Магистратура
2024/2025
Анализ данных в финансах
Статус:
Курс по выбору (Финансы)
Направление:
38.04.08. Финансы и кредит
Кто читает:
Кафедра математической экономики (Нижний Новгород)
Где читается:
Факультет экономики НИУ ВШЭ (Нижний Новгород)
Когда читается:
1-й курс, 3, 4 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Преподаватели:
Ларин Александр Владимирович
Прогр. обучения:
Финансы
Язык:
английский
Кредиты:
6
Course Syllabus
Abstract
During the course, students gain practical abilities in using modern computer software and utilise the tools required to analyze financial data. The course covers the following main topics: importing financial data, primary processing and visualization, building a trading robot and evaluating the efficacy of the chosen strategy, cluster analysis, forming an investment portfolio, estimating the parameters of empirical models, forecasting.
Learning Objectives
- The goal of this course is to develop and improve skills in financial data analysis with Python.
Expected Learning Outcomes
- Importing data from various sources
- Preprocess financial data
- Visualize financial data
- Perform event study
- Perform cluster analysis
- Perform time series analysis
Course Contents
- Data import
- Data preprocessing
- Data visualization
- Event study
- Cluster analysis
- Time series
Bibliography
Recommended Core Bibliography
- Brooks,Chris. (2019). Introductory Econometrics for Finance. Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.cup.cbooks.9781108422536
Recommended Additional Bibliography
- Lewinson, E. (2020). Python for Finance Cookbook : Over 50 Recipes for Applying Modern Python Libraries to Financial Data Analysis. Packt Publishing.
- Weiming, J. M. (2019). Mastering Python for Finance : Implement Advanced State-of-the-art Financial Statistical Applications Using Python, 2nd Edition (Vol. Second edition). Birmingham, UK: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2116431