the Dataism Laboratory for Quantitative Finance (DLQF) and an Assistant Professor in the Department of Economics and the Computational Modeling and Data Analytics program at the College of Science, Virginia Tech.

My research lies at the intersection of statistical machine learning and big data econometrics, with a particular focus on high-dimensional nonlinear time-series analysis and its applications in macroeconomic and financial forecasting, as well as the estimation of large financial networks. I earned my Ph.D. in 2017 from the London School of Economics and Political Science, Department of Statistics.

In addition to my academic work, I occasionally consult for financial firms and governmental organizations, particularly on projects related to pattern recognition and knowledge discovery, including computer modeling and forecasting. I have also worked in the industry for several years as a trader and portfolio strategist, where I developed various algorithmic trading strategies.

Research Interest:

Big Data Econometrics, Statistical Machine Learning, Deep Learning, Quantum Machine Learning, Forecasting, Computational Finance, Network Analysis, Nonlinear Systems, Hyperparameter Optimization

News:

• 2022/05/03 – Ali Habibnia received the PPE Research Fellowship award from the Kellogg Center for Philosophy, Politics, and Economics for the History and New Trends of Measuring Dependence: From Bayes, Galton, and Pearson to the 21^st Century.
• 2021/04/26 – Ali Habibnia, Russell J. Hewett, and Dawson Miller (VT Mathematics) received an award from the Virginia Tech College of Science’s Lay Nam Chang Dean’s Discovery Fund for Deep Learning for Non-linear Common-factor Modeling and Forecasting in Economics.
• I will be presenting  “Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)” at Stanford Institute for Theoretical Economics – Asset Pricing Theory and Computation Summer Workshop, 18 August 2019 | USA
• I will be presenting  “Financial Time-Series Analysis: A Deep Learning Approach” at MATLAB Computational Finance Conference 2018, 24 May | London, UK
• Join us for the 2^nd Big Data Economics Summer School, 5-8 August 2018 | Tehran, Iran