Andres Algaba

Andres Algaba is a postdoctoral researcher in AI at the Data Analytics Laboratory (VUB). His current research interests are fairness in machine learning, and the detection and mitigation of unethical biases in algorithmic decision making. Andres obtained a joint PhD in (business) economics at VUB and UGent, and has published his work in the International Journal of Forecasting and Economic Modelling, among others. He was also a lecturer in Econometrics at VUB and researcher-entrepreneur at the Sentometrics VUB spin-off.

RESEARCH

Bias

Deep Learning

Explainable AI

Fairness

Generative Models

KEY PUBLICATIONS

Algaba, A., Borms, S., Boudt, K. and Verbeken, B., 2021. Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence. International Journal of Forecasting, In Press. https://doi.org/10.1016/j.ijforecast.2021.11.005

Algaba, A., Ardia, D., Bluteau, K., Borms, S. and Boudt, K., 2020. Econometrics meets sentiment: An overview of methodology and applications. Journal of Economic Surveys, 34 (3), 512-547. https://doi.org/10.1111/joes.12370

Algaba, A., Boudt, K. and Vanduffel, S., 2020. The variance implied conditional correlation. The European Journal of Finance, 26 (2-3), 200-222. https://doi.org/10.1080/1351847X.2019.1615524

Algaba, A. and Boudt, K., 2017. Generalized financial ratios to predict the equity premium. Economic Modelling 66, 244-257. https://doi.org/10.1016/j.econmod.2017.07.009