Data Analytics Models and Methods for Financial Engineering and Fintech
金融工程和金融科技中的數據分析模型和方法
Overview
Long Description
Financial decision makers can extract useful information from different types of financial data for informed decision making. This course covers some important data analytics models and methods for various applications in financial engineering and Fintech, such as asset pricing, investment, prediction, and risk management. Students will learn various topics including maximum likelihood estimation, linear and nonlinear regression, model selection for regression, principal component analysis, classification models such as logistic regression and discriminant analysis, time series models, and deep learning models. They will also learn how to implement these models and methods using Python or R and apply them to financial data.
