Thesis Supervision #
Ph.D. Students #
Ming Cheng, 2023 - Present, co-superversion with Prof Peter Boswijk
Sombut Jaidee, 2018 - 2022, co-supervision with Prof Jiti Gao
Tinbergen Institute Research Master Students #
Ming Cheng. A Guided Neural Network Approach to Volatility Forecasting. August 2023.
Hans Ligtenberg, Explaining the unconditional value premium using neural networks, August 2021. Python codes here
Master Students #
University of Amsterdam #
Julian Kerssens, Innovating market sentiment analysis with natural language processing, August 2024 (Nominated for Jan Brouwer Thesis Prize and UvA Theis Prize)
Zixiao Quan, Causal Impact of the Chinese Plastic Import Ban On Global Warming Trends, August 2024. (Currently PhD candidate at HKU)
Jiangcheng Li, Modeling Volatility with Machine Learning for Quantile Forecasting of Natural Gas Consumption: A Comparative Study with Econometric Model, August 2024
Thomas van der Zijden, Optimizing Cryptocurrency Portfolio Tail Risk: An Extreme Value Theory Approach, August 2024
Ruowen Liu, A Time-Dynamic Movie Recommendation System for Capturing User Preference Drift, August 2023
Gijs W.M. de Bruin, Synthetically Extending a Dataset to Improve Machine Learning Prediction, August 2023 (Nominated for Amsterdam AI Thesis Award)
Jiachen Zhong, Comparing Machine Learning Methods with Traditional Methods in the Context of Demand Sensing in a European Postal Industry, August 2023
Viktoria Akpan, Decoding Brainwaves for Thought-Controlled Movement Using Deep Learning, August 2023
Marcin Galas, Comparison of national and global data for VaR estimation of real estate prices, August 2023
Nguyen Hoang Minh Trang, The Impact of Feature Selection on the Deep Recommender Systems. July 2023
Shihan Yu, Analysing the Ranking in Search Engine Keyword Bidding with Different Models and Strategies, August 2022
Jop van Hest, Detecting Ponzi-Scheme Fraud in Ethereum Smart Contracts, August 2022
Wiebe van der Spek, How to Preserve Patient Privacy in Machine Learning Model Training?
Romy Ho, Scaling Federated Learning in Practice: How Heterogeneous Data Impacts Model Accuracy, July 2022
Liselotte van Dam, The effect of a sales promotion on revenue: An application of the causal forest in grocery retailing, Jan 2022
Alex Boosten, Should you invest in Bitcoin? A performance analysis of Bitcoin and reinforcement learning using bootstrap, Jan 2022
Coen van der Meijs, Bitcoin intra-day return prediction and trading using LSTM, August 2021.
Jan Willem Nijenhuis, Application of generalizability theory to construct a reliability framework for machine learning, August 2021. Python codes here
Eefje Roelfsema, How does industry-leading sentiment affect the probability of default of SMEs?, August 2021
Wisse Bemelman, Evaluating the use of artificial neural networks for financial asset price forecasting, July 2021
Dylan Houtman,The identification of personal data in semi-structured text, August 2020
Sophie Abrahamse, Bridging the gap between interpretability and predictability in customer churn modelling, August 2020
Alessandro Peron, A deep learning approach for non-parametric instrumental estimation: an empirical study, August 2020
Melle Gelok, Detecting fake job advertisements, August 2020
Stijn Mouris, Detecting social security fraud with an explanatory algorithm, December 2019
Maarten de Haas, Predicting the direction of stock prices, December 2019
Monash University #
- Yuanjun Lu, Economic Forecasting with Big Data: A Simulation Study, June 2019
- Balaji Dasari, Stock Predictability using Sparse Learning Approach, June 2019
- Thadeu Freitas Filho, Measuring Systemic Risk: Least-squares versus Quantile Regression, October 2018
- Sombut Jaidee, Optimal Investment using High Dimensional Statistics: Theory and Simulation, October 2017 (Best Thesis Award)
- Aishwarya Pillai, Optimal Investment using High Dimensional Statistics: an Empirical Study, October 2017
- Yue Wang, Measuring Systemic Risk with Extreme Value Theory, June 2017