Магистратура
2026/2027
Финансовая эконометрика
ID 1127039
Статус:
Курс по выбору (Финансы)
Кто читает:
Департамент финансов
Где читается:
Санкт-Петербургская школа экономики и менеджмента
Когда читается:
1-й курс, 3 модуль
Охват аудитории:
для всех кампусов НИУ ВШЭ
Преподаватели:
Антипов Артем Игоревич
Язык:
английский
Кредиты:
3
Контактные часы:
32
Course Syllabus
Abstract
This course provides a comprehensive introduction to modern quantitative financial econometrics, combining rigorous statistical theory with practical applications in financial markets. Starting with fundamental concepts such as stylized facts of financial returns and the properties of financial time series, the course progressively builds towards advanced techniques including unit root testing, cointegration analysis, GARCH volatility modeling, factor-based asset pricing, value-at-risk measurement, and portfolio optimization. Through an integrated approach of theoretical exposition and hands-on R programming, students master contemporary statistical methods essential for analyzing financial data, building predictive models, and managing portfolio risk. Upon completion, students are equipped to develop production-grade financial econometric applications, conduct robust backtesting of trading strategies, and apply sophisticated risk measurement techniques in real-world finance environments.
The course is designed for graduate students and finance professionals seeking advanced knowledge in econometric modeling of financial markets. It bridges the gap between classical econometric theory and modern applications in quantitative finance, with particular emphasis on addressing the unique challenges of financial data: non-normality, volatility clustering, non-stationarity, and comovement structures. Students develop both analytical skills (understanding model assumptions and limitations) and practical competencies (implementation in R, model diagnostics, backtesting frameworks). Successful completion prepares students for careers in quantitative trading, risk management, portfolio optimization, and financial research, as well as for advanced doctoral studies in finance and econometrics.
Learning Objectives
- The students will gain substantial knowledge about the financial econometrics and will be able to apply the same in solving real life problems in finance. Successful completion of the course will make them ready for the job market.
Expected Learning Outcomes
- Understand the principles of financial econometrics and its methodology
- Know the tools of financial econometrics
- Understand and be able to implement the correct econometric models for each financial problem
Course Contents
- Introduction to Financial Time Series
- Unit Root Tests and Stationarity
- ARIMA Models and Forecasting
- Cointegration and Vector Autoregression
- ARCH/GARCH Models
- Value-at-Risk and Risk Management
- Factor Models and Asset Pricing
- Portfolio Optimization
Bibliography
Recommended Core Bibliography
- Analysis of financial time series, Tsay, R. S., 2005
- GARCH models : structure, statistical inference and financial applications, Francq, C., 2010
- Time series analysis, Hamilton, J. D., 1994
Recommended Additional Bibliography
- Moffatt, P. G. (2015). Experimetrics : Econometrics for Experimental Economics. Basingstoke: Palgrave Macmillan. Retrieved from https://www.bloomsbury.com/us/experimetrics-9781137456595/