Online advanced PhD course Machine Learning in Asset Pricing with Prof. Xiu from the University of Chicago (19.10.2020 – 02.11.2020)
This online course introduces statistical and machine learning techniques and their applications to empirical asset pricing. Materials cover classical problems, such as the estimation of risk premia and stochastic discount factor, the construction of mean-variance or factor-mimicking portfolios, the test of alphas, and the prediction of returns, but are cast in a modern big data setting, in which variable selection and dimension reduction techniques are necessary. The course also goes beyond structured datasets and imports natural language processing and image recognition techniques from computer science to collect new insights from unstructured text and image data.
Numerical analysis can be conducted in any programming language. Python, R, and Matlab are encouraged.