Rate My Professor Hasan Fallahgoul
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Always patient and encouraging to students.
Helps students unlock their full potential.
Inspires students to love their studies.
Always positive and motivating in class.
Encourages students to explore new ideas.
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About Hasan
Hasan Fallahgoul is a Senior Lecturer of Quantitative Finance in the School of Mathematics, Faculty of Science, at Monash University, a position he has held since July 2017. He is affiliated with the Centre for Quantitative Finance and Investment Strategies and serves as Course Director for the Bachelor of Applied Data Science and the Bachelor of Applied Data Science Advanced (Honours). Prior to joining Monash, Fallahgoul was a postdoctoral researcher at the Swiss Finance Institute at EPFL and at ECARES, the European Center for Advanced Research in Economics and Statistics at the Free University of Brussels, Belgium. In October 2020, he joined the advisory board of the Journal of Financial Data Science. Fallahgoul holds a PhD, with his doctoral research focused on the benefits and costs of tail risk measures based on stable, geo-stable, and tempered stable processes, investigating losses during financial crises and market distress.
His research specializations include financial econometrics, quantitative finance, asset pricing, tail risk, big data, and machine learning. Key publications encompass 'Asset pricing with neural networks: significance tests' (Journal of Econometrics, 2024), 'Risk Premia and Lévy Jumps: Theory and Evidence' (Journal of Financial Econometrics, 2023), 'An L-Moment Approach for Portfolio Choice under Non-Expected Utility' (Journal of Financial Econometrics, 2025), 'Asymptotic Properties of ReLU FFN Sieve Estimators' (Studies in Nonlinear Dynamics and Econometrics, 2025), 'Inside the Mind of Investors During the COVID-19 Pandemic: Evidence from the StockTwits Data' (Journal of Financial Data Science, 2021), 'Modelling tail risk with tempered stable distributions: an overview' (Annals of Operations Research, 2021), and 'Quanto Option Pricing with Lévy Models' (2016). These works contribute to advancements in neural networks for asset pricing, high-dimensional learning, Lévy jump models, and investor sentiment analysis during pandemics. Fallahgoul has produced 19 articles and one book, with research activity spanning 2009 to 2025.