Matteo Farnè currently is senior researcher in Statistics at the University of Bologna. Admitted to the Collegio Superiore of the University of Bologna in 2010, he spent internship and research periods abroad at University College London in 2012, Stanford University in 2014, European Central Bank in 2015, where he could develop the first taxonomy of euro area banks based on balance sheet data. He received his PhD in Statistical Science from the University of Bologna in 2016, discussing a thesis about large covariance matrix estimation with the guidance of Prof. Angela Montanari. His research interests include cluster analysis, outlier detection, spectral analysis, factor models, large covariance matrices, predictive and classification models. In 2016 and 2017, he taught courses in advanced statistics for banking data at the Bank of Italy; in 2018, he was awarded a “British Academy” grant from the Accademia Nazionale dei Lincei for a five-month research period at the London School of Economics; in A.Y. 2019/2020, he served as Visiting Assistant Professor in Statistics at UC Davis in California; in 2022, he was attributed the Chikio Hayashi award for the best statistican aged 30-35
This course emphasizes statistical methods useful for tackling modern-day data analysis problems. A special attention is dedicated to techniques that help managers to make intelligent use of databases by recognizing patterns and making predictions.
The students will develope skills to:
• plan a statistical data analysis process
• manage a data source
• choose the best method to analyze the data
• implement the analysis and interpret the results